Dissertations / Theses on the topic 'Combustion optimization'

Doctor of Philosophy<br>Department of Mechanical and Nuclear Engineering<br>Donald Fenton<br>Combustion turbine performance deterioration, quantified by loss of system power, is an artifact of increased inlet air temperature and continuous degradation of the machine. Furthermore, the combustion turbine operator has to meet ever changing stricter emission levels. Different technologies exist to mitigate the impact of performance loss and meeting the emission standard. However an upgrade using one or more of the available technologies has associated capital and operating costs. Thus, there is a need for a tool that can evaluate power boosting and emission control technologies in concert with the machine maintenance strategy. This dissertation provides the turbine operator with a new and novel tool to examine each of the upgrades and determine its suitability both from the cost and technical stand point. The main contribution of this dissertation is a tool-kit called the Combustion Turbine Operation and Optimization Model (CTOOM) that can evaluate both power-boosting and emission control technologies. It also includes a machine maintenance model to account for degradation recovery. The tool-kit is made up a system level thermodynamic optimization solver (CTOOM-OPTIMIZE) and two one-dimensional, mean-line, aero-thermodynamic component level solvers for the compressor (CTOOMCOMP1DPERF) and the turbine (CTOOMTURB1DPERF) sections. In this work, the cogeneration system as given by the classical CGAM problem was used for system level optimization. The cost function was modified to include the cost of emissions while the maintenance cost of the combustion turbine was separated from the capital cost to include a degradation recovery model. Steam injection was evaluated for NO[subscript]x abatement, power boosting was examined by both the use of inlet air cooling and steam injection, and online washing was used for degradation recovery. Based on the cost coefficients used, it was seen that including the cost of emissions impact resulted in a significant increase in the operational cost. The outcomes of the component level solvers were compressor and turbine performance maps. It was demonstrated that these maps could be used to integrate the components with the system level information.

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2011.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (p. 81-82).<br>Simultaneous multi-variable gradient-based optimization with multi-start is performed on a 300 MWe wet-recycling pressurized oxy-coal combustion process with carbon capture and sequestration. The model accounts for realistic component behavior such as heat losses, steam leaks, pressure drops, cycle irreversibilities, and other technological and economical considerations. The optimization study involves 16 variables, three of which are integer valued, and 10 constraints with the objective of maximizing thermal efficiency. The solution procedure follows active inequality constraints which are identified by thermodynamic-based analysis to facilitate convergence. Results of the multi-variable optimization are compared to a pressure sensitivity analysis similar to those performed in literature; the basecase of both assessments performed here is a favorable solution found in literature. Significant cycle performance improvements are obtained compared to this literature design at a much lower operating pressure and with moderate changes in the other operating variables. The effect of the variables on the cycle performance and on the constraints are analyzed and explained to obtain increased understanding of the actual behavior of the system. This study reflects the importance of simultaneous multi-variable optimization in revealing the system characteristics and uncovering the favorable solutions with higher efficiency than the atmospheric operation or those obtained by single variable sensitivity analysis.<br>by Hussam Zebian.<br>S.M.

This dissertation describes the design and optimization of a CO2-capture unit using aqueous amines to remove of carbon dioxide from the flue gas of a coal-fired power plant. In particular we construct a monolithic model of a carbon capture unit and conduct a rigorous optimization to find the lowest solvent regeneration energy yet reported. Carbon capture is primarily motivated by environmental concerns. The goal of our work is to help make carbon capture and storage (CCS) a more efficient for the sort of universal deployment called for by the Intergovernmental Panel on Climate Change (IPCC) to stabilize anthropomorphic contributions to climate change, though there are commercial applications such as enhanced oil recovery (EOR). We employ the latest simulation tools from Aspen Tech to rigorously model, design, and optimize acid gas systems. We extend this modeling approach to leverage Aspen Plus in the .NET framework through Microsoft's Component Object Model (COM). Our work successfully increases the efficiency of acid gas capture. We report a result optimally implementing multiple energy-saving schemes to reach a thermal regeneration energy of 1.67 GJ/tonne. By contrast, the IPCC had reported that leading technologies range from 2.7 to 3.3 GJ/tonne in 2005. Our work has received significant endorsement for industrial implementation by the senior management from the world's second largest chemical corporation, Sinopec, as being the most efficient technology known today.<br>Ph. D.

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2013.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (p. 103-108).<br>This thesis considers the optimization and hybridization of advanced zero emissions power (AZEP) cycles. More specifically, existing flowsheets for zero and partial emissions are optimized, and new integration schemes with solar energy are proposed and analyzed. First, optimal design and operation of AZEP cycles, both zero and partial emissions, is considered. AZEP consists of a Brayton-like top cycle and a standard triple pressure heat recovery steam generator (HRSG) bottoming cycle, and a CO₂ separation and purification unit. The first-law efficiency is maximized as a function of CO₂ emissions with fixed ion transport membrane (ITM) size and consequently, variable power output. The optimization study involves 6 constraints, and 14 variables for the zero emissions cycle. The partial emissions cycle has one extra optimization variable. A two-step heuristic global optimization of the power cycle is performed. In the first step, the top cycle is optimized. In the next step, the bottoming cycle is optimized for fixed conditions of the top cycle. This procedure is repeated with different initial guesses for the optimization variables of the top cycle to obtain a near-global optimum. The optimization results in a significant increase in the efficiencies of AZEP100 and partial emissions cycles, in the range of 2-2.7 percentage points depending on cycle considered and ITM membrane temperature. This increase in efficiency is important with respect to viability of the partial emissions cycle compared to alternative power cycles. This viability is determined herein using a linear combination metric, which combines efficiency and CO₂ emissions. Optimization and simulations have shown that reducing the maximum membrane temperature results in an increase in the efficiency till membrane temperature reaches 850°C, after which the efficiency starts decreasing. However, reduced temperature results in dramatic drop in net power output of the power plant. In other words, membrane temperature results in a trade-off between power plant efficiency and power output. Second, different solar-thermal integration schemes for an AZEP cycle with total CO₂ capture are proposed and analyzed. The solar subsystem consists of a parabolic trough, a Concentrated Solar Thermal (CST) technology. Four different integration schemes with the bottoming cycle are considered: vaporization of high-pressure stream, preheating of high-pressure stream, heating of intermediate-pressure turbine inlet stream, and heating of low-pressure turbine inlet stream. The power outputs from these integration schemes are compared with each other and with the sum of the power outputs from corresponding standalone AZEP cycle and solar-thermal cycle. It is shown that vaporization of high-pressure stream in the bottoming cycle has the highest power output among the proposed integration schemes. The analysis shows that both the vaporization and heating of intermediate-pressure turbine inlet stream integration schemes have higher power output than the sum of the power outputs from corresponding stand-alone AZEP cycle and solar-thermal cycle. A comparison of the proposed vaporization scheme with existing hybrid technologies without carbon capture and sequestration (CCS) shows that it has a higher annual incremental solar efficiency than most hybrid technologies. Moreover, it has a higher solar share compared to -hybrid technologies with higher incremental efficiency. Hence, AZEP cycles are a promising option to be considered for solar-thermal hybridization.<br>by Surekha Gunasekaran.<br>S.M.

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2004.<br>Includes bibliographical references (p. 95-97).<br>Lean operation of spark ignition (SI) automotive engines offers attractive performance incentives. Lowered combustion temperatures inhibit NO[sub]x pollutant formation while reduced manifold throttling minimizes pumping losses, leading to higher efficiency. These benefits are offset by the reduced combustion speed of lean mixtures, which can lead to high cycle-to-cycle variation and unacceptable engine behavior characteristics. Hydrogen-enhancement can suppress the undesirable consequences of lean operation by accelerating the combustion process, thereby extending the "lean limit." Hydrogen can be produced onboard the vehicle with a plasmatron fuel reformer device. Combustion optimization experiments focused on three key areas: the ignition system, charge motion in the inlet ports, and mixture preparation. The ignition system tests compared a standard inductive coil scheme against high-energy discharge systems. Charge motion experiments focused on the impact of turbulence patterns generated by conventional restrictor plates as well as novel inlet flow modification cones. The turbulent motion of each configuration was characterized using swirl and tumble flow benches. Mixture preparation tests compared a standard single-hole pintle injector against a fine atomizing 12-hole injector. Lastly, a further series of trials was also run to investigate the impact of high exhaust gas recirculation (EGR) dilution rates on combustion stability. Results indicate that optimizations of the combustion system in conjunction with hydrogen-enhancement can extend the lean limit of operation by roughly 25% compared against the baseline configuration. Nearly half of this improvement may be attributed to improvements in the combustion system.<br>(cont.) An inductive ignition system in conjunction with a high tumble-motion inlet configuration leads to the highest levels of combustion performance. Furthermore, hydrogen enhancement affects a nearly constant absolute improvement in the lean misfire limit regardless of baseline combustion behavior. Conversely, the amount of improvement in the point of peak engine NIMEP output is inversely related to the level of baseline performance.<br>by Joshua A. Goldwitz.<br>S.M.

The usage of novel combustion technologies, such as Moderate or Intense Low-oxygen Dilution (MILD) combustion, in the future energy mix provides both a flexible and reliable energy supply, together with low emissions. The implementation though is highly situational and numerical studies can help in the assessment of said technologies. However, the existing uncertainties in numerical modeling of MILD combustion are quite significant, and as detailed kinetics should be considered while modeling MILD combustion, a major part of this uncertainty can be accredited to the kinetics. Combined with the fact that existing detailed mechanisms have been developed and validated against conventional combustion targets, there exists a gap between the performance of existing mechanism and experimental findings. To handle this discrepancy, Uncertainty Quantification (UQ) and Optimization are highly viable techniques for reducing this misfit, and have therefore been applied in this work. The strategy applied consisted of first determining the reactions which showed the largest impact towards the experimental targets, by not only considering the sensitivity, but also the uncertainty of the reactions. By using a so-called impact factor, the most influential reactions could be determined, and only the kinetic parameters with the highest impact factors were considered as uncertain in the optimization studies. The uncertainty range of the kinetic parameters were then determined using the uncertainty bounds of the rate coefficients, by finding the lines which intercepts the extreme points of these maximum and minimum rate coefficient curves. Based on this prior parameter space, the optimal combination of the uncertain parameters were determined using two different approaches. The first one utilized Surrogate Models (SMs) for predicting the behavior of changing the kinetic parameters. This is a highly efficient approach, as the computational effort is reduced drastically for each evaluation, and by comparing the physically viable parameter combinations within the pre-determined parameter space, the optimal point could be determined. However, due to limitations of the amount of uncertain parameters and experimental targets that can be used with SMs, an optimization toolbox was developed which uses a more direct optimization approach. The toolbox, called OptiSMOKE++, utilizes the optimization capabilities of DAKOTA, and the simulation of detailed kinetics in reactive systems by OpenSMOKE++. By using efficient optimization methods, the amount of evaluations needed to find the optimal combination of parameters can be drastically reduced. The tool was developed with a flexibility of choosing experimental targets, uncertain kinetic parameters, objective function and optimization method. To present these features, a series of test cases were used and the performance of OptiSMOKE++ was indeed satisfactory. As a final application, the toolbox OptiSMOKE++ was used for optimizing a kinetic mechanism with respect to a large set of experimental targets in MILD conditions. A large amount of uncertain kinetic parameters were also used in the optimization, and the optimized mechanism showed large improvements with respect to the experimental targets. It was also validated against experimental data consisting of species measurements in MILD conditions, and the optimized mechanism showed similar performance as that of the nominal mechanism. However, as the general trend of the species profiles were captured with the nominal mechanism, this was considered satisfactory. The work of this PhD has shown that the application of optimization to kinetic mechanism, can improve the performance of existing mechanism with respect to MILD combustion. Through the development of an efficient toolbox, a large set of experimental data can be used as targets for the optimization, at the same time as many uncertain kinetic parameters can be used contemporary.<br>Doctorat en Sciences de l'ingénieur et technologie<br>This work has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No 643134, and from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme under grant agreement No 714605.<br>info:eu-repo/semantics/nonPublished

Abstract   The fuel is put into the process through a burner pipe and this burner pipe is modified to reach a more efficient combustion. The primary target is to enable burning of heterogeneous alternative fuels and increase the production level. Other positive effects from this type of optimization is lowered specific fuel consumption and lowered CO2 emissions. A redundant burner is chosen for the project and overall the project steps are the following: 1. Installing a Jet air nozzle ring in a way so it can move both axially and radially due to temperature changes. 2. Remove the present refractory from the burner and order a new form to decrease the weight of the burner 3. Place a K6 blower in operating the axial channel. 4. Install Gauging equipment (Temp, pressure, ampere blower etc) 5. Carefully observe process values during the modified burners run in time. 6. Evaluate the results of the project 7. With the help of proven potential in the kiln system be able to convince management of the proceeds to invest in a new burner 8. If point 7 is fulfilled with the help of experience, be able to operate as a projectcoordinator in the purchase of a professional burner. This task will include coordinating the project group in various meetings and then lead to an RFQ (Request For Quotation). Results from the project show the great potential in an optimization of a burner at a cement plant. A production increase of 5% could be seen together with a lowered specific energy consumption which is extremely satisfactory results. Unfortunately a breakdown of the system occurred a bit down the path of optimisation that resulted in damages to the kiln. At this stage the optimization was stopped and the old burner was put back after finished kiln repair. Finally crucial to underline is that the proven results in this study convinced the Group Management of buying a new burner. The benefits from a professional tailor made burner are far greater than the cost of buying it. The payback time is roughly around a year for such an investment depending on current market conditions. In this report focus is put on the combustion process at a cement plant. Combustion is the heart of the cement making process and absolutely crucial to have under full control and well optimized.

<p>The current interest regarding how to stop the global warming has put focus on the automobile industry and forced them to produce vehicles/engines that are more environmental friendly. This has led to the development of increasingly complex controlsystem of the engines. The introduction of common-rail systems in regular automotives increased the demand of physical models that in an accurate way can describe the complex cycle within the combustion chamber. With these models implemented it is possible to test new strategies on engine steering in a cost- and time efficient way.</p><p>The main purpose with this report is to, build our own model based on the existing theoretical models in diesel engine combustion. The model has then been evaluated in a simulation environment using Matlab/Simulink. The model that has been implemented is a multi-zone type and is able to handle multiple injections.</p><p>The model that this thesis results in can in a good way predict both pressure and torque generated in the cylinder. More investigation in how the parameter settings behave in other work-points must be done to enhance the models accuracy. There is also some work left to do in the validation of the model but to make this possible more experimental data must be accessible.</p>

Thesis (M.S. in Astronautical Engineering)--Naval Postgraduate School, December 2003.<br>Thesis advisor(s): Jose O. Sinibaldi, Garth V. Hobson. Includes bibliographical references (p. 69). Also available online.

PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO<br>COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR<br>O objetivo deste trabalho é predizer e otimizar o desempenho de motores funcionando no modo bicombustível, diesel-gás natural, fazendo uso da inteligência artificial. Pretende-se determinar a taxa de substituição ótima do combustível original diesel pelo gás natural que minimize custos de operação (combustíveis) e emissões de poluentes, tais como: monóxido de carbono, CO, hidrocarbonetos, HC, e óxidos de nitrogênio, NOx, priorizando-se também a eficiência térmica. Os dados analisados foram obtidos de testes anteriormente realizados. O procedimento envolve treinamento, validação e teste (utilizando redes neurais). Com os dados analisados foram treinadas diferentes redes neurais 06 para a aprendizagem e predição, as quais vão prever mapas de novos valores baseando-se nos dados experimentais já apreendidos. Finalmente, e continuando com o processo de otimização (técnica de Algoritmos Genéticos), é determinada a melhor taxa de substituição de diesel-gás natural, com as menores taxas de emissões dentro dos mapas gerados. Os resultados indicam uma boa concordância entre os dados experimentais e os previstos pela rede neural. O processo de otimização utilizado determina os pontos de trabalho adequados para cada caso analisado.<br>The purpose of this study is to predict and optimize the internal combustion engine performance using diesel-natural gas fuel using the artificial intelligence. The ultimate goal is to determine the optimal substitution rate of natural gas to minimize the costs of operation and pollutants emissions such as carbon monoxide CO, hydrocarbons HC and nitrogen oxides NOx, considering the values of efficiency. The analyzed data are obtained from tests performed earlier. The procedure involves training, validation and test (using neural networks). Once these data were analyzed with different trained neural networks for learning and prediction, which are maps of the predicted values based on experimental data have been seized. Finally, and continuing with the process of optimization (technique of Genetic Algorithms), is given the best substitution rate of and lower emissions in the maps generated. The results indicate a good agreement between data and neural network, the process of optimization using certain items of work appropriate for each case analyzed.

A lot of research effort is spent worldwide in order to reduce the environmental impact of the transportation and power generation sector. To minimize the environmental pollution the role of hydrogen fuelled gas turbines is intensively discussed in several research scenarios, like the IGCC-technology or the application of hydrogen as large scale storage for renewable energy sources. The adaptation of the applied gas turbine combustion chamber technology and control technology is mandatory for a stable and secure low NOx operation of a hydrogen fuelled gas turbine.<p>The micromix combustion principle was invented at Aachen University of Applied Sciences and achieves a significant reduction of the NOx-emissions by the application of multi miniaturized diffusion-type flamelets. Based on the research experiences, gained during the two European hydrogen research programs EQHHPP and Cryoplane at Aachen University of Applied Sciences, the intention of this thesis was to continue the scientific research work on low NOx hydrogen fuelled gas turbines. This included the experimental characterization of the micromix combustion principle, the design of an improved combustion chamber, based on the micromix combustion principle, for industrial gas turbine applications and the improvement of the gas turbine’s control and metering technology.<p>The experimental characterization of the micromix combustion principle investigated the impact of several key parameters, which influence the formation of the NOx-emissions, and allows therefore the definition of boundary conditions and design laws, in which a low NOx operation of the micromix combustion principle is practicable. In addition the ability of the micromix combustion principle to operate at elevated energy densities up to 15 MW/(m2bar) was successfully demonstrated. The improved combustion chamber design concept includes the experiences gained during the experimental characterization and covers the industrial needs regarding scalability and manufacturability.<p>The optimization and testing is done with an Auxiliary Power Unit GTCP 36-300. The original kerosene fuelled gas turbine was modified for the hydrogen application. Therefore several hardware and software modifications were realized. The improved gas turbine’s control and metering technology enables stable and comparable operational characteristics as in kerosene reference. An improved hydrogen metering unit, which is controlled by the industrial Versatile Engine Control Box, was successfully implemented. <p>The combination of the micromix combustion technology and of the optimized control and metering technology allows a stable, secure and low NOx hydrogen fuelled gas turbine operation.<p><br>Doctorat en Sciences de l'ingénieur<br>info:eu-repo/semantics/nonPublished

Thesis (Ph. D.)--Ohio State University, 2005.<br>Title from first page of PDF file. Document formatted into pages; contains xv, 222 p.; also includes graphics. Includes bibliographical references (p. 211-222) Available online via OhioLINK's ETD Center

El trabajo presentado en esta Tesis está motivado por la necesidad de los motores de combustión interna alternativos de reducir el consumo de combustible y las emisiones de CO2 mientras se satisfacen las cada vez más restrictivas regulaciones de emisiones contaminantes. Por lo tanto, el objetivo principal de este estudio es optimizar un sistema de combustión de encendido por compresión controlado por mezcla para probar su potencial como motores de futura generación. Con esta meta se ha desarrollado un sistema automático que combina CFD con métodos de optimización avanzados para analizar y entender las configuraciones óptimas. Los resultados presentados en este trabajo se dividen en dos bloques principales. El primero corresponde a la optimización de un sistema de encendido por compresión convencional alimentado con diésel. El segundo se centra en un concepto de combustión avanzado donde se ha sustituido el fuel por Dimetil-eter. En ambos casos, el estudio no sólo halla una configuración óptima sino que también se describen las relaciones causa/efecto entre los parámetros más relevantes del sistema de combustión. El primer bloque aplica métodos de optimización no-evolutivos a un motor medium-duty alimentado por diésel tratando de minimizar consumo a la vez que se mantienen las emisiones contaminantes por debajo de los estándares de emisiones contaminantes impuestos. Una primera parte se centra en la optimización de la geometría de la cámara de combustión y el inyector. Seguidamente se extiende el estudio añadiendo los settings de renovación de la carga de y de inyección al estudio, ampliando el potencial de la optimización. El estudio demuestra el limitado potencial de mejora de consumo que tiene el motor de referencia al mantener los niveles de emisiones contaminantes. Esto demuestra la importancia de incluir parámetros de renovación de la carga e inyección al proceso de optimización. El segundo bloque aplica una metodología basada en algoritmos genéticos al diseño del sistema de combustión de un motor heavy-duty alimentado con Dimetileter. El estudio tiene dos objetivos, primero la optimización de un sistema de combustión convencional controlado por mezcla con el objetivo de lograr mejorar el consumo y reducir las emisiones contaminantes hasta niveles inferiores a los estándares US2010. Segundo la optimización de un sistema de combustión trabajando en condiciones estequiométricas acoplado con un catalizador de tres vías buscando reducir consumo y controlar las emisiones contaminantes por debajo de los estándares 2030. Ambas optimizaciones incluyen tanto la geometría como los parámetros más relevantes de renovación de la carga y de inyección. Los resultados presentan un sistema de combustión convencional óptimo con una notable mejora en rendimiento y un sistema de combustión estequiométrica que es capaz de ofrecer niveles de NOx menores al 1% de los niveles de referencia manteniendo niveles competitivos de rendimiento. Los resultados presentados en esta Tesis ofrecen una visión extendida de las ventajas y limitaciones de los motores MCCI y el camino a seguir para reducir las emisiones de futuros sistemas de combustión por debajo de los estándares establecidos. A su vez, este trabajo también demuestra el gran potencial que tiene el Dimetil-eter como combustible para futuras generaciones de motores.<br>The work presented in this Thesis was motivated by the needs of internal combustion engines (ICE) to decrease fuel consumption and CO2 emissions, while fulfilling the increasingly stringent pollutant emission regulations. Then, the main objective of this study is to optimize a mixing-controlled compression ignition (MCCI) combustion system to show its potential for future generation engines. For this purpose an automatic system based on CFD coupled with different optimization methods capable of optimizing a complete combustion system with a reasonable time cost was designed together with the methodology to analyze and understand the new optimum systems. The results presented in this work can be divided in two main blocks, firstly an optimization of a conventional diesel combustion system and then an optimization of a MCCI system using an alternative fuel with improved characteristics compared to diesel. Due to the methodologies used in this Thesis, not only the optimum combustion system configurations are described, but also the cause/effect relations between the most relevant inputs and outputs are identified and analyzed. The first optimization block applies non-evolutionary optimization methods in two sequential studies to optimize a medium-duty engine, minimizing the fuel consumption while fulfilling the emission limits in terms of NOx and soot. The first study targeted four optimization parameters related to the engine hardware including piston bowl geometry, injector nozzle configuration and mean swirl number. After the analysis of the results, the second study extended to six parameters, limiting the optimization of the engine hardware to the bowl geometry, but including the key air management and injection settings. The results confirmed the limited benefits, in terms of fuel consumption, with constant NOx emission achieved when optimizing the engine hardware, while keeping air management and injection settings. Thus, including air management and injection settings in the optimization is mandatory to significantly decrease the fuel consumption while keeping the emission limits. The second optimization block applies a genetic algorithm optimization methodology to the design of the combustion system of a heavy-duty Diesel engine fueled with dimethyl ether (DME). The study has two objectives, the optimization of a conventional mixing-controlled combustion system aiming to achieve US2010 targets and the optimization of a stoichiometric mixing-controlled combustion system coupled with a three way catalyst to further control NOx emissions and achieve US2030 emission standards. These optimizations include the key combustion system related hardware, bowl geometry and injection nozzle design as input factors, together with the most relevant air management and injection settings. The target of the optimizations is to improve net indicated efficiency while keeping NOx emissions, peak pressure and pressure rise rate under their corresponding target levels. Compared to the baseline engine fueled with DME, the results of the study provide an optimum conventional combustion system with a noticeable NIE improvement and an optimum stoichiometric combustion system that offers a limited NIE improvement keeping tailpipe NOx values below 1% of the original levels. The results presented in this Thesis provide an extended view of the advantages and limitations of MCCI engines and the optimization path required to achieve future emission standards with these engines. Additionally, this work showed how DME is a promising fuel for future generation engines since it is able to achieve future emission standards while maintaining diesel-like efficiency<br>El treball presentat en esta Tesi està motivat per la necessitat dels motors de combustió interna alternatius de reduir el consum de combustible i les emissions de CO2 mentres se satisfan les cada vegada mes restrictives regulacions d'emissions contaminants. Per tant, l'objectiu principal d'este estudi es optimitzar un sistema de combustió d'encesa per compressió controlat per mescla per a provar el seu potencial com a motors de futura generació. Amb esta meta s'ha desenrotllat un sistema automàtic que combina CFD amb mètodes d'optimització avançats per a analitzar i entendre les configuracions òptimes. Els resultats presentats en este treball es dividixen en dos blocs principals. El primer correspon a l'optimització d'un sistema d'encesa per compressió convencional alimentat amb dièsel. El segon se centra en un concepte de combustió avançat on s'ha substituït el fuel per Dimetil-eter. En ambdós casos, l'estudi no sols troba una configuració òptima sinó que també es descriuen les relacions causa/efecte entre els paràmetres més rellevants del sistema de combustió. El primer bloc aplica mètodes d'optimització no-evolutius a un motor mediumduty alimentat per dièsel tractant de minimitzar consum al mateix temps que es mantenen les emissions contaminants per davall dels estàndards d'emissions contaminants impostos. Una primera part se centra en l'optimització de la geometria de la cambra de combustió i l'injector. A continuació s'estén l'estudi afegint els settings de renovació de la càrrega de i d'injecció a l'estudi, ampliant el potencial de l'optimització. L'estudi demostra el limitat potencial de millora de consum que té el motor de referència al mantindre els nivells d'emissions contaminants. Açò demostra la importància d'incloure paràmetres de renovació de la càrrega i injecció al procés d'optimització. El segon bloc aplica una metodologia basada en algoritmes genètics al disseny del sistema de combustió d'un motor heavy-duty alimentat amb Dimetil-eter. L'estudi té dos objectius, primer l'optimització d'un sistema de combustió convencional controlat per mescla amb l'objectiu d'aconseguir millorar el consum i reduir les emissions contaminants fins nivells inferiors als estàndards US2010. Segon l'optimització d'un sistema de combustió treballant en condicions estequiomètriques acoblat amb un catalitzador de tres vies buscant reduir consum i controlar les emissions contaminants per davall dels estàndards 2030. Ambdós optimitzacions inclouen tant la geometria com els paràmetres més rellevants de renovació de la càrrega i d'injecció. Els resultats presenten un sistema de combustió convencional òptim amb una notable millora en rendiment i un sistema de combustió estequiomètrica que és capaç d'oferir nivells de NOx menors al 1% dels nivells de referència mantenint nivells competitius de rendiment. Els resultats presentats en esta Tesi oferixen una visió estesa dels avantatges i limitacions dels motors MCCI i el camï que s'ha de seguir per a reduir les emissions de futurs sistemes de combustió per davall dels estàndards establits. Al seu torn, este treball també demostra el gran potencial que té el Dimetil-eter com a combustible per a futures generacions de motors.<br>Hernández López, A. (2018). Optimization and analysis by CFD of mixing-controlled combustion concepts in compression ignition engines [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/103826<br>TESIS

DI Diesel engine are widely used both for industrial and automotive applications due to their durability and fuel economy. Nonetheless, increasing environmental concerns force that type of engine to comply with increasingly demanding emission limits, so that, it has become mandatory to develop a robust design methodology of the DI Diesel combustion system focused on reduction of soot and NOx simultaneously while maintaining a reasonable fuel economy. In recent years, genetic algorithms and CFD three-dimensional combustion simulations have been successfully applied to that kind of problem. However, combining GAs optimization with actual CFD three-dimensional combustion simulations can be too onerous since a large number of calculations is usually needed for the genetic algorithm to converge, resulting in a high computational cost and, thus, limiting the suitability of this method for industrial processes. In order to make the optimization process less time-consuming, CFD simulations can be more conveniently used to generate a training set for the learning process of an artificial neural network which, once correctly trained, can be used to forecast the engine outputs as a function of the design parameters during a GA optimization performing a so-called virtual optimization. In the current work, a numerical methodology for the multi-objective virtual optimization of the combustion of an automotive DI Diesel engine, which relies on artificial neural networks and genetic algorithms, was developed.

DI Diesel engine are widely used both for industrial and automotive applications due to their durability and fuel economy. Nonetheless, increasing environmental concerns force that type of engine to comply with increasingly demanding emission limits, so that, it has become mandatory to develop a robust design methodology of the DI Diesel combustion system focused on reduction of soot and NOx simultaneously while maintaining a reasonable fuel economy. In recent years, genetic algorithms and CFD three-dimensional combustion simulations have been successfully applied to that kind of problem. However, combining GAs optimization with actual CFD three-dimensional combustion simulations can be too onerous since a large number of calculations is usually needed for the genetic algorithm to converge, resulting in a high computational cost and, thus, limiting the suitability of this method for industrial processes. In order to make the optimization process less time-consuming, CFD simulations can be more conveniently used to generate a training set for the learning process of an artificial neural network which, once correctly trained, can be used to forecast the engine outputs as a function of the design parameters during a GA optimization performing a so-called virtual optimization. In the current work, a numerical methodology for the multi-objective virtual optimization of the combustion of an automotive DI Diesel engine, which relies on artificial neural networks and genetic algorithms, was developed.

Thesis (Ph. D.)--West Virginia University, 1999.<br>Title from document title page. Document formatted into pages; contains vi, 112 p. : ill. (some col.). Vita. Includes abstract. Includes bibliographical references (p. 76-79).

2010 - 2011<br>Combustion engines have been for a long time the most important prime mover for transportation globally. A combustion engine is simple in its nature; a mix of fuel and air is combusted, and work is produced in the operating cycle. The amount of combusted air and fuel controls the amount of work the engine produces. The engine work has to overcome friction and pumping losses, and a smaller engine has smaller losses and is therefore more efficient. Increasing engine efficiency in this way is commonly referred to as downsizing. Downsizing has an important disadvantage; a smaller engine cannot take in as much air and fuel as a larger one, and is therefore less powerful, which can lead to less customer acceptance. By increasing the charge density the smaller engine can be given the power of a larger engine, and regain customer acceptance. A number of charging systems can be used for automotive application, e.g. supercharging, pressure wave charging or turbocharging. Turbocharging has become the most commonly used charging system, since it is a reliable and robust system, that utilizes some of the energy in exhaust gas, otherwise lost to the surroundings. There are however some drawbacks and limits of a turbocharger. The compressor of a single stage turbo system is sized after the maximum engine power, which is tightly coupled to the maximum mass flow. The mass flow range of a compressor is limited, which imposes limits on the pressure build up for small mass flows and thereby engine torque at low engine speed. Further, a turbo needs to spin with high rotational speed to increase air density, and due to the turbo inertia it takes time to spin up the turbo. This means that the torque response of a turbocharged engine is slower than an equally powerful naturally aspirated engine, which also lead to less customer acceptance A two stage turbo system combines two different sized turbo units, where the low mass flow range of the smaller unit, means that pressure can be increased for smaller mass flows. Further, due to the smaller inertia of the smaller unit, it can be spun up faster and thereby speed up the torque response of the engine. The smaller unit can then be bypassed for larger mass flows, where instead the larger turbo unit is used to supply the charge density needed. In the dissertation, the value of engine system modeling has been discussed. It was shown how modeling in-cylinder processes and turbocharger can aid the development of the control strategies saving time and money efforts. All the developed models were experimentally validated and applied for optimization analysis or real-time control. Particularly the model based optimization of the engine control variables of an automotive turbocharged Diesel engine has been presented. The model structure is based on a hybrid approach, with a predictive multi-zone model for the simulation of in-cylinder processes (i.e. combustion and emissions formation) integrated with a control-oriented turbocharger model to predict intake/exhaust processes. Model accuracy was tested via comparison between measured and simulated in-cylinder pressure and engine exhaust temperature on a wide set of experimental data, measured at the test bench. Validation results exhibit a correlation index R2 equal to 0.995 and 0.996 for IMEP and exhaust temperature, respectively. The optimization analysis was aimed at minimizing NO emissions in four steady state engine operating conditions, selected among those of interest for the ECE/EUDC test driving cycle. Constraints were introduced to prevent from increase of soot emissions and low exhaust temperature which would have a negative impact on the efficiency of the after-treatment devices. The optimization results evidence a significant reduction of engine NO emissions by means of increased EGR rate and earlier main fuel injection. A model-based optimization was also applied for a CNG heavy-duty engine, equipped with turbocharger and EGR. The optimization analysis was addressed to design the set-points of engine control variables, following the implementation of an EGR system aimed at reducing the in-cylinder temperature and preventing from the thermal stress of engine components (i.e. head and valves). A co-simulation analysis was carried out by coupling a 1-D engine commercial code with a classical constrained optimization algorithm. The 1-D model accounts for intake and exhaust gas flow arrangement, comprehensive of EGR system and turbocharger, while an empirical formulation based on the classical Wiebe function was implemented to simulate the combustion process. An intensive identification analysis was performed to correlate Wiebe model parameters to engine operation and guarantee model accuracy and generalization even in case of high EGR rate. 1-D model and identification results were successfully validated against a wide set of experimental data, measured on the test bench. The results of the optimization analysis, aimed at minimizing fuel consumption while preventing from thermal stress, showed an increase of fuel economy up to 4.5% and a reduction of the thermal load below the imposed threshold, against five engine operating conditions selected among the most critical of the reference European Transient Cycle (ETC). Particularly, the effectiveness of the co-simulation analysis is evidenced in pursuing the conflicting goal of optimizing engine control while reducing the recourse to time consuming and expensive experiments at the test bed. This latter point is becoming more and more critical as the number of control variables is increasing with engine complexity. Both the presented optimization analyses evidenced the key-role of the turbocharger to face with energy and emissions issues. Particularly the impact of the turbocharger management via wastegate or VGT control was evidenced. Indeed, by acting on these components, the amount of exhaust gases evolving in the turbine can be managed thus regulating the supercharging degree and the boost pressure. This allows keeping the throttle valve fully open with significant decrease of pumping losses. The wastegate position is defined by a pneumatic actuator in which the pressure is regulated by a solenoid valve fed by a PWM signal. The drawback of this system is the dependence of the PWN signal, and afterwards of the performance, from the system supply voltage. During the thesis the development of a wastegate actuator model was carried out in order to compensate the actuator PWM signal to improve boost pressure control. The compressible flow equations were found to be sufficient to describe the actuator system mass flow and both discharge coefficient and static actuator chamber pressure were modeled using polynomials in PWM signal. Furthermore a simple friction model was implemented to simulate the actuator system. The boost pressure controller based on the developed compensator has shown to give limited undershoot and overshoot and is further able to reject the disturbance in supply voltage. The compensator was incorporated into a boost pressure controller and the complete control system has shown to reject system voltage variations and perform good boost pressure control in both simulations analyses and experimental tests on the engine test stand. Model simulations evidenced the need to ensure low enough vacuum pressure to enable fully closed and open actuator while a switch type controller was proved to be sufficient for vacuum tank pressure control. [edited by author]<br>X n.s.

Abstract Circulating Fluidized Bed (CFB) boilers are widely used for multi-fuel combustion of waste and bio-fuels. When several non-homogeneous fuels, having varying heat values, are burned simultaneously, the boiler control system can be affected by various control challenges, especially since it is not feasible to reliably measure the energy content of the multi-fuel flow. In order to fulfill energy production needs and maintain the ability to burn low grade fuels, co-firing with high heat value fuels such as gas, oil or coal is needed. Fuzzy Logic Control (FLC) has been successfully used for solving control challenges, where operators' process expertise can be transformed into automation. Real life control objects are often non-linear because the dynamics change with the operating point, or there might be other essential non-linearities in the combustion process. The proposed fuzzy control applications were developed to solve control challenges the operators meet in daily operation of a 150 MW(th) CFB at Varenso Oy's (Stora Enso Oyj) K6 boiler in Varkaus Finland. Before implementing the applications in the fullscale boiler, they were tested at a 2 MW(e) pilot plant boiler at Foster Wheeler Energia Oy's Research Center in Karhula, Finland. According to the industrial experiments, the four applications (steam pressure control, compensation of fuel quality fluctuation, fuel-feed optimization and increased bed inventory monitoring) discussed in this thesis, showed satisfactory performance and various improvements to the boiler control were achieved. Fuzzy logic control was shown to be a notable tool to improve the multi-fuel CFB boiler control.

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2016.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 224-229).<br>A number of CO₂ capture-enabled power generation technologies have been proposed to address the negative environmental impact of CO₂ emission. An important barrier to adopting these technologies is the associated energy and economic penalties. Chemical-looping (CLC) is an oxycombustion technology that can significantly lower such penalties, utilizing a redox process to eliminate the need for an air separation unit and enable better energy integration. Conventional CLC employs two separate reactors, with metal oxide particles circulating pneumatically in-between, leading to significant irreversibility associated with reactor temperature difference. A rotary reactor, on the other hand, maintains near-thermal equilibrium between the two stages by thermally coupling channels undergoing oxidation and reduction. In this thesis, a multiscale analysis for assessing the integration of the rotary CLC reactor technology in power generation systems is presented. This approach employs a sequence of models that successively increase the resolution of the rotary reactor representation, ranging from interacting thermal reservoirs to higher fidelity quasi-steady state models, in order to assess the efficiency potential and perform a robust optimization of the integrated system. Analytical thermodynamic availability and ideal cycles are used to demonstrate the positive impact of reactor thermal coupling on system efficiency. Next, detailed process flow-sheet models in which the rotary reactor is modeled as a set of interacting equilibrium reactors are used to validate the analytical model results, identify best cycle configurations and perform preliminary parametric analysis for between the reactor and the system while maintaining computational efficiency, an intermediate fidelity model is developed, retaining finite rate surface kinetics and internal heat transfer within the reactor. This model is integrated with a detailed system model and used for optimization, parametric analysis and characterization of the relative techno-economic performance of different oxygen carrier options for thermal plants integrated with the rotary CLC reactor. Results show that thermal coupling in the redox process increases the efficiency by up to 2% points for combined, recuperative and hybrid cycles. The studies also show that the thermal efficiency is a function of the reactor purge steam demand, which depends on the reactivity of the oxygen carrier. While purge steam constitutes a monotonic parasitic loss for the combined cycle, for recuperative and hybrid cycles, it raises the efficiency as long as the steam demand is less than a threshold value. This relationship between reactivity and system efficiency provides a useful selection criteria for the oxygen carrier material. Optimization results based on efficiency and levelized cost of electricity (LCOE) identify nickel-based oxygen carriers as the most suitable for the rotary reactor because its high reactivity ensures low steam demand and reactor cost. Compared to nickel, maximum efficiency and minimum LCOE are respectively 7% lower and 40% higher for a copper-based system; iron-based systems have 4% higher maximum efficiency and 7% higher minimum LCOE. This study also showed that optimal efficiency generally has an inverse profile to that for the optimized LCOE.<br>by Chukwunwike Ogbonnia Iloeje.<br>Ph. D.

The main goal of this work was to develop adaptive filter algorithms and test their performance in active combustion control. Several algorithms were incorporated, which are divided into gradient descent algorithms and pattern searches. The algorithms were tested on three separate platforms. The first was an analog electronic simulator, which uses a second order acoustics model and a first order low pass filter to simulate the flame dynamics of an unstable tube combustor. The second was a flat flame, methane-air Rijke tube. The third can be considered a quasi-LDI liquid fuel combustor with a thermal output of approximately 30 kW. Actuation included the use of an acoustic actuator for the Rijke tube and a proportional throttling valve for the liquid fuel rig. Proportional actuation, pulsed actuation, and subharmonic control were all investigated throughout this work. The proportional actuation tests on the Rijke tube combustor have shown that, in general, the gradient descent algorithms outperformed the pattern search algorithms. Although, the pattern search algorithms were able to suppress the pressure signal to levels comparable to the gradient descent algorithms, the convergence time was lower for the gradient descent algorithms. The gradient algorithms were also superior in the presence of actuator authority limitations. The pulsed actuation on the Rijke tube showed that the convergence time is decreased for this type of actuation. This is due to the fact that there is a fixed amplitude control signal and algorithms did not have to search for sufficient magnitude. It was shown that subharmonic control could be used in conjunction with the algorithms. Control was achieved at the second and third subharmonic, and control was maintained for much higher subharmonics. The cost surface of the liquid fuel rig was obtained as the mean squared error of the combustor pressure as a function of the magnitude and phase of the controller. The adaptive algorithms were able to achieve some suppression of the pressure oscillations but did not converge to the optimal phase as shown in the cost surface. Simulations using the data from this cost surface were also performed. With the addition of a probing function, the algorithms were able to converge to a near-optimal condition.<br>Master of Science

Une variété d’applications techniques dans la conversion d’énergie sont basées sur la combustion turbulente. En dépit du fonctionnement avancé de la technologie, la science de la combustion (turbulente) en est à un stade relativement jeune. Des études détaillées des flammes de référence sont essentielles pour mieux comprendre la physique sous-jacente aux processus mentionnés, ainsi que pour fournir une base de données fiable permettant de valider les modèles numériques développés pour simuler des problèmes de combustion turbulents. La spectroscopie Raman / Rayleigh est une technique extrêmement utile qui permet d’accéder simultanément à des informations sur la température et la concentration en espèces chimiques principales dans les structures de flammes. La data reduction strategy appliquée avec cette technique est cruciale pour extraire des informations fiables des investigations expérimentales. Dans cette thèse, une version modifiée de la stratégie, basée sur la Hybrid Method de Fuest et al., a été développée et testée à l’aide de techniques de résolution de NLP problem, dont des méthodes d’optimisation globale et un algorithme génétique. La stratégie proposée permet une réduction significative du temps de traitement des données, nécessite moins d’expertise de l’utilisateur et réduit l’erreur de mesure. La procédure modifiée a été appliquée à un data set fourni par une étude expérimentale de deux jet flame méthane/air prémélangés turbulentes appartenant au régime flamelet de la combustion prémélangée turbulente. Le data set est composé de plusieurs scalaires, y compris les principales espèces et la température, mesurés simultanément avec la single-shot 1D Raman/Rayleigh spectroscopy. Les résultats des mesures sont analysés et discutés<br>A variety of technical applications in energy conversion are based on turbulent combustion. Despite the advanced contest of operation, (turbulent) combustion science is at a relatively young stage. Detailed investigations of benchmark flames are essential to achieve a better understanding of the physics behind the mentioned processes, as well as to provide reliable database for validating numerical models developed to simulate turbulent combustion problems. Raman/Rayleigh spectroscopy is a highly valuable technique which allows to access simultaneous information on temperature and main chemical species concentration within the flame structures. The data reduction strategy applied with this technique is crucial, in order to extract reliable information from the experimental investigations. In this this thesis, a modified version of the strategy, based on the Hybrid Method by Fuest et al., has been developed and tested using NLP problem solving techniques, including global optimization methods and a genetic algorithm. The proposed strategy allows for a significant reduction of the data processing time, requires less user’s expertise and returns better results in reduced measurements error. The modified routine has been applied to data set provided by an experimental investigation of two turbulent premixed methane/air jet flames belonging to the flamelet regime of turbulent premixed combustion. The data set is composed by multiple scalars, including major species and temperature, simultaneously measured with single-shot 1D Raman/Rayleigh spectroscopy. The results of the measurements are analyzed and discussed

The deregulation of the electric power market introduced a strong element of competition. Power plant operators strive to develop advanced operational strategies to maximize the profitability in the dynamic electric power market. New methodologies for gas turbine power plant operational modeling and optimization are needed for power plant operation to enhance operational decision making, and therefore to maximize power plant profitability by reducing operations and maintenance cost and increasing revenue. In this study, a profit based, lifecycle oriented, and unit specific methodology for gas turbine based power plant operational modeling was developed, with the power plant performance, reliability, maintenance, and market dynamics considered simultaneously. The generic methodology is applicable for a variety of optimization problems, and several applications for operational optimization were implemented using this method. A multiple time-scale method was developed for gas turbine power plants long term generation scheduling. This multiple time-scale approach allows combining the detailed granularity of the day-to-day operations with global (seasonal) trends, while keeping the resulting optimization model relatively compact. Using the multiple timescale optimization method, a profit based outage departure planning method was developed, and the key factors for this profit based approach include power plant aging, performance degradation, reliability deterioration, and the energy market dynamics. A novel approach for gas turbine based power plant sequential preventive maintenance scheduling was also introduced. Finally, methods to evaluate the impact of upgrade packages on gas turbine power plant performance, reliability, and economics were developed, and TIES methodology was applied for effective evaluation and selection of gas turbine power plant upgrade packages.

La nécessité de diminuer l'impact climatique de l'aviation pousse les avionneurs à réfléchir à de nouvelles technologies pour "décarboner" l'aviation. En ce qui concerne la propulsion, l'une des alternatives envisagées est de remplacer le kérosène par de l'hydrogène. Ce changement de carburant permettrait de ne pas produire de CO2 mais implique des modifications profondes au niveau des injecteurs de la chambre de combustion. Historiquement, les différentes technologies d'injections ont été développées par essais-erreurs. Ce processus de conception a permis des avancées majeures mais manque de généricité et ne garantit pas l'obtention d'un injecteur optimal. Aujourd'hui, profitant de l'augmentation des moyens numériques, il est possible d'envisager l'utilisation massive de la CFD couplée avec des techniques d'optimisation pour concevoir et développer les nouvelles générations de chambre de combustion fonctionnant à l'hydrogène. Dans ce travail de thèse, une nouvelle méthode de conception est proposée afin de concevoir des injecteurs H2-air. Dans un premier temps, il est nécessaire de commencer par trois étapes préliminaires. À partir d'une version de base de l'injecteur MICADO qu'on cherche à améliorer, différentes méthodologies CFD sont comparées à des simulations de référence pour trouver le meilleur compromis précision-temps de restitution. Cette comparaison nous mène à retenir une approche haute fidélité utilisant des simulations LES et une approche basse fidélité basée sur des simulations RANS. En parallèle, une chaîne de calcul automatique est conçue pour faciliter la mise en pratique de la méthode de conception. Ensuite, la dernière étape préliminaire consiste à vérifier l'applicabilité d'une stratégie multi-fidélité, stratégie ayant le potentiel de réduire le coût total de l'optimisation. À la suite de ces étapes préliminaires, plusieurs études d'optimisation à deux et quatre paramètres sont menées afin de déterminer l'algorithme d'optimisation le plus performant à iso-budget entre différentes méthodes d'optimisation bayésienne. Cette comparaison entre les différentes études montre les capacités et limites des algorithmes sélectionnés à identifier des injecteurs prometteurs<br>The need to decrease the climate impact of aviation motivates aircraft manufacturers to find new technologies to decarbonize aviation. One of the possible solution concerning aircraft propulsion is to replace the use of kerosene by hydrogen. The combustion of hydrogen does not emit CO2 but it involves in-depth modifications of the injectors of the combustion chamber. Historically, injector design are based on a trial and error method. This approach was successful for legacy kerosene injectors but is fundamentally limited because it is both costly and tedious to explore all the given parameter space by hand. Nowadays, with the advances in computing science, CFD simulations can be considered massively in the combustor design process combined with the use of optimization techniques. In this thesis, we propose a new design method for the design of H2-air injectors. Firstly, it is necessary to begin with three preliminary steps. Starting from a baseline version of the MICADO injector that we want to improve, several CFD methodologies are compared to reference simulations in order to find the best trade-off accuracy/restitution time. This comparison leads us to retain a high fidelity approach based on LES simulations and a low fidelity approach based on RANS simulations. An automatic CFD workflow is developped simultaneously to ease the optimization studies. Then, the last preliminary step is to check the applicability of a multi-fidelity strategy, knowing that such a strategy can reduce the total cost of the optimization study. After these preliminary steps, several optimization studies of two and four dimensions are performed in order to determine the most efficient algorithm at a fixed budget between different Bayesian optimization methods. This comparison between the different studies shows the capabilities and the limits of the selected algorithms to identify promising injectors

Considered the influence of meteorological parameters (temperature, pressure, humidity) on oxygen quantitative content in the air. Showed the bias that introduced with not accounting the parameter of the oxygen current concentration in the air during the energy calculations in the power system. On the basis of experimental data established the dependence of oxygen volume concentration in the air from meteorological parameters (temperature, pressure, humidity). Analyzed the seasonal changes of oxygen concentration in the air in 12 European capitals (based on 2014 year): Brussels (Belgium), Paris (France), Berlin (Germany), Vienna (Austria), London (United Kingdom), Helsinki (Finland), Warsaw (Poland), Bucharest (Romania), Prague (Czech Republic), Sofia (Bulgaria), Riga (Latvia), Rome (Italy). Proposed the method for eliminating the methodical error of the excess air ratio measurement based on current oxygen volume concentration in the environment.

Thesis (S.M.)--Massachusetts Institute of Technology, System Design and Management Program, 2008.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Includes bibliographical references (leaves 119-124).<br>In-Cylinder Pressure Sensors (ICPS) today are close to satisfying the robustness, performance and cost requirements for application to closed loop control and monitoring of production automotive engines. Using the Robust Design framework as a compass, this thesis first checks the evidence for emergence followed by tracking the evolution of the sensor component itself and its application to robust closed loop control of the combustion process in internal combustion engines. After identifying the potential system level impact of the emerging ICPS technology, System Dynamic and Technology Strategy frameworks are used to find spillover triggers and to recommend a number of strategic options to generate and capture value for integrated system solution providers so that they can beat the very stable status quo that persists in the slow and mature prime mover industries. In addition, Chapter 2 gives a data driven method for identifying the Skills needed for suppliers to realize the above recommendations. This method is based on collective intelligence of 690 experienced professionals with 20 years of work experience on average from 40 targeted companies, representing a large body of engineering and managerial experience in battling complex engineering system hurdles. This approach is more effective than blindly copying the prominent integrated system solution providers or OEM's, because a side effect of long term incremental innovation in the mature prime mover industry is that the underlying reasons for their success is ingrained in their "tacit knowledge" and "organizational furniture" and hence not explicitly understood.<br>by Kamran Eftekhari Shahroudi.<br>S.M.

Dans l’optique de refroidir les parois des chambres de combustion aéronautiques le plus efficacement possible, un intérêt particulier est aujourd’hui porté à la technologie de refroidissement par transpiration. L’air de refroidissement s’écoule au travers d’une paroi poreuse dans laquelle une grande quantité de chaleur est échangée par convection. L’éjection de l’air profite ensuite de la distribution des pores pour former une couche limite protectrice relativement homogène.Les matériaux métalliques obtenus à partir de poudres partiellement frittées sont de bons candidats pour former ces parois poreuses. Ce travail se focalise sur les échanges internes et consiste à développer une méthodologie permettant de dégager les architectures partiellement frittées les plus adaptées à ce type d’application.L’écoulement et les échanges de chaleur lors du refroidissement par transpiration sont régis par quelques propriétés effectives des matériaux qui sont fonction de l’architecture : la conductivité thermique effective, le coefficient de transfert convectif volumique et les propriétés de perméabilité. A l’aide de travaux expérimentaux ou d’études numériques sur des échantillons numérisés par tomographie aux rayons X, des relations simples entre les propriétés effectives des matériaux partiellement frittés et leurs paramètres architecturaux sont tout d’abord développées. La porosité, la surface spécifique et le type de poudre utilisé sont retenus pour prédire les paramètres effectifs.Ces relations sont finalement intégrées dans un modèle de transfert de chaleur prédisant la performance d’une solution dans les conditions de fonctionnement du moteur. Une optimisation "multi-objectifs" et une analyse des designs optimaux permettent alors de mettre en valeur quelques architectures montrant un fort potentiel pour des applications de refroidissement par transpiration. Des matériaux peu poreux formés à partir de larges poudres irrégulières semblent assurer le meilleur compromis entre tous les critères pris en compte<br>In order to cool aero-engine combustion chambers as efficiently as possible, there is today a special interest given to transpiration cooling technology. The cooling air flows through a porous liner in which a large amount of heat can be exchanged by convection. The air injection could then take benefit of the pore distribution to form a more homogeneous protective boundary layer.Partially sintered metallic materials are potential candidates to form these porous liners. The present work focuses on internal heat transfers. It aims to develop a methodology capable of highlighting the most adapted partially sintered architectures to this kind of application.During transpiration cooling, flows and heat transfers are governed by some effective material properties which depends on the porous architecture: the effective solid phase thermal conductivity, the volumetric heat transfer coefficient and the permeability properties. Thanks to experimental works and numerical studies on samples digitized by X-ray tomography, simple relationships are first developed between the effective material properties of partially sintered materials and their architectural parameters. The porosity, the specific surface area and the powder type are selected to predict the effective properties.These relationships are finally integrated into a heat transfer model predicting the thermal performance of a design at working engine conditions. A multi-objective optimization and an analysis of the optimal designs highlight some architectures as being potentially interesting for transpiration cooling. Materials with a low porosity and made of large irregular powders seem to ensure the best trade-off among the different criteria taken into consideration

The development of a sustainable manufacturing process requires a comprehensive evaluation method and fundamental understanding of the processes. Coolant application is a critical sustainability concern in the widely used machining process. Cryogenic machining is considered a candidate for sustainable coolant application. However, the lack of comprehensive evaluation methods leaves significant uncertainties about the overall sustainability performance of cryogenic machining. Also, the lack of practical application guidelines based on scientific understanding of the heat transfer mechanism in cryogenic machining limits the process optimization from achieving the most sustainable performance. In this dissertation, based on a proposed Process Sustainability Index (ProcSI) methodology, the sustainability performance of the cryogenic machining process is optimized with application guidelines established by scientific modeling of the heat transfer mechanism in the process. Based on the experimental results, the process optimization is carried out with Genetic Algorithm (GA). The metrics-based ProcSI method considers all three major aspects of sustainable manufacturing, namely economy, environment and society, based on the 6R concept and the total life-cycle aspect. There are sixty five metrics, categorized into six major clusters. Data for all relavant metrics are collected, normalized, weighted, and then aggregated to form the ProcSI score, as an overall judgment for the sustainability performance of the process. The ProcSI method focuses on the process design as a manufacturer’s aspect, hoping to improve the sustainability performance of the manufactured products and the manufacturing system. A heat transfer analysis of cryogenic machining for a flank-side liquid nitrogen jet delivery is carried out. This is performed by micro-scale high-speed temperature measurement experiments. The experimental results are processed with an innovative inverse heat transfer solution method to calculate the surface heat transfer coefficient at various locations throughout a wide temperature range. Based on the results, the application guidelines, including suggestions of a minimal, but sufficient, coolant flow rate are established. Cryogenic machining experiments are carried out, and ProcSI evaluation is applied to the experimental scenario. Based on the ProcSI evaluation, the optimization process implemented with GA provides optimal machining process parameters for minimum manufacturing cost, minimal energy consumption, or the best sustainability performance.

Design and analysis of conceptually different cooling systems for the human heart preservation are numerically investigated. A heart cooling container with required connections was designed for a normal size human heart. A three-dimensional, high resolution human heart geometric model obtained from CT-angio data was used for simulations. Nine different cooling designs are introduced in this research. The first cooling design (Case 1) used a cooling gelatin only outside of the heart. In the second cooling design (Case 2), the internal parts of the heart were cooled via pumping a cooling liquid inside both the heart’s pulmonary and systemic circulation systems. An unsteady conjugate heat transfer analysis is performed to simulate the temperature field variations within the heart during the cooling process. Case 3 simulated the currently used cooling method in which the coolant is stagnant. Case 4 was a combination of Case 1 and Case 2. A linear thermoelasticity analysis was performed to assess the stresses applied on the heart during the cooling process. In Cases 5 through 9, the coolant solution was used for both internal and external cooling. For external circulation in Case 5 and Case 6, two inlets and two outlets were designed on the walls of the cooling container. Case 5 used laminar flows for coolant circulations inside and outside of the heart. Effects of turbulent flow on cooling of the heart were studied in Case 6. In Case 7, an additional inlet was designed on the cooling container wall to create a jet impinging the hot region of the heart’s wall. Unsteady periodic inlet velocities were applied in Case 8 and Case 9. The average temperature of the heart in Case 5 was +5.0oC after 1500 s of cooling. Multi-objective constrained optimization was performed for Case 5. Inlet velocities for two internal and one external coolant circulations were the three design variables for optimization. Minimizing the average temperature of the heart, wall shear stress and total volumetric flow rates were the three objectives. The only constraint was to keep von Mises stress below the ultimate tensile stress of the heart’s tissue.

Cette thèse traite de l'optimisation sous incertitude de fonctions coûteuses dans le cadre de la conception de systèmes aéronautiques. Nous développons dans un premier temps une stratégie d'optimisation robuste multiobjectifs par modèles de substitution. Au delà de fournir une représentation plus rapide des fonctions initiales, ces modèles facilitent le calcul de la robustesse des solutions par rapport aux incertitudes du problème. L'erreur de modélisation est maîtrisée grâce à une approche originale d'enrichissement de plan d'expériences qui permet d'améliorer conjointement plusieurs modèles au niveau des régions de l'espace possiblement optimales. Elle est appliquée à la minimisation des émissions polluantes d'une chambre de combustion de turbomachine dont les injecteurs peuvent s'obstruer de façon imprévisible. Nous présentons ensuite une méthode heuristique dédiée à l'optimisation robuste multidisciplinaire. Elle repose sur une gestion locale de la robustesse au sein des disciplines exposées à des paramètres incertains, afin d'éviter la mise en place d'une propagation d'incertitudes complète à travers le système. Un critère d'applicabilité est proposé pour vérifier a posteriori le bien-fondé de cette approche à partir de données récoltées lors de l'optimisation. La méthode est mise en oeuvre sur un cas de conception avion où la surface de l'empennage vertical n'est pas connue avec précision.

Transport Membrane Condenser (TMC) is an innovative technology based on the property of a nano-scale porous material which can extract both waste heat and water from exhaust gases. This technology tremendously improves the efficiency of boilers and gas/coal combustors by lowering waste heat and increasing water recovery. Contaminants in the flue gases, such as CO2, O2, NOx, and SO2 are inhibited from passing through the membrane by the membrane’s high selectivity. The condensed water through these tubes is highly pure and can be used as the makeup water for many industrial applications. The goal of this research is to investigate the heat transfer, condensation rate, pressure drop and overall performance of crossflow heat exchangers. In this research, a numerical model has been developed to predict condensation of water vapor over and inside of nano-porous layers. Both capillary condensation inside the nanoscale porous structure of the TMC and the surface condensation were considered in the proposed method using a semi-empirical model. The transport of the water vapor and the latent heat of condensation were applied in the numerical model using the pertinent mass, momentum, turbulence and energy equations. By using the proposed model and simulation procedure, the effect of various inlet parameters such as inlet mass flow rate, inlet temperature, and water vapor content of the inlet flow on the performance of the cross-flow TMC heat exchanger was studied to obtain the optimum performance of the heat exchangers at different working conditions. The performance of the TMC heat exchangers for inlet flue gas rate 40 to 120 kg/h, inlet water rate 60 to 140 kg/h, inlet flue gas relative humidity 20 to 90%, and tube pitch ratio 0.25 to 2.25 has been studied. The obtained results show that the water condensation flux continuously increases with the increase of the inlet flue-gas flow rate, water flow rate, and the flue-gas humidity. The total heat flux also follows the same trend due to the pronounced effect of the latent heat transfer from the condensation process. The water condensation flux and the overall heat transfer increase at the beginning for small values of the tube pitches and then decreases as the tube pitch increases furthermore. In addition to the cross-flow TMC heat exchangers, the performance of a shell and tube TMC heat exchanger for high pressure and temperature oxy-combustion applications has been investigated. The performance analysis for a 6-heat exchanger TMC unit shows that heat transfer of the 2-stage TMC unit is higher than the 2-stage with the same number of the heat exchanger in each unit.

Lors de la modélisation d’un processus de combustion, l’obtention de données globales telles que la vitesse de flamme peut sous certaines condition être réalisée à l’aide de mécanismes très réduits. En revanche, la prédiction de données détaillées comme la concentration d’espèces polluantes minoritaires nécessite l’utilisation de mécanismes cinétiques détaillés mettant en jeu de nombreuses espèces chimiques. Du fait de leur taille et des différences d’échelles de temps, l’intégration de tels modèles chimiques à des simulations numériques complexes est cependant extrêmement coûteuse en temps de calcul. Pour s’affranchir de cette limite, un outil de réduction basé sur les méthodes de Directed Relation Graph et d’analyse de sensibilité a été développé. Il permet la génération automatique de mécanismes réduits en fonction de quantités d’intérêt telles que les données globales (vitesse de flamme, délai d’auto-allumage, etc) et détaillées (profils de concentration) en fonction de tolérances d’erreur définies par l’utilisateur. Les opérations de réduction sont couplées à une optimisation par algorithme génétique des constantes de réaction afin de compenser au maximum les erreurs issues de la perte d’information. Cette optimisation peut être réalisée par rapport à des données issues de simulations numériques mais également par rapport à des mesures expérimentales. L’outil complet a été testé sur différentes configurations canoniques pour différents combustibles (méthane, éthane et n-heptane) et des taux de réduction supérieurs à 80% ont pu être obtenus<br>In the modeling of a combustion process, obtention of global data such as flame speed can, under certain circumstances, be achieved through extremely reduced mechanisms. On the contrary, prediction of detailed data such as polluant species requires the use of detailed kinetic mechanisms involving many chemical species. Due to the size and to the presence of many differents time scales, the integration of those models to complex numerical simulations is a non trivial task. A reduction tool based on Directed Relation Graph and sensitivity analysis methods is proposed to tackle this issue. Reduced mechanisms fitting user defined tolerances for quantities of interest such as global (flame speed, ignition delay, etc) and detailed data (concentration profiles) are automatically generated. The reduction process is paired up with an optimisation of reaction rates through a genetic algorithm to make up for the error induced by the loss of information. This process can use both numerical and experimental reference entries. The complete numerical tool has been tested on several canonical configurations for several fuels (methane, ethane and n-heptane) and reduction rates up to 90% have been observed

Avec la sévérisation des réglementations environnementales sur les émissions polluantes (normes Euro) des moteurs d'automobiles, la nécessité de maitriser les phénomènes de combustion a motivé le développement de la simulation numérique comme outil d'aide à la conception. Tenant compte de la complexité des phénomènes à modéliser, et de l'antagonisme des objectifs à optimiser, l'optimisation évolutionnaire multi-objectif semble être la mieux adaptée pour résoudre ce type de problèmes. Cependant, l'inconvénient principal de cette approche reste le coût très élevé en termes de nombre d'évaluations qui peut devenir très contraignant dans le contexte des optimisations réelles caractérisées par des évaluations très coûteuseL'objectif principal de ce travail de thèse est de réduire le coût global des optimisations du monde réel, en explorant la parallélisation des algorithmes évolutionnaires multi-objectifs, et en utilisant les techniques de réduction du nombre d'évaluations (méta-modèles).Motivés par le phénomène d'hétérogénéité des coûts des évaluations, nous nous proposons d'étudier les schémas d'évolution stationnaires asynchrones dans une configuration parallèle de type " maître-esclave ". Ces schémas permettent une utilisation plus efficace des processeurs sur la grille de calcul, et par conséquent de réduire le coût global de l'optimisation.Ce problème a été attaqué dans un premier temps d'un point de vue algorithmique, à travers une adaptation artificielle des algorithmes évolutionnaires multi-objectifs au contexte des optimisations réelles caractérisées par un coût d'évaluation hétérogène. Dans un deuxième temps, les approches développées et validées dans la première partie sur des problèmes analytiques, ont été appliquées sur la problématique de la combustion Diesel qui représente le contexte industriel de cette thèse. Dans ce cadre, deux types de modélisations ont été utilisés: la modélisation phénoménologique 0D et la modélisation multidimensionnelle 3D. La modélisation 0D a permis par son temps de retour raisonnable (quelques heures par évaluation) de comparer l'approche stationnaire asynchrone avec celle de l'état de l'art en réalisant deux optimisations distinctes. Un gain de l'ordre de 42 % a été réalisé avec l'approche stationnaire asynchrone. Compte tenu du temps de retour très coûteux de la modélisation complète 3D (quelques jours par évaluation), l'approche asynchrone stationnaire déjà validée a été directement appliquée. L'analyse physique des résultats a permis de dégager un concept intéressant de bol de combustion permettant de réaliser un gain en termes d'émissions polluantes.

An investigation into the performance of several combined gas-steam power generating plants’ cycles was undertaken at the School of Engineering and Technology at the University of Hertfordshire and it is predominantly analytical in nature. The investigation covered in principle the aspect of the fundamentals and the performance parameters of the following cycles: gas turbine, steam turbine, ammonia-water, partial oxidation and the absorption chiller. Complete thermal analysis of the individual cycles was undertaken initially. Subsequently, these were linked to generate a comprehensive computer model which was employed to predict the performance and characteristics of the optimized combination. The developed model was run using various input parameters to test the performance of the cycle’s combination with respect to the combined cycle’s efficiency, power output, specific fuel consumption and the temperature of the stack gases. In addition, the impact of the optimized cycles on the generation of CO2 and NOX was also investigated. This research goes over the thermal power stations of which most of the world electrical energy is currently generated by. Through which, to meet the increase in the electricity consumption and the environmental pollution associated with its production as well as the limitation of the natural hydrocarbon resources necessitated. By making use of the progressive increase of high temperature gases in recent decades, the advent of high temperature material and the use of large compression ratios and generating electricity from high temperature of gas turbine discharge, which is otherwise lost to the environment, a better electrical power is generated by such plant, which depends on a variety of influencing factors. This thesis deals with an investigation undertaken to optimize the performance of the combined Brayton-Rankine power cycles' performance. This work includes a comprehensive review of the previous work reported in the literature on the combined cycles is presented. An evaluation of the performance of combined cycle power plant and its enhancements is detailed to provide: A full understanding of the operational behaviour of the combined power plants, and demonstration of the relevance between power generations and environmental impact. A basic analytical model was constructed for the combined gas (Brayton) and the steam (Rankine) and used in a parametric study to reveal the optimization parameters, and its results were discussed. The role of the parameters of each cycle on the overall performance of the combined power cycle is revealed by assessing the effect of the operating parameters in each individual cycle on the performance of the CCPP. P impacts on the environment were assessed through changes in the fuel consumption and the temperature of stack gases. A comprehensive and detailed analytical model was created for the operation of hypothetical combined cycle power and power plant. Details of the operation of each component in the cycle was modelled and integrated in the overall all combined cycle/plant operation. The cycle/plant simulation and matching as well as the modelling results and their analysis were presented. Two advanced configurations of gas turbine cycle for the combined cycle power plants are selected, investigated, modelled and optimized as a part of combined cycle power plant. Both configurations work on fuel rich combustion, therefore, the combustor model for rich fuel atmosphere was established. Additionally, models were created for the other components of the turbine which work on the same gases. Another model was created for the components of two configurations of ammonia water mixture (kalina) cycle. As integrated to the combined cycle power plant, the optimization strategy considered for these configurations is for them to be powered by the exhaust gases from either the gas turbine or the gases leaving the Rankine boiler (HRSG). This included ChGT regarding its performance and its environmental characteristics. The previously considered combined configuration is integrated by as single and double effect configurations of an ammonia water absorption cooling system (AWACS) for compressor inlet air cooling. Both were investigated and designed for optimizing the triple combination power cycle described above. During this research, tens of functions were constructed using VBA to look up tables linked to either estimating fluids' thermodynamic properties, or to determine a number of parameters regarding the performance of several components. New and very interesting results were obtained, which show the impact of the input parameters of the individual cycles on the performance parameters of a certain combined plant’s cycle. The optimized parameters are of a great practical influence on the application and running condition of the real combined plants. Such influence manifested itself in higher rate of heat recovery, higher combined plant thermal efficiency from those of the individual plants, less harmful emission, better fuel economy and higher power output. Lastly, it could be claimed that various concluding remarks drawn from the current study could help to improve the understanding of the behaviour of the combined cycle and help power plant designers to reduce the time, effort and cost of prototyping.

Les moteurs à combustion interne jouent un rôle crucial dans notre société moderne, alimentant une variété d'applications allant des transports aux générateurs d'énergie. Face aux défis croissants en matière d'efficacité, d'émissions et de durabilité, une compréhension approfondie et une modélisation précise de la combustion sont essentielles. Cette thèse se consacre à la modélisation de la combustion dans les moteurs à combustion interne en se concentrant sur le mode dual fuel. L'objectif est de contribuer de manière significative à la compréhension, à la modélisation et à l'optimisation de la combustion dans ces moteurs. Les contributions incluent l'amélioration des modèles existants, la validation expérimentale, la caractérisation des performances des moteurs dans divers modes de combustion, ainsi que la proposition de stratégies de modélisation et d'optimisation pour réduire les émissions et améliorer l'efficacité énergétique. La thèse présente plusieurs axes d'exploitation basés sur divers outils et approches. Un modèle prédictif 0D a été développé pour un moteur dual fuel fonctionnant avec un mélange de gaz naturel et d'hydrogène comme carburant primaire. Ensuite, la thèse aborde la modélisation des problèmes limitant le fonctionnement du moteur dual fuel, notamment le cliquetis et la surchauffe des injecteurs. La décarbonation de ces moteurs est ensuite mise en œuvre via l'utilisation de combustibles alternatifs tels que l'ammoniac et le méthanol, en se basant sur des simulations 3D. Enfin, des méta-modèles innovants ont été développés à des fins d'optimisation des moteurs, incluant une nouvelle approche de modélisation multi-fidélité et une optimisation multi-objectifs. Les résultats de cette thèse apportent des avancées significatives dans la modélisation et l'optimisation des moteurs à combustion interne fonctionnant en mode dual fuel, proposant des solutions potentielles pour améliorer l'efficacité énergétique et réduire les émissions, répondant ainsi aux défis environnementaux et énergétiques actuels et futurs<br>Internal combustion engines play a crucial role in our modern society, powering a variety of applications ranging from transportation to power generators. Given the growing challenges related to efficiency, emissions, and sustainability, a deep understanding and precise modeling of combustion are essential. This thesis is devoted to modeling dual fuel engines. The aim is to make significant contributions to the understanding, modeling, and optimization of combustion in these engines. Contributions include the improvement of existing models, experimental validation, characterization of engine performance in various combustion modes, and the proposal of modeling and optimization strategies to reduce emissions and improve energy efficiency. The thesis presents several lines of exploitation based on various tools and approaches. A 0D predictive model was developed for dual fuel engine operating with a mixture of natural gas and hydrogen as the primary fuel. Subsequently, the thesis addresses the modeling of issues limiting the operation of the dual fuel engine, such as knocking and injector overheating. The decarbonization of dual fuel engines is then implemented using alternative fuels such as ammonia and methanol, based on 3D simulations. Finally, innovative meta-models have been developed for engine optimization, including a new multi-fidelity modeling approach and multi-objective optimization. The thesis results provide significant advancements in the modeling and optimization of internal combustion engines operating in dual fuel mode, proposing potential solutions to improve energy efficiency and reduce emissions, thereby addressing current and future environmental and energy challenges

Environmentally friendly and efficiently produced energy from sustainable and renewable resources is of great importance. Carbon dioxide (CO2) and nitric oxides (NOx) are the main emissions of air-breathing gas turbines in power plants. Gas turbines of the power generation industry are normally fueled with liquid fuels, natural gas or syngas in changing qualities. Syngas can be produced by gasification processes in IGCC power plants and consist of varying percentages of the main fractions hydrogen (H2) and carbon monoxide (CO). CO2 emissions can be reduced by a decrease of the CO-share and an increase of the hydrogen-share in the syngas fuel, and by using pre-combustion carbon capture and sequestration (CCS) technology. For low NOx, current gas turbine combustion chamber technologies require diluents, a rather low H2 content and modifications of the combustor hardware. A feasible solution for low NOx hydrogen and syngas combustion in gas turbines is the Micromix principle developed at Aachen University of Applied Sciences. The goal of this doctoral thesis is the research on a Micromix combustor with increased power densities fueled with hydrogen-rich syngas with about 90% by volume hydrogen, and going up to 100% hydrogen in the fuel. Test burner experiments are used to characterize the combustion and emission properties of a multitude of key drivers. Based on this optimization with a variety of scaled model test burners, a prototype dual-fuel hydrogen/syngas Micromix combustor is designed and integrated into the annular combustion chamber of an industrial gas turbine. In the gas turbine, the performance characteristics of the prototype-combustor are investigated under real operational conditions with hydrogen-rich syngas and pure hydrogen.<br>Doctorat en Sciences de l'ingénieur et technologie<br>info:eu-repo/semantics/nonPublished

The thesis deals with the design of a small-volume four-stroke internal combustion engine with a maximum displacement of 10 cc and a power of 1 kW for autonomous devices of smaller dimensions. In addition to the analysis of individual propulsions for small aircraft, there is also a chapter with the comparison of an internal combustion engine and an electric motor with similar power. Another part of the work is the creation of a thermodynamic model in the GT Power program and its subsequent optimization to increase the overall efficiency of the engine.

O presente trabalho objetivou ilustrar procedimentos de analise auxiliada por computador e metodologia de desenvolvimento para arvores de manivela tendo-se como meta sugestões de boas praticas de projeto visando a otimização de componentes segundo necessidades ditadas pelos clientes, competidores e legislações vigentes. Ilustrou-se uma lista das etapas principais do projeto e desenvolvimento de virabrequins com foco na analise dinâmica e estrutural do componente. Para estas etapas especificas, resumiu-se a teoria básica envolvida nos cálculos e analises necessários e, para casos de abordagens consagradas distintas na resolução de um mesmo problema, realizou-se uma comparação de precisão e custo envolvidos. Posteriormente, aplicou-se o conjunto de ferramentas analisadas em um estudo de caso com uma arvore de manivelas de quatro cilindros em linha, obtendo-se o desempenho estrutural e dinâmico do componente seguido de uma otimização paramétrica. Observou-se um potencial de ganho de precisão desde o calculo do carregamento aplicado no componente a otimização do mesmo, com o uso de métodos clássicos aplicados a nova tecnologia de software e hardware disponível. Concluiu-se que a organização adequada e utilização específica das ferramentas disponíveis trazem benefícios expressivos na qualidade dos resultados, melhor utilização dos recursos disponíveis e visão global do vinculo de diferentes parâmetros de desempenho.<br>In the current dissertation it was aimed to illustrate procedures regarding computer aided analysis and methodology for development of crankshafts seeking best practices suggestions to design and focusing on component optimization. These methods must adequate component design to customer, competitors and laws demands. Main development and design tasks for crankshafts were shown centering attention on dynamic and structural analysis. The basic needed theory for these specific tasks with calculus and analyses was summarized and, when more than one common approach was applicable, a cost and precision comparison was performed. Afterward, these tools were applied in a case study where main performance parameters for an inline four cylinder engine crankshaft were obtained. The component was analyzed structurally and dynamically for a subsequent parametric optimization. A potential benefit in precision was observed from applied loads calculation to the mentioned optimization by using available classic methods and modern software and hardware technology mutually. It was concluded that, with an adequate project organization and specific usage of available methods, expressive results can be obtained in results quality, best resources employment and general understanding of performance parameters links.

With the demand of computing power from electronic chips on a constant rise, innovative methods are needed for effective and efficient thermal management. Forced convection cooling through an array of micro pin-fins acts not only as a heat sink, but also allows for the electrical interconnection between stacked layers of integrated circuits. This work performs a multi-objective optimization of three shapes of pin-fins to maximize the efficiency of this cooling system. An inverse design approach that allows for the design of cooling configurations without prior knowledge of thermal mapping was proposed and validated. The optimization study showed that pin-fin configurations are capable of containing heat flux levels of next generation electronic chips. It was also shown that even under these high heat fluxes the structural integrity is not compromised. The inverse approach showed that configurations exist that are capable of cooling heat fluxes beyond those of next generation chips. Thin film heat spreaders made of diamond and graphene nano-platelets were also investigated and showed that further reduction in maximum temperature, increase in temperature uniformity and reduction in thermal stresses are possible.

Vibro-acoustic comfort has become an increasingly integral part of vehicle development over the past 20 years. The perception inside the cabin has a high impact on customer satisfaction and expresses the quality of premium vehicles. The phenomenon of interior noise has always been very complex to study. The problem is complicated by the fact that there is a well-known variability in products. This is due both to variability in the assembly line and in the properties of individual components. The goal is for as many vehicles as possible to meet the design requirements. Among the various categories of noise, low-frequency noise has deserved special attention from development engineers over the years. It is, in fact, particularly annoying, and can also cause loss of attention and drowsiness while driving. In the category of low-frequency noise, booming is one of those phenomena that one surely wants to avoid while developing a vehicle. This phenomenon is used in this work as a target for the analysis. Almost all components, which directly, or via isolating elements, are mounted to the vehicle chassis, can generate booming under certain circumstances. This is the case, for example, of the powertrain. In conventional vehicles powered by an internal combustion engine, the powertrain is bound to the chassis with a system of elastomeric mounts. The forces generated by the engine, during operation, are transferred through the mounts to the body, and here generate structural noise, which is perceived with discomfort by passengers. Using isolating elements to decouple components is a very common practice. Yet the dynamic properties of the mounts are hardly known with sufficient accuracy. Therefore there is always the need to make measurements and to check if the used mounts meet the requirements. It is also well known that the characteristics of these components depend on various parameters. The most important of these are static preload, frequency and amplitude of excitation. Hardly all three dependencies are measured and simulated simultaneously. Mounts present, moreover, a marked variability of their characteristics, from which it follows a variability of vehicle's acoustic quality. In the first part of this thesis, a methodology is presented for the characterization of powertrain mounts, under real operating conditions, which allows to experimentally measure and model the three dependencies described above. Starting from measurements on a dedicated test bench, using response surfaces, and a virtual point transformation methodology, parametric models of the dynamic stiffnesses of the mounts are generated. With these, considering a representative pool of vehicles, a robust optimization of the powertrain mounts is proposed, aiming at reducing the booming noise in a population of vehicles. However, not only conventional vehicles are affected by this phenomenon. In electric vehicles, the endothermic engine is replaced by a quieter electric motor. In doing so, other components, whose noise was previously masked by the powertrain, become paramount. One such component is the air-conditioning compressor, which has acquired a new function in electric vehicles, that of cooling the battery module during charging. When in full load operation, it can generate low frequency booming noise. In the second part of this thesis, this effect is analyzed, using inverse methodologies, coupled with virtual point transformation techniques. The analysis includes, in this case, the identification of the characteristics of the component, identifying its internal forces and moments acting during operation. An analytical modeling of the component mounted in the vehicle is proposed and validated through experimental measurements. The dynamic stiffnesses of the mounts are modeled through parametric functions, whose parameters are optimized through "in-situ" experimental measurements.<br>Vibro-acoustic comfort has become an increasingly integral part of vehicle development over the past 20 years. The perception inside the cabin has a high impact on customer satisfaction and expresses the quality of premium vehicles. The phenomenon of interior noise has always been very complex to study. The problem is complicated by the fact that there is a well-known variability in products. This is due both to variability in the assembly line and in the properties of individual components. The goal is for as many vehicles as possible to meet the design requirements. Among the various categories of noise, low-frequency noise has deserved special attention from development engineers over the years. It is, in fact, particularly annoying, and can also cause loss of attention and drowsiness while driving. In the category of low-frequency noise, booming is one of those phenomena that one surely wants to avoid while developing a vehicle. This phenomenon is used in this work as a target for the analysis. Almost all components, which directly, or via isolating elements, are mounted to the vehicle chassis, can generate booming under certain circumstances. This is the case, for example, of the powertrain. In conventional vehicles powered by an internal combustion engine, the powertrain is bound to the chassis with a system of elastomeric mounts. The forces generated by the engine, during operation, are transferred through the mounts to the body, and here generate structural noise, which is perceived with discomfort by passengers. Using isolating elements to decouple components is a very common practice. Yet the dynamic properties of the mounts are hardly known with sufficient accuracy. Therefore there is always the need to make measurements and to check if the used mounts meet the requirements. It is also well known that the characteristics of these components depend on various parameters. The most important of these are static preload, frequency and amplitude of excitation. Hardly all three dependencies are measured and simulated simultaneously. Mounts present, moreover, a marked variability of their characteristics, from which it follows a variability of vehicle's acoustic quality. In the first part of this thesis, a methodology is presented for the characterization of powertrain mounts, under real operating conditions, which allows to experimentally measure and model the three dependencies described above. Starting from measurements on a dedicated test bench, using response surfaces, and a virtual point transformation methodology, parametric models of the dynamic stiffnesses of the mounts are generated. With these, considering a representative pool of vehicles, a robust optimization of the powertrain mounts is proposed, aiming at reducing the booming noise in a population of vehicles. However, not only conventional vehicles are affected by this phenomenon. In electric vehicles, the endothermic engine is replaced by a quieter electric motor. In doing so, other components, whose noise was previously masked by the powertrain, become paramount. One such component is the air-conditioning compressor, which has acquired a new function in electric vehicles, that of cooling the battery module during charging. When in full load operation, it can generate low frequency booming noise. In the second part of this thesis, this effect is analyzed, using inverse methodologies, coupled with virtual point transformation techniques. The analysis includes, in this case, the identification of the characteristics of the component, identifying its internal forces and moments acting during operation. An analytical modeling of the component mounted in the vehicle is proposed and validated through experimental measurements. The dynamic stiffnesses of the mounts are modeled through parametric functions, whose parameters are optimized through "in-situ" experimental measurements.

Orientador: Marco Lúcio Bittencourt<br>Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica<br>Made available in DSpace on 2018-08-24T09:08:40Z (GMT). No. of bitstreams: 1 LimaeSilva_RafaelAugustode_M.pdf: 10555723 bytes, checksum: 1d037ebafbabc24e214c06ad76c5f54a (MD5) Previous issue date: 2013<br>Resumo: O trabalho descreve o projeto mecânico convencional de uma biela automotiva de motor de combustão interna e apresenta uma metodologia alternativa baseada em métodos de otimização estrutural com o objetivo de reduzir a massa do componente. Para tal, é feita a descrição de todos os parâmetros de projeto assim como a definição de critérios de projeto. Em virtude da criticidade da aplicação selecionada, motor de ciclo Diesel utilizado em caminhões de trabalho pesado com picos de pressão de combustão de até 240 bar, a biela foi projetada sem bucha utilizando-se extensivamente os métodos numéricos. O Método dos Elementos Finitos foi aplicado para cálculo de tensões, deslocamentos, pressões de contato, flambagem, fadiga e para a síntese modal de componentes utilizados na análise dinâmica de multicorpos com mancais elasto-hidrodinâmicos. Dois modelos de fadiga dos materiais foram estudados: o modelo americano baseado no diagrama de Goodman e tensões principais e o modelo alemão baseado no diagrama de Haigh e efeito do gradiente de tensões multiaxiais; dos quais concluiu-se que o modelo americano é suficiente para o projeto da biela ao passo que o modelo alemão traz oportunidades adicionais de redução de massa. A otimização topológica, otimização de forma e análise de sensibilidade permitiram a obtenção de uma biela 210g (3\%) mais leve e com melhor desempenho dos mancais hidrodinâmicos. Finalmente, concluiu-se que o Método da Otimização Topológica apresenta oportunidades interessantes aos projetistas na fase de conceituação de produtos como alternativa aos desenhos convencionais, no entanto, demanda esforço adicional para o atendimento de todos os critérios de projeto do componente<br>Abstract: The present work consists of the conventional mechanical design description of an internal combustion engine connecting rod and also the proposal of an alternative methodology based on optimization methods with the objective of reducing the component mass. Therefore, it is performed a detailed view of all design parameters as well as the definition of design criteria. Because of the critical application selected, Diesel engine of heavy duty truck with combustion pressure reaching up to 240bar, the connecting rod was designed without bushing and with extensive use of numerical methods. The Finite Element Method was applied to assess stresses, displacements, contact pressures, buckling, fatigue and to perform the Component Modal Synthesis for multi-body dynamics simulation with elasto-hydrodynamic bearings. Two fatigue models were studied: the American model based on Goodman's diagram and principal stresses and the German model based on Haigh's diagram and multiaxial stress gradient effect; from which it was concluded that the American model is enough to design the connecting rod, while the German model presents additional weight reduction opportunities. The topology optimization, shape optimization and sensitivity analysis enabled a 210g (3\%) lighter connecting rod with improved bearings performance. Finally, it was concluded that the Topology Optimization Method presents good opportunities for the design engineers in the conceptual phases of product development with alternatives to the conventional designs. However, additional effort is necessary to fit the concept into all design criteria<br>Mestrado<br>Mecanica dos Sólidos e Projeto Mecanico<br>Mestre em Engenharia Mecânica

The aim of this report is to study a proposed air pollution control (APC) system designed to treat flue gases produced during the combustion of waste derived syngas. In order to achieve this objective, a literature study was done to gain insight into the pollution formation during gasification and combustion of syngas, and a model of the APC system was built using the Aspen Plus software. This model was used in four different case studies aimed at optimizing the water and chemical requirements throughout the system. Several different types of wastes were considered; municipal solid waste (MSW) representing that which is normally generated in developed countries, MSW representing that which is normally generated in developing countries, a waste composition representing that of the plastic fraction of MSW, and a waste composition representing that of the biomass fraction of MSW.   Based on the results of the literature study, a few conclusions could be drawn. Sulfur compounds could be expected to be found in the form of H2S in the syngas and SO2 in the flue gases. Chlorine compounds could be expected to be found in the form of HCl and the nitrogen compounds in the form of NH3, HCN and N2 after gasification and NO after combustion. The amount of research done in the area of MSW gasification, and combustion of MSW based syngas, is, however, small, and more research is needed.   Based on the results of the case studies, the amount of NaOH varied greatly depending on flue gas composition and negligibly depending on recirculation setup. The total amount of water required varied notably between the different cases studied and no case stood out clearly as the optimal case for all four waste compositions. The case studies seemed to indicate a trend towards an increased total water requirement with an increase in the amount recirculation. The four best cases where cases 2,3,4 and 10, out of which case three has been recommended as a good initial estimate from which to depart when finding the optimal setup for a specific system under study. In case 3, 40 wt% of the fresh water from the first splitter was sent to the direct contact scrubber, 50 wt% of the remaining fresh water was sent to the absorption tower, 40 wt% of the liquid leaving the absorption tower was recycled back to the direct contact scrubber, and 40 wt% of the remaining water leaving the absorption tower was recycled back to the absorption tower.

Un moteur diesel faible puissance a était converti en A. C. Puis alimenté au gaz naturel. Les caractéristiques générales de la combustion (délais, durées de combustion, dispersion cyclique) ont été étudiées en fonction du rapport air-gaz, de l'avance à l'allumage, et du type de bougie ainsi que les performances du moteur. Pour le comportement en mélange très pauvre, nous avons déterminé les limites opératoires, analyse le déroulement de la combustion et observe les variations de pression. En utilisant un générateur de turbulence en forme de cône, nous avons reculé les limites pauvres et réduit la dispersion cyclique et la pollution estimée en fonction de la richesse du mélange, de l'avance à l'allumage, de la vitesse et de la charge du moteur. A la fin de l'étude, nous donnons les conditions opératoires optimum pour différentes charges et vitesses.

[EN] This Thesis is focused on the development and implementation of efficient numerical methods for the acoustic modelling and design of noise control devices in the exhaust system of combustion engines. Special attention is paid to automotive perforated dissipative silencers, in which significant differences are likely to appear in their acoustic behaviour, depending on the temperature variations within the absorbent material. Also, material heterogeneities can alter the silencer attenuation performance. Therefore, numerical techniques considering all these features are required to guarantee the accuracy of the results. A literature review is carried out, mainly related to one-dimensional models, as well as to acoustic models for absorbent materials and perforated surfaces. However, plane wave model limitations make indispensable using alternative multidimensional methods. In addition, the possibility of using new acoustic elements is explored. These elements have as an objective being a potential alternative to the fibrous absorbent materials, which can have a negative impact on health. The Thesis considers the use of microperforated and sintered surfaces. The latter have, in some cases, a nearly constant acoustic impedance, whose value depends, among others, on the thickness and porosity of the plates. To avoid the limitations of plane wave models, a finite element (FE) approach is proposed for the acoustic analysis of dissipative silencers including a perforated duct with uniform axial mean flow and an outer chamber with a heterogeneous distribution of the absorbent material. On the other hand, property variations can be also produced by temperature gradients. In this case, a hybrid FE model has been derived for perforated dissipative silencers including: (1) Thermal gradients in the central duct and the chamber; (2) A perforated passage carrying non-uniform axial mean flow. A FE approach has been implemented to solve the pressure-based wave equation for a non-moving heterogeneous medium, associated with the chamber. Also, the governing equation in the central duct has been written and solved in terms of an acoustic velocity potential to allow the presence of an axially inhomogeneous flow. The coupling between both regions has been carried out by means of a perforated duct and its acoustic impedance, adapted here to include absorbent material heterogeneities and mean flow effects. It has been found that the presence of non-homogeneities can have a significant influence on the acoustic attenuation of a silencer and should be included in the theoretical models. Optimization techniques for industrial noise control devices are relevant, since they lead to the production of elements with better characteristics. Evolutionary algorithms are emergent techniques able to obtain a solution, even in those problems in which the traditional optimization have difficulties. Optimization techniques are combined with the FE method to achieve the maximum attenuation in the frequency range of interest. A multichamber silencer optimization problem is defined and several analyses are carried out to obtain the most suitable configuration for each application. Under certain assumptions of axial uniformity, several techniques have been considered to reduce the computational effort of a full 3D FE analysis for dissipative silencers with temperature gradients and mean flow. These are based on a decomposition of the acoustic field into transversal and axial modes within each silencer subdomain, and a matching procedure of the modal expansions at the silencer area changes through the continuity conditions of the acoustic fields. The relative computational efficiency and accuracy of predictions for the matching techniques are studied, including point collocation at nodes and Gauss points and also mode-matching with weighted integration. All of them provide accurate predictions of the attenuation and improve the computational cost of a FE calculation<br>[ES] Esta Tesis se centra en el desarrollo e implementación de métodos numéricos eficientes para el diseño y modelado de componentes de la línea de escape en motores de combustión interna. Merecen especial atención los silenciadores disipativos perforados de automóviles, ya que su comportamiento acústico puede sufrir variaciones importantes debidas a las variaciones de temperatura en el material absorbente, así como a las heterogeneidades de la fibra. Por tanto, se requieren técnicas numéricas que consideren estos casos para garantizar la precisión de los resultados. Se lleva a cabo una revisión bibliográfica que recoge los modelos de onda unidimensionales, así como modelos acústicos de materiales absorbentes y superficies perforadas. Sin embargo, las limitaciones de los primeros hacen indispensable el uso de modelos multidimensionales. Además se explora la posibilidad de usar nuevos elementos acústicos, cuyo objetivo es ser una alternativa potencial a los materiales absorbentes, que pueden tener un efecto negativo sobre la salud. La Tesis considera el uso de superficies microperforadas y sinterizadas. Estas últimas en algunos casos presentan una impedancia casi constante, cuyo valor depende, entre otras cosas, del espesor y la porosidad de las placas. Para evitar las limitaciones de los modelos de onda plana, se propone un enfoque en elementos finitos (EF) para el análisis acústico de silenciadores disipativos que incluyen un conducto con flujo medio axial uniforme y una cámara externa con una distribución heterogénea de material absorbente. Por otro lado, la variación de las propiedades también puede producirse por gradientes térmicos. En este caso, se propone una formulación híbrida de EF para silenciadores disipativos perforados que incluye: (1) Gradientes térmicos en el conducto central y la cámara; (2) Un conducto perforado que canaliza flujo medio axial no uniforme. Se ha implementado una formulación de EF para resolver la ecuación de ondas en términos de presión para el medio estacionario heterogéneo asociado a la cámara. Además, la ecuación asociada al conducto central, expresada en términos de potencial de velocidad acústica, permite la presencia de flujo axial no uniforme. El acoplamiento entre ambas regiones se ha realizado mediante un conducto perforado y su impedancia acústica y se ha adaptado para incluir la citada falta de homogeneidad. Se ha visto que las heterogeneidades pueden influir notablemente en la atenuación acústica de un silenciador, debiéndose incluir en los modelos teóricos. Las técnicas de optimización para componentes industriales de control de ruido son importantes, ya que producen elementos con mejores características. Los algoritmos evolutivos son técnicas emergentes capaces de obtener una solución, incluso cuando la optimización tradicional tiene dificultades. Las técnicas de optimización se combinan con el MEF para conseguir la máxima atenuación posible en el rango de frecuencias de interés. Se ha definido un problema de optimización de un silenciador multicámara y se han llevado a cabo varios análisis para obtener la configuración más adecuada para cada caso. Bajo ciertas hipótesis de uniformidad axial, se han considerado varias técnicas para reducir el coste computacional de un análisis 3D completo para silenciadores disipativos con gradientes de temperatura y flujo medio. Éstas se basan en la descomposición del campo acústico en modos axiales y transversales dentro de cada subdominio, y un procedimiento de acoplamiento de las expansiones modales en los cambios de sección del silenciador mediante las condiciones de continuidad de los campos acústicos. Se estudia la eficiencia computacional y precisión de las predicciones de las técnicas de acoplamiento, incluyendo colocación puntual en nodos y puntos de Gauss, así como ajuste modal. Todos ellos proporcionan predicciones precisas de la atenuación mejorando el coste<br>[CAT] Aquesta Tesi es centra en el desenvolupament i implementació de mètodes numèrics eficients per al disseny i modelatge de components de la línia d'escapament en motors de combustió interna. Mereixen especial atenció els silenciadors dissipatius perforats d'automòbils, ja que el seu comportament acústic pot patir variacions importants degudes a les variacions de temperatura en el material absorbent, així com a les heterogeneïtats de la fibra. Per tant, es requereixen tècniques numèriques que considerin aquests casos per garantir la precisió dels resultats. Es porta a terme una revisió bibliogràfica que recull els models d'ona unidimensionals, així com models acústics de materials absorbents i superfícies perforades. No obstant això, les limitacions dels primers fan indispensable l'ús de models multidimensionals. A més s'explora la possibilitat d'usar nous elements acústics amb l'objectiu que siguen una alternativa potencial als materials absorbents, que poden tenir un efecte negatiu sobre la salut. La Tesi considera l'ús de superfícies microperforades i sinteritzades. Aquestes últimes en alguns casos presenten una impedància gairebé constant. El seu valor depèn, entre altres coses, del gruix i la porositat de les plaques. Per evitar les limitacions dels models d'ona plana, es proposa un enfocament amb elements finits (EF) per a l'anàlisi acústic de silenciadors dissipatius que inclouen un conducte amb flux mig axial uniforme i una càmera externa amb una distribució heterogènia de material absorbent. D'altra banda, la variació de les propietats també es pot produir per gradients tèrmics. En aquest cas, es proposa una formulació híbrida d'EF per silenciadors dissipatius perforats que inclou: (1) Gradients tèrmics en el conducte central i la càmera; (2) Un conducte perforat que canalitza flux mig axial no uniforme. S'ha implementat una formulació d'EF per resoldre l'equació d'ones en termes de pressió per al medi estacionari heterogeni associat a la càmera. A més, l'equació associada al conducte central, expressada en termes de potencial de velocitat acústica, permet la presència de flux axial no uniforme. L'acoblament entre les dues regions s'ha realitzat mitjançant un conducte perforat i la seva impedància acústica i s'ha adaptat per incloure la esmentada falta d'homogeneïtat. S'ha vist que les heterogeneïtats poden influir notablement en l'atenuació acústica d'un silenciador i s'han d'incloure en els models teòrics. Les tècniques d'optimització per a components industrials de control de soroll són importants, ja que produeixen elements amb millors característiques. Els algoritmes evolutius són tècniques emergents capaces d'obtenir una solució, fins i tot quan l'optimització tradicional té dificultats. Les tècniques d'optimització es combinen amb el mètode d'elements finits (MEF) per aconseguir la màxima atenuació possible en el rang de freqüències d'interès. S'ha definit un problema d'optimització d'un silenciador multicàmera i s'han dut a terme diverses anàlisis per obtenir la configuració més adequada per a cada cas. Sota certes hipòtesis d'uniformitat axial, s'han considerat diverses tècniques per reduir el cost computacional d'una anàlisi 3D complet per silenciadors dissipatius amb gradients de temperatura i flux mig. Aquestes es basen en la descomposició del camp acústic en modes axials i transversals dins de cada subdomini, i un procediment d'acoblament de les expansions modals en els canvis de secció del silenciador mitjançant les condicions de continuïtat dels camps acústics. S'estudia l'eficiència computacional i precisió de les prediccions de les tècniques d'acoblament, incloent col·locació puntual en nodes i punts de Gauss, així com ajust modal. Tots ells proporcionen prediccions precises de l'atenuació millorant el cost computacional d'EF.<br>Sánchez Orgaz, EM. (2016). Advanced numerical techniques for the acoustic modelling of materials and noise control devices in the exhaust system of internal combustion engines [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/64090<br>TESIS