Relevant bibliographies by topics / Flowsheet optimization

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Flowsheet optimization'

Author: Grafiati
Published: 4 June 2021
Last updated: 8 February 2022

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Journal articles on the topic "Flowsheet optimization"

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Lang, Y.-D., and L. T. Biegler. "A unified algorithm for flowsheet optimization." Computers & Chemical Engineering 11, no. 2 (1987): 143–58. http://dx.doi.org/10.1016/0098-1354(87)80014-5.

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Yang, Linlin, and Ignacio E. Grossmann. "Water Targeting Models for Simultaneous Flowsheet Optimization." Industrial & Engineering Chemistry Research 52, no. 9 (2012): 3209–24. http://dx.doi.org/10.1021/ie301112r.

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Turkay, Metin, and Ignacio E. Grossmann. "Structural flowsheet optimization with complex investment cost functions." Computers & Chemical Engineering 22, no. 4-5 (1998): 673–86. http://dx.doi.org/10.1016/s0098-1354(97)00221-4.

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Samborskaya, M. A., I. A. Gryaznova, and A. V. Volf. "Pre-design Optimization of Crude Oil Distillation Flowsheet." Procedia Chemistry 15 (2015): 134–42. http://dx.doi.org/10.1016/j.proche.2015.10.022.

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Grossmann, Ignacio E., Héctor Yeomans, and Zdravko Kravanja. "A rigorous disjunctive optimization model for simultaneous flowsheet optimization and heat integration." Computers & Chemical Engineering 22 (March 1998): S157—S164. http://dx.doi.org/10.1016/s0098-1354(98)00050-7.

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Biegler, L. T. "Process flowsheet optimization strategies: recent results and future directions." Applied Numerical Mathematics 3, no. 5 (1987): 393–408. http://dx.doi.org/10.1016/0168-9274(87)90029-8.

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Medeiros, J. L., L. C. Barbosa, F. M. Vargas, O. Q. F. Araújo, and R. M. F. Silva. "Flowsheet optimization of a lubricant base oil hydrotreatment process." Brazilian Journal of Chemical Engineering 21, no. 2 (2004): 317–24. http://dx.doi.org/10.1590/s0104-66322004000200022.

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Brice, A. A., and W. R. Johns. "Optimization of flowsheet drawing layout using a genetic algorithm." Computers & Chemical Engineering 22, no. 1-2 (1998): 47–67. http://dx.doi.org/10.1016/s0098-1354(96)00351-1.

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Palmer, K., and M. Realff. "Metamodeling Approach to Optimization of Steady-State Flowsheet Simulations." Chemical Engineering Research and Design 80, no. 7 (2002): 760–72. http://dx.doi.org/10.1205/026387602320776830.

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Palmer, K., and M. Realff. "Optimization and Validation of Steady-State Flowsheet Simulation Metamodels." Chemical Engineering Research and Design 80, no. 7 (2002): 773–82. http://dx.doi.org/10.1205/026387602320776849.

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Dissertations / Theses on the topic "Flowsheet optimization"

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Kisala, Thomas P. "Successive Quadratic Programming in sequential modular process flowsheet simulation and optimization." Thesis, Massachusetts Institute of Technology, 1985. http://hdl.handle.net/1721.1/99554.

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Thesis (Sc. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 1985.<br>MICROFICHE COPY AVAILABLE IN ARCHIVES AND SCIENCE.<br>Bibliography: leaves 244-248.<br>by Thomas Patrick Kisala.<br>Sc.D.
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Dowling, Alexander W. "An Equation-based Framework for Large-Scale Flowsheet Optimization and Applications for Oxycombustion Power System Design." Research Showcase @ CMU, 2015. http://repository.cmu.edu/dissertations/568.

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Over the past thirty years, flowsheet optimization methods have evolved from “black box” approaches to sophisticated equation-oriented methods for simultaneous flowsheet convergence and optimization. This thesis explores the next generation of flowsheet optimization tools that leverage completely open models (with exact first and second derivatives) and utilizes start-of-theart nonlinear programming (optimization) solvers. A five part framework is proposed in this thesis: 1. Embedded cubic equation of state thermodynamic models with complementarity constraints to accommodate vanishing and reappearing phases 2. Simultaneous heat integration and process optimization using the pinch location method 3. Aggregate short-cut and rigorous tray-by-tray distillation models 4. Steam cycle equipment (e.g., turbine) and boiler models 5. Trust region optimization algorithm to incorporate models with expensive derivatives into the equations-based framework A systematic initialization routine based on model refinement and multistart procedure are also presented as practical alternatives to global optimization. Complementarity constraints are used throughout the framework to model switches, such as vanishing phases. Degeneracy Hunter, an algorithm that identifies irreducible sets of degenerate constraints (i.e., constraints with a rank deficient Jacobian) is proposed and used to refine the models. The framework is demonstrated in a series of case studies related to the design of oxycombustion power systems with CO2 capture. Two case studies focus on the simultaneous optimization of gases separation systems and their accompanying multistream heat exchangers. In one of these case studies, the optimization procedure identifies common air separation unit configurations with comparable specific energy requirements to industrial designs. The framework is also used to optimize regenerate Rankine cycles, where steam flowrates from nine extraction points for boiler feedwater heating are considered as optimization variables. This allows for waste heat from compression to the completely integrated into the steam cycle. Steam table lookups (without derivatives) are incorporated using reduced models and a trust region optimization algorithm.
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Bongartz, Dominik [Verfasser], Alexander [Akademischer Betreuer] Mitsos, and Benoit [Akademischer Betreuer] Chachuat. "Deterministic global flowsheet optimization for the design of energy conversion processes / Dominik Bongartz ; Alexander Mitsos, Benoit Chachuat." Aachen : Universitätsbibliothek der RWTH Aachen, 2020. http://d-nb.info/1216638357/34.

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Abrol, Sidharth. "Advanced tabulation techniques for faster dynamic simulation, state estimation and flowsheet optimization." 2009. http://hdl.handle.net/2152/6521.

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Large-scale processes that are modeled using differential algebraic equations based on mass and energy balance calculations at times require excessive computation time to simulate. Depending on the complexity of the model, these simulations may require many iterations to converge and in some cases they may not converge at all. Application of a storage and retrieval technique, named in situ adaptive tabulation or ISAT is proposed for faster convergence of process simulation models. Comparison with neural networks is performed, and better performance using ISAT for extrapolation is shown. In particular, the requirement of real-time dynamic simulation is discussed for operating training simulators (OTS). Integration of ISAT to a process simulator (CHEMCAD®) using the input-output data only is shown. A regression technique based on partial least squares (PLS) is suggested to approximate the sensitivity without accessing the first-principles model. Different record distribution strategies to build an ISAT database are proposed and better performance using the suggested techniques is shown for different case studies. A modified ISAT algorithm (mISAT) is described to improve the retrieval rate, and its performance is compared with the original approach in a case study. State estimation is a key requirement of many process control and monitoring strategies. Different nonlinear state estimation techniques studied in the past are discussed with their relative advantages/disadvantages. A robust state estimation technique like moving horizon estimation (MHE) has a trade-off between accuracy of state estimates and the computational cost. Implementation of MHE based ISAT is shown for faster state estimation, with an accuracy same as that of MHE. Flowsheet optimization aims to optimize an objective or cost function by changing various independent process variables, subject to design and model constraints. Depending on the nonlinearity of the process units, an optimization routine can make a number of calls for flowsheet (simulation) convergence, thereby making the computation time prohibitive. Storage and retrieval of the simulation trajectories can speed-up process optimization, which is shown using a CHEMCAD® flowsheet. Online integration of an ISAT database to solve the simulation problem along with an outer-loop consisting of the optimization routine is shown using the sequential-modular approach.<br>text
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Books on the topic "Flowsheet optimization"

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Ponce-Ortega, José María, and Luis Germán Hernández-Pérez. Optimization of Process Flowsheets through Metaheuristic Techniques. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-91722-1.

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Ponce-Ortega, José María, and Luis Germán Hernández-Pérez. Optimization of Process Flowsheets through Metaheuristic Techniques. Springer, 2018.

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Ponce-Ortega, José María, and Luis Germán Hernández-Pérez. Optimization of Process Flowsheets through Metaheuristic Techniques. Springer, 2019.

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Book chapters on the topic "Flowsheet optimization"

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Spinola, Michele, Alexander Keimer, Doris Segets, Lukas Pflug, and Günter Leugering. "Modeling, Simulation and Optimization of Process Chains." In Dynamic Flowsheet Simulation of Solids Processes. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-45168-4_16.

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Kennedy, Mark William. "Metallurgical Plant Optimization through the Use of Flowsheet Simulation Modelling." In Celebrating the Megascale. John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118889657.ch34.

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Kennedy, Mark William. "Metallurgical Plant Optimization Through the use of Flowsheet Simulation Modelling." In Celebrating the Megascale. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-48234-7_34.

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Ponce-Ortega, José María, and Luis Germán Hernández-Pérez. "Metaheuristic Optimization Programs." In Optimization of Process Flowsheets through Metaheuristic Techniques. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91722-1_3.

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Ponce-Ortega, José María, and Luis Germán Hernández-Pérez. "Optimization of Industrial Process 1." In Optimization of Process Flowsheets through Metaheuristic Techniques. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91722-1_6.

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Ponce-Ortega, José María, and Luis Germán Hernández-Pérez. "Optimization of Industrial Process 2." In Optimization of Process Flowsheets through Metaheuristic Techniques. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91722-1_7.

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Ponce-Ortega, José María, and Luis Germán Hernández-Pérez. "Interlinking Between Process Simulators and Optimization Programs." In Optimization of Process Flowsheets through Metaheuristic Techniques. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91722-1_4.

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Ponce-Ortega, José María, and Luis Germán Hernández-Pérez. "Introduction." In Optimization of Process Flowsheets through Metaheuristic Techniques. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91722-1_1.

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Ponce-Ortega, José María, and Luis Germán Hernández-Pérez. "Process Simulators." In Optimization of Process Flowsheets through Metaheuristic Techniques. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91722-1_2.

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Ponce-Ortega, José María, and Luis Germán Hernández-Pérez. "Performance Evaluation." In Optimization of Process Flowsheets through Metaheuristic Techniques. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91722-1_5.

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Conference papers on the topic "Flowsheet optimization"

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Royyuru, Haritha, Lijian Sun, Yitung Chen, et al. "Development of Systems Engineering Model for UREX Process." In ASME 2003 International Mechanical Engineering Congress and Exposition. ASMEDC, 2003. http://dx.doi.org/10.1115/imece2003-42043.

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The mission of the Transmutation Research Program (TRP) at University of Nevada, Las Vegas (UNLV) is to establish a national nuclear technology research capability, a nuclear engineering test bed that can carry out effective transmutation and advanced reactor research and development effort. The main task of the Chemical Engineering Division, Argonne National Laboratories (ANL) is to design, model, and demonstrate countercurrent uranium solvent-extraction process. The division has developed MS Excel macros interface, called Argonne Model for Universal Solvent Extraction (AMUSE), to calculate flowsheets for treating high-level liquid waste. The AMUSE code forms all computational basis for flowsheet design and process development. The extraction process, including U, Tc, Pu/Np, Cs/Sr, and Am/Cm separations, is complicate and requires further system optimization for robust performance. A systems engineering model is proposed by the Nevada Center for Advanced Computational Methods (NCACM) at UNLV that provides process optimization through the adjustment on feed compositions, stages, number of sections and flow rates. The NCACM is designing and developing a MS Visual Basic graphical user interface (GUI) that provides multiple-run results and data reporting and presentation. All calculations are made by the interaction with the MS Excel macros, defined in ANL AMUSE codes. An optimization model, developed with the GUI, interconnects with MatLab’s optimization toolbox, commercial software from MathWorks. Due to the nature of the AMUSE code, all the computational results are generated from the existing AMUSE macros. The model also examines measure effects of process deviations, caused by operational upsets or product diversion.
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Yokoyama, Ryohei, and Koichi Ito. "Performance Evaluation of Gas Turbine Cogeneration Plants Using a Design Optimization Tool: OPS-Design." In ASME Turbo Expo 2006: Power for Land, Sea, and Air. ASMEDC, 2006. http://dx.doi.org/10.1115/gt2006-90611.

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To attain the highest performance of gas turbine cogeneration plants, it is important to rationally determine their structures as well as equipment numbers and capacities in consideration of their operational strategies corresponding to seasonal and hourly variations in energy demands. However, it needs much task and time. In this paper, a design optimization tool named “OPS-Design” is developed to determine the structures as well as equipment numbers and capacities for given super structures of energy supply plants. This tool uses optimization approaches based on the mixed-integer linear programming, and has a user-friendly interface for the functions of data registration, graphical flowsheet editing, automatic programming and optimization calculation, and graphical representation of results. In addition, the performance of a gas turbine cogeneration plant is evaluated using the tool in terms of the annual total cost and primary energy consumption. It is demonstrated that the tool is very effective to evaluate the performance rationally, easily, and flexibly.
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Yokoyama, Ryohei, and Koichi Ito. "Evaluation of Operational Performance of Gas Turbine Cogeneration Plants Using an Optimization Tool: OPS-Operation." In ASME Turbo Expo 2003, collocated with the 2003 International Joint Power Generation Conference. ASMEDC, 2003. http://dx.doi.org/10.1115/gt2003-38381.

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To attain the highest performance of gas turbine cogeneration plants, it is necessary to rationally select the numbers and capacities of gas turbines and auxiliary equipment in consideration of their operational strategies corresponding to energy demands which change with season and time. It is also important to rationally select the options such as the variable heat to power by the steam injection or combined cycle, and the inlet air cooling by the ice storage combined with electric compression refrigeration or steam absorption refrigeration. The evaluation of the effects of these alternatives on the performance is an important work for designers. However, it takes much time to conduct the work thoroughly. The authors have developed an optimization tool named “OPS-Operation” to assess the operational strategies for given configurations and specifications of energy supply plants. This tool has a user-friendly interface for the functions of data registration, graphical flowsheet editing, automatic programming and optimization calculation, and graphical representation of results. In this paper, the effects of the aforementioned alternatives on the operational performance of gas turbine cogeneration plants are evaluated using the optimization tool in terms of many criteria including operational cost, energy consumption, and CO2 emission. It is demonstrated that the tool is very effective to evaluate the performance rationally, flexibly, and easily.
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Sun, Lijian, Haritha Royyuru, Hsuan-Tsung Hsieh, et al. "Development of Systems Engineering Model for Spent Fuel Extraction Process." In ASME 2004 International Mechanical Engineering Congress and Exposition. ASMEDC, 2004. http://dx.doi.org/10.1115/imece2004-60178.

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The mission of the Transmutation Research Program (TRP) at University of Nevada, Las Vegas (UNLV) is to establish a nuclear engineering test bed that can carry out effective transmutation and advanced reactor research and development effort. Chemical Engineering Division, Argonne National Laboratories (ANL) is in charge the design, modeling, and demonstration of countercurrent solvent-extraction process for treating high-level liquid waste, such as U and Tc. The Nevada Center for Advanced Computational Methods (NCACM) at UNLV is developing a systems engineering model that provides process optimization through the automatic adjustment on input parameters, such as feed compositions, stages, flow rates, etc., based on the extraction efficiency of components and concerned output factors. An object-oriented programming (OOP) is considered. Previously designed Microsoft (MS) Excel macro-based program, Argonne Model for Universal Solvent Extraction (AMUSE) code, based on firm understanding of the chemistry and thermodynamics, is the core module for Uranium Extraction process (UREX). Currently AMUSE is the only available module. The Transmutation Research Program System Engineering Model Project (TRPSEMPro) consists of task manager, task integration and solution/monitor modules. A MS SQL server database is implemented for managing large data flow from optimization processing. Task manager coordinates and interacts with other two modules. Task integration module works as a flowsheet constructor that builds task hierarchy, input parameter values and constrains. Task solution/monitor component presents both final and in-progress outputs in tabular and graphical formats. The package also provides a multiple-run process that executes a design matrix without invoking the optimization module. Experimental reports can be generated through database query and formatting.
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Miller, Jason D., David J. Buckmaster, Katherine Hart, et al. "Comparison of Supercritical CO2 Power Cycles to Steam Rankine Cycles in Coal-Fired Applications." In ASME Turbo Expo 2017: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/gt2017-64933.

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Increasing the efficiency of coal-fired power plants is vital to reducing electricity costs and emissions. Power cycles employing supercritical carbon dioxide (sCO2) as the working fluid have the potential to increase power cycle efficiency by 3–5% points over state-of-the-art oxy-combustion steam-Rankine cycles operating under comparable conditions. To date, the majority of studies have focused on the integration and optimization of sCO2 power cycles in waste heat, solar, or nuclear applications. The goal of this study is to demonstrate the potential of sCO2 power cycles, and quantify the power cycle efficiency gains that can be achieved versus the state-of-the-art steam-Rankine cycles employed in oxy-fired coal power plants. Turbine inlet conditions were varied among the sCO2 test cases and compared with existing Department of Energy (DOE)/National Energy Technology6 Laboratory (NETL) steam base cases. Two separate sCO2 test cases were considered and the associated flow sheets developed. The turbine inlet conditions for this study were chosen to match conditions in a coal-fired ultra-supercritical steam plant (Tinlet = 593°C, Pinlet = 24.1 MPa) and an advanced ultra-supercritical steam plant (Tinlet = 730°C, Pinlet = 27.6 MPa). A plant size of 550 MWe, was selected to match available information on existing DOE/NETL bases cases. The effects of cycle architecture, combustion-air preheater temperature, and cooling source type were considered subject to comparable heat source and reference conditions taken from the steam Rankine reference cases. Combinations and variants of sCO2 power cycles — including cascade and recompression and variants with multiple reheat and compression steps — were considered with varying heat-rejection subsystems — air-cooled, direct cooling tower, and indirect-loop cooling tower. Where appropriate, combustion air preheater inlet temperature was also varied. Through use of a multivariate nonlinear optimization design process that considers both performance and economic impacts, curves of minimum cost versus efficiency were generated for each sCO2 test case and combination of architecture and operational choices. These curves indicate both peak theoretical efficiency and suggest practical limits based on incremental cost versus performance. For a given test case, results for individual architectural and operational options give insight to cost and performance improvements from step-changes in system complexity and design, allowing down selection of candidate architectures. Optimized designs for each test case were then selected based on practical efficiency limits within the remaining candidate architectures and compared to the relevant baseline steam plant. sCO2 cycle flowsheets are presented for each optimized design.
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