Academic literature on the topic 'ASPEN-Plus'

This thesis project is focusing on the modeling, optimization and control analysis of a debutanizer column using Aspen PLUS and Aspen Dynamics. A complex mixture of hydrocarbons contained a different range of hydrogen and carbon from C2 until nC8 was fed into the debutanizer column for the separation process. There are two products coming out from this distillation column; the light-end hydrocarbons (C2-C4) and the heavier-end hydrocarbons (C5+). The C2-C4 became the desired product for debutanizer column which required to be separated from the mixed hydrocarbons. This C2-C4 was removed from distillate stream as an overhead product. Meanwhile, the C5+ was removed from the bottoms stream as a bottoms product. The target of this project was to recover 90% of butane (C4) and maximum 5 mol% of pentane (C5) composition in the distillate stream. This target was achieved at the end of the project by obtaining approximately 91.1% of C4 recovery and 4.039 mol% of C5 in the distillate stream. Therefore, it concluded the recovery of C5 in the bottoms stream was 90.3%. The debutanizer model was firstly constructed in the Aspen PLUS for steady-state simulation which relied on several specifications of the column and the criteria of the process. The simulation of this separation process was designed using rigorous distillation column simulator, RadFrac. A comparison of physical property methods between Peng-Robinson and RK-Soave were investigated by considering the same theoretical stages in each configuration. Then, the final type of property model was selected depending on the lowest offset from industrial data. A sensitivity analysis was performed to simulate the column within a range of the parameter, and an optimization problem was formulated to be solved. The steady-state flowsheet generated in Aspen PLUS was exported into Aspen Dynamics to simulate the column in dynamic simulation. The debutanizer system has multiple input variables to control the multiple output variables. Therefore, the relative gain array (RGA) analysis was calculated based on the steady-state gain obtained from open loop transfer functions to find the best pairing of input-output. The conventional Proportional-Integral (PI) and cascade control were implemented into the debutanizer column and both control required to be tuned. Therefore, a relay auto-tuning in Aspen Dynamics was used to determine the ultimate period (Pu) and ultimate gain (KCU) of each process. Then, the controller parameters could be calculated using Ziegler-Nichols method. The control strategy was carried out to observe the process response towards changes of set-point and to analyze the relationships between the process variables (PV) and manipulated variables (MV). The disturbance rejection was performed to determine the success of established control scheme. At the end of the project, multiple comparisons were made between the results obtained from Aspen PLUS and Aspen Dynamics with the literature papers. Overall, all thesis objectives were completed, and the purpose of the debutanizer column to be simulated in Aspen PLUS and Aspen Dynamics were successful.

Orientador: Maria Regina Wolf Maciel<br>Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Quimica<br>Made available in DSpace on 2018-08-01T10:10:37Z (GMT). No. of bitstreams: 1 Torres_ArmandoAntoniodeOliveira_M.pdf: 3727476 bytes, checksum: fd50582b75f3a0a86a9bcd1a8428aa68 (MD5) Previous issue date: 2001<br>Resumo: O Processo Bayer é definido como uma tecnologia para a produção de óxido de alumínio (Ah03), principal matéria prima para a produção de Alumínio. Este processo transforma o minério de bauxita em alumina Ah03, utilizando soda cáustica e vapor gerado por caldeiras. Os sub processos que compõem o processo Bayer são a Moagem, Digestão, Filtração, Troca Térmica, Precipitação, Calcinação e Evaporação. Utilizando os dados da Refinaria de Poços de Caldas e trabalhando no Laboratório de Desenvolvimento de Processos de Separação da Faculdade de Engenharia Química da Unicamp, foi desenvolvido um método que utiliza os modelos existentes no software Aspen Plus para compor o "Modelo do Processo Bayer".O principal objetivo deste trabalho foi inter-relacionar os modelos do Aspen Plus para representar a Refinaria de Poços de Caldas, simulando o balanço de massa e energia do processo Bayer. A simulação foi conduzi da utilizando o módulo do simulador para sistemas eletrolíticos, considerando o estado dos componentes em seu modo verdadeiro, para melhor representar a não idealidade da solução. O licor do processo Bayer é uma solução eletrolítica, em que a água é o solvente e os demais componentes da mistura, NaOH, NaAlOz, NazCO3 estão completamente dissociados em íons como Na+, AlOz-, CO3-z, e OH-. As operações unitárias utilizadas do software para construir o "Modelo do Processo Bayer" foram o reator estequiométrico, tanques de "flash", lavadores simples, decantadores de contra corrente, misturadores, aquecedores e condensadores. O processo Bayer é controlado através do monitoramento das concentrações alcalina (TA), cáustica (TC) na unidade de equivalente g NazCO3 por litro de licor, como também a concentração de alumina em g AlzO3 por litro de licor. Foi necessário desenvolver uma metodologia que transformasse estas concentrações para expressões na base em massa para os compostos NaOH, NaAlOz, NazCO3 e água. A equação de densidade do Aspen Plus apresentou um desvio de 15% quando tentou-se obter os volumes e massas da solução. Foi necessária a utilização de uma outra equação de densidade (Equação de Russel) para desenvolver o método de transformação das concentrações de solução em massa. Comparando-se este método com dados analíticos, encontrou-se desvios da ordem de 1 %, demonstrando grande precisão do método. A entrada de dados para as simulações foram provenientes de amostras e análises químicas do licor e medidas de fluxo, temperatura e pressão do processo produtivo. Com os resultados da simulação do "Modelo do Processo Bayer", as massas dos íons Na+, AL02-, C03-2, e OH- são obtidas, as quais são transformadas em concentrações nas bases TA, TC e AhO3, para que seja possível a comparação entre os resultados do modelo e os dados analíticos de cada sub processo. Os desvios entre os resultados dos modelos de cada sub processo e as concentrações de planta estiveram entre O e 3 %. F oram utilizados fatores de ajuste para representar o sub processo da digestão e a evaporação natural dos tanques de processo para aumentar a precisão do modelo. O "Modelo do Processo Bayer" apresentou baixos desvios da realidade quando foram comparadas com as concentrações da solução cáustica da planta e as geradas pelo modelo. Foi observado o grande potencial de utilização nas seguintes atividades: Planejamento operacional e estimativa do custo de produção da alumina de acordo com o consumo de soda, bauxita e energia. Controle de volume da planta. Predizer as concentrações cáusticas do licor; Diferenças e perdas de energia em aquecedores; Identificação de anonnalidades no processo<br>Abstract: (AlzO3), main raw material to produce Aluminum. This process transforms Bauxite ore in a white sand alumina (AlzO3), using Caustic Soda and Steam from the Boilers. The sub processes that represent a Bayer Refinery are Grinding, Digestion, Filtration, Heat Exchange, Precipitation, Ca1cination and Evaporation. Using the Poços de Caldas Refinery data, and working at the Separation Process Development Laboratory at Campinas State University, a method to link the models in Aspen Plus software, to build up the Bayer process was developed. The main objective of this work was to interrelate the models from the Aspen Plus to represent the Poços de Caldas Refinery, to simulate the Energy and Mass Balances from the Bayer Process. Simulation for Electrolyte Systems were performed, with true components and to represent the non-ideality ofthe liquid solution, the NRTL thermodynamic model was used to get the activity coefficients in order to calculate the vapor-liquid phase equilibria. The Bayer liquor is an electrolyte solution, in which water is the solvent and the components from the mixture, NaOH, NaAlO2, Na2CO3 are completely dissociated in ions as Na+, AlO2-, CO3-Z and OH-. The unit operations used from the software to build up the Bayer process are: Stoichometric Reactor, Flash Tank, Single Wash, Counter Current Decanter, Mixers, Heaters and Condensers. The Bayer process is controlled by following the alkaline, caustic and alumina concentrations in equivalent unit (g Na2CO3 per liquor liter). A methodology to transform this concentration expression in mass of NaOH, NaAlOz, Na2CO3 and water was necessary to be developed. The density equation from the Aspen Plus gave 15% of error when it was tried to calculate the volumes or the masses. Another equation (Russell equation) was, then, used to develop the method to transform the concentration number in mass. Comparing with analytical data, the error were about 1 %, giving a good accuracy to the translated method. Samples and chemical analyses, flows, temperature and pressure measurements are the inputs for the model from the planto The outputs from the "Bayer Model" in Na+, AIO2-, CO3-and OR mass, were transformed in TA, TC and AhO3 concentrations (Alkaline, Caustic and Alumina concentration) to compare with the results of the analytical plant that were collected in the outlets from each sub processo Each sub processes was runned and the outputs plant concentrations were compared with the results from Aspen giving deviations between O and 3%. Fitting factors in the reactor to represent the digestors were used. The natural evaporation that occurs in the tanks was necessary to be considered in the model to increase its accuracy. The Bayer Model developed can be used to: Control the plant volume. Predict liquor concentration and find ilegal dilution in the process. Carry out an operating plan and to estimate the alumina cash cost according to the consumption of Soda, Bauxite and Energy Proceed with mass and energy balances and lost in the heaters. So, using the models from Aspen Plus for Electrolyte System, it is possible to build up a "Bayer Process Model" to represent a Plant with deviation between O to 3%. With this accuracy, the model can predict the energy and mass balances and the solution concentrations from the plant liquor. The density equation from Russell is necessary to be used to get the accuracy commented to translate the liquor concentration (TA, TC and AhO3) to the NaOH, NaAlO2, Na2CO3 and Water<br>Mestrado<br>Desenvolvimento de Processos Químicos<br>Mestre em Engenharia Química

Syftet med den här studien är att göra en teknoekonomisk utvärdering av processer för förvätskning av CO2 med hjälp av Aspen Plus. Ett flertal förvätskningsprocesser från tidigare studier jämfördes och från dessa valdes två förvätskningsprocesser ut för fortsatta studier och simuleringar. Dessa två förvätskningsprocesser var ett internt kylt förvätskningssystem och ett externt kylt förvätskningssystem av Øi et al., Energy Procedia 86 (2016) 500-510, som kallats system A, samt av Seo et al., International Journal of Greenhouse Gas Control 35 (2015) 1-12 kallat system B. Dessa två olika processer simulerades för teknisk analys med hjälp av Aspen Plus. Aspen Economical Analyzer (AEA) användes för att göra den ekonomiska analysen. I dessa simuleringar användes ett massflöde på 45 ton/h inkluderat vatteninnehåll, i jämförelse med tidigare studier med högre massflöden runt 100 ton/h. Elektricitet-och kylbehovet undersöktes i ett flertal olika fall med varierande kyltemperatur mellan kompressorerna. Två fall med integrering av fjärrvärme samt två fall med en värmepump undersöktes också med varierande återgående temperatur på fjärrvärmevattnet. Detta gjordes för att undersöka hur mycket värme som kan tillvaratas från förvätskningsprocessen. Vidare bestämdes även investeringskostnader samt driftskostnader med hjälp av AEA. Från detta bestämdes även den årliga kostnaden av kapitalet, CAPEX, och kostnaden att förvätska CO2 räknades ut i form av €/ton.  Resultaten visade att integrering av fjärrvärme samt värmepumpar är användbart för att tillvarata på så mycket värme som möjligt från förvätskningssystemen. I de fall med en värmepump samt en återgående temperatur på 47°C i fjärrvärmenätet hade ett COP på 3.07 samt 3.15 för system A samt system B vardera. Kostanden att förvätska CO2 var 17.42 €/ton för system A samt 17.75 €/ton för system B utan använding av en värmepump samt en återgående temperatur på 47°C i fjärrvärmenätet. Vid integrering av en värmepump gick kostnaden av förvätskning upp till 20.85 €/ton för system A samt 21.69 €/ton för system B. Kostnaden av förvätskning dominerades av driftskostnader med kostnaden av kapitalet har en mindre påverkan. Utnyttjandegraden har även en stor påverkan på kostanden av förvätskning, då lägre kapaciteter visade sig leda till markant högre förvätskningskostnader. När intäkterna från fjärrvärmeproduktionen adderades till kostnadskalkylen, minskade kostnaden av förvätskning, speciellt för de system med en värmepump, där priset minskade till 10.26 €/ton för system A eller 10.98 €/ton för system B. I linje med tidigare studier pekar även dessa resultat på att det ekonomiska optimumet sammanfaller med energioptimum. Resultaten visade även att system A, det internt kylda systemet, hade den lägsta förvätskningskostanden och minsta elektricitetsförbrukningen med och utan värmepump, och därför är system A optimalt för småskalig CO2 förvätskning.<br>The aim of this study is to do a technoeconomical analysis on CO2 liquefaction systems using Aspen Plus. Several liquefaction systems from previous studies were compared, and from these, two liquefaction systems were chosen for further studies and simulations. These liquefaction systems were namely an internal liquefaction system and an external liquefaction system by Øi et al., Energy Procedia 86 (2016) 500-510, called system A and Seo et al., International Journal of Greenhouse Gas Control 35 (2015) 1-12, called system B. These systems were simulated for technical analysis using Aspen Plus, and Aspen Economical Analyzer (AEA) was used for economical studies. A small-scale liquefaction system was studied with a mass flow rate of 45 tonne/h including the water content, as compared to other studies with higher mass flow rates of around 100 tonne/h. The electricity demand and cooling demand were studied in several cases of interstage cooling between compressors. Furthermore, two cases of district heating as well as two cases of heat pumps were studied with varying return temperatures of the district heating water. This was done to study how much heat could be recovered from the liquefaction process. Furthermore, the capital expenses as well as the operating expenses were also determined using AEA. From this, the annual CAPEX and the cost of CO2 was calculated in terms of €/tonne CO2.  The results showed that district heating and heat pumps can be useful to recover heat from the liquefaction processes. The simulations that included a heat pump and assumed a return temperature of 47°C had a COP of 3.07 and 3.15 for system A and B respectively. The determined cost of production was 17.42 €/tonne for system A and 17.75 €/tonne for system B when not using a heat pump and a return temperature of 47°C in the district heating grid. However, when adding a heat pump the total production cost (TPC) increased to 20.85 €/tonne for system A, and 21.69 €/tonne for system B. It was also shown that the TPC is highly dominated by the operating expenses while the total capital investment has a smaller impact on the TPC. The capacity is also important for the TPC as lower capacities was shown to lead to significantly increased production costs. When taking the revenue streams from district heating into account the TPC was decreased, in particular for the systems including the heat pumps, where the TPC for system A was 10.26 €/tonne while for system B it was 10.98 €/tonne. In accordance with previous studies it was shown that the economical optimum is closely related to the energy optimum. It was concluded that as system A, the internal liquefaction system, had the lowest TPC and electricity input with and without the heat pump and thus it is the optimal configuration for small-scale CO2 liquefaction.

Gasification of petroleum coke (Petcoke) has emerged in the last decades as one of the attractive options and is gaining more attention to convert petcoke and oil residue to synthesis gas (Syngas). Syngas consists mainly of hydrogen (H2), carbon monoxide (CO), some other gases, and impurities. In this study, a simulation of Tuscaloosa petcoke, typical gulf coast refineries petcoke, gasification was developed using ASPEN PLUS software. Sensitivity analysis of the simulated model was performed to study the variation in operation conditions of the gasifier such as temperature, pressure, oxygen flow rate, and steam flow rate. The approach correlates the behavior of these parameters with the syngas yield (i.e., H2, CO, CO2, H2O, CH4, and H2S). Consequently, the desired syngas yield can be obtained by manipulating the gasifier parameters. Implementing optimization calculation shows that up to (81 %) of the gasifier cold gas efficiency (Based on LHV) can be achieved for the developed model. Therefore, Tuscaloosa petcoke gasification under the aforementioned parameters is feasible and can be commercialized. This leads to more utilization of the bottom of oil barrel by upgrading it to more valuable gases with less environmental impacts.

This project modelled a thermal liquefaction industrial facility for biofuel production from sugarcane bagasse using the process modelling software ASPEN Plus. Techno-economic models of liquefaction, pyrolysis and gasification processes were completed to assess the comparative feasibility of these thermochemical biofuel production processes. Model liquefaction biocrudes, were developed in ASPEN Plus using simulated distillation data and this method's utility in modelling biocrudes was validated.

The aim of this research was to produce an integrated modelling platform in which an anaerobic digester could be linked to the other unit operations which serve it, both in maintaining the physical-chemical conditions in the digester and in transforming the digestion products to useful fuel and nutrient sources. Within these system boundaries an accurate mass and energy balance could be determined and further optimised, particularly where the desired energy products are a mix of heat, power, and biomethane. The anaerobic digestion of food waste was choosen as the subject of the research because of its growing popularity and the availability of validation data. Like many other organic substrates, food waste is potentially a good source of renewable energy in the form of biogas through anaerobic digestion. A number of experimental studies have, however, reported difficulties in the digestion of this material which may limit the applicability of the process. These arise from the complexity of the biochemical processes and the interaction between the microbial groups that make up the anaerobic community. When using food waste there is a tendency to accumulate intermediate volatile fatty acid products, and in particular propionic acid, which eventually causes the pH to drop and the digester to fail. Two factors are important in understanding and explaining the changes in the biochemical process that leads to this condition. The first is due to the differential in sensitivity to free ammonia of the two biochemical pathways that lead to methane formation. The acetoclastic methanogenic route is inhibited at a lower concentration than the hydrogenotrophic route, and methane formation therefore occurs almost exclusively via acetate oxidation to CO2 and H2 at high free ammonia concentrations. The accumulation of propionic acid is thought to be because formate, a product of its degradation, cannot be converted to CO2 and H2 as the necessary trace elements to build a formate dehydrogenase enzyme complex are missing. The Anaerobic Digestion Model No. 1 (ADM1) was modified to reflect ammonia inhibition of acertoclastic methanogenesis and an acetate oxidation pathway was added. A further modification was included which allowed a 'metabolic switch' to operate in the model based on the availability of key trace elements. This operated through the H2 feedback inhibition route rather than creating a new set of equations to consider formate oxidation in its own right: the end result is, however, identical in modelling terms. With these two modifications ADM1 could simulate experimental observations from food waste digesters where the total ammoniacal nitrogen(TAN) concentration exceeded 4 gN l-1. Under these conditions acetate accumulation is first seen, followed by proprionate accumulation, but with the subsequent decrease in acetate until a critical pH is reached. The ADM1 model was implemented in MATLAB with these modifications incorporated. The second part of the research developed an energy model which linked ADM1 to the mechanical processes for biogas upgrading, Combined Heat and Power (CHP)production, and the digester mixing system. The energy model components were developed in the framework of the Aspen Plus modelling platform, with sub-units for processes not available in the standard Aspen Package being developed in Fortran, MS Excel or using the Aspen Simulation Workbook (ASW). This integration of the process components allows accurate sizing of the CHP and direct heating units required for an anaerobic digestion plant designed for fuel grade methane production. Based on the established model and its sub-modules, a number of case studies were developed. To this end the modified ADM1 was applied to mesophilic digestion of Sugar Beet Pulp to observe how the modified ADM1 responded to different substrate types. Secondly, to assess the capability of adding further mechanical processes the model was used to integrate and optimise single stage biogas upgrading. Finally, the digestion of food waste in the municipal solid waste stream of urban areas in Vietnam was considered.

In practice, distillation may be carried out by either of two methods. The first method is based on the production of vapor by boiling the liquid mixture to be separated and condensing the vapour without allowing any liquid to return to the still. Then, there is no reflux. The second method is based upon the return of part of the condensate to the still under such conditions that this returning liquid is brought into the intimate contact with the vapours on their way to the condenser. Either of these two methods may be conducted as a continuous or as a batch process, but the study of dynamics and control of the process is one of most important part of each process. Distillation is one of the commonly used separation technique in the chemical industries. The separation is based on differences in “volatilities” (tendencies to vaporize) among various chemical components. In a distillation column the more volatile, or lighter, components are removed from the top of the column, and the less volatile, or heavier, components are removed from the lower part of the column. Further Aspen Plus makes it easy to build and run the process simulation model by providing with a comprehensive system of the online process modelling. Process simulation allows one to predict the behaviour of a process by using basic engineering relationships, such as mass and energy balances, and phase and chemical equilibrium. Process simulation enables one to run many cases, conduct „what if‟ analysis and perform sensitivity analysis and optimization runs. With simulation one can design better plants and increase the profitability of the existing plants. Process simulation is helpful throughout the entire life of a process, from research and development through process design to production. This thesis studies the dynamics and control of distillation columns using Aspen Plus. In this thesis, simulation studies of the distillation column are presented. Steady-state simulations are being performed using Aspen Plus followed by Aspen Dynamic simulation. In the steady state simulation, it was tried to see the effect of changing the flow rate of the extractive distillation. And finding the optimum flow rate in the distillation column. Controllers are then implemented for controlling sump level, reflux level and feed flow rate. Furthermore, two strategies were used for controlling the purity of distillate product controlling the distillation column tray temperature where the maximum change of temperature is observed due to reboiler heat change and the purity of the product by using composition controller. The case study was an example taken from Aspen Plus (version 8.4v). In the example, there are two main streams enters the distillation column and phenol will be the stream one, and methyl cyclone hexane (MCH) and toluene mixer will enter the distillation column as the second stream. MCH has been distilled from the top of the column and the phenol and toluene the bottom product. With the latest Aspen Plus and Aspen Dynamics version V10 with operating under Windows 10, because of that, we will come across few compatibility issues in Aspen Dynamics mainly when it comes to MATLAB. Moreover, due to incompatibility MATLAB and Simulink were not tested for this process. In this study, Methyl Cyclo Hexane (MCH) been separated from Toluene by using Phenol as the third component in an extractive distillation column. And in Aspen Dynamics new controllers been developed to control the product Methyl Cyclo Hexane (MCH) purity by making adjusting the flow rate level of the Phenol. DMC controllers were tried to implement in the process to replaces the PI controller but fail attempt. All the PI controllers have been auto-tuned in Aspen Dynamics using it tool of the faceplates. Which given the best possible controller parameters to for the process. Therefore, all the controller’s other was able to reach its set-point expect the composition controller. The controllers were helping to achieve the maximum purity of the distillate stream. All the obtained results have been discussed and the Important guidelines been outlined and explained in the overall simulation. Most of the objective been achieved in this thesis.

The global fossil reserves are dwindling and there is need to find alternative sources of energy. With global warming in mind, some of the most commonly considered suitable alternatives include solar, wind, nuclear, geothermal and hydro energy. A common challenge with use of most alternative energy sources is ensuring continuity of supply, which necessitates the use of energy storage. Hydrogen has properties that make it attractive as an energy carrier. To efficiently store energy from alternative sources in hydrogen, several methods of hydrogen production are under study. Several literature sources show thermochemical cycles as having high potential but requiring further development. Using literature sources, an initial screening of thermochemical cycles was done to select a candidate thermochemical cycle. The copper–chlorine thermochemical cycle was selected due to its relatively low peak operating temperature, which makes it flexible enough to be connected to different energy sources. Once the copper–chlorine cycle was identified, the three main copper–chlorine cycles were simulated in Aspen Plus to examine which is the best configuration. Using experimental data from literature and calculating optimal conditions, flowsheets were developed and simulated in Aspen Plus. The simulation results were then used to determine the configuration with the most favourable energy requirements, cycle efficiency, capital requirements and product cost. Simulation results show that the overall energy requirements increase as the number of steps decrease from five–steps to three–steps. Efficiencies calculated from simulation results show that the four and five–step cycles perform closely with 39% and 42%, respectively. The three–step cycle has a much lower efficiency, even though the theoretical calculations imply that the efficiency should also be close to that of the four and five–step cycles. The five–step reaction cycle has the highest capital requirements at US$370 million due to more equipment and the three–step cycle has the lowest requirement at US$ 275 million. Payback analysis and net present value analysis indicate that the hydrogen costs are highest for the three–step cycle at between US$3.53 per kg for a 5–10yr payback analysis and the five–step cycle US$2.98 per kg for the same payback period.<br>Thesis (M.Ing. (Chemical Engineering))--North-West University, Potchefstroom Campus, 2012.

The present work investigates further development of a small-scale fixed bed batch operating gasification pilot system intended to be used as a waste-to-energy process to reduce littering of PET-bottles on Pemba Island in Tanzania. By developing a simplified gasification model and identifying the most important parameters to obtain a syngas with a lower heating value suitable for combustion and maximizing the overall efficiency and cold gas efficiency. By a literature study the most important parameters were identified along with how the methodology for developing the model and selection of modelling software. The model was developed as an equilibrium-based model in Aspen Plus representing the pilot system, the most important parameters was identified as equivalence ratio and temperature. Multiple scenarios, regarding sensitivity analysis of these parameters was conducted to determine how the outcome of the process was affected. The model was validated against a reference study and was proven to be accurate with small variations. High content of methane and carbon monoxide promoted the highest lower heating value which was at an equivalence ratio of 0.25 and a temperature of 450°C, which also indicated the highest overall efficiency. Increasing the temperature favoured the carbon monoxide content and the cold gas efficiency but indicated a decrease in lower heating value and overall efficiency. It was concluded that the optimal operational conditions were at an equivalence ratio at 0.25 and a temperature at 450°C. At these conditions, the formation of by-products from the gasification is higher than at higher equivalence ratios and temperature which needs to be further investigated through experimental work. It was also concluded that the system could benefit to operate in a semi- batch configuration with a higher equivalence ratio to utilize the excess heat from the process.

Master of Science<br>Department of Chemical Engineering<br>Larry Erickson<br>Oxy-fired boilers are receiving increasing focus as a potential response to reduced boiler emissions limits and greenhouse gas legislation. Among the challenges in cleaning boiler gas for sequestration is attaining the necessary purity of the CO[subscript]2. A key component in the oxy-fired cleaning path is high purity SO[subscript]x and NO[subscript]x removal, often through absorption using the lead-chamber or similar process. Aerosol formation has been found to be a source of product contamination in many flue gas absorption processes. A number of authors presented simulation methods to determine the formation of aerosols in gas absorption. But these methods are numerically challenging and not suitable for day-to-day analysis of live processes in the field. The goal of this study is to devise a simple and practical method to predict the potential for and effect of aerosol formation in gas absorption using information from Aspen Plus, a commonly used process simulation tool. The NO[subscript]x absorber in an oxy-fired boiler CO[subscript]2 purification system is used as a basis for this investigation. A comprehensive review of available data suitable for simulating NO[subscript]x absorption in an oxy-fired boiler slipstream is presented. Reaction rates for eight reactions in both liquid and vapor phases are covered. These are entered into an Aspen Plus simulation using a RadFrac block for both rate-based and equilibrium reactions. A detailed description of the simulation format is given. The resulting simulation was compared to a previously published simulation and process data with good agreement. An overall description of the aerosol formation mechanism is presented, along with an estimate of expected aerosol nuclei reaching the NO[subscript]x absorption process. A method to estimate aerosol quantities produced based on inlet gas nuclei concentration and available condensable water vapor is presented. To estimate aerosol composition and emissions, an exit gas slipstream is used to equilibrate with a pure water aerosol using an Aspen Plus Equilibrium Reactor block. Changing the composition of the initial aerosol feed liquid suggests that the location of aerosol formation may influence the final composition and emissions.