Relevant bibliographies by topics / Aspen Plus modeling

Academic literature on the topic 'Aspen Plus modeling'

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Published: 6 September 2023

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Journal articles on the topic "Aspen Plus modeling"

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Somers, C., A. Mortazavi, Y. Hwang, R. Radermacher, P. Rodgers, and S. Al-Hashimi. "Modeling water/lithium bromide absorption chillers in ASPEN Plus." Applied Energy 88, no. 11 (November 2011): 4197–205. http://dx.doi.org/10.1016/j.apenergy.2011.05.018.

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Zebert, Tristan Lee, David Lokhat, Swamy Kurella, and B. C. Meikap. "Modeling and simulation of ethane cracker reactor using Aspen Plus." South African Journal of Chemical Engineering 43 (January 2023): 204–14. http://dx.doi.org/10.1016/j.sajce.2022.11.005.

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Yan, H. M., and D. K. Zhang. "Modeling of a Low Temperature Pyrolysis Process Using ASPEN PLUS." Developments in Chemical Engineering and Mineral Processing 7, no. 5-6 (May 15, 2008): 577–91. http://dx.doi.org/10.1002/apj.5500070511.

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Hussain, Maham, Omer Ali, Nadeem Raza, Haslinda Zabiri, Ashfaq Ahmed, and Imtiaz Ali. "Recent advances in dynamic modeling and control studies of biomass gasification for production of hydrogen rich syngas." RSC Advances 13, no. 34 (2023): 23796–811. http://dx.doi.org/10.1039/d3ra01219k.

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Modeling strategies via Aspen Plus® for biomass gasification were assessed. Dynamic modeling can be essential in aiding control studies of biomass gasification process using Aspen Dynamics. Model predictive control is a widely recognized optimal controller for biomass gasification.
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Adeyemi, Idowu, and Isam Janajreh. "Modeling of the entrained flow gasification: Kinetics-based ASPEN Plus model." Renewable Energy 82 (October 2015): 77–84. http://dx.doi.org/10.1016/j.renene.2014.10.073.

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Kozlova, A. A., M. M. Trubyanov, A. A. Atlaskin, N. R. Yanbikov, and M. G. Shalygin. "Modeling Membrane Gas and Vapor Separation in the Aspen Plus Environment." Membranes and Membrane Technologies 1, no. 1 (January 2019): 1–5. http://dx.doi.org/10.1134/s2517751619010049.

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Jayawardhana, Kemantha, and G. Peter Van Walsum. "Modeling of Carbonic Acid Pretreatment Process Using ASPEN-Plus®." Applied Biochemistry and Biotechnology 115, no. 1-3 (2004): 1087–102. http://dx.doi.org/10.1385/abab:115:1-3:1087.

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Mutlu, Özge Çepelioğullar, and Thomas Zeng. "Challenges and Opportunities of Modeling Biomass Gasification in Aspen Plus: A Review." Chemical Engineering & Technology 43, no. 9 (July 12, 2020): 1674–89. http://dx.doi.org/10.1002/ceat.202000068.

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Mukhitdinov, Djalolitdin, Olim Sattarov, Abdumalik Akhmatov, Dildora Abdullayeva, and Elshod Bekchanov. "Computer simulation and optimization of the oxidation process in the production of nitric acid in the Aspen Plus environment." E3S Web of Conferences 417 (2023): 05004. http://dx.doi.org/10.1051/e3sconf/202341705004.

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The article presents a method for determining the optimal technological and design parameters of the process, as well as the procedure for conducting technological analysis in the Aspen Plus environment. With the help of a wide range of thermodynamic models and process property databases, this modeling environment allows for an accurate representation of their behavior in the production of nitric acid. By using computer modeling in Aspen Plus, a 60.09% aqueous solution of HNO3 was obtained for 93465.8 kg/h of air and 5458.9 kg/h of ammonia. The objective of this modeling was to determine the optimal process parameters and its configuration, conduct a technological analysis, and determine the flows and properties of substances at various points. The main process parameters were analyzed, and their interrelation is shown in the graphs.
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Sharifian, Seyedmehdi, Michael Harasek, and Bahram Haddadi. "Simulation of Membrane Gas Separation Process Using Aspen Plus® V8.6." Chemical Product and Process Modeling 11, no. 1 (March 1, 2016): 67–72. http://dx.doi.org/10.1515/cppm-2015-0067.

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Abstract Implementing membrane gas separation systems have led to remarkable profits in both processes and products. This study presents the modeling and simulation of membrane gas separation systems using Aspen Plus® V8.6. A FORTRAN user model and a numerical solution procedure have been developed to characterize asymmetric hollow fiber membrane modules. The main benefit of this model is that it can be easily incorporated into a commercial simulator and used as a unit operation model in complex systems. A comparison between the model and the experimental cases at different operation conditions shows that calculated values are in good agreement with measured values. This model is suitable for future developments as well as design and performance analysis of multicomponent gas permeation systems prior to experimental realization.
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Dissertations / Theses on the topic "Aspen Plus modeling"

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Salih, Saif Yoseif. "THE MODELING OF PETROLEUM COKE GASIFICATION USING ASPEN PLUS SOFTWARE." OpenSIUC, 2015. https://opensiuc.lib.siu.edu/theses/1777.

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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.
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Abu, Bakar Nurul Atiqah. "Modeling, optimizing and control analysis of a debutanizer column using Aspen Plus and Aspen Dynamic." Thesis, Abu Bakar, Nurul Atiqah (2017) Modeling, optimizing and control analysis of a debutanizer column using Aspen Plus and Aspen Dynamic. Honours thesis, Murdoch University, 2017. https://researchrepository.murdoch.edu.au/id/eprint/41926/.

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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.
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Smestad, Haley Hayden. "Modeling of an Ethanol - Water- LiBr Ternary System for the Simulation of Bioethanol Purification using Pass-Through Distillation." Digital WPI, 2016. https://digitalcommons.wpi.edu/etd-theses/452.

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Accurate modeling of mixed solvent electrolyte systems is difficult and is not readily available in property modeling software such as Aspen Plus. Support for modeling these systems requires the knowledge and input of parameters specific to the compounds in question. The need for these parameters is particularly relevant in simulating new designs based upon recent developments in a concept known as pass-through distillation (PTD). In support of a specific application of PTD, this work determines and validates with existing experimental data, accurate user-parameters for the eNRTL property model in the ternary system of ethanol, water, and lithium bromide. Furthermore, this work creates the foundation for simulating this new PTD process by modeling the removal of bioethanol from a fermentation broth using low temperature evaporation in conjunction with absorption and stripping units to omit the need of a condenser requiring refrigeration. This will enable future investigations into the applications of PTD as well as provide a foundation for modeling the ternary system of ethanol, water and lithium bromide.
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Afanga, Khalid. "Modélisation systémique des filières sidérurgiques en vue de leur optimisation énergétique et environnementale." Thesis, Université de Lorraine, 2014. http://www.theses.fr/2014LORR0268/document.

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Ce travail de recherche porte sur la modélisation mathématique des principaux procédés sidérurgiques en suivant une approche systémique. L’objectif est d’élaborer un outil de modélisation de l’ensemble de la filière destiné à l’optimiser du point de vue énergétique et environnemental. Nous avons développé des modèles physico-chimiques du haut fourneau, de la cokerie, de l’agglomération et du convertisseur. Ces modèles ont ensuite été reliés entre eux sous forme d’un diagramme de flux unique en utilisant le logiciel ASPEN Plus. Dans une première partie, nous nous sommes particulièrement intéressés au haut fourneau à recyclage, une variante innovante du haut fourneau dans laquelle les gaz de gueulard sont recyclés et réinjectés aux tuyères après capture du CO2. Nous avons testé une réinjection à un niveau (aux tuyères) et à deux niveaux (tuyères et ventre). Les résultats ont été comparés avec succès à des données expérimentales issues d’un réacteur pilote et montrent que le recyclage permet une baisse de plus de 20 % des émissions de CO2 du haut fourneau. Le recyclage à deux niveaux ne semble pas plus performant que celui à un seul niveau. Dans un deuxième temps, nous avons simulé le fonctionnement d’une usine sidérurgique intégrée dans son ensemble. Différentes configurations ont été testées, pour un haut fourneau classique ou un haut fourneau à recyclage, en considérant un éventuel recyclage du laitier de convertisseur à l’agglomération, et en étudiant l’influence de la teneur en silicium de la fonte sur toute la filière. On montre notamment qu’il est possible de réduire le prix de revient de la tonne d’acier en substituant et recyclant différents sous-produits
This research study deals with mathematical modeling of the main steelmaking processes following a systems approach. The objective was to build a modeling tool of the whole steelmaking route devoted to its energetic and environmental optimization. We developed physical-chemical models for the blast furnace, the coke oven, the sintering plant and the basic oxygen furnace. These models were then linked together in a single flow sheet using the ASPEN Plus software. First, we focused on the top gas recycling blast furnace, a novel variant of the blast furnace in which the top gas is recycled and re-injected into the tuyeres after CO2 removal and capture. We tested both a reinjection at one level (tuyeres only) and at two levels (tuyeres and shaft). The results were successfully compared with experimental data from a pilot reactor and demonstrate that recycling can lower the blast furnace CO2 emissions by more than 20%. Recycling at two levels does not seem more efficient than at a single level. Second, we simulated the operation of an entire integrated steelmaking plant. Different configurations were tested, using a conventional blast furnace or a top gas recycling blast furnace, considering a possible recycling of the converter slag to the sintering plant, and studying the influence of Si content in the hot metal on the entire steelmaking plant operation. We show that it is possible to reduce the cost of producing steel by substituting and recycling various by-products
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Hedström, Sofia. "Thermal energy recovery of low grade waste heat in hydrogenation process." Thesis, Karlstads universitet, Fakulteten för hälsa, natur- och teknikvetenskap (from 2013), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-32335.

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The waste heat recovery technologies have become very relevant since many industrial plants continuously reject large amounts of thermal energy during normal operation which contributes to the increase of the production costs and also impacts the environment. The simulation programs used in industrial engineering enable development and optimization of the operational processes in a cost-effective way. The company Chematur Engineering AB, which supplies chemical plants in many different fields of use on a worldwide basis, was interested in the investigation of the possibilities for effective waste heat recovery from the hydrogenation of dinitrotoluene, which is a sub-process in the toluene diisocyanate manufacture plant. The project objective was to implement waste heat recovery by application of the Organic Rankine Cycle and the Absorption Refrigeration Cycle technologies. Modeling and design of the Organic Rankine Cycle and the Absorption Refrigeration Cycle systems was performed by using Aspen Plus® simulation software where the waste heat carrier was represented by hot water, coming from the internal cooling system in the hydrogenation process. Among the working fluids investigated were ammonia, butane, isobutane, propane, R-123, R-134a, R-227ea, R-245fa, and ammonia-water and LiBr-water working pairs. The simulations have been performed for different plant capacities with different temperatures of the hydrogenation process. The results show that the application of the Organic Rankine Cycle technology is the most feasible solution where the use of ammonia, R-123, R-245fa and butane as the working fluids is beneficial with regards to power production and pay-off time, while R-245fa and butane are the most sustainable choices considering the environment.
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François, Jessica. "Modélisation et évaluation environnementale des filières de cogénération par combustion et gazéification du bois." Thesis, Université de Lorraine, 2014. http://www.theses.fr/2014LORR0071/document.

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Le développement du bois énergie est un des principaux leviers dans la lutte contre le changement climatique. Cependant son utilisation à grande échelle n’est pas sans risque pour l’environnement. Afin de quantifier les impacts environnementaux de la filière bois énergie, nous avons, dans un premier temps, développé un modèle systémique de la filière, depuis la forêt jusqu’à la production d’énergie. Deux technologies ont été considérées pour la co-production d’électricité et de chaleur à partir de biomasse forestière : l’une, traditionnelle, par combustion directe, et l’autre, plus avancée mais moins mature, par gazéification. Dans le cas de la gazéification, nous avons défini les conditions opératoires les plus favorables du procédé en tenant compte des rendements énergétiques et exergétiques ainsi que de la qualité du syngas. Dans un deuxième temps, nous avons calculé les flux de carbone et de minéraux exportés lors de la récolte du bois ainsi que le nombre d’hectares requis, puis les ressources et rejets liées au fonctionnement des centrales biomasses. Nous avons noté qu’une intensification des pratiques sylvicoles résultait en une augmentation des exportations de minéraux. Enfin, nous avons évalué les performances environnementales des deux filières à l’aide d’une Analyse de Cycle de Vie (ACV). Dans le contexte énergétique français, les deux systèmes offrent des performances très similaires, avec un léger avantage à la combustion. Du point de vue du changement climatique, il serait plus particulièrement bénéfique de développer ces procédés biomasse afin de remplacer les technologies de production d’énergie basées sur les combustibles fossiles
Biomass is one of the most promising renewable energy source in Europe. Its use as a substitute to fossil energy is expected to mitigate climate change. However, potential drawbacks are also feared with large scale development. In order to assess the environmental impacts of the biomass-to-energy chain, we firstly developed a model of the bioenergy system, from the forest to the energy production. We focused on two biomass power plants for combined heat and power (CHP) production: one is based on the conventional direct combustion process while the other is based on the more advanced gasification process. Gasification offers higher electrical efficiency, but its development is still facing technical difficulties. In case of the gasification process, we defined the best operating conditions regarding energetic and exergetic efficiencies, as well as the syngas quality requirements. Secondly, we calculated the carbon and mineral flows taken from the forest through energy wood harvesting, along with the forested area required to feed the CHP plant. The other resources and emissions related to the plant operation were also predicted. We observed that more extensive forestry practices led to an increase in the mineral exports. Finally, we evaluated the environmental performance of the two biomass CHP plants using life cycle assessment (LCA). Within French energy context, we found that both CHP technologies had very similar impacts with a slight advantage toward the combustion process. It appears of particular benefit to replace current fossil energy systems with biomass CHP plants to reduce climate change
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Higgins, Stuart James. "Design and Optimization of Post-Combustion CO2 Capture." Diss., Virginia Tech, 2016. http://hdl.handle.net/10919/80003.

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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.
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Ramirez, Jerome Luigi A. "Modelling a commercial-scale bagasse liquefaction plant using ASPEN Plus." Thesis, Queensland University of Technology, 2018. https://eprints.qut.edu.au/120019/1/Jerome_Ramirez_Thesis.pdf.

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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.
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Nguyen, Hoa Huu. "Modelling of food waste digestion using ADM1 integrated with Aspen Plus." Thesis, University of Southampton, 2014. https://eprints.soton.ac.uk/375082/.

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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.
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Olofsson, Fanny, and Henrik Halvarsson. "SMALL SCALE ENERGY CONVERSION OF PLASTIC WASTE : Identification of gasification process parameters through modelling in Aspen Plus." Thesis, Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-49162.

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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.
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Books on the topic "Aspen Plus modeling"

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Cheung, Miranda. Modelling of the nickel and cobalt kinetics during pressure acid leaching of laterites using Aspen Plus 11.1TM and OLI. 2004.

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Book chapters on the topic "Aspen Plus modeling"

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Madeddu, Claudio, Massimiliano Errico, and Roberto Baratti. "Process Modeling in Aspen Plus®." In SpringerBriefs in Energy, 13–30. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-04579-1_2.

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Jayawardhana, Kemantha, and G. Peter Van Walsum. "Modeling of Carbonic Acid Pretreatment Process Using ASPEN-Plus®." In Proceedings of the Twenty-Fifth Symposium on Biotechnology for Fuels and Chemicals Held May 4–7, 2003, in Breckenridge, CO, 1087–102. Totowa, NJ: Humana Press, 2004. http://dx.doi.org/10.1007/978-1-59259-837-3_88.

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Adeyemi, Idowu A., and Isam Janajreh. "Detailed Kinetics-Based Entrained Flow Gasification Modeling of Utah Bituminous Coal and Waste Construction Wood Using Aspen Plus." In ICREGA’14 - Renewable Energy: Generation and Applications, 607–22. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-05708-8_49.

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Hantoko, Dwi, Mi Yan, Bayu Prabowo, Herri Susanto, Xiaodong Li, and Chong Chen. "Aspen Plus Modeling Approach in Solid Waste Gasification." In Current Developments in Biotechnology and Bioengineering, 259–81. Elsevier, 2019. http://dx.doi.org/10.1016/b978-0-444-64083-3.00013-0.

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Cormos, Ana-Maria, Calin-Cristian Cormos, and Paul Ş. Agachi. "Making soda ash manufacture more sustainable. A modeling study using ASPEN Plus." In Computer Aided Chemical Engineering, 551–56. Elsevier, 2007. http://dx.doi.org/10.1016/s1570-7946(07)80115-5.

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Sadhwani, Narendra, Pengcheng Li, Mario R. Eden, and Sushil Adhikari. "Process Modeling of Fluidized Bed Biomass-CO 2 Gasification using ASPEN Plus." In Computer Aided Chemical Engineering, 2509–14. Elsevier, 2017. http://dx.doi.org/10.1016/b978-0-444-63965-3.50420-7.

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Marchesan, Andressa Neves, Ingrid Lopes Motta, Rubens Maciel Filho, and Maria Regina Wolf Maciel. "Modeling the hydrodynamic sizing and rating of reactive packing in Aspen Plus." In Computer Aided Chemical Engineering, 313–18. Elsevier, 2022. http://dx.doi.org/10.1016/b978-0-323-95879-0.50053-9.

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J. Sanchez-Ruiz, Francisco. "Reactive Distillation Modeling Using Artificial Neural Networks." In Distillation Processes - From Solar and Membrane Distillation to Reactive Distillation Modelling, Simulation and Optimization. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.101261.

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The use of artificial intelligence techniques in the design of processes has generated a line of research of interest, in areas of chemical engineering and especially in the so-called separation processes, in this chapter the combination of artificial neural networks (ANN) is presented and fuzzy dynamic artificial neural networks (DFANN). Applied to the calculation of thermodynamic properties and the design of reactive distillation columns, the ANN and DFANN are mathematical models that resemble the behavior of the human brain, the proposed models do not require linearization of thermodynamic equations, models of mass and energy transfer, this provides an approximate and tight solution compared to robust reactive distillation column design models. Generally, the models must be trained according to a dimensionless model, for the design of a reactive column a dimensionless model is not required, it is observed that the use of robust models for the design and calculation of thermodynamic properties give results that provide better results than those calculated with a commercial simulator such as Aspen Plus (R), it is worth mentioning that in this chapter only the application of neural network models is shown, not all the simulation and implementation are presented, mainly because it is a specialized area where not only requires a chapter for its explanation, it is shown that with a neural network of 16 inputs, 2 hidden layers and 16 outputs, it generates a robust calculation system compared to robust thermodynamic models that contain the same commercial simulator, a characteristic of the network presented is the minimization of overlearning in which the network by its very nature is low. In addition, it is shown that it is a dynamic model that presents adjustment as a function of time with an approximation of 96–98% of adjustment for commercial simulator models such as Aspen Plus (R), the DFANN is a viable alternative for implementation in processes of separation, but one of the disadvantages of the implementation of these techniques is the experience of the programmer both in the area of artificial intelligence and in separation processes.
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Othman, Mohamad Rizza, Sivanesh Kumar Anpalagam, and Nur Fitriyanni Jafary. "Modeling and Analysis of Clinical & Municipal Waste Incineration Process using Aspen Plus." In Computer Aided Chemical Engineering, 101–6. Elsevier, 2023. http://dx.doi.org/10.1016/b978-0-443-15274-0.50017-2.

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B. Dehankar, Prashant. "Assessment of Augmentation Techniques to Intensify Heat Transmission Power." In Heat Exchangers. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.101670.

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The heat exchanger detects heat between two processes of liquids in the chemical, petrochemical, food, beverage, and hot metals, and so on. Although the required heat transfer calculations and pressure reductions are achieved with a two-pipeline temperature switch (DPHE), the optimization of the heat transfer parameter is used to measure laboratory test settings. This will allow you to build a DPHE model with twisted tapes and mimic the ASPEN PLUS and work it out by trying to scale the lab that has already been produced and standardized for DPHE. Parameter values for this study range from 0.02 kg / sec −0.033 kg / sec as suspension, pressure reduction, and Reynolds numbers. Also to study the mechanism of increased heat transfer by the use of twisted tape with Y1 = 4.3 and Y2 = 7.7 deviations. They are trying to compare the results of a mathematical model with simulation. This mode of inactivity has the effect of equilibrium heat transfer, pressure drop, the collision factor, and the number Reynolds. We tested the modeling and simulation effects and tried to measure the 4 input parameters of the two output parameters: cold flow rate, hot flow rate, cold and cold temperatures. DPHE, therefore, confirmed the flow rates of weight between 0.02–0.07 kg/s with experiments and simulations performed by Aspen Plus.
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Conference papers on the topic "Aspen Plus modeling"

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Bloomingburg, G. F., J. M. Simonson, R. C. Moore, H. D. Cochran, and R. E. Mesmer. "AQUEOUS ELECTROLYTE MODELING IN ASPEN PLUS." In Physical Chemistry of Aqueous Systems: Meeting the Needs of Industry. Connecticut: Begellhouse, 2023. http://dx.doi.org/10.1615/icpws-1994.630.

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Haji, Shaker, Omar Al Deeb, and Ashraf Hassan. "Optimizing a methanol reactor in Aspen Plus." In 2019 8th International Conference on Modeling Simulation and Applied Optimization (ICMSAO). IEEE, 2019. http://dx.doi.org/10.1109/icmsao.2019.8880381.

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Dronov, Stanislav A., Alexander V. Fedyukhin, Daniil V. Semin, Aleksei S. Malenkov, and Aleksei G. Gusenko. "Mathematical modeling of methane-hydrogen fuel combustion processes in Aspen Plus." In 2023 5th International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE). IEEE, 2023. http://dx.doi.org/10.1109/reepe57272.2023.10086881.

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Cheng, Ming, Matthew Hodges, Kenny Kwan, Hsuan-Tsung Hsieh, Yitung Chen, George Vandegrift, Jackie Copple, and James Laidler. "An Object-Oriented Systems Engineering Model Design for Integrating Spent Fuel Treatment Facility and Chemical Separation Processes." In ASME 2006 International Mechanical Engineering Congress and Exposition. ASMEDC, 2006. http://dx.doi.org/10.1115/imece2006-15885.

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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. TRPSEMPro package, developed from previous project period, integrated a chemical separation code from the Argonne National Laboratories (ANL). Current research focus has two folds: development of simulation system processes applied to Spent Fuel Treatment Facility (SFTF) using ASPEN-plus and further interaction of ASPEN+ program from TRPSEMPro interface. More details will be discussed below. ANL has identified three processes simulations using their separation technologies. The first process is to separate aqueous acid streams of acetic acid, nitric acid, water and a variety of fission product nitric salts. Distillation separation method is used to remove the desired components from the streams. The second simulation is to convert plutonium nitrate to plutonium metal. Steps used for the process simulation are precipitation, calcinations, fluorination and reduction. The third process currently under development is vitrification of fission product of raffinate streams. During the process, various waste streams from the plant are mixed and fed to a process that converts them to a solid state glass phase. The vitrification process used by the Hanford and Savannah River facilities was selected as a guideline to develop the prototype simulation process using ASPEN-Plus. Current research is focusing on identifying unit operations required to perform the vitrification of the waste streams. The first two processes are near completion stage. Microsoft Visual Basic (MS VB) has been used to develop the entire system engineering model package, TRPSEMPro. Currently a user friendly interface is under development to facilitate direct execution of ASPEN-plus within TRPSEMPro. The major purpose for the implementation is to create iterative interaction among system engineering modeling, ANL separation model and ASPEN-Plus process that outputs optimized separation/process simulation results. The ASPEN-plus access interface from TRPSEMPro allows users to modify and execute process parameters derived from the ASPEN Plus simulations without navigating through ASPEN-Plus. All ASPEN-plus simulation results can be also accessible by the interface. Such integration provide a single interaction gateway for researchers interested in SFTF process simulation without struggling with complicate data manipulation and joggling among various software packages.
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Wang, Zhiyuan, and Chao Zhang. "Energy Efficiency Analysis of Ultra-Supercritical Thermal Power Plant Based on Aspen Plus Modeling." In 2023 International Conference on Power Energy Systems and Applications (ICoPESA). IEEE, 2023. http://dx.doi.org/10.1109/icopesa56898.2023.10141439.

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Yuan, Bin, Ao Wang, Yun Feng Liu, and Yuan Ting Peng. "Modeling and Numerical Simulation of Hydrogen Production by Diesel Reforming Based on ASPEN PLUS." In 2022 6th International Conference on Green Energy and Applications (ICGEA). IEEE, 2022. http://dx.doi.org/10.1109/icgea54406.2022.9791872.

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Dong, Zhihui, Changqing Dong, Junjiao Zhang, and Yongping Yang. "Modeling the Combustion of Coal in a 300MW Circulating Fluidized Bed Boiler with Aspen Plus." In 2010 Asia-Pacific Power and Energy Engineering Conference. IEEE, 2010. http://dx.doi.org/10.1109/appeec.2010.5448266.

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Kolodney, Matthew, and Bruce C. Conger. "Integrated Model of G189A and Aspen-Plus for the Transient Modeling of Extravehicular Activity Atmospheric Control Systems." In International Conference On Environmental Systems. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 1990. http://dx.doi.org/10.4271/901268.

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Giorgetti, Simone, Diederik Coppitters, Francesco Contino, Ward De Paepe, Laurent Bricteux, Gianmarco Aversano, and Alessandro Parente. "Surrogate-Assisted Modeling and Robust Optimization of a Micro Gas Turbine Plant With Carbon Capture." In ASME Turbo Expo 2019: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/gt2019-91400.

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Abstract The growing share of wind and solar power in the total energy mix has caused severe problems in balancing the electrical power production. Consequently, in the future, all fossil fuel-based electricity generation will need to be run on a completely flexible basis. Micro Gas Turbines (mGTs) constitutes a mature technology which can offer such flexibility. Even though their greenhouse gas emissions are already very low, stringent carbon reduction targets will require them to be completely carbon neutral: this constraint implies the adoption of post-combustion Carbon Capture (CC) on these energy systems. To reduce the CC energy penalty, Exhaust Gas Recirculation (EGR) can be applied to the mGTs increasing the CO2 content in the exhaust gas and reducing the mass flow rate of flue gas to be treated. As a result, a lower investment and operational cost of the CC unit can be achieved. In spite of this attractive solution, an in-depth study along with a robust optimization of this system has not yet been carried out. Hence, in this paper, a typical mGT with EGR has been coupled with an amine-based CC plant and simulated using the software Aspen Plus®. A rigorous rate-based simulation of the CO2 absorption and desorption in the CC unit offers an accurate prediction; however, its time complexity and convergence difficulty are severe limitations for a stochastic optimization. Therefore, a surrogate-based optimization approach has been used, which makes use of a Gaussian Process Regression (GPR) model, trained using the Aspen Plus® data, to quickly find operating points of the plant at a very low computational cost. Using the validated surrogate model, a robust optimization using a Non-dominated Sorting Genetic Algorithm II (NSGA II) has been carried out, assessing the influence of each input uncertainty and varying several design variables. As a general result, the analysed power plant proves to be intrinsically very robust, even when the input variables are affected by strong uncertainties.
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Cujia, Gabriel, Antonio Bula, Alberto Mercado, and Jorge Mendoza. "Modeling and Simulation of Syngas Produced From Biomass Gasification Enriched With Solar Hydrogen." In ASME 2009 3rd International Conference on Energy Sustainability collocated with the Heat Transfer and InterPACK09 Conferences. ASMEDC, 2009. http://dx.doi.org/10.1115/es2009-90056.

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Biomass gasification process is simulated in order to determine the influence of the operating parameters on the quality of the gas produced. Furthermore, the hydrogen required to enrich the syngas is also established. The modeling and simulation showed that the gas obtained by gasification at atmospheric pressure is mainly composed of H2 and CO; however, the molar ratio H2/CO is not favorable for synthesizing fuels such as methanol. This shows the need to enrich the syngas with additional hydrogen. For the case study developed, for each 100 kg / hr of biomass waste gasified, the amount of additional hydrogen required ranges between 2 to 6 kg / hr in order to obtain a molar ratio H2/CO close to 2. Using palm fiber, the amount of hydrogen required would be 4 kg / hr. This additional hydrogen could be derived from solar energy using thermoelectric modules with an effective area of solar radiation close to 400 m2 per kg of biomass. The simulation was performed using ASPEN PLUS®.
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