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Статті в журналах з теми "Aspen Plus modeling"

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Автор: Grafiati

Опубліковано: 6 вересня 2023

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1

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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2

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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3

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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4

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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Анотація:

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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5

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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6

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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7

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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8

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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9

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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10

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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11

Bai, Jing Ru, Zhang Bai, Shao Hua Li, and Qing Wang. "Modeling of an Oil Shale Low Temperature Retorting Process by Using Aspen Plus." Advanced Materials Research 608-609 (December 2012): 1459–62. http://dx.doi.org/10.4028/www.scientific.net/amr.608-609.1459.

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In this paper, the feasibility of employing Aspen Plus in the simulation of oil shale retorting would be discussed by modeling of a low temperature retorting process with fischer assay experimental condition. The samples of 4th layer of No.1 deposit and 11th layer of No.2 deposit of Huadian oil shale have been simulated, and draw a comparison between the simulation and determination results of oil content, moisture content, retorting gas yield, semi-coke yield and ultimate analysis. The tolerance between the simulation and determination results is within a reasonable range, which indicate that the process built and the physical method selected are correct and reasonable and would provide reference for building the process of oil shale comprehensive utilization system.

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12

Ahmed, Reem, and Mohan Sinnathambi Chandra. "Equilibrium Modeling in Updraft Gasifier for Refinery Sludge Gasification Using ASPEN PLUS Simulator." Applied Mechanics and Materials 393 (September 2013): 729–34. http://dx.doi.org/10.4028/www.scientific.net/amm.393.729.

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The production of refinery sludge has been increasing during tank cleaning, deslugging, and wastewater treatment process. Many efforts have been done to manage the large amount of generated sludge. The gasification of sludge is the most versatile alternative or /and is one potential treatment process for power generation and syngas production. The thermodynamic of gasifier is still not well understood for refinery sludge feedstock. As far as optimising the operational conditions of gasification process is concerned, a successful simulated work is introduced by making use of ASPEN PLUS software simulator. This software was tailored and developed to describe an equilibrium model in updraft gasifier of dry refinery sludge (DRS). The textural characteristic properties of refinery sludge are shown in this paper (ultimate and proximate analysis). In the present study four parameters ( i.e. oxidation zone temperature, operating pressure, air flow rate (l/min) and equivalent ratio) were analyzed. In the present work, details of the equilibrium model are presented. This model shows a better agreement with literature model for biomass gasification. From our model results, the mass fractions yield of the desired products (CO and H2) increases as the oxidation zone temperature increases while their yield decreases after 3 bar. The desired products are found to decrease as the air flow increases while CO2 mass fraction favors high air/fuel ratio. The model results are validated by comparison with experimental data issued from the literature.

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13

Abdelouahed, L., O. Authier, G. Mauviel, J. P. Corriou, G. Verdier, and A. Dufour. "Detailed Modeling of Biomass Gasification in Dual Fluidized Bed Reactors under Aspen Plus." Energy & Fuels 26, no. 6 (June 12, 2012): 3840–55. http://dx.doi.org/10.1021/ef300411k.

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14

Hasan, M. M., M. G. Rasul, M. I. Jahirul, and M. M. K. Khan. "Modeling and process simulation of waste macadamia nutshell pyrolysis using Aspen Plus software." Energy Reports 8 (December 2022): 429–37. http://dx.doi.org/10.1016/j.egyr.2022.10.323.

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15

Vaquerizo, Luis, and María José Cocero. "CFD–Aspen Plus interconnection method. Improving thermodynamic modeling in computational fluid dynamic simulations." Computers & Chemical Engineering 113 (May 2018): 152–61. http://dx.doi.org/10.1016/j.compchemeng.2018.03.019.

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16

Han, Jun, Yan Liang, Jin Hu, Linbo Qin, Jason Street, Yongwu Lu, and Fei Yu. "Modeling downdraft biomass gasification process by restricting chemical reaction equilibrium with Aspen Plus." Energy Conversion and Management 153 (December 2017): 641–48. http://dx.doi.org/10.1016/j.enconman.2017.10.030.

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17

Queiroz, João A., Vitor M. S. Rodrigues, Henrique A. Matos, and F. G. Martins. "Modeling of existing cooling towers in ASPEN PLUS using an equilibrium stage method." Energy Conversion and Management 64 (December 2012): 473–81. http://dx.doi.org/10.1016/j.enconman.2012.03.030.

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18

Cecílio, Duarte M., J. Ricardo M. Gonçalves, Maria Joana Neiva Correia, and Maria Margarida Mateus. "Aspen Plus® Modeling and Simulation of an Industrial Biomass Direct Liquefaction Process." Fuels 4, no. 2 (May 26, 2023): 221–42. http://dx.doi.org/10.3390/fuels4020014.

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The current energy and climate crisis calls for immediate action in replacing fossil fuels with those derived from renewable sources. The Energreen process performs the direct liquefaction of biomass to produce a liquid biofuel for the cement industry and an aqueous solution of added-value compounds for further processing. The present work details the development of an Aspen Plus® model to simulate this biomass liquefaction process. The proposed model describes the Energreen liquefaction process using simplified reaction kinetics and thermodynamic models. The model was validated using data from a real liquefaction pilot plant with a deviation of 6.4%. The simulation, conducted with several biomass samples of variable compositions, showed that the process is robust enough to deal with different compositions and, due to the substitution of the fossil fuels presently used in the cement plant, it will allow savings of up to USD 102,000 per year to be achieved. Several analyses of the sensitivity of the results to the process variables were performed and it was possible to identify the reactor temperature and the reaction activation energy as the most impactful parameters on the process output. Overall, the results allow us to conclude that the proposed model is a solid framework for the optimization of industrial liquefaction processes.

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19

Jiao, Liguo, Jian Li, Beibei Yan, Guanyi Chen, and Sarwaich Ahmed. "Microwave torrefaction integrated with gasification: Energy and exergy analyses based on Aspen Plus modeling." Applied Energy 319 (August 2022): 119255. http://dx.doi.org/10.1016/j.apenergy.2022.119255.

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20

Ismail, Hamza Y., Ali Abbas, Fouad Azizi, and Joseph Zeaiter. "Pyrolysis of waste tires: A modeling and parameter estimation study using Aspen Plus®." Waste Management 60 (February 2017): 482–93. http://dx.doi.org/10.1016/j.wasman.2016.10.024.

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21

Ahmed, A. M. A., A. Salmiaton, T. S. Y. Choong, and W. A. K. G. Wan Azlina. "Review of kinetic and equilibrium concepts for biomass tar modeling by using Aspen Plus." Renewable and Sustainable Energy Reviews 52 (December 2015): 1623–44. http://dx.doi.org/10.1016/j.rser.2015.07.125.

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22

Tamnitra, Rujiroj, Rujira Jitwung, Tarawipa Puangpetch, Weerawat Patthaveekongka, and Kamonrat Leeheng. "Kinetic modeling and simulation of bio-methanol process from biogas by using aspen plus." MATEC Web of Conferences 192 (2018): 03030. http://dx.doi.org/10.1051/matecconf/201819203030.

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A process of bio-methanol from biogas was studied by modifying kinetic model of reaction’s Richardson and Paripatyadar comparing with laboratory data. Bio-methanol process consists of 2 steps: reforming reaction (at atmospheric pressure, temperature 500 - 750 °C) and methanol synthesis (at constant pressure 40 bar, temperature 140 - 280 °C). The reaction model of each step was individual simulated. Next both steps were integrated, then they were simulated using ASPEN PLUS software. This work investigated the optimum operating condition and predicted result of both reactions. The developing model was obtained, then it was applied for ten thousand liters per day of methanol. The simulation result received from reforming reaction showed increasing temperature effect to rising in CH4 and CO2 conversion and relating with laboratory result. The optimum condition of methanol synthesis is temperature 200 °C under constant pressure 40 bar.

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23

Gulied, Mona, Ahmed Al Nouss, Majeda Khraisheh, and Fares AlMomani. "Modeling and simulation of fertilizer drawn forward osmosis process using Aspen Plus-MATLAB model." Science of The Total Environment 700 (January 2020): 134461. http://dx.doi.org/10.1016/j.scitotenv.2019.134461.

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24

Cekovic, Ivana, Nebojsa Manic, Dragoslava Stojiljkovic, Marta Trninic, Dusan Todorovic, and Aleksandar Jovovic. "Modelling of wood chips gasification process in ASPEN Plus with multiple validation approach." Chemical Industry and Chemical Engineering Quarterly 25, no. 3 (2019): 217–28. http://dx.doi.org/10.2298/ciceq180709034c.

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A thermochemical equilibrium model is formulated for wood chips downdraft gasification. Steady state ASPEN Plus simulator was utilized to evaluate producer gas composition and low heating value. Three cases are considered, due to mathematical model developed issues, and described in details. Experimental work was carried out within commercial small-scale CHP system where twelve beech wood samples were taken. Equivalence ratio is between 0.32 and 0.38 and air-fuel ratio ranges from 1.49 to 1.81, when gasifier capacity is optimal, at 250 kW. Mole fractions of CO2, H2, CO, CH4 and N2, in dry producer gas, are respectively, 16.06-17.64, 17.98-20.33, 13.71-17.26, 1.65-2.89 and 43.21-48.36. Multiple validation approach was applied for model verification. The results are in reasonable agreement with different literature sources (experimental work and modeling) and in a great agreement with the modified equilibrium model developed in Engineering Equation Solver found in the literature. Result deviations are explained by two major facts: wood downdraft gasification experiments are to a certain extent different and the model parameters could not be adjusted enough to fully minimize differences between model results. Predicted low heating value of dry producer gas is between 4.67-5.61 MJ/Nm3.

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25

Saleh, A. R., B. Sudarmanta, S. Mujiarto, K. Suharno, and S. Widodo. "Modeling of oil palm frond gasification process in a multistage downdraft gasifier using aspen plus." Journal of Physics: Conference Series 1517 (April 2020): 012036. http://dx.doi.org/10.1088/1742-6596/1517/1/012036.

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26

Rasool Lone, Sohail, and Mushtaq Ahmad Rather. "Modeling and Simulation of a Distillation Column using ASPEN PLUS for separating methanol/water mixture." International Journal of Scientific and Engineering Research 6, no. 3 (March 25, 2015): 619–27. http://dx.doi.org/10.14299/ijser.2015.03.002.

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27

Bagchi, Bishwadeep, Sushmita Sati, and Vidyasagar Shilapuram. "Modeling solubility of CO2/hydrocarbon gas in ionic liquid ([emim][FAP]) using Aspen Plus simulations." Environmental Science and Pollution Research 24, no. 22 (June 19, 2017): 18106–22. http://dx.doi.org/10.1007/s11356-017-9408-4.

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28

von Kurnatowski, Martin, and Michael Bortz. "Modeling and Multi-Criteria Optimization of a Process for H2O2 Electrosynthesis." Processes 9, no. 2 (February 23, 2021): 399. http://dx.doi.org/10.3390/pr9020399.

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This article introduces a novel laboratory-scale process for the electrochemical synthesis of hydrogen peroxide (H2O2). The process aims at an energy-efficient, decentralized production, and a mathematical optimization of it is presented. A dynamic, zero-dimensional mathematical model of the reactor is set up in Aspen custom modeler®. The proposed model constitutes a reasonable compromise between complexity and convergence. After thoroughly determining the reaction kinetics by adjustment to experimental data, the reactor unit is embedded in an Aspen Plus® flowsheet in order to investigate its interaction with other unit operations. The downstream contains another custom module for membrane distillation. Electricity appears as a resource in the process, and optimization shows that it reaches product purities of up to 3 wt.-%. Both the process optimization and the adjustment of the reaction kinetics are treated as multi-criteria optimization (MCO) problems.

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29

Ali, Arshid Mahmood, Muhammad Shahbaz, Khurram Shahzad, Muddasser Inayat, Salman Naqvi, Abdulrahim Ahmad Al-Zahrani, Muhammad Imtiaz Rashid, Mohammad Rehan, and Aishah Binti Mahpudz. "Polygeneration syngas and power from date palm waste steam gasification through an Aspen Plus process modeling." Fuel 332 (January 2023): 126120. http://dx.doi.org/10.1016/j.fuel.2022.126120.

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30

Furda, Patrik, Miroslav Variny, Zuzana Labovská, and Tomáš Cibulka. "Process Drive Sizing Methodology and Multi-Level Modeling Linking MATLAB® and Aspen Plus® Environment." Processes 8, no. 11 (November 19, 2020): 1495. http://dx.doi.org/10.3390/pr8111495.

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Optimal steam process drive sizing is crucial for efficient and sustainable operation of energy-intense industries. Recent years have brought several methods assessing this problem, which differ in complexity and user-friendliness. In this paper, a novel complex method was developed and presented and its superiority over other approaches was documented on an industrial case study. Both the process-side and steam-side characteristics were analyzed to obtain correct model input data: Driven equipment performance and efficiency maps were considered, off-design and seasonal operation was studied, and steam network topology was included. Operational data processing and sizing calculations were performed in a linked MATLAB®–Aspen Plus® environment, exploiting the strong sides of both software tools. The case study aimed to replace a condensing steam turbine by a backpressure one, revealing that: 1. Simpler methods neglecting frictional pressure losses and off-design turbine operation efficiency loss undersized the drive and led to unacceptable loss of deliverable power to the process; 2. the associated process production loss amounted up to 20%; 3. existing bottlenecks in refinery steam pipelines operation were removed; however, new ones were created; and 4. the effect on the marginal steam source operation may vary seasonally. These findings accentuate the value and viability of the presented method.

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31

de Andrés, Juan Manuel, Michel Vedrenne, Matteo Brambilla, and Encarnación Rodríguez. "Modeling and model performance evaluation of sewage sludge gasification in fluidized-bed gasifiers using Aspen Plus." Journal of the Air & Waste Management Association 69, no. 1 (October 16, 2018): 23–33. http://dx.doi.org/10.1080/10962247.2018.1500404.

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32

Ye, Genyin, Donglai Xie, Weiyan Qiao, John R. Grace, and C. Jim Lim. "Modeling of fluidized bed membrane reactors for hydrogen production from steam methane reforming with Aspen Plus." International Journal of Hydrogen Energy 34, no. 11 (June 2009): 4755–62. http://dx.doi.org/10.1016/j.ijhydene.2009.03.047.

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33

Darmawan, Arif, Flabianus Hardi, Kunio Yoshikawa, Muhammad Aziz, and Koji Tokimatsu. "Enhanced Process Integration of Entrained Flow Gasification and Combined Cycle: Modeling and Simulation Using Aspen Plus." Energy Procedia 105 (May 2017): 303–8. http://dx.doi.org/10.1016/j.egypro.2017.03.318.

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34

HOU, Weifeng, Hongye SU, Yongyou HU, and Jian CHU. "Modeling, Simulation and Optimization of a Whole Industrial Catalytic Naphtha Reforming Process on Aspen Plus Platform." Chinese Journal of Chemical Engineering 14, no. 5 (October 2006): 584–91. http://dx.doi.org/10.1016/s1004-9541(06)60119-5.

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35

Mperiju, Thlama, Tome Sylvain, Moses NyoTonglo Arowo, Tilak Dhanda, Abdulhalim Abubakar, Babakaumi Ahmadu Goriya, and Aminullah Zakariyyah Abdul. "Optimized Production of High Purity Sulphuric Acid via Contact Process." Logistic and Operation Management Research (LOMR) 2, no. 1 (May 29, 2023): 1–13. http://dx.doi.org/10.31098/lomr.v2i1.1436.

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Sulphuric acid (H2SO4) is of immense importance to the chemical industry and humanity. The use of Aspen Plus modeling, simulation, and optimization via the contact process has enabled the production of grade sulphuric acid. Notably, the research findings highlight the sensitivity of water flow rate to the maximization of H2SO4 production. Through these methods, a production capacity of around 8 tons per day was achieved, with a purity level of 98.9%. This achievement significantly contributes to meeting the demand for sulphuric acid in various industries. Moreover, exploring alternative sourcing methods, such as utilizing elemental sulphur, offers the potential for further optimizing H2SO4 production. The benefits of improving H2SO4 production extend beyond the chemical industry. Sulphuric acid finds applications in agriculture, petroleum refining, pharmaceuticals, and metal processing. Enhancing the production process ensures a reliable supply for these sectors. In summary, sulphuric acid is indispensable to the chemical industry and humanity at large. Aspen Plus modeling and optimization techniques have successfully improved the production of high-grade sulphuric acid, resulting in increased capacity and purity. Exploring alternative sourcing methods further enhances production possibilities. These advancements have wide-ranging implications, benefiting multiple industries and driving progress in sectors reliant on sulphuric acid.

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36

Lu, Wang, Pietro Bartocci, Alberto Abad, Aldo Bischi, Haiping Yang, Arturo Cabello, Margarita de Las Obras Loscertales, Mauro Zampilli, and Francesco Fantozzi. "Dimensioning Air Reactor and Fuel Reactor of a Pressurized CLC Plant to Be Coupled to a Gas Turbine: Part 2, the Fuel Reactor." Energies 16, no. 9 (April 30, 2023): 3850. http://dx.doi.org/10.3390/en16093850.

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Bioenergy with Carbon Capture and Storage (BECCS) technologies are fundamental to reach negative CO2 emissions by removing it from the atmosphere and storing it underground. A promising solution to implement BECCS is pressurized Chemical Looping Combustion (CLC), which involves coupling a pressurized CLC reactor system to a turboexpander. The typical configuration chosen is to have an air reactor and a fuel reactor based on coupled circulating fluidized beds. The fluidization regime in both reactors is preferred to be fast fluidization to enhance gas particle contact and solids circulation among reactors. To design the two reactors, Aspen Plus software was used, given that the new version has a module for fluidized bed modeling. At first, the oxygen carrier was designed ex novo, but given that it is a composite compound mainly made by nickel oxide freeze-granulated on alumina (Ni40Al-FG), the molecular structure has been inserted in Aspen Plus. Then, based on the power of the gas turbine, the power output per kg of evolving fluid (in this case, depleted air) is calculated using Aspen Plus. Once the nitrogen content in the depleted air is known, the total air at the inlet of the air reactor is calculated. The fuel reactor is modeled by inserting the reduction reactions for nickel-based oxygen carriers. The paper presents a useful methodology for developing pressurized Chemical Looping Combustors to be coupled to gas turbines for power generation. The provided data will be cross-validated with 0D-models and experimental results.

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37

Choi, YongMan, Changsik Choi, Bumeui Hong, Sung Su Cho, Yong Jin Kim, and Hak Joon Kim. "Heat Recovery Modeling and Exergy Analysis of Dry Combustion Process for Explosive Gas Treatment Using Aspen Plus." Journal of Korean Society for Atmospheric Environment 33, no. 5 (October 31, 2017): 521–28. http://dx.doi.org/10.5572/kosae.2017.33.5.521.

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38

Tangsriwong, Kwanchanok, Puttida Lapchit, Tanatip Kittijungjit, Thepparat Klamrassamee, Yanin Sukjai, and Yossapong Laoonual. "Modeling of chemical processes using commercial and open-source software: A comparison between Aspen Plus and DWSIM." IOP Conference Series: Earth and Environmental Science 463 (April 7, 2020): 012057. http://dx.doi.org/10.1088/1755-1315/463/1/012057.

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39

Liu, Jialin, Han-Ci Gao, Chao-Chin Peng, David Shan-Hill Wong, Shi-Shang Jang, and Jui-Fu Shen. "Aspen Plus rate-based modeling for reconciling laboratory scale and pilot scale CO2 absorption using aqueous ammonia." International Journal of Greenhouse Gas Control 34 (March 2015): 117–28. http://dx.doi.org/10.1016/j.ijggc.2015.01.009.

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40

Liu, Gang, Jian Zhang, and Jie Bao. "Cost evaluation of cellulase enzyme for industrial-scale cellulosic ethanol production based on rigorous Aspen Plus modeling." Bioprocess and Biosystems Engineering 39, no. 1 (November 5, 2015): 133–40. http://dx.doi.org/10.1007/s00449-015-1497-1.

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41

Noh, Jaehyun, Alyssa Marie Fulgueras, Leah Jessica Sebastian, Hyeon Gon Lee, Dong Sun Kim, and Jungho Cho. "Estimation of thermodynamic properties of hydrogen isotopes and modeling of hydrogen isotope systems using Aspen Plus simulator." Journal of Industrial and Engineering Chemistry 46 (February 2017): 1–8. http://dx.doi.org/10.1016/j.jiec.2016.07.053.

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42

Zhuo, Wencai, Baiqian Dai, Kaibing Zhang, Yunpeng Yu, Zhicheng Zhang, Hailiang Zhou, and Bin Zhou. "Modeling optimization for a typical VOCs thermal conversion process." E3S Web of Conferences 385 (2023): 03012. http://dx.doi.org/10.1051/e3sconf/202338503012.

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Aiming at the current environmental problems, the thermal oxidation treatment for industrial VOCs emission is a common and effective measure. This paper studies on the optimization effect of one optimization method for direct VOCs thermal oxidation of a color aluminum spraying production line based on Aspen-Plus. According to the direct VOCs thermal oxidation process with a 30000 m³/h circulating air volume, propose the flue gas reflux and coating room drainage technology. Use the second law of thermodynamics, and the exergy flow analysis shows the methane consumption could be reduced 12%. Carbon emissions also decreased significantly, with 3.42% reduction. These findings are practical for industrial production cost saving and environmental protection problems solving.

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43

Hammer, Nicole L., Akwasi A. Boateng, Charles A. Mullen, and M. Clayton Wheeler. "Aspen Plus® and economic modeling of equine waste utilization for localized hot water heating via fast pyrolysis." Journal of Environmental Management 128 (October 2013): 594–601. http://dx.doi.org/10.1016/j.jenvman.2013.06.008.

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44

Vikse, Matias, Harry Watson, Truls Gundersen, and Paul Barton. "Simulation of Dual Mixed Refrigerant Natural Gas Liquefaction Processes Using a Nonsmooth Framework." Processes 6, no. 10 (October 17, 2018): 193. http://dx.doi.org/10.3390/pr6100193.

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Natural gas liquefaction is an energy intensive process where the feed is cooled from ambient temperature down to cryogenic temperatures. Different liquefaction cycles exist depending on the application, with dual mixed refrigerant processes normally considered for the large-scale production of Liquefied Natural Gas (LNG). Large temperature spans and small temperature differences in the heat exchangers make the liquefaction processes difficult to analyze. Exergetic losses from irreversible heat transfer increase exponentially with a decreasing temperature at subambient conditions. Consequently, an accurate and robust simulation tool is paramount to allow designers to make correct design decisions. However, conventional process simulators, such as Aspen Plus, suffer from significant drawbacks when modeling multistream heat exchangers. In particular, no rigorous checks exist to prevent temperature crossovers. Limited degrees of freedom and the inability to solve for stream variables other than outlet temperatures also makes such tools inflexible to use, often requiring the user to resort to a manual iterative procedure to obtain a feasible solution. In this article, a nonsmooth, multistream heat exchanger model is used to develop a simulation tool for two different dual mixed refrigerant processes. Case studies are presented for which Aspen Plus fails to obtain thermodynamically feasible solutions.

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45

Al-Sobhi, Saad, Ali Elkamel, Fatih Erenay, and Munawar Shaik. "Simulation-Optimization Framework for Synthesis and Design of Natural Gas Downstream Utilization Networks." Energies 11, no. 2 (February 3, 2018): 362. http://dx.doi.org/10.3390/en11020362.

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Many potential diversification and conversion options are available for utilization of natural gas resources, and several design configurations and technology choices exist for conversion of natural gas to value-added products. Therefore, a detailed mathematical model is desirable for selection of optimal configuration and operating mode among the various options available. In this study, we present a simulation-optimization framework for the optimal selection of economic and environmentally sustainable pathways for natural gas downstream utilization networks by optimizing process design and operational decisions. The main processes (e.g., LNG, GTL, and methanol production), along with different design alternatives in terms of flow-sheeting for each main processing unit (namely syngas preparation, liquefaction, N2 rejection, hydrogen, FT synthesis, methanol synthesis, FT upgrade, and methanol upgrade units), are used for superstructure development. These processes are simulated using ASPEN Plus V7.3 to determine the yields of different processing units under various operating modes. The model has been applied to maximize total profit of the natural gas utilization system with penalties for environmental impact, represented by CO2eq emission obtained using ASPEN Plus for each flowsheet configuration and operating mode options. The performance of the proposed modeling framework is demonstrated using a case study.

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46

Tumilar, Aldric, Manish Sharma, Dia Milani, and Ali Abbas. "Modeling and Simulation Environments for Sustainable Low-Carbon Energy Production – A Review." Chemical Product and Process Modeling 11, no. 2 (June 1, 2016): 97–124. http://dx.doi.org/10.1515/cppm-2015-0035.

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Abstract This paper reviews research trends in modeling for low-carbon energy production. The focus is on two currently significant low-carbon energy processes; namely, bioenergy and post-combustion carbon capture (PCC) processes. The fundamentals of these two processes are discussed and the role of modeling and simulation tools (MSTs) is highlighted. The most popular modeling software packages are identified and their use in the literature is analyzed. Among commercially available packages, it is found that no single software package can handle all process development needs such as, configuration studies, techno-economic analysis, exergy optimization, and process integration. This review also suggests that optimal modeling results reported in literature can be viewed as optimal at the individual plant level, but sub-optimal for plant superstructure level. This review has identified key gaps pertinent to developing hybrid models that describe integrated energy production processes. ASPEN Plus is found to be dominant for modeling both bioenergy and PCC processes for both steady-state and dynamic modes respectively.

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Marseglia, Guido, Carlo Maria Medaglia, Alessandro Petrozzi, Andrea Nicolini, Franco Cotana, and Federico Sormani. "Experimental Tests and Modeling on a Combined Heat and Power Biomass Plant." Energies 12, no. 13 (July 8, 2019): 2615. http://dx.doi.org/10.3390/en12132615.

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Renewable energy sources can help the countries to achieve some of the Sustainable Development Goals (SDGs) provided from the recent 2030 Agenda, allowing for clean, secure, reliable and affordable energy. Biomass technology is a relevant renewable energy to contribute to reach a clean and affordable energy production system with important emissions reduction of greenhouse gases (GHG). An innovative technological application of biomass energy consisting of a burner coupled with an external fired gas turbine (EFGT) has been developed for the production of electricity. This paper shows the results of the plant modelling by Aspen Plus environment and preliminary experimental tests; the validation of the proposed model allows for the main parameters to be defined that regulate the energy production plant supplied by woodchips.

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Mazanov, S. V., F. M. Gumerov, A. I. Kourdioukov, A. R. Gabitova, R. A. Usmanov, L. Kh Safiullina, Z. I. Zaripov, and Yu A. Shapovalov. "Biodiesel fuel. Part III. Quantum chemical research and simulation of the process." Power engineering: research, equipment, technology 25, no. 1 (April 23, 2023): 24–44. http://dx.doi.org/10.30724/1998-9903-2023-25-1-24-44.

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THE PURPOSE. The purpose of this work was to use the associated paradigm for a correct quantum-chemical description of non-catalytic and catalytic supercritical fluid processes of transesterification of triglycerides with alcohols and hydrolysis of triglycerides and to model a one-stage process for obtaining biodiesel fuel, carried out under supercritical fluid conditions with its subsequent scaling to the commercial level.METHODS. The Gaussian09 software product was used to describe quantum chemical studies. The process modeling was carried out using the ASPEN Plus® v2006 software product. The behavior of thermodynamic systems at high temperatures and pressures is modeled using "RK ASPEN EOS". For modeling processes carried out at low pressures, mathematical models UNIQUAC and UNIFAC-LL were used. The scaling of the process was carried out in the VMGSim program.RESULTS. The third part of the review focuses on the quantum-chemical modeling of the transesterification reaction carried out under supercritical fluid conditions. It is shown that taking into account the associative paradigm makes it possible to obtain calculated reaction rate constants that agree in order with the experimental values. And also an analysis was carried out and the results of modeling the process of obtaining biodiesel fuel and scaling it to a commercial level, with a capacity of up to 9000 tons / year, were presented.CONCLUSION. The conducted analysis showed that biodiesel fuel can be a competitive fuel in our and the world market.

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Wang, Xiao Ming, Xian Bin Xiao, Xu Jiao Chen, Ji Liu, and Wen Yan Li. "Steam Gasification of Biomass Coupled with Lime-Based CO₂ Capture in a Dual Fluidized Bed: A Modeling Study." Applied Mechanics and Materials 716-717 (December 2014): 142–45. http://dx.doi.org/10.4028/www.scientific.net/amm.716-717.142.

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Biomass is an important renewable energy and making hydrogen-rich syngas from biomass is promising. Dual fluidized bed gasification technology can increase hydrogen content in the syngas. Moreover, steam gasification of biomass coupled with lime-based CO2 capture in a dual fluidized bed can further improve the syngas quality . This paper established a dual fluidized bed gasification model using Aspen plus,in order to explore the effect of different gasification temperatures and steam to biomass ratios on hydrogen content in syngas, providing a theoretical basis for the optimization of operating parameters and process.

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Ali, Syed Sadiq, Sk Safdar Hossain, and Mohammad Asif. "Dynamic modeling of the isoamyl acetate reactive distillation process." Polish Journal of Chemical Technology 19, no. 1 (March 28, 2017): 59–66. http://dx.doi.org/10.1515/pjct-2017-0009.

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Abstract The cost-effectiveness of reactive distillation (RD) processes makes them highly attractive for industrial applications. However, their preliminary design and subsequent scale-up and operation are challenging. Specifically, the response of RD system during fluctuations in process parameters is of paramount importance to ensure the stability of the whole process. As a result of carrying out simulations using Aspen Plus, it is shown that the RD process for isoamyl acetate production was much more economical than conventional reactor distillation configuration under optimized process conditions due to lower utilities consumption, higher conversion and smaller sizes of condenser and reboiler. Rigorous dynamic modeling of RD system was performed to evaluate its sensitivity to disturbances in critical process parameters; the product flow was quite sensitive to disturbances. Even more sensitive was product composition when the disturbance in heat duties of condenser or reboiler led to a temperature decrease. However, positive disturbance in alcohol feed is of particular concern, which clearly made the system unstable.

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