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{"title":"使用 gPROMS® 和 GAMS® 建立复杂化学反应平衡模型介绍","authors":"Raoudha Garma, Doniazed Sioud, Housam Binous, Ahmed Bellagi","doi":"10.1002/cae.22714","DOIUrl":null,"url":null,"abstract":"<p>In the present paper several aspects of the simulation of complex chemical equilibrium are discussed, using two research and educational software: gPROMS® and GAMS®. All computations are performed to boost the understanding of chemical engineering students, undergraduate, and graduate, of the complex concepts behind both thermo-chemical processes and optimization techniques. Four case studies with varying levels of difficulty illustrate the proposed methodology and robustness of the modeling systems:\n\n </p><p>Our results indicate that the use of optimization tools offered bygPROMS® and GAMS®software are useful and efficient tools to calculate the chemical and phase equilibrium by minimizing the Gibbs energy, provided that adequate initial guesses are used. Furthermore, the computational time spent in the calculations was generally quite short. The obtained equilibrium compositions are benchmarked using the ubiquitous process simulators: ASPEN-Plus® and/or ASPEN-Hysys® as well as data available from the open literature. We obtained excellent agreement between our results and their counterpart obtained using ASPEN-Plus®. In the last part of this manuscript, authors share their experience in supervising senior term projects on the subject. A questionnaire was used to collect qualitative and quantitative feedback from the nine students involved in the projects. Their responses to a questionnaire focused on the chemical engineering thermodynamics theory as well as software usage during their investigations. This questionnaire demonstrates that students can overcome mathematical complexity by either using mathematical software or equivalent modeling systems (e.g., \n<span>Matlab</span>®, \n<span>Mathematica<sup>©</sup></span>, gPROMS®, and GAMS®).</p>","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2024-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Introduction to the modeling of complex chemical reaction equilibrium using gPROMS® and GAMS®\",\"authors\":\"Raoudha Garma, Doniazed Sioud, Housam Binous, Ahmed Bellagi\",\"doi\":\"10.1002/cae.22714\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>In the present paper several aspects of the simulation of complex chemical equilibrium are discussed, using two research and educational software: gPROMS® and GAMS®. All computations are performed to boost the understanding of chemical engineering students, undergraduate, and graduate, of the complex concepts behind both thermo-chemical processes and optimization techniques. Four case studies with varying levels of difficulty illustrate the proposed methodology and robustness of the modeling systems:\\n\\n </p><p>Our results indicate that the use of optimization tools offered bygPROMS® and GAMS®software are useful and efficient tools to calculate the chemical and phase equilibrium by minimizing the Gibbs energy, provided that adequate initial guesses are used. Furthermore, the computational time spent in the calculations was generally quite short. The obtained equilibrium compositions are benchmarked using the ubiquitous process simulators: ASPEN-Plus® and/or ASPEN-Hysys® as well as data available from the open literature. We obtained excellent agreement between our results and their counterpart obtained using ASPEN-Plus®. In the last part of this manuscript, authors share their experience in supervising senior term projects on the subject. A questionnaire was used to collect qualitative and quantitative feedback from the nine students involved in the projects. Their responses to a questionnaire focused on the chemical engineering thermodynamics theory as well as software usage during their investigations. This questionnaire demonstrates that students can overcome mathematical complexity by either using mathematical software or equivalent modeling systems (e.g., \\n<span>Matlab</span>®, \\n<span>Mathematica<sup>©</sup></span>, gPROMS®, and GAMS®).</p>\",\"PeriodicalId\":2,\"journal\":{\"name\":\"ACS Applied Bio Materials\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2024-01-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Bio Materials\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/cae.22714\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATERIALS SCIENCE, BIOMATERIALS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cae.22714","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
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