Hamid Reza Homayonfar, H. A. Ebrahim, M. Azarhoosh
{"title":"Determining the Optimum Temperature Path Versus the Catalyst Working Time in a Trickle Bed Diesel Hydrodesulfurization Reactor","authors":"Hamid Reza Homayonfar, H. A. Ebrahim, M. Azarhoosh","doi":"10.15255/cabeq.2023.2266","DOIUrl":null,"url":null,"abstract":"This study consists of four main parts. First, a heterogeneous reactor model was developed to simulate a diesel hydrodesulfurization (HDS) reactor with catalyst deactivation. Second, operating conditions were investigated. Third, the simulation results from the first part were modeled using the response surface method and artificial neural networks (ANNs) to shorten the temperature path optimization time. Among the different modeling methods, the feed-forward ANN method employing the Bayesian Regularization (BR) training method with 10 neurons in the hidden layer demonstrated the highest accuracy. Finally, the temperature path of the trickle bed reactor was optimized. A three-dimensional curve depicting sulfur output content versus temperature and catalyst operation time was plotted using the most effective ANN approach as a fitness function. When the sulfur content met the Euro-6 requirement, the temperature path versus catalyst working period was optimized.","PeriodicalId":1,"journal":{"name":"Accounts of Chemical Research","volume":null,"pages":null},"PeriodicalIF":16.4000,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Accounts of Chemical Research","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.15255/cabeq.2023.2266","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
This study consists of four main parts. First, a heterogeneous reactor model was developed to simulate a diesel hydrodesulfurization (HDS) reactor with catalyst deactivation. Second, operating conditions were investigated. Third, the simulation results from the first part were modeled using the response surface method and artificial neural networks (ANNs) to shorten the temperature path optimization time. Among the different modeling methods, the feed-forward ANN method employing the Bayesian Regularization (BR) training method with 10 neurons in the hidden layer demonstrated the highest accuracy. Finally, the temperature path of the trickle bed reactor was optimized. A three-dimensional curve depicting sulfur output content versus temperature and catalyst operation time was plotted using the most effective ANN approach as a fitness function. When the sulfur content met the Euro-6 requirement, the temperature path versus catalyst working period was optimized.
期刊介绍:
Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance.
Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.