Sara Hemmatian Larki, Hossein Sasani, Ali Haghighi
{"title":"利用模糊集理论对序批式反应器工艺进行不确定性分析","authors":"Sara Hemmatian Larki, Hossein Sasani, Ali Haghighi","doi":"10.1016/j.jwpe.2024.106314","DOIUrl":null,"url":null,"abstract":"<div><div>This study uses Fuzzy Sets Theory to investigate the uncertainty analysis of the Sequencing Batch Reactor (SBR) process, focusing on key input parameters and biokinetic coefficients. Wastewater data from Shahid Chamran University of Ahvaz (SCU) were utilized as the case study, and extreme output values were identified using a Many-Objective Genetic Algorithm (MOGA) and the Impact Table Method (ITM). Four scenarios were developed to evaluate uncertainty in SBR design, each representing different sources of uncertainty. In the most comprehensive scenario (Scenario 4), significant variations in output parameters were observed: soluble BOD (SBODe) varied from −78 % to +363 %, soluble COD (SCODe) ranged from −24 % to +78 %, and total nitrogen in the effluent (TNe) fluctuated between −85 % and +116 %. Additionally, the Food-to-Microorganism (F/M) ratio and organic loading (Lorg) exceeded permissible limits, reaching values of 0.12 kg BOD/kg MLVSS·day and 0.34 kg BOD/m<sup>3</sup>·day, respectively. The results indicate that the MOGA method enhances the accuracy of effluent quality predictions and provides a robust framework for optimizing SBR processes in practical applications.</div></div>","PeriodicalId":17528,"journal":{"name":"Journal of water process engineering","volume":"68 ","pages":"Article 106314"},"PeriodicalIF":6.3000,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Uncertainty analysis of the Sequencing Batch Reactor process using the Fuzzy Sets Theory\",\"authors\":\"Sara Hemmatian Larki, Hossein Sasani, Ali Haghighi\",\"doi\":\"10.1016/j.jwpe.2024.106314\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This study uses Fuzzy Sets Theory to investigate the uncertainty analysis of the Sequencing Batch Reactor (SBR) process, focusing on key input parameters and biokinetic coefficients. Wastewater data from Shahid Chamran University of Ahvaz (SCU) were utilized as the case study, and extreme output values were identified using a Many-Objective Genetic Algorithm (MOGA) and the Impact Table Method (ITM). Four scenarios were developed to evaluate uncertainty in SBR design, each representing different sources of uncertainty. In the most comprehensive scenario (Scenario 4), significant variations in output parameters were observed: soluble BOD (SBODe) varied from −78 % to +363 %, soluble COD (SCODe) ranged from −24 % to +78 %, and total nitrogen in the effluent (TNe) fluctuated between −85 % and +116 %. Additionally, the Food-to-Microorganism (F/M) ratio and organic loading (Lorg) exceeded permissible limits, reaching values of 0.12 kg BOD/kg MLVSS·day and 0.34 kg BOD/m<sup>3</sup>·day, respectively. The results indicate that the MOGA method enhances the accuracy of effluent quality predictions and provides a robust framework for optimizing SBR processes in practical applications.</div></div>\",\"PeriodicalId\":17528,\"journal\":{\"name\":\"Journal of water process engineering\",\"volume\":\"68 \",\"pages\":\"Article 106314\"},\"PeriodicalIF\":6.3000,\"publicationDate\":\"2024-10-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of water process engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2214714424015460\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, CHEMICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of water process engineering","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2214714424015460","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, CHEMICAL","Score":null,"Total":0}
Uncertainty analysis of the Sequencing Batch Reactor process using the Fuzzy Sets Theory
This study uses Fuzzy Sets Theory to investigate the uncertainty analysis of the Sequencing Batch Reactor (SBR) process, focusing on key input parameters and biokinetic coefficients. Wastewater data from Shahid Chamran University of Ahvaz (SCU) were utilized as the case study, and extreme output values were identified using a Many-Objective Genetic Algorithm (MOGA) and the Impact Table Method (ITM). Four scenarios were developed to evaluate uncertainty in SBR design, each representing different sources of uncertainty. In the most comprehensive scenario (Scenario 4), significant variations in output parameters were observed: soluble BOD (SBODe) varied from −78 % to +363 %, soluble COD (SCODe) ranged from −24 % to +78 %, and total nitrogen in the effluent (TNe) fluctuated between −85 % and +116 %. Additionally, the Food-to-Microorganism (F/M) ratio and organic loading (Lorg) exceeded permissible limits, reaching values of 0.12 kg BOD/kg MLVSS·day and 0.34 kg BOD/m3·day, respectively. The results indicate that the MOGA method enhances the accuracy of effluent quality predictions and provides a robust framework for optimizing SBR processes in practical applications.
期刊介绍：
The Journal of Water Process Engineering aims to publish refereed, high-quality research papers with significant novelty and impact in all areas of the engineering of water and wastewater processing . Papers on advanced and novel treatment processes and technologies are particularly welcome. The Journal considers papers in areas such as nanotechnology and biotechnology applications in water, novel oxidation and separation processes, membrane processes (except those for desalination) , catalytic processes for the removal of water contaminants, sustainable processes, water reuse and recycling, water use and wastewater minimization, integrated/hybrid technology, process modeling of water treatment and novel treatment processes. Submissions on the subject of adsorbents, including standard measurements of adsorption kinetics and equilibrium will only be considered if there is a genuine case for novelty and contribution, for example highly novel, sustainable adsorbents and their use: papers on activated carbon-type materials derived from natural matter, or surfactant-modified clays and related minerals, would not fulfil this criterion. The Journal particularly welcomes contributions involving environmentally, economically and socially sustainable technology for water treatment, including those which are energy-efficient, with minimal or no chemical consumption, and capable of water recycling and reuse that minimizes the direct disposal of wastewater to the aquatic environment. Papers that describe novel ideas for solving issues related to water quality and availability are also welcome, as are those that show the transfer of techniques from other disciplines. The Journal will consider papers dealing with processes for various water matrices including drinking water (except desalination), domestic, urban and industrial wastewaters, in addition to their residues. It is expected that the journal will be of particular relevance to chemical and process engineers working in the field. The Journal welcomes Full Text papers, Short Communications, State-of-the-Art Reviews and Letters to Editors and Case Studies
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
