用响应面法和模糊逻辑估计介质阻挡放电等离子体中臭氧的产生

K. Nishanth, Apeksha Madhukar, BS Rajanikanth
{"title":"用响应面法和模糊逻辑估计介质阻挡放电等离子体中臭氧的产生","authors":"K. Nishanth, Apeksha Madhukar, BS Rajanikanth","doi":"10.1109/POWERCON48463.2020.9230546","DOIUrl":null,"url":null,"abstract":"Ozone is being used in several applications such as oxidation of gaseous pollutants, wastewater treatment, surface disinfection, food processing etc. One of the popular means of producing ozone is by using electrical discharges. In this paper, ozone generation using non-thermal plasma is discussed, in the context of its use for diesel engine exhaust treatment. To achieve maximum oxidation of nitric oxide and other pollutants in the exhaust for varying engine loads, the ozone generation needs to be varied accordingly. As the parameters controlling ozone generation can have multiple combinations, finding the right set of parameters to achieve a specific ozone concentration requires several experimental trials. In such cases, the availability of a model that accurately predicts the concentration of ozone for a given set of parameters reduces the experimental burden of conducting such trials. With this objective, two mathematical models, Response Surface Methodology and Fuzzy Logic Model, have been explored as possible techniques for prediction of ozone concentration.","PeriodicalId":306418,"journal":{"name":"2020 IEEE International Conference on Power Systems Technology (POWERCON)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Estimation of Ozone Generation in Dielectric Barrier Discharge Plasma using Response Surface Methodology and Fuzzy Logic\",\"authors\":\"K. Nishanth, Apeksha Madhukar, BS Rajanikanth\",\"doi\":\"10.1109/POWERCON48463.2020.9230546\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Ozone is being used in several applications such as oxidation of gaseous pollutants, wastewater treatment, surface disinfection, food processing etc. One of the popular means of producing ozone is by using electrical discharges. In this paper, ozone generation using non-thermal plasma is discussed, in the context of its use for diesel engine exhaust treatment. To achieve maximum oxidation of nitric oxide and other pollutants in the exhaust for varying engine loads, the ozone generation needs to be varied accordingly. As the parameters controlling ozone generation can have multiple combinations, finding the right set of parameters to achieve a specific ozone concentration requires several experimental trials. In such cases, the availability of a model that accurately predicts the concentration of ozone for a given set of parameters reduces the experimental burden of conducting such trials. With this objective, two mathematical models, Response Surface Methodology and Fuzzy Logic Model, have been explored as possible techniques for prediction of ozone concentration.\",\"PeriodicalId\":306418,\"journal\":{\"name\":\"2020 IEEE International Conference on Power Systems Technology (POWERCON)\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE International Conference on Power Systems Technology (POWERCON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/POWERCON48463.2020.9230546\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Conference on Power Systems Technology (POWERCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/POWERCON48463.2020.9230546","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

臭氧被广泛应用于气态污染物的氧化、废水处理、表面消毒、食品加工等领域。产生臭氧的常用方法之一是利用放电。本文讨论了利用非热等离子体产生臭氧在柴油机废气处理中的应用。为了在不同的发动机负荷下最大限度地氧化废气中的一氧化氮和其他污染物,臭氧的产生需要相应改变。由于控制臭氧生成的参数可以有多种组合,找到正确的参数集来实现特定的臭氧浓度需要多次实验试验。在这种情况下,如果有一种模型可以准确地预测给定一组参数下的臭氧浓度,就可以减轻进行这种试验的实验负担。为此,我们探索了两种数学模型——响应面法和模糊逻辑模型——作为预测臭氧浓度的可能技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimation of Ozone Generation in Dielectric Barrier Discharge Plasma using Response Surface Methodology and Fuzzy Logic
Ozone is being used in several applications such as oxidation of gaseous pollutants, wastewater treatment, surface disinfection, food processing etc. One of the popular means of producing ozone is by using electrical discharges. In this paper, ozone generation using non-thermal plasma is discussed, in the context of its use for diesel engine exhaust treatment. To achieve maximum oxidation of nitric oxide and other pollutants in the exhaust for varying engine loads, the ozone generation needs to be varied accordingly. As the parameters controlling ozone generation can have multiple combinations, finding the right set of parameters to achieve a specific ozone concentration requires several experimental trials. In such cases, the availability of a model that accurately predicts the concentration of ozone for a given set of parameters reduces the experimental burden of conducting such trials. With this objective, two mathematical models, Response Surface Methodology and Fuzzy Logic Model, have been explored as possible techniques for prediction of ozone concentration.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信