用于沼气生产的下吹气化技术:人工智能的作用

Vandana Sharma, Kamal Upreti, Arul Kumar Natarajan, Nishi Jain, Sanjay Kumar, Anant Rajee Bara, Sushma Kumari
{"title":"用于沼气生产的下吹气化技术:人工智能的作用","authors":"Vandana Sharma, Kamal Upreti, Arul Kumar Natarajan, Nishi Jain, Sanjay Kumar, Anant Rajee Bara, Sushma Kumari","doi":"10.1115/1.4066059","DOIUrl":null,"url":null,"abstract":"\n Artificial intelligence (AI) can help improve many areas of waste management and biogas generation. The world has reached a state where waste generation is increasing daily, while an effective waste management system is essential for the sustainable development of a country. AI could be of great use in optimizing the waste management scheme by technical differentiation of all sorts and recycling techniques. AI can contribute to the improvement of waste segmentation, recycling, and disposal. Thus, by assessing availability and composition, AI can easily contribute to the selection of the most suitable feedstock for biogas generation. This paper will discuss the optimization of gasifier design, an important part of biogas production, to enhance gasification efficiency for more efficient syngas production. Several gains accrue from AI applications, and among them is the selection of feedstocks and gasifiers optimal for more efficient and sustainable waste management and use in the production of biogas systems. This review paper identifies the potential application areas in either waste management practices or biogas production and puts forward ways in which AI can be used in these areas.","PeriodicalId":509700,"journal":{"name":"Journal of Energy Resources Technology","volume":"45 7","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Downdraft Gasification for Biogas Production: The Role of Artificial Intelligence\",\"authors\":\"Vandana Sharma, Kamal Upreti, Arul Kumar Natarajan, Nishi Jain, Sanjay Kumar, Anant Rajee Bara, Sushma Kumari\",\"doi\":\"10.1115/1.4066059\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n Artificial intelligence (AI) can help improve many areas of waste management and biogas generation. The world has reached a state where waste generation is increasing daily, while an effective waste management system is essential for the sustainable development of a country. AI could be of great use in optimizing the waste management scheme by technical differentiation of all sorts and recycling techniques. AI can contribute to the improvement of waste segmentation, recycling, and disposal. Thus, by assessing availability and composition, AI can easily contribute to the selection of the most suitable feedstock for biogas generation. This paper will discuss the optimization of gasifier design, an important part of biogas production, to enhance gasification efficiency for more efficient syngas production. Several gains accrue from AI applications, and among them is the selection of feedstocks and gasifiers optimal for more efficient and sustainable waste management and use in the production of biogas systems. This review paper identifies the potential application areas in either waste management practices or biogas production and puts forward ways in which AI can be used in these areas.\",\"PeriodicalId\":509700,\"journal\":{\"name\":\"Journal of Energy Resources Technology\",\"volume\":\"45 7\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Energy Resources Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1115/1.4066059\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Energy Resources Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/1.4066059","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

人工智能(AI)可以帮助改善废物管理和沼气发电的许多领域。当今世界,废物产生量与日俱增,而有效的废物管理系统对于一个国家的可持续发展至关重要。人工智能可以通过各种技术差异和回收技术,在优化废物管理计划方面发挥巨大作用。人工智能有助于改进废物分类、回收和处理。因此,通过评估可用性和成分,人工智能很容易为选择最适合的沼气生产原料做出贡献。本文将讨论沼气生产的一个重要环节--气化炉设计的优化,以提高气化效率,从而更高效地生产合成气。人工智能应用可带来多项收益,其中包括选择最佳原料和气化器,以实现更高效和可持续的废物管理,并将其用于沼气生产系统。本综述文件确定了废物管理实践或沼气生产的潜在应用领域,并提出了在这些领域使用人工智能的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Downdraft Gasification for Biogas Production: The Role of Artificial Intelligence
Artificial intelligence (AI) can help improve many areas of waste management and biogas generation. The world has reached a state where waste generation is increasing daily, while an effective waste management system is essential for the sustainable development of a country. AI could be of great use in optimizing the waste management scheme by technical differentiation of all sorts and recycling techniques. AI can contribute to the improvement of waste segmentation, recycling, and disposal. Thus, by assessing availability and composition, AI can easily contribute to the selection of the most suitable feedstock for biogas generation. This paper will discuss the optimization of gasifier design, an important part of biogas production, to enhance gasification efficiency for more efficient syngas production. Several gains accrue from AI applications, and among them is the selection of feedstocks and gasifiers optimal for more efficient and sustainable waste management and use in the production of biogas systems. This review paper identifies the potential application areas in either waste management practices or biogas production and puts forward ways in which AI can be used in these areas.
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
期刊最新文献
Effects of fines migration and reservoir heterogeneity on well productivity: analytical model and field cases Downdraft Gasification for Biogas Production: The Role of Artificial Intelligence FUEL CONSUMPTION PREDICTION IN DUAL-FUEL LOW-SPEED MARINE ENGINES WITH LOW-PRESSURE GAS INJECTION Transforming Oil Well Drilling: Prediction of Real-Time Rate of Penetration with Novel Machine Learning Approach in Varied Lithological Formations Construction Parameters Optimization of CO2 Composite Fracturing for Horizontal Shale Wells
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1