Gasification of Organic Waste:Parameters,Mechanism and Prediction with the Machine Learning Approach

作     者：Feng Gao Liang Bao Qin Wang 

作者机构：Yibin Research InstituteSouthwest Jiaotong UniversityYibinChina Office of Domestic Cooperation and Educational Training ManagementSouthwest Jiaotong UniversityChengduChina School of Computer Science and TechnologyXidian UniversityXi’anChina Faculty of Geosciences and Environmental EngineeringSouthwest Jiaotong UniversityChengduChina 

出 版 物：《Journal of Renewable Materials》 (可再生材料杂志（英文）)

年 卷 期：2023年第11卷第6期

页      面：2771-2786页

核心收录：

学科分类：0711[理学-系统科学] 080702[工学-热能工程] 08[工学] 0807[工学-动力工程及工程热物理] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：This work is supported by Sichuan Science and Technology Program(2021JDR0343) the Project Fund of Chengdu Science and Technology Bureau(2019-YF09-00086-SN) 

主　　题：Gasification organic waste machine learning gas composition 

摘      要：Gasification of organic waste represents one of the most effective valorization pathways for renewable energy and resources recovery,while this process can be affected by multi-factors like temperature,feedstock,and steam content,making the product’s prediction *** the popularization and promotion of artificial intelligence such as machine learning(ML),traditional artificial neural networks have been paid more attention by researchers from the data science field,which provides scientific and engineering communities with flexible and rapid prediction frameworks in the field of organic waste *** this work,critical parameters including temperature,steam ratio,and feedstock during gasification of organic waste were reviewed in three scenarios including steam gasification,air gasification,and oxygen-riched gasification,and the product distribution and involved mechanism were ***,we presented the details of ML methods like regression analysis,artificial neural networks,decision trees,and related methods,which are expected to revolutionize data analysis and modeling of the gasification of organic *** outputs including the syngas yield,composition,and HHVs were discussed with a better understanding of the gasification process and ML *** review focused on the combination of gasification and ML,and it is of immediate significance for the resource and energy utilization of organic waste.