Biomass Gasification and Applied Intelligent Retrieval in Modeling

Author:

Meena Manish12ORCID,Kumar Hrishikesh23,Chaturvedi Nitin Dutt1,Kovalev Andrey A.4,Bolshev Vadim4ORCID,Kovalev Dmitriy A.4ORCID,Sarangi Prakash Kumar5ORCID,Chawade Aakash6ORCID,Rajput Manish Singh7,Vivekanand Vivekanand2ORCID,Panchenko Vladimir8ORCID

Affiliation:

1. Department of Chemical and Biochemical Engineering, Indian Institute of Technology Patna, Patna 801106, Bihar, India

2. Centre for Energy and Environment, Malaviya National Institute of Technology Jaipur, Jaipur 302017, Rajasthan, India

3. Dr. B.R. Ambedkar National Institute of Technology Jalandhar, Jalandhar 144011, Punjab, India

4. Federal State Budgetary Scientific Institution “Federal Scientific Agroengineering Center VIM”, 1st Institutskiy Proezd, 5, 109428 Moscow, Russia

5. College of Agriculture, Central Agricultural University, Imphal 795004, Manipur, India

6. Department of Plant Breeding, Swedish University of Agricultural Sciences, Alnarp, 23053 Uppsala, Sweden

7. Department of Biotechnology, Dr. Ambedkar Institute of Technology for Handicapped, Kanpur 208024, Uttar Pradesh, India

8. Russian University of Transport, 127994 Moscow, Russia

Abstract

Gasification technology often requires the use of modeling approaches to incorporate several intermediate reactions in a complex nature. These traditional models are occasionally impractical and often challenging to bring reliable relations between performing parameters. Hence, this study outlined the solutions to overcome the challenges in modeling approaches. The use of machine learning (ML) methods is essential and a promising integration to add intelligent retrieval to traditional modeling approaches of gasification technology. Regarding this, this study charted applied ML-based artificial intelligence in the field of gasification research. This study includes a summary of applied ML algorithms, including neural network, support vector, decision tree, random forest, and gradient boosting, and their performance evaluations for gasification technologies.

Funder

MNIT Jaipur

IIT Patna

Publisher

MDPI AG

Subject

Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous),Building and Construction

Reference129 articles.

1. Gopalakrishnan, P. (2013). Modelling of Biomass Steam Gasification in a Bubbling Fluidized Bed Gasifier. [Ph.D. Thesis, University of Canterb].

2. Prediction of product distribution and bio-oil heating value of biomass fast pyrolysis;Chen;Chem. Eng. Process.-Process Intensif.,2018

3. Advanced modeling approaches for CFD simulations of coal combustion and gasification;Hasse;Prog. Energy Combust. Sci.,2021

4. Kinetic model of biomass gasification;Wang;Sol. Energy,1993

5. Thermodynamic modelling and evaluation of a two-stage thermal process for waste gasification;Materazzi;Fuel,2013

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3