本文主要研究内容
作者（2019）在《一维固定床煤粉富氧燃烧的辐射能流特性与模型分析（英文）》一文中研究指出：目的:1.从辐射能利用角度出发,探究一维固定床煤粉富氧燃烧的辐射能流特性,为固体燃料燃烧能量分质分级转化应用提供参考;2.对比研究半经验模型与人工神经网络模型这两种建模方法,为人工神经网络模型在后续研究中的应用提供参考。创新点:1.提出燃烧光热能量分级转化的概念,为燃烧光热能量分质分级转化系统提供研究基础;2.从辐射能量利用的角度研究煤粉燃烧的辐射能流特性;3.不局限于实验报告,基于实验数据探究2种建模方法,揭示神经网络模型的优势。方法:1.在一维管式炉反应器上进行实验,探究不同燃烧条件下煤粉富氧燃烧的辐射能流特征;2.基于辐射传热理论,通过半经验模型描述煤粉在固定床中燃烧的辐射能流;3.训练神经网络模型来描述实验结果,通过对比2种方法来揭示神经网络模型在预测结果方面的优势。结论:1.固定床煤燃烧过程中的挥发分及煤烟会降低辐射能;可利用低挥发分燃料以及增大氧浓度来提高火焰辐射能比例。2.较高的燃烧温度是提升燃烧辐射能比例最重要的因素;实践中可以通过采用高热值燃料以及烟气回热等方法来提高燃烧温度。3.多联产半焦燃烧辐射能比例高于原煤;可通过煤热解多联产技术与半焦燃烧光热能量分级利用相结合的方式构成新的煤炭高效清洁利用系统。4.人工神经网络不但可以对实验结果进行建模,还能够很好地预测未知工况结果,因此值得在更多的后续研究中使用。
Abstract
mu de :1.cong fu she neng li yong jiao du chu fa ,tan jiu yi wei gu ding chuang mei fen fu yang ran shao de fu she neng liu te xing ,wei gu ti ran liao ran shao neng liang fen zhi fen ji zhuai hua ying yong di gong can kao ;2.dui bi yan jiu ban jing yan mo xing yu ren gong shen jing wang lao mo xing zhe liang chong jian mo fang fa ,wei ren gong shen jing wang lao mo xing zai hou xu yan jiu zhong de ying yong di gong can kao 。chuang xin dian :1.di chu ran shao guang re neng liang fen ji zhuai hua de gai nian ,wei ran shao guang re neng liang fen zhi fen ji zhuai hua ji tong di gong yan jiu ji chu ;2.cong fu she neng liang li yong de jiao du yan jiu mei fen ran shao de fu she neng liu te xing ;3.bu ju xian yu shi yan bao gao ,ji yu shi yan shu ju tan jiu 2chong jian mo fang fa ,jie shi shen jing wang lao mo xing de you shi 。fang fa :1.zai yi wei guan shi lu fan ying qi shang jin hang shi yan ,tan jiu bu tong ran shao tiao jian xia mei fen fu yang ran shao de fu she neng liu te zheng ;2.ji yu fu she chuan re li lun ,tong guo ban jing yan mo xing miao shu mei fen zai gu ding chuang zhong ran shao de fu she neng liu ;3.xun lian shen jing wang lao mo xing lai miao shu shi yan jie guo ,tong guo dui bi 2chong fang fa lai jie shi shen jing wang lao mo xing zai yu ce jie guo fang mian de you shi 。jie lun :1.gu ding chuang mei ran shao guo cheng zhong de hui fa fen ji mei yan hui jiang di fu she neng ;ke li yong di hui fa fen ran liao yi ji zeng da yang nong du lai di gao huo yan fu she neng bi li 。2.jiao gao de ran shao wen du shi di sheng ran shao fu she neng bi li zui chong yao de yin su ;shi jian zhong ke yi tong guo cai yong gao re zhi ran liao yi ji yan qi hui re deng fang fa lai di gao ran shao wen du 。3.duo lian chan ban jiao ran shao fu she neng bi li gao yu yuan mei ;ke tong guo mei re jie duo lian chan ji shu yu ban jiao ran shao guang re neng liang fen ji li yong xiang jie ge de fang shi gou cheng xin de mei tan gao xiao qing jie li yong ji tong 。4.ren gong shen jing wang lao bu dan ke yi dui shi yan jie guo jin hang jian mo ,hai neng gou hen hao de yu ce wei zhi gong kuang jie guo ,yin ci zhi de zai geng duo de hou xu yan jiu zhong shi yong 。
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论文作者分别是来自Journal of Zhejiang University-Science A(Applied Physics & Engineering)的，发表于刊物Journal of Zhejiang University-Science A(Applied Physics & Engineering)2019年06期论文，是一篇关于辐射能流论文,固定床论文,富氧燃烧论文,人工神经网络论文,能量分质分级转化论文,Journal of Zhejiang University-Science A(Applied Physics & Engineering)2019年06期论文的文章。本文可供学术参考使用，各位学者可以免费参考阅读下载，文章观点不代表本站观点，资料来自Journal of Zhejiang University-Science A(Applied Physics & Engineering)2019年06期论文网站，若本站收录的文献无意侵犯了您的著作版权，请联系我们删除。
标签：辐射能流论文; 固定床论文; 富氧燃烧论文; 人工神经网络论文; 能量分质分级转化论文; Journal of Zhejiang University-Science A(Applied Physics & Engineering)2019年06期论文;