Fast reconstruction of boiler numerical physical field based on proper orthogonal decomposition and conditional deep convolutional generative adversarial networks

IF 3.1 4区 工程技术 Q3 ENERGY & FUELS International Journal of Green Energy Pub Date : 2024-03-03 DOI:10.1080/15435075.2024.2322976
Jiajian Long, Meirong Dong, Jieheng Zhou, Youcai Liang, Jidong Lu
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Abstract

Obtaining real-time physical field data inside the boiler furnace is crucial for combustion diagnostics and optimization. In this work, we propose a fast reconstruction technique for the physical f...
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基于适当正交分解和条件深度卷积生成对抗网络的锅炉数值物理场快速重建技术
获取锅炉炉膛内的实时物理场数据对于燃烧诊断和优化至关重要。在这项工作中,我们提出了一种快速重建物理场数据的技术。
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来源期刊
International Journal of Green Energy
International Journal of Green Energy 工程技术-能源与燃料
CiteScore
6.60
自引率
9.10%
发文量
112
审稿时长
3.7 months
期刊介绍: International Journal of Green Energy shares multidisciplinary research results in the fields of energy research, energy conversion, energy management, and energy conservation, with a particular interest in advanced, environmentally friendly energy technologies. We publish research that focuses on the forms and utilizations of energy that have no, minimal, or reduced impact on environment, economy and society.
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