文献类型：期刊文献

英文题名：Gas dispersion modeling in stereoscopic space with obstacles using a novel spatiotemporal prediction network

作者：Chen, Shikuan[1];Du, Wenli[1];Wang, Xinjie[1];Wang, Bing[1];Cao, Chenxi[1];Peng, Xin[1]

机构：[1]East China Univ Sci & Technol, State Key Lab Ind Control Technol, Shanghai 200237, Peoples R China; East China Univ Sci & Technol, Minist Educ, Key Lab Smart Mfg Energy Chem Proc, Shanghai, Peoples R China

年份：2025

卷号：194

外文期刊名：COMPUTERS & CHEMICAL ENGINEERING

收录：;EI(收录号：20244917462956);WOS:【SCI-EXPANDED(收录号:WOS:001371844600001)】；

基金：This work was supported by National Natural Science Foundation of China (Basic Science Center Program: 61988101) , National Natural Science Foundation of China (Key Program: 62136003) , National Natural Science Foundation of China (62394345) , the Shanghai Committee of Science and Technology, China (Grant No. 22DZ1101500) and Shanghai Science and Technology Planning Program (23DZ2201700) .

语种：英文

外文关键词：Gas dispersion; 3DConvLSTM; Spatiotemporal prediction; Obstructed scene

摘要：Gas leakage can lead to catastrophic consequences on both the environment and human health. To mitigate these losses, it is imperative to develop accurate and efficient spatiotemporal models for gas dispersion. The gas diffusion process occurs in a 3-dimensional (3D) space, but most research has been confined to flat-plane scenarios, neglecting the stereoscopic distribution of gas concentrations. To address this issue, we propose a novel method that combines 3D convolution with along short-term memory neural network (3DConvLSTM) to forecast the 3D spatiotemporal concentration distribution of gas leakage in obstructed scenes. The 3D convolutional filters fully operate in the spatial domain, capturing spatial features horizontally and vertically. To provide data for the experiment, ethane leak scenarios with different sources, rates and wind directions are simulated by computational fluid dynamics (CFD). The results demonstrate that the 3DConvLSTM exhibits higher accuracy and requires fewer parameters, highlighting the effectiveness of the proposed method.