CFD Simulation and ANN Prediction of Hydrogen Leakage and Diffusion Behavior in a Hydrogen Refuelling Station

IF 4.3 3区 工程技术 Q2 ENERGY & FUELS International Journal of Energy Research Pub Date : 2024-07-15 DOI:10.1155/2024/8910533
Jinsheng Xiao, Nianfeng Xu, Yaze Li, Guodong Li, Min Liu, Liang Tong, Chengqing Yuan, Xuefang Li, Tianqi Yang
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Abstract

Hydrogen refueling station (HRS) is an essential part of the infrastructure for promoting the hydrogen economy. Since hydrogen is a flammable and explosive gas, hydrogen released from high-pressure hydrogen storage equipment in HRS will likely cause combustion or explosion accidents. Studying high-pressure hydrogen leakage in HRS is a prerequisite for promoting hydrogen fuel cell vehicles and HRS. A computational fluid dynamics (CFD) model of an HRS in a demonstrated project in Ningbo, China, was established on the ANSYS FLUENT software platform. The CFD model for hydrogen leakage simulation was validated by comparing the simulation results with experimental data in the literature. The effects of the direction and mass flow rate of the hydrogen leakage jet, as well as the direction and speed of ambient wind, on hydrogen diffusion behavior were investigated. The spreading distances of the flammable hydrogen cloud were predicted using an artificial neural network for horizontal leakage. The results show that the jet direction strongly affected the flammable cloud flow. The greater the mass flow rate of the leak, the greater the hydrogen dispersion distance and the volume of the flammable hydrogen cloud. At a hydrogen leakage mass flow rate of 4.5589 kg/s, the volume of the hydrogen flammable cloud reached 6,140.46 m3 at 30 s of leakage. The ambient wind speed has complicated effects on spreading the flammable cloud. The wind makes the flammable cloud move in certain directions, and the higher wind speed accelerates the diffusion of the flammable gas in the air. The results of the study can be used as a reference for the study of high-pressure hydrogen leakage in HRS and will play an important role in the safe demonstration of the studied project.

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加氢站氢气泄漏和扩散行为的 CFD 仿真和 ANN 预测
加氢站(HRS)是促进氢经济发展的基础设施的重要组成部分。由于氢气是易燃易爆气体,加氢站内高压储氢设备释放的氢气很可能引发燃烧或爆炸事故。研究氢燃料电池系统中的高压氢泄漏是推广氢燃料电池汽车和氢燃料电池系统的先决条件。在 ANSYS FLUENT 软件平台上,建立了中国宁波示范项目中氢燃料电池车的计算流体动力学(CFD)模型。通过将模拟结果与文献中的实验数据进行比较,验证了氢气泄漏模拟的 CFD 模型。研究了氢气泄漏射流的方向和质量流量以及环境风的方向和速度对氢气扩散行为的影响。利用水平泄漏的人工神经网络预测了可燃氢气云的扩散距离。结果表明,喷射方向对可燃氢云的流动有很大影响。泄漏质量流量越大,氢气扩散距离和可燃氢气云的体积就越大。在氢气泄漏质量流量为 4.5589 kg/s 时,泄漏 30 s 时可燃氢气云的体积达到 6 140.46 m3。环境风速对可燃云的扩散有复杂的影响。风会使可燃云向特定方向移动,而较高的风速会加速可燃气体在空气中的扩散。研究结果可作为 HRS 高压氢气泄漏研究的参考,并将对所研究项目的安全论证起到重要作用。
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来源期刊
International Journal of Energy Research
International Journal of Energy Research 工程技术-核科学技术
CiteScore
9.80
自引率
8.70%
发文量
1170
审稿时长
3.1 months
期刊介绍: The International Journal of Energy Research (IJER) is dedicated to providing a multidisciplinary, unique platform for researchers, scientists, engineers, technology developers, planners, and policy makers to present their research results and findings in a compelling manner on novel energy systems and applications. IJER covers the entire spectrum of energy from production to conversion, conservation, management, systems, technologies, etc. We encourage papers submissions aiming at better efficiency, cost improvements, more effective resource use, improved design and analysis, reduced environmental impact, and hence leading to better sustainability. IJER is concerned with the development and exploitation of both advanced traditional and new energy sources, systems, technologies and applications. Interdisciplinary subjects in the area of novel energy systems and applications are also encouraged. High-quality research papers are solicited in, but are not limited to, the following areas with innovative and novel contents: -Biofuels and alternatives -Carbon capturing and storage technologies -Clean coal technologies -Energy conversion, conservation and management -Energy storage -Energy systems -Hybrid/combined/integrated energy systems for multi-generation -Hydrogen energy and fuel cells -Hydrogen production technologies -Micro- and nano-energy systems and technologies -Nuclear energy -Renewable energies (e.g. geothermal, solar, wind, hydro, tidal, wave, biomass) -Smart energy system
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