通风系统对地下车库内氢气泄漏扩散影响的数值模拟研究

戴君豪, 杨石刚, 杨亚, 方秦

太阳能学报 ›› 2026, Vol. 47 ›› Issue (6) : 607-615.

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太阳能学报 ›› 2026, Vol. 47 ›› Issue (6) : 607-615. DOI: 10.19912/j.0254-0096.tynxb.2025-0190

通风系统对地下车库内氢气泄漏扩散影响的数值模拟研究

  • 戴君豪1, 杨石刚1, 杨亚2, 方秦1
作者信息 +

NUMERICAL SIMULATION OF VENTILATION SYSTEM EFFECTS ON HYDROGEN LEAKAGE AND DISPERSION IN UNDERGROUND PARKING GARAGE

  • Dai Junhao1, Yang Shigang1, Yang Ya2, Fang Qin1
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文章历史 +

摘要

以地下车库和丰田Mirai二代车型为对象,利用FLACS软件模拟地下车库内氢燃料电池汽车发生意外泄漏的情况,研究通风方案、通风口朝向及换气次数的影响规律,研究结果表明:吊顶与通风系统协同作用能完全将车库内可燃气云排出,氢气去除效率最高;上排风的氢气去除效率高于其他通风口朝向;当换气次数为24次/h,等效化学计量云体积峰值较无通风时下降22.5%,可燃气云排出时间较12次/h缩短43.4%,进一步提高换气次数对可燃气云排出效果提升有限。

Abstract

This study employed FLACS software to simulate hydrogen leakage scenarios involving a Toyota Mirai Gen II fuel cell vehicle in underground parking garages, to systematically investigate the impacts of ventilation scheme, vent orientation, and ventilation rate. Results indicate that the combined action of the suspended ceiling and ventilation system completely removes the flammable gas clouds, achieving the highest hydrogen removal efficiency. Upward-exhaust ventilation is more effective than other orientations. At a ventilation rate of 24 air changes per hour (ACH), the peak equivalent stoichiometric cloud volume is 22.5% lower than that for no ventilation, and the cloud removal time is 43.4% shorter than that at 12 ACH. Further increases in ventilation rate provide limited enhancement in flammable cloud evacuation efficiency.

关键词

氢气 / 通风 / 数值模拟 / 地下车库 / 氢燃料电池汽车 / 泄漏扩散

Key words

hydrogen / ventilation / numerical simulation / underground parking garage / hydrogen fuel cell vehicle / leakage and dispersion

引用本文

导出引用
戴君豪, 杨石刚, 杨亚, 方秦. 通风系统对地下车库内氢气泄漏扩散影响的数值模拟研究[J]. 太阳能学报. 2026, 47(6): 607-615 https://doi.org/10.19912/j.0254-0096.tynxb.2025-0190
Dai Junhao, Yang Shigang, Yang Ya, Fang Qin. NUMERICAL SIMULATION OF VENTILATION SYSTEM EFFECTS ON HYDROGEN LEAKAGE AND DISPERSION IN UNDERGROUND PARKING GARAGE[J]. Acta Energiae Solaris Sinica. 2026, 47(6): 607-615 https://doi.org/10.19912/j.0254-0096.tynxb.2025-0190
中图分类号: TK91   

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基金

国家重点研发计划(2020TFB20103300); 江苏省自然科学基金(BK20180081)

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