在通风条件下的地下实验室中,对扩散行为的因素分析和GA-BP-ANN预测
Baochun Li1, Minghua Chi2, Minglun Gao1
1China Construction Third Bureau Group Co., Ltd., Wuhan, 430064, People's Republic of China.
Scientific reports
|June 11, 2024
概括
实验室气泄漏在地下实验室等狭窄空间中构成严重风险. 这项研究使用计算流体动力学和人工智能来模拟扩散,以预测风险并为通风系统设计提供信息.
科学领域:
- 化学安全工程 化学安全工程
- 环境监测 环境监测
- 计算流体动力学的流体动力学.
背景情况:
- 在实验室中是必不可少的,但在狭窄的空间,特别是地下的泄漏,存在重大安全隐患.
- 地下实验室缺乏自然通风,加剧了与积累相关的风险.
研究的目的:
- 调查在封闭的地下环境中影响气扩散的通风和泄漏因素.
- 根据已识别的因素,开发度和扩散特征的预测模型.
主要方法:
- 利用计算流体动力学 (CFD) 来模拟来自中国金平地下实验室 (CJPL) 液坦克泄漏的扩散.
- 采用拉丁式超立方采样 (LHS) 来参数化通风 (输入/输出位置,速度) 和泄漏 (孔尺寸,质量流速) 因素.
- 开发并验证了人工神经网络 (ANN) 模型,特别是GA-BP-ANN,用于预测度和扩散行为.
主要成果:
- 详细分析通风参数和泄漏特征如何影响度场和扩散模式.
- 参数化影响因素和采样参数空间使用LHS进行全面分析.
- GA-BP-ANN模型在预测度和扩散特征方面表现出高的准确性和识别率.
结论:
- 开发的模型有效地根据通风和泄漏因素预测的度和扩散行为.
- 这些发现为优化地下实验室的通风系统设计提供了理论基础,以减轻气泄漏风险.
- 这项研究提高了实验人员在封闭的,通风不良的环境中的安全协议.
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