A dimensionless model for smoke backflow length prediction with mobile ventilation in tunnel fire

IF 5.1 3区工程技术 Q2 ENERGY & FUELS

Thermal Science and Engineering Progress Pub Date : 2024-11-02 DOI:10.1016/j.tsep.2024.103026

Yanming Ding , Jiaoxin Mei , Xiang Li , Kaihua Lu , Changhai Li

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引用次数: 0

Abstract

The smoke in tunnel fire is the main factor that causes casualties. Mobile ventilation technology can effectively control smoke and improve ventilation conditions inside the tunnel through mobile fans, especially emergency rescue. Smoke backflow is an important feature of tunnel fires and the smoke backflow length is used as the evaluation index of the smoke control effect. In this paper, a prediction model of smoke backflow length is studied under mobile ventilation unit (MVU) in tunnel fires. The dimensional analysis method is adopted to deduce the expressions of smoke backflow length. Based on the numerical simulation validated by the experiments, the effects of MVU location, fan flow and fire source heat release rate on backflow length are investigated, respectively. Furthermore, artificial neural network is used for data augmentation to obtain the smoke backflow length in a wider range of data. Eventually, the optimal location for mobile fan is established, and a new dimensionless prediction model of smoke backflow length with MVU is proposed. This model is helpful to provide guidance for smoke control in tunnel fire during emergency rescue.

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隧道火灾中移动通风的烟气回流长度预测无量纲模型

隧道火灾中的烟雾是造成人员伤亡的主要因素。移动通风技术可以通过移动风机有效控制烟雾，改善隧道内的通风条件，尤其是应急救援。烟气倒流是隧道火灾的一个重要特征，烟气倒流长度是烟气控制效果的评价指标。本文研究了隧道火灾中移动通风装置（MVU）下烟气倒流长度的预测模型。采用尺寸分析法推导烟气倒流长度的表达式。在数值模拟的基础上，通过实验验证，分别研究了 MVU 位置、风机流量和火源热释放率对回流长度的影响。此外，还利用人工神经网络进行数据增强，以获得更大数据范围内的烟气回流长度。最终，确定了移动风机的最佳位置，并提出了一种新的带 MVU 的烟气倒流长度无量纲预测模型。该模型有助于为隧道火灾应急救援中的烟雾控制提供指导。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Thermal Science and Engineering Progress Chemical Engineering-Fluid Flow and Transfer Processes

CiteScore

7.20

自引率

10.40%

发文量

327

审稿时长

41 days

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