主管:中华人民共和国应急管理部
主办:应急管理部天津消防研究所
ISSN 1009-0029  CN 12-1311/TU

消防科学与技术 ›› 2021, Vol. 40 ›› Issue (6): 827-830.

• • 上一篇    下一篇

基于人工智能的外立面开口火溢流温度场预测

蒋亚强1,王自龙2,黄鑫炎2   

  1. 1. 应急管理部四川消防研究所,四川成都610036;2. 香港理工大学屋宇设备工程系,中国香港999077
  • 出版日期:2021-06-15 发布日期:2021-06-15
  • 通讯作者: 黄鑫炎,香港理工大学助理教授,博士生导师,主要从事火灾燃烧理论研究。
  • 作者简介:蒋亚强(1984-),男,应急管理部四川消防研究所助理研究员,主要从事建筑火灾防控、结构防火等研究,四川省成都市金牛区金科南路69 号,610036。
  • 基金资助:
    应急管理部消防救援局重点项目(2019XFGG10);香港研究资助局主题研发项目(T22-505/19-N)

Artificial intelligence based facade spilled flame temperature field prediction

JIANG Ya-qiang1, WANG Zi-long2, HUANG Xin-yan2   

  1. 1. Sichuan Fire Science and Technology Research Institute of MEM, Sichuan Chengdu 610036, China; 2. Department of Building Services Engineering, Hong Kong Polytechnic University, Hong Kong 999077, China
  • Online:2021-06-15 Published:2021-06-15

摘要: 为了明确外立面构造形式对开口火溢流的影响,对不同外立面构造条件下的开口火溢流进行实验研究,并对外立面火灾温度场的实时预测进行探索。通过不同翼墙间距和进深条件下的外立面火灾实验构建外立面火灾预测数据库,并将其应用于人工智能方法—卷积神经网络的训练和验证,建立不同外立面构造形式下开口溢流火焰温度的实时预测模型,为外立面构造形式的设计和外立面火灾防控提供支撑。

关键词: 开口火溢流, 外立面, 温度场, 卷积神经网络

Abstract: In order to clarify the influence of facade wing walls on spilled flame, an experimental study on the spilled flame under different facade wing wall conditions was conducted and the real- time prediction of the fire temperature field of the facade was predicted. The facade fire prediction database was constructed through facade fire experiments under different wingwall spacing and depth conditions, and applied to the training and validation of convolutional neural network (CNN), so as to establish a real-time prediction model for the flame temperature of spilled flame under different facade wing- wall conditions, and provide support for the design of facade construction forms and facade fire protection.

Key words: spilled flame, facade, temperature field, CNN