Influence of wind on natural smoke and heat exhaust system performance in fire conditions-Reference-Cited by-同舟云学术

Influence of wind on natural smoke and heat exhaust system performance in fire conditions

Published:2017-05 Issue: Volume:164 Page:44-53
ISSN:0167-6105
Container-title:Journal of Wind Engineering and Industrial Aerodynamics
language:en
Short-container-title:Journal of Wind Engineering and Industrial Aerodynamics

Author:

Węgrzyński Wojciech,Krajewski Grzegorz

Publisher

Elsevier BV

Subject

Mechanical Engineering,Renewable Energy, Sustainability and the Environment,Civil and Structural Engineering

Reference36 articles.

1. ANSYS, 2014. ANSYS Fluent 14.5.0 - Technical Documentation.

2. 50 years of computational wind engineering: past, present and future;Blocken;J. Wind Eng. Ind. Aerodyn.,2014

3. BSI, 2003. BS 7974 Part 4: Components for Smoke and Heat Control Systems. Functional Recommendations and Calculation Methods for Smoke and Heat Exhaust Ventilation Systems, Employing Steady-state Design Fires. Code of Practice.

4. BSI, 2004. The Application of Fire Safety Engineering Principles to Fire Safety Design of Buildings - Part 6: Human Factors: Life Safety Strategies - Occupant Evacuation, Behavious and Condition (Sub-system 6), PD 7974-6.

5. CEN, 2003. EN 12101-2:2003 Smoke and Heat Control Systems. Specification for Natural Smoke and Heat Exhaust Ventilators.

Cited by 30 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Scaled experiment and numerical study on the effect of a novel makeup air system on smoke control in atrium fires;Journal of Building Engineering;2024-10

2. Experimental study on the effect of makeup air inlets height on the fire combustion and smoke diffusion;Case Studies in Thermal Engineering;2024-09

3. Problems of operation of positive pressure ventilators on the basis of surveys of Polish officers of the State Fire Service;Scientific Reports;2024-05-11

4. Problems of operation of positive pressure ventilators on the basis of surveys of Polish officers of the State Fire Service;2024-01-17

5. Weather image-based short-term dense wind speed forecast with a ConvLSTM-LSTM deep learning model;Building and Environment;2023-07