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Yanfu Zeng

PhD student (2021 - )

Research Center for Fire Safety Engineering

Building Services Engineering

Hong Kong Polytechnic University, Hong Kong

Email: yan-fu.zeng@connect.polyu.hk

Office: ZN 808

Biography:

Mr. Yanfu Zeng is currently a PhD student of Fire Safety Engineering at the Hong Kong Polytechnic University. He received his Master’s Degree (2018) from the University of Leeds and Bachelor’s Degree (2017) from Southwest Jiaotong University. Prior to joining PolyU, Yanfu was a fire engineer in the Arup Shenzhen Office (2018-2021), where he provided consulting services of fire safety design for projects, including super high building, train station, hotel, etc. His research interests include smart firefighting and performance-based fire engineering design. 

曾彦夫,香港理工大学火灾安全实验室博士研究生。彦夫于英国利兹大学获得硕士学位(2018),于西南交通大学获得学士学位(2017)。加入香港理工大学前,曾彦夫在奥雅纳工程顾问公司深圳办公室任消防工程师(2018-2021),为建筑消防设计方案提供咨询服务,参与项目包括超高层、综合交通枢纽、高铁站、商业综合体、酒店、办公楼等。曾彦夫的主要研究方向为智慧消防和消防性能化设计。

Background of Education:

  • 2021 - 2024 (Exp) Ph.D, in Building Environment and Energy Engineering, The Hong Kong Polytechnic University

  • 2023.07 - 2024.01, Visiting Ph.D. in Civil Engineering, Tsinghua University, China

  • 2017 - 2018, M.Sc. in Fire and Explosion Engineering, University of Leeds, UK.

  • 2013 - 2017, B.Eng. in Fire Protection Engineering, Southwest Jiaotong University, China.

Research Areas:

Smart Firefighting, Performance-based Fire Engineering Design, Fire Modeling

Prizes and Awards:

  • 2019 Certificate Excellent Paper Award (9th International Conference on Fire Science and Fire Protection Engineering)

  • 2016&2017 Outstanding Scholarship (Southwest Jiaotong University)

  • 2016 Top Award of The Competition of Fire Hazard Investigation and Solution Design (Southwest Jiaotong University)

Book Chapters:

  • Y. Zeng, X. Huang (2023) Smart Building Fire Safety Design Driven by Artificial Intelligence, Chapter 5, Interpretable Machine Learning for the Analysis, Design, Assessment, and Informed Decision Making for Civil Infrastructure (M.Z. Naser Ed.), Elsevier.

  • Y. Zeng, X. Huang (2023) Artificial Intelligence Powered Building Fire Safety Design Analysis. In X. Huang and W.C. Tam (eds) Intelligent Building Fire Safety and Smart Firefighting, Springer, Chapter 5. [Accepted, to be published in 2023]

Journal Publications:

 

Conference Papers:

  • Y. Zeng, Y Li, X Huang, Deep-learning Prediction on Fire-induced Temperature Field in Complex Room Layouts, 2023 China National Symposium on Combustion, Hefei, China, 12-15 October 2023. [Oral]

  • Y. Zeng, Y. Li, X. Huang, Floorplan-based Fire Detection Prediction via Generative Adversarial Network, 14th International Symposium on Fire Safety Science, Tsukuba, Japan, October 23-27, 2023. [Poster]

  • Y. Zeng, X. Huang, Intelligent ASET Assessment in Large Open Spaces via AI Fire Safety Design Software, 14th International Symposium on Fire Safety Science, Tsukuba, Japan, October 23-27, 2023. [Poster]

  • Y. Zeng, T. Zhang, X. Huang, Prediction of Fire-induced Ceiling Jet Characteristics Based on Artificial Intelligence. 14th Asia-Pacific Conference on Combustion, Kaohsiung, Taiwan, 14-18 May 2023. [Oral]

  • W. Cheung, Y. Zeng, X. Huang, A Study of Building Fire Safety Performance under Smoldering. 14th Asia-Pacific Conference on Combustion, Kaohsiung, Taiwan, 14-18 May 2023. [Oral]

  • Y. Zeng, H. Wong, X. Huang, Validation and Expansion of the Temperature Field on Fire and Smoke Ceiling Jet, 2022 China National Symposium on Combustion, Shanghai, China, December 8-11, 2022. [Poster]

  • Y. Zeng, L. Su, X. Zhang, X. Wu, X. Huang, Artificial Intelligent Method and Software for Building Fire Safety Performance-Based Design, 14th International Conference on Performance-Based Codes and Fire Safety Design Methods, March 23-25, 2022. [Oral]

  • Y. Zeng, K. Hon-Leung Wong and L. Chen, Numerical Study of the Performance of Automatic Sprinkler System in Dense Equipment Room, 2019 9th International Conference on Fire Science and Fire Protection Engineering (ICFSFPE), 2019, pp. 1-7, doi: 10.1109/ICFSFPE48751.2019.9055794. [Oral]

Patents:

  • X. Huang, X. Zhang, L. Su, X. Wu, Y. Zeng, A method for evaluating fire engineering designs based on artificial intelligence and the apparatus, China Patent, Application No. 202111317179X.

  • X. Huang, X. Wu, X. Zhang, Y. Zeng, A. Usmani, A methodology and system for fire monitoring based on artificial intelligence and digital twin, China Patent, Application No. 2021114957278.

 
 
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