Brief

Mr Tianhang Zhang is currently a PhD student at the Hong Kong Polytechnic University. He received his Master’s Degree (2020) from College of Civil Engineering and Architecture (CCEA) at Zhejiang University (ZJU), where he performed studies on tunnel fire dynamics and tunnel ventilation. He also got his BE (2017) from Zhejiang University (ZJU).

​

Education

2017 - 2020, M.Eng, College of Civil Engineering and Architecture, Zhejiang University.

2013 - 2017, B.Eng, College of Civil Engineering and Architecture, Zhejiang University.

 

Research Interests

Compartment Fire, Smart Firefighting, Tunnel Fire and Ventilation.

​

Prizes and Awards​

• 2022 Outstanding Master thesis of China Highway and Transportation Society

• 2022 SFPE Grand Challenge Initiative Fellowship

• 2021 Best Paper Award at 9th ISTSS (International Symposium on Tunnel Safety and Security)

• 2020 Hong Kong PhD Fellowship Scheme, Research Grants Council (RGC) of Hong Kong

• 2018 National Scholarship, Ministry of Education of the People's Republic of China

• 2017 Outstanding Graduate of Zhejiang Province, Education Department of Zhejiang Province

• 2016 National Scholarship, Ministry of Education of the People's Republic of China

​

Publications

Journal:

1. Zhang T., Wang Z., Zeng Y., et al., (2022) Building Artificial-Intelligence Digital Fire (AID-Fire) System: A Real-scale Demonstration. Journal of Building Engineering (Under review)

2. Wu K., Wang G., Zhang T.*, (2022) Numerical study on plume bifurcation in longitudinally ventilated tunnel fires. Tunnelling and Underground Space Technology (Under review)

3. Wang, Z. , Zhang, T*. , Huang, X*. (2022) Predicting Real-time Fire Heat Release Rate based on Flame Images and Deep Learning. Proceedings of the Combustion Institute (In press)

4. Zhang, T. , Wang, Z. , Wong H. Y. et al. (2022) Real-time Forecast of Flashover based on Deep Learning Method in a Reduced-Scale Compartment Fire. Fire Safety Journal 

5. Jiang. Y#., Zhang, T.# , Liu S. et al. (2022) Full-scale fire tests in the underwater tunnel section model with sidewall smoke extraction. Tunnelling and Underground Space Technology 

6. Wang, Z. , Zhang, T. , Huang, X. (2022) Numerical Modeling of Compartment Fires: Ventilation Characteristics and Limitation of Kawagoe’s Law. Fire Technology 

7. Wang, Z., Zhang,T., Wu, X., Huang, X. (2022) Predicting Transient Building Fire Based on External Smoke Images and Deep Learning. Journal of Building Engineering

8. Zhang, T. , Wang G. , Li J. et al. (2021) Experimental study of back-layering length and critical velocity in longitudinally ventilated tunnel fire with various cross-sections. Fire Safety Journal.

9. Zhang, T. , Wang G. , Hu H. et al. (2021) Study on temperature decay characteristics of fire smoke backflow layer in tunnels with wide-shallow cross-section. Tunnelling and Underground Space Technology. 

10. Zhang, X. , Zhang, T. , Hou, Y. et al. (2019) Local loss model of dividing flow in a bifurcate tunnel with a small angle. Journal of Zhejiang University Science A：Applied Physics & Engineering.

11. Zhang X., Zhang T., Zhu K. et al. (2018) Numerical Research on the Mixture Mechanism of Polluted and Fresh Air at the Staggered Tunnel Portals[J]. Applied Sciences.

12. Zhang, X., Huang, Z. Zhang, T. et al. (2018) Scaled model test for ventilation characteristics of urban tunnels with Off-ramps[J]. China Journal of Highway and Transport.

13. Zhang, X., Zhang, T. ,Huang, Z. et al. (2018) Local loss and flow characteristic of dividing flow in bifurcated tunnel[J]. Journal of Zhejiang University (Engineering Science).

 

Conference:

1. Zhang T., Wang G., Huang Y.. et al., Experimental study of Backlayering Length and Critical Velocity in a Longitudinally Ventilated Tunnel with Wide-shallow Cross-section, 9th International Symposium on Tunnel Safety and Security, Online, May 2021 [Oral]

2. Zhang T., Wang Z., Huang X., Xiao F., Real-time Flashover Prediction in Compartment Fire via Computer Vision and AI. . Online, Dec 7 - 9 2021 [Oral]

3. T. Zhang, Z. Wang, X. Huang. Smart Prediction of Backdraft in Compartment Fire with Deep Learning. 39th International Symposium on Combustion, Vancouver, Canada, 25-29 Jul 2022. [Poster]

4. Zhang T., Wang Z., Zeng Y., Huang X., Smart Fire Monitoring System for High-Risk Facilities. SFPE 2022 Performance-Based Design Virtual Conference & Expo, Online, 23 - 25 March 2022  [Poster]

5. Zhang T., Wang Z., Huang X., Predicting the Development of Compartment Fire with Deep Learning. Chinese National Combustion Conference, online, 14 - 16 Jan 2022 [Poster]

6. Zhang T., Wang Z., Huang X., Xiao F.. Prediction of Flashover in Compartment Fire via Computer Vision and AI. 38th International Symposium on Combustion, online, 24-29 Jan 2021. [Poster]

​

​

Patents:

• Huang X., Zhang T., Wu X., et al., A system, device and method to collect the real-time 3D data from the fire scene, China Patent, Ref. No. 348710306.

• Wu K, Zhang T, Yin M et al. A fire tests system of underground traffic turning region. CN109712501A [P]. 2019.(Substantive examination)

• Wu K, Zhang T, Qian D et al. An experimental facility for fog penetration characteristic measure of light. CN107782532A [P]. 2018.(authorized)