Guo Xiaolong
DC8: Experimental characterisation of ammonia ignition using nanosecond barrier discharges
My research within DT-HATS will explore decarbonisation pathways for heavy-duty transport using ammonia and hydrogen, employing a combination of experiments, simulations, and machine learning for efficient system optimisation. My role involves the experimental characterisation of ammonia ignition and combustion driven by nanosecond barrier discharge. Using a CVCC to replicate engine environments, I will study the fundamental processes of ammonia mixing, ignition, and flame propagation.
My research addresses this challenge by replacing high-dimensional lookup tables with a deep-learning-based surrogate model. The model will learn thermodynamic relationships from precomputed datasets and provide fast property predictions during CFD runtime. Implemented within the CONVERGE CFD framework, this approach aims to maintain the accuracy of detailed thermodynamic models while drastically reducing computational cost, enabling efficient simulations of complex H₂/NH₃ combustion processes.
Supervisor Prof. Zhao Hua hosted by
1st secondment: industrial hosted by
About me
I obtained my Beng. Naval Architecture and Marine Engineering from Shanghai Jiao Tong University, Shanghai, China, in 2023. As part of my MPhil. in Naval Architecture and Marine Engineering, Shanghai Jiao Tong University, Shanghai, China, my research focused on multi-objective co-optimisation of compression ratio and combustion chamber geometry for ammonia-diesel dual-fuel engines.
My research focuses on the performance optimisation of ammonia-fuelled engines, the development of high-efficiency and clean combustion technologies, and the fundamental physics of ammonia combustion. I am currently shifting my research focus toward fundamental combustion mechanisms to deepen the comprehensive understanding of ammonia fuel, which will provide critical support for its engineering application and performance optimisation. Driven by a steadfast commitment to the decarbonisation of the transportation sector, I aim to deliver high-fidelity empirical data to underpin digital twin modeling and advance the development of sustainable power systems.
I follow the motto: The scientist merely explores that which exists, while the engineer creates what has never existed before. (Theodore von Kármán)