Associate Professor at Dalian University of Technology, China
Dr. Shaohua Wu is a leading expert in reactive flow simulations and multiphase thermofluid systems, serving as an Associate Professor at the Dalian University of Technology. His academic journey spans globally, with research and teaching stints in China, Singapore, and the UK. With over a decade of experience in high-fidelity computational modeling and AI-driven simulations, he has established a significant footprint in both fundamental research and industrial applications in energy and combustion systems.
Profile
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Best Researcher Award
Dr. Wu is a highly deserving candidate for the “Best Researcher Award” due to his significant contributions to population balance modeling, soot dynamics, and AI-integrated combustion simulations. His innovative methodologies and high-impact publications have enhanced the understanding and design of clean energy systems. Moreover, his leadership in high-profile national and international projects demonstrates his continued influence and excellence in advancing research for energy sustainability and environmental impact reduction.
Education
Dr. Wu completed his Ph.D. in Thermodynamics from the National University of Singapore in 2018 with joint training at the University of Cambridge. He earned his M.A. and B.S. from Tianjin University in Power Machinery and Thermal Energy Engineering, respectively. His cross-institutional and interdisciplinary education has laid a robust foundation for his advanced simulation and modeling expertise in energy systems.
Experience
Currently an Associate Professor and Ph.D. supervisor, Dr. Wu leads a research group on multiphase reactive flows at Dalian University of Technology. He has served as a Research Fellow at the National University of Singapore and as a Research Associate at the University of Cambridge. His work spans industrial collaborations, governmental funded research, and innovative AI applications in energy systems.
Research Interest
Dr. Wu’s research centers around computational fluid dynamics for multiphase and reactive flow systems, particularly in propulsion and power generation. He integrates population balance modeling, chemical kinetics, and AI-enhanced simulation tools to investigate complex particulate and soot dynamics. His current focus includes machine learning-driven flow simulations, chemical mechanism reduction, and thermal system optimization.
Publications
Dr. Wu has authored numerous high-impact journal articles. Key recent publications include:
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“A tri-variate moment projection method for multi-dimensional particle population balance dynamics,” Journal of Aerosol Science, 2024.
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“An efficient data-driven approach for reactivity-controlled compression ignition engine,” International Journal of Hydrogen Energy, 2024.
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“Analysis of soot formation in diesel engines fueled by biofuel blends,” Fuel, 2024.
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“Efficient simulation of soot particle processes in diesel engines,” Applied Energy, 2020.
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“Development of a compact kinetic mechanism for furan biofuels combustion,” Fuel, 2021.
These works reflect his blend of deep theoretical insight and practical application, especially in clean combustion and particle modeling.