Ke Wang

College of Mechanical and Transportation Engineering, China University of Petroleum (Beijing)

Bio

Dr. Wang Ke is currently an Associate Professor at the College of Mechanical and Transportation Engineering of China University of Petroleum (Beijing), as well as the Deputy Director of the Department of Thermal Energy Engineering. He is recognized as a distinguished young talent by the university. He obtained his Ph.D. in 2012 from the State Key Laboratory of Multiphase Flow in Power Engineering at Xi'an Jiaotong University. From 2012 to 2016, he conducted postdoctoral research at Nanyang Technological University in Singapore and the Royal Institute of Technology in Sweden, engaging in teaching and research on the fundamentals of multiphase flow dynamics and heat and mass transfer. His research, which focuses on control of multiphase flow in pipeline transport, design and evaluation of novel heat exchangers, and analysis of pollutant dispersion following severe accidents, has led to a series of theoretical and applied innovations and breakthroughs. He has published over 30 papers in journals in his field.  His achievements have earned him two provincial and ministerial first-class awards in China.

Title

Prediction of Path and Diffusion of Leaked Crude Oil in Mountainous Area

Abstract

The China-Myanmar oil and gas pipeline traverses southwestern China, a region characterized by natural disasters and complex terrain. Operating a refined oil products pipeline in this challenging environment poses significant risks, including potential ruptures that could lead to spills. Such spills may cause environmental issues like soil degradation and water contamination, and increase the risk of explosions. Therefore, promptly predicting the trajectory of a refined oil spill is crucial for effective rescue operations, emergency resource management, and equipment protection. Traditional research methods primarily rely on CFD numerical simulations to predict the impact range of leak pollution. However, due to their extensive grid requirements and time-consuming iterative processes, CFD methods are impractical for emergency responses in pipeline leakage incidents. In contrast, the Smoothed Particle Hydrodynamics (SPH) algorithm, with its computational efficiency and accuracy, is considered capable of quickly predicting the spread patterns of leaked pollutants following a pipeline leak. In this research, the SPH method and Digital Elevation Modeling (DEM) are used to create realistic digital terrain models of mountainous regions and predict the spread of refined oil spills. To better capture the diffusion patterns of leaked pollutants in the context of mountainous geographical environments, we considered factors such as spill site location, terrain characteristics, surface vegetation, initial leakage velocity and direction, and oil adsorption