Dr Hao Zhang
School of Metallurgy
Northeastern University, China
Dr Hao Zhang obtained his Ph.D at Technical University of Catalonia and is now an Associate Professor at Northeastern University, China. His research interests currently focus on the computational particle technology mainly in four fields: (1) Process metallurgy; (2) Air pollution controlling and environmental protection; (3) Efficient and quality conversion of renewable energy and (4) Drying technology. He has had profound experience of using various particle-based numerical schemes on >10 projects. He has acquired 21 authorized invention patents, published 70 high quality papers in total (>1900 citations and H index is 21 based on Google scholar) and most of them are high quality papers in reputable international journals including 3 ESI highly cited papers. In recent years, he has also been awarded with various significant research grants including the projects financially supported by the National Key R&D Program of China and National Natural Science Foundation of China.
Title: Theoretical, Experimental and Numerical Investigations on Movement and Heat Transfer Mechanisms of Non-spherical Particles in Blast Furnace Raceway
Abstract: Investigations of experimental and numerical are conducted to explore the changing laws of blast furnace (BF) raceway morphology and pressure drop. A theoretical correlation about raceway size is established containing the particle shape influence. Experimental data show that there are five typical stages for the pressure drop during the raceway formation. The closer the aspect ratio (Ar) of particle to 1, the bigger the raceway size and the wider the particle moving band will be. When the raceway is in stable stage, the pressure drop can be ascribed to the cooperative action of the bed height, inlet gas velocity and Ar. Numerical results reveal that the formation of large raceway for sphere-like particle is due to the small drag and contact forces in this system. The contact forces in the prolate particle system are very large and thus result in a small raceway. Finally, the influence of particle shape is employed to improve a raceway size predictive correlation which can increase the average calculational accuracy by 3.4%.