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Michele 教授学术报告会
澳门网上赌彩网址:2019-12-05 | 浏览次数: 次

题目:Towards predictive two-phase flow and combustion simulations in future energy systems

主讲:Michele Battistoni




主讲简介Michele Battistoni is an Associate Professor in the Department of Engineering at the University of Perugia in Italy. He received his MS and his PhD in Mechanical Engineering from the University of Perugia. He was appointed Visiting Professor at KAUST in 2019 and was also appointed Visiting Researcher and Mechanical Engineer at Argonne National Laboratory. His research and teaching interests lie in the areas of energy-thermal-fluid sciences, thermo-fluid dynamics, multiphase flow, CFD modeling, and energy conversion systems, with main applications to engines, advanced fuels and injection systems, bio-derived and alternative fuel sprays and combustion. He serves as SAE session organizer for the Fuel Injection and Sprays sessions, and he is actively involved in the Engine Combustion Network activities where he is leader of the primary atomization topic. He has been invited to give presentations at Argonne, Sandia and IFP-EN. He published 30+ journal papers and 40+ peer-reviewed conference papers.

主讲内容Accurate and robust two-phase flow, spray and combustion models, ensuring grid-convergent results, can facilitate predictive simulations of fuel air-mixing and subsequent combustion process in internal combustion engine and advanced propulsion systems. The first part of the talk provides an overview of novel spray Eulerian models, including sub-critical and supercritical regimes with real fluid thermodynamics. Results are compared against accurate experimental data, like x-ray radiography and interfacial area data. In a second part, some recent simulations of spark ignition engine combustion will also be presented, relating the effects of standard and advanced ignition systems with the engine stability behavior in lean conditions. The seminar will conclude with a discussion concerning the challenges with respect to further developing the two-phase and combustion models.


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