Background and objectives:
Design and operation of modern combustion engines faces the need to combine high efficiency with low pollutants emissions, even under real trafic conditions. Computational Fluid Dynamics has become a powerful tool in design and analysis of internal engines. Many numerical models exist, each having a range of applicability, computational cost and accuracy. Consequently, CFD experts involved in internal engine simulations, in addition to usual CFD skills, need specific insight and knowledge in spray and combustion modelling in order to conduct thorough analysis. The present course addresses this need.
In this course, the participants will learn the best practices in CFD of internal engines. They will discover how to select models, how to validate numerical simulations, and which accuracy to expect. Spray injection, flame ignition, flame propagation, pollutants emissions, efficiency and knock effects, including complex fuels, are critical issues in the design of modern internal engines and a major part of the course is devoted to them.
The lectures of this course, all by well-known experts in the field, cover from basics to applications.
The course is held at the occasion of the publication of the ERCOFTAC Best Practice Guide on CFD of combustion, a copy of which will be provided to the participants.
In the course also the link will be made with the CFD programs and cases of interest for the participants. As a result, the course provides the means for CFD analysts to significantly enhance their use of commercial and open-source CFD software for combustion engineering applications.
Prof. U. Mass (Karlsruhe Institute of Technology, Germany)
Prof. F. Di Mare (Technical University Darmstadt, Germany)
Prof. A. Sadiki (Technical University Darmstadt, Germany)
Prof. B. Boehm (Technical University Darmstadt, Germany)
Prof. C. Hasse (Technical University Freiburg, Germany)
Dr. O. Laget (IFPEN, France).
Fees; ERCOFTAC Members €595 Non-members €895,
Please note Course fees do NOT include accommodation