Juan J. Alonso
Vance D. and Arlene C. Coffman Professor
Department of Aeronautics & Astronautics
Plenary Title: Using Probabilistic CFD Methods for Aircraft Certification by Analysis
The length of the flight certification phase of modern commercial transports and the staggering costs associated are motivating a strong interest in utilizing the result of high-fidelity simulations as an alternative to flight testing. For this to become a reality, the results of high-fidelity simulations must have the same level of confidence/uncertainty that is typically associated with flight tests. Unfortunately, the current state of the art only provides deterministic predictions of the derived quantities of interest, leaving little chance that the FAA or EASA would accept the results as proof of compliance. We must endow simulations with estimates of numerical errors and uncertainties. This talk discusses our efforts to develop probabilistic aerodynamic databases that can be consumed by 6-dof simulation techniques to provide both distributions and levels of confidence of the quantities of interest required. Two certification maneuvers of interest are discussed, the emergency descent and the pitch-recovery maneuvers, both of which pose significant challenges to state-of-the-art RANS predictions. Our hope is that methodologies of this sort can pave the way for more pervasive use of Certification by Analysis in the future transport fleet.
Biography: Juan J. Alonso is the Vance D. and Arlene C. Coffman Professor of Aeronautics and Astronautics at Stanford University. Prof. Alonso is the founder and director of the Aerospace Design Laboratory (ADL) where he specializes in the development of high-fidelity computational analysis and design methodologies to enable the creation of realizable and efficient aerospace systems. He is the author of over 200 technical publications on the topics of computational aircraft and spacecraft design, multi-disciplinary optimization, fundamental numerical methods, and high-performance parallel computing. During the period spanning 2006-09, Prof. Alonso was the Director of the NASA Fundamental Aeronautics Program in Washington, DC. In that position he was responsible for the entire portfolio of aerospace vehicle and vehicle technology research for the agency in the subsonic rotary wing, subsonic fixed wing, supersonic, and hypersonic regimes, with particular emphasis on the energy and fuel efficiency of the aviation enterprise and its environmental impact. He is the recipient of several AIAA Best Paper Awards, the NASA Exceptional Public Service Medal, the NASA ARMD Associate Administrator Award, and the AIAA Stanford Chapter Professor of the Year award (8 times). Prof. Alonso has served in the NASA Advisory Council, the Secretary of Transportation’s Future of Aviation Advisory Committee, the FAA Administrator’s Management Advisory Council, and as an Independent Expert in the ICAO/CAEP fuel burn, noise, and emissions technology goals evaluation. Prof. Alonso and the ADL are responsible for the development of the open-source SU2 analysis and design environment, intended for use by the worldwide community to advance the state-of-the-art in numerical optimization of fluid flows. Prof. Alonso earned his Ph.D. in Mechanical and Aerospace Engineering at Princeton University and his B.S. degree at the Massachusetts Institute of Technology.
Professor, Department of Mechanical Engineering
Tokyo University of Science
Plenary Title: Multi-physics CFD simulation of particle deposition with a hybrid grid- and particle-based method
Particle deposition occurs in a jet engine, when a jet engine is operated in a particulate environment like volcanic ash clouds. The ingested ash is melted in a combustion chamber and becomes a small droplet because the temperature exceeds the melting point of ash. Since turbine components are colder than the droplet, some droplets adhere and accrete on the surfaces. The particle deposition does not only leads to deterioration of the turbine performance, but also shorten the life time of the turbine. Therefore, the prediction and understanding of the particle deposition phenomena are of importance from the engineering viewpoint. The objectives of the present study are to model the particle deposition phenomenon with a hybrid grid- and particle-based method, and to investigate the particle deposition around the leading edge of a modeled high-pressure turbine vane. The finite difference method was used as the grid-based method to simulate the flow field, the E-MPS method was employed as the particle-based method to simulate the solidification of droplets, and these two methods were effectively coupled. In the presentation, the detail of numerical procedures will be explained, and then some typical results will be introduced.
Professor, Interfaculty Initiative in Information Studies
The Institute of Industrial Science, The University of Tokyo
Plenary Title: Challenges towards clinical applications: Computational hemodynamics for cerebral circulation
Biography: Prof. Oshima's main research area has been computational hemodynamics, particularly medical-image based modeling and blood flow simulation for cardiovascular diseases such as atherosclerosis. She has been also working on flow visualization and measurements using micro PIV (Particle Image Velocimetry) technique for blood flow related problems. She has been the director of the Office for the Next Generation at IIS since 2011, working on STEAM (Science, Technology, Engineering, Arts, and Mathematics) education for the young generation. In 2017 Prof. Oshima was the president of the Japan Society of Mechanical Engineers.
Corporate Research & Development
Plenary Title: Development of Floating Type Ocean Current Turbine for Kuroshio Current
Biography: Dr. Masafumi Kawai finished Master Course of Applied Mechanics in Kyushu University in 1983. Then he joined IHI as a research scientist of fluid engineering. He received Ph.D. from Kyushu University in 2008. He has been working as the Chief Engineer in IHI Corporate R & D since 2013. He served as the Chairman of the JSME FED in 2014.
His main R & D activity is the solution of various flow-related problems encountered in the development, design and operation stages in the heavy industry.