学术活动发布与订制系统

Worldwide airline traffic continues to grow at a much faster pace than the world Gross Domestic Product. In order to sustain that growth, commercial airplanes’ environment impact from greenhouse gas emission and noise must be dramatically reduced. A new generation of ‘green’ aircraft will be needed in the not so distant future. Major breakthroughs in aircraft configurations, engines and design tools are necessary. In this talk, I will argue that high-order methods will be a critical element of the next generation CFD tools. After that, we review the current state-of-the-art in high-order CFD methods, and identify several bottlenecks. Some recent progresses in these areas will be presented: (1) high-order mesh generation, (2) solution based hp-adaptations and (3) shock-capturing. The talk will conclude with several remaining pacing items, which need to be overcome before high-order methods are used routinely in aircraft design.

Z.J. Wang, Spahr Professor and Chair of Aerospace Engineering at the University of Kansas (KU), received his Ph.D. in Aerospace Engineering from the University of Glasgow in 1990. Then he conducted post-doctoral research in Glasgow and Oxford before joining CFD Research Corporation in Huntsville, Alabama in 1991 as a Research Engineer, and later becoming a Technical Fellow. In 2000, he joined the faculty of Michigan State University as an Associate Professor of Mechanical Engineering. In 2005 he returned to Aerospace Engineering at ISU. In 2012 he joined KU’s Aerospace Engineering Department. His research areas include adaptive high-order methods for the Navier-Stokes equations, algorithm and flow solver development for structured and unstructured, overset and adaptive Cartesian grids, computational aeroacoustics and electromagnetic, large eddy simulation of transitional and bio-inspired flow problems, high performance computing on CPU and GPU clusters, geometry modeling and grid generation. He is an Associate Editor of the AIAA Journal. He was awarded the degree of Doctor of Science in Engineering by the University of Glasgow in 2008.

Most fluid flows we encounter are turbulent, which occurs due to the strong destabilizing inertial effect compared to the smoothing, viscous effect (the ratio of the strength of the two mechanisms is measured by the Reynolds number). To date, despite very impressive progresses in the modeling and controlling of engineering flows, our understanding of turbulence is still limited. Traditionally, experimental study of turbulence has been almost exclusively in the Eulerian frame, i.e., in a coordinate system fixed in the laboratory frame. The last 15 years witnessed significant development in Lagrangian measurement techniques, i.e. following ‘fluid particles’ that move with the fluid in the turbulent flow field. The new perspective resulted from these measurements revealed many interesting properties of turbulence and advanced our understanding, but also posed intriguing questions. In this talk, we will first review briefly the image-based Lagrangian Particle Tracking (LPT) technique developed at Cornell University, Ithaca, USA, and the Max Planck Institute of Dynamics and Self-Organization (MPIDS), Göttingen, Germany. I will then report some recent and ongoing work at MPIDS for which the LPT method provided essential information. Examples include a new view of the alignment between vorticity and strain, and the role of pressure gradient in the balance of kinetic energy following fluid particles.