报 告 人：代尔夫特理工大学 Richard P. Dwight教授

邀 请 人：韩忠华教授

时    间：2019年11月25日

地    点：友谊校区航空楼A817（星期一）上午9:30-11:00

题    目：The anti-fairing: Drag reduction at junctions

摘    要：Interference drag from junctions represents about 5-10% of the total cruise drag of modern commercial air-transport, primarily originating from the wing-fuselage, tail-fuselage, and nacelle-pylon-wing junctions. Starting from a blank-slate, we applied adjoint shape-optimization procedures within a RANS model, to design a fairing for reducing drag in this class of flows. The result was an "anti-fairing", a shallow depression in the fuselage that appeared to reduce the interference drag by about ~10-40%. This talk will recount the history over the past 4 years of our experimental, numerical (including LES) and theoretical investigations of this highly surprising result, and our attempts to confirm it, establish its magnitude and a working mechanism, and finally apply it to real applications.

报告人简介：

Richard P. Dwight教授，2006年获得英国曼切斯特大学博士学位; 2009年起任职于代尔夫特理工大学航空航天工程学院空气动力学系副教授；2017年起任职于荷兰数学与计算机科学中心（CWI）客座教授。Richard P. Dwight教授在计算流体力学、机器学习、气动优化设计、代理优化方法、伴随方程方法、不确定优化方法等领域均有建树。

飞行器复杂流动与控制引智基地全英文课程—Prof. Richard P. Dwight: Uncertainty Quantification and Inverse problems

应887700线路检测手机版“飞行器复杂流动与控制学科创新引智基地”韩忠华教授邀请代尔夫特理工大学Richard P. Dwight教授将于11月27日在我校针对Uncertainty Quantification and Inverse problems进行课程培训，热情欢迎感兴趣的老师和同学们报名参加！

联系人：柳斐

电  话：18729537605

微  信：ltwbtf

授课专家：代尔夫特理工大学Richard P. Dwight教授

邀请人：887700线路检测手机版流体力学系 韩忠华教授

时  间：2019年11月27日 9:00-12:00 14:30-17:30

地  点：友谊校区航空楼A817

课程题目：Uncertainty Quantification and Inverse problems

        课程简介：

This course is a short introduction to the field of uncertainty quantification, with emphasis on techniques for model calibration and large-scale inverse problems with the Bayesian framework.  Lectures are complemented by 3 tutorial exercises in Python, which exploit the theory learned.  Prerequisites are: (1) a first-course on probability/statistics (though this material will be briefly refreshed in the first lecture), (2) experience with Python (and numpy) programming would be very beneficial for the tutorials.  If 1) is missing I recommend reading Chapter 4 of the textbook Ralph C. Smith "Uncertainty Quantification" in advance of the course.

       授课专家简介：

Richard P. Dwight教授，2006年获得英国曼切斯特大学博士学位; 2009年起任职于代尔夫特理工大学航空航天工程学院空气动力学系副教授；2017年起任职于荷兰数学与计算机科学中心（CWI）客座教授。Richard P. Dwight教授在计算流体力学、机器学习、气动优化设计、代理优化方法、伴随方程方法、不确定优化方法等领域均有建树。

            Uncertainty Quantification and Inverse problems课程安排