UQ and data-driven techniques for turbulent flow problems
|Dates:||7 March 2023|
|Times:||15:00 - 16:00|
|What is it:||Seminar|
|Organiser:||Department of Mechanical, Aerospace and Civil Engineering|
|Who is it for:||University staff, External researchers, Families, Adults, Alumni, Current University students, General public|
|Speaker:||Dr. Saleh Rezaeiravesh|
Abstract of the lecture:
Several challenges are involved in scale-resolving simulations of wall-bounded turbulent flows which appear in various engineering applications. The main challenges include high computational cost of the simulations especially at high Reynolds numbers, and also the uncertainties in the simulations outputs due to various factors. In this regard, the present talk discusses our recent progress on three connected topics: i) uncertainty quantification (UQ) and sensitivity analysis for parametric and time-averaging uncertainties in turbulence simulations, ii) Bayesian optimization, and iii) multifidelity models (MFMs) for UQ and prediction of quantities of interest in turbulent flows.
About the speaker:
Saleh Rezaeiravesh is a lecturer in Engineering Simulation and Data Science at the Department of Fluids and Environment/MACE, the University of Manchester. He earned his PhD in Scientific Computing (Numerical Analysis) from Uppsala University, Sweden, in 2018 and then joined the FLOW Centre at KTH Royal Institute of Technology, Sweden. His research interests include the development and application of uncertainty quantification (UQ) and data-driven techniques such as Bayesian optimization and multifidelity models to turbulent flow problems, as well as, high-fidelity scale-resolving simulation of turbulence and turbulence time series analysis. He has been leading the development of UQit, a Python package for UQ in computational fluid dynamics (CFD), and actively participated in European projects.
Dr. Saleh Rezaeiravesh
Role: Lecturer in Engineering Simulation and Data Science
Organisation: University of Manchester
Travel and Contact Information
Engineering Building A, Room 1A.023