Title:	Large-scale Simulations in Stability, Transition, Turbulence and Control
DNr:	SNIC 2019/2-5
Project Type:	SNIC Large Compute
Principal Investigator:	Dan Henningson <henning@mech.kth.se>
Affiliation:	Kungliga Tekniska högskolan
Duration:	2020-01-01 – 2021-01-01
Classification:	20306 10508 10501
Homepage:	http://www.flow.kth.se/
Keywords:

Abstract

We present our large-level request for computer time on high-performance computing (HPC) resources within the Swedish National Infrastructure for Computing (SNIC). The proposed projects by the research groups of the Linné FLOW Centre at KTH Mechanics are summarized. The group of applicants consists of a total of 5 senior researchers, 3 application experts and Postdocs and PhD students, i.e. a total of researchers. We actively promote collaboration within our large user group to facilitate HPC support, sharing of simulation methods and codes, and user experience. We have thus found it beneficial to apply for a single large allocation instead of multiple medium-level requests. In this proposal we describe our projects which rely on HPC resources, grouped into four main areas: 1) aeronautics; 2) wind turbines and geophysical flows; 3) dynamical systems, uncertainty quantification and machine learning; 4) fundamentals of transition and turbulence. Due to the large number of participants and collaborators, we do not list all individual projects, but rather give an overview of the general research directions. Our research makes use of various numerical codes, such as Simson, Nek5000, Edge-M and OpenFOAM, described in more detail in the proposal. Note that we get specific application support through the Swedish e-Science Research Centre (SeRC) in the form of three application experts, Dr.\ Niclas Jansson, Dr.\ Jing Gong and Dr.\ Adam Peplinski. In particular, the possibility to use different machines depending on job size and job characteristic is beneficial for the efficient usage of the available computer time; also having a good mix between computer centres has been helpful to us. We have thus found that, depending on problem size and code, Tetralith (NSC), Kebnekaise (HPC2N), Tegner and Beskow (PDC) are excellent choices.