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FlowZoom Project

Breaking Big Data barriers in numerical simulations to enable next-level flow and climate research

The Visualization group at KTH has received a large grant from SSF, the Swedish Foundation for Strategic Research. It is in close collaboration with Erwin Laure (KTH EECSC, KTH CST), Philipp Schlatter (KTH Mechanics), Rodrigo Cabellero and Gunilla Svensson (Stockholm University, MISU), and Ingrid Hotz (LiU).

The goal of this project is to break Big Data barriers in numerical simulations to enable next-level flow and climate research. The sheer size and complexity of the simulation data overwhelms current storage systems and post-processing analysis tools, which leads to data being underutilized and slows progress in flow and climate research.

The group will develop, implement and apply novel feature-based data analysis methods to be run alongside the simulation (in situ), which condense the main aspects of the data by several orders of magnitude. This is accompanied by sophisticated task scheduling to exploit the heterogeneous hardware of modern supercomputers, and interactive visualization of the analysis results. For the first time, this will enable an interactive zoom into the smallest spatial and temporal scales of the largest flow and climate simulations.

We apply our methods to target high-impact research questions. For the flow case, we address turbulent separation and wake-wake interactions; the former can directly lead to improved performance of vehicles and planes, the latter is crucial for the design of wind parks. For the climate case, we study the spatio-temporal development of extreme storms to assess the hazard posed to Sweden and other regions in Europe.

Dissemination of our results is ensured by implementing our novel methods in a widely spread, open source in situ library, and incorporating this library into three simulation packages actively used in Sweden.

This grant will finance 5 PhD students over 5 years, 3 of those at KTH.

Overview of the FlowZoom consortium, project structure and impact
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Belongs to: Computational Science and Technology
Last changed: Feb 17, 2020