PAVING THE WAY FOR FUTURE ACCURATE CFD
Date: 22th-24th September 2021
Location: Toulouse, France (or online from anywhere)
The simulation of turbulent flows using CFD methods has progressed rapidly over the last decades and has given rise to significant changes in the design processes of many areas of fluid mechanics. However, despite over a century of research, the modelling of turbulence and transition in industrial relevant configurations is still far from being achieved successfully.
With the advent and growing availability of large scale computing power and facilities, a new area of turbulence research is opening with the ability to perform reliable high-fidelity large-eddy simulations (LES) and direct numerical simulations (DNS) for industrial relevant flow configurations.
This availability is opening up exciting new avenues towards understanding and modeling turbulence and transition by:
i. Direct generation of High-Fidelity LES/DNS to fully predict complex flows, by capturing most or all of the relevant turbulent scales and interactions
ii. Analyzing in depth the underlying physics, supported in particular by new technologies of Machine Learning
iii. Confronting available turbulence and transition models, identifying their deficiencies, improving the range of validity of current models and generate new ones.
This novel approach of High-Fidelity LES/DNS data has attracted many researchers in recent years, stimulated by other emerging areas, as Big Data, Artificial Intelligence (AI) and Machine Learning (ML), providing new efficient methodologies for interrogating and investigating very large data sets .
The HiFiLeD Symposium will be focusing on all aspects related to these objectives, ranging from issues concerning the complexity, reliability, accuracy and uncertainties in generating the High-Fidelity LES/DNS data, to their application towards turbulence and transition modelling.
It will include progress on the underlying high-order numerical methods (HOMs), innovative approaches for CPU acceleration for LES and DNS, exploitation of massive parallel architectures, efficient post-processing on massive parallel hardware, innovative machine learning methods, as well as experimental data.
Moreover, the Symposium offers the opportunity to communicate and exchange knowledge for academic researchers, graduate students, industrial engineers, as well as industrial R&D managers and consultants working in the fields of turbulent flow modelling, simulations, measurements and multidisciplinary CFD applications.
MORE INFORMATION HERE
Call for contributions - Keynote speakers - Mini-Symposia - Registration