The UPSCALE project will present a poster at the Machine Learning for Fluid Mechanics: Analysis, Modelling, Control and Closures event, organized by the von Karman Institute as part of its lecture series.
The research presented in the poster, and entitled Application of Physics Informed Machine Learning model for correcting RANS modeled Reynolds Stress Anisotropy, aims at enhancing the accuracy of the an-isotropic component of Reynolds Stress tensor (R) modeled by Reynolds Averaged Navier Stokes (RANS) based turbulence models using machine learning techniques.
The event will start on 24 February 2020, lasting until Friday 28 February. During these 4 days, the poster will be exhibited at the Free University of Brussels (ULB – Erasme Campus). Bhanu Prakash, who is involved in this research being conducted at the Computational fluid dynamics (CFD) team of Applus+ IDIADA, will also have the opportunity to make a short presentation of the conducted research to professors and attendees.
The event aims at providing a unified treatment of the machine learning tools that are now paving the way towards advanced methods for model order reduction, system identification, and flow control. The lectures will gather ideas and notions from various fields, starting from the data decompositions that were pioneered in fluid mechanics and moving towards machine learning methods that were initially developed in machine vision, pattern recognition, and artificial intelligence.
More information about the event and its location can be found here.