13 citations · 14 across the 3 of their papers we have counts for
6 papers
Revisiting Tensor Basis Neural Networks for Reynolds stress modeling: application to plane channel and square duct flows
Jiayi Cai, Pierre-Emmanuel Angeli, Jean-Marc Martinez +2
Several Tensor Basis Neural Network (TBNN) frameworks aimed at enhancing turbulence RANS modeling have recently been proposed in the literature as data-driven constitutive models f…
Conformal Approach To Gaussian Process Surrogate Evaluation With Coverage Guarantees
Edgar Jaber, Vincent Blot, Nicolas Brunel +6
Gaussian processes (GPs) are a Bayesian machine learning approach widely used to construct surrogate models for the uncertainty quantification of computer simulation codes in indus…
Sensitivity Analyses of a Multi-Physics Long-Term Clogging Model For Steam Generators
Edgar Jaber, Vincent Chabridon, Emmanuel Remy +4
Long-term operation of nuclear steam generators can result in the occurrence of clogging, a deposition phenomenon that may increase the risk of mechanical and vibration loadings on…
Machine learning with data assimilation and uncertainty quantification for dynamical systems: a review
Sibo Cheng, Cesar Quilodran-Casas, Said Ouala +14
Data Assimilation (DA) and Uncertainty quantification (UQ) are extensively used in analysing and reducing error propagation in high-dimensional spatial-temporal dynamics. Typical a…
Reynolds Stress Anisotropy Tensor Predictions for Turbulent Channel Flow using Neural Networks
Jiayi Cai, Pierre-Emmanuel Angeli, Jean-Marc Martinez +2
The Reynolds-Averaged Navier-Stokes (RANS) approach remains a backbone for turbulence modeling due to its high cost-effectiveness. Its accuracy is largely based on a reliable Reyno…
Reduced-order modeling for parameterized large-eddy simulations of atmospheric pollutant dispersion
Bastien X Nony, Mélanie Rochoux, Thomas Jaravel +1
Mapping near-field pollutant concentration is essential to track accidental toxic plume dispersion in urban areas. By solving a large part of the turbulence spectrum, large-eddy si…