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Incorporating Deep Bagging Ensemble Method as a Surrogate Model for Simulating Hyper-Concentrated Sediment-Laden Flows

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On the Capability of Wall-Modeled Large Eddy Simulations to Predict Particle Dispersion in Complex Turbulent Flows

Mohamed Aly Hashem Mohamed Sayed

Predicting particle transport in turbulent flows has a plethora of applications, some of which are: the transport of atmospheric aerosols, the deposition of blood cells in the arteries of human bodies and the atomization of fuel droplets in combustion cham ...

EPFL2022

This thesis focuses on the development and validation of a reduced order technique for cardiovascular simulations. The method is based on the combined use of the Reduced Basis method and a Domain Decomposition approach and can be seen as a particular imple ...

EPFL2021

Physics Informed Neural Networks for Surrogate Modelling and Inverse Problems in Geotechnics

Finite elements methods (FEMs) have benefited from decades of development to solve partial differential equations (PDEs) and to simulate physical systems. In the recent years, machine learning (ML) and artificial neural networks (ANN) have shown great pote ...

2021

Numerical simulation of sediment dynamics with free surface flows

Arwa Mrad

We present a numerical model for the simulation of 3D mono-dispersed sediment dynamics in a Newtonian flow with free surfaces. The physical model is a macroscopic model for the transport of sediment based on a sediment concentration with a single momentum ...

EPFL2021

When Is Amplification Necessary for Composition in Randomized Query Complexity?

Mika Tapani Göös

Suppose we have randomized decision trees for an outer function f and an inner function g. The natural approach for obtaining a randomized decision tree for the composed function (f∘ gⁿ)(x¹,…,xⁿ) = f(g(x¹),…,g(xⁿ)) involves amplifying the success probabili ...

Schloss Dagstuhl - Leibniz-Zentrum für Informatik2020

Stochastic Frequency Masking to Improve Super-Resolution and Denoising Networks

Sabine Süsstrunk, Majed El Helou, Ruofan Zhou

Super-resolution and denoising are ill-posed yet fundamental image restoration tasks. In blind settings, the degradation kernel or the noise level are unknown. This makes restoration even more challenging, notably for learning-based methods, as they tend t ...

2020

Regularity In Time Of Holder Solutions Of Euler And Hypodissipative Navier-Stokes Equations

Maria Colombo, Luigi De Rosa

In this work we investigate some regularization properties of the incompressible Euler equations and of the fractional Navier-Stokes equations where the dissipative term is given by (-Delta)(alpha) for a suitable power alpha is an element of (0, 1/2) (the ...

SIAM PUBLICATIONS2020

Méthodes numériques liées à la distribution d'alumine dans une cuve d'électrolyse d'aluminium

Thomas Frédéric Hilke

Metallic aluminium plays a key role in our modern economy. Primary metallic aluminium is produced by the transformation of aluminium oxide using the Hall-Héroult industrial process. This process, which requires enormous quantities of energy, consists in pe ...

EPFL2019

High-Order Accurate Conservative Finite Difference Methods For Vlasov Equations In 2D+2V

Stephan Brunner

This manuscript discusses discretization of the Vlasov-Poisson system in 2D+2V phase space using high-order accurate conservative finite difference algorithms. One challenge confronting direct kinetic simulation is the significant computational cost associ ...

SIAM PUBLICATIONS2019

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In the past decade, model order reduction (MOR) has been successful in reducing the computational complexity of elliptic and parabolic systems of partial differential equations (PDEs). However, MOR of hyperbolic equations remains a challenge. Symmetries an ...

Springer Verlag2018