Publications associées à On uncertainty quantification in hydrogeology and hydrogeophysics

Publications associées (28)

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

EPFL2024

Design of an Open-Loop Pile-Oscillation Program in the CROCUS Reactor

Andreas Pautz, Vincent Pierre Lamirand, Axel Guy Marie Laureau, Thomas Jean-François Ligonnet

As a follow-up to the CEA-EPFL PETALE experimental program on stainless steel nuclear data, the EPFL initiated an open-loop pile-oscillation experimental program in the CROCUS reactor: BLOOM. A reproduction of the critical experiments of PETALE, the progra ...

2024

A cut-cell method for the numerical simulation of 3D multiphase flows with strong interfacial effects

Marco Picasso, Alexandre Caboussat, Alexandre Masserey, Julien Hess

We present a numerical model for the approximation of multiphase flows with free surfaces and strong interfacial effects. The model relies on the multiphase incompressible Navier-Stokes equations, and includes surface tension effects on the interfaces betw ...

Academic Press Inc Elsevier Science2024

Adaptive Finite Elements with Large Aspect Ratio. Application to Aluminium Electrolysis

Paride Passelli

The goal of this work is to use anisotropic adaptive finite elements for the numerical simulation of aluminium electrolysis. The anisotropic adaptive criteria are based on a posteriori error estimates derived for simplified problems. First, we consider an ...

EPFL2024

Swift : a modern highly parallel gravity and smoothed particle hydrodynamics solver for astrophysical and cosmological applications

Yves Revaz, Yannick Michael Bahé, Loïc Hausammann, Mladen Ivkovic

Numerical simulations have become one of the key tools used by theorists in all the fields of astrophysics and cosmology. The development of modern tools that target the largest existing computing systems and exploit state-of-the-art numerical methods and ...

2024

Computation of sensitivity coefficients in fixed source simulations with SERPENT2

Andreas Pautz, Mathieu Hursin

Within the scope of the implementation of a nuclear data pipeline aiming at producing the best possible evaluated nuclear data files, a major point is the production of relevant sensitivity coefficients when including integral benchmark information. Thanks ...

Elsevier Science Sa2024

High-Resolution Modeling Without Computation Slowdown for PETALE in CROCUS

Andreas Pautz, Vincent Pierre Lamirand, Axel Guy Marie Laureau, Thomas Jean-François Ligonnet

In a collaboration between Ecole Polytechnique Fédérale de Lausanne (EPFL) and CEA, in the fall of 2020, the experimental Programme d’Étude en Transmission de l’Acier Lourd et ses Eléments (PETALE) was successfully carried out in the CROCUS reactor of EPFL ...

2024

Toward Reliable Human Pose Forecasting With Uncertainty

Alexandre Massoud Alahi, Saeed Saadatnejad, Taylor Ferdinand Mordan

Recently, there has been an arms race of pose forecasting methods aimed at solving the spatio-temporal task of predicting a sequence of future 3D poses of a person given a sequence of past observed ones. However, the lack of unified benchmarks and limited ...

2024

Experimental Investigation on Size-Effect of Rubble Stone Masonry Walls Under In-Plane Horizontal Loading: Overview and Preliminary Results

Katrin Beyer, Savvas Saloustros

Rubble stone masonry is a common construction typology of historical city centres and vernacular architecture. While past earthquakes have shown that it is one of the most vulnerable masonry construction typologies, there are few experimental campaigns giv ...

2024

ZigZag: Universal Sampling-free Uncertainty Estimation Through Two-Step Inference

Minh Hieu Lê, Nikita Durasov

Whereas the ability of deep networks to produce useful predictions on many kinds of data has been amply demonstrated, estimating the reliability of these predictions remains challenging. Sampling approaches such as MC-Dropout and Deep Ensembles have emerge ...

2024

Pseudo-Three-Dimensional Analytical Model of Linear Induction Motors for High-Speed Applications

Mario Paolone, André Hodder, Simone Rametti, Lucien André Félicien Pierrejean

Literature on linear induction motors (LIMs) has proposed several approaches to model the behavior of such devices for different applications. In terms of accuracy and fidelity, field analysis-based models are the most relevant. Closed-form or numerical so ...

2024

Analytical Model of Single-Sided Linear Induction Motors for High-Speed Applications

Mario Paolone, André Hodder, Simone Rametti, Lucien André Félicien Pierrejean

This article describes a field-based analytical model of single-sided linear induction motors (SLIMs) that explicitly considers the following effects altogether: finite motor length, magnetomotive force mmf space harmonics, slot effect, edge effect, and ta ...

IEEE2024

A fully-coupled highly-parallelized geomechanical simulator for assessing induced seismicity

Jean-François Molinari, Brice Tanguy Alphonse Lecampion, Guillaume Anciaux, Nicolas Richart, Emil Gallyamov

Induced seismicity caused by anthropogenic modification of the subsurface effective stress state has been observed in a number of industrial applications -- from hydrocarbon extraction (e.g., Groningen [1]), drilling waste-water disposal (e.g., [2]) to the ...

2023

Traversing Time Dependent Light Fields for Daylight Glare Evaluation

Stephen William Wasilewski

To understand how daylight gives shape and life to architectural spaces, whether existing or imagined, requires quantifying its dynamism and energy. Maintaining these details presents a challenge to simulation and analysis methods that flatten data into di ...

EPFL2023

Model-based constraints for trajectory determination of quad-copters: Design, calibration & merits for direct orientation

Jan Skaloud, Davide Antonio Cucci, Kenneth Joseph Paul

This paper proposes a novel method to improve georeferencing of airborne laser scanning by improved trajectory estimation using Vehicle Dynamic Model. In Vehicle Dynamic Model (VDM), the relationship between the dynamics of the platform and control inputs ...

2023

Reliability analysis and partial safety format calibration considering the characteristics of the resistance of reinforced concrete structures

Qianhui Yu

Every engineering calculation is an approximation of reality, with inevitable uncertainties involved. This fact implies that a reliability verification accounting for the uncertainties is a necessary step in the design and assessment of structures. Nowaday ...

EPFL2023

lifex-ep: a robust and efficient software for cardiac electrophysiology simulations

Alfio Quarteroni, Francesco Regazzoni, Stefano Pagani

Background: Simulating the cardiac function requires the numerical solution of multi-physics and multi-scale mathematical models. This underscores the need for streamlined, accurate, and high-performance computational tools. Despite the dedicated endeavors ...

BMC2023

Rock-Flow Cell Parameters Evaluation Using Ultrasound Doppler Velocimetry

Giovanni De Cesare

This work presents a study of two-phase flow generated inside a rock-flow cell setup. It is characterized by a pipe section filled with fluid (oil in our studies) that is put into oscillation around its mass centre by an electric motor. This type of appara ...

2023

Euclid preparation XXIV. Calibration of the halo mass function in λ(ν)CDM cosmologies

Maurizio Martinelli, Frédéric Courbin, Georges Meylan, Slobodan Ilic, Gianluca Castignani, Austin Chandler Peel

Euclid's photometric galaxy cluster survey has the potential to be a very competitive cosmological probe. The main cosmological probe with observations of clusters is their number count, within which the halo mass function (HMF) is a key theoretical quanti ...

EDP SCIENCES S A2023

RaFSIP: Parameterizing ice multiplication in models using a machine learning approach

Athanasios Nenes, Paraskevi Georgakaki

Accurately representing mixed-phase clouds (MPCs) in global climate models (GCMs) is critical for capturing climate sensitivity and Arctic amplification. Secondary ice production (SIP), can significantly increase ice crystal number concentration (ICNC) in ...

2024