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A posteriori analysis of the Chorin-Temam scheme for Stokes equations

Related publications (29)

Multi-Level Monte Carlo Methods for Uncertainty Quantification and Risk-Averse Optimisation

This work aims to study the effects of wind uncertainties in civil engineering structural design. Optimising the design of a structure for safety or operability without factoring in these uncertainties can result in a design that is not robust to these per ...

EPFL2022

Optimization and Real-Time Aspects of Aircraft Model-Based Navigation

Gabriel François Laupré

The Vehicle Dynamic Model (VDM) based navigation of fixed-wing drones determines the airborne trajectory in conjunction with Inertial Measurement Unit (IMU) sensors. Without Global Navigation Satellite Systems (GNSS) signals, this method estimates navigati ...

EPFL2022

Bayesian Methods for the Identification of Distribution Networks

Jean-Sébastien Hubert Brouillon, Giancarlo Ferrari Trecate, Pulkit Nahata

The increasing integration of intermittent renewable generation, especially at the distribution level, necessitates advanced planning and optimisation methodologies contingent on the knowledge of the admittance matrix, capturing the topology and line param ...

IEEE2021

A probabilistic finite element method based on random meshes: A posteriori error estimators and Bayesian inverse problems

Assyr Abdulle, Giacomo Garegnani

We present a novel probabilistic finite element method (FEM) for the solution and uncertainty quantification of elliptic partial differential equations based on random meshes, which we call random mesh FEM (RM-FEM). Our methodology allows to introduce a pr ...

ELSEVIER SCIENCE SA2021

Drift Estimation of Multiscale Diffusions Based on Filtered Data

Assyr Abdulle, Giacomo Garegnani, Andrea Zanoni, Grigorios A. Pavliotis

We study the problem of drift estimation for two-scale continuous time series. We set ourselves in the framework of overdamped Langevin equations, for which a single-scale surrogate homogenized equation exists. In this setting, estimating the drift coeffic ...

2023

Model order reduction based on functional rational approximants for parametric PDEs with meromorphic structure

Davide Pradovera

Many engineering fields rely on frequency-domain dynamical systems for the mathematical modeling of physical (electrical/mechanical/etc.) structures. With the growing need for more accurate and reliable results, the computational burden incurred by frequen ...

EPFL2021

Probabilistic and Bayesian methods for uncertainty quantification of deterministic and stochastic differential equations

Giacomo Garegnani

In this thesis we explore uncertainty quantification of forward and inverse problems involving differential equations. Differential equations are widely employed for modeling natural and social phenomena, with applications in engineering, chemistry, meteor ...

EPFL2021

A Modular Workflow for Model Building, Analysis, and Parameter Estimation in Systems Biology and Neuroscience

Daniel Keller, Andrii Stepaniuk

Neuroscience incorporates knowledge from a range of scales, from single molecules to brain wide neural networks. Modeling is a valuable tool in understanding processes at a single scale or the interactions between two adjacent scales and researchers use a ...

HUMANA PRESS INC2022

Separating Algorithms From Questions and Causal Inference With Unmeasured Exposures: An Application to Birth Cohort Studies of Early Body Mass Index Rebound

Mats Julius Stensrud, Aaron Leor Sarvet

Observational studies reporting on adjusted associations between childhood body mass index (BMI; weight (kg)/height (m)(2)) rebound and subsequent cardiometabolic outcomes have often not paid explicit attention to causal inference, including definition of ...

2021