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A stochastic inverse heat transfer problem is formulated to infer the transient heat flux, treated as an unknown Neumann boundary condition. Therefore, an Ensemble-based Simultaneous Input and State Filtering as a Data Assimilation…

Numerical Analysis · Mathematics 2024-03-01 Kabir Bakhshaei , Umberto Emil Morelli , Giovanni Stabile , Gianluigi Rozza

We address a question concerning the issue of existence to a Boussinesq type system with a heat source. The problem is studied in the whole two dimensional plane and the heat source is a measure transported by the flow. For arbitrary…

Analysis of PDEs · Mathematics 2020-01-22 Piotr B. Mucha , Liutang Xue

We consider the Virtual Element discretization of the Navier-Stokes equations coupled with the heat equation where the viscosity depends on the temperature. We present the Virtual Element discretization of the coupled problem, show its…

Numerical Analysis · Mathematics 2022-05-03 Paola Francesca Antonietti , Giuseppe Vacca , Marco Verani

In this work, we consider an optimal control problem subject to a nonlinear PDE constraint and apply it to the regularized $p$-Laplace equation. To this end, a reduced unconstrained optimization problem in terms of the control variable is…

Numerical Analysis · Mathematics 2020-06-29 Bernhard Endtmayer , Ulrich Langer , Ira Neitzel , Winnifried Wollner , Thomas Wick

A posteriori estimates for mixed finite element discretizations of the Navier-Stokes equations are derived. We show that the task of estimating the error in the evolutionary Navier-Stokes equations can be reduced to the estimation of the…

Numerical Analysis · Mathematics 2016-12-23 Javier de Frutos , Bosco García-Archilla , Julia Novo

Inverse problems use physical measurements along with a computational model to estimate the parameters or state of a system of interest. Errors in measurements and uncertainties in the computational model lead to inaccurate estimates. This…

Numerical Analysis · Mathematics 2015-02-02 Vishwas Rao , Adrian Sandu

We consider the Navier-Stokes-Fourier system governing the motion of a general compressible, heat conducting, Newtonian fluid driven by random initial/boundary data. Convergence of the stochastic collocation and Monte Carlo numerical…

Numerical Analysis · Mathematics 2024-01-12 Eduard Feireisl , Maria Lukacova-Medvidova , Bangwei She , Yuhuan Yuan

Motivated by the need for energetically consistent climate models, the Boussinessq-Coriolis (BC) equations are studied with a focus on the averaged vertical heat transport, ie the Nusselt number. A set of formulae are derived by which…

Analysis of PDEs · Mathematics 2025-06-02 Roland Welter

This paper is concerned with the initial-boundary value problem to 2D magnetohydrodynamics-Boussinesq system with the temperature-dependent viscosity, thermal diffusivity and electrical conductivity. First, we establish the global weak…

Analysis of PDEs · Mathematics 2017-02-28 Dongfen Bian , Jitao Liu

In this paper we propose a continuous data assimilation (downscaling) algorithm for a two-dimensional B\'enard convection problem. Specifically we consider the two-dimensional Boussinesq system of a layer of incompressible fluid between two…

Analysis of PDEs · Mathematics 2017-02-01 Aseel Farhat , Evelyn Lunasin , Edriss S. Titi

In the present work we propose and analyze a fully coupled virtual element method of high order for solving the two dimensional nonstationary Boussinesq system in terms of the stream-function and temperature fields. The discretization for…

Numerical Analysis · Mathematics 2023-03-22 L. Beirão da Veiga , D. Mora , A. Silgado

This work presents the application of density-based topology optimisation to the design of three-dimensional heat sinks cooled by natural convection. The governing equations are the steady-state incompressible Navier-Stokes equations…

Fluid Dynamics · Physics 2018-09-14 Joe Alexandersen , Ole Sigmund , Niels Aage

This paper proposes a higher-order multiscale computational method for nonlinear thermo-electric coupling problems of composite structures, which possess temperature-dependent material properties and nonlinear Joule heating. The innovative…

Numerical Analysis · Mathematics 2025-01-24 Hao Dong , Zongze Yang , Yufeng Nie

In this paper, the boundary flex control problem of non stationary equation governing the coupled mass and heat flow of a viscous incompressible fluid in a generalized Boussinesq approximation by assuming that viscosity and heat…

Analysis of PDEs · Mathematics 2012-07-18 Gol Kim

We develop an optimization-based approach to the problem of reconstructing temperature-dependent material properties in complex thermo-fluid systems described by the equations for the conservation of mass, momentum and energy. Our goal is…

Fluid Dynamics · Physics 2013-04-11 Vladislav Bukshtynov , Bartosz Protas

The paper is concerned with a posteriori error bounds for a wide class of numerical schemes, for $n\times n$ hyperbolic conservation laws in one space dimension. These estimates are achieved by a "post-processing algorithm", checking that…

Numerical Analysis · Mathematics 2021-04-28 Alberto Bressan , Maria Teresa Chiri , Wen Shen

We study the Navier-Stokes-Darcy-Boussinesq system that models the thermal convection of a fluid overlying a saturated porous medium in a general decomposed domain. In both two and three spatial dimensions, we first prove the existence of…

Analysis of PDEs · Mathematics 2024-08-21 Xiaoming Wang , Hao Wu

A new technique of residual-type a posteriori error analysis is developed for the lowest-order Raviart-Thomas mixed finite element discretizations of convection-diffusion-reaction equations in two- or three-dimension. Both centered mixed…

Numerical Analysis · Mathematics 2015-03-26 Shaohong Du , Xiaoping Xie

This paper focuses on a posteriori error estimates for a pressure-robust finite element method, which incorporates a divergence-free reconstruction operator, within the context of the distributed optimal control problem constrained by the…

Numerical Analysis · Mathematics 2026-01-30 Jingshi Li , Jiachuan Zhang

In application areas where data generation is expensive, Gaussian processes are a preferred supervised learning model due to their high data-efficiency. Particularly in model-based control, Gaussian processes allow the derivation of…

Machine Learning · Computer Science 2021-01-15 Armin Lederer , Jonas Umlauft , Sandra Hirche
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