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An intrinsic property of almost any physical measuring device is that it makes observations which are slightly blurred in time. We consider a nudging-based approach for data assimilation that constructs an approximate solution based on a…

Analysis of PDEs · Mathematics 2018-09-05 Michael S. Jolly , Vincent R. Martinez , Eric J. Olson , Edriss S. Titi

A constructive numerical approximation of the two-dimensional unsteady stochastic Navier-Stokes equations of an incompressible fluid is proposed via a pseudo-compressibility technique involving a parameter $\epsilon$. Space and time are…

Numerical Analysis · Mathematics 2022-05-02 Jad Doghman

By means of a unifying measure-theoretic approach, we establish lower bounds on the Hausdorff dimension of the space-time set which can support anomalous dissipation for weak solutions of fluid equations, both in the presence or absence of…

Analysis of PDEs · Mathematics 2024-07-29 Luigi De Rosa , Theodore D. Drivas , Marco Inversi

We positively answer Question 2.2 and Question 2.3 in [Bru\`e, De Lellis, 2023] in dimension $4$ by building new examples of solutions to the forced $4d$ incompressible Navier-Stokes equations, which exhibit anomalous dissipation, related…

Analysis of PDEs · Mathematics 2026-02-24 Carl Johan Peter Johansson , Massimo Sorella

We consider stationary solutions of the three dimensional Navier--Stokes equations (NS3D) with periodic boundary conditions and driven by an external force which might have a deterministic and a random part. The random part of the force is…

Analysis of PDEs · Mathematics 2007-05-23 Cyril Odasso

In this paper, we investigate the nonlinear stability of the Couette flow for the two-dimensional compressible Navier--Stokes equations at high Reynolds numbers ($Re$) regime. It was proved that if the initial data $(\rho_{in},u_{in})$…

Analysis of PDEs · Mathematics 2026-04-22 Minling Li , Chao Wang , Zhifei Zhang

We establish a solution theory for the incompressible Navier--Stokes--Fourier system with thermal noise, posed on the three-dimensional torus. While in the incompressible deterministic setting the equation for the velocity can be solved…

Probability · Mathematics 2026-03-30 Benjamin Gess , Max Sauerbrey , Zhengyan Wu

In this paper, both semidiscrete and fully discrete finite element methods are analyzed for the penalized two-dimensional unsteady Navier-Stokes equations with nonsmooth initial data. First order backward Euler method is applied for the…

Numerical Analysis · Mathematics 2026-04-16 Bikram Bir , Deepjyoti Goswami , Amiya K. Pani

We consider singular quasilinear stochastic partial differential equations (SPDEs) studied in \cite{FHSX}, which are defined in paracontrolled sense. The main aim of the present article is to establish the global-in-time solvability for a…

Probability · Mathematics 2021-06-03 Tadahisa Funaki , Bin Xie

We prove space-time decay estimates of suitable weak solutions to the Navier-Stokes Cauchy problem, corresponding to a given asymptotic behavior of the initial data of the same order of decay. We use two main tools. The first is a result…

Mathematical Physics · Physics 2016-03-23 Francesca Crispo , Paolo Maremonti

This paper deals with the Navier-Stokes system governing the evolution of a compressible barotropic fluid. We extend D. Hoff's intermediate regularity solutions framework by relaxing the integrability needed for the initial density which is…

Analysis of PDEs · Mathematics 2022-03-25 Didier Bresch , Cosmin Burtea

This paper is concerned with the global smooth non-vacuum solutions with large data to the Cauchy problem of the one-dimensional compressible Navier-Stokes equations with degenerate temperature dependent transport coefficients which satisfy…

Analysis of PDEs · Mathematics 2013-05-27 Hongxia Liu , Tong Yang , Huijiang Zhao , Qingyang Zou

The efficacy of a nudging data assimilation algorithm using higher order finite element interpolating operators is studied. Numerical experiments are presented for the 2D Navier-Stokes equations in two cases: shear flow in an annulus and a…

Numerical Analysis · Mathematics 2021-08-10 Michael S. Jolly , Ali Pakzad

This paper focuses on deriving optimal-order full moment error estimates in strong norms for both velocity and pressure approximations in the Euler-Maruyama time discretization of the stochastic Navier-Stokes equations with multiplicative…

Numerical Analysis · Mathematics 2025-10-10 Xiaobing Feng , Liet Vo

We propose a modification to the nonlinear term of the three-dimensional incompressible Navier-Stokes equations (NSE) in either advective or rotational form which "calms" the system in the sense that the algebraic degree of the nonlinearity…

Analysis of PDEs · Mathematics 2024-01-01 Matthew Enlow , Adam Larios , Jiahong Wu

This paper aims to investigate the numerical approximation of semilinear non-autonomous stochastic partial differential equations (SPDEs) driven by multiplicative or additive noise. Such equations are more realistic than autonomous SPDEs…

Numerical Analysis · Mathematics 2020-11-18 Jean Daniel Mukam , Antoine Tambue

We consider the inverse problem of retrieving aerosol extinction coefficients from Raman lidar measurements. In this problem the unknown and the data are related through the exponential of a linear operator, the unknown is non-negative and…

Numerical Analysis · Mathematics 2018-08-21 Giulia Denevi , Sara Garbarino , Alberto Sorrentino

The compressible Navier-Stokes-Allen-Cahn system models the motion of a mixture of two macroscopically immiscible viscous compressible fluids. In this paper, we are concerned with the large time behavior of solutions to the Cauchy problem…

Analysis of PDEs · Mathematics 2025-10-24 Dan Lei , Zhengzheng Chen

In this work, we prove a threshold theorem for the 2D Navier-Stokes equations posed on the periodic channel, $\mathbb{T} \times [-1,1]$, supplemented with Navier boundary conditions $\omega|_{y = \pm 1} = 0$. Initial datum is taken to be a…

Analysis of PDEs · Mathematics 2023-11-02 Jacob Bedrossian , Siming He , Sameer Iyer , Fei Wang

Uncertainty estimation for unlabeled data is crucial to active learning. With a deep neural network employed as the backbone model, the data selection process is highly challenging due to the potential over-confidence of the model…

Machine Learning · Computer Science 2024-02-14 Xingjian Li , Pengkun Yang , Yangcheng Gu , Xueying Zhan , Tianyang Wang , Min Xu , Chengzhong Xu