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Related papers: A physics-infused Immersed Boundary Method using o…

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This paper extends the ensemble Kalman filter (EnKF) for inverse problems to identify trending model coefficients. This is done by repeatedly inflating the ensemble while maintaining the mean of the particles. As a benchmark serves a…

Optimization and Control · Mathematics 2020-01-30 M. Schwenzer , G. Visconti , M. Ay , T. Bergs , M. Herty , D. Abel

Although data assimilation originates from control theory, the relationship between modern data assimilation methods in geoscience and model predictive control has not been extensively explored. In the present paper, I discuss that the…

Geophysics · Physics 2024-10-21 Yohei Sawada

We present hidden fluid mechanics (HFM), a physics informed deep learning framework capable of encoding an important class of physical laws governing fluid motions, namely the Navier-Stokes equations. In particular, we seek to leverage the…

Computational Engineering, Finance, and Science · Computer Science 2018-08-20 Maziar Raissi , Alireza Yazdani , George Em Karniadakis

Ensemble data assimilation methods such as the Ensemble Kalman Filter (EnKF) are a key component of probabilistic weather forecasting. They represent the uncertainty in the initial conditions by an ensemble which incorporates information…

Applications · Statistics 2018-10-17 Sylvain Robert , Daniel Leuenberger , Hans R. Künsch

A volume penalization-based immersed boundary technique is developed and thoroughly validated for fluid flow problems, specifically flow over bluff bodies. The proposed algorithm has been implemented in an Open Source Field Operation and…

Fluid Dynamics · Physics 2023-09-19 Prashant Kumar , Vivek Kumar , Di Chen , Yosuke Hasegawa

A hybrid sharp-interface immersed-boundary/front-tracking (IB/FT) method is developed for interface-resolved simulation of evaporating droplets in incompressible multiphase flows. A one-field formulation is used to solve the flow, species…

Fluid Dynamics · Physics 2025-10-30 Faraz Salimnezhad , Hasret Turkeri , Iskender Gokalp , Metin Muradoglu

This paper introduces a new immersed boundary (IB) method for viscous incompressible flow, based on a Fourier spectral method for the fluid solver and on the nonuniform fast Fourier transform (NUFFT) algorithm for coupling the fluid with…

Fluid Dynamics · Physics 2023-02-20 Zhe Chen , Charles S. Peskin

Ensemble Kalman Filtering (EnKF) is a popular technique for data assimilation, with far ranging applications. However, the vanilla EnKF framework is not well-defined when perturbations are nonlinear. We study two non-linear extensions of…

Machine Learning · Statistics 2024-09-24 Zachariah Malik , Romit Maulik

The hybrid wall-modeled large-eddy simulation (WMLES) and immersed boundary (IB) method offers significant flexibility for simulating high Reynolds number flows involving complex boundaries. However, the approximate boundary conditions…

Fluid Dynamics · Physics 2025-06-30 Zhideng Zhou , Fengshun Zhang , Xiaolei Yang

We present a novel moving immersed boundary method (IBM) and employ it in direct numerical simulations (DNS) of the closed-vessel swirling von Karman flow in laminar and turbulent regimes. The IBM extends direct-forcing approaches by…

Fluid Dynamics · Physics 2022-02-17 M. Houssem Kasbaoui , Tejas Kulkarni , Fabrizio Bisetti

Reliable prediction of turbulent flows is an important necessity across different fields of science and engineering. In Computational Fluid Dynamics (CFD) simulations, the most common type of models are eddy viscosity models that are…

Fluid Dynamics · Physics 2023-07-25 Minghan Chu , Weicheng Qian

The ensemble Kalman filter (EnKF) (Evensen, 2009) has proven effective in quantifying uncertainty in a number of challenging dynamic, state estimation, or data assimilation, problems such as weather forecasting and ocean modeling. In these…

This paper presents the machine learning-based ensemble conditional mean filter (ML-EnCMF) -- a filtering method based on the conditional mean filter (CMF) previously introduced in the literature. The updated mean of the CMF matches that of…

Machine Learning · Computer Science 2022-08-02 Truong-Vinh Hoang , Sebastian Krumscheid , Hermann G. Matthies , Raúl Tempone

We present an immersed boundary method to simulate the creeping motion of a rigid particle in a fluid described by the Stokes equations discretized thanks to a finite element strategy on unfitted meshes, called Phi-FEM, that uses the…

Numerical Analysis · Mathematics 2023-01-30 Michel Duprez , Vanessa Lleras , Alexei Lozinski

This work develops advanced numerical methods for free-surface simulations of polymer mixing processes, integrating a Volume of Fluid (VOF) interface-capturing approach with a non-conforming Immersed Boundary (IB) method to model two-phase…

We present a novel sampling-based method for estimating probabilities of rare or failure events. Our approach is founded on the Ensemble Kalman filter (EnKF) for inverse problems. Therefore, we reformulate the rare event problem as an…

Numerical Analysis · Mathematics 2021-12-15 Fabian Wagner , Iason Papaioannou , Elisabeth Ullmann

We present the implementation and validation of an immersed boundary volume penalization method in the computational fluid dynamics solver CODA (from ONERA, DLR, and Airbus). Our goal is to model and simulate turbulent fluid flows in…

The phase-field approach to brittle fracture provides a continuum framework for modeling crack initiation and propagation without explicit representation of discrete crack surfaces, provided the spatial discretization is fine enough to…

Computational Engineering, Finance, and Science · Computer Science 2026-03-11 Lucas Hermann , Ralf Jänicke , Knut Andreas Meyer , Ulrich Römer

In this paper we employ two implementations of the fictitious domain (FD) method to simulate water-entry and water-exit problems and demonstrate their ability to simulate practical marine engineering problems. In FD methods, the fluid…

In the process of reproducing the state dynamics of parameter dependent distributed systems, data from physical measurements can be incorporated into the mathematical model to reduce the parameter uncertainty and, consequently, improve the…

Numerical Analysis · Mathematics 2022-10-06 Francesco A. B. Silva , Cecilia Pagliantini , Martin Grepl , Karen Veroy