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Numerical simulation of multi-component flow systems characterized by the simultaneous presence of pressure-velocity coupling and pressure-density coupling dominated regions remains a significant challenge in computational fluid dynamics.…

Fluid Dynamics · Physics 2025-10-17 Xi Deng , Bin Xie , Omar K. Matar , Pierre Boivin

Mixed finite element methods are considered for a ferrofluid flow model with magnetization paralleled to the magnetic field. The ferrofluid model is a coupled system of the Maxwell equations and the incompressible Navier-Stokes equations.…

Numerical Analysis · Mathematics 2022-08-11 Yongke Wu , Xiaoping Xie

A fully coupled implicit finite-volume algorithm for incompressible viscoelastic interfacial flows is proposed, whereby the viscoelasticity of the flow is described by an upper-convected Maxwell constitutive model, including limited…

Fluid Dynamics · Physics 2026-02-10 Ayman Mazloum , Gabriele Gennari , Fabian Denner , Berend van Wachem

Seawater intrusion (SWI) is a complex process, where 3D modeling is often necessary in order to monitor and manage the affected aquifers. Here, we present a synthetic study to test a joint hydrogeophysical inversion approach aimed at…

Geophysics · Physics 2016-08-05 K. Steklova , E. Haber

Adapting a pre-trained foundation model on downstream tasks should ensure robustness against distribution shifts without the need to retrain the whole model. Although existing weight interpolation methods are simple yet effective, we argue…

Machine Learning · Computer Science 2025-06-02 Changdae Oh , Yixuan Li , Kyungwoo Song , Sangdoo Yun , Dongyoon Han

We present an enhanced immersed interface method for simulating incompressible fluid flows in thin gaps between closely spaced immersed boundaries. This regime, common in engineered structures such as including tribological interfaces and…

Fluid Dynamics · Physics 2026-03-17 Michael J. Facci , Qi Sun , Boyce E. Griffith

Many optimization problems in electrical engineering consider a large number of design parameters. A sensitivity analysis identifies the design parameters with the strongest influence on the problem of interest. This paper introduces the…

Computational Engineering, Finance, and Science · Computer Science 2023-07-07 M. Greta Ruppert , Yvonne Späck-Leigsnering , Julian Buschbaum , Herbert De Gersem

The paper is concerned with a node-based, gradient-driven, continuous adjoint two-phase flow procedure to optimize the shapes of free-floating vessels and discusses three topics. First, we aim to convey that elements of a Cahn-Hilliard…

Fluid Dynamics · Physics 2022-02-10 Niklas Kühl , Thanh Tung Nguyen , Michael Palm , Dirk Jürgens , Thomas Rung

We use the adjoint methods to study the static Hamilton-Jacobi equations and to prove the speed of convergence for those equations. The main new ideas are to introduce adjoint equations corresponding to the formal linearizations of…

Analysis of PDEs · Mathematics 2012-01-04 Hung Vinh Tran

Efficient shape morphing techniques play a crucial role in the approximation of partial differential equations defined in parametrized domains, such as for fluid-structure interaction or shape optimization problems. In this paper, we focus…

Numerical Analysis · Mathematics 2023-08-08 Francesco Ballarin , Alessandro D'Amario , Simona Perotto , Gianluigi Rozza

Versatile mixed finite element methods were originally developed by Chen and Williams for isothermal incompressible flows in "Versatile mixed methods for the incompressible Navier-Stokes equations," Computers & Mathematics with…

Numerical Analysis · Mathematics 2025-07-29 Edward A. Miller , David M. Williams

This paper presents a novel computational scheme for sensitivity analysis of the velocity field in the level set method using the discrete adjoint method. The velocity field is represented in B-spline space, and the adjoint equations are…

Numerical Analysis · Mathematics 2023-08-03 Hao Deng , Kazu Saitou

Adjoint methods form a class of importance sampling methods that are used to accelerate Monte Carlo (MC) simulations of transport equations. Ideally, adjoint methods allow for zero-variance MC estimators provided that the solution to an…

Mathematical Physics · Physics 2015-03-19 Guillaume Bal , Ian Langmore

For simulating incompressible flows by projection methods. it is generally accepted that the pressure-correction stage is the most time-consuming part of the flow solver. The objective of the present work is to develop a fast hybrid…

Fluid Dynamics · Physics 2023-06-05 Jiannong Fang

We introduce Adjoint Sampling, a highly scalable and efficient algorithm for learning diffusion processes that sample from unnormalized densities, or energy functions. It is the first on-policy approach that allows significantly more…

Wavefield reconstruction inversion (WRI) extends the search space of Full Waveform Inversion (FWI) by allowing for wave equation errors during wavefield reconstruction to match the data from the first iteration. Then, the wavespeeds are…

Optimization and Control · Mathematics 2020-05-18 Hossein S. Aghamiry , Ali Gholami , Stéphane Operto

A comprehensive scheme for the spatial discretisation of continuity equation, momentum advection and normal and shear stresses at the fluid interfaces is presented for numerically simulating the incompressible two phase flows based on the…

Fluid Dynamics · Physics 2014-08-11 Jun-De Li

Full waveform inversion (FWI) is a nonlinear waveform matching procedure, which suffers from cycle skipping when the initial model is not kinematically-accurate enough. To mitigate cycle skipping, wavefield reconstruction inversion (WRI)…

Optimization and Control · Mathematics 2019-10-29 Hossein S. Aghamiry , Ali Gholami , Stéphane Operto

Whilst surface-stress integration remains the standard approach for fluid force evaluation, control-volume integral methods provide deeper physical insights through functional relationships between the flow field and the resultant force. In…

Fluid Dynamics · Physics 2026-01-14 An-Kang Gao , Chenyue Xie , Xi-Yun Lu

Propensity score matching (PSM) and augmented inverse propensity weighting (AIPW) are widely used in observational studies to estimate causal effects. The two approaches present complementary features. The AIPW estimator is doubly robust…

Methodology · Statistics 2025-12-12 Tanchumin Xu , Yunshu Zhang , Shu Yang