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We construct an ensemble distribution to describe steady immiscible two-phase flow of two incompressible fluids in a porous medium. The system is found to be ergodic. The distribution is used to compute macroscopic flow parameters. In…

Fluid Dynamics · Physics 2017-03-08 Isha Savani , Dick Bedeaux , Signe Kjelstrup , Morten Vassvik , Santanu Sinha , Alex Hansen

In this paper, we first establish a new fractional magnetohydrodynamic (MHD) coupled flow and heat transfer model for a generalized second-grade fluid. This coupled model consists of a fractional momentum equation and a heat conduction…

Numerical Analysis · Mathematics 2022-11-29 Xiaoqing Chi , Hui Zhang , Xiaoyun Jiang

In this work, we demonstrate how to reliably estimate epistemic uncertainty while maintaining the flexibility needed to capture complicated aleatoric distributions. To this end, we propose an ensemble of Normalizing Flows (NF), which are…

Machine Learning · Computer Science 2023-10-05 Lucas Berry , David Meger

Understanding event-by-event correlations and fluctuations is crucial for the comprehension of the dynamics of heavy ion collisions. Relativistic hydrodynamics is an elegant tool for modeling these phenomena; however, such simulations are…

Computational Physics · Physics 2018-02-19 J. Porter-Sobieraj , M. Słodkowski , D. Kikoła , J. Sikorski , P. Aszklar

We prove the existence of both local and global smooth solutions to the Cauchy problem in $\R^3$ for the incompressible magnetohydrodynamics (MHD) system. We also prove that the solution to the incompressible MHD system can be obtained as…

Analysis of PDEs · Mathematics 2020-11-16 Anthony Suen

This work proposes multi-agent systems setting for concurrent engineering system design optimization and gradually paves the way towards examining graph theoretic constructs in the context of multidisciplinary design optimization problem.…

Optimization and Control · Mathematics 2012-09-18 Amir Noori

In this paper, we present a multi-dimensional, arbitrary-order hybrid reconstruction framework for compressible flows on unstructured meshes. The method combines the efficiency of linear reconstruction with the robustness of high-order…

Numerical Analysis · Mathematics 2026-01-22 Yiren Tong , Panagiotis Tsoutsanis

The modeling of multi-scale and multi-physics complex systems typically involves the use of scientific software that can optimally leverage extreme scale computing. Despite major developments in recent years, these simulations continue to…

Computational Physics · Physics 2023-07-11 Shawn G. Rosofsky , E. A. Huerta

We study decaying magnetohydrodynamics (MHD) turbulence stemming from the evolution of the Taylor-Green (TG) flow generalized recently to MHD, with equal viscosity and magnetic resistivity and up to equivalent grid resolutions of 2048^3…

Fluid Dynamics · Physics 2015-05-13 A. Pouquet , E. Lee , M. E. Brachet , P. D. Mininni , D. Rosenberg

An algorithm for simulating self-gravitating cosmological astrophysical fluids is presented. The advantages include a large dynamic range, parallelizability, high resolution per grid element and fast execution speed. The code is based on a…

Astrophysics · Physics 2009-10-30 Ue-Li Pen

We consider the problem of estimating a vector of unknown constant parameters for a class of hybrid dynamical systems -- that is, systems whose state variables exhibit both continuous (flow) and discrete (jump) evolution. Using a hybrid…

Optimization and Control · Mathematics 2023-08-16 Ryan S. Johnson , Stefano Di Cairano , Ricardo G. Sanfelice

High-fidelity flow simulations are indispensable when analyzing systems exhibiting multiphase flow phenomena. The accuracy of multiphase flow simulations is strongly contingent upon the finest mesh resolution used to represent the…

Computational Physics · Physics 2023-04-05 Kumar Saurabh , Masado Ishii , Makrand A. Khanwale , Hari Sundar , Baskar Ganapathysubramanian

Computational Fluid Dynamics (CFD) is a major sub-field of engineering. Corresponding flow simulations are typically characterized by heavy computational resource requirements. Often, very fine and complex meshes are required to resolve…

Machine Learning · Computer Science 2021-02-26 Keefe Huang , Moritz Krügener , Alistair Brown , Friedrich Menhorn , Hans-Joachim Bungartz , Dirk Hartmann

In plasma edge simulations, kinetic Monte Carlo (MC) is often used to simulate neutral particles and estimate source terms. For large-sized reactors, like ITER and DEMO, high particle collision rates lead to a substantial computational cost…

Computational Engineering, Finance, and Science · Computer Science 2025-09-16 Zhirui Tang , Emil Løvbak , Julian Koellermeier , Giovanni Samaey

Ideal systems like MHD and Euler flow may develop singularities in vorticity (w = curl v). Viscosity and resistivity are dissipative regularizations. We propose a minimal, local, conservative, nonlinear, dispersive regularization of…

Fluid Dynamics · Physics 2016-11-15 Govind S. Krishnaswami , Sonakshi Sachdev , Anantanarayanan Thyagaraja

An efficient algorithm for computing the terms appearing in the Generalised Kolmogorov Equation (GKE) written for the indefinite plane channel flow is presented. The algorithm, which features three distinct strategies for parallel…

Fast and stable fluid simulations are an essential prerequisite for applications ranging from computer-generated imagery to computer-aided design in research and development. However, solving the partial differential equations of…

Machine Learning · Computer Science 2021-03-03 Nils Wandel , Michael Weinmann , Reinhard Klein

Advancements in computational fluid mechanics have largely relied on Newtonian frameworks, particularly through the direct simulation of Navier-Stokes equations. In this work, we propose an alternative computational framework that employs…

Fluid Dynamics · Physics 2024-12-10 H. Sababha , A. Elmaradny , H. Taha , M. Daqaq

Designing effective optimisation strategies for unsteady flows in the presence of complex dynamics is challenging. Gradient-based optimisation algorithms that rely on gradient information obtained from adjoint equations are efficient for…

This paper is devoted to provide a theoretical underpinning for ensemble forecasting with rapid fluctuations in body forcing and in boundary conditions. Ensemble averaging principles are proved under suitable `mixing' conditions on random…

Probability · Mathematics 2012-07-26 Wei Wang , Jian Ren , Jinqiao Duan , Guowei He