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We describe a novel Godunov-type numerical method for solving the equations of resistive relativistic magnetohydrodynamics. In the proposed approach, the spatial components of both magnetic and electric fields are located at zone interfaces…

Computational Physics · Physics 2019-05-01 A. Mignone , G. Mattia , G. Bodo , L. Del Zanna

Inverse problems in fluid dynamics are ubiquitous in science and engineering, with applications ranging from electronic cooling system design to ocean modeling. We propose a general and robust approach for solving inverse problems in the…

Numerical Analysis · Mathematics 2020-11-20 Tiffany Fan , Kailai Xu , Jay Pathak , Eric Darve

Linear modal instabilities of flow over finite-span untapered wings have been investigated numerically at Reynolds number 400, at a range of angles of attack and sweep on two wings having aspect ratios 4 and 8. Base flows have been…

Clusters of wave-scattering oscillators offer the ability to passively control wave energy in elastic continua. However, designing such clusters to achieve a desired wave energy pattern is a highly nontrivial task. While the forward…

Signal Processing · Electrical Eng. & Systems 2024-02-29 Joshua R. Tempelman , Tobias Weidemann , Eric B. Flynn , Kathryn H. Matlack , Alexander F. Vakakis

We present a coupled large-eddy simulation (LES) and bed morphodynamics study to investigate the influence of sediment dynamics on the performance of a utility-scale marine hydrokinetic vertical-axis turbine (VAT) parametrized by an…

The present study investigates the accurate inference of Reynolds-averaged Navier-Stokes solutions for the compressible flow over aerofoils in two dimensions with a deep neural network. Our approach yields networks that learn to generate…

Fluid Dynamics · Physics 2022-11-17 Li-Wei Chen , Nils Thuerey

Collective wind farm flow control, where wind turbines are operated in an individually suboptimal strategy to benefit the aggregate farm, has demonstrated potential to reduce wake interactions and increase farm energy production. However,…

Fluid Dynamics · Physics 2023-03-29 Kirby S. Heck , Hannah M. Johlas , Michael F. Howland

A data-driven framework for formulation of closures of the Reynolds-Average Navier--Stokes (RANS) equations is presented. In recent years, the scientific community has turned to machine learning techniques to distill a wealth of highly…

Fluid Dynamics · Physics 2020-09-02 S. Beetham , J. Capecelatro

Motivated by the idea of turbomachinery active subspace performance maps, this paper studies dimension reduction in turbomachinery 3D CFD simulations. First, we show that these subspaces exist across different blades---under the same…

Applications · Statistics 2019-10-22 Pranay Seshadri , Shaowu Yuchi , Shahrokh Shahpar , Geoffrey Parks

The inverse problems of particle neutral transport models have many important engineering and medical applications. Safety protocols, quality control procedures, and optical medical solutions can be developed based on inverse transport…

Numerical Analysis · Mathematics 2023-10-24 Nelson Garcia Roman , Pedro Costa dos Santos , Pedro Henrique de Almeida Konzen

Ice accumulation in the blades of wind turbines can cause them to describe anomalous rotations or no rotations at all, thus affecting the generation of electricity and power output. In this work, we investigate the problem of ice…

Machine Learning · Computer Science 2021-12-07 Alan Preciado-Grijalva , Victor Rodrigo Iza-Teran

Bio-inspired oscillatory foil propulsion has the ability to traverse various propulsive modes by dynamically changing the foil's heave and pitch kinematics. This research characterizes the propulsion properties and wake dynamics of a…

Fluid Dynamics · Physics 2020-09-24 Mukul Dave , Arianne Spaulding , Jennifer A. Franck

Cross-flow turbines convert kinetic power in wind or water currents to mechanical power. Unlike axial-flow turbines, the influence of geometric parameters on turbine performance is not well-understood, in part because there are neither…

Fluid Dynamics · Physics 2021-04-16 Aidan Hunt , Carl Stringer , Brian Polagye

This work introduces a novel data-driven framework to formulate explicit algebraic Reynolds-averaged Navier-Stokes (RANS) turbulence closures. Recent years have witnessed a blossom in applying machine learning (ML) methods to revolutionize…

Fluid Dynamics · Physics 2023-01-24 Hongwei Tang , Yan Wang , Tongguang Wang , Linlin Tian

Inverse design aims to find design parameters $x$ achieving target performance $y^*$. Generative approaches learn bidirectional mappings between designs and labels, enabling diverse solution sampling. However, standard conditional flow…

Machine Learning · Computer Science 2026-03-18 Miguel de Campos , Werner Krebs , Hanno Gottschalk

Wind turbines operating within wind farms experience complex aerodynamic loading arising from the interplay between wake-induced velocity deficits, enhanced turbulence, and varying operational conditions. Understanding the relationship…

Turbulent flows have high requirements for very fine meshes near the boundary to ensure accuracy. In the context of topology optimization (TO), such fine meshes become unrealistic and common approaches are hampered by low accuracy and…

Fluid Dynamics · Physics 2026-01-06 Amirhossein Bayat , Hao Li , Joe Alexandersen

As the integration of wind power accelerates, wind power plants (WPPs) are expected to play a crucial role in ensuring stability in future power grids. This paper examines the nonlinear stability boundary of a multi-converter system in a…

Systems and Control · Electrical Eng. & Systems 2024-02-15 Sujay Ghosh , Mohammad Kazem Bakhshizadeh , Guangya Yang , Łukasz Kocewiak

Composite materials often exhibit mechanical anisotropy owing to the material properties or geometrical configurations of the microstructure. This makes their inverse design a two-fold problem. First, we must learn the type and orientation…

Computational Engineering, Finance, and Science · Computer Science 2024-12-19 Asghar A. Jadoon , Karl A. Kalina , Manuel K. Rausch , Reese Jones , Jan N. Fuhg

This paper proposes a phenomenological Reynolds Averaged Navier-Stokes (RANS) calculation model based on physical constraints. In this model part of the source terms in the e equation was replaced with the deep learning model, using the…

Fluid Dynamics · Physics 2021-12-28 Shuming Zhang , Haiwang Li , Ruquan You , Tinglin Kong , Zhi Tao
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