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Engineering problems frequently require solution of governing equations with spatially-varying discontinuous coefficients. Even for linear elliptic problems, mapping large ensembles of coefficient fields to solutions can become a major…

Machine Learning · Computer Science 2024-11-12 Conlain Kelly , Surya R. Kalidindi

Machine learning models are gaining increasing popularity in the domain of fluid dynamics for their potential to accelerate the production of high-fidelity computational fluid dynamics data. However, many recently proposed machine learning…

Machine Learning · Computer Science 2023-03-01 Dule Shu , Zijie Li , Amir Barati Farimani

Plasma supports collective modes and particle-wave interactions that leads to complex behavior in inertial fusion energy applications. While plasma can sometimes be modeled as a charged fluid, a kinetic description is useful towards the…

Plasma Physics · Physics 2022-11-28 Archis S. Joglekar , Alexander G. R. Thomas

Bayesian inverse design provides a principled framework for inferring aerodynamic geometries from sparse flow observations while quantifying uncertainty. However, its practical use in computational fluid dynamics (CFD) is severely limited…

Fluid Dynamics · Physics 2026-05-26 Bipin Tiwari , Omer San

The high cost of high-resolution computational fluid/flame dynamics (CFD) has hindered its application in combustion related design, research and optimization. In this study, we propose a new framework for turbulent combustion simulation…

Fluid Dynamics · Physics 2020-03-03 Jian An , Hanyi Wang , Bing Liu , Kai Hong Luo , Fei Qin , Guo Qiang He

Adjoint-based optimization methods are attractive for aerodynamic shape design primarily due to their computational costs being independent of the dimensionality of the input space and their ability to generate high-fidelity gradients that…

Computational Physics · Physics 2020-08-18 S. Ashwin Renganathan , Romit Maulik and , Jai Ahuja

The steep computational cost of diffusion models at inference hinders their use as fast physics emulators. In the context of image and video generation, this computational drawback has been addressed by generating in the latent space of an…

Machine Learning · Computer Science 2025-11-04 François Rozet , Ruben Ohana , Michael McCabe , Gilles Louppe , François Lanusse , Shirley Ho

Defects in laser powder bed fusion (L-PBF) parts often result from the meso-scale dynamics of the molten alloy near the laser, known as the melt pool. For instance, the melt pool can directly contribute to the formation of undesirable…

High fidelity design evaluation processes such as Computational Fluid Dynamics and Finite Element Analysis are often replaced with data driven surrogates to reduce computational cost in engineering design optimization. However, building…

Machine Learning · Computer Science 2025-12-01 Sarthak Kapoor , Harsh Vardhan , Umesh Timalsina , Sumit Kumar , Peter Volgyesi , Janos Sztipanovits

Surrogate models are effective tools for accelerated design of complex systems. The result of a design optimization procedure using surrogate models can be used to initialize an optimization routine using the full order system. High…

Computational Engineering, Finance, and Science · Computer Science 2025-01-15 Anas Abdelrehim , Dhairya Gandhi , Sharan Yalburgi , Ashutosh Bharambe , Ranjan Anantharaman , Chris Rackauckas

In this contribution, we present the results of the application of a parameter space reduction methodology based on active subspaces to the hull hydrodynamic design problem. Several parametric deformations of an initial hull shape are…

Numerical Analysis · Mathematics 2018-04-04 Nicola Demo , Marco Tezzele , Andrea Mola , Gianluigi Rozza

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

The process of calibrating computer models of natural phenomena is essential for applications in the physical sciences, where plenty of domain knowledge can be embedded into simulations and then calibrated against real observations. Current…

Machine Learning · Computer Science 2025-01-20 Rafael Oliveira , Dino Sejdinovic , David Howard , Edwin V. Bonilla

High-fidelity, high-resolution numerical simulations are crucial for studying complex multiscale phenomena in fluid dynamics, such as turbulent flows and ocean waves. However, direct numerical simulations with high-resolution solvers are…

Numerical Analysis · Mathematics 2025-04-14 Wuzhe Xu , Yulong Lu , Lian Shen , Anqing Xuan , Ali Barzegari

We consider adapting a canonical computer model calibration apparatus, involving coupled Gaussian process (GP) emulators, to a computer experiment simulating radiative shock hydrodynamics that is orders of magnitude larger than what can…

In computational fluid dynamics, there is an inevitable trade off between accuracy and computational cost. In this work, a novel multi-fidelity deep generative model is introduced for the surrogate modeling of high-fidelity turbulent flow…

Computational Physics · Physics 2021-01-12 Nicholas Geneva , Nicholas Zabaras

The design of inertial confinement fusion experiments, alongside improving the development of energy density physics theory and experimental methods, is one of the key challenges in the quest for nuclear fusion as a viable energy source.…

Plasma Physics · Physics 2019-06-26 P. W. Hatfield , S. J. Rose , R. H. H. Scott

The role of hydrodynamic mixing in astrophysics is reviewed, emphasizing connections with laser physics experiments and inertial confinement fusion (ICF). Computer technology now allows two dimensional (2D) simulations, with complex…

Astrophysics · Physics 2009-10-31 David Arnett

The design process of centrifugal compressors requires applying an optimization process which is computationally expensive due to complex analytical equations underlying the compressor's dynamical equations. Although the regression…

Machine Learning · Computer Science 2023-09-07 Shadi Ghiasi , Guido Pazzi , Concettina Del Grosso , Giovanni De Magistris , Giacomo Veneri

Engineering simulations are usually based on complex, grid-based, or mesh-free methods for solving partial differential equations. The results of these methods cover large fields of physical quantities at very many discrete spatial…

Fluid Dynamics · Physics 2025-08-08 Eduardo Di Costanzo , Niklas Kühl , Jean-Christophe Marongiu , Thomas Rung