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Accurate and predictive scale-resolving simulations of laser-ignited rocket engines are highly time-consuming because the problem includes turbulent fuel-oxidizer mixing dynamics, laser-induced energy deposition, and high-speed flame…

Machine Learning · Computer Science 2026-03-10 Tony Zahtila , Ettore Saetta , Murray Cutforth , Davy Brouzet , Diego Rossinelli , Gianluca Iaccarino

We present two promising applications of training machine learning models inside a differentiable astrophysical (magneto)hydrodynamics simulator. First, we address the problem of slow convergence in hydrodynamical simulations of wind-blown…

Instrumentation and Methods for Astrophysics · Physics 2025-12-09 Leonard Storcks , Tobias Buck

Hydrodynamical simulations are the most accurate way to model structure formation in the universe, but they often involve a large number of astrophysical parameters modeling subgrid physics, in addition to cosmological parameters. This…

Cosmology and Nongalactic Astrophysics · Physics 2025-11-05 Benjamin Horowitz , Zarija Lukic

The applicability of computational fluid dynamics (CFD) based design tools depend on the accuracy and complexity of the physical models, for example turbulence models, which remains an unsolved problem in physics, and rotor models that…

Fluid Dynamics · Physics 2023-05-09 Shanti Bhushan , Greg W Burgreen , Joshua L Bowman , Ian D Dettwiller , Wesley Brewer

Computational fluid dynamics (CFD) studies have been increasingly used for blood flow simulations in intracranial aneurysms (ICAs). However, despite the continuous progress of body-fitted CFD solvers, generating a high quality mesh is still…

Computational Engineering, Finance, and Science · Computer Science 2020-07-28 D. S. Lampropoulos , G. C. Bourantas , B. F. Zwick , G. C. Kagadis , A. Wittek , K. Miller , V. C. Loukopoulos

Three-dimensional FLASH radiation-magnetohydrodynamics (radiation-MHD) modeling is carried out to study the hydrodynamics and magnetic fields in the shock-shear derived platform. Simulations indicate that fields of tens of Tesla can be…

Molecular dynamics simulations are powerful tools to extract the microscopic mechanisms characterizing the properties of soft materials. We recently introduced machine learning surrogates for molecular dynamics simulations of soft materials…

Soft Condensed Matter · Physics 2021-10-29 J. C. S. Kadupitiya , Nasim Anousheh , Vikram Jadhao

Magnetised plasma turbulence pervades the universe and is likely to play an important role in a variety of astrophysical settings. Magnetohydrodynamics (MHD) provides the simplest theoretical framework in which phenomenological models for…

Plasma Physics · Physics 2012-07-23 Joanne Mason , Jean C. Perez , Stanislav Boldyrev , Fausto Cattaneo

Integration of machine learning (ML) models of unresolved dynamics into numerical simulations of fluid dynamics has been demonstrated to improve the accuracy of coarse resolution simulations. However, when trained in a purely offline mode,…

Fluid Dynamics · Physics 2023-07-26 Christian Pedersen , Laure Zanna , Joan Bruna , Pavel Perezhogin

Designing a high-quality plasma injector electron source driven by a laser beam relies on numerical parametric studies using particle-in-cell codes. The common input parameters to explore are laser characteristics, plasma species and…

A high fidelity fluid-structure interaction simulation may require many days to run, on hundreds of cores. This poses a serious burden, both in terms of time and economic considerations, when repetitions of such simulations may be required…

Computational Engineering, Finance, and Science · Computer Science 2021-04-12 Wensi Wu , Christophe Bonneville , Christopher J. Earls

Modeling the dynamic behavior of deformable objects is crucial for creating realistic digital worlds. While conventional simulations produce high-quality motions, their computational costs are often prohibitive. Subspace simulation…

Computational Fluid Dynamics (CFD) simulations are a very important tool for many industrial applications, such as aerodynamic optimization of engineering designs like cars shapes, airplanes parts etc. The output of such simulations, in…

Computer Vision and Pattern Recognition · Computer Science 2021-03-12 Theodoros Georgiou , Sebastian Schmitt , Thomas Bäck , Nan Pu , Wei Chen , Michael Lew

This study introduces a hybrid fluid simulation approach that integrates generative diffusion models with physics-based simulations, aiming at reducing the computational costs of flow simulations while still honoring all the physical…

The precision, stability, and performance of lightweight high-strength steel structures in heavy machinery is affected by their highly nonlinear dynamics. This, in turn, makes control more difficult, simulation more computationally…

Systems and Control · Electrical Eng. & Systems 2025-03-11 Qasim Khadim , Peter Manzl , Emil Kurvinen , Aki Mikkola , Grzegorz Orzechowski , Johannes Gerstmayr

The coupling of excited states and ionic dynamics is the basic and challenging point for the materials response at extreme conditions. In laboratory, the intense laser produces transient nature and complexity with highly nonequilibrium…

Computational Physics · Physics 2023-11-27 Qiyu Zeng , Bo Chen , Shen Zhang , Dongdong Kang , Han Wang , Xiaoxiang Yu , Jiayu Dai

An effective computer program for three dimensional relativistic hydrodynamical model has been developed. It implements a new approach to the early hot phase of relativistic heavy-ion collisions. The computer program simulates time-space…

Nuclear Theory · Physics 2009-11-11 Daniel Kikola , Wiktor Peryt , Yuri M. Sinyukov , Marcin Slodkowski , Marek Szuba

The 100 MW cryogenic liquid oxygen/hydrogen multi-injector combustor BKD operated by the DLR Institute of Space Propulsion is a research platform that allows the study of thermoacoustic instabilities under realistic conditions,…

We propose a neural physics system for real-time, interactive fluid simulations. Traditional physics-based methods, while accurate, are computationally intensive and suffer from latency issues. Recent machine-learning methods reduce…

Machine Learning · Computer Science 2025-05-27 Jingxuan Xu , Hong Huang , Chuhang Zou , Manolis Savva , Yunchao Wei , Wuyang Chen

The treatment of mixing processes is still one of the major uncertainties in 1D stellar evolution models. This is mostly due to the need to parametrize and approximate aspects of hydrodynamics in hydrostatic codes. In particular, the effect…

Solar and Stellar Astrophysics · Physics 2017-08-02 Philipp V. F. Edelmann , Friedrich K. Roepke , Raphael Hirschi , Cyril Georgy , Samuel Jones