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Accurate subgrid-scale closures are essential for weather/climate models, where predicting extreme events is critical. Traditional closures have structural errors, e.g., producing excessive diffusion that dampens extremes. Artificial…

This paper examines the application of adaptive mesh refinement (AMR) in the field of numerical weather prediction (NWP). We implement and assess two distinct AMR approaches and evaluate their performance through standard NWP benchmarks. In…

数值分析 · 数学 2024-04-26 Daniel S. Abdi , Ann Almgren , Francis X. Giraldo , Isidora Jankov

Current Adaptive Mesh Refinement (AMR) simulations require algorithms that are highly parallelized and manage memory efficiently. As compute engines grow larger, AMR simulations will require algorithms that achieve new levels of efficient…

太阳与恒星天体物理 · 物理学 2015-03-19 Jonathan J. Carroll-Nellenback , Brandon Shroyer , Adam Frank , Chen Ding

This work presents a methodology to predict a near-optimal spacing function, which defines the element sizes, suitable to perform steady RANS turbulent viscous flow simulations. The strategy aims at utilising existing high fidelity…

计算工程、金融与科学 · 计算机科学 2024-06-25 Sergi Sanchez-Gamero , Oubay Hassan , Ruben Sevilla

Structured Adaptive Mesh Refinement (Structured AMR) enables simulations to adapt the domain resolution to save computation and storage, and has become one of the dominant data representations used by scientific simulations; however,…

图形学 · 计算机科学 2020-09-08 Ingo Wald , Stefan Zellmann , Will Usher , Nate Morrical , Ulrich Lang , Valerio Pascucci

In this paper we propose and test the validity of simple and easy-to-implement algorithms within the immersed boundary framework geared towards large scale simulations involving thousands of deformable bodies in highly turbulent flows.…

计算物理 · 物理学 2018-09-26 Vamsi Spandan , Detlef Lohse , Marco D. de Tullio , Roberto Verzicco

The interaction of supercritical turbulent flows with granular sediment beds is challenging to study both experimentally and numerically; this challenging task has hampered the advances in understanding antidunes, the most characteristic…

We present a scheme to solve the nonlinear multigroup radiation diffusion (MGD) equations. The method is incorporated into a massively parallel, multidimensional, Eulerian radiation-hydrodynamic code with adaptive mesh refinement (AMR). The…

天体物理学 · 物理学 2008-11-26 A. I. Shestakov , S. S. R. Offner

The application machine learning (ML) algorithms to turbulence modeling has shown promise over the last few years, but their application has been restricted to eddy viscosity based closure approaches. In this article we discuss rationale…

流体动力学 · 物理学 2021-05-31 J. P. Panda , H. V. Warrior

The physics of turbulence in magnetized plasmas remains an unresolved problem. The most poorly understood aspect is intermittency -- spatio-temporal fluctuations superimposed on the self-similar turbulent motions. We employ a novel…

高能天体物理现象 · 物理学 2025-05-21 Trung Ha , Joonas Nättilä , Jordy Davelaar , Lorenzo Sironi

We have developed a new computer code, RAM, to solve the conservative equations of special relativistic hydrodynamics (SRHD) using adaptive mesh refinement (AMR) on parallel computers. We have implemented a characteristic-wise, finite…

天体物理学 · 物理学 2009-11-11 Weiqun Zhang , Andrew I. MacFadyen

Today's scientific simulations require a significant reduction of data volume because of extremely large amounts of data they produce and the limited I/O bandwidth and storage space. Error-bounded lossy compression has been considered one…

分布式、并行与集群计算 · 计算机科学 2022-05-09 Daoce Wang , Jesus Pulido , Pascal Grosset , Sian Jin , Jiannan Tian , James Ahrens , Dingwen Tao

The main objective of this work is to develop a unified framework that can be used as a lens to quantitatively assess and augment a wide range of coarse-grained models of turbulence, viz. large eddy simulations (LES), hybrid…

流体动力学 · 物理学 2023-01-25 Aniruddhe Pradhan , Karthik Duraisamy

Machine learning has recently become a promising technique in fluid mechanics, especially for active flow control (AFC) applications. A recent work [J. Fluid Mech. (2019), vol. 865, pp. 281-302] has demonstrated the feasibility and…

流体动力学 · 物理学 2021-03-22 Feng Ren , Jean Rabault , Hui Tang

We present a new numerical algorithm for the solution of coupled collisional and collisionless systems, based on the block structured adaptive mesh and time refinement strategy (AMR). We describe the issues associated with the…

天体物理学 · 物理学 2008-11-26 Francesco Miniati , Phillip Colella

This paper presents a new computer code to solve the general relativistic magnetohydrodynamics (GRMHD) equations using distributed parallel adaptive mesh refinement (AMR). The fluid equations are solved using a finite difference Convex ENO…

广义相对论与量子宇宙学 · 物理学 2009-11-11 Matthew Anderson , Eric Hirschmann , Steven L. Liebling , David Neilsen

SAM, a plant-level system analysis tool for advanced reactors (SFR, LFR, MSR/FHR) is under development at Argonne. As a modern system code, SAM aims to improve the predictions of 3D flows relevant to reactor safety during transient…

流体动力学 · 物理学 2020-05-04 Yangmo Zhu , Nam Dinh , Rui Hu , Adam Kraus

A model hierarchy that is based on the one-dimensional isothermal Euler equations of fluid dynamics is used for the simulation and optimisation of gas flow through a pipeline network. Adaptive refinement strategies have the aim of bringing…

数值分析 · 数学 2017-02-01 Pia Domschke , Aseem Dua , Jeroen J. Stolwijk , Jens Lang , Volker Mehrmann

We present a description of the adaptive mesh refinement (AMR) implementation of the PLUTO code for solving the equations of classical and special relativistic magnetohydrodynamics (MHD and RMHD). The current release exploits, in addition…

高能天体物理现象 · 物理学 2015-05-30 A. Mignone , C. Zanni , P. Tzeferacos , B. van Straalen , P. Colella , G. Bodo

We present MARUT, a scalable multi-GPU computational fluid dynamics (CFD) framework designed for high-fidelity simulations of compressible flows spanning subsonic to hypersonic regimes, including chemically reacting nonequilibrium flows…

计算物理 · 物理学 2026-05-29 Trishit Mondal , Ameya D. Jagtap