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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

A cell-centered AMR-ALE framework for 3D multi-material hydrodynamics. Part I: Lagrangian and indirect Euler AMR algorithms

Many applications of physics and engineering involve wide ranges of time and spatial scales. The numerical simulation of localized small scales such as shock waves and material interfaces requires a large number of computational cells in these regions. For these applications, Lagrangian and Arbitrary-Lagrangian-Eulerian (ALE) related methods are engaging since the moving mesh feature naturally brings mesh cells on shock discontinuities and material interfaces are carefully captured. In addition, Adaptive-Mesh-Refinement (AMR) strategies aim to optimize computational resources by concentrating finer mesh cells only in areas of interest while using coarser cells elsewhere. A key but challenging AMR requirement consists in efficiently distributing the computational effort to achieve high accuracy without the prohibitive computational costs associated with uniformly fine grids. Here, in this document, the coupling of the p4est AMR library with a cell-centered Lagrangian scheme is presented with the goal to perform reliable 3D Lagrangian-AMR and indirect Euler-AMR multi-material simulations. In particular, it is shown that starting from a 3D indirect ALE code, the memory management and load balancing requirements can be delegated to an external library (here the p4est library) to unlock ALE-AMR capabilities. First, we present a strategy to transcribe the octant-based connectivity of the 3D AMR framework with that of an unstructured mesh of polygonal cells used in Lagrangian hydrodynamics. Then, we show how refinement and coarsening operations must be adapted to the particular Lagrangian framework to ensure the conservation of volume during those steps. Finally, several numerical test cases are presented that demonstrate the capabilities of the Lagrangian-AMR and indirect Euler-AMR algorithms.

3D cell-centered Lagrangian numerical scheme↗
DOE OSTI2026

A cell-centered AMR-ALE framework for 3D multi-material hydrodynamics. Part II: linesweep ALE rezoning for nonconformal block-structured AMR meshes

The simulation of flows presenting contact discontinuities, vorticity, and large variations in spatial scales can be performed in a framework coupling Arbitrary Lagrangian Eulerian (ALE) algorithms and Adaptive Mesh Refinement (AMR). This coupling requires adaptation of ALE rezoning techniques to meshes containing nonconformal nodes arising from both the AMR topology and the junction of mesh blocks. Here, in this paper, we present an ALE rezoning strategy that is compatible with such meshes, and that can also act as a disentangling algorithm. Emphasis is put on an algorithm that respects intrinsic Lagrangian mesh properties in order to preserve accuracy around discontinuities. To that end, we adapt the weighted linesweep algorithm to nonconformal block-structured AMR meshes. Then, we present control parameters introduced in the method for it to be applicable in practical situations. Notably, the method is coupled to a specific metric optimization in order to palliate some shortcomings of the linesweep method. Finally, numerical test cases are presented that feature the capabilities of the ALE-AMR algorithm for flows that present discontinuities, vorticity, and a variety of scales. Notably, we show that our ALE-AMR algorithm gives results at least similar to Euler-AMR, but provides better accuracy in cases where discontinuities are involved, thanks to a method that respects the Lagrangian features of the mesh. Additionally, it enables Euler-AMR-like computations on domains with temporally varying domain boundaries.

Adaptive mesh refinement↗
DOE OSTI2025

AMR-Wind: A Performance-Portable, High-Fidelity Flow Solver for Wind Farm Simulations

We present AMR-Wind, a verified and validated high-fidelity computational-fluid-dynamics code for wind farm flows. AMR-Wind is a block-structured, adaptive-mesh, incompressible-flow solver that enables predictive simulations of the atmospheric boundary layer and wind plants. It is a highly scalable code designed for parallel high-performance computing with a specific focus on performance portability for current and future computing architectures, including graphical processing units (GPUs). In this paper, we detail the governing equations, the numerical methods, and the turbine models. Establishing a foundation for the correctness of the code, we present the results of formal verification and validation. The verification studies, which include a novel actuator line test case, indicate that AMR-Wind is spatially and temporally second-order accurate. The validation studies demonstrate that the key physics capabilities implemented in the code, including actuator disk models, actuator line models, turbulence models, and large eddy simulation (LES) models for atmospheric boundary layers, perform well in comparison to reference data from established computational tools and theory. We conclude with a demonstration simulation of a 12-turbine wind farm operating in a turbulent atmospheric boundary layer, detailing computational performance and realistic wake interactions.

17 WIND ENERGY↗
DOE OSTI2023

Code for Value Decomposition Graph Network and environment for AMR on linear advection

This is the code for the paper [Multi-Agent Reinforcement Learning for Adaptive Mesh Refinement](https://arxiv.org/abs/2211.00801), published at AAMAS 2023. It contains the implementation of a new algorithm, called Value Decomposition Graph Network (VDGN), for applying multi-agent reinforcement learning to the problem of adaptive mesh refinement (AMR). It also contains the implementation of a multi-agent environment for AMR on a linear advection problem. VDGN is the first learning algorithm to display anticipatory refinement behavior in AMR, and it outperforms local error threshold-based heuristic strategies.

Yang, Jiachen↗
DOE OSTI2023

Spurious instability growth introduced by AMR [Slides]

The following slides summarize the effect that AMR has on results obtained using the inviscid version of xRAGE, i.e., when solving the Euler equations. The simulations are 2D and were done in the context of the ModCons experiments, where a shock travels from a heavy material (PAI of density 1.45 g/cm 3 ) to a light material (foam of density 0.1 g/cm 3 ). The shock is initialized using the 1D shock relations and is sustained by a freeze region during the entire simulation (0 ≤ t ≤ 6 ns). The initial perturbation has a wavelength of λ = 100 µm and an initial amplitude of a 0 = 10 µm. Five cases are considered: four with AMR with decreasing resolutions (from 1 µm to 1/8 µm at the interface) and one without AMR with 1/8 µm resolution in the entire domain.

36 MATERIALS SCIENCE↗
NASA NTRS2017

The Advanced Microwave Radiometer – Climate Quality (AMR-C) Instrument for Sentinel-6

The Advanced Microwave Radiometer – Climate Quality (AMR-C) is designed to measure the path delay due to atmospheric water vapor along Sentinel-6 altimeter path over one decade. The AMR-C receiver is based on heritage from previous AMR instruments with the addition of a THz-frequency radiometer, the High Resolution Microwave Radiometer (HRMR), for improved coastal zone accuracy and a Supplemental Calibration System (SCS) to meet level 3 requirements that the path delay error due to the altimeter-derived sea surface height be less at 0.8 cm and the path delay stability be maintained to 0.7 mm averaged over a 1-year time period.

Maiwald, Frank↗
DOE OSTI2024

Diffusion Limit–Preserving Lumped DFEMs on AMR Meshes

Here, we present sweep-compatible, novel upwinding recipes for the bilinear discontinuous (BLD) finite element method (FEM) that allows lumped BLD to be used on adaptive mesh refinement (AMR) meshes for thick transport applications without adding additional degrees of freedom at hanging nodes that exist on refinement boundaries. We analyze the properties of the upwinding and lumping that are needed for BLD to get the thick diffusion limit on such meshes, present results demonstrating locking with the wrong recipe, and present results showing error convergence and robustness properties for two diffusive problems on a variety of AMR meshes.

42 ENGINEERING↗
DOE OSTI2025

Twelve turbine wind farm simulation with AMR-Wind

This dataset contains simulation data of a twelve turbine wind farm simulation performed with AMR-Wind. The simulation is documented in Kuhn, M. B., Henry de Frahan, M. T., Mohan, P., Deskos, G., Churchfield, M., Cheung, L., ... & Sprague, M. (2025). AMR‐Wind: A Performance‐Portable, High‐Fidelity Flow Solver for Wind Farm Simulations. Wind Energy, 28(5), e70010 (https://doi.org/10.1002/we.70010).

17 WIND ENERGY↗
DOE OSTI2022

Modeling pre-Exascale AMR Parallel I/O Workloads via Proxy Applications

The present work investigates the modeling of preexascale input/output (I/O) workloads of Adaptive Mesh Refinement (AMR) simulations through a simple proxy application. We collect data from the AMReX Castro framework running on the Summit supercomputer for a wide range of scales and mesh partitions for the hydrodynamic Sedov case as a baseline to provide sufficient coverage to the formulated proxy model. The non-linear analysis data production rates are quantified as a function of a set of input parameters such as output frequency, grid size, number of levels, and the Courant-Friedrichs-Lewy (CFL) condition number for each rank, mesh level and simulation time step. Linear regression is then applied to formulate a simple analytical model which allows to translate AMReX inputs into MACSio proxy I/O application parameters, resulting in a simple “kernel” approximation for data production at each time step. Results show that MACSio can simulate actual AMReX nonlinear “static” I/O workloads to a certain degree of confidence on the Summit supercomputer using the present methodology. The goal is to provide an initial level of understanding of AMR I/O workloads via lightweight proxy applications models to facilitate autotune data management strategies in anticipation of exascale systems.

Godoy, William↗
DOE OSTI2021

Evaluation of Anisotropic Magnetoresistive (AMR) Sensors for a Magnetic Field Scanning System for SRF Cavities

One of the significant causes of residual losses in superconducting radio-frequency (SRF) cavities is trapped magnetic flux. The flux trapping mechanism depends on many factors that include cool-down conditions, surface preparation techniques, and ambient magnetic field orientation. Suitable diagnostic tools are not yet available to quantitatively correlate such factors’ effect on the flux trapping mechanism. A magnetic field scanning system (MFSS) consisting of AMR sensors, fluxgate magnetometers, or Hall probes is recently commissioned to scan the local magnetic field of trapped vortices around 1.3 GHz single-cell SRF cavities. In this contribution, we will present results from sensitivity calibration and the first tests of AMR sensors in the MFSS.

Parajuli, I. P.↗
DOE OSTI2022

H-AMR: A New GPU-accelerated GRMHD Code for Exascale Computing with 3D Adaptive Mesh Refinement and Local Adaptive Time Stepping

General relativistic magnetohydrodynamic (GRMHD) simulations have revolutionized our understanding of black hole accretion. Here, we present a GPU-accelerated GRMHD code H-AMR with multifaceted optimizations that, collectively, accelerate computation by 2–5 orders of magnitude for a wide range of applications. First, it introduces a spherical grid with 3D adaptive mesh refinement that operates in each of the three dimensions independently. This allows us to circumvent the Courant condition near the polar singularity, which otherwise cripples high-resolution computational performance. Second, we demonstrate that local adaptive time stepping on a logarithmic spherical-polar grid accelerates computation by a factor of ≲10 compared to traditional hierarchical time-stepping approaches. Jointly, these unique features lead to an effective speed of ~10 9 zone cycles per second per node on 5400 NVIDIA V100 GPUs (i.e., 900 nodes of the OLCF Summit supercomputer). We illustrate H-AMR's computational performance by presenting the first GRMHD simulation of a tilted thin accretion disk threaded by a toroidal magnetic field around a rapidly spinning black hole. With an effective resolution of 13,440 × 4608 × 8092 cells and a total of ≲22 billion cells and ~0.65 × 10 8 time steps, it is among the largest astrophysical simulations ever performed. We find that frame dragging by the black hole tears up the disk into two independently precessing subdisks. The innermost subdisk rotation axis intermittently aligns with the black hole spin, demonstrating for the first time that such long-sought alignment is possible in the absence of large-scale poloidal magnetic fields.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1999

Innovative Language-Based & Object-Oriented Structured AMR Using Fortran 90 and OpenMP

Parallel adaptive mesh refinement (AMR) is an important numerical technique that leads to the efficient solution of many physical and engineering problems. In this paper, we describe how AMR programing can be performed in an object-oreinted way using the modern aspects of Fortran 90 combined with the parallelization features of OpenMP.

software↗
NASA NTRS2004

Developing parallel GeoFEST(P) using the PYRAMID AMR library

The PYRAMID parallel unstructured adaptive mesh refinement (AMR) library has been coupled with the GeoFEST geophysical finite element simulation tool to support parallel active tectonics simulations. Specifically, we have demonstrated modeling of coseismic and postseismic surface displacement due to a simulated Earthquake for the Landers system of interacting faults in Southern California. The new software demonstrated a 25-times resolution improvement and a 4-times reduction in time to solution over the sequential baseline milestone case. Simulations on workstations using a few tens of thousands of stress displacement finite elements can now be expanded to multiple millions of elements with greater than 98% scaled efficiency on various parallel platforms over many hundreds of processors. Our most recent work has demonstrated that we can dynamically adapt the computational grid as stress grows on a fault. In this paper, we will describe the major issues and challenges associated with coupling these two programs to create GeoFEST(P). Performance and visualization results will also be described.

adaptive mesh refinement (AMR)↗
DOE OSTI2023

PeleLMeX: an AMR Low Mach Number Reactive Flow Simulation Code without level sub-cycling

PeleLMeX simulates chemically reacting low Mach number flows with block-structured adaptive mesh refinement (AMR). The code is built upon the AMReX library, which provides the underlying data structures and tools to manage and operate on them across massively parallel computing architectures. PeleLMeX algorithmic features are inherited from its predecessor PeleLM but key improvements allow representation of more complex physical processes. Together with its compressible flow counterpart PeleC, the thermo-chemistry library PelePhysics and the multi-physics library PeleMP, it forms the Pele suite of open-source reactive flow simulation codes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Amorphous Metal Ribbon (AMR) and Metal Amorphous Nanocomposite (MANC) Materials Enabled High Power Density Vehicle Motor Applications (Final Technical Report)

A collaborative team from Carnegie Mellon Univ. (CMU), North Carolina State Univ. (NCSU) and Metglas, South Carolina have studied new high speed motors (HSMs) with high-power density for traction motor applications. These are enabled by hybrid designs, including Flux Switching with Permanent Magnets (FSWPM) motors, exploiting permanent magnets without heavy rare earths (RE-lean) and high induction/high resistivity soft magnetic materials that allow for high switching frequencies needed to increase power densities. Team members include Michael E. McHenry, Prof. Materials Science & Eng., CMU, with > 30 years experience in magnetic materials development; Subashish Bhattacharya, Prof. Electrical Eng. and Freedom Center Director at NCSU with > 30 years experience in development of power electronic components and systems and Eric Theisen, Director of Research at Metglas, the only US located supplier of AMR and MANC materials. The team offers novel axial motor architectures exploiting soft magnetic materials (SMMs) that switch with low loss at high frequencies and heavy rare earth free permanent magnets that address materials criticality issues, supply chain risks, and high costs for traction motors. Axial-flux permanent magnet motors (APFM), offer efficiency improvements reducing rotor losses and also significantly higher power density. Axial-flux construction requires less core material, high torque-to-weight ratio. Since AFPM machines have thin magnets, they are smaller than radial flux motors making them attractive in space-limited applications. Noise and vibration are less and planar air gaps are easily adjusted. Flexibility in air-gap direction allows many topologies.

36 MATERIALS SCIENCE↗
NASA NTRS1977

Extended applications study of AMOOS and AMRS

The potential advantages of the Aeromaneuvering Orbit-to-Orbit Shuttle (AMOOS) over the all-propulsive Orbit Transfer Vehicle (OTV) are shown. In particular, the kit concept studies and the dual fueled AMOOS studies show its versatility and option potential over the all-propulsive vehicle. All of this potential of AMOOS and the Aeromaneuvering Recovery System (AMRS) depends upon the ability to control the trajectory during atmospheric flight and so use an ablative TPS. In turn, this TPS must be light weight, which can be attained by spraying a lightweight ablator directly onto the load bearing skin.

White, J.↗
NASA NTRS1992

AMR on the CM-2

We describe the development of a structured adaptive mesh algorithm (AMR) for the Connection Machine-2 (CM-2). We develop a data layout scheme that preserves locality even for communication between fine and coarse grids. On 8K of a 32K machine we achieve performance slightly less than 1 CPU of the Cray Y-MP. We apply our algorithm to an inviscid compressible flow problem.

Berger, Marsha J.↗