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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,531 records · Page 85
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Mapping unstructured grid computations to massively parallel computers

Investigated here is this mapping problem: assign the tasks of a parallel program to the processors of a parallel computer such that the execution time is minimized. First, a taxonomy of objective functions and heuristics used to solve the mapping problem is presented. Next, we develop a highly parallel heuristic mapping algorithm, called Cyclic Pairwise Exchange (CPE), and discuss its place in the taxonomy. CPE uses local pairwise exchanges of processor assignments to iteratively improve an initial mapping. A variety of initial mapping schemes are tested and recursive spectral bipartitioning (RSB) followed by CPE is shown to result in the best mappings. For the test cases studied here, problems arising in computational fluid dynamics and structural mechanics on unstructured triangular and tetrahedral meshes, RSB and CPE outperform methods based on simulated annealing. Much less time is required to do the mapping and the results obtained are better. Compared with random and naive mappings, RSB and CPE reduce the communication time two fold for the test problems used. Finally, we use CPE in two applications on a CM-2. The first application is a data parallel mesh-vertex upwind finite volume scheme for solving the Euler equations on 2-D triangular unstructured meshes. CPE is used to map grid points to processors. The performance of this code is compared with a similar code on a Cray-YMP and an Intel iPSC/860. The second application is parallel sparse matrix-vector multiplication used in the iterative solution of large sparse linear systems of equations. We map rows of the matrix to processors and use an inner-product based matrix-vector multiplication. We demonstrate that this method is an order of magnitude faster than methods based on scan operations for our test cases.

Hammond, Steven Warren↗
NASA NTRS1993

Sensitivity calculations for a 2D, inviscid, supersonic forebody problem

The use of a sensitivity equation method to computer derivatives for optimization based design algorithms are discussed. The problem of designing an optimal forebody simulator is used to motivate the algorithm and to illustrate the basic ideas. Finally, how an existing computational fluid dynamics (CFD) code can be modified to compute sensitivities and a numerical example is presented.

Borggaard, Jeff↗
NASA NTRS2011

CFD-CAA Coupled Calculations of a Tandem Cylinder Configuration to Assess Facility Installation Effects

This paper presents a numerical assessment of acoustic installation effects in the tandem cylinder (TC) experiments conducted in the NASA Langley Quiet Flow Facility (QFF), an open-jet, anechoic wind tunnel. Calculations that couple the Computational Fluid Dynamics (CFD) and Computational Aeroacoustics (CAA) of the TC configuration within the QFF are conducted using the CFD simulation results previously obtained at NASA LaRC. The coupled simulations enable the assessment of installation effects associated with several specific features in the QFF facility that may have impacted the measured acoustic signature during the experiment. The CFD-CAA coupling is based on CFD data along a suitably chosen surface, and employs a technique that was recently improved to account for installed configurations involving acoustic backscatter into the CFD domain. First, a CFD-CAA calculation is conducted for an isolated TC configuration to assess the coupling approach, as well as to generate a reference solution for subsequent assessments of QFF installation effects. Direct comparisons between the CFD-CAA calculations associated with the various installed configurations allow the assessment of the effects of each component (nozzle, collector, etc.) or feature (confined vs. free jet flow, etc.) characterizing the NASA LaRC QFF facility.

Redonnet, Stephane↗
NASA NTRS2012

A Computational Investigation for Determining the Natural Frequencies and Damping Effects of Diaphragm-Implemented Spacecraft Propellant Tanks

Spin-stabilization maneuvers are typically performed by spacecraft entering low-earth orbit to maintain attitude stability. These maneuvers induce periodic fluid movement inside the spacecraft's propellant tank known as fuel slosh, which is responsible for creating forces and moments on the sidewalls of the propellant tank. These forces and moments adversely affect spin-stabilization and risk jeopardizing the mission of the spacecraft. Therefore, propellant tanks are designed with propellant management devices (PMD's) such as barnes or diaphragms which work to counteract the forces and moments associated with fuel slosh. However, despite the presence of PMD's, the threat of spin-stabilization interference still exists should the propellant tank be excited at its natural frequency. When the fluid is excited at its natural frequency, the forces and moments acting on the propellant tank are amplified and may result in destabilizing the spacecraft. Thus, a computational analysis is conducted concerning diaphragm-implemented propellant tanks excited at their natural frequencies. Using multi-disciplinary computational fluid dynamics (CFD) software, computational models are developed to reflect potential scenarios that spacecraft propellant tanks could experience. By simulating the propellant tank under a wide array of parameters and variables including fill-level, gravity and diaphragm material and shape, a better understanding is gained as to how these parameters individually and collectively affect liquid propellant tanks and ultimately, spacecraft attitude dynamics.

Lenahen, Brian↗
NASA NTRS2017

Simulation of Liquid Injection Thrust Vector Control for Mars Ascent Vehicle

The Jet Propulsion Laboratory is currently in the initial design phase for a potential Mars Ascent Vehicle; which will be landed on Mars, stay on the surface for period of time, collect samples from the Mars 2020 rover, and then lift these samples into orbit around Mars. The engineers at JPL have down selected to a hybrid wax-based fuel rocket using a liquid oxidizer based on nitrogen tetroxide, or a Mixed Oxide of Nitrogen. To lower the gross lift-off mass of the vehicle the thrust vector control system will use liquid injection of the oxidizer to deflect the thrust of the main nozzle instead of using a gimbaled nozzle. The disadvantage of going with the liquid injection system is the low technology readiness level with a hybrid rocket. Presented in this paper is an effort to simulate the Mars Ascent Vehicle hybrid rocket nozzle and liquid injection thrust vector control system using the computational fluid dynamic flow solver Loci/Chem. This effort also includes determining the sensitivity of the thrust vector control system to a number of different design variables for the injection ports; including axial location, number of adjacent ports, injection angle, and distance between the ports.

Gudenkauf, Jared↗
DOE OSTI2025

Active-noise-induced dynamic clustering of passive colloidal particles

Active fluids generate spontaneous, often chaotic mesoscale flows. Harnessing these flows to drive soft materials embedded within an active fluid into structures with controlled length scales and lifetimes is a key challenge at the interface between the fields of active matter and nonequilibrium self-assembly. Here, we present a simple and efficient computational approach to model soft materials advected by active fluids, by simulating particles moving in a spatiotemporally correlated noise field. To illustrate our approach, we simulate the dynamical self-organization of repulsive colloids within such an active noise field. The colloids form structures whose sizes and dynamics can be tuned by the correlation time and length of the active fluid, and range from small rotating droplets to clusters with internal flows and system-spanning sizes that vastly exceed the active correlation length. Our results explain how the interplay between active fluid time and length scales and emergent driven assembly can be used to rationally design functional assemblies. More broadly, our approach can be used to efficiently simulate diverse active fluids and other systems with spatiotemporally correlated noise.

Brownian dynamics↗
DOE OSTI2025

An intercomparison of wall fluxes in a turbulent thermal convection chamber: Direct numerical simulations and wall-modeled large-eddy simulations enhanced by machine learning

Thermal convection in a closed chamber is driven by a warm bottom, a cold top, and side walls at various temperatures. Although wall fluxes are the source of convection energy, accurately modeling these fluxes (i.e., the wall model) is challenging. In large-eddy simulations (LESs), many wall models are traditionally derived from the canonical boundary layer, which may be unsuitable for thermal convection bounded by both horizontal and vertical walls. This study conducts a model intercomparison of dry convection in a cubic-meter chamber using three direct numerical simulations (DNSs) and four LESs with different wall models. The LESs employ traditional wall models, a new wall model employing physics-aware neural networks, and a refined grid near the walls. The experiment involves four cases with varying sidewall temperatures. Our results show that LESs capture the main flow features and the trends of mean fluxes. The physics-aware neural networks and refined wall grids can improve the temporally averaged local fluxes when the large-scale circulation has a preferred direction. Even without the local improvement of wall fluxes, the LES flow quantities (temperature and velocities) can still largely match those in DNSs, provided the mean flux largely matches the DNSs. Additionally, DNSs reveal that a variation in corner treatments has minimal impacts on the flow quantities away from corners. Finally, LESs underestimate the mean fluxes of the entire wall due to their inability to resolve corner regions, but their mean flux away from the corner can better match DNS.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2013

Solutions of the Taylor-Green Vortex Problem Using High-Resolution Explicit Finite Difference Methods

A computational fluid dynamics code that solves the compressible Navier-Stokes equations was applied to the Taylor-Green vortex problem to examine the code s ability to accurately simulate the vortex decay and subsequent turbulence. The code, WRLES (Wave Resolving Large-Eddy Simulation), uses explicit central-differencing to compute the spatial derivatives and explicit Low Dispersion Runge-Kutta methods for the temporal discretization. The flow was first studied and characterized using Bogey & Bailley s 13-point dispersion relation preserving (DRP) scheme. The kinetic energy dissipation rate, computed both directly and from the enstrophy field, vorticity contours, and the energy spectra are examined. Results are in excellent agreement with a reference solution obtained using a spectral method and provide insight into computations of turbulent flows. In addition the following studies were performed: a comparison of 4th-, 8th-, 12th- and DRP spatial differencing schemes, the effect of the solution filtering on the results, the effect of large-eddy simulation sub-grid scale models, and the effect of high-order discretization of the viscous terms.

DeBonis, James R.↗
DOE OSTI2020

Fluid-driven fractures in granular media: Insights from numerical investigations

We investigate the mechanisms of opening-mode fracture initiation in granular media. The study is based on a simulation of grain-scale fluid-grain interactions through a coupled numerical approach in which the discrete element method is used to solve for the mechanics of a solid granular medium, and computational fluid dynamics is used to model fluid flow and drag forces. In this work, we present benchmark problems with analytical solutions and validate this numerical model against experiments on a viscous-drag-driven cavity in the literature. Additional simulation results show fracture initiation mechanisms in a random granular packing subjected to constant boundary stresses and to fluid injection with a localized source. The dimensionless variable $F_s/F_{sk}$ (ratio of seepage force $F_s$ and skeletal force $F_{sk}$) incorporates the impacts of physical properties and injection parameters including fluid viscosity, injection velocity, grain size, and effective stresses, and it has been used as a criterion separating regimes of fluid invasion and drag-driven fracture opening. Our simulation results show that $F_s/F_{sk}$ in combination with $τ_1$ (ratio of diffusion time from hydromechanical coupling and injection time) serves as a prediction of fracture opening within granular packing. We suggest a simple criterion ($F_s/F_{sk}$ > 1 or $τ_1$ > 0.17) that is valid for various types of granular media and injection conditions to determine if fracture opening will occur. Among other applications, this study is useful to predict the initiation and propagation of fractures in natural sediments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Mixed-precision numerics in scientific applications: survey and perspectives

The explosive demand for artificial intelligence (AI) workloads has led to a significant increase in silicon area dedicated to lower-precision computations on recent high-performance computing hardware designs. However, mixed-precision capabilities, which can achieve performance improvements of up to 8x compared to double-precision in extreme compute-intensive workloads, remain largely untapped in most scientific applications. A growing number of efforts have shown that mixed-precision algorithmic innovations can deliver superior performance without sacrificing accuracy. These developments should prompt computational scientists to seriously consider whether their scientific modeling and simulation applications could benefit from the acceleration offered by new hardware and mixed-precision algorithms. In this survey, we (1) review progress across diverse scientific domains—fluid dynamics, weather and climate, quantum chemistry, and computational genomics—that have begun adopting mixed-precision strategies; (2) examine state-of-the-art algorithmic techniques such as iterative refinement, splitting and emulation schemes, and adaptive precision solvers; (3) assess their implications for accuracy, performance, and resource utilization; and (4) survey the emerging software ecosystem that enables mixed-precision methods at scale. We conclude with perspectives and recommendations on cross-cutting opportunities, domain-specific challenges, and the role of co-design between application scientists, numerical analysts, and computer scientists. Collectively, this survey underscores that mixed-precision numerics can reshape computational science by aligning algorithms with the evolving landscape of hardware capabilities.

Graphics processing units↗
NASA NTRS2008

Scalability of Localized Arc Filament Plasma Actuators

Temporal flow control of a jet has been widely studied in the past to enhance jet mixing or reduce jet noise. Most of this research, however, has been done using small diameter low Reynolds number jets that often have little resemblance to the much larger jets common in real world applications because the flow actuators available lacked either the power or bandwidth to sufficiently impact these larger higher energy jets. The Localized Arc Filament Plasma Actuators (LAFPA), developed at the Ohio State University (OSU), have demonstrated the ability to impact a small high speed jet in experiments conducted at OSU and the power to perturb a larger high Reynolds number jet in experiments conducted at the NASA Glenn Research Center. However, the response measured in the large-scale experiments was significantly reduced for the same number of actuators compared to the jet response found in the small-scale experiments. A computational study has been initiated to simulate the LAFPA system with additional actuators on a large-scale jet to determine the number of actuators required to achieve the same desired response for a given jet diameter. Central to this computational study is a model for the LAFPA that both accurately represents the physics of the actuator and can be implemented into a computational fluid dynamics solver. One possible model, based on pressure waves created by the rapid localized heating that occurs at the actuator, is investigated using simplified axisymmetric simulations. The results of these simulations will be used to determine the validity of the model before more realistic and time consuming three-dimensional simulations are conducted to ultimately determine the scalability of the LAFPA system.

Brown, Clifford A.↗
DOE OSTI2025

Software Quality Assurance for the MOOSE-Based Open-Source Multiphysics Code Cardinal - An Expanded CI Testing Suite

Cardinal is a wrapping of the GPU-oriented spectral element Computational Fluid Dynamics (CFD) code NekRS and the Monte Carlo particle transport code OpenMC within the Multiphysics Object-Oriented Simulation Environment (MOOSE). Cardinal provides high-resolution thermal-hydraulics and/or radiation transport feedback to MOOSE multiphysics simulations. Multiphysics feedback is implemented in a geometry-agnostic manner which eliminates the need for rigid one-to-one mappings. A generic data transfer implementation also allows NekRS and OpenMC to couple to any MOOSE application, enabling a broad set of multiphysics capabilities. Cardinal simulations can also leverage combinations of MPI, OpenMP, and GPU resources. Cardinal continuous development and improvement efforts have led to the software being considered as a high-fidelity design and licensing tool for key areas of nuclear reactor relevant physics, including neutron transport, fluid flow, heat transfer, and mechanical processes. The fast development and expansion of the software from a pure R&D framework towards its application in the nuclear industry and regulation require a focus on developing, enhancing and, maintaining Cardinal’s software quality through strict adherence to a Software Quality Assurance (SQA) framework and SQA program. To facilitate compliance with SQA standards, the Cardinal SQA Program has been initiated during Fiscal Year 2023 (FY23). During the development of the Cardinal SQA Program, multiple gaps have been identified. These gaps are primarily related to model verification and code pedigree as they relate to the use of Cardinal as a safety analysis tool. These gaps have been captured in a report published in 2023. A second report highlighted the progress made during Fiscal Year 2024 (FY24) and described Argonne’s effort to document and integrate software verification within Cardinal’s software development process. This report documents a snapshot of the verification test cases currently available for Cardinal and NekRS in their assimilation into a Continuous Integration (CI) platform. Following the CI practice permits the integrating of source code changes frequently and ensuring that the integrated codebase clears the verification testing for the software. It should be noted that the SQA program itself, including the program plans, procedures, configuration management, and testing strategies, need to be developed in a future step of this task.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1992

Structural Tailoring/Analysis for Hypersonic Components - A computational simulation

The development of STAHYC (Structural Tailoring/Analysis for Hypersonic Components), a numerical tool for the optimum design of an engine inlet wall panel for hypersonic aerospace vehicles, is described. STAHYC integrates FORTRAN modules of different disciplines, including fluid dynamics, heat transfer, structural analysis, and optimization. The discussion covers the system design concept, system components, system automation, system testing, established links, and data transfer between different computational modules. The various algorithms used in STAHYC are also discussed.

Narayanan, G. V.↗
DOE OSTI2025

Progress Towards NQA-1 for Cardinal in FY25

Cardinal is a wrapping of the GPU-oriented spectral element Computational Fluid Dynamics (CFD) code NekRS and the Monte Carlo particle transport code OpenMC within the Multiphysics Object-Oriented Simulation Environment (MOOSE). Cardinal provides high-resolution thermal-hydraulics and/or radiation transport feedback to MOOSE multiphysics simulations. Multiphysics feedback is implemented in a geometry-agnostic manner which eliminates the need for rigid one-to-one mappings. A generic data transfer implementation also allows NekRS and OpenMC to couple to any MOOSE application, enabling a broad set of multiphysics capabilities. Cardinal simulations can also leverage combinations of MPI, OpenMP, and GPU resources. Cardinal continuous development and improvement efforts have led to the software being considered as a high-fidelity design and licensing tool for key areas of nuclear reactor relevant physics, including neutron transport, fluid flow, heat transfer, and mechanical processes. The fast development and expansion of the software from a pure R&D framework towards its application in the nuclear industry and regulation require a focus on developing, enhancing,and maintaining Cardinal’s software quality through strict adherence to a Software Quality Assurance (SQA) framework and SQA program. To facilitate compliance with SQA standards, the Cardinal SQA Program was initiated during Fiscal Year 2023 (FY23). During the development of the Cardinal SQA Program, multiple gaps have been identified. These gaps are primarily related to model verification and code pedigree as they relate to the use of Cardinal as an analysis tool. These gaps were captured in a report published in 2023. A second report highlighted the progress made during Fiscal Year 2024 (FY24) and described Argonne’s effort to document and integrate software verification within Cardinal’s software development process. This report documents the progress made towards NQA-1 for Cardinal in the Fiscal Year 2025 (FY25). All cases in the expanded Continuous Integration (CI) suite of NekRS are included in this report which test the solvers and modules available in NekRS exhaustively. The NekRS tests are integrated with the Cardinal CI suite and made available in publicly accessible Github documentation. Following the CI practice permits integrating of source code changes frequently and ensuring that the integrated codebase clears the verification testing for the software. Also in this report is a brief overview of the development of the Cardinal Software Quality Assurance Plan (SQAP) that was done in FY25, though it should be noted that the rest of the documentation for the SQA program needs to be developed in a future step of this task.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Deep learning interfacial momentum closures in coarse-mesh CFD two-phase flow simulation using validation data

Multiphase flow phenomena have been widely observed in the industrial applications while it remains a challenging yet unsolved problems. Three-dimensional computational fluid dynamics (CFD) approaches resolve the flow fields on a finer special and temporal scales which can complement the dedicated experimental study. However, closures have to be introduced to reflect the underlying physics in multiphase flow. Among them, the interfacial forces, including drag, lift, turbulent dispersion and wall lubrication forces, play in important role on the bubble’s distribution and migration in liquid-vapor two-phase flow. Development of those closures traditionally rely on the experimental data and analytical derivation with simplified assumptions which usually cannot deliver a universal solution across wide range of flow conditions. In this paper, a data-driven approach, named as Feature Similarity Measurement (FSM), is developed and applied to improve the simulation capability of two-phase flow with coarse-mesh CFD approach. Interfacial momentum transfer in adiabatic bubbly flow serves as the focus of the present study. Both a mature and a simplified set of interfacial closures are taken as the low fidelity data. Experimental data and fine mesh CFD simulations results are adopted as high-fidelity data. Qualitative and quantitative analysis are performed in this paper which reveals that FSM can substantially improve the prediction of coarse mesh CFD model regardless of the choice of interfacial closures and it provides scalability and consistency across discontinuous flow regimes. Furthermore, it demonstrates that data-driven method can aid the multiphase flow modeling by exploring the connections between local physical features and simulation errors.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2014

Increased Mach Number Capability for the NASA Glenn 10x10 Supersonic Wind Tunnel

Computational simulations and wind tunnel testing were conducted to explore the operation of the Abe Silverstein Supersonic Wind Tunnel at the NASA Glenn Research Center at test section Mach numbers above the current limit of Mach 3.5. An increased Mach number would enhance the capability for testing of supersonic and hypersonic propulsion systems. The focus of the explorations was on understanding the flow within the second throat of the tunnel, which is downstream of the test section and is where the supersonic flow decelerates to subsonic flow. Methods of computational fluid dynamics (CFD) were applied to provide details of the shock boundary layer structure and to estimate losses in total pressure. The CFD simulations indicated that the tunnel could be operated up to Mach 4.0 if the minimum width of the second throat was made smaller than that used for previous operation of the tunnel. Wind tunnel testing was able to confirm such operation of the tunnel at Mach 3.6 and 3.7 before a hydraulic failure caused a stop to the testing. CFD simulations performed after the wind tunnel testing showed good agreement with test data consisting of static pressures along the ceiling of the second throat. The CFD analyses showed increased shockwave boundary layer interactions, which was also observed as increased unsteadiness of dynamic pressures collected in the wind tunnel testing.

Wind tunnel↗
NASA NTRS2015

Increased Mach Number Capability for the NASA Glenn 10x10 Supersonic Wind Tunnel

Computational simulations and wind tunnel testing were conducted to explore the operation of the Abe Silverstein Supersonic Wind Tunnel at the NASA Glenn Research Center at test section Mach numbers above the current limit of Mach 3.5. An increased Mach number would enhance the capability for testing of supersonic and hypersonic propulsion systems. The focus of the explorations was on understanding the flow within the second throat of the tunnel, which is downstream of the test section and is where the supersonic flow decelerates to subsonic flow. Methods of computational fluid dynamics (CFD) were applied to provide details of the shock boundary layer structure and to estimate losses in total pressure. The CFD simulations indicated that the tunnel could be operated up to Mach 4.0 if the minimum width of the second throat was made smaller than that used for previous operation of the tunnel. Wind tunnel testing was able to confirm such operation of the tunnel at Mach 3.6 and 3.7 before a hydraulic failure caused a stop to the testing. CFD simulations performed after the wind tunnel testing showed good agreement with test data consisting of static pressures along the ceiling of the second throat. The CFD analyses showed increased shockwave boundary layer interactions, which was also observed as increased unsteadiness of dynamic pressures collected in the wind tunnel testing.

Diffuser↗