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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Validation of a Three-Dimensional Ablation and Thermal Response Simulation Code

The 3dFIAT code simulates pyrolysis, ablation, and shape change of thermal protection materials and systems in three dimensions. The governing equations, which include energy conservation, a three-component decomposition model, and a surface energy balance, are solved with a moving grid system to simulate the shape change due to surface recession. This work is the first part of a code validation study for new capabilities that were added to 3dFIAT. These expanded capabilities include a multi-block moving grid system and an orthotropic thermal conductivity model. This paper focuses on conditions with minimal shape change in which the fluid/solid coupling is not necessary. Two groups of test cases of 3dFIAT analyses of Phenolic Impregnated Carbon Ablator in an arc-jet are presented. In the first group, axisymmetric iso-q shaped models are studied to check the accuracy of three-dimensional multi-block grid system. In the second group, similar models with various through-the-thickness conductivity directions are examined. In this group, the material thermal response is three-dimensional, because of the carbon fiber orientation. Predictions from 3dFIAT are presented and compared with arcjet test data. The 3dFIAT predictions agree very well with thermocouple data for both groups of test cases.

Chen, Yih-Kanq↗
DOE OSTI2025

Visualization techniques for the gyrokinetic tokamak simulation code

Gyrokinetic simulations of plasma microturbulence in tokamaks are challenging to visualize because the compute grid follows the magnetic field lines that spiral around the torus. We have overcome this challenge by developing three new approaches that improve visualization of gyrokinetics. Our techniques work directly with the topology of magnetic flux surfaces where the simulation stores variables in concentric rings on poloidal planes (vertical cross sections of the torus). Our visualization preview step triangulates each consecutive pair of rings to display the data on a poloidal plane. The second visualization technique follows spiral field lines around the torus and constructs polygons to visualize a flux surface. Third, the poloidal triangles are connected between planes to form prisms that compose a 3-D model of the entire torus. The visualization workflow produces detailed geometry that matches the high resolution, irregular compute grid for every time step. The surface and solid models are displayed in scientific visualization programs to effectively explore and communicate the results, including fluctuation of electron density, ion temperature, and electrostatic potential. Highly detailed renderings verify plasma behavior along magnetic field lines over time.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1994

Some Problems and Solutions in Transferring Ecosystem Simulation Codes to Supercomputers

Many computer codes for the simulation of ecological systems have been developed in the last twenty-five years. This development took place initially on main-frame computers, then mini-computers, and more recently, on micro-computers and workstations. Recent recognition of ecosystem science as a High Performance Computing and Communications Program Grand Challenge area emphasizes supercomputers (both parallel and distributed systems) as the next set of tools for ecological simulation. Transferring ecosystem simulation codes to such systems is not a matter of simply compiling and executing existing code on the supercomputer since there are significant differences in the system architectures of sequential, scalar computers and parallel and/or vector supercomputers. To more appropriately match the application to the architecture (necessary to achieve reasonable performance), the parallelism (if it exists) of the original application must be exploited. We discuss our work in transferring a general grassland simulation model (developed on a VAX in the FORTRAN computer programming language) to a Cray Y-MP. We show the Cray shared-memory vector-architecture, and discuss our rationale for selecting the Cray. We describe porting the model to the Cray and executing and verifying a baseline version, and we discuss the changes we made to exploit the parallelism in the application and to improve code execution. As a result, the Cray executed the model 30 times faster than the VAX 11/785 and 10 times faster than a Sun 4 workstation. We achieved an additional speed-up of approximately 30 percent over the original Cray run by using the compiler's vectorizing capabilities and the machine's ability to put subroutines and functions "in-line" in the code. With the modifications, the code still runs at only about 5% of the Cray's peak speed because it makes ineffective use of the vector processing capabilities of the Cray. We conclude with a discussion and future plans.

Skiles, J. W.↗
NASA NTRS2016

Parallel Grand Canonical Monte Carlo (ParaGrandMC) Simulation Code

This report provides an overview of the Parallel Grand Canonical Monte Carlo (ParaGrandMC) simulation code. This is a highly scalable parallel FORTRAN code for simulating the thermodynamic evolution of metal alloy systems at the atomic level, and predicting the thermodynamic state, phase diagram, chemical composition and mechanical properties. The code is designed to simulate multi-component alloy systems, predict solid-state phase transformations such as austenite-martensite transformations, precipitate formation, recrystallization, capillary effects at interfaces, surface absorption, etc., which can aid the design of novel metallic alloys. While the software is mainly tailored for modeling metal alloys, it can also be used for other types of solid-state systems, and to some degree for liquid or gaseous systems, including multiphase systems forming solid-liquid-gas interfaces.

Vesselin I Yamakov↗
NASA NTRS1985

Electromagnetic particle simulation codes

Electromagnetic particle simulations solve the full set of Maxwell's equations. They thus include the effects of self-consistent electric and magnetic fields, magnetic induction, and electromagnetic radiation. The algorithms for an electromagnetic code which works directly with the electric and magnetic fields are described. The fields and current are separated into transverse and longitudinal components. The transverse E and B fields are integrated in time using a leapfrog scheme applied to the Fourier components. The particle pushing is performed via the relativistic Lorentz force equation for the particle momentum. As an example, simulation results are presented for the electron cyclotron maser instability which illustrate the importance of relativistic effects on the wave-particle resonance condition and on wave dispersion.

Pritchett, P. L.↗
DOE OSTI2025

Understanding power and energy utilization in large scale production physics simulation codes

Power is an often-cited reason for the move to advanced architectures on the path to Exascale computing. Here, this is due to practical considerations related to delivering enough power to successfully site and operate these machines, as well as concerns about energy usage while running large simulations. Since obtaining accurate power measurements can be challenging, it may be tempting to use the processor thermal design power (TDP) as a surrogate due to its simplicity and availability. However, TDP is not indicative of typical power usage while running simulations. Using commodity and advanced technology systems at Lawrence Livermore and Sandia National Labs, we performed a series of experiments to measure power and energy usage in running simulation codes. These experiments indicate that large scale Lawrence Livermore simulation codes are significantly more efficient than a simple processor TDP model might suggest.

HPC↗
NASA NTRS1995

Transferring ecosystem simulation codes to supercomputers

Many ecosystem simulation computer codes have been developed in the last twenty-five years. This development took place initially on main-frame computers, then mini-computers, and more recently, on micro-computers and workstations. Supercomputing platforms (both parallel and distributed systems) have been largely unused, however, because of the perceived difficulty in accessing and using the machines. Also, significant differences in the system architectures of sequential, scalar computers and parallel and/or vector supercomputers must be considered. We have transferred a grassland simulation model (developed on a VAX) to a Cray Y-MP/C90. We describe porting the model to the Cray and the changes we made to exploit the parallelism in the application and improve code execution. The Cray executed the model 30 times faster than the VAX and 10 times faster than a Unix workstation. We achieved an additional speedup of 30 percent by using the compiler's vectoring and 'in-line' capabilities. The code runs at only about 5 percent of the Cray's peak speed because it ineffectively uses the vector and parallel processing capabilities of the Cray. We expect that by restructuring the code, it could execute an additional six to ten times faster.

Skiles, J. W.↗
DOE OSTI2026

INtegrated Fluid & paRticles simulatioN cOde (INF&RNO) v1.0

INF&RNO (INtegrated Fluid & paRticle simulation cOde) is a 2D cylindrical (r-z) code to model the interaction of short laser pulse(s) with an underdense plasma. The code is based on an envelope model for the laser field, and the action of the laser on the plasma is modeled with the time-averaged ponderomotive force approximation. The code features an improved laser envelope solver which enables an accurate description of the laser pulse evolution deep into depletion even at a reasonably low resolution.

Benedetti, Carlo [Lawrence Berkeley National Labor↗
NASA NTRS2003

Large-Eddy Simulation Code Developed for Propulsion Applications

A large-eddy simulation (LES) code was developed at the NASA Glenn Research Center to provide more accurate and detailed computational analyses of propulsion flow fields. The accuracy of current computational fluid dynamics (CFD) methods is limited primarily by their inability to properly account for the turbulent motion present in virtually all propulsion flows. Because the efficiency and performance of a propulsion system are highly dependent on the details of this turbulent motion, it is critical for CFD to accurately model it. The LES code promises to give new CFD simulations an advantage over older methods by directly computing the large turbulent eddies, to correctly predict their effect on a propulsion system. Turbulent motion is a random, unsteady process whose behavior is difficult to predict through computer simulations. Current methods are based on Reynolds-Averaged Navier- Stokes (RANS) analyses that rely on models to represent the effect of turbulence within a flow field. The quality of the results depends on the quality of the model and its applicability to the type of flow field being studied. LES promises to be more accurate because it drastically reduces the amount of modeling necessary. It is the logical step toward improving turbulent flow predictions. In LES, the large-scale dominant turbulent motion is computed directly, leaving only the less significant small turbulent scales to be modeled. As part of the prediction, the LES method generates detailed information on the turbulence itself, providing important information for other applications, such as aeroacoustics. The LES code developed at Glenn for propulsion flow fields is being used to both analyze propulsion system components and test improved LES algorithms (subgrid-scale models, filters, and numerical schemes). The code solves the compressible Favre-filtered Navier- Stokes equations using an explicit fourth-order accurate numerical scheme, it incorporates a compressible form of Smagorinsky s model for the subgrid-scale turbulence, and it uses generalized curvilinear coordinates to allow analysis of a wide range of geometries. The code runs in parallel on shared memory multiprocessor computers and is written in Fortran 90 with dynamic memory allocation. A sample result for a Mach-1.4 round jet is presented in the figure. Instantaneous Mach number contours in several cross-planes downstream of the nozzle exit are shown, illustrating how an LES captures the large unsteady three-dimensional turbulent structures present in the jet.

DeBonis, James R.↗
NASA NTRS2015

Use of a Viscous Flow Simulation Code for Static Aeroelastic Analysis of a Wing at High-Lift Conditions

In this paper, we present a static aeroelastic analysis of a wind tunnel test model of a wing in high-lift configuration using a viscous flow simulation code. The model wing was tailored to deform during the tests by amounts similar to a composite airliner wing in highlift conditions. This required use of a viscous flow analysis to predict the lift coefficient of the deformed wing accurately. We thus utilized an existing static aeroelastic analysis framework that involves an inviscid flow code (Cart3d) to predict the deformed shape of the wing, then utilized a viscous flow code (Overflow) to compute the aerodynamic loads on the deformed wing. This way, we reduced the cost of flow simulations needed for this analysis while still being able to predict the aerodynamic forces with reasonable accuracy. Our results suggest that the lift of the deformed wing may be higher or lower than that of the non-deformed wing, and the washout deformation of the wing is the key factor that changes the lift of the deformed wing in two distinct ways: while it decreases the lift at low to moderate angles of attack simply by lowering local angles of attack along the span, it increases the lift at high angles of attack by alleviating separation.

Aeroelastic↗
NASA NTRS1985

Hybrid simulation codes with application to shocks and upstream waves

Hybrid codes in which part of the plasma is represented as particles and the rest as a fluid are discussed. In the past few years such codes with particle ions and massless, fluid electrons have been applied to space plasmas, especially to collisionless shocks. All of these simulation codes are one-dimensional and similar in structure, except for how the field equations are solved. The various approaches that are used (resistive Ohm's law, predictor-corrector, Hamiltonian) are described in detail and results from the various codes are compared with examples taken from collisionless shocks and low frequency wave phenomena upstream of shocks.

Winske, D.↗
NASA NTRS1987

On the inadequacies of current multi-flexible body simulation codes

DISCOS was used to simulate the spin-up of a uniform flexible beam mounted on a rigid spinning disk. The system operated well for the first few seconds but then there was a drastic rise in deflection as the whole system became unstable. Attention is given to the reason for the breakdown of DISCOS and how this affects the simulation results from DISCOS and other multiflexible-body simulation programs. It is found that a formulation option already available in DISCOS will eliminate the dramatic divergence observed in high spin regimes and give good results in low spin regimes while requiring highly simplified input data.

Eke, Fidelis O.↗
NASA NTRS1994

Scalability study of parallel spatial direct numerical simulation code on IBM SP1 parallel supercomputer

The implementation and the performance of a parallel spatial direct numerical simulation (PSDNS) code are reported for the IBM SP1 supercomputer. The spatially evolving disturbances that are associated with laminar-to-turbulent in three-dimensional boundary-layer flows are computed with the PS-DNS code. By remapping the distributed data structure during the course of the calculation, optimized serial library routines can be utilized that substantially increase the computational performance. Although the remapping incurs a high communication penalty, the parallel efficiency of the code remains above 40% for all performed calculations. By using appropriate compile options and optimized library routines, the serial code achieves 52-56 Mflops on a single node of the SP1 (45% of theoretical peak performance). The actual performance of the PSDNS code on the SP1 is evaluated with a 'real world' simulation that consists of 1.7 million grid points. One time step of this simulation is calculated on eight nodes of the SP1 in the same time as required by a Cray Y/MP for the same simulation. The scalability information provides estimated computational costs that match the actual costs relative to changes in the number of grid points.

Hanebutte, Ulf R.↗
NASA NTRS1989

A general concurrent algorithm for plasma particle-in-cell simulation codes

The general concurrent particle-in-cell (GCPIC) algorithm has been used to implement an electrostatic particle-in-cell code on a 32-node hypercube parallel computer. The GCPIC algorithm decomposes the PIC code by dividing the particle simulation physical domain into subdomains that are equal in number to the number of processors; all subdomains will accordingly possess approximately equal numbers of particles. The portion of the code which updates particle positions and velocities is nearly 100 percent efficient when the number of particles increases linearly with that of hypercube processors.

Liewer, Paulett C.↗
NASA NTRS2007

An Introduction to Thermodynamic Performance Analysis of Aircraft Gas Turbine Engine Cycles Using the Numerical Propulsion System Simulation Code

This document is intended as an introduction to the analysis of gas turbine engine cycles using the Numerical Propulsion System Simulation (NPSS) code. It is assumed that the analyst has a firm understanding of fluid flow, gas dynamics, thermodynamics, and turbomachinery theory. The purpose of this paper is to provide for the novice the information necessary to begin cycle analysis using NPSS. This paper and the annotated example serve as a starting point and by no means cover the entire range of information and experience necessary for engine performance simulation. NPSS syntax is presented but for a more detailed explanation of the code the user is referred to the NPSS User Guide and Reference document (ref. 1).

Jones, Scott M.↗
NASA NTRS2019

WRLES: Wave Resolving Large-Eddy Simulation Code, Theory and Usage

A computational fluid dynamics code has been developed for large-eddy simulations (LES) of turbulent flow. The code uses high-order of accuracy and high-resolution numerical methods to minimize solution error and maximize the resolution of the turbulent structures. Spatial discretization is performed using explicit central differencing. The central differencing schemes in the code include 2nd- to 12th-order standard central difference methods as well as 7-, 9-, 11- and 13-point dispersion relation preserving schemes. Solution filtering and high-order shock capturing are included for stability. Time discretization is performed using multistage Runge-Kutta methods that are up to 4th order accurate. Several options are available to model turbulence including: Baldwin-Lomax and Spalart-Allmaras Reynolds-averaged Navier-Stokes turbulence models, and Smagorinsky, Dynamic Smagorinsky and Vreman sub-grid scale models for LES. This report presents the theory behind the numerical and physical models used in the code and provides a user's manual to the operation of the code.

High-Order↗
NASA NTRS2008

Evaluation of Recent Upgrades to the NESS (Nuclear Engine System Simulation) Code

The Nuclear Thermal Rocket (NTR) concept is being evaluated as a potential propulsion technology for exploratory expeditions to the moon, Mars, and beyond. The need for exceptional propulsion system performance in these missions has been documented in numerous studies, and was the primary focus of a considerable effort undertaken during the Rover/NERVA program from 1955 to 1973. The NASA Glenn Research Center is leveraging this past NTR investment in their vehicle concepts and mission analysis studies with the aid of the Nuclear Engine System Simulation (NESS) code. This paper presents the additional capabilities and upgrades made to this code in order to perform higher fidelity NTR propulsion system analysis and design, and a comparison of its results to the Small Nuclear Rocket Engine (SNRE) design.

Fittje, James E.↗
NASA NTRS2007

Upgrades to the NESS (Nuclear Engine System Simulation) Code

In support of the President's Vision for Space Exploration, the Nuclear Thermal Rocket (NTR) concept is being evaluated as a potential propulsion technology for human expeditions to the moon and Mars. The need for exceptional propulsion system performance in these missions has been documented in numerous studies, and was the primary focus of a considerable effort undertaken during the 1960's and 1970's. The NASA Glenn Research Center is leveraging this past NTR investment in their vehicle concepts and mission analysis studies with the aid of the Nuclear Engine System Simulation (NESS) code. This paper presents the additional capabilities and upgrades made to this code in order to perform higher fidelity NTR propulsion system analysis and design.

Fittje, James E.↗