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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

A high-performance workflow system for subsurface simulation

Subsurface modeling applications typically neglect uncertainty in the conceptual models, past or future scenarios, and attribute most or all uncertainty to errors in model parameters. In this contribution, uncertainty in technetium-99 transport in a heterogeneous, deep vadose zone is explored with respect to the conceptual model using a next generation user environment called Akuna. Akuna provides a range of tools to manage environmental modeling projects, from managing simulation data to visualizing results from high-performance computational simulators. Core toolsets accessible through the user interface include model setup, grid generation, parameter estimation, and uncertainty quantification. The BC Cribs site at Hanford in southeastern Washington State is used to demonstrate Akuna capabilities. At the BC Cribs site, conceptualization of the system is highly uncertain because only sparse information is available for the geologic conceptual model, the physical and chemical properties of the sediments, and the history of waste disposal operations. Using the Akuna toolset to perform an analysis of conservative solute transport, significant prediction uncertainty in simulated concentrations is demonstrated by conceptual model variation. This demonstrates that conceptual model uncertainty is an important consideration in sparse data environments such as BC Cribs. It is also demonstrated that Akuna and the underlying toolset provides an integrated modeling environment that streamlines model setup, parameter optimization, and uncertainty analyses for high-performance computing applications.

Akuna↗
NASA NTRS1995

Three Dimensional Solution of Pneumatic Active Control of Forebody Vortex Asymmetry

Pneumatic active control of asymmetric vortical flows around a slender pointed forebody is investigated using the three dimensional solution for the compressible thin-layer Navier-Stokes equation. The computational applications cover the normal and tangential injection control of asymmetric flows around a 5 degree semi-apex angle cone at a 40 degree angle of attack, 1.4 freestream Mach number and 6 x 10(exp 6) freestream Reynolds number (based on the cone length). The effective tangential angle range of 67.5 approaches minus 67.5 degrees is used for both normal and tangential ports of injection. The effective axial length of injection is varied from 0.03 to 0.05. The computational solver uses the implicit, upwind, flux difference splitting finite volume scheme, and the grid consists of 161 x 55 x 65 points in the wrap around, normal and axial directions, respectively. The results show that tangential injection is more effective than normal injection.

Kandil, Osama A.↗
DOE OSTI2016

Limited‐memory adaptive snapshot selection for proper orthogonal decomposition

Summary Reduced order models are useful for accelerating simulations in many‐query contexts, such as optimization, uncertainty quantification, and sensitivity analysis. However, offline training of reduced order models (ROMs) can have prohibitively expensive memory and floating‐point operation costs in high‐performance computing applications, where memory per core is limited. To overcome this limitation for proper orthogonal decomposition, we propose a novel adaptive selection method for snapshots in time that limits offline training costs by selecting snapshots according an error control mechanism similar to that found in adaptive time‐stepping ordinary differential equation solvers. The error estimator used in this work is related to theory bounding the approximation error in time of proper orthogonal decomposition‐based ROMs, and memory usage is minimized by computing the singular value decomposition using a single‐pass incremental algorithm. Results for a viscous Burgers' test problem demonstrate convergence in the limit as the algorithm error tolerances go to zero; in this limit, the full‐order model is recovered to within discretization error. A parallel version of the resulting method can be used on supercomputers to generate proper orthogonal decomposition‐based ROMs, or as a subroutine within hyperreduction algorithms that require taking snapshots in time, or within greedy algorithms for sampling parameter space. Copyright © 2016 John Wiley & Sons, Ltd.

Oxberry, Geoffrey M.↗
DOE OSTI2025

Derivation of at-birth neutron energy distribution of americium-beryllium source based on ISO8529 spectral data

In many practical applications, the accuracy of neutron transport calculations depends on an estimate of the energy distribution provided in the source definition. While the energy distribution of neutrons emitted by spontaneous fission sources is well-defined, the spectra of neutrons produced in (α,n) reactions in compound mixtures, such as americium-beryllium (AmBe), depend on the microstructural properties of the source material, which may vary. Although the energy of neutrons produced in nuclear reactions can be calculated from first principles, such computations require detailed knowledge of the key characteristics of the source material, which are often unknown. Here, this study focuses on deriving the at-birth neutron energy distribution for an AmBe source by applying reverse transport calculations to the externally measured high-precision spectrum recommended in the latest revision of the international standard. The derived at-birth spectrum was validated through indirect energy-sensitive neutron emission rate measurements of AmBe sources calibrated at national primary metrology institutions. The resulting at-birth neutron energy distribution serves as essential input data for radiation transport modeling, providing a validated spectrum for broader experimental and computational applications.

AmBe↗
NASA NTRS2023

Users' Guide to Vinci: Personal Computer Software for Planning Image-based Measurements in Wind Tunnels

Vinci is software that can be used to plan image-based measurements in wind tunnels. It allows the user to plan the placement of cameras and the choice of lenses well in advance of a test, thereby reducing the set-up time and cost when tunnel occupancy begins. It can also be used post-test to display data (pressure-sensitive paint, particle image velocimetry, model deformation) in context with the test article. Vinci is self-contained and runs on personal computers under Windows operating systems. No other software is required. Test articles are represented by CFD-like surface grids that may be read from an external file or created within the program as a combination of simple geometric shapes. The user controls the position and orientation of the test article through a Graphical User Interface (GUI) and may add many additional objects, including tunnel walls and windows, a wide variety of simple geometric shapes, mirrors, lamps, and laser sheets. The application computes simulated images from up to 40 cameras. Images are based on pinhole projection. Each camera is defined by the sensor size and the focal length of the lens. All camera parameters, including position and point angles, are controlled through the GUI. Simulated images are displayed in a window of the GUI and may be saved as bitmaps.

Users’ Guide, Image Planning, Wind Tunnels, Softwa↗
DOE OSTI2018

Qualifying for the Green500: Experience with the newest generation of supercomputers at LANL

The High Performance Computing Division of Los Alamos National Laboratory recently brought four new supercomputing platforms on line: Trinity with separate partitions built around the Haswell and Knights Landing CPU architectures for capability computing and Grizzly, Fire, and Ice for capacity computing applications. The power monitoring infrastructure of these machines is significantly enhanced over previous supercomputing generations at LANL and all were qualified at the highest level of the Green500 benchmark. Here, this paper discusses supercomputing at LANL, the Green500 benchmark, and notes on our experience meeting the Green500's reporting requirements.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Materials for Ultra‐Coherent, Mobile, Electron‐Spin Qubits

This research project has had the goal of gaining a better understanding of the physics of electrons bound to the surface of superfluid helium from both experimental and theoretical perspectives. It has particularly been aimed at two areas which had not been well studied: the relaxation and decoherence of the spin of the electrons on the helium surface and how the properties of underlying metallic layers affect the behavior of the electrons when the helium covering the metal is thin. This work is motivated in part by interest in using the spin of these electrons as a quantum bit, or qubit. Low levels of decoherence are advantageous for qubits, and moving the electrons, as one might do in a quantum processor, will be easiest if thin helium films can be employed. It had been suggested that spin decoherence should be very weak for electrons bound to superfluid He, but before this work there have been no quantitative studies of spin relaxation and decoherence. It is especially important to know how moving the electrons across the helium surface would affect their spin coherence. Calculations performed as part of this project show that the Rashba effective magnetic field, the mechanism which limits the spin coherence of mobile electrons in silicon-based devices (an actively pursued qubit technology), is exceptionally weak for electrons bound to helium. This project has identified other decoherence mechanisms which are stronger, but still weak compared to analogous silicon-based structures. Calculated spin coherence times for mobile electrons approach one day, as compared to microseconds in silicon. With coherence times of this magnitude, the spin qubit errors on helium will be completely dominated by errors in the quantum gates. In related work, the possibility of using an artificial spin-orbit interaction (a gradient magnetic field) for quantum operations on the electrons spins was considered. The calculations show that a moderate gradient field, small enough to be generated by a narrow superconducting wire, will enable high-fidelity quantum operations on electrons held in lithographically-defined quantum dots by driving them with a microwave electric field. The spin and motional coherence of the electrons is sufficient to allow high-fidelity 2-qubit quantum operations between electrons in neighboring quantum dots. As an outgrowth of experiments aiming to measure electron spin coherence it was discovered that very high densities of electrons can be stably supported on thin helium films coating ultra-smooth amorphous metallic layers. The measured densities are high enough that the electron system has almost certainly transitioned from an ordered array of electrons, known as a Wigner crystal (ordered by the electrons’ mutual repulsion), to a quantum fluid known as a Fermi liquid. This transition has been a subject of intense interest for over 40 years, since the electron Wigner crystal was first observed with electrons bound to superfluid helium, but it has never been unambiguously observed. Experiments are still underway in these new structures to definitively determine whether true quantum melting of the Wigner crystal has been demonstrated. This work has also catalyzed the development of a new approach for measuring the transport of electrons across very thin helium films, as will be needed for some of the quantum computing applications. The high electron density experiments as well as experiments with electrons bound in quantum dots have led to new techniques which may enable spin coherence measurements.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Limited-memory adaptive snapshot selection for proper orthogonal decomposition

Reduced order models are useful for accelerating simulations in many-query contexts, such as optimization, uncertainty quantification, and sensitivity analysis. However, offline training of reduced order models can have prohibitively expensive memory and floating-point operation costs in high-performance computing applications, where memory per core is limited. To overcome this limitation for proper orthogonal decomposition, we propose a novel adaptive selection method for snapshots in time that limits offline training costs by selecting snapshots according an error control mechanism similar to that found in adaptive time-stepping ordinary differential equation solvers. The error estimator used in this work is related to theory bounding the approximation error in time of proper orthogonal decomposition-based reduced order models, and memory usage is minimized by computing the singular value decomposition using a single-pass incremental algorithm. Results for a viscous Burgers’ test problem demonstrate convergence in the limit as the algorithm error tolerances go to zero; in this limit, the full order model is recovered to within discretization error. The resulting method can be used on supercomputers to generate proper orthogonal decomposition-based reduced order models, or as a subroutine within hyperreduction algorithms that require taking snapshots in time, or within greedy algorithms for sampling parameter space.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Quantum Computing and Simulations for Energy Applications

While quantum computing (QC) is considered as a paradigm shift in our basic understanding of physical computation, effective implementation of QC in energy applications also depends on progress and development in the dimensions of both QC hardware and algorithms. To fully address the status and future challenges of QC applied within the energy sector, in this presentation, we firstly summarize recent advancements on the applications of QC to energy infrastructure and materials, complex energy system processes, advanced manufacturing, and energy system security. Then, we will demonstrate the results of QC performed both on a simulator and a quantum device targeting on energy-related applications.

Paudel, Hari P.↗
NASA NTRS1992

Tenth Workshop for Computational Fluid Dynamic Applications in Rocket Propulsion, part 1

Experimental and computational fluid dynamic activities in rocket propulsion were discussed. The workshop was an open meeting of government, industry, and academia. A broad number of topics were discussed including computational fluid dynamic methodology, liquid and solid rocket propulsion, turbomachinery, combustion, heat transfer, and grid generation.

R.W. Williams↗
DOE OSTI2015

Optimization of X-ray tomography through a cooperative computing system in grid

Cooperative Computing implemented as Cooperative Computing System (CCS) in grid has been proved a considerably reliable technique to execute the tasks with real time constraints in a grid environment. This technique can be applied in many high performance distributed computing applications. HPC has a large number of applications in various fields of physics. One such application in radiation physics is X-ray tomography. X-Ray tomography contains numerous applications in various fields of science, technology and research. As the technology is changing from analog to digital in almost all the scenarios, this paper presents an idea towards the attachment of X-ray tomography assembly to HPC environment so as to obtain the highly reliable optimization.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Neuromorphic Photonics Based on Phase Change Materials

Neuromorphic photonics devices based on phase change materials (PCMs) and silicon photonics technology have emerged as promising solutions for addressing the limitations of traditional spiking neural networks in terms of scalability, response delay, and energy consumption. In this review, we provide a comprehensive analysis of various PCMs used in neuromorphic devices, comparing their optical properties and discussing their applications. We explore materials such as GST (Ge 2 Sb 2 Te 5 ), GeTe-Sb 2 Te 3 , GSST (Ge 2 Sb 2 Se 4 Te 1 ), Sb 2 S 3 /Sb 2 Se 3 , Sc 0.2 Sb 2 Te 3 (SST), and In 2 Se 3 , highlighting their advantages and challenges in terms of erasure power consumption, response rate, material lifetime, and on-chip insertion loss. By investigating the integration of different PCMs with silicon-based optoelectronics, this review aims to identify potential breakthroughs in computational performance and scalability of photonic spiking neural networks. Further research and development are essential to optimize these materials and overcome their limitations, paving the way for more efficient and high-performance photonic neuromorphic devices in artificial intelligence and high-performance computing applications.

36 MATERIALS SCIENCE↗
NASA NTRS1988

User's manual for EZPLOT version 5.5: A FORTRAN program for 2-dimensional graphic display of data

EZPLOT is a computer applications program that converts data resident on a file into a plot displayed on the screen of a graphics terminal. This program generates either time history or x-y plots in response to commands entered interactively from a terminal keyboard. Plot parameters consist of a single independent parameter and from one to eight dependent parameters. Various line patterns, symbol shapes, axis scales, text labels, and data modification techniques are available. This user's manual describes EZPLOT as it is implemented on the Ames Research Center, Dryden Research Facility ELXSI computer using DI-3000 graphics software tools.

Garbinski, Charles↗
DOE OSTI2025

Harnessing ferro-valleytricity in pentalayer rhombohedral graphene for memory and compute

Two-dimensional materials with multiple degrees of freedom, including spin, valleys, and orbitals, open up an exciting avenue for engineering multifunctional devices. Beyond spintronics, these degrees of freedom can lead to novel quantum effects such as valley-dependent Hall effects and orbital magnetism, which could revolutionize next-generation electronics. However, achieving independent control over valley polarization and orbital magnetism has been a challenge due to the need for large electric fields. A recent breakthrough involving pentalayer rhombohedral graphene has demonstrated the ability to individually manipulate anomalous Hall signals and orbital magnetic hysteresis, forming what is known as a valley-magnetic quartet. Here, we leverage the electrically tunable ferro-valleytricity of pentalayer rhombohedral graphene to develop nonvolatile memory and in-memory computation applications. We propose an architecture for a dense, scalable, and selector-less nonvolatile memory array that harnesses the electrically tunable ferro-valleytricity. In our designed array architecture, nondestructive read and write operations are conducted by sensing the valley state through two different pairs of terminals, allowing for independent optimization of read/write peripheral circuits. The power consumption of our PRG-based array is remarkably low, with only ∼6 nW required per write operation and ∼2.3 nW per read operation per cell. This consumption is orders of magnitude lower than that of the majority of state-of-the-art cryogenic memories. Additionally, we engineer in-memory computation by implementing majority logic operations within our proposed nonvolatile memory array without modifying the peripheral circuitry. In conclusion, our framework presents a promising pathway toward achieving ultra-dense cryogenic memory and in-memory computation capabilities.

2D materials↗
DOE OSTI2016

Calculating Reuse Distance from Source Code

The efficient use of a system is of paramount importance in high-performance computing. Applications need to be engineered for future systems even before the architecture of such a system is clearly known. Static performance analysis that generates performance bounds is one way to approach the task of understanding application behavior. Performance bounds provide an upper limit on the performance of an application on a given architecture. Predicting cache hierarchy behavior and accesses to main memory is a requirement for accurate performance bounds. This work presents our static reuse distance algorithm to generate reuse distance histograms. We then use these histograms to predict cache miss rates. Experimental results for kernels studied show that the approach is accurate.

Cache memory↗
DOE OSTI2016

Polymer heat exchanger design for condensing boiler applications

Condensing boilers achieve very high efficiency levels by recovering both sensible heat and water vapor latent heat from the flue gas. Research since the 1980's has focused on corrosion in such condensing heat exchangers related to the acidic condensate and material selection. Polymers in condensing heat exchangers have been considered to avoid the cost and corrosion concerns of metallic designs. Past efforts have shown that polymers offer the advantage of corrosion resistance and cost, however, lower thermal conductivity limited their application. More recent developments have introduced thermally conductive polymers which now offer promising conductivity values. This project focused on the evaluation of a thermally conductive polymer heat exchanger for this application. Computational fluid dynamic results indicated thermal conductivity values of stainless steel, a typical heat exchanger material, do not need to be achieved for similar heat transfer performance. An increase in thermal conductivity from about 10 times that of the base polymer can achieve an overall heat exchanger effectiveness similar to that achieved with stainless steel. A polymer composite thermal conductivity of approximately 2.5 W/m∙K would be adequate. Thermally conductive polymer materials are now commercially available which offer values up to 20 W/m∙K. In this work, one Nylon-12 and one thermally conductive polymer composite heat exchanger prototypes were constructed for a condensing boiler application. In conclusion, tests demonstrated that good overall heat transfer performance was achieved. The lower thermal conductivity of the polymer heat exchanger will lead to higher surface temperatures and lower water condensation rates.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

SU-F-T-111: Investigation of the Attila Deterministic Solver as a Supplement to Monte Carlo for Calculating Out-Of-Field Radiotherapy Dose

Purpose: To use the Attila deterministic solver as a supplement to Monte Carlo for calculating out-of-field organ dose in support of epidemiological studies looking at the risks of second cancers. Supplemental dosimetry tools are needed to speed up dose calculations for studies involving large-scale patient cohorts. Methods: Attila is a multi-group discrete ordinates code which can solve the 3D photon-electron coupled linear Boltzmann radiation transport equation on a finite-element mesh. Dose is computed by multiplying the calculated particle flux in each mesh element by a medium-specific energy deposition cross-section. The out-of-field dosimetry capability of Attila is investigated by comparing average organ dose to that which is calculated by Monte Carlo simulation. The test scenario consists of a 6 MV external beam treatment of a female patient with a tumor in the left breast. The patient is simulated by a whole-body adult reference female computational phantom. Monte Carlo simulations were performed using MCNP6 and XVMC. Attila can export a tetrahedral mesh for MCNP6, allowing for a direct comparison between the two codes. The Attila and Monte Carlo methods were also compared in terms of calculation speed and complexity of simulation setup. A key perquisite for this work was the modeling of a Varian Clinac 2100 linear accelerator. Results: The solid mesh of the torso part of the adult female phantom for the Attila calculation was prepared using the CAD software SpaceClaim. Preliminary calculations suggest that Attila is a user-friendly software which shows great promise for our intended application. Computational performance is related to the number of tetrahedral elements included in the Attila calculation. Conclusion: Attila is being explored as a supplement to the conventional Monte Carlo radiation transport approach for performing retrospective patient dosimetry. The goal is for the dosimetry to be sufficiently accurate for use in retrospective epidemiological investigations.

60 APPLIED LIFE SCIENCES↗