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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 1,729 records · Page 96

Orientation Effects in Two-Phase Microgap Flow

The high power density of emerging electronic devices is driving the transition from remote cooling, which relies on con-duction and spreading, to embedded cooling, which extracts dissipated heat on-site. Two-phase microgap coolers employ the forced flow of dielectric fluids undergoing phase change in a heated channel within or between devices. Such coolers must work reliably in all orientations for a variety of applications (e.g., vehicle-based equipment), as well as in microgravity and high-g for other applications (e.g., spacecraft and aircraft). The lack of acceptable models and correlations for orientation- and gravity-independent operation has limited the use of two-phase coolers in such applications. Previous research has revealed that gravita-tional acceleration plays a diminishing role in establishing flow regimes and transport rates as the channel size shrinks, but there is considerable variation among the proposed microscale criteria and limited research on two-phase flows in low aspect ratio mi-crogap channels. Reliable criteria for achieving orientation- and gravity-independent flow boiling would enable emerging sys-tems to exploit this thermal management technique and streamline the technology development process. As a first step toward understanding the effect of gravity on two-phase microgap flow and transport, in the present effort the authors have studied the effect of evaporator orientation and mass flux on near-saturated flow boiling of HFE7100 in a 1.01 mm tall by 13.0 mm wide by 12.7 mm long microgap channel. Orientation-independence, defined as achieving similar critical heat fluxes, heat transfer coefficients, and flow regimes across evaporator orientations, was achieved for mass fluxes of 400 kg/m2-s and greater. The present results are compared to pub-lished criteria for achieving gravity-independence.

orientation↗

Space-Hardware Design for Long Life With High Reliability

In 1991, the Cassini Project, NASA's planetary project to place a spacecraft in orbit about Saturn, funded a study at the Jet Propulsion Laboratory (JPL) to identify rules for design and test of hardware required to function reliably in space for very long lifetimes. Twenty-nine subjects were considered comprising 130 specific rules related to long-life issues such as accelerated life testing, cycling of mechanical devices, selection and application of parts, semiconductor junction temperatures, and worst-case analysis for long life. The study was subsequently published as a JPL document. One major conclusion of the workshop was that unattended space missions extending out to 25 years or more are feasible.

design↗

Accelerating SNP Development with Radiation Source Approximations for Far-Field Environment Modeling

The successful development and deployment of space nuclear power and propulsion technology requires a high-fidelity, efficient means of modeling ex-core radiation fields. Monte Carlo particle transport codes provide enable the highest level of fidelity in radiation field modeling but are inefficient for modeling ex-core radiation without modification. This paper details the development of an approach to ex-core radiation field modeling that maintains the fidelity of a Monte Carlo transport approach without sacrificing computational efficiency. This approach is based on recent improvements to an existing Monte Carlo transport acceleration technique known as surface source banking. As the transport of many particles is required to ensure adequate uncertainty in far field transport, analytical reconstruction techniques are employed to represent surface source banks as sampleable series of distributions in particle phase from which an arbitrarily large number of particles can be generated and simulated. All steps of this approach are incorporated into an AMA model to test both the underlying mathematics of the analytical source reconstruction process, as well as the relevance of the technique as a whole towards SNP applications. These tests demonstrated that this approach is capable of accelerating far-field radiation modeling in SNP-relevant scenarios by factors of at least nine over purely eigenvalue-based scenarios without significantly sacrificing simulation accuracy.

Surface Source Banking↗

PCS: A Productive Computational Science Platform

As modern supercomputers continue to be increasingly heterogeneous with diverse computational accelerators, software becomes a critical aspect necessary to fully exploit these accelerators while not increasing the effort and time required to make variable scientific discovery in the face of complicated programming environments introduced by these accelerators. This paper presents PCS, a productive computational science platform for cluster-scale heterogeneous computing. The PCS platform by design follows a basic principle that, multiple programming models in a unified programming environment, is essential to facilitate large-scale, accelerator-aware, heterogeneous computing for next-generation scientific applications. We propose a new scheme — Edge Neural Network — for managing regularity in large dataflow graphs using higher-order bulk synchronous operators, providing a foundation for formalizing computational models for cluster-wide dataflow programming of heterogeneous clusters.

Ojika, David↗

Development of a S{sub n} transport code based on discontinuous finite element method and coarse mesh finite difference formulation

The methods and performance of a three-dimensional S{sub n} transport code employing the Discontinuous Finite Element Method (DFEM) and the Coarse Mesh Finite Difference (CMFD) formulation are presented. The mesh generator GMSH and a post processing visualization tool Visit are combined with the code for flexible geometry processing and versatile visualization. The CMFD method for DFEM Sn applications is formulated and the performance of the CMFD acceleration of eigenvalue calculations is demonstrated for a simple set of neutron transport problems. (authors)

97 MATHEMATICS AND COMPUTING↗

Irradiation in the Swiss Spallation Neutron Source and its Applications

In high power (∼ 1 MW or higher) spallation targets being operated or developed for different attractive applications such as neutron scattering science and technology or accelerator driven systems (ADS) for nuclear waste transmutation, both target and structural materials are exposed to intensive irradiation of high energy protons and spallation neutrons. Since spallation reactions induced by high energy protons can produce helium (He) and hydrogen (H) and other transmutation elements at very high rates, the behavior of materials used in a spallation irradiation environment can be much different from those observed from materials irradiated with neutrons in fission reactors. Therefore, the damage induced by spallation irradiation cannot be simply simulated by fission neutron irradiation experiments. Seven irradiation experiments have been conducted in the targets of the Swiss Spallation Neutron Source (SINQ) at the Paul Scherrer Institute (PSI) since 1998 within a broad international collaboration with Commissariat a L'energie Atomique Centre d'Etudes de Saclay (CEA), Forschungszentrum Juelich (FZJ), Japan Atomic Energy Agency (JAEA), Los Alamos National Laboratory (LANL), Oak Ridge National Laboratory (ORNL), University California Santa Barbara (UCSB) and several institutes of Chinese Academy of Sciences. More than 7000 samples from various Al-, Ti-, Fe-, Ni-, Zr-, and W-alloys and SiC/SiC, C/SiC and MAX-phase ceramics composites have been irradiated to doses up to ∼25 dpa (in Fe) and ∼2000 appm He at temperatures up to ∼800 deg. C. In addition, quite many specimens were irradiated in contact with stagnant liquid metals such as Hg, PbBi, PbLi etc. Dedicated post-irradiation examinations (PIE) have been performed, together with the international collaborators. Various mechanical tests including tensile, bend, Charpy-impact, small punch and hardness have been carried out to obtain the mechanical properties of the materials after irradiation. The microstructural changes in the irradiated specimens have been investigated by means of transmission electron microscopy, positron annihilation spectroscopy, atom probe tomography etc. Many novel results have been obtained from the PIE conducted by PSI and other STIP partner laboratories. The DBTT-shift of different FM steels increases more or less linearly with dose after irradiation in the SINQ target, while it saturates at a level of few dpa in fission neutron irradiation cases. This phenomenon can be mostly attributed to helium effects. In addition to the strong embrittlement effect, pronounced hardening effect was also detected in high dose specimens, which was contributed by high density helium bubbles.

36 MATERIALS SCIENCE↗

Engagement: Hyperparameter Optimization of Generative Adversarial Network Models for High-Energy Physics Simulations

We present our SciDAC FASTMath-HEP partnership results for tuning generative adversarial models (GANs) for high energy physics applications. The GANs are used in hybrid simulations to accelerate otherwise time-consuming computations. We optimize for both, prediction accuracy and variability with the goal to find GAN architectures that are reliable and robust.

high energy physics↗

Gamma Ray Detection In Liquid Argon Time Projection Chambers

Gamma rays are photons in excess of 100 keV of energy and can be produced by a variety of mechanisms like radioactive decay and inelastic neutrino-argon interactions. A reconstruc- tion of Compton scattering gamma rays was developed for use in liquid argon time projection chambers. This reconstruction was tested with detectors developed to demonstrate the ca- pabilities of Deep Underground Neutrino Experiment (DUNE) Near Detector Liquid Argon target (ND LAr). In October 2024, a radioactive fluorine-18 source was placed next to the Full Scale Demonstrator. The data obtained was used to test this reconstruction algorithm. It was able to determine the direction of the photons with an error of less than 10 percent. In addition to this work, there has been significant work on designing a liquid argon based Positron Emission Tomography (PET) scanner. PET scanners detect gamma rays emitted by a tracer chemical to help screen for diseases like cancer. In addition to the applications to medical imaging, this thesis briefly explores the applications of this reconstruction to de-excitation photons produced in interactions between neutrinos and argon nuclei. These applications could improve studies focusing on neutrinos originating from accelerators and supernovae.

Murphy, Thomas [Syracuse U.]↗

CRADA Final Report: CRADA Number NFE-14-05227 with Total E&P Research and Technology USA LLC

Cooperative Research and Development Agreement (CRADA) NFE-14-05227 between Oak Ridge National Laboratory (ORNL) and Total E&P Research and Development USA LLC (Total) focused on exploration of programming models and optimization opportunities for two families of seismic imaging algorithms frequently used within the oil and gas sector. Studies involved the use of OpenACC and OpenMP directive-based programming models for GPU accelerators on Reverse Time Migration (RTM), and Time Reverse Time Migration (tRTM) model applications. The work provided insights into both the directive language capabilities and gaps with respect to the needs of these algorithms and how the algorithms can be ported to GPU accelerators using directive languages.

58 GEOSCIENCES↗

Evolution of artificial intelligence for application in contemporary materials science

Abstract Contemporary materials science has seen an increasing application of various artificial intelligence techniques in an attempt to accelerate the materials discovery process using forward modeling for predictive analysis and inverse modeling for optimization and design. Over the last decade or so, the increasing availability of computational power and large materials datasets has led to a continuous evolution in the complexity of the techniques used to advance the frontier. In this Review, we provide a high-level overview of the evolution of artificial intelligence in contemporary materials science for the task of materials property prediction in forward modeling. Each stage of evolution is accompanied by an outline of some of the commonly used methodologies and applications. We conclude the work by providing potential future ideas for further development of artificial intelligence in materials science to facilitate the discovery, design, and deployment workflow. Graphical abstract

Materials Science↗

A novel sample-positioning system for microgravity application

This paper proposes a novel method for sample positioning in containerless processing at microgravity, using a system based on pulsed lasers. The method has two attributes. First, by generating beams that cancel out vectorially, the suspended material can be heated without being accelerated, a feature that can be used in melting and heat-treatment applications. Second, the specimen can be positioned within a fairly large work space. It is emphasized that this method can service a regime unfulfilled by the other levitation methods, such as electromagnetic levitation, active magnetic suspension, acoustic levitation, of electrostatic suspension.

Sridharan, G.↗

Development of scintillation materials for medical imaging and other applications

Scintillation materials that produce pulses of visible light in response to the absorption of energetic photons, neutrons, and charged particles, are widely used in various applications that require the detection of radiation. The discovery and development of new scintillators has accelerated in recent years, due in large part to their importance in medical imaging as well as in security and high energy physics applications. Better understanding of fundamental scintillation mechanisms as well as the roles played by defects and impurities have aided the development of new high performance scintillators for both gamma-ray and neutron detection. Although single crystals continue to dominate gamma-ray based imaging techniques, composite materials and transparent optical ceramics potentially offer advantages in terms of both synthesis processes and scintillation performance. A number of promising scintillator candidates have been identified during the last few years, and several are currently being actively developed for commercial production. Purification and control of raw materials and cost effective crystal growth processes can present significant challenges to the development of practical new scintillation materials.

36 MATERIALS SCIENCE↗

Variational encoder geostatistical analysis (VEGAS) with an application to large scale riverine bathymetry

Estimation of riverbed profiles, also known as bathymetry, plays a vital role in many applications, such as safe and efficient inland navigation, prediction of bank erosion, land subsidence, and flood risk management. The high cost and complex logistics of direct bathymetry surveys, i.e, depth imaging, have encouraged the use of indirect measurements such as surface flow velocities. However, estimating high-resolution bathymetry from indirect measurements is an inverse problem that can be computationally challenging. Here, we propose a reduced-order model (ROM) based approach that utilizes a variational autoencoder (VAE), a type of deep neural network with a narrow layer in the middle, to compress bathymetry and flow velocity information and accelerate bathymetry inverse problems from flow velocity measurements. In our application, the shallow-water equations (SWE) with appropriate boundary conditions (BCs), e.g., the discharge and/or the free surface elevation, constitute the forward problem, to predict flow velocity. Then, ROMs of the SWEs are constructed on a nonlinear manifold of low dimensionality through a variational encoder and the bathymetry inversion problem is derived on the low-dimensional latent space in a Hierarchical Bayesian setting. Further, the reformulation allows variational inference with a small number (e.g., $\mathscr{O}$ (100) of ROM runs and efficient uncertainty quantification. We have tested our inversion approach on a one-mile reach of the Savannah River, GA, USA. Once the neural network is trained (offline stage), the proposed technique can perform the inversion operation orders of magnitude faster than traditional inversion methods that are commonly based on linear projections, such as principal component analysis (PCA), or the principal component geostatistical approach (PCGA). Furthermore, tests show that the algorithm can estimate the bathymetry with good accuracy even with sparse flow velocity measurements.

54 ENVIRONMENTAL SCIENCES↗

Accelerating Floating-Point Computations with Intel AMX

Intel AMX is a built-in component of recent Intel CPU architectures, first supported by the Intel Sapphire Rapids in 2023, that enables efficient dense matrix multiplications using mixed precision with low-precision data types. The popularity of mixed-precision algorithms has grown recently, primarily due to their use on GPUs to enhance the efficiency of HPC applications, particularly for the training of large language models. The availability of mixed precision on CPUs represents a cost-effective solution for applications where high speed is not critical. This report shows how to use the Intel AMX accelerator through examples in C++ and Python. The examples will focus on mixed-precision floating-point operations obtained by the use of bfloat16 (or BF16) to accelerate code in single precision. We employ a bottom-up methodology, starting from specific register instructions (TMUL operation) to higher-level applications in libraries such as Intel MKL, PyTorch, and TensorFlow, ensuring a comprehensive understanding of the accelerator's potential. Additionally, we provide insights into the expected performance gains when leveraging the accelerator on the Kestrel HPC machine at the National Renewable Energy Laboratory.

97 MATHEMATICS AND COMPUTING↗

Laser-heated capillary discharge waveguides as tunable structures for laser-plasma acceleration

Laser-heated capillary discharge waveguides are novel, low plasma density guiding structures able to guide intense laser pulses over many diffraction lengths and have recently enabled the acceleration of electrons to 7.8 GeV by using a laser-plasma accelerator (LPA). These devices represent an improvement over conventional capillary discharge waveguides, as the channel matched spot size and plasma density can be tuned independently of the capillary radius. This has allowed the guiding of petawatt-scale pulses focused to small spot sizes within large diameter capillaries, preventing laser damage of the capillary structure. High performance channel-guided LPAs require control of matched spot size and density, which experiments and simulations reported here show can be tuned over a wide range via initial discharge and laser parameters. In this paper, measurements of the matched spot size and plasma density in laser-heated capillary discharges are presented, which are found to be in excellent agreement with simulations performed using the MHD code MARPLE. Strategies for optimizing accelerator performance are identified based on these results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Extensions of BLUP Models for Genomic Prediction in Heterogeneous Populations: Application in a Diverse Switchgrass Sample

Genomic prediction is a useful tool to accelerate genetic gain in selection using DNA marker information. However, this technology typically relies on standard prediction procedures, such as genomic BLUP, that are not designed to accommodate population heterogeneity resulting from differences in marker effects across populations. In this study, we assayed different prediction procedures to capture marker-by-population interactions in genomic prediction models. Prediction procedures included genomic BLUP and two kernel-based extensions of genomic BLUP which explicitly accounted for population heterogeneity. To model population heterogeneity, dissemblance between populations was either depicted by a unique coefficient (as previously reported), or a more flexible function of genetic distance between populations (proposed herein). Models under investigation were applied in a diverse switchgrass sample under two validation schemes: whole-sample calibration, where all individuals except selection candidates are included in the calibration set, and cross-population calibration, where the target population is entirely excluded from the calibration set. First, we showed that using fixed effects, from principal components or putative population groups, appeared detrimental to prediction accuracy, especially in cross-population calibration. Then we showed that modelling population heterogeneity by our proposed procedure resulted in highly significant improvements in model fit. In such cases, gains in accuracy were often positive. These results suggest that population heterogeneity may be parsimoniously captured by kernel methods. However, in cases where improvement in model fit by our proposed procedure is null-to-moderate, ignoring heterogeneity should probably be preferred due to the robustness and simplicity of the standard genomic BLUP model.

59 BASIC BIOLOGICAL SCIENCES↗

Applications of Wynn's epsilon-algorithm to transonic flow-calculations

Convergence acceleration of iterative solutions of potential and Euler equations, based on Wynn's epsilon-algorithm, is demonstrated. The extra computational work, to apply the technique, is negligible, while the storage requirement is definitely affordable with the present computers, at least, for two-dimensional inviscid flow problems.

Hafez, M.↗

Simultaneous operation of two soft x-ray free-electron lasers driven by one linear accelerator

Extreme-ultraviolet to x-ray free-electron lasers (FELs) in operation for scientific applications are up to now single-user facilities. While most FELs generate around 100 photon pulses per second, FLASH at DESY can deliver almost two orders of magnitude more pulses in this time span due to its superconducting accelerator technology. This makes the facility a prime candidate to realize the next step in FELs—dividing the electron pulse trains into several FEL lines and delivering photon pulses to several users at the same time. Hence, FLASH has been extended with a second undulator line and self-amplified spontaneous emission (SASE) is demonstrated in both FELs simultaneously. Here, FLASH can now deliver MHz pulse trains to two user experiments in parallel with individually selected photon beam characteristics. First results of the capabilities of this extension are shown with emphasis on independent variation of wavelength, repetition rate, and photon pulse length.

47 OTHER INSTRUMENTATION↗