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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Predictive Models and Novel Accelerated Tests for the Reliability of Cell Metallization in Photovoltaic Modules (Final Report)

Studies of metallization corrosion m photovoltaics have mainly been limited to comparisons of modules placed in accelerated chambers to fielded modules [1]. Damp Heat accelerated tests and phenomenological equations [2] are used to assess metallization corrosion without understanding the effect of UV light and temperature and humidity cycles on encapsulant adhesion degradation. The roles of encapsulant in-and out-diffusions of moisture and encapsulant impurities are important. Furthermore, few photovoltaic metallization corrosion studies included the role of bias and leakage currents, which are crucial in the electrochemical reaction of metallization. Leakage currents can highly accelerate the corrosion mechanism and are important to include in the studies of corrosion. In our research plan, we will address the following gaps in the PV community's understanding of metallization corrosion: (1) metallization corrosion with bias, humidity, and impurities in the encapsulant or metallization; (2) humidity diffusion through fresh and degraded encapsulants; and (3) comparison of model predictions with outdoor field modules and SunPower's extensive data for its back-contact and front-contact fleets [2] along with NREL's store of >20 year old modules. Our goal is to build models and accelerated tests to predict long term degradation of metallization corrosion of photovoltaic modules in the field. Our studies will include metals used in c-Si solar cells (Cu, Ag, and Al) and commonly used encapsulants (EV A (ethylene vinyl acetate), TPO (thermoplastic olefin), and silicone).

14 SOLAR ENERGY↗
DOE OSTI2023

Accelerating Adoption of Energy-Efficient Technology with the Thermalize Model

The accelerating impacts of climate change destabilize food systems and ecosystems alongside the communities that rely on them. Thus, climate resilience is a health equity issue at both a physical (relating to biological impacts of pollution and environmental degradation) and a cultural level (loss of subsistence lifestyles, languages, etc). With roughly 20% of US energy-related greenhouse gas emissions stemming from heating, cooling, and powering households, accessible energy-efficient home retrofits are a critical element of climate change mitigation strategies. For communities already producing electricity from renewable sources, like Juneau, incentivizing ductless heat pump upgrades and energy efficiency retrofits provides an accessible pathway to transition households away from oil heating and drastically reduce emissions. Thermalize Juneau is a pilot program that will explore a repeatable framework for accelerating the adoption of energy-efficient technology in Alaska communities. This poster will describe Thermalize Juneau's goals and framework, progress through spring 2021, and future plans.

ductless heat pumps↗
NASA NTRS1990

Simple model of plasma acceleration in a magnetic nozzle

A collisionless, steady-state, cold-plasma model is used to calculate the three-dimensional trajectory of a plasma as it is accelerated through a diverging magnetic field. The magnetic field is assumed to be axisymmetric with nonzero radial and axial components and zero azimuthal component. Although random thermal motion of plasma species is neglected in the cold plasma approximation, an important effect of plasma thermal energy is accounted for in the model as the kinetic energy of electrons in their Larmor motion about magnetic field lines. Calculations based on this model confirm previous studies which suggested that plasma separation from the field of a magnetic nozzle can take place even in the absence of collisional diffusion. It is shown that plasma divergence in a magnetic nozzle can be controlled by tailoring the field geometry.

Sercel, Joel C.↗
DOE OSTI2026

Acute wood smoke exposure is associated with cell-specific hippocampal transcriptomic responses in an accelerated ovarian failure mouse model

Background Wildfire events are increasing in frequency and intensity, and aging individuals demonstrate heightened biological susceptibility to air pollution exposures including increased risk of neurological sequelae. Declining ovarian hormones levels that occur with aging in females along with associated systemic physiological and inflammatory changes may contribute to increased cerebral vulnerability to air pollution, representing a potential but underexplored mechanism. Menopause and the menopausal transition represent a period of profound physiological change that affects cardiovascular, neurological, and immune health. Methods We tested whether peri-menopausal–like hormonal status amplifies hippocampal responses to acute wood smoke (WS) using an ovary-intact, 4-vinylcyclohexene diepoxide (VCD) model of moderate accelerated ovarian failure (AOF) in female C57BL/6 mice. Animals were exposed to HEPA-filtered air (FA) or WS for 4 h/day over 2 consecutive days (∼0.5 mg/m³). Exposure characterization confirmed a complex mixture of combustion products with significant levels of both trace metals and gas release during WS exposure. Results Spatial transcriptomics (10x Visium; n = 4 sections/group) with automated cell-type annotation identified astrocytes, GABAergic and glutamatergic neurons, oligodendrocytes, revealed cell type-specific transcriptional alterations following WS exposure. Distinct transcriptional patterns were observed across all identified neuronal and glial cell populations. Conclusion Together, these findings define a cell-type specific transcriptomic framework describing how WS exposure and ovarian hormone decline interact to influence hippocampal responses and identify potential cellular pathways relevant to hippocampal vulnerability.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2023

Advanced Modeling of Conventional Particle Accelerators

SciDAC-5 goals: Deliver particle accelerator and beam simulations tools that go beyond the current state of the art, up to the realization of virtual twins of particle accelerators, enabling design and modeling of particle accelerators at unprecedented speed, levels of accuracy, and realism; and apply these tools to key accelerator facilities relevant to DOE HEP (such as PIP-II/DUNE, FACET-II).

43 PARTICLE ACCELERATORS↗
NASA NTRS1986

A model of impulsive acceleration and transport of energetic particles in Mercury's magnetosphere

A qualitative model of substorm processes in the Mercury magnetosphere is presented based on Mariner 10 observations obtained in 1974-1975. The model is predicated on close analogies observed with the terrestrial case. Particular emphasis is given to energetic particle phenomena as observed by Mariner on March 29, 1974. The suggestion is supported that energetic particles up to about 500 keV are produced by strong induced electric fields at 3 to about 6 Mercury radii in the Hermean tail in association with substorm neutral line formation. The bursts of energetic particles produced are, in this model, subsequently confined on closed field lines near Mercury and drift adiabatically on quasi-trapped orbits for many tens of seconds. Such gradient and curvature drift of the particles can explain prominent periodicities of 5-10 s seen in the Mariner for greater than 170-keV electron flux profiles.

Baker, D. N.↗
DOE OSTI2021

An integrated Imaging and Modeling Toolbox for Accelerated Development of Root-focused Crops at Field Scales

This project, led by Yuxin Wu at the LBNL, was proposed to develop an integrated imaging-modeling toolbox allowing for accelerated development of root-focused crops at field scales. Our approach is based on a novel root phenotyping method we termed Tomographic Electrical Rhizosphere Imaging (TERI), which provides advanced phenotyping of key root traits by sensing the electrical impedance response of roots and soil to external electrical excitations, and mapping these responses to root and soil properties. The role of Noble Research Institute in this project is to assist TERI model establishment and validation by collecting various above- and below-ground traits data from container- and field-grown plants (mainly wheat). Over the last three years, Noble Research Institute has conducted 3 phases of experiments as proposed including: (Phase 1) greenhouse and hoop-house experiments in wheat and pecan plants grown under controlled container-grown conditions; (Phase 2) space-planted individual plant field experiment using different wheat varieties; and (Phase 3) small-plot planted field experiment using different wheat varieties, as well as using different small grains species including wheat, rye, triticale, oat and barley for increasing plant variation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Progress Towards Accelerating the Unified Model on Hybrid Multi-Core Systems

The cloud microphysics scheme, CASIM, and the radiation scheme, SOCRATES, are two computationally intensive parts within the Met Office's Unified Model (UM). This study enables CASIM and SOCRATES to use accelerated multi-core systems for optimal computational performance of the UM. Using profiling to guide our efforts, we refactored the code for optimal threading and kernel arrangement and implemented OpenACC directives manually or through the CLAW source-to-source translator. Initial porting results achieved 10.02x and 9.25x speedup in CASIM and SOCRATES respectively on 1 GPU compared with 1 CPU core. A granular performance analysis of the strategy and bottlenecks are discussed. These improvements will enable UM to run on heterogeneous computers and a path forward for further improvements is provided.

Zhang, Wei↗
DOE OSTI2024

Toward a Holistic Performance Evaluation of Large Language Models Across Diverse AI Accelerators

Artificial intelligence (AI) methods have become critical in scientific applications to help accelerate scientific discovery. Large language models (LLMs) are being considered a promising approach to address some challenging problems because of their superior generalization capabilities across domains. The effectiveness of the models and the accuracy of the applications are contingent upon their efficient execution on the underlying hardware infrastructure. Specialized Al accelerator hardware systems have recently become available for accelerating Al applications. However, the comparative performance of these AI accelerators on large language models has not been previously studied. In this paper, we systematically study LLMs on multiple AI accelerators and GPUs and evaluate their performance characteristics for these models. We evaluate these systems with (i) a micro-benchmark using a core transformer block, (ii) a GPT-2 model, and (iii) an 1,I,M-driven science use case, GenSLM. We present our findings and analyses of the models' performance to better understand the intrinsic capabilities of AI accelerators. Furthermore, our analysis takes into account key factors such as sequence lengths, scaling behavior, and sensitivity to gradient accumulation steps.

Emani, Murali↗
NASA NTRS1992

Electron acceleration in Tycho's and Kepler's supernova remnants - Spectral evidence of Fermi shock acceleration

First model synchrotron spectra calculated with a self-consistent nonlinear shock model of first order Fermi acceleration are presented and compared with the observed radio spectra of Tycho's and Kepler's SNR. Excellent agreement is obtained, and the correct mean spectral indices of about -0.64 are easily reproduced. The model spectra are slightly concave, with hardening toward higher energies, and there is evidence for such an effect in the data, allowing the mean magnetic field strength to be estimated in each remnant. Improvements in both theory and observation could allow accurate values of magnetic fields to be inferred from sufficiently precise integrated synchrotron spectra.

Reynolds, Stephen P.↗
NASA NTRS1989

An asymmetric outgassing model for cometary nongravitational accelerations

The standard nongravitation force model has been modified by allowing the water-vaproization curve to peak a certain number of days (DT) either before or after perihelion, and the modification is shown to often improve the data fit. The best fit to the astrometric data is generally achieved for a value of DT corresponding to the offset in the comet's visual light curve. The asymmetric model, which more accurately mimics the comet's outgassing history, suggests only weakly that the rotation direction of Comet Halley is direct, and it does not provide evidence that the rotation axis of Comet Kopff passed through its orbit plane in the early twentieth century. Approximate lag angles of 4 deg for Comet Halley and 10 deg for Comet d'Arrest are found using the asymmetric model, and it is noted that these values are lower than those obtained with the standard model.

Yeomans, D. K.↗
NASA NTRS1985

A leaky magnetohydrodynamic waveguide model for the acceleration of high-speed solar wind streams in coronal holes

It is now reasonably well established that there is a correlation between high-speed solar wind streams and coronal holes. It has been concluded that a significant addition of momentum and/or energy in the region of supersonic flow is needed to explain the observed particle flux and flow speed observed in the high-speed streams. The most likely source of this additional momentum appears to be magnetohydrodynamic (MHD) waves propagating up from the solar surface. The present investigation is concerned with the propagation of MHD waves in a structure of finite transverse size, taking into account the consequences for the acceleration of high-speed solar wind streams. A waveguide solution for a model coronal hole is described, giving attention to a geometric or ray analysis of the slab waveguide, a wave mode analysis, an analytic solution of the dispersion relation for high-frequency waves, and the calculation of the time-averaged wave force.

Davila, J. M.↗
DOE OSTI2024

Robust errant beam prognostics with conditional modeling for particle accelerators

Abstract Particle accelerators are complex and comprise thousands of components, with many pieces of equipment running at their peak power. Consequently, they can fault and abort operations for numerous reasons, lowering efficiency and science output. To avoid these faults, we apply anomaly detection techniques to predict unusual behavior and perform preemptive actions to improve the total availability. Supervised machine learning (ML) techniques such as siamese neural network models can outperform the often-used unsupervised or semi-supervised approaches for anomaly detection by leveraging the label information. One of the challenges specific to anomaly detection for particle accelerators is the data’s variability due to accelerator configuration changes within a production run of several months. ML models fail at providing accurate predictions when data changes due to changes in the configuration. To address this challenge, we include the configuration settings into our models and training to improve the results. Beam configurations are used as a conditional input for the model to learn any cross-correlation between the data from different conditions and retain its performance. We employ conditional siamese neural network (CSNN) models and conditional variational auto encoder (CVAE) models to predict errant beam pulses at the spallation neutron source under different system configurations and compare their performance. We demonstrate that CSNNs outperform CVAEs in our application.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Differentiable Preisach Modeling for Characterization and Optimization of Particle Accelerator Systems with Hysteresis

Future improvements in particle accelerator performance are predicated on increasingly accurate online modeling of accelerators. Hysteresis effects in magnetic, mechanical, and material components of accelerators are often neglected in online accelerator models used to inform control algorithms, even though reproducibility errors from systems exhibiting hysteresis are not negligible in high precision accelerators. Here, we combine the classical Preisach model of hysteresis with machine learning techniques to efficiently create nonparametric, high-fidelity models of arbitrary systems exhibiting hysteresis. We experimentally demonstrate how these methods can be used in situ, where a hysteresis model of an accelerator magnet is combined with a Bayesian statistical model of the beam response, allowing characterization of magnetic hysteresis solely from beam-based measurements. Finally, we explore how using these joint hysteresis-Bayesian statistical models allows us to overcome optimization performance limitations that arise when hysteresis effects are ignored.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Accelerated radiation transport modeling techniques for pencil beam computed tomography using gamma rays

Monte Carlo radiation transport modeling studies were performed for a compact, and high-resolution gamma-ray computed tomography system designed for imaging irradiated nuclear fuel. The system comprises a 60 Co source – chosen for its highly penetrating 1173 keV and 1332 keV gamma rays – a pair of high-aspect-ratio pencil beam collimators, and an inorganic scintillator detector. Here two acceleration methods are proposed to rapidly model a transmission type gamma-ray tomography system. The first, a variance reduction technique, is based on performing Monte Carlo simulations with a monodirectionally-biased source, sampled from a characteristic sub-volume of the full source volume. The second acceleration method is based on the deterministic calculations using the Beer–Lambert law and detector response characteristics. Comparison of simulations using acceleration approaches with analog simulations of the fully isotropic, full-volume equivalent, show that the Monte Carlo variance reduction technique gives quantitatively accurate predictions for large collimator aspect ratios while the deterministic calculations are semi-quantitative but converge close to the correct result as the collimator aspect ratio increases. As such, these techniques can be used to reduce the computational cost in generating simulated radiographs and tomographs by several orders of magnitude. Experimental validation efforts are currently underway and will be demonstrated in future work.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1990

Li-7 and Be-7 de-excitation lines - Probes for accelerated particle transport models in solar flares

The photon energy spectrum of a spectral feature composed of the 429 and 478 keV gamma-ray lines from Be-7 and Li-7 (produced by interactions of flare-accelerated alpha particles with ambient He in the solar atmosphere) depends on the angular distribution of the interacting accelerated particles. This spectrum is calculated for limb and disk-centered flares using a loop model for the transport of the ions. The resulting spectra are compared with data from the April 27, 1981 limb flare obtained with the gamma-ray spectrometer on SMM, providing convincing evidence for the existence of the (Li-7)-(Be-7) feature in this flare. By comparing the fluence of this feature with that of the 511 keV line, it is shown that the accelerated alpha particle abundance or the ambient He abundance, or both, must be enhanced.

Murphy, R. J.↗
NASA NTRS1989

The Li-7 and Be-7 deexcitation lines: Probes for accelerated particle transport models in solar flares

The photon energy spectrum of a spectral feature composed of the 429 and 478 keV gamma-ray lines from Li-7 and Be-7 (produced by interactions of flare-accelerated alpha particles with ambient He in the solar atmosphere) depends on the angular distribution of the interacting accelerated particles. This spectrum is calculated for limb and disc-centered flares using a loop model for the transport of the ions. In this model, the flux tube magnetic field is constant in the corona and converges in the chromosphere to the photosphere. Magnetic mirroring and MHD pitch-angle scattering are both taken into account. Comparison of these results with data from other experiments is presented.

Murphy, Ronald J.↗
DOE OSTI2026

Multiscale and multidimensional modeling of particle acceleration and transport in solar flares

Multi-messenger, multi-viewpoint, and time-resolved observations of solar flares are now providing unprecedented constraints on particle acceleration sites, energy conversion, and energy transport. The interpretation of current observations, including microwave imaging spectroscopy from EOVSA, hard x-ray (HXR) imaging from Solar Orbiter/STIX, gamma-ray diagnostics from Fermi, and in situ measurements from Parker Solar Probe and Solar Orbiter, collectively demands modeling frameworks that go beyond traditional spatially unresolved, one-zone models or single-mechanism descriptions. This review surveys multiscale and multidimensional modeling approaches, including kinetic, magnetohydrodynamic (MHD), and macroscopic particle models, that are being developed to meet the need. Kinetic simulations reveal that three-dimensional (3D) effects, including field-line chaos and self-generated turbulence, are essential for sustained power-law particle acceleration. MHD simulations now capture flux-rope eruptions, plasmoid-unstable current sheets, and turbulent flare regions in realistic magnetic topologies. Macroscopic models coupling MHD with energetic-particle models produce spatially resolved electron distributions and synthetic HXR and microwave emissions for direct comparison with observations. Despite these advances, outstanding challenges remain in bridging kinetic and global scales, improving MHD simulations and macroscopic particle models, and achieving quantitative model-observation closure.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗