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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
DOE OSTI2022

Evaluating seasonal and regional distribution of snowfall in regional climate model simulations in the Arctic

In this study, we investigate how the regional climate model HIRHAM5 reproduces the spatial and temporal distribution of Arctic snowfall when compared to CloudSat satellite observations during the examined period of 2007–2010. For this purpose, both approaches, i.e., the assessments of the surface snowfall rate (observation-to-model) and the radar reflectivity factor profiles (model-to-observation), are carried out considering spatial and temporal sampling differences. The HIRHAM5 model, which is constrained in its synoptic representation by nudging to ERA-Interim, represents the snowfall in the Arctic region well in comparison to CloudSat products. The spatial distribution of the snowfall patterns is similar in both identifying the southeastern coast of Greenland and the North Atlantic corridor as regions gaining more than twice as much snowfall as the Arctic average, defined here for latitudes between 66 and 81°N. Excellent agreement (difference less than 1%) in the Arctic-averaged annual snowfall rate between HIRHAM5 and CloudSat is found, whereas ERA-Interim reanalysis shows an underestimation of 45% and significant deficits in the representation of the snowfall rate distribution. From the spatial analysis, it can be seen that the largest differences in the mean annual snowfall rates are an overestimation near the coastlines of Greenland and other regions with large orographic variations as well as an underestimation in the northern North Atlantic Ocean. To a large extent, the differences can be explained by clutter contamination, blind zone or higher resolution of CloudSat measurements, but clearly HIRHAM5 overestimates the orographic-driven precipitation. The underestimation of HIRHAM5 within the North Atlantic corridor south of Svalbard is likely connected to a poor description of the marine cold air outbreaks which could be identified by separating snowfall into different circulation weather type regimes. By simulating the radar reflectivity factor profiles from HIRHAM5 utilizing the Passive and Active Microwave TRAnsfer (PAMTRA) forward-modeling operator, the contribution of individual hydrometeor types can be assessed. Looking at a latitude band at 72–73°N, snow can be identified as the hydrometeor type dominating radar reflectivity factor values across all seasons. The largest differences between the observed and simulated reflectivity factor values are related to the contribution of cloud ice particles, which is underestimated in the model, most likely due to the small sizes of the particles. The model-to-observation approach offers a promising diagnostic when improving cloud schemes, as illustrated by comparison of different schemes available for HIRHAM5.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Systems and methods for assessing cable insulation

Methods for assessing cable insulation are provided that can include engaging a first tine gap interdigital capacitor assembly with the exterior of the cable jacket to determine a first capacitance and dissipation factor value of the insulation using the first tine gap interdigital capacitor assembly; engaging a second tine gap interdigital capacitor assembly with the exterior of the cable jacket to determine a second capacitance and dissipation factor value of the insulation using the second tine gap interdigital capacitor assembly.Systems for assessing cable insulation are also provided. The systems can include a cable jacket encompassing cable insulation and conductive material; at least two tine gap interdigital capacitor assemblies engaged with the cable jacket; and processing circuitry operatively engaged with the capacitor assemblies.

Glass, III, Samuel W.↗
DOE OSTI2022

Effect of Coaxial Electrode Geometry on the Electric Field Enhancement Factor for a High Voltage Vacuum Gap

We present an experimental analysis of the change in the electric field enhancement factor with varying gap size and penetration depth (P.D) of cathode into anode for a coaxial vacuum gap, diagnosed using Fowler–Nordheim analysis and optical imaging via scanning electron microscope (SEM) and time integrated Digital single lens reflex camera (DSLR). Data were collected on the Coaxial Gap Breakdown Machine (240 A, 25 kV, 150 ns, 0.1 Hz). Experiments using five different gap sizes at nine different P.Ds are compared over runs comprising 50 shots for each case. The results show a strong link between enhancement factor and gap size, with P.D and surface topology. For large gap sizes, 150, 330, and 700 μm, the average enhancement factor value increases with increasing P.D. For smaller gap sizes, 50 and 100 μm, the average enhancement factor decreases with P.D. SEM imaging before and after plasma formation for each gap size allows for quantifying surface finish, microprotrusion growth, average blast diameter, and an estimation of the surface area breakdowns occupy. Time integrated DSLR imaging analysis of the gap at each shot allows for a determination of the distribution of breakdowns about the circumference of the gap for each case tested. Here, the Fowler–Nordheim analysis allows for a quantitative analysis of the surface roughness of all gap sizes tested. Results show that for large gap sizes, the gap geometry and increasing area of breakdown is the main cause for increasing average enhancement factor. For small gap sizes, the dominant driving factor for small average enhancement factors—that subsequently decrease with P.D—is significant changes in surface topology due to an increased number of breakdowns.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Westcott g factors extended to arbitrary neutron energy spectra

Westcott 𝑔 factors are used in Neutron Activation Analysis (NAA) and Prompt Gamma-ray Activation Analysis (PGAA) to evaluate the impact of non-1∕𝑣 behavior in the neutron-capture cross sections of certain nuclei on activation product yields. This non-1∕𝑣 behavior arises from the presence of neutron resonances in the neutron- capture cross sections that overlap with the source neutron spectrum at low (< 5 eV) energies. Historically, Westcott 𝑔 factors that have been cataloged for NAA and PGAA applications are the result of calculations that assume a Maxwellian neutron flux distribution with a given temperature. In this work, we use this approach with updated neutron-capture cross sections from the Evaluated Nuclear Data File, version VIII.1 (ENDF/B-VIII.1) to tabulate Westcott 𝑔 factor values for a broad range of Maxwellian distribution temperatures, comparing the results against currently-available 𝑔 factors from International Atomic Energy Agency tables and other sources. Here, it was discovered during this analysis that the use of guided thermal and cold-neutron beams at certain facilities necessitates an approach for evaluating Westcott 𝑔 factors based on arbitrary non-Maxwellian spectra. In this paper, we present an approach for calculating 𝑔 factors with user-specified neutron spectra, and we demonstrate these methods to obtain Westcott 𝑔-factors for guided- and cold-neutron beams at the Budapest Research Reactor and the Forschungsreaktor München II reactor. As part of this work, open-source software has been developed that can be used to perform these calculations for applications in PGAA and NAA experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Additive Manufactured Compact Microwave Absorbers

A high-performance, compact microwave absorber was created using Fused Deposition Modeling (FDM) 3D printing. Both a narrowband and a broadband absorber were created. The narrowband absorber was designed at 4.9 GHz, mid-band in WR-187 waveguide. The broadband absorber tried to achieve the best attenuation across the entire 3.95 to 5.85 GHz band. Two types of carbon loaded polylactic acid (PLA) plastic and one type of unloaded PLA were 3D printed with variable percentages of air to achieve different values of effective dielectric constant and loss tangent. The absorber comprised five or six rectangular pieces of these plastic materials. The thickness and fill factor values for each piece were optimized to minimize reflection through fast analytic modeling in MATLAB®. The results were then verified by HFSS® simulation as well. The stack progressed from the lowest loss and lowest dielectric constant to the highest at the shorting end. The final narrowband load had simulated return loss of 87 dB at 4.9 GHz with an analytic solution in MATLAB. The measured return loss of the 3D printed attenuator was 73 dB at 4.929 GHz. The total length of the absorber was 2.44 inches. A commercial absorber for WR-187 with return loss of 40 dB has length of 13 inches. The experiment proves that an effective and compact microwave absorber can be created using 3D printing.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Performance Optimization for Relative-Error-Bounded Lossy Compression on Scientific Data

Scientific simulations in high-performance computing (HPC) environments generate vast volume of data, which may cause a severe I/O bottleneck at runtime and a huge burden on storage space for postanalysis. Unlike traditional data reduction schemes such as deduplication or lossless compression, not only can error-controlled lossy compression significantly reduce the data size but it also holds the promise to satisfy user demand on error control. Pointwise relative error bounds (i.e., compression errors depends on the data values) are widely used by many scientific applications with lossy compression since error control can adapt to the error bound in the dataset automatically. Pointwise relative-error-bounded compression is complicated and time consuming. In this article, we develop efficient precomputation-based mechanisms based on the SZ lossy compression framework. Our mechanisms can avoid costly logarithmic transformation and identify quantization factor values via a fast table lookup, greatly accelerating the relative-error-bounded compression with excellent compression ratios. In addition, we reduce traversing operations for Huffman decoding, significantly accelerating the decompression process in SZ. Experiments with eight well-known real-world scientific simulation datasets show that our solution can improve the compression and decompression rates (i.e., the speed) by about 40 and 80 p, respectively, in most of cases, making our designed lossy compression strategy the best-in-class solution in most cases.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2021

Lorentzian dynamics and factorization beyond rationality

We investigate the emergence of topological defect lines in the conformal Regge limit of two-dimensional conformal field theory. We explain how a local operator can be factorized into a holomorphic and an anti-holomorphic defect operator connected through a topological defect line, and discuss implications on analyticity and Lorentzian dynamics including aspects of chaos. We derive a formula relating the infinite boost limit, which holographically encodes the “opacity” of bulk scattering, to the action of topological defect lines on local operators. Leveraging the unitary bound on the opacity and the positivity of fusion coefficients, we show that the spectral radii of a large class of topological defect lines are given by their loop expectation values. Factorization also gives a formula relating the local and defect operator algebras and fusion categorical data. We then review factorization in rational conformal field theory from a defect perspective, and examine irrational theories. On the orbifold branch of the c = 1 free boson theory, we find a unified description for the topological defect lines through which the twist fields are factorized; at irrational points, the twist fields factorize through “non-compact” topological defect lines which exhibit continuous defect operator spectra. Along the way, we initiate the development of a formalism to characterize non-compact topological defect lines.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Tuning Perovskites’ Hydration-Induced Chemical Expansion with Octahedral Tilt Angles

Hydration-induced strains in proton-conducting oxides compromise chemo-mechanical stability when these materials are applied in protonic ceramic electrochemical cells. Here, to develop design principles for zero-strain materials, we systematically studied the hydration coefficients of chemical expansion (CCEs) in perovskite (Sr, Ba)(Ce, Zr, Y)O 3–x solid solutions with in situ dilatometry and thermogravimetric analysis in the range of 430–630 °C. By including and decoupling a wide range of tolerance factors and lattice parameters, we were able to identify a minimum in hydration CCEs (0–0.02) at intermediate tolerance factor values (t ≈ 0.95). Conversely, despite expectations of lower CCEs in larger unit cells, no general trend in CCE versus lattice parameter was found, and opposite trends could be seen for Sr(Ce, Zr, Y)O 3–x versus Ba(Ce, Zr, Y)O 3–x separately. In situ neutron diffraction (ND) enabled atomistic insight. Upon decreasing t, chemical strain anisotropy increased, but this trend did not match the U-shaped dependence of macroscopic CCEs on t. Instead, perovskites with intermediate t, hosting intermediate octahedral tilt angles in the nominally dry state, underwent the largest change in the B–O–B angles during hydration. Accommodating hydration through decreasing B–O–B angles is beneficial because it does not result in large lattice parameter changes. We propose an intermediate tolerance factor as a simple structural descriptor to enable near-zero hydration strains in proton-conducting perovskites.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Co-optimizing water-alternating-carbon dioxide injection projects using a machine learning assisted computational framework

In this report, a robust machine-learning-based computational framework that couples multi-layer neural network (MLNN) proxies and a multi-objective particle swarm optimizer (MOPSO) to design water-alternating-carbon dioxide injection (CO 2 -WAG) projects is presented. The proposed optimization protocol considers various objectives, including oil recovery and CO 2 storage volume. Expert MLNN systems are trained and employed as surrogate models of the high-fidelity compositional simulator in the optimization workflow. When multiple objective functions are considered, two approaches are employed to treat the objectives: the weighted sum method and the Pareto-front-based scheme. A field-scale implementation focusing on tertiary recovery in the Morrow B formation at Farnsworth Unit (FWU) is presented. The developed Pareto-optimal solutions indicate the maximal available oil production can be 1.64 × 10 7 barrels and maximal carbon storage can achieve 2.35 × 10 7 tons. Trade-offs factor is defined to divide the constructed Pareto front into 4 sections with the trade-off factors’ value ranges from 0.35 to 49.9. This work also compares the optimum solution found by the aggregative objective function and the solution repository covered by the Pareto front that considers the physical and operational constraints and reduces uncertainties involved by the multi-objective optimization process. Our comparison indicates multiple solutions exist to satisfy the objective criteria of the WAG design, and these results cannot be found using the traditional weighted sum method. The Pareto front solution can provide more options for project designers, but decisions regarding necessary trade-offs must be made using the solution repository to balance the project economics and CO 2 storage amount.

10 SYNTHETIC FUELS↗
DOE OSTI2022

Machine learning prediction on the fractional free volume of polymer membranes

Fractional free volume (FFV) characterizes the microstructural level features of polymers and affects their properties including thermal, mechanical, and separation performance. Experimental measurements and theoretical analyses have been used to quantify the FFV of polymers, but challenges remain because of their limitations. Experimental measurements are laborious and based on semi empirical equations, while Bondi’s group contribution theory involves ambiguities like the determination of van der Waals volume and the choice of factor values in the theoretical equation. To efficiently evaluate the FFV of polymers, this study utilizes high-throughput molecular dynamics (MD) simulations to build a large dataset regarding polymer’s FFV. Based on this large dataset, we further build machine learning (ML) models to establish the composition-structure relation. Inspired by group contribution theory which correlates polymer’s functional groups to FFV, our ML models correlate polymer’s substructures or physico-chemical indexes to FFV. Here, our study first benchmarks the MD simulation protocol to obtain reliable FFV of polymers and then carries out high-throughput MD simulations for more than 6,500 homopolymers and 1,400 polyamides. Such a large and diverse dataset makes the well-trained ML models more generalizable, compared with the group contribution theory. The efficiency of a feed forward neural network model is further demonstrated by applying it to a hypothetical polyimide dataset of more than 8 million chemical structures. The predicted FFVs of hypothetical polyimides are further validated by MD simulations. The obtained FFVs of the 8 million polymers, plus their previously reported gas separation performances, demonstrate the promising capability of ML virtual screening for the discovery of polymer membranes with exceptional permeability/selectivity.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Coherent Phonon Dynamics in Plasmonic Gold Tetrahedral Nanoparticle Ensembles

Coherent phonon modes supported by plasmonic nanoparticles offer prospective applications in chemical and biological sensing. Whereas characterization of these phonon modes often requires single particle measurements, synthetic routes to narrow size distributions of nanoparticles permit ensemble investigations. Recently, the synthesis of highly monodisperse gold tetrahedral nanoparticles with tunable edge length and corner sharpness has been developed. Herein, we characterize a size series of these nanoparticles in colloidal dispersion via transient absorption spectroscopy to examine their mechanical and plasmonic responses upon photoexcitation. Oscillations of transient absorption signals are observed in the plasmon resonance and correspond to the lowest order radial breathing modes of the nanoparticles, the frequencies of which are affected by edge length and truncation of the corners. Furthermore, quality factor values ranging from 10 to 15 are observed for the oscillations that convey potential utility in mass-sensing and plasmon-exciton coupling photonics schemes. Finite-difference time domain and finite element analysis calculations establish the specific optically-relevant phonon modes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Chemical treatment effects on Schottky contacts to metalorganic chemical vapor deposited n-type N-polar GaN

In this article, we investigate the effect of different chemical treatments, such as solvents, bases, and acids, on the surface properties and electrical behavior of Schottky diodes fabricated on metalorganic chemical vapor deposition-grown, n-type, N-polar GaN. The I–V and C–V barrier heights of the as-grown Schottky diodes are found to be 0.40 eV and 0.60 eV, respectively, with an ideality factor n = 1.07. It is found that the solvent treatments neither change the surface nor the electrical performance of the Schottky diodes, as expected. However, the treatments by the alkaline photolithography developer and acid—the latter of which is often used to clean the surface of Ga-polar GaN films prior to metal contact deposition—degrade the performance of N-polar GaN. These base and acid treatments severely roughen the surface by creating triangular/hexagonal crystallographic facets. The I–V and C–V barrier heights of these base- and acid-treated diodes are increased to 0.63 eV and 1.00 eV, respectively, with ideality factor values n < 1.2. X-ray photoelectron spectroscopy studies indicate that base- and acid-treated surfaces have lower oxygen content as compared to the as-grown sample surface. It is understood that the increment in the barrier height for base- and acid-treated diodes could be due to the change in polarity, from N-polar to semi-polar/non-polar, on these crystallographic features. All these results demonstrate that, unlike for Ga-polar GaN, the N-polar GaN surface is highly reactive to bases and acids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Novel intrinsic helical cores and MHD dynamo flux pumping evidence in DIII-D

Evidence of a MHD dynamo brought about by intrinsic helical core structures in negative triangularity (NT) and ITER baseline scenario (IBS) plasmas demonstrates paths to operating tokamaks without seeds for deleterious global MHD modes. A stationary sawtooth- and edge localized mode-free state maintains high performance for long durations in a strong NT shape in the DIII-D tokamak. Disparity between minimum safety factor values predicted by magnetic flux diffusion theory and derived from experiment suggests anomalous flux diffusion by an MHD dynamo, driven by flows associated with quasi-interchange modes. Stability calculations with the GATO code find NT and IBS experimental equilibria unstable to quasi-interchange modes, in agreement with observed saturated activity. IBS discharges with similar magnetic winding structure occupy robust helical core states following a transition from sawtooth instabilities. These states agree with prior modeling of helical core bifurcation thresholds with the VMEC equilibrium code.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Magnetism and spin dynamics in room-temperature van der Waals magnet Fe 5 GeTe 2

Two-dimensional van der Waals (vdWs) materials have gathered a lot of attention recently. However, the majority of these materials have Curie temperatures that are well below room temperature, making it challenging to incorporate them into device applications. In this work, we synthesized a room-temperature vdW magnetic crystal Fe 5 GeTe 2 with a Curie temperature T c = 332 K, and studied its magnetic properties by vibrating sample magnetometry (VSM) and broadband ferromagnetic resonance (FMR) spectroscopy. The experiments were performed with external magnetic fields applied along the c -axis (H∥ c ) and the ab -plane (H∥ ab ), with temperatures ranging from 300 to 10 K. We have found a sizable Landé g -factor difference between the H∥ c and H∥ ab cases. In both cases, the Landé g -factor values deviated from g = 2. This indicates contribution of orbital angular momentum to the magnetic moment. The FMR measurements reveal that Fe 5 GeTe 2 has a damping constant comparable to Permalloy. With reducing temperature, the linewidth was broadened. Together with the VSM data, our measurements indicate that Fe 5 GeTe 2 transitions from ferromagnetic to ferrimagnetic at lower temperatures. Our experiments highlight key information regarding the magnetic state and spin scattering processes in Fe 5 GeTe 2 , which promote the understanding of magnetism in Fe 5 GeTe 2 , leading to implementations of Fe 5 GeTe 2 based room-temperature spintronic devices.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Study of the ${{^{25}}}$Mg(d,p)${{^{26}}}$Mg reaction to constrain the ${{^{25}}}$Al(p,${\gamma }$)${{^{26}}}$Si resonant reaction rates in nova burning conditions

The rate of the 25 Al( p,γ) 26 Si reaction is one of the few key remaining nuclear uncertainties required for predicting the production of the cosmic γ-ray emitter 26 Al in explosive burning in novae. This reaction rate is dominated by three key resonances (J π = 0 + , 1 + and 3 + ) in 26 Si. Only the 3 + resonance strength has been directly constrained by experiment. A high resolution measurement of the 25 Mg(d, p) reaction was used to determine spectroscopic factors for analog states in the mirror nucleus, 26 Mg. A first spectroscopic factor value is reported for the 0 + state at 6.256 MeV, and a strict upper limit is set on the value for the 1 + state at 5.691 MeV, that is incompatible with an earlier ( 4 He, 3 He) study. These results are used to estimate proton partial widths, and resonance strengths of analog states in 26 Si contributing to the 25 Al( p,γ) 26 Si reaction rate in nova burning conditions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Near-Surface Hydrology and Soil Properties Drive Heterogeneity in Permafrost Distribution, Vegetation Dynamics, and Carbon Cycling in a Sub-Arctic Watershed: Modeling Archive

This Modeling Archive is in support of a NGEE-Arctic publication: Shirley et al. (2022) “Near-Surface Hydrology and Soil Properties Drive Heterogeneity in Permafrost Distribution, Vegetation Dynamics, and Carbon Cycling in a Sub-Arctic Watershed". [DOI].The dataset contains outputs from the global sensitivity analysis (GSA) of the “ecosys” model as reported in Shirley et al. (2022). The study showed that discontinuous permafrost environments are characterized by complex feedback loops and strong spatial heterogeneity which is created by variability in near-surface hydrology and soil properties. Additionally, the study demonstrated that missing representation of sub-grid heterogeneity in terrestrial ecosystem models can lead to biased estimates of the high-latitude carbon budget. Included in this dataset are the factor values for each run in the GSA and the model outputs used in this study. Included are two *.csv data files and one *.pdf.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

A Physics-Informed Reinforcement Learning Framework for Economic-Thermal Co-Optimization of Crypto Mining Data Centers: Preprint

The rapid expansion of cryptocurrency mining has created a new class of high-density data centers characterized by extreme thermal flux and high sensitivity to volatile economic markets. Traditional thermal management strategies, typically reliant on rule-based control, maintain static setpoints that fail to account for fluctuating electricity prices and cryptocurrency values - factors critical to mining profitability. To address this, we present a physics-informed reinforcement learning (PIRL) framework for economic-thermal co-optimization in crypto mining data centers. This framework consists of a proximal policy optimization (PPO) agent, a virtual testbed powered by high-fidelity physics-based models, and an interactive frontend dashboard. The PPO agent is trained using the virtual testbed and strict hardware safety limits. This physics-informed approach allows the agent to learn a stochastic policy that dynamically balances mining revenue against operational costs by co-optimizing HVAC cooling setpoints and IT computational hashrate. The simulation results demonstrate that the integrated framework achieved an 8.62% increase in net operational profit compared to traditional baseline strategies while strictly adhering to safety-critical temperature constraints (coolant supply temperature < 32 degrees C). This work provides a scalable template for the deployment of reinforcement learning in mission critical facilities where economic volatility and physical safety must be managed simultaneously.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗