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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Measuring the Muon Neutrino Magnetic Moment in the NOvA Near Detector

Measuring an enhanced neutrino magnetic moment would be a clear indication of physics beyond the Standard Model, shedding light on the correct beyond Standard Model theory or the potential Majorana nature of neutrinos. It would manifest in the NOvA near detector as an excess of neutrino-on-electron elastic scattering interactions at low electron recoil energies. Leveraging an intense and highly pure muon neutrino beam, along with a finely segmented liquid scintillator detector technology specifically designed for electromagnetic shower separation, enables NOvA to achieve a potentially world-leading sensitivity in probing the effective muon neutrino magnetic moment. This analysis, based on neutrino data collected between 2014 and 2021, corresponding to an exposure of $13.8\times10^{20}$ protons-on-target, yields a result consistent with the Standard Model-only hypothesis with a p-value of 0.31. An upper limit on the effective muon neutrino magnetic moment is set at $\mu_{\nu_\mu}<19.1\times 10^{-10}\mu_B$ at $90\%$ confidence level. Despite facing statistical limitations stemming from low cross section of the signal process, systematic uncertainties have a significant impact on this result. To address these challenges, the NOvA Test Beam experiment focuses on mitigating some of the largest systematic uncertainties within NOvA by investigating particle interactions and energy deposition in a small-scale replica NOvA detector. This thesis describes the calibration of the NOvA Test Beam detector, which is a crucial step in analysing the Test Beam data before they can be utilised to reduce NOvA systematic uncertainties.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Validation of the Cloud_CCI (Cloud Climate Change Initiative) cloud products in the Arctic

The role of clouds in the Arctic radiation budget is not well understood. Ground-based and airborne measurements provide valuable data to test and improve our understanding. However, the ground-based measurements are intrinsically sparse, and the airborne observations are snapshots in time and space. Passive remote sensing measurements from satellite sensors offer high spatial coverage and an evolving time series, having lengths potentially of decades. However, detecting clouds by passive satellite remote sensing sensors is challenging over the Arctic because of the brightness of snow and ice in the ultraviolet and visible spectral regions and because of the small brightness temperature contrast to the surface. Consequently, the quality of the resulting cloud data products needs to be assessed quantitatively. In this study, we validate the cloud data products retrieved from the Advanced Very High Resolution Radiometer (AVHRR) post meridiem (PM) data from the polar-orbiting NOAA-19 satellite and compare them with those derived from the ground-based instruments during the sunlit months. The AVHRR cloud data products by the European Space Agency (ESA) Cloud Climate Change Initiative (Cloud_CCI) project uses the observations in the visible and IR bands to determine cloud properties. The ground-based measurements from four high-latitude sites have been selected for this investigation: Hyytiälä (61.84°N, 24.29°E), North Slope of Alaska (NSA; 71.32°N, 156.61°W), Ny-Ålesund (Ny-Å; 78.92°N, 11.93°E), and Summit (72.59°N, 38.42°W). The liquid water path (LWP) ground-based data are retrieved from microwave radiometers, while the cloud top height (CTH) has been determined from the integrated lidar–radar measurements. The quality of the satellite products, cloud mask and cloud optical depth (COD), has been assessed using data from NSA, whereas LWP and CTH have been investigated over Hyytiälä, NSA, Ny-Å, and Summit.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Effects of Supplementation in Upper Yakima River Chinook Salmon

Abstract To promote recovery of natural salmonid populations, managers are utilizing hatchery supplementation programs to increase abundance of spawners on the spawning grounds. However, studies have provided evidence that captive breeding can result in domestication, demonstrated by lower fitness of hatchery‐origin compared with natural‐origin fish. Supplementation programs, therefore, typically use natural‐origin broodstock in an effort to minimize long‐term negative fitness impacts. Here we evaluated the upper Yakima River spring supplementation program for Chinook Salmon Oncorhynchus tshawytscha , which has broodstock comprised exclusively of unmarked fish presumed to be of natural‐origin. Using 5 years of spawner data, we tested for effects of hatchery breeding and rearing on total adult returns and their individual reproductive success when spawning naturally. Our study revealed that supplementation increased overall abundance of fish spawning naturally on the spawning grounds. However, on average, compared with natural‐origin spawners, hatchery‐origin fish had reduced reproductive success, which also translated to reduced reproductive success in three out of five return years for natural‐origin fish that spawned with hatchery‐origin fish. As expected, body length and return timing were also significant predictors of reproductive success. However, more generations of data are needed to establish the extent to which reduced reproductive success is passed on to naturally produced progeny.

Koch, Ilana J.↗
DOE OSTI2020

Wave-by-Wave Forecasting via Assimilation of Marine Radar Data

Abstract This work describes a phase-resolving wave-forecasting algorithm that is based on the assimilation of marine radar image time series. The algorithm is tested against synthetic data and field observations. The algorithm couples X-band marine radar observations with a phase-resolving wave model that uses the linear mild slope equations for reconstruction of water surface elevations over a large domain of O (km) and a prescribed time window of O (min). The reconstruction also enables wave-by-wave forecasting through forward propagation in space and time. Marine radar image time series provide the input wave observations through a previously given relationship between backscatter intensity and the radial component of the sea surface slope. The algorithm assimilates the wave slope information into the model via a best-fit wave source function at the boundary that minimizes the slope reconstruction error over an annular region at the outer ranges of the radar images. The wave model is then able to propagate the waves across a polar domain to a location of interest at nearer ranges. The constraints on the method for achieving real-time forecasting are identified, and the algorithm is verified against synthetic data and tested using field observations.

Engineering↗
DOE OSTI2023

Continental Scale Hydrostratigraphy: Comparing Geologically Informed Data Products to Analytical Solutions

Abstract This study synthesizes two different methods for estimating hydraulic conductivity (K) at large scales. We derive analytical approaches that estimate K and apply them to the contiguous United States. We then compare these analytical approaches to three‐dimensional, national gridded K data products and three transmissivity (T) data products developed from publicly available sources. We evaluate these data products using multiple approaches: comparing their statistics qualitatively and quantitatively and with hydrologic model simulations. Some of these datasets were used as inputs for an integrated hydrologic model of the Upper Colorado River Basin and the comparison of the results with observations was used to further evaluate the K data products. Simulated average daily streamflow was compared to daily flow data from 10 USGS stream gages in the domain, and annually averaged simulated groundwater depths are compared to observations from nearly 2000 monitoring wells. We find streamflow predictions from analytically informed simulations to be similar in relative bias and Spearman's rho to the geologically informed simulations. R ‐squared values for groundwater depth predictions are close between the best performing analytically and geologically informed simulations at 0.68 and 0.70 respectively, with RMSE values under 10 m. We also show that the analytical approach derived by this study produces estimates of K that are similar in spatial distribution, standard deviation, mean value, and modeling performance to geologically‐informed estimates. The results of this work are used to inform a follow‐on study that tests additional data‐driven approaches in multiple basins within the contiguous United States.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Small-Scale Drying: FY2020 Interim Report

This report documents the interim experimental status of small-scale drying tests currently being performed at Pacific Northwest National Laboratory. These small-scale drying tests are to develop the technical bases for sensors, techniques, and approaches that will be used to address the challenges faced when determining moisture content from gas samples taken at the North Anna Nuclear Generating Station for the High Burnup Demonstration Project. Specifically, the purpose of these tests is to support Sandia National Laboratories gas sample methods and analyses through a series of small-scale experiments. Key focus areas include performing tests to: • Correlate sample bottle measurements to in-cask conditions • Estimate the amount of trapped and absorbed water on cask features and surfaces that can contribute to water vapor • Assess the accuracy of the hygrometer used in the measurements under similar conditions • Identify additional methods for measuring humidity in casks easily and accurately using lessons-learned from Sandia National Laboratories, including direct gravimetric and isotopic tracer techniques. To address these topics this report outlines a series of five tests and any data collected to date that were planned for FY 2020 that include 1) humidity measurement method development, 2) gas bottle sampling tests, 3) surface drying tests on cladding, 4) small-scale drying of cladding, and 5) small-scale drying of guide-tube/dashpots. This interim report documents the experimental background, design and progress of these small-scale drying tests. Further data gathered will be summarized in the FY 2021 report.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Galaxy–galaxy lensing with the DES-CMASS catalogue: measurement and constraints on the galaxy-matter cross-correlation

ABSTRACT The DMASS sample is a photometric sample from the DES Year 1 data set designed to replicate the properties of the CMASS sample from BOSS, in support of a joint analysis of DES and BOSS beyond the small overlapping area. In this paper, we present the measurement of galaxy–galaxy lensing using the DMASS sample as gravitational lenses in the DES Y1 imaging data. We test a number of potential systematics that can bias the galaxy–galaxy lensing signal, including those from shear estimation, photometric redshifts, and observing conditions. After careful systematic tests, we obtain a highly significant detection of the galaxy–galaxy lensing signal, with total S/N = 25.7. With the measured signal, we assess the feasibility of using DMASS as gravitational lenses equivalent to CMASS, by estimating the galaxy-matter cross-correlation coefficient rcc. By jointly fitting the galaxy–galaxy lensing measurement with the galaxy clustering measurement from CMASS, we obtain $r_{\rm cc}=1.09^{+0.12}_{-0.11}$ for the scale cut of $4 \, h^{-1}{\rm \,\,Mpc}$ and $r_{\rm cc}=1.06^{+0.13}_{-0.12}$ for $12 \, h^{-1}{\rm \,\,Mpc}$ in fixed cosmology. By adding the angular galaxy clustering of DMASS, we obtain rcc = 1.06 ± 0.10 for the scale cut of $4 \, h^{-1}{\rm \,\,Mpc}$ and rcc = 1.03 ± 0.11 for $12 \, h^{-1}{\rm \,\,Mpc}$. The resulting values of rcc indicate that the lensing signal of DMASS is statistically consistent with the one that would have been measured if CMASS had populated the DES region within the given statistical uncertainty. The measurement of galaxy–galaxy lensing presented in this paper will serve as part of the data vector for the forthcoming cosmology analysis in preparation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Updates and Validation for the n+ 63,65 Cu Cross Sections [Abstract]

The neutron induced total, elastic, and capture cross sections of 63,65 Cu isotopes were selected for evaluation in the resolved and unresolved resonance energy ranges by the National Criticality Safety Program to resolve discrepancies related to benchmark performance. This is especially evident for the series of ZEUS benchmarks in which copper is used as a reflector. Because copper is also used as structural material in both fission and fusion reactors, the need to address benchmark discrepancies linked to nuclear data deficiencies is a task of primary importance. The aim of this work is to describe the steps of evaluation work towards a consistent improvement of the benchmark performance. The R-matrix analysis with the SAMMY code focused on the 63 Cu(n,γ) reaction channel between 100-300 keV coupled to unresolved resonance region parameters up to 650 keV to fit average cross section data from a recent experiment. Due to the high sensitivity of many benchmarks to elastic scattering angular distribution data, especially for the 65 Cu isotope, the impact of these data was tested by generating Legendre coefficients from both resonance parameters and the Hauser-Feshbach model. Guided by the findings of Shaw et al., the performance of the current evaluation for 65 Cu was compared to that of ENDF/B-VII.1 and ENDF/B-VIII.0 by testing the reactivity coefficients corresponding to the validation suite of experimental criticality benchmarks for thermal, intermediate, and fast systems taken from the International Criticality Safety Benchmark Experiments Project Handbook. The benchmark performance is especially sensitive to 63 Cu(n,γ) and 65 Cu elastic scattering for neutron energies in the 100–500 keV region, whereas 100 keV is the upper limit of the resolved resonance region in the ENDF/B-VIII.0 evaluations for 63,65 Cu. The results highlight the need to handle the transition from the resolved resonance region to the high energy region carefully.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2024

Tunable Metamaterials for Impact Mitigation

Traditional methods of shielding fragile goods and human tissues from impact energy rely on isotropic foam materials. The mechanical properties of these foams are inferior to an emerging class of metamaterials called plate lattices, which have predominantly been fabricated in simple 2.5-dimensional geometries using conventional methods that constrain the feasible design space. Here in this work, additive manufacturing is used to relax these constraints and realize plate lattice metamaterials with nontrivial, locally varying geometry. The limitations of traditional computer-aided design tools are circumvented and allow the simulation of complex buckling and collapse behaviors without a manual meshing step. By validating these simulations against experimental data from tests on fabricated samples, sweeping exploration of the plate lattice design space is enabled. Numerical and experimental tests demonstrate plate lattices absorb up to six times more impact energy at equivalent densities relative to foams and shield objects from impacts ten times more energetic while transmitting equivalent peak stresses. In contrast to previous investigations of plate lattice metamaterials, designs with nonuniform geometric prebuckling in the out-of-plane direction is explored and showed that these designs exhibit 10% higher energy absorption efficiency on average and 25% higher in the highest-performing design.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Bringing HPE Slingshot 11 support to Open MPI

The Cray HPE Slingshot 11 network is used on the new exascale systems arriving at the U.S. Department of Energy (DoE) laboratories (e.g., Frontier, Aurora, Perlmutter). As such, the support of this network is an important capability to meet the needs of exascale applications. Here, this article highlights recent work to develop supporting infrastructure to enable Open MPI to efficiently support these new platforms. A key component of this effort involves development of a new Open Fabrics Interface (OFI) provider, LinkX. We discuss the design and development of enhancements that take advantage of the new Slingshot 11 network and AMD GPUs. We include performance data from tests on the Frontier supercomputer using synthetic communication benchmarks, and the vendor provided MPI as a baseline for comparison. The tests demonstrate full functionality of Open MPI on the system and initial results show favorable performance when compared to the highly tuned vendor implementation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Non-linear Wire Rope Isolator Model to Enhance Transportation Simulation of Fragile Equipment

Abstract Introduction Wire rope isolators are often used as means of vibration isolation for the transportation of fragile machine equipment. When deployed as suspension systems in a transportation scenario, a simple spring–damper model is often used to predict the dynamic loads that act on the structure being transported. However, this simple model has proved to be too simplistic to be used in the development of an accurate numerical model that can predict the vibration levels experienced by the inner components of fragile equipment during its transportation. This paper describes the experimental tests conducted on a wire rope isolator used for the transportation of the prototype SSR1 cryomodule. Materials and methods A hysteretic Bouc–Wen model has been used to analytically describe the force–deformation relationship of the wire rope isolators. The developed model of the isolator has been implemented in a larger model to simulate the actual transportation of the prototype SSR1 cryomodule, a section of the new PIP-II linear accelerator under construction at Fermilab. A series of multibody dynamic simulations with rigid and flexible components was used to numerically determine the acceleration of some critical components. Results and conclusions An actual experimental transportation was simulated using two numerical models: the developed Bouc–Wen model and a conventional spring–damper model. It is shown how the Bouc–Wen formulation of the isolator characteristics drastically improves the correspondence between experimental and simulated results if compared to a spring–damper model, especially in the range of 0–30 Hz which is the most critical for transportation problems.

42 ENGINEERING↗
DOE OSTI2023

Characterizing the flux effect on the irradiation embrittlement of reactor pressure vessel steels using machine learning

In-service exposure to high-energy neutrons embrittles reactor pressure vessel (RPV) steels. An increase in the yield stress (Δσ y ) results in a corresponding increase in the brittle to ductile transition temperature (ΔT c ). Most existing models underpredict ΔT c at higher fluence following accelerated irradiations in test reactors. High fluence, up to 10 20 n/cm 2 in some cases, will be reached over extended RPV vessel operation of 80 years, or more, at low service flux. Embrittlement has been extensively studied in accelerated, higher flux test reaction irradiations. However, the use of test reactor data naturally raises the question of flux effects. Here, this study used a machine learning approach trained on a set of hardening data, covering a wide range of flux, fluence, and steel compositions to determine the interactive effects of both irradiation and material variables on Δσ y . The analysis included machine learning-based cross-plots of the variable dependence of Δσ y for six core steels (i.e., CM6, LC, LD, LG, LH, and LI), with controlled differences in their Cu and Ni contents. A primary objective is to evaluate an effective to actual fluence (Φt e /Φt) ratio, as a function of flux, fluence, and steel composition. This is information critical to properly use intermediate flux-high fluence data in calibrating a low flux-high fluence embrittlement model. The predicted Φt e /Φt is reasonably consistent with estimates previously derived from a physics-based solute recombination trap model.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A model for oblique impacts on material surfaces

Many practical situations of material damage, wear, and erosion involve collisions between small particles and surfaces at inclined angles. While there are many well-validated models of normal incidence impact situations, elastic-plastic models for oblique incidence impact events are lacking. Here the finite element method is used to predict the normal and tangential coefficient of restitution in oblique impacts for hard, elastic spheres impacting an elastic-perfectly plastic material surface. The proposed model covers various impact angles ranging from 0° to 45°, within a limiting impact velocity below which the effects of heating are negligible. The normal coefficient of restitution follows power-laws with respect to normalized values of the impact velocity. Interestingly, the tangential coefficient of restitution follows a linear relationship with impact velocity. Together, these results provide a semi-empirical set of equations predicting oblique impact rebounds (both velocity and trajectory) for a wide range of conditions and material properties, with which experimental results can be rapidly interpreted. As a result, Laser-Induced Particle Impact Test (LIPIT) data are also presented for aluminum particles impacting aluminum substrates, at impact angles of 25° and 40°; the results compare favorably with the model and validate the general use of such models for the analysis of experimental data.

Coefficient of restitution↗
DOE OSTI2024

VAN-DAMME: GPU-accelerated and symmetry-assisted quantum optimal control of multi-qubit systems

We present an open-source software package, VAN-DAMME (Versatile Approaches to Numerically Design, Accelerate, and Manipulate Magnetic Excitations), for massively-parallelized quantum optimal control (QOC) calculations of multi-qubit systems. To enable large QOC calculations, the VAN-DAMME software package utilizes symmetry-based techniques with custom GPU-enhanced algorithms. This combined approach allows for the simultaneous computation of hundreds of matrix exponential propagators that efficiently leverage the intra-GPU parallelism found in high-performance GPUs. In addition, to maximize the computational efficiency of the VAN-DAMME code, we carried out several extensive tests on data layout, computational complexity, memory requirements, and performance. These extensive analyses allowed us to develop computationally efficient approaches for evaluating complex-valued matrix exponential propagators based on Padé approximants. To assess the computational performance of our GPU-accelerated VAN-DAMME code, we carried out QOC calculations of systems containing 10 - 15 qubits, which showed that our GPU implementation is 18.4× faster than the corresponding CPU implementation. Our GPU-accelerated enhancements allow efficient calculations of multi-qubit systems, which can be used for the efficient implementation of QOC applications across multiple domains.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Predictive model using artificial neural network to design phase change material-based ocean thermal energy harvesting systems for powering uncrewed underwater vehicles

Uncrewed Underwater Vehicles (UUVs) are a major beneficiary of the phase change material (PCM)-based ocean thermal energy harvesting technology for their mission needs. However, this technology relies on different parameters and energy conversion steps that could be critical to the general energy generation efficiency. Sea trials showed that the design performed lower than their laboratory design specifications. This underperformance results from different factors, mainly the UUV’s trajectory, travel time, underwater ocean currents, temperature fluctuations, and biofouling on the heat exchanger due to long term underwater operations. Therefore, there exists a need to continuously monitor the ambient energy harvesting system and predict system performance, for mission planning purposes. Two major parameters influencing the energy harvesting system include the final pressure inside the hydraulic energy storage vessel or accumulator, and the electrical load value. Here, this work focuses on the hydraulic to electric energy conversion system. Therefore, a combination of numerical model and experimental testing is used to develop a predictive model using artificial neural network using MATLAB. After validation with experimental testing, 1000 data samples obtained from the numerical model are used to train the ANN. Compared to the experimental results, the developed ANN model can predict in less than a second the designed benchtop system’s total efficiency with less than 15 percent maximum error range. This predictive model development represents a cost-effective way for optimization and a computational energy efficient mode aboard UUVs for mission planning for deployed UUVs using PCM-based ocean thermal energy harvesting technology.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2020

Landslide monitoring using seismic refraction tomography – The importance of incorporating topographic variations

Seismic refraction tomography provides images of the elastic properties of subsurface materials in landslide settings. Seismic velocities are sensitive to changes in moisture content, which is a triggering factor in the initiation of many landslides. However, the application of the method to long-term monitoring of landslides is rarely used, given the challenges in undertaking repeat surveys and in handling and minimizing the errors arising from processing time-lapse surveys. This work presents a simple method and workflow for producing a reliable time-series of inverted seismic velocity models. This method is tested using data acquired during a recent, novel, long-term seismic refraction monitoring campaign at an active landslide in the UK. Potential sources of error include those arising from inaccurate and inconsistent determination of first-arrival times, inaccurate receiver positioning, and selection of inappropriate inversion starting models. At our site, a comparative analysis of variations in seismic velocity to real-world variations in topography over time shows that topographic error alone can account for changes in seismic velocity of greater than ±10% in a significant proportion (23%) of the data acquired. The seismic velocity variations arising from real material property changes at the near-surface of the landslide, linked to other sources of environmental data, are demonstrated to be of a similar magnitude. Over the monitoring period we observe subtle variations in the bulk seismic velocity of the sliding layer that are demonstrably related to variations in moisture content. This highlights the need to incorporate accurate topographic information for each time-step in the monitoring time-series. The goal of the proposed workflow is to minimize the sources of potential errors, and to preserve the changes observed by real variations in the subsurface. Following the workflow produces spatially comparable, time-lapse velocity cross-sections formulated from disparate, discretely-acquired datasets. These practical steps aim to aid the use of the seismic refraction tomography method for the long-term monitoring of landslides prone to hydrological destabilization.

Whiteley, J. S.↗
DOE OSTI2023

Optimization of the number and locations of the calibration stations needed to monitor soil moisture using distributed temperature sensing systems: A proof-of-concept study

The single-probe heat-pulse (SPHP) technique combined with the Fiber-optic Distributed Temperature Sensing (DTS) technology can offer novel high-resolution measurements of soil moisture (θ) over spatial scales ranging from several centimeters to several kilometers. However, the key limitation of this method is in obtaining the calibration relationship between θ and soil thermal conductivity (λ) across a specific field. In a previous study, a new methodology using a Gaussian processes model was presented to account for the spatial variability in the λ-θ relationship. The model aggregated θ measurements from soil moisture sensors scattered over the SPHP transect with the corresponding DTS λ measurements at their locations. In this study, a novel methodology is tested to optimize the number and locations of soil moisture sensors required to account for the spatial variability of the λ - θ relationship to achieve higher accuracy from the SPHP technique. The proposed methodology utilizes hierarchical clustering to analyze the information contained in the spatial structure of the SPHP measurements as the soil dries from a nearly-saturated condition. The proposed methodology was tested using data from a field in Oklahoma. Monte-Carlo simulation was performed to validate the performance of the proposed methodology. The predictions obtained from the proposed methodology resulted in θ measurements accuracy comparable to those obtained from the 10% best Monte-Carlo iterations of randomly assigned soil moisture locations. Further, this study demonstrates that the proposed methodology is more efficient than the traditional practice of randomly spreading calibration soil moisture sensors along the SPHP transect.

54 ENVIRONMENTAL SCIENCES↗