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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 OSTI2024

Conceptual Design of Neutron Sensor Qualification Device

The Advanced Sensors and Instrumentation Program at Idaho National Laboratory has been formulating strategies to qualify sensors for use in nuclear environments, particularly in irradiation experiments and advanced reactors. When qualifying neutron sensors for use in high-temperature environments, the wide range of neutron flux levels and representative energy spectra presents significant challenges. This paper discusses the development of the Neutron Sensor Qualification Device (NQD), which is designed to test neutron sensors in high temperature controlled environments with known neutron spectra, addressing the spatial and spectral complexities of neutron fluxes in reactor cores. The proposed NQD will be situated in the exposure room at the Armed Forces Radiobiology Research Institute, thus affording a unique capability to expose sensors to high neutron and gamma fluxes. To achieve thermal control, the device will utilize a radiation-hardened tube furnace, accommodating multiple sensors and neutron activation dosimetry wires. Titanium, iron, and cobalt dosimeter wires are chosen from the American Society for Testing and Materials and International Reactor Dosimetry and Fusion File libraries as references for providing energy-dependent fluence measurements. The design ensures precise sensor positioning to minimize mutual shielding and flux perturbation, which are evaluated via Monte Carlo N particle Transport Code (MCNP) simulations. These simulations have informed the development of guidelines on sensor placement within the NQD. The NQD is essential to the qualification of neutron sensors for advanced reactor technologies. It enables controlled testing of a statistically significant number of sensors, thereby supporting assessments of sensor performance across various neutron flux levels and temperatures. This paper highlights the detailed planning for the NQD prototype, along with its inaugural irradiation (scheduled for fiscal year [FY] 2025). The results from this initial testing will be fundamental in evaluating the device’s performance and establishing measurement uncertainty for in-pile neutron sensor measurements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

KiDS-1000 cosmology: Combined second- and third-order shear statistics

Aims.In this work, we perform the first cosmological parameter analysis of the fourth release of Kilo Degree Survey (KiDS-1000) data with second- and third-order shear statistics. This paper builds on a series of studies aimed at describing the roadmap to third-order shear statistics. Methods.We derived and tested a combined model of the second-order shear statistic, namely, the COSEBIs and the third-order aperture mass statistics 〈ℳ ap 3 〉 in a tomographic set-up. We validated our pipeline withN-body mock simulations of the KiDS-1000 data release. To model the second- and third-order statistics, we used the latest version of HMCODE2020 for the power spectrum and BIHALOFITfor the bispectrum. Furthermore, we used an analytic description to model intrinsic alignments and hydro-dynamical simulations to model the effect of baryonic feedback processes. Lastly, we decreased the dimension of the data vector significantly by considering only equal smoothing radii for the 〈ℳ ap 3 〉 part of the data vector. This makes it possible to carry out a data analysis of the KiDS-1000 data release using a combined analysis of COSEBIs and third-order shear statistics. Results.We first validated the accuracy of our modelling by analysing a noise-free mock data vector, assuming the KiDS-1000 error budget, finding a shift in the maximum of the posterior distribution of the matter density parameter, ΔΩ m < 0.02 σ Ω m , and of the structure growth parameter, ΔS 8 < 0.05 σ S 8 . Lastly, we performed the first KiDS-1000 cosmological analysis using a combined analysis of second- and third-order shear statistics, where we constrained Ω m = 0.248 −0.055 +0.062 andS 8 = σ 8 √(Ω m /0.3 )= 0.772 ± 0.022. The geometric average on the errors of Ω m andS 8 of the combined statistics decreases, compared to the second-order statistic, by a factor of 2.2.

Astronomy & Astrophysics↗
DOE OSTI2023

Equibiaxial flexural strength determination of UO 2 using a ball-on-ring test

To increase nuclear fuel performance and reliability, their mechanical properties require an accurate and statistically relevant assessment. Biaxial flexural strength tests provide an alternative to bend bar techniques for assessing mechanical behavior; namely, the transverse rupture strength (TRS) of ceramic samples. Biaxial test samples require simple geometries and minimal surface preparation, reducing fabrication costs and handling hazards. This study investigated the TRS of polycrystalline UO 2 fuel forms at room temperature using a ball-on-ring test fixture. Here, pellets were fabricated from UO 2 powder using conventional powder processing and sintering techniques. The TRS and Weibull parameters were obtained through Weibull statistics on over 60 UO 2 samples tested under equibiaxial flexure. The larger sample size in this study enabled a more robust Weibull statistical analysis than alternative test methods, which may not capture the stochastic failure of typical ceramics. Furthermore, two different loading ball diameters were employed to assess the impact of contact damage on fracture strength. While Hertzian contact damage was observed with the smaller loading ball, the fracture strength remained unaffected. A fracture analysis of the tested UO 2 samples indicated a mixture of intergranular and transgranular fracture that transitions to transgranular fracture with increasing distance from the fracture origin. The characteristic strength of the combined data sets was determined to be 148 MPa, and the Weibull modulus was determined to be 9.1. The TRS values and Weibull parameters were close to values found in the literature for alternative testing techniques using samples with similar microstructure and density. The findings in this study validate the ball-on-ring method used to obtain the TRS of UO 2 with a sample geometry more representative of nuclear fuels. Additionally, experimental TRS results from this study can be implemented in modeling codes to predict fuel performance, which is critical to fuel burnup extension and advanced nuclear fuel technologies.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

(U) A Linear Response Model Predicts Reactivity From a Density Profile

We tested the ability to predict the system reactivity, described by alpha, given a density profile using a simple linear system response. We generated a suite of 1-dimensional density profiles that consisted of nominal density, a discontinuity, and a decay. These profiles were prescribed a functional form and the mass was conserved in all cases. From these density profiles, we calculated the alpha value of the 3-dimensional system.We calculated a linear response function given a training set of the 1-dimensional density profiles, and the system reactivity described by alpha. We tested the robustness of the response function using the remaining test data. Our results showed very good agreement between the predicted and calculated test values, where the distribution of alpha differences was centered about zero and had a standard deviation of 0.005 gens/shake. The predicted and calculated alpha values did not significantly differ (t=-0.0009 p<0.99). We used Singular Value Decomposition (SVD) to reduce the matrix rank by retaining95% of the cumulative singular value contributions. This reduced the matrix rank by 91.7%. We generated the linear response matrix and calculated the difference between the predicted and calculated alpha values. Using the reduced order matrix, we showed good agreement between the predicted and calculated alpha values where the distribution of differences was centered near zero, the standard deviation was 0.006 gens/shake, and the statistical t-test showed good agreement (t=0.02, p<0.98). These results show a linear relationship between a series of 1-dimensional density profiles,where the mass was conserved, and the system reactivity. The next steps of this work will be to investigate the linear response using 2-dimensional density profiles.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

The development and application of the stirred‐reactor coupon analysis (SRCA) test method

A new technique, termed the stirred‐reactor coupon analysis (SRCA) method, has been developed to measure the rate of glass dissolution in forward‐rate conditions. Monolithic glass coupons are partially masked with an inert material before placement in a large volume of well‐mixed solution with known chemistry and temperature for a predetermined duration. After the test, the mask is removed, and the difference in step height between the protected area and the exposed corroded portions of the sample coupon is measured to determine the extent of glass dissolution. The step height is converted to a rate measurement using the test duration and glass density. Test parameters such as sample surface preparation and test duration were evaluated to determine their effects on the measured rates. Additionally, results from an interlaboratory study (ILS) consisting of 12 laboratories from 11 different institutions are presented, where each laboratory performed 12 independent tests. When removing experimental outlier data, the 95% reproducibility limits for the SRCA method has no statistical difference with previously published standardized test methods used to determine the forward rate of glass dissolution. Overall, this paper describes steps necessary to perform the test method and provides the statistical calculations to evaluate test accuracy.

chemical durability↗
DOE OSTI2020

A2Cloud‐RF : A random forest based statistical framework to guide resource selection for high‐performance scientific computing on the cloud

Summary This article proposes a random‐forest based A2Cloud framework to match scientific applications with Cloud providers and their instances for high performance. The framework leverages four engines for this task: PERF engine, Cloud trace engine, A2Cloud‐ext engine, and the random forest classifier (RFC) engine. The PERF engine profiles the application to obtain performance characteristics, including the number of single‐precision (SP) floating‐point operations (FLOPs), double‐precision (DP) FLOPs, x87 operations, memory accesses, and disk accesses. The Cloud trace engine obtains the corresponding performance characteristics of the selected Cloud instances including: SP floating point operations per second (FLOPS), DP FLOPS, x87 operations per second, memory bandwidth, and disk bandwidth. The A2Cloud‐ext engine uses the application and Cloud instance characteristics to generate objective scores that represent the application‐to‐Cloud match. The RFC engine uses these objective scores to generate two types of random forests to assist users with rapid analysis: application‐specific random forests (ARF) and application‐class based random forests. The ARF consider only the input application's characteristics to generate a random forest and provide numerical ratings to the selected Cloud instances. To generate the application‐class based random forests, the RFC engine downloads the application profiles and scores of previously tested applications that perform similar to the input application. Using these data, the RFC engine creates a random forest for instance recommendation. We exhaustively test this framework using eight real‐world applications across 12 instances from different Cloud providers. Our tests show significant statistical agreement between the instance ratings given by the framework and the ratings obtained via actual Cloud executions.

Samuel, David↗
DOE OSTI2021

Higher Compact Multiple Occurrence around Metal-poor M-dwarfs and Late-K-dwarfs

The planet–metallicity correlation serves as a potential link between exoplanet systems as we observe them today and the effects of bulk composition on the planet formation process. Many observers have noted a tendency for Jovian planets to form around stars with higher metallicities; however, there is no consensus on a trend for smaller planets. Here, we investigate the planet–metallicity correlation for rocky planets in single- and multi-planet systems around Kepler M-dwarf and late-K-dwarf stars. Due to molecular blanketing and the dim nature of these low-mass stars, it is difficult to make direct elemental abundance measurements via spectroscopy. We instead use a combination of accurate and uniformly measured parallaxes and photometry to obtain relative metallicities and validate this method with a subsample of spectroscopically determined metallicities. We use the Kolmogorov–Smirnov (K-S) test, Mann–Whitney U-test, and Anderson–Darling (AD) test to compare the compact multiple planetary systems with single-transiting planet systems and systems with no detected transiting planets. We find that the compact multiple planetary systems are derived from a statistically more metal-poor population, with a p-value of 0.015 in the K-S test, a p-value of 0.005 in the Mann–Whitney U-test, and a value of 2.574 in the AD test statistic, which exceeds the derived threshold for significance by a factor of 25. We conclude that metallicity plays a significant role in determining the architecture of rocky planet systems. Compact multiples either form more readily, or are more likely to survive on gigayear timescales, around metal-poor stars.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Strange hadron production in Au + Au collisions at s N N = 7.7 , 11.5, 19.6, 27, and 39 GeV

In this paper, we present STAR measurements of strange hadron (K$0\atop{s}$, Λ, $\bar{Λ}$, $Ξ$ - , $\bar{Ξ}$ + , Ω - , $\bar{Ω}$ + , and Φ ) production at mid-rapidity (|y|<0.5) in Au+Au collisions at √s NN = 7.7 – 39 GeV from the Beam Energy Scan Program at the Relativistic Heavy Ion Collider (RHIC). Transverse momentum spectra, averaged transverse mass, and the overall integrated yields of these strange hadrons are presented versus the centrality and collision energy. Antibaryon-to-baryon ratios(Λ/$\bar{Λ}$, $Ξ$ - / $\bar{Ξ}$ + , Ω - / $\bar{Ω}$ + ) are presented as well, and used to test a thermal statistical model and to extract the temperature normalized strangeness and baryon chemical potentials at hadronic freeze-out (μ B / T ch μ S / T ch ) in central collisions. Strange baryon-to-pion ratios are compared to various model predictions in central collisions for all energies. The nuclear modification factors (R CP ) and antibaryon-to-meson ratios as a function of transverse momentum are presented for all collision energies. The K$0\atop{s}$ R CP shows no suppression for p T up to 3.5 GeV/c at energies of 7.7 and 11.5 GeV. The $\bar{Λ}$/ K$0\atop{s}$ ratio also shows baryon-to-meson enhancement at intermediate p T (~2.5 GeV/c) in central collisions at energies above 19.6 GeV. In conclusion, both observations suggest that there is likely a change of the underlying strange quark dynamics at collision energies below 19.6 GeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Indirect Tool Condition Monitoring Using Ensemble Machine Learning Techniques

Abstract Tool condition monitoring (TCM) has become a research area of interest due to its potential to significantly reduce manufacturing costs while increasing process visibility and efficiency. Machine learning (ML) is one analysis technique which has demonstrated advantages for TCM applications. However, the commonly studied individual ML models lack generalizability to new machining and environmental conditions, as well as robustness to the unbalanced datasets which are common in TCM. Ensemble ML models have demonstrated superior performance in other fields, but have only begun to be evaluated for TCM. As a result, it is not well understood how their TCM performance compares to that of individual models, or how homogeneous and heterogeneous ensemble models’ performances compare to one another. To fill in these research gaps, milling experiments were conducted using various cutting conditions, and the model groups were compared across several performance metrics. Statistical t-tests were also used to evaluate the significance of model performance differences. Through the analysis of four individual ML models and five ensemble models, all based on the processes’ sound, spindle power, and axial load signals, it was found that on average, the ensemble models performed better than the individual models, and that the homogeneous ensembles outperformed the heterogeneous ensembles.

Engineering↗
DOE OSTI2022

Bimolecular Chemistry in the Ultracold Regime

Advances in atomic, molecular, and optical physics techniques allowed the cooling of simple molecules down to the ultracold regime ([Formula: see text]1 mK) and opened opportunities to study chemical reactions with unprecedented levels of control. This review covers recent developments in studying bimolecular chemistry at ultralow temperatures. We begin with a brief overview of methods for producing, manipulating, and detecting ultracold molecules. We then survey experimental works that exploit the controllability of ultracold molecules to probe and modify their long-range interactions. Further combining the use of physical chemistry techniques such as mass spectrometry and ion imaging significantly improved the detection of ultracold reactions and enabled explorations of their dynamics in the short range. We discuss a series of studies on the reaction KRb + KRb → K 2 + Rb 2 initiated below 1 μK, including the direct observation of a long-lived complex, the demonstration of product rotational state control via conserved nuclear spins, and a test of the statistical model using the complete quantum state distribution of the products.

Chemistry↗
DOE OSTI2025

DeepBench: A simulation package for physical benchmarking data

We introduce **DeepBench**, a python library that generates simple simulated image data from first principles, such as basic geometric shapes and astronomical objects. These data are highly valuable for developing (calibration, testing, and benchmarking) statistical and machine learning models because they make it possible to connect the final data product to physically interpretable inputs. This software includes tools to curate and store the datasets to maximize reproducibility.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Unitary Bethe-Salpeter Methods in Two- and Three-Body Systems

The study of resonances, unstable particles formed in particle scattering, is motivated by the questions about the strong interaction and the composition of hadrons. In order to advance this study in the intermediate energy region, a variety of techniques are used. In this thesis, we present work done on two different analyses that use the principle of unitarity and the Bethe-Salpeter equation to study the resonances Lambda(1405), Sigma(1385), and a1(1260). Firstly, we perform a simultaneous analysis of Sand P-waves of the Strangeness = -1 two-body meson-baryon scattering amplitude using all low-energy data. For the first time, differential cross section data are included for chiral unitary coupled-channel models. From this model, S- and P-wave amplitudes are extracted and we observe both well-known I(JP)=0(1/2^-) S-wave states as well as a new I(JP)=1(1/2^+) state absent in quark models and lattice QCD results. Multiple statistical and phenomenological tests suggest that, while the data clearly require an I =1 P-wave resonance, the new state just accounts for the absence of the decuplet Sigma(1385)3/2+ in the model which is subsequently included in the parameterization. Secondly, we formulate the final state interaction of the a1(1260) resonance decay in a manifestly three-body-unitary parameterization and fit it to the a1(1260) lineshape measured by the ALEPH experiment. Dalitz plots calculated from this fit are presented. The work demonstrates the feasibility to numerically solve a previously derived amplitude and its generalization to isobars with spin and coupled channels. The model is a good test case because it can also be applied to other meson decays including exotic states and modified for the finite-volume problem as it arises in lattice QCD due to its manifest unitarity. The understanding of the resonances being analyzed in both the two-body work and the three-body work gives a better understanding of intermediate energy QCD.

Sadasivan, Daniel↗
DOE OSTI2021

Assessment of BQ-9000 Biodiesel Properties for 2020 (CRADA CRD-15-593)

Biodiesel producers in the United States and Canada can voluntarily participate in the industry's BQ-9000 quality assurance program. This is the fourth in a series of reports documenting biodiesel quality from participating producers. Participants in the BQ-9000 program were requested to voluntarily provide data to a third-party team. This team anonymized and randomized the data prior to providing to the National Renewable Energy Laboratory (NREL) for analysis and reporting. The critical quality parameters analyzed are: sodium and potassium, calcium and magnesium, phosphorus, flash point and alcohol control, water and sediment, cloud point, acid number, free and total glycerin, monoglycerides, sulfur, oxidation stability, and cold soak filterability test (CSFT). The statistical analysis for these parameters is presented in Table ES-1.

09 BIOMASS FUELS↗
DOE OSTI2023

Report on Hydrogen Content Measurements of Yttrium Hydrides

This report describes the hydrogen content measurements of yttrium samples as irradiated at Advanced Test Reactor as part of the Microreactor Program. Irradiated samples were prepared at the facilities of Analytical Research Laboratory (ARL) of Materials and Fuels Complex (MFC). Hydrogen content measurements were performed on reduced size specimens using an inert gas fusion analyzer. For a single sample, replicate samples were prepared and tested to improve statistics of results. Uncertainty analyses were conducted using two approaches to determine the hydrogen content variations in the samples. Hydrogen content of irradiated specimens were both lower and higher than the expected values, indicating stoichiometry variations. Hydrogen was detected in all samples, even for the cracked capsule’s specimens. Results also suggested a potential hydrogen redistribution is present between samples inside the capsules.

08 HYDROGEN↗
DOE OSTI2023

Automated, high-accuracy classification of textured microstructures using a convolutional neural network

Crystallographic texture is an important descriptor of material properties but requires time-intensive electron backscatter diffraction (EBSD) for identifying grain orientations. While some metrics such as grain size or grain aspect ratio can distinguish textured microstructures from untextured microstructures after significant grain growth, such morphological differences are not always visually observable. This paper explores the use of deep learning to classify experimentally measured textured microstructures without knowledge of crystallographic orientation. A deep convolutional neural network is used to extract high-order morphological features from binary images to distinguish textured microstructures from untextured microstructures. The convolutional neural network results are compared with a statistical Kolmogorov–Smirnov tests with traditional morphological metrics for describing microstructures. Results show that the convolutional neural network achieves a significantly improved classification accuracy, particularly at early stages of grain growth, highlighting the capability of deep learning to identify the subtle morphological patterns resulting from texture. The results demonstrate the potential of a convolutional neural network as a tool for reliable and automated microstructure classification with minimal preprocessing.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Multi-Semester Mentoring and GPA Trajectories in SPINS: A Longitudinal Program Evaluation of STEM Scholars

This exploratory longitudinal program evaluation examined GPA trajectories among 14 STEM scholars participating in the Scholarly Partnership in Nuclear Security (SPINS) mentoring program at an HBCU. Using de-identified administrative data (37 scholar-semester observations), the study compared baseline and latest term GPAs anchored to each scholar’s first funded semester. A Wilcoxon signed-rank test was used to assess within-student change. Mean GPA increased modestly from 3.46 (SD = 0.30) at baseline to 3.61 (SD = 0.33) at the latest observed semester, with 12 of 14 scholars (85.7%) showing net improvement (median change = +0.12). The Wilcoxon signed-rank test indicated a statistically significant positive shift (W = 18, p = 0.030). However, scholars entered the program with a high baseline GPA, and ceiling effects were evident for several participants. Grounded in Social Cognitive Career Theory, findings suggest that multi-semester participation in SPINS is associated with GPA stability and modest improvement in an already high-performing cohort. Results should be interpreted cautiously given the small sample size and single-group design. The study highlights the value of sustained, culturally responsive mentoring at an HBCU while underscoring the need for larger evaluations with comparison cohorts and broader psychosocial outcomes. An evidence-informed mentoring framework is proposed to strengthen multi-semester support.

42 ENGINEERING↗
DOE OSTI2026

Hidden-sectors search and probe of discrete symmetries at the REDTOP experiment

The $η$ and $η^{\prime}$ mesons are nearly unique in the particle universe since they are nearly Goldstone bosons, and their decay dynamics are strongly constrained. While earlier experiments collected samples of order $\sim 10^{9}η$, the proposed REDTOP (Rare Eta Decays To Observe Physics Beyond the Standard Model) facility targets $\mathcal{O}(10^{14})η$ and $\mathcal{O}(10^{12})η^\prime$, enabling broad searches for physics beyond the Standard Model. In this work, we present studies evaluating REDTOP sensitivity to processes that couple the Standard Model to New Physics through four portals: the Vector (dark photon), the Scalar (Higgs-mixing), the Axion-like, and the Heavy Lepton. In parallel, the proposed statistics allow precise tests of $CP$ and $T$ invariance and lepton universality and improve determinations of the $η/η'$ transition form factors, which are crucial inputs to the hadronic light-by-light contribution to the muon anomalous magnetic moment $(g-2)_μ$.

Gatto, C. [INFN, Naples; Northern Illinois U.]↗