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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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NASA NTRS1996

BATSE Observations of the Large-Scale Isotropy of Gamma-Ray Bursts

We use dipole and quadrupole statistics to test the large-scale isotropy of the first 1005 gamma-ray bursts observed by the Burst and Transient Source Experiment (BATSE). In addition to the entire sample of 1005 gamma-ray bursts, many subsets are examined. We use a variety of dipole and quadrupole statistics to search for Galactic and other predicted anisotropies and for anisotropies in a coordinate-system independent manner. We find the gamma-ray burst locations to be consistent with isotropy, e.g., for the total sample the observed Galactic dipole moment (cos theta) differs from the value predicted for isotropy by 0.9 sigma and the observed Galactic quadrupole moment (sin(exp 2) b - 1/3) by 0.3 sigma. We estimate for various models the anisotropies that could have been detected. If one-half of the locations were within 86 deg of the Galactic center, or within 28 deg of the Galactic plane, the ensuing dipole or quadrupole moment would have typically been detected at the 99% confidence level. We compare the observations with the dipole and quadrupole moments of various Galactic models. Several Galactic gamma-ray bursts models have moments within 2 sigma of the observations; most of the Galactic models proposed to date are no longer in acceptable agreement with the data. Although a spherical dark matter halo distribution could be consistent with the data, the required core radius is larger than the core radius of the dark matter halo used to explain the Galaxy's rotation curve. Gamma-ray bursts are much more isotropic than any observed Galactic population, strongly favoring but not requiring an origin at cosmological distances.

Briggs, Michael S.↗
NASA NTRS1989

Singular spectrum analysis in nonlinear dynamics, with applications to paleoclimatic time series

Two dimensions of a dynamical system given by experimental time series are distinguished. Statistical dimension gives a theoretical upper bound for the minimal number of degrees of freedom required to describe the attractor up to the accuracy of the data, taking into account sampling and noise problems. The dynamical dimension is the intrinsic dimension of the attractor and does not depend on the quality of the data. Singular Spectrum Analysis (SSA) provides estimates of the statistical dimension. SSA also describes the main physical phenomena reflected by the data. It gives adaptive spectral filters associated with the dominant oscillations of the system and clarifies the noise characteristics of the data. SSA is applied to four paleoclimatic records. The principal climatic oscillations and the regime changes in their amplitude are detected. About 10 degrees of freedom are statistically significant in the data. Large noise and insufficient sample length do not allow reliable estimates of the dynamical dimension.

Vautard, R.↗
NASA NTRSDate not supplied

The Containment Assurance Risk Framework of the Mars Sample Return Program

The Mars Sample Return campaign aims at bringing rock and atmospheric samples from Mars to Earth through a series of robotic missions. These missions would collect the samples being cached and deposited on Martian soil by the Perseverance rover, place them in a container, and launch them into Martian orbit for subsequent capture by an orbiter that would bring them back. Given there exists a non-zero probability that the samples contain biological material, precautions are being taken to design systems that would break the chain of contact between Mars and Earth. These include techniques such as sterilization of Martian particles, redundant containment vessels, and a robust reentry capsule capable of accurate landings without a parachute. Requirements exist that the probability of containment not assured of Martian-contaminated material into Earth’s biosphere be less than one in a million. To demonstrate compliance with this strict requirement, a statistical framework was developed to assess the likelihood of containment loss during each sample return phase and make a statement about the total combined mission probability of containment not assured. The work presented here describes this framework, which considers failure modes or fault conditions that can initiate failure sequences ultimately leading to containment not assured. Reliability estimates are generated from databases, design heritage, component specifications, or expert opinion in the form of probability density functions or point estimates and provided as inputs to the mathematical models that simulate the different failure sequences. The probabilistic outputs are then combined following the logic of several fault trees to compute the ultimate probability of containment not assured. Given the multidisciplinary nature of the problem and the different types of mathematical models used, the statistical tools needed for analysis are required to be computationally efficient. While standard Monte Carlo approaches are used for fast models, a multi-fidelity approach to rare event probabilities is proposed for expensive models. In this paradigm, inexpensive low-fidelity models are developed for computational acceleration purposes while the expensive high-fidelity model is kept in the loop to retain accuracy in the results. This work presents an example of end-to-end application of this framework highlighting the computational benefits of a multi-fidelity approach.

Giuseppe Cataldo↗
NASA NTRS1983

Statistical summaries of fatigue data for design purposes

Two methods are discussed for constructing a design curve on the safe side of fatigue data. Both the tolerance interval and equivalent prediction interval (EPI) concepts provide such a curve while accounting for both the distribution of the estimators in small samples and the data scatter. The EPI is also useful as a mechanism for providing necessary statistics on S-N data for a full reliability analysis which includes uncertainty in all fatigue design factors. Examples of statistical analyses of the general strain life relationship are presented. The tolerance limit and EPI techniques for defining a design curve are demonstrated. Examples usng WASPALOY B and RQC-100 data demonstrate that a reliability model could be constructed by considering the fatigue strength and fatigue ductility coefficients as two independent random variables. A technique given for establishing the fatigue strength for high cycle lives relies on an extrapolation technique and also accounts for "runners." A reliability model or design value can be specified.

Wirsching, P. H.↗
DOE OSTI2015

Instrument for precision long-term β-decay rate measurements

We describe an experimental setup for making precision measurements of relative β-decay rates of {sup 22}Na, {sup 36}Cl, {sup 54}Mn, {sup 60}Co, {sup 90}Sr, {sup 133}Ba, {sup 137}Cs, {sup 152}Eu, and {sup 154}Eu. The radioactive samples are mounted in two automated sample changers that sequentially position the samples with high spatial precision in front of sets of detectors. The set of detectors for one sample changer consists of four Geiger-Müller (GM) tubes and the other set of detectors consists of two NaI scintillators. The statistical uncertainty in the count rate is few times 0.01% per day for the GM detectors and about 0.01% per hour on the NaI detectors. The sample changers, detectors, and associated electronics are housed in a sealed chamber held at constant absolute pressure, humidity, and temperature to isolate the experiment from environmental variations. The apparatus is designed to accumulate statistics over many years in a regulated environment to test recent claims of small annual variations in the decay rates. We demonstrate that absent this environmental regulation, uncontrolled natural atmospheric pressure variations at our location would imprint an annual signal of 0.1% on the Geiger-Müller count rate. However, neither natural pressure variations nor plausible indoor room temperature variations cause a discernible influence on our NaI scintillator detector count rate.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Enabling probabilistic learning on manifolds through double diffusion maps

Here, we present a generative learning framework for probabilistic sampling that extends Probabilistic Learning on Manifolds (PLoM), which is designed to generate statistically consistent realizations of a random vector in a finite-dimensional Euclidean space, informed by a (representative) set of observations. In its original form, PLoM constructs a reduced-order probabilistic model by combining three main components: (a) kernel density estimation to approximate the underlying probability measure, (b) Diffusion Maps to characterize the manifold of the data, and (c) a reduced-order Itô Stochastic Differential Equation (ISDE) to sample from the learned distribution. However, its sampling dynamics are posed in the ambient space and the retained number of reduced coordinates is chosen by projection-reconstruction error. In practice, this often (i) requires more coordinates than the data’s intrinsic dimension to achieve stable sampling and (ii) lacks a smooth, basis-independent lifting back to the data domain; moreover, standard Diffusion Maps emphasize harmonic eigenfunctions and can miss non-harmonic latent structure. We address these limitations by decoupling geometry learning from sampling: a first Diffusion Maps pass identifies non-harmonic coordinates on which we formulate a full-order ISDE directly in the latent space, while Double Diffusion Maps captures multiscale geometric features and Geometric Harmonics (GH) learns a smooth lifting map to the ambient variables that is independent of the particular diffusion basis. This hybrid design preserves the system’s dynamical richness with a compact geometric representation and enables principled out-of-sample inference. The effectiveness and robustness of the proposed method are illustrated through two numerical studies: one based on data generated from two-dimensional Hermite polynomial functions and another based on high-fidelity simulations of a detonation wave in a reactive flow.

Double diffusion maps↗
DOE OSTI2015

Statistical features of magnetic noise in mixed-type impact fracture

We study the statistical features of magnetic noise accompanying the dynamic fracture of steel samples during mixed type fracture, where the overall ductile character of crack propagation is interrupted by a sudden brittle jump. The structure of the voltage time series is investigated by identifying discrete peaks which correspond to elementary steps of the jerky cracking process. We show that the height, duration, area, and energy of peaks have power law distributions with exponents falling close to the corresponding values of pure ductile fracture. For single peaks, a power law correlation of the height and area with the width is evidenced; however, the mixed nature of fracture gives rise to a crossover between two regimes of different exponents. The average pulse shape of micro-cracking events has a parabolic form with a right handed asymmetry similarly to quasi-static fracture propagation. The asymmetry emerges due to stress localization at the advancing crack front.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Chaotic state to self-organized critical state transition of serrated flow dynamics during brittle-to-ductile transition in metallic glass

We study serrated flow dynamics during brittle-to-ductile transition induced by tuning the sample aspect ratio in a Zr-based metallic glass. The statistical analysis reveals that the serrated flow dynamics transforms from a chaotic state characterized by Gaussian-distribution serrations corresponding to stick-slip motion of randomly generated and uncorrelated single shear band and brittle behavior, into a self-organized critical state featured by intermittent scale-free distribution of shear avalanches corresponding to a collective motion of multiple shear bands and ductile behavior. The correlation found between serrated flow dynamics and plastic deformation might shed light on the plastic deformation dynamic and mechanism in metallic glasses.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

The initial magnetic susceptibility of polydisperse ferrofluids: A comparison between experiment and theory over a wide range of concentration

Temperature dependencies of the static initial magnetic susceptibility for ferrofluids at various concentrations are studied using experiment and statistical-mechanical theories. Magnetic susceptibility measurements are carried out for twelve samples of magnetite-based fluids stabilized with oleic acid over a wide range of temperatures (210 K ≲T ≲ 390 K); all samples have the same granulometric composition but different volume ferroparticle concentrations (0.2 ≲ φ ≲ 0.5). Experimental results are analyzed using three theories: the second-order modified mean-field theory (MMF2) [A. O. Ivanov and O. B. Kuznetsova, Phys. Rev. E 64, 41405 (2001)]; its correction for polydisperse ferrofluids arising from Mayer-type cluster expansion and taking into account the first terms of the polydisperse second virial coefficient [A. O. Ivanov and E. A. Elfimova, J. Magn. Magn. Mater 374, 327 (2015)]; and a new theory based on MMF2 combined with the first terms of the polydisperse second and third virial contributions to susceptibility. It turns out that the applicability of each theory depends on the experimental sample density. If twelve ferrofluid samples are split into three groups of strong, moderate, and low concentrated fluids, the temperature dependences of the initial magnetic susceptibility in each group are very precisely described by one of the three theories mentioned above. The determination of a universal formula predicting a ferrofluid susceptibility over a broad range of concentrations and temperatures remains as a challenge.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Analytic results for scalar-mediated Higgs boson production in association with two jets

Abstract We present compact analytic formulae for all one-loop amplitudes representing the production of a Higgs boson in association with two jets, mediated by a colour triplet scalar particle. Many of the integral coefficients present for scalar mediators are identical to the case when a massive fermion circulates in the loop, reflecting a close relationship between the two theories. The calculation is used to study Higgs boson production in association with two jets in a simplified supersymmetry (SUSY) scenario in which the dominant additional contributions arise from loops of top squarks. The results presented here facilitate an indirect search for top squarks in this channel, by a precision measurement of the corresponding cross section. However, we find that the potential for improved discrimination between the Standard Model and SUSY cases suggested by the pattern of results in the one- and two-jet samples is unlikely to be realized due to the loss in statistical power compared to an inclusive analysis.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Wavelet flow for extragalactic foreground simulations

Extragalactic foregrounds in cosmic microwave background (CMB) observations are both a source of cosmological and astrophysical information and a nuisance to the CMB. Effective field-level modeling that captures their non-Gaussian statistical distributions is increasingly important for optimal information extraction, particularly given the low-noise observations from current and upcoming experiments. Here, we explore the use of Wavelet Flow (WF) models to tackle the novel task of modeling the field-level probability distributions of multi-component CMB secondaries and foregrounds. Specifically, we jointly train correlated CMB lensing convergence (κ) and cosmic infrared background (CIB) maps with a WF model and obtain a network that statistically recovers the input to high accuracy — the trained network generates samples of κ and CIB fields whose average power spectra are within a few percent of the inputs across all scales, and whose Minkowski functionals are similarly accurate compared to the inputs. Leveraging the multiscale architecture of these models, we fine-tune both the model parameters and the priors at each scale independently, optimizing performance across different resolutions. These results demonstrate that WF models can accurately simulate correlated components of CMB secondaries, supporting improved analysis of cosmological data. Our code and trained models can be found on this GitHub repo.

cosmological simulations↗
DOE OSTI2020

Unified bulk semiclassical theory for intrinsic thermal transport and magnetization currents

In this work, we reveal the unexpected role of the material inhomogeneity in unifying the formulation of intrinsic thermal and thermoelectric transport as well as magnetization currents. The smooth inhomogeneity leads to the position dependent local band dispersion and phase-space Berry curvature, enabling a general and rapid access to transport and magnetization currents displaying the momentum-space Berry curvature physics. Our theory does not invoke the boundary current, the thermodynamic approach to magnetization or any mechanical counterpart of statistical forces. By introducing a fictitious inhomogeneity, it applies to homogeneous samples as well, promoting the inhomogeneity to be a basic trick in semiclassical transport theories. Such a trick works regardless of the driving force of transport, e.g., temperature gradient, in contrast to the trick of fictitious gravitational field in quantum transport theories. We thus include more general mechanical driving forces and establish the Mott relation between the resulting transport thermal and electric currents, whereas this relation for these two currents was previously only known when an electric field is the driving force.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Lensing covariance on cut sky and SPT - P l a n c k lensing tensions

We investigate correlations induced by gravitational lensing on simulated cosmic microwave background data of experiments with an incomplete sky coverage and their effect on inferences from the South Pole Telescope (SPT) data. These correlations agree well with the theoretical expectations, given by the sum of supersample and intrasample lensing terms, with only a typically negligible ~5 % discrepancy in the amplitude of the supersample lensing effect. Including these effects we find that lensing constraints are in 3.0 σ or 2.1 σ tension between the SPT polarization measurements and Planck temperature or lensing reconstruction constraints respectively. If the lensing-induced covariance effects are neglected, the significance of these tensions increases to 3.5 σ or 2.5 σ . Using the standard scaling parameter AL substantially underestimates the significance of the tension once other parameters are marginalized over. By parameterizing the supersample lensing through the mean convergence in the SPT footprint, we find a hint of underdensity in the SPT region. We also constrain extra sharpening of the cosmic microwave background acoustic peaks due to missing smoothing of the peaks by supersample lenses at a level that is much smaller than the lens sample variance. Finally, we extend the usual “shift in the means” statistic for evaluating tensions to non-Gaussian posteriors, generalize an approach to extract correlation modes from noisy simulated covariance matrices, and present a treatment of correlation modes not as data covariances but as auxiliary model parameters.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

SU-E-T-79: A Study of the Effect of Clinical Tumor Volume Displacement On the Dosage of Post Modified Radical Mastectomy Intensity-Modulated Radiation Therapy Plans for Left-Sided Breast Cancer

Purpose: To explore the effect of clinical tumor volume (CTV) displacement on the dosage of intensity-modulated radiation therapy (IMRT) plans for left-sided breast cancer after modified radical mastectomy. Methods: We created 2 sets of IMRT plans based on PTV0.5 and PTV0.7 (with CTV displacement of 0.5cm and 0.7cm respectively) for each of the ten consecutive left-sided breast cancer patients after modified radical mastectomy, and compared the difference in PTV coverage and organ at risk (OAR) sparing between the two groups. And then, we compared the difference in PTV coverage in IMRT plans based on PTV0.5 between the group with properly estimated CTV displacement (presuming the actual CTV displacement was 0.5cm) and the one with underestimated CTV displacement (presuming the actual CTV displacement was 0.7cm). The difference in results between the corresponding two groups was compared using paired-sample t-test. P values less than 0.05 were considered statistically significant. Results: IMRT plans derived from PTV0.5 had more homogenous PTV coverage, and less heart, left lung, right breast, right lung, left humeral head and B-P radiation exposure, as well as less total Mu as compared with the ones stemmed from PTV0.7 (all p<0.05). IMRT plans with appropriate estimation of CTV displacement had better PTV coverage compared with the ones with underestimated CTV displacement (all p<0.01). Conclusion: The IMRT plans with smaller CTV displacement in post modified radical mastectomy radiotherapy for left-sided breast cancer has dosimetrical advantages over the ones with larger CTV displacement. Underestimation of CTV displacement can lead to significant reduction of PTV coverage. Individually quantifying and minimizing CTV displacement can significantly improve PTV coverage and OAR (including heart and left lung) sparing. This work was supported by the Medical Scientific Research Foundation of Guangdong Procvince (A2014455 to Changchun Ma)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

2D-DIC Challenge MATLAB Analysis Code v. 1.0

This code replicates the analysis completed in the published article (see reference below) for the 2D-DIC Challenge (https://sem.org/dic-challenge/), conducted under the auspices of the Society for Experimental Mechanics (SEM). The purpose of the DIC Challenge is to provide a set of vetted and standard images, which all users and developers of Digital Image Correlation (DIC) software can use -DIC Challenge results from Sample 14 and Sample 15 of the DIC-Challenge images, and computes various statistics on the data, such as the noise, bias, and spatial resolution. P.L. Reu, E. Toussaint, E. Jones, H.A. Bruck, M. Iadicola, R. Balcaen, D.Z. Turner, T. Siebert, P. Lava, M. Simonsen (2018) Exp. Mech. 58(7):1067-1099, https://doi.org/10.1007/s11340-017-0349-0.

Jones, Elizabeth↗
DOE OSTI2021

Models for synthetic data generation

The software includes a suite of probabilistic statistical/machine learning models that can generate discrete synthetic data. Each model is trained on a set of real (private) data and then it can be used to generate synthetic but statistically similar data. Once ready, the model can generate as many samples as we want. Finally, in addition to the actual models, the software includes code to process data, evaluate results (based on cross validation), and produce reports.

De Oliveira Sales, Ana Paula↗
DOE OSTI2024

Data and scripts associated with “Riverine dissolved organic matter transformations increase with watershed area, water residence time, and Damköhler numbers in nested watersheds” (v2)

This data package is associated with the publication “Riverine dissolved organic matter transformations increase with watershed area, water residence time, and Damköhler numbers in nested watersheds” submitted to Biogeochemistry by Ryan et al., 2024 (DOI: https://doi.org/10.1007/s10533-024-01169-5). This study aims to investigate fundamental and transferable drivers of dissolved organic matter (DOM) diversity across five nested watersheds within the contiguous United States. DOM diversity was explored using ultrahigh-resolution Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). The samples and the unprocessed FTICR-MS data used in this study are publicly available on the Environmental System Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE) data repository (see DOIs below). The data for the Willamette, Gunnison, Connecticut, and Deschutes basins were collected as part of a collaboration between the Watershed Rules of Life (WROL) project and Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS). The data for the Yakima River basin (YRB) was collected by the PNNL River Corridor SFA. The raw, unprocessed FTICR-MS data with additional (meta)data can be found at doi:10.15485/1895159 for WROL samples and doi:10.15485/1898912 for YRB samples. This data package contains the processed data used in the associated manuscript. This package also contains ancillary geospatial, hydrological, and geochemical information that supports the interpretation of the FTICR-MS data within Ryan et al., 2024. This data package is associated with the GitHub repository found at https://github.com/WHONDRS-Hub/rcsfa-RC4-WROL-YRB_DOM_Diversity. This data package was originally published August 2024. It was updated January 2025 (modified files). See the change history in the readme more details. At the directory level, the data package is comprised of three folders: (1) data, (2) output, and (3) src; and five additional files including the data dictionary (file ending in "_dd.csv”) and file-level metadata (file ending in “_flmd.csv”). The “src” folder contains the scripts used to process the FTICR data, conduct the analyses, and produce the manuscript figures. The inputs for these scripts are in the “data” folder and the returned outputs in the “output” folder. Inputs include temporal and spatial metadata associated with the sampling efforts, processed FTICR data, and total and normalized putative biochemical transformations per sample. Outputs include cleaned and combined data presented as tables, descriptive statistics, and plots. The file-level metadata file lists all files contained in this data package and descriptions for each. The data dictionary describes the units and definitions for each tabular data column or row header.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Hierarchical Linear Regression (Rev. 1)

We describe an algorithm for making inferences in a hierarchical linear model. The model allows different slopes and intercepts for different groups, and ties together the different slopes by representing them as samples from a higher level distribution. (The intercepts are treated as statistically independent.) Our model and code permit many options for the variance of this hierarchical distribution for the slopes, including gamma distributions on the precision, t-distributions on the standard error, pooled slopes (all equal), and independent slopes. The algorithm is described in the paper; an implementation of the algorithm in R is available on request.

97 MATHEMATICS AND COMPUTING↗