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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Modeling the effects of exercise during 100% oxygen prebreathe on the risk of hypobaric decompression sickness

BACKGROUND: Several previous studies indicated that exercise during prebreathe with 100% O2 decreased the incidence of hypobaric decompression sickness (DCS). We report a meta-analysis of these investigations combined with a new study in our laboratory to develop a statistical model as a predictive tool for DCS. HYPOTHESIS: Exercise during prebreathe increases N2 elimination in a theoretical 360-min half-time compartment decreasing the incidence of DCS. METHODS: A dose-response probability tissue ratio (TR) model with 95% confidence limits was created for two groups, prebreathe with exercise (n = 113) and resting prebreathe (n = 113), using nonlinear regression analysis with maximum likelihood optimization. RESULTS: The model predicted that prebreathe exercise would reduce the residual N2 in a 360-min half-time compartment to a level analogous to that in a 180-min compartment. This finding supported the hypothesis. The incidence of DCS for the exercise prebreathe group was significantly decreased (Chi-Square = 17.1, p < 0.0001) from the resting prebreathe group. CONCLUSIONS: The results suggested that exercise during prebreathe increases tissue perfusion and N2 elimination approximately 2-fold and markedly lowers the risk of DCS. Based on the model, the prebreathe duration may be reduced from 240 min to a predicted 91 min for the protocol in our study, but this remains to be verified. The model provides a useful planning tool to develop and test appropriate prebreathe exercise protocols and to predict DCS risks for astronauts.

NASA Program Environmental Health↗
DOE OSTI2024

Highly accelerated life testing (HALT): A review from a statistical perspective

Despite its use in one form or another for at least four decades, HALT and related techniques [e.g., highly accelerated-stress screening (HASS) and stress audits (HASA)] are not well understood within the statistical community and remain controversial. This largely reflects a conflict in motivation between engineers, testing under harsh conditions to discover and eliminate failure modes, and statisticians, taking a more cautious approach to develop quantitative estimates of parameters such as mean time between failures (MTBF). Here, this review article will clarify HALT concepts and methods and explain where it fits within the universe of methods that involve the application of accelerating factors to compress the time required to evaluate or enhance product reliability. A major distinction is between methods such as HALT, a high-stress test-analyze-fix-test iterative process directed at improving reliability by discovering and fixing weak points in a design, and quantitative accelerated life testing (QALT), whose goal is the estimation of product life for a fixed design. We discuss methods such as physics of failure that offer some hope of bridging the gap between the qualitative nature of HALT, and purely quantitative statistical methods. We present a variety of engineering applications of HALT including metal fatigue, piping and pressure vessels, structural damage, radiation damage, and rotating machinery. We also discuss potential synergies between HALT and QALT, such as rapid identification, through HALT, of failure modes requiring quantitative analysis. For further study, extensive references to the applicable literature are provided as well as an appendix that describes related methods.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2010

Failure Bounding And Sensitivity Analysis Applied To Monte Carlo Entry, Descent, And Landing Simulations

In the study of entry, descent, and landing, Monte Carlo sampling methods are often employed to study the uncertainty in the designed trajectory. The large number of uncertain inputs and outputs, coupled with complicated non-linear models, can make interpretation of the results difficult. Three methods that provide statistical insights are applied to an entry, descent, and landing simulation. The advantages and disadvantages of each method are discussed in terms of the insights gained versus the computational cost. The first method investigated was failure domain bounding which aims to reduce the computational cost of assessing the failure probability. Next a variance-based sensitivity analysis was studied for the ability to identify which input variable uncertainty has the greatest impact on the uncertainty of an output. Finally, probabilistic sensitivity analysis is used to calculate certain sensitivities at a reduced computational cost. These methods produce valuable information that identifies critical mission parameters and needs for new technology, but generally at a significant computational cost.

Gaebler, John A.↗
DOE OSTI2024

U.S. Average Market Carbon Dioxide Production Baseline Documentation For 45Q Life Cycle Analysis: Version 1.0 (2018-2022)

U.S. Average Benchmark life cycle inventory documentation for market carbon dioxide production for calendar years 2018 - 2022. The documentation includes a technical report describing data sources and statistical methods used and an Excel file showing calculations. The calculations performed are used in the 45Q benchmark json-ld dataset, compatible with the NETL CO2U LCA Guidance Toolkit. Summary impact results will be included in the NETL CO2U LCA Documentation Spreadsheet within the Toolkit. To access the model referenced in the report, please visit https://www.netl.doe.gov/energy-analysis/details?id=21915ba8-d2cf-43ea-b9b2-1d76363a46a7

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Geospatial analysis of preterm and small-for-gestational age births in Washington D.C.

Background: This study is based on the recognition that adverse pregnancy outcomes significantly affect maternal and infant health, leading to increased morbidity and mortality. These outcomes are shaped by a complex interplay of individual-level factors—like maternal age and education—and community-level influences, including socio-economic status and access to healthcare. Understanding these determinants is crucial for developing effective public health strategies, especially for marginalized populations, by identifying high-risk areas and informing targeted interventions that address both individual and structural barriers. Methods: We utilized geospatial analysis to explore the association between individual- and community-level factors and adverse pregnancy outcomes, specifically preterm birth (PTB) and small-for-gestational-age (SGA) birthweight in Washington, D.C. We used Empirical Bayes smoothing methods to calculate rates of adverse birth outcomes from 2010 to 2018 at the U.S. Census tract–level. Spatial scan statistics were used to investigate if adverse birth outcomes clustered in specific areas. ANOVA tests were conducted for individual- and community-level factors within identified clusters. Results: Spatial analysis identified significant high-risk clusters for PTB and SGA infants primarily in southeastern Washington, D.C., particularly in Wards 7 and 8. Individuals residing within these clusters experienced a 47% increased risk of PTB (RR = 1.467) and a 56% increased risk of SGA (RR = 1.560) compared to those outside clusters. Space–time analysis revealed temporal variation, with PTB clusters persisting from 2011 to 2014 and SGA clusters extending through 2017. Compared to low-risk clusters, high-risk clusters had younger birthing individuals (mean age ~26.5 vs. ~33 years), lower maternal college degree attainment (~20% vs. ~80%), higher rates of late or no prenatal care (~16% vs. 11%), and increased prevalence of smoking and hypertension (all P < 0.001). Community-level indicators showed lower median household incomes ($\$40,000$ vs. ~$\$105,000$), greater poverty (~16% vs. ~7% below $\$10,000$/year), higher public assistance use (~32% vs. ~5%), and reduced healthcare access (greater distances to emergency and specialty care) in high-risk areas (all P < 0.001). Neighborhood deprivation indices were significantly elevated, commutes were longer, and population density was lower in these clusters. These findings highlight that adverse birth outcomes cluster in neighborhoods with pronounced socioeconomic and health disparities. Conclusion: High-risk birth clusters highlight intertwined factors: individual, socio-economic, and geographic. Addressing these requires comprehensive interventions focusing on social and structural determinants of health.

Birth outcomes↗
DOE OSTI2024

A Computational Review of Privacy-Preserving Mechanisms for the Smart Grid

Smart grid technologies have rapidly become one of the largest and most comprehensive sources of data for the modern utility. For the most part, data streams are seen as an essential tool that enable utilities to carry their day-to-day business operations, but they also create the need for efficient and secure data management strategies. In the context of the smart grid, ensuring data privacy is becoming an increasing concern due to a combination of factors that range from shifts in operational paradigms and rapid technology evolution to changes in legislation. Furthermore, researchers have highlighted the risks associated with improperly protected energy records. For example, energy consumption data from homes could be used to infer the behaviors and habits of home occupants through activity recognition or user profiling (Fan, 2017), which may lead to unfair service pricing, targeted advertising, or other personal security violations. Similarly, Electric Vehicles’ (EVs) charging metadata could be used to reveal private information about the owner such as their payment methods, preferred charging stations, and other locational and timing information that could be used to reconstruct the vehicle owner’s behaviors. The privacy of user data, even when used for statistical analysis or machine learning training processes, also needs to be carefully considered, as an individual’s private traits may still be vulnerable if their inclusion/exclusion greatly impacts the result or could be linked to a public dataset through cross-reference. The breach of user privacy also has severe impacts for organizations that store, transmit, or work on the data in the form of diminishing the public’s trust in them while potentially incurring legal consequences (e.g., fines and suspensions under the European Union General Data Protection Regulation, Health Insurance Portability and Accountability Act, etc.). Because of these risks, several privacy-preserving mechanisms are available to help organizations comply with privacy legislations and prevent the unauthorized and malicious use of user data. In light of these concerns, this report focuses on performing a computational review of privacy-preserving mechanisms that have received a significant amount of interest in literature. It specifically focuses on 1) homomorphic encryption, 2) zero-knowledge proofs, 3) differential privacy, and 4) federated learning. It is worth noting that although many of the methods presented in this document rely on cryptographic primitives, their intent is not to provide perfect secrecy, but rather to enable users to maintain privacy, and thus they shall not be compared or equated to other constructs that are aimed to address cybersecurity constructs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1992

Helicopter response to atmospheric turbulence

A new time-domain method for simulating cyclostationary turbulence as seen by a translating and rotating blade element has recently been developed for the case of one-dimensional spectral distribution. This paper extends the simulation method to the cases of two- and three-dimensional spectral distributions and presents validation results for the two-dimensional case. The statistics of an isolated rigid blade flapping response to turbulence are computed using a two-dimensional spectral representation of the von Karman turbulence model, and the results are compared with those obtained using the conventional space-fixed turbulence analysis. The new turbulence simulation method is used for predicting the Black Hawk helicopter response to atmospheric turbulence.

Riaz, J.↗
NASA NTRS1992

Abundance recovery error analysis using simulated AVIRIS data

Measurement noise and imperfect atmospheric correction translate directly into errors in the determination of the surficial abundance of materials from imaging spectrometer data. The effects of errors on abundance recovery were investigated previously using Monte Carlo simulation methods by Sabol et. al. The drawback of the Monte Carlo approach is that thousands of trials are needed to develop good statistics on the probable error in abundance recovery. This computational burden invariably limits the number of scenarios of interest that can practically be investigated. A more efficient approach is based on covariance analysis. The covariance analysis approach expresses errors in abundance as a function of noise in the spectral measurements and provides a closed form result eliminating the need for multiple trials. Monte Carlo simulation and covariance analysis are used to predict confidence limits for abundance recovery for a scenario which is modeled as being derived from Airborne Visible/Infrared Imaging Spectrometer (AVIRIS).

Stoner, William W.↗
DOE OSTI2026

Opportunities in AI/ML for the Rubin LSST Dark Energy Science Collaboration

The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) will produce unprecedented volumes of heterogeneous astronomical data (images, catalogs, and alerts) that challenge traditional analysis pipelines. The LSST Dark Energy Science Collaboration (DESC) aims to derive robust constraints on dark energy and dark matter from these data, requiring methods that are statistically powerful, scalable, and operationally reliable. Artificial intelligence and machine learning (AI/ML) are already embedded across DESC science workflows, from photometric redshifts and transient classification to weak lensing inference and cosmological simulations. Yet their utility for precision cosmology hinges on trustworthy uncertainty quantification, robustness to covariate shift and model misspecification, and reproducible integration within scientific pipelines. This white paper surveys the current landscape of AI/ML across DESC's primary cosmological probes and cross-cutting analyses, revealing that the same core methodologies and fundamental challenges recur across disparate science cases. Since progress on these cross-cutting challenges would benefit multiple probes simultaneously, we identify key methodological research priorities, including Bayesian inference at scale, physics-informed methods, validation frameworks, and active learning for discovery. With an eye on emerging techniques, we also explore the potential of the latest foundation model methodologies and LLM-driven agentic AI systems to reshape DESC workflows, provided their deployment is coupled with rigorous evaluation and governance. Finally, we discuss critical software, computing, data infrastructure, and human capital requirements for the successful deployment of these new methodologies, and consider associated risks and opportunities for broader coordination with external actors.

Aubourg, Eric [APC, Paris] (ORCID:000000025592023X↗
NASA NTRS1974

Basic elements of power spectral analysis

The basic elements of power spectral analysis with emphasis on the Blackman-Tukey method are presented. Short discussions are included on the topics of pre-whitening, frequency and spectral windows, and statistical reliability. Examples are included whenever possible, and a FORTRAN subroutine for calculating a power spectrum is presented.

Sentman, D. D.↗
NASA NTRS1975

Propagation of transients in a random medium

The propagation of transient scalar waves in a three-dimensional random medium is considered. The analysis is based on the smoothing method. An integro-differential equation for the coherent (or average) wave is derived and solved for the case of a statistically homogeneous and isotropic medium and a delta-function source. This yields the coherent Green's function of the medium. It is found that the waveform of the coherent wave depends generally on the distance from the source measured in terms of a certain dimensionless parameter. Based on the magnitude of this parameter, three propagation zones, called the near zone, the far zone, and the intermediate zone, are defined.

Wenzel, A. R.↗
NASA NTRS1987

Statistical analysis of 59 inspected SSME HPFTP turbine blades (uncracked and cracked)

The numerical results of statistical analysis of the test data of Space Shuttle Main Engine high pressure fuel turbopump second-stage turbine blades, including some with cracks are presented. Several statistical methods use the test data to determine the application of differences in frequency variations between the uncracked and cracked blades.

Wheeler, John T.↗
NASA NTRS1991

Clutter modeling of the Denver Airport and surrounding areas

To accurately simulate and evaluate an airborne Doppler radar as a wind shear detection and avoidance sensor, the ground clutter surrounding a typical airport must be quantified. To do this, an imaging airborne Synthetic Aperture Radar (SAR) was employed to investigate and map the normalized radar cross sections (NRCS) of the ground terrain surrounding the Denver Stapleton Airport during November of 1988. Images of the Stapleton ground clutter scene were obtained at a variety of aspect and elevation angles (extending to near-grazing) at both HH and VV polarizations. Presented here, in viewgraph form with commentary, are the method of data collection, the specific observations obtained of the Denver area, a summary of the quantitative analysis performed on the SAR images to date, and the statistical modeling of several of the more interesting stationary targets in the SAR database. Additionally, the accompanying moving target database, containing NRCS and velocity information, is described.

Harrah, Steven D.↗
NASA NTRS1918

An Investigation of the Elements which Contribute to Statical and Dynamical Stability, and of the Effects of Variation in Those Elements

Part 1 gives details of models tested and methods of testing of the Eiffel 36 wing alone and the JN2 aircraft. Characteristics and performance curves for standard JN are included. Part 2 presents a statistical analysis of the following: lift and drag contributed by body and chassis tested without wings; lift and drag contributed by tail, tested without wings; the effect on lift and drift of interference between the wings of a biplane combination; lift and drag contributed by the addition of body, chassis, and tail to a biplane combination; total parasite resistance; effect of varying size of tail, keeping angle of setting constant; effect of varying length of body and size of tail at the same time, keeping constant moment of tail surface about the center of gravity; forces on the tail and the effects of downwash; effect of size and setting of tail on statical longitudinal stability effects of length of body on stability; the effects of the various elements of an airplane on longitudinal stability and the placing of the force vectors. Part 3 presents the fundamental principals of dynamical stability; computations of resistance derivatives; solution of the stability equation; dynamical stability of the Curtiss JN2; tabulation of resistance derivatives; discussion of the resistance derivatives; formation and solution of stability equations; physical conceptions of the resistance derivatives; elements contributing to damping and an investigation of low speed conditions. Part 4 includes a summary of the results of the statistical investigation and a summary of the results for dynamic stability.

Klemin, Alexander↗
NASA NTRS1997

Sulfur in Cometary Dust

The computer-intensive project consisted of the analysis and synthesis of existing data on composition of comet Halley dust particles. The main objective was to obtain a complete inventory of sulfur containing compounds in the comet Halley dust by building upon the existing classification of organic and inorganic compounds and applying a variety of statistical techniques for cluster and cross-correlational analyses. A student hired for this project wrote and tested the software to perform cluster analysis. The following tasks were carried out: (1) selecting the data from existing database for the proposed project; (2) finding access to a standard library of statistical routines for cluster analysis; (3) reformatting the data as necessary for input into the library routines; (4) performing cluster analysis and constructing hierarchical cluster trees using three methods to define the proximity of clusters; (5) presenting the output results in different formats to facilitate the interpretation of the obtained cluster trees; (6) selecting groups of data points common for all three trees as stable clusters. We have also considered the chemistry of sulfur in inorganic compounds.

Fomenkova, M. N.↗
NASA NTRS2004

Aquarius Instrument Science Calibration During the Risk Reduction Phase

This final report presents the results of work performed under NASA Grant NAG512726 during the period 15 January 2003 through 30 June 2004. An analysis was performed of a possible vicarious calibration method for use by Aquarius to monitor and stabilize the absolute and relative calibration of its microwave radiometer. Stationary statistical properties of the brightness temperature (T(sub B)) measured by a low Earth orbiting radiometer operating at 1.4135 GHz are considered as a means of validating its absolute calibration. The global minimum, maximum, and average T(sub B) are considered, together with a vicarious cold reference method that detects the presence of a sharp lower bound on naturally occurring values for T(sub B). Of particular interest is the reliability with which these statistics can be extracted from a realistic distribution of T(sub B) measurements that would be observed by a typical sensor. Simulations of measurements are performed that include the effects of instrument noise and variable environmental factors such as the global water vapor and ocean surface temperature, salinity and wind distributions. Global minima can vary widely due to instrument noise and are not a reliable calibration reference. Global maxima are strongly influenced by several environmental factors as well as instrument noise and are even less stationary. Global averages are largely insensitive to instrument noise and, in most cases, to environmental conditions as well. The global average T(sub B) varies at only the 0.1 K RMS level except in cases of anomalously high winds, when it can increase considerably more. The vicarious cold reference is similarly insensitive to instrument effects and most environmental factors. It is not significantly affected by high wind conditions. The stability of the vicarious reference is, however, found to be somewhat sensitive (at the several tenths of Kelvins level) to variations in the background cold space brightness, T(sub c). The global average is much less sensitive to this parameter and so using two approaches together can be mutually beneficial.

Ruf, Christopher S.↗
NASA NTRS2005

Minimizing Uncertainty in Cryogenic Surface Figure Measurement

A new facility at the Goddard Space Flight Center is designed to measure with unusual accuracy the surface figure of mirrors at cryogenic temperatures down to 12 K. The facility is currently configured for spherical mirrors with a radius of curvature (ROC) of 600 mm, and apertures of about 150 mm or less. The goals of the current experiment were to 1) Obtain the best possible estimate of test mirror surface figure, S(x,y) at 87 K and 20 K; 2) Obtain the best estimate of the cryo-change, Delta (x,y): the change in surface figure between room temperature and the two cryo-temperatures; and 3) Determine the uncertainty of these measurements, using the definitions and guidelines of the ISO Guide to the Expression of Uncertainty in Measurement. A silicon mirror was tested, and the cry-change from room temperature to 20K was found to be 3.7 nm rms, with a standard uncertainty of 0.23 nm in the rms statistic. Both the cryo-change figure and the uncertainty are among the lowest such figures yet published. This report describes the facilities, experimental methods, and uncertainty analysis of the measurements.

Blake, Peter↗
NASA NTRS2005

Surface Figure Measurement of Silicon Carbide Mirrors at Cryogenic Temperatures

The surface figure of a developmental silicon carbide mirror, cooled to 87 K and then 20 K within a cryostat, was measured with unusually high precision at the Goddard Space Flight Center (GSFC). The concave spherical mirror, with a radius of 600 mm and a clear aperture of 150 mm, was fabricated of sintered silicon carbide. The mirror was mounted to an interface plate representative of an optical bench, made of the material Cesic@, a composite of silicon, carbon, and silicon carbide. The change in optical surface figure as the mirror and interface plate cooled from room temperature to 20 K was 3.7 nm rms, with a standard uncertainty of 0.23 nm in the rms statistic. Both the cryo-change figure and the uncertainty are among the lowest such figures yet published. This report describes the facilities, experimental methods, and uncertainty analysis of the measurements.

Blake, Peter↗