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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
NASA NTRS2010

Composite Overwrapped Pressure Vessel (COPV) Stress Rupture Testing

This paper reports stress rupture testing of Kevlar(TradeMark) composite overwrapped pressure vessels (COPVs) at NASA White Sands Test Facility. This 6-year test program was part of the larger effort to predict and extend the lifetime of flight vessels. Tests were performed to characterize control parameters for stress rupture testing, and vessel life was predicted by statistical modeling. One highly instrumented 102-cm (40-in.) diameter Kevlar(TradeMark) COPV was tested to failure (burst) as a single-point model verification. Significant data were generated that will enhance development of improved NDE methods and predictive modeling techniques, and thus better address stress rupture and other composite durability concerns that affect pressure vessel safety, reliability and mission assurance.

Greene, Nathanael J.↗
NASA NTRS2010

Composite Overwrapped Pressure Vessels (COPV): Developing Flight Rationale for the Space Shuttle Program

Introducing composite vessels into the Space Shuttle Program represented a significant technical achievement. Each Orbiter vehicle contains 24 (nominally) Kevlar tanks for storage of pressurized helium (for propulsion) and nitrogen (for life support). The use of composite cylinders saved 752 pounds per Orbiter vehicle compared with all-metal tanks. The weight savings is significant considering each Shuttle flight can deliver 54,000 pounds of payload to the International Space Station. In the wake of the Columbia accident and the ensuing Return to Flight activities, the Space Shuttle Program, in 2005, re-examined COPV hardware certification. Incorporating COPV data that had been generated over the last 30 years and recognizing differences between initial Shuttle Program requirements and current operation, a new failure mode was identified, as composite stress rupture was deemed credible. The Orbiter Project undertook a comprehensive investigation to quantify and mitigate this risk. First, the engineering team considered and later deemed as unfeasible the option to replace existing all flight tanks. Second, operational improvements to flight procedures were instituted to reduce the flight risk and the danger to personnel. Third, an Orbiter reliability model was developed to quantify flight risk. Laser profilometry inspection of several flight COPVs identified deep (up to 20 mil) depressions on the tank interior. A comprehensive analysis was performed and it confirmed that these observed depressions were far less than the criterion which was established as necessary to lead to liner buckling. Existing fleet vessels were exonerated from this failure mechanism. Because full validation of the Orbiter Reliability Model was not possible given limited hardware resources, an Accelerated Stress Rupture Test of a flown flight vessel was performed to provide increased confidence. A Bayesian statistical approach was developed to evaluate possible test results with respect to the model credibility and thus flight rationale for continued operation of the Space Shuttle with existing flight hardware. A non-destructive evaluation (NDE) technique utilizing Raman Spectroscopy was developed to directly measure the overwrap residual stress state. Preliminary results provide optimistic results that patterns of fluctuation in fiber elastic strains over the outside vessel surface could be directly correlated with increased fiber stress ratios and thus reduced reliability.

Kezirian, Michael T.↗
DOE OSTI2020

Sterilization of N95 Respirators via Gamma Radiation: Comparison of Post-sterilization Efficacy

This study evaluated gamma irradiation for sterilization and reuse of two models of N95 respirators after gamma radiation sterilization as a method to increase availability of N95 respirators during a shortage. The Sandia National Laboratories Gamma Irradiation Facility was used to irradiate two different models of N95 filtering facepiece respirators at doses ranging from 0 kGy(tissue) to 50 kGy(tissue). The following tests were used to determine the efficacy of the respirator after irradiation sterilization: Ambient Aerosol Condensation Nuclei Counter Quantitative Fit Test, tensile test, strain cycling, oscillatory dynamic mechanical analysis, microscopic image analysis of fiber layers, and electrostatic field measurements. Both of the respirator models exhibited statistically significant changes after gamma irradiation as shown by the Quantitative Fit Test, electrostatic testing and the aerosol testing. The change in electrostatic capability of the filter reduced the efficiency of challenging particles near the 200 nm size by approximately 40-50%. Both tested respirators showed statistically significant changes associated with gamma sterilization. However, our results indicate that choices in materials and manufacturing methods to achieve N95 filtration lead to different magnitudes of damage when exposed to gamma radiation at sterilization relevant doses. This damage results in lower filtration performance. While our sample size (2 different types of respirators) was small, we did observe a change in electrostatic properties on a filter layer that coincided with the failure on the Quantitative Fit Test.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2020

Sterilization of N95 Respirators via Gamma Radiation: Comparison of Post-sterilization Efficacy

This study evaluated gamma irradiation for sterilization and reuse of two models of N95 respirators after gamma radiation sterilization as a method to increase availability of N95 respirators during a shortage. The Sandia National Laboratories Gamma Irradiation Facility was used to irradiate two different models of N95 filtering facepiece respirators at doses ranging from 0 kGy(tissue) to 50 kGy(tissue). The following tests were used to determine the efficacy of the respirator after irradiation sterilization: Ambient Aerosol Condensation Nuclei Counter Quantitative Fit Test, tensile test, strain cycling, oscillatory dynamic mechanical analysis, microscopic image analysis of fiber layers, and electrostatic field measurements. Both of the respirator models exhibited statistically significant changes after gamma irradiation as shown by the Quantitative Fit Test, electrostatic testing and the aerosol testing. The change in electrostatic charge of the filter was correlated with a reduction in capturing particles near the 200 nm size by approximately 40-50%. Both tested respirators showed statistically significant changes associated with gamma sterilization. However, our results indicate that choices in materials and manufacturing methods to achieve N95 filtration lead to different magnitudes of damage when exposed to gamma radiation at sterilization relevant doses. This damage results in lower filtration performance. While our sample size (2 different types of respirators) was small, we did observe a change in electrostatic properties on a filter layer that coincided with the failure on the Quantitative Fit Test and reduction in aerosol filtering efficiency. Key Words: N95 respirators, respirators, airborne transmission, pandemic prevention, COVID-19, gamma sterilization

COVID-19↗
NASA NTRS1985

Investigation of the dayside boundary region of the magnetosphere

The region near the dayside boundary of the magnetosphere is of particular interest mainly because it is the most likely site for solar wind energy transfer. Exactly where and how this transfer occurs is one of the basic problems of magnetospheric physics. The global nature of the energy transfer is addressed in this research. In order to test whether energy transfer affects the large scale plasma flow in the magnetosheath, global properties of the magnetosheath were analyzed and compared to models with no energy transfer. Also, global models of merging sites on the magnetopause were modeled with the aid of the magnetosheath models. Since energy transfer and intrinsic magnetosheath properties depend upon the orientation of the interplanetary magnetic field (IMF), it was essential to have an IMF monitor for these studies. In the course of using ISEE 3 in this role, statistical studies were performed to test the accuracy of using data from an orbit so far upstream. Global properties of the magnetosheath energetic ion population, magnetic field strength and orientation, and flow pattern, determined with ISEE data are summarized.

Crooker, N.↗
DOE OSTI2020

Conservative Estimation of Tail Probabilities from Limited Sample Data

Several sparse-sample uncertainty quantification (UQ) methods are compared for conservative but not overly conservative estimation of small tail probabilities involving responses that lay beyond specified thresholds in the tails of probability distributions. Sixteen very differently shaped distributions (or probability density functions, PDFs) and tail probability magnitudes ranging from 10 -5 to 10 -1 are considered in order for the study to be relevant to a wide range of risk analysis and quantification of margins and uncertainty (QMU) problems. The emphasis of the study is on limited data regimes ranging from N = 2 to 20 samples, reflective of most experimental and some expensive computational situations. Relatively simple sparse-sample UQ methods tested for this regime involve statistical tolerance interval "Equivalent Normal and related "Ensemble of Normals" and "Superdistribution (SD) approaches. (The independently derived SD is effectively equivalent to the Bayesian posterior predictive distribution given the assumptions of the derivation.) The performance of the methods was generally improved for N ≥ 5 samples with a generalized Jackknife resampling technique, which determines a tail probability estimate by averaging estimates from smaller sub-samples. Several quantitative metrics for method conservatism and accuracy of tail probability estimation are used to assess and rank the methods' performance over many random trials for each test PDF and probability magnitude. A variant of Bootstrap resampling was also tried, but did not significantly improve tail probability estimates in most cases. Detailed results are presented from over 100-million tests over the above factors that provide useful granular information on which methods or combination of methods perform best in various areas of the factor space.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1999

On-Line Analysis of Physiologic and Neurobehavioral Variables During Long-Duration Space Missions

The goal of this project is to develop reliable statistical algorithms for on-line analysis of physiologic and neurobehavioral variables monitored during long-duration space missions. Maintenance of physiologic and neurobehavioral homeostasis during long-duration space missions is crucial for ensuring optimal crew performance. If countermeasures are not applied, alterations in homeostasis will occur in nearly all-physiologic systems. During such missions data from most of these systems will be either continually and/or continuously monitored. Therefore, if these data can be analyzed as they are acquired and the status of these systems can be continually assessed, then once alterations are detected, appropriate countermeasures can be applied to correct them. One of the most important physiologic systems in which to maintain homeostasis during long-duration missions is the circadian system. To detect and treat alterations in circadian physiology during long duration space missions requires development of: 1) a ground-based protocol to assess the status of the circadian system under the light-dark environment in which crews in space will typically work; and 2) appropriate statistical methods to make this assessment. The protocol in Project 1, Circadian Entrainment, Sleep-Wake Regulation and Neurobehavioral will study human volunteers under the simulated light-dark environment of long-duration space missions. Therefore, we propose to develop statistical models to characterize in near real time circadian and neurobehavioral physiology under these conditions. The specific aims of this project are to test the hypotheses that: 1) Dynamic statistical methods based on the Kronauer model of the human circadian system can be developed to estimate circadian phase, period, amplitude from core-temperature data collected under simulated light- dark conditions of long-duration space missions. 2) Analytic formulae and numerical algorithms can be developed to compute the error in the estimates of circadian phase, period and amplitude determined from the data in Specific Aim 1. 3) Statistical models can detect reliably in near real- time (daily) significant alternations in the circadian physiology of individual subjects by analyzing the circadian and neurobehavioral data collected in Project 1. 4) Criteria can be developed using the Kronauer model and the recently developed Jewett model of cognitive -performance and subjective alertness to define altered circadian and neurobehavioral physiology and to set conditions for immediate administration of countermeasures.

Brown, Emery N.↗
DOE OSTI2019

Cross-correlation of CMB Polarization Lensing with High-$z$ Submillimeter $Herschel$-ATLAS Galaxies

Herein we report a 4.8σ measurement of the cross-correlation signal between the cosmic microwave background (CMB) lensing convergence reconstructed from measurements of the CMB polarization made by the P OLARBEAR experiment and the infrared-selected galaxies of the $Herschel$-ATLAS survey. This is the first measurement of its kind. We infer a best-fit galaxy bias of $b$ = 5.76 ± 1.25, corresponding to a host halo mass of log 10 (M h /M ⊙ ). =13.5$^{+0.2}_{-0.3}$ at an effective redshift of $z$ ~ 2 from the cross-correlation power spectrum. Residual uncertainties in the redshift distribution of the submillimeter galaxies are subdominant with respect to the statistical precision. We perform a suite of systematic tests, finding that instrumental and astrophysical contaminations are small compared to the statistical error. This cross-correlation measurement only relies on CMB polarization information that, differently from CMB temperature maps, is less contaminated by galactic and extragalactic foregrounds, providing a clearer view of the projected matter distribution. This result demonstrates the feasibility and robustness of this approach for future high-sensitivity CMB polarization experiments.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1991

Relationship between voids and interlaminar shear strength of polymer matrix composites

The effect of voids on the interlaminar shear strength of a polyimide matrix composite system is described. The AS4 graphite/PMR-15 composite was chosen for study because this system can be readily processed by using the standard specified cure cycle to produce void-free composites and because preliminary work in this study had shown that the processing parameters of this resin matrix system can be altered to produce cured composites of varying void contents. Thirty-eight 12-ply unidirectional composite panels were fabricated for this study. A significant range of void contents (0 to 10 percent) was produced. The panels were mapped, ultrasonically inspected, and sectioned into interlaminar shear, flexure, and fiber content specimens. The density of each specimen was measured and interlaminar shear and flexure strength measurements were then made. The fiber content was measured last. The results of these tests were evaluated by using ultrasonic results, photomicrographs, statistical methods, theoretical relationships derived by other investigators, and comparison of the test data with the Integrated Composite Analyzer (ICAN) computer program developed at the Lewis Research Center for predicting composite ply properties. The testing is described in as much detail as possible in order to help others make realistic comparisons.

Bowles, Kenneth J.↗
NASA NTRS1991

Relationship between voids and interlaminar shear strength of polymer matrix composites

The effect of voids on the interlaminar shear strength of a polyimide matrix composite system is described. The AS4 graphite/PMR-15 composite was chosen for study because this system can be readily processed by using the standard specified cure cycle to produce void-free composites and because preliminary work in this study had shown that the processing parameters of this resin matrix system can be altered to produce cured composites of varying void contents. Thirty-eight 12-ply unidirectional composite panels were fabricated for this study. A significant range of void contents (0 to 10 percent) was produced. The panels were mapped, ultrasonically inspected, and sectioned into interlaminar shear, flexure, and fiber content specimens. The density of each specimen was measured and interlaminar shear and flexure strength measurements were then made. The fiber content was measured last. The results of these tests were evaluated by using ultrasonic results, photomicrographs, statistical methods, theoretical relationships derived by other investigations, and comparison of the test data with the Integrated Composite Analyzer (ICAN) computer program developed at the Lewis Research Center for predicting composite ply properties. The testing is described in as much detail as possible in order to help others make realistic comparisons.

Bowles, Kenneth J.↗
NASA NTRS2010

Advances in Landslide Hazard Forecasting: Evaluation of Global and Regional Modeling Approach

A prototype global satellite-based landslide hazard algorithm has been developed to identify areas that exhibit a high potential for landslide activity by combining a calculation of landslide susceptibility with satellite-derived rainfall estimates. A recent evaluation of this algorithm framework found that while this tool represents an important first step in larger-scale landslide forecasting efforts, it requires several modifications before it can be fully realized as an operational tool. The evaluation finds that the landslide forecasting may be more feasible at a regional scale. This study draws upon a prior work's recommendations to develop a new approach for considering landslide susceptibility and forecasting at the regional scale. This case study uses a database of landslides triggered by Hurricane Mitch in 1998 over four countries in Central America: Guatemala, Honduras, EI Salvador and Nicaragua. A regional susceptibility map is calculated from satellite and surface datasets using a statistical methodology. The susceptibility map is tested with a regional rainfall intensity-duration triggering relationship and results are compared to global algorithm framework for the Hurricane Mitch event. The statistical results suggest that this regional investigation provides one plausible way to approach some of the data and resolution issues identified in the global assessment, providing more realistic landslide forecasts for this case study. Evaluation of landslide hazards for this extreme event helps to identify several potential improvements of the algorithm framework, but also highlights several remaining challenges for the algorithm assessment, transferability and performance accuracy. Evaluation challenges include representation errors from comparing susceptibility maps of different spatial resolutions, biases in event-based landslide inventory data, and limited nonlandslide event data for more comprehensive evaluation. Additional factors that may improve algorithm performance accuracy include incorporating additional triggering factors such as tectonic activity, anthropogenic impacts and soil moisture into the algorithm calculation. Despite these limitations, the methodology presented in this regional evaluation is both straightforward to calculate and easy to interpret, making results transferable between regions and allowing findings to be placed within an inter-comparison framework. The regional algorithm scenario represents an important step in advancing regional and global-scale landslide hazard assessment and forecasting.

Kirschbaum, Dalia B.↗
DOE OSTI2024

Nonparametric Multiparticle Set Methods for Interpreting Environmental Samples

Collection and analysis of environmental samples is commonly used by a range of stakeholders in nuclear safeguards and security contexts. While the ubiquity of samples and their transport in the environment allow regular collection, developing and demonstrating methods for analyzing these samples is difficult. In this work, an environmental sample consists of a set of one or more individual particles. Recent advances in reactor simulation have allowed us to generate data that are more representative of real-world environmental samples, enabling statistically defensible method development and testing. The most notable of these advances is a drastic increase in the number of material depletion regions, which allows our simulations to capture the variation in isotopic composition seen at length scales consistent with environmental samples. Traditional approaches for handling multiparticle samples treat each particle in the sample individually, estimating the quantity of interest (e.g., core-average burnup) resulting from measurement and analysis of signatures (e.g., nuclide assays) from each individual particle. Individual estimates are then averaged to generate a single estimate of the quantity of interest over the entire sample. In this presentation, we introduce two novel approaches for interpreting environmental samples that comprise of multiple particles: (1) the Quantile-Quantile Comparator, which uses a multivariate generalization of quantile-quantile plots for comparing unknown statistical distributions, and (2) the Set Transformer, an attention-based neural network module designed to model interactions among elements (particles) in the input set (sample). Statistically representative sampling cannot be guaranteed as samples are passively collected and are beholden to what particles are available in the environment. These new analysis methods for set-input problems are expected to be more robust than traditional approaches to issues of sampling bias where particles are not uniformly distributed throughout regions of interest, as well as generally outperform traditional approaches by jointly considering all elements in the set. We will present results comparing the performance of traditional single particle approaches and the novel Quantile-Quantile Comparator and Set Transformer for interpretation of simulated environmental samples.

Phathanapirom, Birdy↗
DOE OSTI2020

Correlation approach for quality assurance of additive manufactured parts based on optical metrology

Surface topography and surface finish are two significant factors for evaluating the quality of products in additive manufacturing (AM). AM parts are fabricated layer by layer, which is quite different from traditional formative or subtractive methods. Despite rapid progress in additive manufacturing and associated optical metrology for quality control and in-situ monitoring, limited research has been conducted to investigate the reliability of 3D surface measurement data. The surface topologies scanned by multiple optical systems demonstrated significant differences due to varying sampling mechanisms, resolutions, system noises, etc. The 3D datasets should be trustworthy in order to extract parameters for quality assurance or feedback control from 3D surface measurements. In this paper, we set up new standards to evaluate the reliability of 3D surface measurement data and analyze the variation in the topographical profile. In this study, two non-contact optical methods based on Focus Variation Microscopy (FVM) and Structured Light System (SLS) were adopted to measure the surface topography of the target components. The two optical metrology systems generated two entirely different point cloud datasets. Statistical methods were applied to test the difference between the data obtained from the two systems. By using a data analytics approach for comparison, it was found that the surface roughness estimated from the point cloud data sets of FVM and SLS has no significant difference, though the point cloud data sets were completely different. This paper provides standard validation approach to evaluate the plausibility of metrology data from in-situ real-time surface analysis for process planning of AM.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Improving multiwell petrophysical interpretation from well logs via machine learning and statistical models

Well-log interpretation estimates in situ rock properties along well trajectory, such as porosity, water saturation, and permeability, to support reserve-volume estimation, production forecasts, and decision making in reservoir development. However, due to measurement errors, variability of well logs caused by multiple measurement vendors, different borehole tools, and nonuniform drilling/borehole conditions, estimations of rock properties with original well logs without proper preprocessing may not be accurate, especially in the context of multiwell estimation. Well-log normalization techniques such as two-point scaling and mean-variance normalization are commonly used to improve the robustness of multiwell rock-property estimation. However, these techniques do not consider the correlation between well logs and require subjective knowledge for their effective implementation. To reduce uncertainties and processing time associated with multiwell rock-property estimation from well logs, we develop discriminative adversarial (DA) and linear constraint models for well-log normalization and rock-property estimation. The DA neural network model developed for well-log normalization and interpretation can perform linear and nonlinear well-log normalization while considering the joint distribution of each well log and rock properties. However, the linear constraint model uses an ensemble of predictions from linear models to constrain well-log normalization and rock-property estimation. We also develop a divergence-based type well identification method to select type (training) wells for a test well based on the statistical similarity of associated well-log distributions instead of the interwell distance. We apply the DA model to perform well-log normalization and prediction of permeability for the Seminole San Andres Unit carbonate reservoir. Compared with the permeability predicted with the classical machine learning model without well-log normalization and models with two-point scaling normalization, the DA model yields the most accurate permeability prediction by decreasing the mean-squared error of permeability prediction by 20%–50%.

Geochemistry & Geophysics↗
NASA NTRS1979

Performance characteristics and statistics of a laser initiated microdetonator

The test results of 320 units of the laser initiated microdetonator are summarized. The commercially fabricated units used a lead styphnate/lead azide/HMX (1 mg/17.5 mg/13.5 mg) explosive train design contained in a miniature aluminum can and completed with a glass-metal seal window. The test parameters were the high and low laser energy, high and low temperature, laser pulse duration, laser wavelength and nuclear radiation (5 x 10 to the 6th rads of 1 MeV gamma ray). The performance parameters were the laser energy for ignition and the actuation response time. Included also is a description of the development of a flexible, continuously advanced train of explosive devices by using the units, miniature optics and fiber optics.

Yang, L. C.↗
NASA NTRS1994

Is a data set distributed as a power law? A test, with application to gamma-ray burst brightnesses

We present a method to determine whether an observed sample of data is drawn from a parent distribution that is pure power law. The method starts from a class of statistics which have zero expectation value under the null hypothesis, H(sub 0), that the distribution is a pure power law: F(x) varies as x(exp -alpha). We study one simple member of the class, named the `bending statistic' B, in detail. It is most effective for detection a type of deviation from a power law where the power-law slope varies slowly and monotonically as a function of x. Our estimator of B has a distribution under H(sub 0) that depends only on the size of the sample, not on the parameters of the parent population, and is approximated well by a normal distribution even for modest sample sizes. The bending statistic can therefore be used to test a set of numbers is drawn from any power-law parent population. Since many measurable quantities in astrophysics have distriibutions that are approximately power laws, and since deviations from the ideal power law often provide interesting information about the object of study (e.g., a `bend' or `break' in a luminosity function, a line in an X- or gamma-ray spectrum), we believe that a test of this type will be useful in many different contexts. In the present paper, we apply our test to various subsamples of gamma-ray burst brightness from the first-year Burst and Transient Source Experiment (BATSE) catalog and show that we can only marginally detect the expected steepening of the log (N (greater than C(sub max))) - log (C(sub max)) distribution.

Wijers, Ralph A. M. J.↗