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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Transmission overhaul and replacement predictions using Weibull and renewel theory

A method to estimate the frequency of transmission overhauls is presented. This method is based on the two-parameter Weibull statistical distribution for component life. A second method is presented to estimate the number of replacement components needed to support the transmission overhaul pattern. The second method is based on renewal theory. Confidence statistics are applied with both methods to improve the statistical estimate of sample behavior. A transmission example is also presented to illustrate the use of the methods. Transmission overhaul frequency and component replacement calculations are included in the example.

Savage, M.↗
NASA NTRS1989

Transmission overhaul and replacement predictions using Weibull and renewal theory

A method to estimate the frequency of transmission overhauls is presented. This method is based on the two-parameter Weibull statistical distribution for component life. A second method is presented to estimate the number of replacement components needed to support the transmission overhaul pattern. The second method is based on renewal theory. Confidence statistics are applied with both methods to improve the statistical estimate of sample behavior. A transmission example is also presented to illustrate the use of the methods. Transmission overhaul frequency and component replacement calculations are included in the example.

Savage, M.↗
DOE OSTI2023

(U) A General-Purpose Code for Correlated Sampling Using Batch Statistics with MCNP6 for Fixed-Source Problems

Correlated sampling can be used to reduce the uncertainty of a difference of tallies by taking advantage of the negative covariance term in the sandwich formula. Booth first showed how correlated sampling can be applied with batch statistics using MCNP’s tally fluctuation chart (TFC) to reduce the uncertainty of a difference of tallies in fixed-source problems. Booth presented a problem in which a 1273% uncertainty in a difference was reduced to 8% by accounting for correlations. Researchers He and Su recently studied correlated sampling using the TFC in MCNP version 5. They determined that the code did not print enough digits in the TFC tally means for accurate batch statistics in some cases. After modifying the source code, they concluded that “correlated sampling can yield a standard deviation of about one magnitude smaller than that predicted by the direct, un-correlated simulation when the changes in system response are small (say about 1%), which is equivalent to saving in CPU time by a factor of 100. Such saving [sic] becomes less significant as the change in system response becomes larger.” He and Su provided the formulas needed to apply batch statistics to compute the correlated uncertainty of a difference of tallies. In this report, we follow up on their work by providing the formulas needed to apply batch statistics to compute the correlated uncertainty of a ratio of tallies and of a difference of two tallies divided by a third tally. We extend these formulas to differences and ratios of ratios. These formulas are applied to reduce the uncertainty associated with calculating a relative sensitivity. He and Su did not investigate the accuracy of their correlated sampling uncertainty estimates. We use their test problems and evaluate the accuracy of the uncertainty estimates by comparing with results obtained from random sampling, and, in simple cases, with theoretical values of the “exact” uncertainties. We find that the uncertainties obtained from batch statistics are accurate as long as at least 100 batches are used. We present a new computer code, COSUBS (COrrelated Sampling Using Batch Statistics), that reads MCNP6 TFCs and applies correlated sampling using batch statistics for the tally combinations that the user specifies. COSUBS is a very general tool that compares all TFCs for a base case and one or two perturbed cases. It computes uncertainties for ratios if given only a base case. This report is organized as follows. The equations to apply batch statistics to the difference of random tallies are reviewed in Sec. II. Section III presents the equations for applying batch statistics to a ratio of random tallies; this is useful for computing relative sensitivities using a one-sided finite difference and the relative sensitivity using the differential operator method. Section IV presents the equations for applying batch statistics to a difference of two random tallies divided by a third; this is useful for computing a relative sensitivities using a central difference. Section V presents the equations for applying batch statistics to a difference of two ratios with four random tallies. Section VI presents the equations for applying batch statistics to a one-sided finite difference estimate of the relative sensitivity of a ratio (this uses four random tallies). Section VII presents the equations for applying batch statistics to a central difference estimate of the relative sensitivity of a ratio (this uses six random tallies). Section VIII presents the equations for applying batch statistics to a sum of random tallies. Section IX discusses how to apply batch statistics using MCNP6. Section X presents COSUBS, describing its command-line options and logic. Sections XI through XVI present numerical results for various test problems. Section XVII is a summary and conclusions. Appendix A derives the theoretical Monte Carlo tally variance given certain assumptions; these variances are used to verify the batch statistics for some of the problems. Appendix B lists the MCNP6 input for the unperturbed example problem. Appendix C presents modifications made to MCNP6.3 to support this work.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Evaluation of Applied Stress on Atmospheric Corrosion and Pitting Characteristics in 304L Stainless Steel

For this study, the effects of applied stress, ranging from tensile to compressive, on the atmospheric pitting corrosion behavior of 304L stainless steel (SS304L) were analyzed through accelerated atmospheric laboratory exposures and microelectrochemical cell analysis. After exposing the lateral surface of a SS304L four-point bend specimen to artificial seawater at 50°C and 35% relative humidity for 50 d, pitting characteristics were determined using optical profilometry and scanning electron microscopy. The SS304L microstructure was analyzed using electron backscatter diffraction. Additionally, localized electrochemical measurements were performed on a similar, unexposed, SS304L four-point bend bar to determine the effects of applied stress on corrosion susceptibility. Under the applied loads and the environment tested, the observed pitting characteristics showed no correlation with the applied stress (from 250 MPa to -250 MPa). Pitting depth, surface area, roundness, and distribution were found to be independent of location on the sample or applied stress. The lack of correlation between pitting statistics and applied stress was more likely due to the aggressive exposure environment, with a sea salt loading of 4 g/m 2 chloride. The pitting characteristics observed were instead governed by the available cathode current and salt distribution, which are a function of sea salt loading, as well as pre-existing underlying microstructure. In microelectrochemical cell experiments performed in Cl - environments comparable to the atmospheric exposure and in environments containing orders of magnitude lower Cl - concentrations, effects of the applied stress on corrosion susceptibility were only apparent in open-circuit potential in low Cl - concentration solutions. Cl - concentration governed the current density and transpassive dissolution potential.

36 MATERIALS SCIENCE↗
NASA NTRS1998

Examination of two methods for statistical analysis of data with magnitude and direction emphasizing vestibular research applications

When the dependent (or response) variable response variable in an experiment has direction and magnitude, one approach that has been used for statistical analysis involves splitting magnitude and direction and applying univariate statistical techniques to the components. However, such treatment of quantities with direction and magnitude is not justifiable mathematically and can lead to incorrect conclusions about relationships among variables and, as a result, to flawed interpretations. This note discusses a problem with that practice and recommends mathematically correct procedures to be used with dependent variables that have direction and magnitude for 1) computation of mean values, 2) statistical contrasts of and confidence intervals for means, and 3) correlation methods.

Vestibule↗
DOE OSTI2022

Device and methods for determination of molecular weight distributions of polymers and distributions of other polymer properties without physical separation

Devices and methods for determining the cumulative distribution of a polymer property in a reactor without physical separation of reaction subcomponents. The device includes a means of measuring an instantaneous property of the polymers being produced in a reaction vessel a plurality of times during a polymerization reaction as well as a means of determining the corresponding change in polymer concentration in the reaction vessel between measurements of the instantaneous polymer property The device also includes a means of computing a statistical distribution appropriate to the polymer characteristic and applying the statistical distribution to a recently measured instantaneous value of the polymer property so as to have an instantaneous distribution of the polymer property and a means of adding together the instantaneous distributions of the polymer property in order to obtain the cumulative distribution of the polymer property in the reactor.

Reed, Wayne Frederick↗
DOE OSTI2024

Device and methods for determination of molecular weight distributions of polymers and distributions of other polymer properties without physical separation

Devices and methods for determining the cumulative distribution of a polymer property in a reactor without physical separation of reaction subcomponents. The device includes a means of measuring an instantaneous property of the polymers being produced in a reaction vessel a plurality of times during a polymerization reaction as well as a means of determining the corresponding change in polymer concentration in the reaction vessel between measurements of the instantaneous polymer property. The device also includes a means of computing a statistical distribution appropriate to the polymer characteristic and applying the statistical distribution to a recently measured instantaneous value of the polymer property so as to have an instantaneous distribution of the polymer property and a means of adding together the instantaneous distributions of the polymer property in order to obtain the cumulative distribution of the polymer property in the reactor.

Reed, Wayne Frederick↗
NASA NTRS2019

Computational Bayesian Methods Applied to Complex Problems in Bio and Astro Statistics

In this dissertation we apply computational Bayesian methods to three distinct problems. In the first chapter, we address the issue of unrealistic covariance matrices used to estimate collision probabilities. We model covariance matrices with a Bayesian Normal-Inverse-Wishart model, which we fit with Gibbs sampling. In the second chapter, we are interested in determining the sample sizes necessary to achieve a particular interval width and establish non-inferiority in the analysis of prevalences using two fallible tests. To this end, we use a third order asymptotic approximation. In the third chapter, we wish to synthesize evidence across multiple domains in measurements taken longitudinally across time, featuring a substantial amount of structurally missing data, and fit the model with Hamiltonian Monte Carlo in a simulation to analyze how estimates of a parameter of interest change across sample sizes.

Elrod, Chris↗
NASA NTRS1989

Chi-squared and C statistic minimization for low count per bin data

Results are presented from a computer simulation comparing two statistical fitting techniques on data samples with large and small counts per bin; the results are then related specifically to X-ray astronomy. The Marquardt and Powell minimization techniques are compared by using both to minimize the chi-squared statistic. In addition, Cash's C statistic is applied, with Powell's method, and it is shown that the C statistic produces better fits in the low-count regime than chi-squared.

Nousek, John A.↗
NASA NTRS2017

The Statistical Mechanics of Solar Wind Hydroxylation at the Moon, Within Lunar Magnetic Anomalies, and at Phobos

We present a new formalism to describe the outgassing of hydrogen initially implanted by the solar wind protons into exposed soils on airless bodies. The formalism applies a statistical mechanics approach similar to that applied recently to molecular adsorption onto activated surfaces. The key element enabling this formalism is the recognition that the interatomic potential between the implanted H and regolith-residing oxides is not of singular value but possess a distribution of trapped energy values at a given temperature, F(U,T). All subsequent derivations of the outward diffusion and H retention rely on the specific properties of this distribution. We find that solar wind hydrogen can be retained if there are sites in the implantation layer with activation energy values exceeding 0.5eV. We especially examine the dependence of H retention applying characteristic energy values found previously for irradiated silica and mature lunar samples. We also apply the formalism to two cases that differ from the typical solar wind implantation at the Moon. First, we test for a case of implantation in magnetic anomaly regions where significantly lower-energy ions of solar wind origin are expected to be incident with the surface. In magnetic anomalies, H retention is found to be reduced due to the reduced ion flux and shallower depth of implantation. Second, we also apply the model to Phobos where the surface temperature range is not as extreme as the Moon. We find the H atom retention in this second case is higher than the lunar case due to the reduced thermal extremes (that reduces outgassing).

Solar Wind↗
NASA NTRS2002

Experimental Investigations of Non-Stationary Properties In Radiometer Receivers Using Measurements of Multiple Calibration References

Radiometers must be periodically calibrated because the receiver response fluctuates. Many techniques exist to correct for the time varying response of a radiometer receiver. An analytical technique has been developed that uses generalized least squares regression (LSR) to predict the performance of a wide variety of calibration algorithms. The total measurement uncertainty including the uncertainty of the calibration can be computed using LSR. The uncertainties of the calibration samples used in the regression are based upon treating the receiver fluctuations as non-stationary processes. Signals originating from the different sources of emission are treated as simultaneously existing random processes. Thus, the radiometer output is a series of samples obtained from these random processes. The samples are treated as random variables but because the underlying processes are non-stationary the statistics of the samples are treated as non-stationary. The statistics of the calibration samples depend upon the time for which the samples are to be applied. The statistics of the random variables are equated to the mean statistics of the non-stationary processes over the interval defined by the time of calibration sample and when it is applied. This analysis opens the opportunity for experimental investigation into the underlying properties of receiver non stationarity through the use of multiple calibration references. In this presentation we will discuss the application of LSR to the analysis of various calibration algorithms, requirements for experimental verification of the theory, and preliminary results from analyzing experiment measurements.

Racette, Paul↗
NASA NTRS1995

Eclipse timings of the low-mass X-ray binary EXO 0748-676: Statistical arguments against orbital period changes

EXO 0748-676, an eclipsing low-mass X-ray binary, is one of only about four or five low-mass X-ray binaries for which orbital period evolution has been reported. We observed a single eclipse egress with ROSAT . The time of this egress is consistent with the apparent increase in P(sub orb) previously reported on the basis of EXOSAT and Ginga observations. Standard analysis, in which O-C (observed minus calculated) timing residuals are examined for deviations from a constant period, implicitly assume that the only uncertainty in each residual is measurement error and that these errors are independent. We argue that the variable eclipse durations and profiles observed in EXO 0748-676 imply that there is an additional source of uncertainty in timing measurements, that this uncertainty is intrinsic to the binary system, and that it is correlated from observation to observation with a variance which increases as a function of the number of binary cycles between observations. This intrinsic variability gives rise to spurious trends in O-C residuals which are misinterpreted as changes in the orbital period. We describe several statistics tests which can be used to test for the presence of intrinsic variability. We apply those statistical tests which are suitable to the EXO 0748-676 observations. The apparent changes in the orbital period of EXO 0748-676 can be completely accounted for by intrinsic variability with an rms variability of approximately 0.35 s per orbital cycle. The variability appears to be correlated from cycle-to-cycle on timescales of less than 1 yr. We suggest that the intrinsic variability is related to slow changes in either the source's X-ray luminosity or the structure of the companion star's atmosphere. We note that several other X-ray binaries and cataclysmic variables have previously reported orbital period changes which may also be due to intrinsic variability rather than orbital period evolution.

Hertz, Paul↗
DOE OSTI2021

Markov Chain Monte Carlo Predictions of Neutron-rich Lanthanide Properties as a Probe of r -process Dynamics

Lanthanide element signatures are key to understanding many astrophysical observables, from merger kilonova light curves to stellar and solar abundances. To learn about the lanthanide element synthesis that enriched our solar system, we apply the statistical method of Markov Chain Monte Carlo to examine the nuclear masses capable of forming the r-process rare-earth abundance peak. We describe the physical constraints we implement with this statistical approach and demonstrate the use of the parallel chains method to explore the multidimensional parameter space. We apply our procedure to three moderately neutron-rich astrophysical outflows with distinct types of r-process dynamics. We show that the mass solutions found are dependent on outflow conditions and are related to the r-process path. We describe in detail the mechanism behind peak formation in each case. We then compare our mass predictions for neutron-rich neodymium and samarium isotopes to the latest experimental data from the CPT at CARIBU. Here, we find our mass predictions given outflows that undergo an extended (n,γ)⇌(γ,n) equilibrium to be those most compatible with both observational solar abundances and neutron-rich mass measurements.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Feasibility of Correlation-Aware Inference and Universal Precision Scaling in Bonse–Hart Ultra-Small-Angle Neutron Scattering

Bonse–Hart ultra-small-angle neutron scattering (USANS) provides access to micrometre-scale structure, but useful measurements often require long counting times. In this work, we test whether the expected smoothness of the scattering profile can be exploited to improve data quality at lower counting statistics. We apply a Gaussian-process-based method to Bonse–Hart USANS data and evaluate its performance on pseudo-measurements generated from high-statistics experiments under Poisson statistics. This provides a stringent test of how well the underlying I(Q) profile can be reconstructed when the available counts are substantially reduced. We further show that, in the counting-limited regime, the reconstruction error follows a universal scaling behaviour that differs from the usual independent-counting expectation. At higher counts, the improvement crosses over to a resolution-limited regime set by analyser-angle discretization and rocking-curve width. These results clarify when correlation-aware inference is useful in USANS and provide a practical basis for improving measurement efficiency and beam-time usage.

Tung, Chi-Huan [ORNL] (ORCID:0000000221972074)↗
NASA NTRS1966

Problems of stellar dynamics

Many-body problem, continuum, and statistical methods applied to dynamics of star clusters, with bibliography

STAR CLUSTER↗
DOE OSTI2023

Best practices in NMR metabolomics: Current state

A literature survey was conducted to identify current practices used by NMR metabolomics investigators when conducting and reporting their metabolomics studies. A total of 463 papers from 2020 and 80 papers from 2010 were selected from PubMed and were manually analyzed by a team of investigators to assess the extent and completeness of the experimental procedures and protocols reported. A significant number of the papers did not report on essential experimental details, incompletely stated which statistical methods were used, improperly applied supervised multivariate statistical analyses, or lacked validation of statistical models. A large diversity of protocols and software were identified, which suggests a lack of consensus and a relatively limited use of commonly agreed upon standards for conducting and reporting NMR metabolomics studies. In conclusion, the overall intent of the survey is to inform and encourage the NMR metabolomics community to develop and adopt best-practices for the field.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗