Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “statistics”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,351 records · Page 75
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Statistical Process Control and Analysis on the Water Content Measurements in NASA Glenn’s Icing Research Tunnel

The Icing Research Tunnel at NASA Glenn follows the recommended practice for calibration outlined in SAE’s ARP5905. The calibration team has followed the schedule of a full calibration every five years with a check calibration done every six months following. The liquid water content of the IRT has maintained stability within the stated specifications of variation within +/- 10% of the curve fit equation generated from calibration data. Using past measurements and data trends, IRT characterization engineers wanted to develop methods for the ability to know when data were not within variation. Trends can be observed in the liquid water content measurement process by constructing statistical process control charts. This paper describes data processing procedures for the Multi-Element Sensor in the IRT, including collision efficiency corrections, canonical correlation analysis, process for rejection of data, and construction of control charts. Data are presented to display the control capability to meet defined liquid water content specifications of the IRT with the Multi-Element Sensor mounted in the center of the test section.

Statistical Process Control↗
NASA NTRSDate not supplied

Launch Vehicle Design and Requirements Verification Using Statistical Methods

- This presentation applies statistics to launch vehicle design, but the methods may be used for other engineering applications - Vehicle Models: What do we know when? How to separate parameters for making Monte Carlo runs - Known when assembling the vehicle but not during design - Known prior to committing to flight - Unknown at lift off - How do we correctly model the vehicle during the design phases? - Number of Monte Carlo samples - Requirements success - Design parameter values

Monte Carlo↗
DOE OSTI2014

Statistical Distributions from Lens Manufacturing Data

Optical designers assume a mathematically derived statistical distribution of the relevant design parameters for their Monte Carlo tolerancing simulation. Presented are measured distributions using lens manufacturing data to better inform the decision-making process.

optical design, statistics, optomechanical, manufa↗
DOE OSTI2018

Statistical Interpolation for Surface Reconstruction of PDV and BLR Data

Data collection is becoming more and more dense in dynamic experiments, requiring a variety of diagnostics. Data are detected through such means as holography, Mie scattering / extinction, assay foils, surface imaging, and high-speed photography. The data are measured by radiography, velocimetry, ranging, Fiber Bragg, and pyrometry. The question is how can we unify information from multiple diagnostics and incorporate uncertainties to tell a coherent story about an experiment in a meaningful way? This presentation provides an overview of statistical interpolation by means of Kriging. Kriging involves three basic steps: (1) compute and model covariance spatial structure; (2) compute weights by minimizing mean squared prediction error; and (3) predict at the desired prediction sites.

dynamic experiments, holography, Mie scattering/ex↗
DOE OSTI2021

FedFleet 2021: Federal Automotive Statistical Tool - Federal Vehicle Fleet Data Collection

This presentation presents a brief overview of the collection of information about the US government's fleet of motor vehicles using the Federal Automotive Statistical Tool (FAST), discusses the makeup and operation of the vehicle fleet during FY 2020, discusses challenges associated with quality of the submitted data, and touches on future aspects of fleet data collection and reporting. FAST is a web-based information system sponsored by GSA's Office of Government-wide Policy and DOE's Federal Energy Management Program to collect information about the US federal government's fleet of motor vehicles; FAST is developed, maintained, and supported by DOE's Idaho National Laboratory (INL).

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

FedFleet 2022: Federal Automotive Statistical Tool - FY 2021 Fleet Trends and Data Quality

This presentation presents a brief overview of the collection of information about the US government's fleet of motor vehicles using the Federal Automotive Statistical Tool (FAST), discusses the makeup and operation of the vehicle fleet during FY 2021, discusses quality of the submitted data, and touches on future aspects of fleet data collection and reporting. FAST is a web-based information system sponsored by GSA's Office of Government-wide Policy and DOE's Federal Energy Management Program to collect information about the US federal government's fleet of motor vehicles; FAST is developed, maintained, and supported by DOE's Idaho National Laboratory (INL).

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2015

Using spatial statistical methods to determine an effective minimum detectable activity - 15681

Instrument minimum detectable activity (MDA) is generally established by collecting multiple measurements over time of a single representative background location to estimate a probability distribution of instrument readings. A reading that is considered to be greater than would be expected from the background probability distribution (i.e., a low-probability event) is deemed to be sufficiently unlikely that it must be attributable to added radioactivity and is therefore used as the instrument MDA. An effective MDA can be determined from spatially distributed data that are much lower than the instrument MDA. This has been accomplished using a large number of spatially distributed data points (from a radiation survey) where patterns of elevated survey readings can be distinguished from background at levels. Given the variation of the instrument response and the relatively low regulatory action levels, it is vital to establish MDA thresholds that are well below corrective action levels. Processing of radiological survey data with the use of histogram binning and geo-statistics in enabling pattern recognition can be used to establish effective field MDAs that are much lower than instrument MDAs. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Statistical Estimation of EV Driver Charging Behavior and Influential Factors

INL received data collected via telematics from battery electric vehicles (BEVs), and these vehicles were owned by retail customers who had entered into a telematics user agreement. The goal of analyzing these data was to develop mathematical models to characterize how different sets of BEV drivers use charging infrastructure at home and away from home (i.e., public charging) and quantify how various factors influence BEV drivers’ decision to charge and use available infrastructure. The data used in this analysis are unique because they provide real world BEV driving and charging behavior at the individual driving and parking event level. In this study we seek to leverage this data to quantify BEV charging and driving metrics to help inform models that predict quantities like the specific times when loads are imposed on the electrical grid due to BEV charging. Most models that have been developed to predict electrical grid load due to BEV charging, use simulations of BEV driving events and rely on assumptions such as every vehicle charges every night. Using a statistical modelling framework, we seek to investigate BEV charging behavior and quantitatively assess these common assumptions of BEV charging behavior.

33 - ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2014

Aerosol Effects on Cirrus through Ice Nucleation in the Community Atmosphere Model CAM5 with a Statistical Cirrus Scheme

A statistical cirrus cloud scheme that tracks ice saturation ratio in the clear-sky and cloudy portion of a grid box separately has been implemented into NCAR CAM5 to provide a consistent treatment of ice nucleation and cloud formation. Simulated ice supersaturation and ice crystal number concentrations strongly depend on the number concentrations of heterogeneous ice nuclei (IN), subgrid temperature formulas and the number concentration of sulfate particles participating in homogeneous freezing, while simulated ice water content is insensitive to these perturbations. 1% to 10% dust particles serving as heterogeneous IN is 20 found to produce ice supersaturaiton in better agreement with observations. Introducing a subgrid temperature perturbation based on long-term aircraft observations of meso-scale motion produces a better hemispheric contrast in ice supersaturation compared to observations. Heterogeneous IN from dust particles significantly alter the net radiative fluxes at the top of atmosphere (TOA) (-0.24 to -1.59 W m-2) with a significant clear-sky longwave component (0.01 to -0.55 W m-2). Different cirrus treatments significantly perturb the net TOA anthropogenic aerosol forcing from -1.21 W m-2 to -1.54 W m-2, with a standard deviation of 0.10 W m-2. Aerosol effects on cirrus clouds exert an even larger impact on the atmospheric component of the radiative fluxes (two or three times the changes in the TOA radiative fluxes) and therefore on the hydrology cycle through the fast atmosphere response. This points to the urgent need to quantify aerosol effects on cirrus clouds through ice nucleation and how these further affect the hydrological cycle.

Wang, Minghuai↗
DOE OSTI2016

Robust effects of cloud superparameterization on simulated daily rainfall intensity statistics across multiple versions of the C ommunity E arth S ystem M odel

Abstract This study evaluates several important statistics of daily rainfall based on frequency and amount distributions as simulated by a global climate model whose precipitation does not depend on convective parameterization—Super‐Parameterized Community Atmosphere Model (SPCAM). Three superparameterized and conventional versions of CAM, coupled within the Community Earth System Model (CESM1 and CCSM4), are compared against two modern rainfall products (GPCP 1DD and TRMM 3B42) to discriminate robust effects of superparameterization that emerge across multiple versions. The geographic pattern of annual‐mean rainfall is mostly insensitive to superparameterization, with only slight improvements in the double‐ITCZ bias. However, unfolding intensity distributions reveal several improvements in the character of rainfall simulated by SPCAM. The rainfall rate that delivers the most accumulated rain (i.e., amount mode) is systematically too weak in all versions of CAM relative to TRMM 3B42 and does not improve with horizontal resolution. It is improved by superparameterization though, with higher modes in regions of tropical wave, Madden‐Julian Oscillation, and monsoon activity. Superparameterization produces better representations of extreme rates compared to TRMM 3B42, without sensitivity to horizontal resolution seen in CAM. SPCAM produces more dry days over land and fewer over the ocean. Updates to CAM's low cloud parameterizations have narrowed the frequency peak of light rain, converging toward SPCAM. Poleward of 50°, where more rainfall is produced by resolved‐scale processes in CAM, few differences discriminate the rainfall properties of the two models. These results are discussed in light of their implication for future rainfall changes in response to climate forcing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Statistical tests of simple earthquake cycle models: Testing Earthquake Cycle Models

A central goal of observing and modeling the earthquake cycle is to forecast when a particular fault may generate an earthquake: a fault late in its earthquake cycle may be more likely to generate an earthquake than a fault early in its earthquake cycle. Models that can explain geodetic observations throughout the entire earthquake cycle may be required to gain a more complete understanding of relevant physics and phenomenology. Previous efforts to develop unified earthquake models for strike-slip faults have largely focused on explaining both preseismic and postseismic geodetic observations available across a few faults in California, Turkey, and Tibet. An alternative approach leverages the global distribution of geodetic and geologic slip rate estimates on strike-slip faults worldwide. Here we use the Kolmogorov-Smirnov test for similarity of distributions to infer, in a statistically rigorous manner, viscoelastic earthquake cycle models that are inconsistent with 15 sets of observations across major strike-slip faults. We reject a large subset of two-layer models incorporating Burgers rheologies at a significance level of α = 0.05 (those with long-term Maxwell viscosities η M <~ 4.0 × 10 19 Pa s and η M >~ 4.6 × 10 20 Pa s) but cannot reject models on the basis of transient Kelvin viscosity η K . Finally, we examine the implications of these results for the predicted earthquake cycle timing of the 15 faults considered and compare these predictions to the geologic and historical record.

58 GEOSCIENCES↗
DOE OSTI2016

A statistical study of EMIC waves observed by Cluster: 2. Associated plasma conditions

This is the second in a pair of papers discussing a statistical study of electromagnetic ion cyclotron (EMIC) waves detected during 10 years (2001–2010) of Cluster observations. In the first paper, an analysis of EMIC wave properties (i.e., wave power, polarization, normal angle, and wave propagation angle) is presented in both the magnetic latitude (MLAT)-distance as well as magnetic local time (MLT)-L frames. In addition, this paper focuses on the distribution of EMIC wave-associated plasma conditions as well as two EMIC wave generation proxies (the electron plasma frequency to gyrofrequency ratio proxy and the linear theory proxy) in these same frames. Based on the distributions of hot H + anisotropy, electron and hot H+ density measurements, hot H + parallel plasma beta, and the calculated wave generation proxies, three source regions of EMIC waves appear to exist: (1) the well-known overlap between cold plasmaspheric or plume populations with hot anisotropic ring current populations in the postnoon to dusk MLT region; (2) regions all along the dayside magnetosphere at high L shells related to dayside magnetospheric compression and drift shell splitting; and (3) off-equator regions possibly associated with the Shabansky orbits in the dayside magnetosphere.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Statistical properties of the radiation belt seed population

Here, we present a statistical analysis of phase space density data from the first 26 months of the Van Allen Probes mission. In particular, we investigate the relationship between the tens and hundreds of keV seed electrons and >1 MeV core radiation belt electron population. Using a cross-correlation analysis, we find that the seed and core populations are well correlated with a coefficient of ≈0.73 with a time lag of 10–15 h. We present evidence of a seed population threshold that is necessary for subsequent acceleration. The depth of penetration of the seed population determines the inner boundary of the acceleration process. However, we show that an enhanced seed population alone is not enough to produce acceleration in the higher energies, implying that the seed population of hundreds of keV electrons is only one of several conditions required for MeV electron radiation belt acceleration.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

A statistical approach for isolating fossil fuel emissions in atmospheric inverse problems

We study independent verification and quantification of fossil fuel (FF) emissions that constitutes a considerable scientific challenge. By coupling atmospheric observations of CO 2 with models of atmospheric transport, inverse models offer the possibility of overcoming this challenge. However, disaggregating the biospheric and FF flux components of terrestrial fluxes from CO 2 concentration measurements has proven to be difficult, due to observational and modeling limitations. In this study, we propose a statistical inverse modeling scheme for disaggregating winter time fluxes on the basis of their unique error covariances and covariates, where these covariances and covariates are representative of the underlying processes affecting FF and biospheric fluxes. The application of the method is demonstrated with one synthetic and two real data prototypical inversions by using in situ CO 2 measurements over North America. Also, inversions are performed only for the month of January, as predominance of biospheric CO 2 signal relative to FF CO 2 signal and observational limitations preclude disaggregation of the fluxes in other months. The quality of disaggregation is assessed primarily through examination of a posteriori covariance between disaggregated FF and biospheric fluxes at regional scales. Findings indicate that the proposed method is able to robustly disaggregate fluxes regionally at monthly temporal resolution with a posteriori cross covariance lower than 0.15 µmol m -2 s -1 between FF and biospheric fluxes. Error covariance models and covariates based on temporally varying FF inventory data provide a more robust disaggregation over static proxies (e.g., nightlight intensity and population density). However, the synthetic data case study shows that disaggregation is possible even in absence of detailed temporally varying FF inventory data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Resolution dependence of precipitation statistical fidelity in hindcast simulations

This article is a U.S. Government work and is in the public domain in the USA. Numerous studies have shown that atmospheric models with high horizontal resolution better represent the physics and statistics of precipitation in climate models. While it is abundantly clear from these studies that high-resolution increases the rate of extreme precipitation, it is not clear whether these added extreme events are “realistic”; whether they occur in simulations in response to the same forcings that drive similar events in reality. In order to understand whether increasing horizontal resolution results in improved model fidelity, a hindcast-based, multiresolution experimental design has been conceived and implemented: the InitiaLIzed-ensemble, Analyze, and Develop (ILIAD) framework. The ILIAD framework allows direct comparison between observed and simulated weather events across multiple resolutions and assessment of the degree to which increased resolution improves the fidelity of extremes. Analysis of 5 years of daily 5 day hindcasts with the Community Earth System Model at horizontal resolutions of 220, 110, and 28 km shows that: (1) these hindcasts reproduce the resolution-dependent increase of extreme precipitation that has been identified in longer-duration simulations, (2) the correspondence between simulated and observed extreme precipitation improves as resolution increases; and (3) this increase in extremes and precipitation fidelity comes entirely from resolved-scale precipitation. Evidence is presented that this resolution-dependent increase in precipitation intensity can be explained by the theory of Rauscher et al. (), which states that precipitation intensifies at high resolution due to an interaction between the emergent scaling (spectral) properties of the wind field and the constraint of fluid continuity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Radiation belt seed population and its association with the relativistic electron dynamics: A statistical study: Radiation Belt Seed Population

Using the Van Allen Probes data, we study the radiation belt seed population and it associated with the relativistic electron dynamics during 74 geomagnetic storm events. Based on the flux changes of 1 MeV electrons before and after the storm peak, these storm events are divided into two groups of “non-preconditioned” and “preconditioned”. The statistical study shows that the storm intensity is of significant importance for the distribution of the seed population (336 keV electrons) in the outer radiation belt. However, substorm intensity can also be important to the evolution of the seed population for some geomagnetic storm events. For non-preconditioned storm events, the correlation between the peak fluxes and their L-shell locations of the seed population and relativistic electrons (592 keV, 1.0 MeV, 1.8 MeV, and 2.1 MeV) is consistent with the energy-dependent dynamic processes in the outer radiation belt. For preconditioned storm events, the correlation between the features of the seed population and relativistic electrons is not fully consistent with the energy-dependent processes. It is suggested that the good correlation between the radiation belt seed population and ≤1.0 MeV electrons contributes to the prediction of the evolution of ≤1.0 MeV electrons in the Earth’s outer radiation belt during periods of geomagnetic storms.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Direct Breakthrough Curve Prediction From Statistics of Heterogeneous Conductivity Fields

In this paper, we present a methodology to predict the shape of solute breakthrough curves in heterogeneous aquifers at early times and/or under high degrees of heterogeneity, both cases in which the classical macrodispersion theory may not be applicable. The methodology relies on the observation that breakthrough curves in heterogeneous media are generally well described by lognormal distributions, and mean breakthrough times can be predicted analytically. The log-variance of solute arrival is thus sufficient to completely specify the breakthrough curves, and this is calibrated as a function of aquifer heterogeneity and dimensionless distance from a source plane by means of Monte Carlo analysis and statistical regression. Using the ensemble of simulated groundwater flow and solute transport realizations employed to calibrate the predictive regression, reliability estimates for the prediction are also developed. Additional theoretical contributions include heuristics for the time until an effective macrodispersion coefficient becomes applicable, and also an expression for its magnitude that applies in highly heterogeneous systems. Finally, it is seen that the results here represent a way to derive continuous time random walk transition distributions from physical considerations rather than from empirical field calibration.

58 GEOSCIENCES↗