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At least 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Case Studies for the Statistical Design of Experiments Applied to Powered Rotor Wind Tunnel Tests

The application of statistical Design of Experiments (DOE) to helicopter wind tunnel testing was explored during two powered rotor wind tunnel entries during the summers of 2012 and 2013. These tests were performed jointly by the U.S. Army Aviation Development Directorate Joint Research Program Office and NASA Rotary Wing Project Office, currently the Revolutionary Vertical Lift Project, at NASA Langley Research Center located in Hampton, Virginia. Both entries were conducted in the 14- by 22-Foot Subsonic Tunnel with a small portion of the overall tests devoted to developing case studies of the DOE approach as it applies to powered rotor testing. A 16-47 times reduction in the number of data points required was estimated by comparing the DOE approach to conventional testing methods. The average error for the DOE surface response model for the OH-58F test was 0.95 percent and 4.06 percent for drag and download, respectively. The DOE surface response model of the Active Flow Control test captured the drag within 4.1 percent of measured data. The operational differences between the two testing approaches are identified, but did not prevent the safe operation of the powered rotor model throughout the DOE test matrices.

Overmeyer, Austin D.↗
NASA NTRS2014

Data Analysis & Statistical Methods for Command File Errors

This paper explains current work on modeling for managing the risk of command file errors. It is focused on analyzing actual data from a JPL spaceflight mission to build models for evaluating and predicting error rates as a function of several key variables. We constructed a rich dataset by considering the number of errors, the number of files radiated, including the number commands and blocks in each file, as well as subjective estimates of workload and operational novelty. We have assessed these data using different curve fitting and distribution fitting techniques, such as multiple regression analysis, and maximum likelihood estimation to see how much of the variability in the error rates can be explained with these. We have also used goodness of fit testing strategies and principal component analysis to further assess our data. Finally, we constructed a model of expected error rates based on the what these statistics bore out as critical drivers to the error rate. This model allows project management to evaluate the error rate against a theoretically expected rate as well as anticipate future error rates.

Correlation Analysis↗
NASA NTRS2016

Flat Plate Wake Velocity Statistics Obtained With Circular And Elliptic Trailing Edges

The near wake of a flat plate with circular and elliptic trailing edges is investigated with data from direct numerical simulations. The plate length and thickness are the same in both cases. The separating boundary layers are turbulent and statistically identical. Therefore the wake is symmetric in the two cases. The emphasis in this study is on a comparison of the wake-distributions of velocity components, normal intensity and fluctuating shear stress obtained in the two cases.

CFD↗
NASA NTRS2016

A Statistical Analysis of the Accuracy of the Digitized Magnitudes of Photometric Plates on the Timescale of Decades with an Application to the Century-Long Light Curve of KIC 8462852

We present a statistical analysis of the accuracy of the digitized magnitudes of photometric plates on the timescale of decades. In our examination of archival Johnson B photometry from the Harvard DASCH archive, we find a median rt mean square scatter of light curves of the order of 0.15 magnitude over the range B approximately equal to 9-17 for all calibrations. Slight underlying systematics (trends or flux discontinuities) are on a level of less than or equal to 0.2 magnitudes per century (1889–1990) for the majority of constant stars. These historic data can be unambiguously used for processes that happen on scales of magnitudes, and need to be carefully examined in cases approaching the noise floor. The characterization of these limits in photometric stability may guide future studies in their use of plate archives. We explain these limitations for the example case of KIC 8462852, which has been claimed to dim by 0.16 magnitudes per century, and show that this trend cannot be considered as significant.

digitized magnitudes of photometric plates↗
NASA NTRS2016

Statistical Analysis of Deflation in Covariance and Resultant Pc Values for AQUA, AURA and TERRA

This presentation will display statistical analysis performed for raw conjunction CDMs received for the EOS Aqua, Aura and Terra satellites within the period of February 2015 through July 2016. The analysis performed indicates a discernable deflation in covariance calculated at the JSpOC after the utilization of the dynamic drag consider parameter was implemented operationally in May 2015. As a result, the overall diminution in the conjunction plane intersection of the primary and secondary objects appears to be leading to reduced probability of collision (Pc) values for these conjunction events. This presentation also displays evidence for this theory with analysis of Pc trending plots using data calculated by the SpaceNav CRMS system.

raw conjunction↗
NASA NTRS2017

Probabilistic Forecasting of Surface Ozone with a Novel Statistical Approach

The recent change in the Environmental Protection Agency's surface ozone regulation, lowering the surface ozone daily maximum 8-h average (MDA8) exceedance threshold from 75 to 70 ppbv, poses significant challenges to U.S. air quality (AQ) forecasters responsible for ozone MDA8 forecasts. The forecasters, supplied by only a few AQ model products, end up relying heavily on self-developed tools. To help U.S. AQ forecasters, this study explores a surface ozone MDA8 forecasting tool that is based solely on statistical methods and standard meteorological variables from the numerical weather prediction (NWP) models. The model combines the self-organizing map (SOM), which is a clustering technique, with a step wise weighted quadratic regression using meteorological variables as predictors for ozone MDA8. The SOM method identifies different weather regimes, to distinguish between various modes of ozone variability, and groups them according to similarity. In this way, when a regression is developed for a specific regime, data from the other regimes are also used, with weights that are based on their similarity to this specific regime. This approach, regression in SOM (REGiS), yields a distinct model for each regime taking into account both the training cases for that regime and other similar training cases. To produce probabilistic MDA8 ozone forecasts, REGiS weighs and combines all of the developed regression models on the basis of the weather patterns predicted by an NWP model. REGiS is evaluated over the San Joaquin Valley in California and the northeastern plains of Colorado. The results suggest that the model performs best when trained and adjusted separately for an individual AQ station and its corresponding meteorological site.

Ozone variables↗
NASA NTRS2016

Global Statistical Maps of Extreme-Event Magnetic Observatory 1 Min First Differences in Horizontal Intensity

Analysis is made of the long-term statistics of three different measures of ground level, storm time geomagnetic activity: instantaneous 1 min first differences in horizontal intensity (delta)Bh, the root-mean-square of 10 consecutive 1 min differences S, and the ramp change R over 10 min. Geomagnetic latitude maps of the cumulative exceedances of these three quantities are constructed, giving the threshold(nTmin) for which activity within a 24 h period can be expected to occur once per year, decade, and century. Specifically, at geomagnetic 55deg, we estimate once-per-century (delta)Bh, S, and R exceedances and a site-to-site,proportional, 1 standard deviation range [1(sigma), lower and upper] to be, respectively, 1000, [690, 1450]; 500,[350, 720]; and 200, [140, 280] nTmin. At 40deg, we estimate once-per-century (delta)Bh, S, and R exceedances and1(sigma) values to be 200, [140, 290]; 100, [70, 140]; and 40, [30, 60] nTmin.

Love, Jeffrey J.↗
NASA NTRS2016

Statistical Correlation of Low-Altitude ENA Emissions with Geomagnetic Activity from IMAGE MENA Observations

Plasma sheet particles transported Earthward during times of active magnetospheric convection can interact with exospheric/thermospheric neutrals through charge exchange. The resulting Energetic Neutral Atoms (ENAs) are free to leave the influence of the magnetosphere and can be remotely detected. ENAs associated with low-altitude (300-800 km) ion precipitation in the high-latitude atmosphere/ionosphere are termed low-altitude emissions (LAEs). Remotely observed LAEs are highly nonisotropic in velocity space such that the pitch angle distribution at the time of charge exchange is near 90deg. The Geomagnetic Emission Cone of LAEs can be mapped spatially, showing where proton energy is deposited during times of varying geomagnetic activity. In this study we present a statistical look at the correlation between LAE flux (intensity and location) and geomagnetic activity. The LAE data are from the MENA imager on the IMAGE satellite over the declining phase of solar cycle 23 (2000-2005). The SYM-H, AE, and Kp indices are used to describe geomagnetic activity. The goal of the study is to evaluate properties of LAEs in ENA images and determine if those images can be used to infer properties of ion precipitation. Results indicate a general positive correlation to LAE flux for all three indices, with the SYM-H showing the greatest sensitivity. The magnetic local time distribution of LAEs is centered about midnight and spreads with increasing activity. The invariant latitude for all indices has a slightly negative correlation. The combined results indicate LAE behavior similar to that of ion precipitation.

Mackler, D. A.↗
NASA NTRS2016

Prompt Injections of Highly Relativistic Electrons Induced by Interplanetary Shocks: A Statistical Study of Van Allen Probes Observations

We conduct a statistical study on the sudden response of outer radiation belt electrons due to interplanetary (IP) shocks during the Van Allen Probes era, i.e., 2012 to 2015. Data from the Relativistic Electron-Proton Telescope instrument on board Van Allen Probes are used to investigate the highly relativistic electron response (E greater than 1.8 MeV) within the first few minutes after shock impact. We investigate the relationship of IP shock parameters, such as Mach number, with the highly relativistic electron response, including spectral properties and radial location of the shock-induced injection. We find that the driving solar wind structure of the shock does not affect occurrence for enhancement events, 25% of IP shocks are associated with prompt energization, and 14% are associated with MeV electron depletion. Parameters that represent IP shock strength are found to correlate best with highest levels of energization, suggesting that shock strength may play a key role in the severity of the enhancements. However, not every shock results in an enhancement, indicating that magnetospheric preconditioning may be required.

Schiller, Q.↗
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 NTRS2017

Statistical Approaches for the Definition of Landslide Rainfall Thresholds and their Uncertainty Using Rain Gauge and Satellite Data

Models for forecasting rainfall-induced landslides are mostly based on the identification of empirical rainfall thresholds obtained exploiting rain gauge data. Despite their increased availability, satellite rainfall estimates are scarcely used for this purpose. Satellite data should be useful in ungauged and remote areas, or should provide a significant spatial and temporal reference in gauged areas. In this paper, the analysis of the reliability of rainfall thresholds based on rainfall remote sensed and rain gauge data for the prediction of landslide occurrence is carried out. To date, the estimation of the uncertainty associated with the empirical rainfall thresholds is mostly based on a bootstrap resampling of the rainfall duration and the cumulated event rainfall pairs (D,E) characterizing rainfall events responsible for past failures. This estimation does not consider the measurement uncertainty associated with D and E. In the paper, we propose (i) a new automated procedure to reconstruct ED conditions responsible for the landslide triggering and their uncertainties, and (ii) three new methods to identify rainfall threshold for the possible landslide occurrence, exploiting rain gauge and satellite data. In particular, the proposed methods are based on Least Square (LS), Quantile Regression (QR) and Nonlinear Least Square (NLS) statistical approaches. We applied the new procedure and methods to define empirical rainfall thresholds and their associated uncertainties in the Umbria region (central Italy) using both rain-gauge measurements and satellite estimates. We finally validated the thresholds and tested the effectiveness of the different threshold definition methods with independent landslide information. The NLS method among the others performed better in calculating thresholds in the full range of rainfall durations. We found that the thresholds obtained from satellite data are lower than those obtained from rain gauge measurements. This is in agreement with the literature, where satellite rainfall data underestimate the 'ground' rainfall registered by rain gauges.

landslide prediction↗
NASA NTRS2018

The Statistical Properties of Solar Wind Temperature Parameters Near 1 Au

We present a long-duration (approx. 10 yr) statistical analysis of the temperatures, plasma betas, and temperature ratios for the electron, proton, and alpha-particle populations observed by the Wind spacecraft near 1 au. The mean(median) scalar temperatures are T(sub e)(sub tot) = 12.2(11.9) eV, T(sub p)(sub tot) = 12.7(8.6) eV, and T(sub a)(sub tot) = 23.9(10.8) eV. The mean(median) total plasma betas are Beta(sub e)(sub tot) = 2.31(1.09), Beta(sub p)(sub tot) = 1.79(1.05), and Beta(sub a)(sub tot) = 0.17(0.05). The mean(median) temperature ratios are (T(sub e)/T(sub p))(sub tot) = 1.64(1.27), (T(sub e)/T(sub a))(sub tot) = 1.24(0.82), and (T(sub a)/T(sub p))(sub tot) = 2.50(1.94). We also examined these parameters during time intervals that exclude interplanetary (IP) shocks, times within the magnetic obstacles (MOs) of interplanetary coronal mass ejections (ICMEs), and times that exclude MOs. The only times that show significant alterations to any of the parameters examined are those during MOs. In fact, the only parameter that does not show a significant change during MOs is the electron temperature. Although each parameter shows a broad range of values, the vast majority are near the median. We also compute particle–particle collision rates and compare to effective wave–particle collision rates. We find that, for reasonable assumptions of wave amplitude and occurrence rates, the effect of wave–particle interactions on the plasma is equal to or greater than the effect of Coulomb collisions. Thus, wave–particle interactions should not be neglected when modeling the solar wind.

Wilson, Lynn B., III↗
NASA NTRS2018

Increasing the Statistical Rigor of Cross-Species Differential Expression Analysis

Microgravity inflicts substantial, but undercharacterized, pressure on organisms that induces metabolic responses such as increased microbial virulence and antibiotic resistance, altered organ weights in developing rats, and loss of bone tissue in astronauts. Numerous studies have analyzed the effects of microgravity on specific organisms, tissues, or test conditions, but these projects are necessarily limited by the small sample size of space research. Increasing the sample size of spaceflight studies is non-trivial; however, pooling data from numerous studies can greatly increase the statistical rigor of comparative analyses. The GeneLab houses datasets from 73 spaceflight studies that performed transcription profiling assays. These data encompass a diverse array of organisms ranging from Escherichia coli to Mus musculus to Homo sapiens and comprise studies analyzing ionizing radiation, mammalian pregnancy, etc. Collectively, the GeneLab database contains a large quantity of transcription assays and RNA sequence data analyzing Differential Gene Expression (DGE) between microand normogravity. Xspecies, a cross-species analysis method for DGE developed by Kristiansson, et al. in 2012, identifies homologous genes between species that are universally up- or downregulated in response to test conditions. Previous work by an intern at GeneLab applied Xspecies to 19 datasets containing seven different species and identified 14 homologous groups differentially expressed under spaceflight conditions including several heat shock proteins and cytoskeletal components. Unfortunately, these results may be biased by the disproportionate number of studies on Arabidopsis thaliana (5) and Mus musculus (6) and the results are not normalized by evolutionary distances. Here, we present modifications to the Xspecies algorithm that permits incorporation of multi-omic data and normalizes data for effect size, directionality, and evolutionary distances. We then apply this algorithm to all currently available GeneLab studies

Xspecies↗
NASA NTRS2018

Combining Fractional Calorimetry with Statistical Methods to Characterize Thermal Runaway

Thermal management systems designed to handle the impacts of thermal runaway (TR) are key to safe operation of lithium-ion (Li-ion) batteries. Critical factors for optimizing these systems include the total energy released and the fraction of the total energy that is released through the cell casing versus through the ejecta material. A unique calorimeter, designed to characterize said factors, was utilized to examine the TR behavior of a variety of 18650-format Li-ion cells. Statistical methods were implemented to interpret the data.

Walker, William↗
NASA NTRS2018

Coupling Fractional Thermal Runaway Calorimetry (FTRC) Results with Statistical Analysis Methods

Important factors to consider when optimizing Lithium-ion (Li-ion) battery thermal management systems, from a battery safety perspective, include the total energy released during a single cell thermal runaway (TR) event and the fraction of the total energy that is released through the cell casing versus through the ejecta material. A fractional thermal runaway calorimeter (FTRC) was used to examine the TR behavior of the following 18650-format Li-ion cells: (1) Molicel 18650-J, (2) LG 18650-HG2, (3) Samsung 18650-30Q, (4) 3.35 Ah LG 18650 test cell, (5) Sony 18650-VC7, and (6) LG 18650-MJ1. These cells were intentionally selected to represent a variety of manufacturers, chemistries, capacities, and safety features. Because of the large number of random and non-random variables associated with the FTRC results, a linear regression model, developed using engineering statistical methods, was utilized to provide final interpretation of the TR behavior for each cell type and design variable combination.

Walker, William↗
NASA NTRS1962

Application of Statistical Filter Theory to the Optimal Estimation of Position and Velocity on Board a Circumlunar Vehicle

Statistical filter theory is employed to develop a method for determining the best possible estimate of the position and velocity of a space vehicle in the midcourse phase of flight. Results of a computer simulation are given to illustrate the performance attainable. An on-board system is visualized in which the source of information is an arbitrary sequence of observations of space angles, corrupted by measurement errors. The scheme is in effect a dynamical time-varying filter, implemented by a digital computer, which processes the incoming data to compute an up-to-date optimal estimate of position and velocity.

Smith, Gerald L.↗
NASA NTRS2019

A Global Climatology of Extratropical Transition Part II: Statistical Performance of the Cyclone Phase Space

This study analyzes the differences between an objective, automated identification of tropical cyclones (TCs) that undergo extratropical transition (ET), and the designation of ET determined subjectively by human forecasters in best-track data in all basins globally. The objective identification of ET is based on the cyclone phase space (CPS), calculated from the Japanese 55-year Reanalysis (JRA-55) or the ECMWF Interim Reanalysis (ERA-Interim). The resulting classification into “ET storms” and “non-ET storms” underlies the global climatology of ET presented in Part I of this study. Here, the authors investigate how well the CPS classifications agree with those in the best-track records calculated from JRA-55 or from ERA-Interim data. According to F1 scores and Matthews correlation coefficients (MCCs), the classification of ET storms in the CPS agrees best with the best-track classification in the Western North Pacific (MCC > 0.7) and the North Atlantic (MCC > 0.5). In other basins, the correlation between the CPS classification and the best-track classification is only slightly higher than that of a random classification. The JRA-55 classification achieves higher performance scores than does the ERA-Interim classification, and the differences are statistically significant in all basins. The lower performance of ERA-Interim is mainly due to a higher false alarm rate, particularly in the Eastern North Pacific. Overall, the results show that while the CPS-based classifications are good enough to be useful for many purposes, there is almost certainly room for improvement – in the representation of the storms in reanalyses, in our objective metrics of ET, and in our scientific understanding of the ET process.

Melanie Bieli↗
NASA NTRS2019

Statistical Process Control and Capability Study on the Water Content Measurements in NASA Glenn's Icing Research Tunnel

The Icing Research Tunnel (IRT) at NASA Glenn Research Center follows the recommended practice for icing tunnel calibration outlined in SAE's ARP5905 document. 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 in the specifications presented to customers that the variation is within +/- 10% of the calibrated, target measurement. With recent measurements and instrumentation errors, a more thorough assessment of error source was desired. By constructing statistical process control charts, the ability to determine how the instrument varies in the short term, mid term, and long term was gained. The control charts offer a view of instrument error, facility error, or installation changes. It was discovered that there was a shift from target to mean baseline thus leading to the study of the overall capability indices of the liquid water content measuring instrument to perform within specifications defined in the IRT. This presentation describes data processing procedures for the Multi-Element Sensor in the IRT, including collision efficiency corrections, canonical correlation analysis, Chauvenet's Criterion for rejection of data, distribution check of data, and mean, median and mode for construction of control charts. Further data is presented to describe the repeatability of the IRT with the Multi-Element Sensor and the ability to maintain a stable process for the defined calibration schedule.

Timko, Emily N.↗