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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

An analysis of penetration and ricochet phenomena in oblique hypervelocity impact

An experimental investigation of phenomena associated with the oblique hypervelocity impact of spherical projectiles on multisheet aluminum structures is described. A model that can be employed in the design of meteoroid and space debris protection systems for space structures is developed. The model consists of equations that relate crater and perforation damage of a multisheet structure to parameters such as projectile size, impact velocity, and trajectory obliquity. The equations are obtained through a regression analysis of oblique hypervelocity impact test data. This data shows that the response of a multisheet structure to oblique impact is significantly different from its response to normal hypervelocity impact. It was found that obliquely incident projectiles produce ricochet debris that can severely damage panels or instrumentation located on the exterior of a space structure. Obliquity effects of high-speed impact must, therefore, be considered in the design of any structure exposed to the meteoroid and space debris environment.

Schonberg, William P.↗
NASA NTRS1988

Analysis of oblique hypervelocity impact phenomena

This paper describes the results of an experimental investigation of phenomena associated with the oblique hypervelocity impact of spherical projectiles on multisheet aluminum structures. A model that can be employed in the design of meteoroid and space debris protection systems for space structures is developed. The model consists of equations that relate crater and perforation damage of a multisheet structure to parameters such as projectile size, impact velocity, and trajectory obliquity. The equations are obtained through a regression analysis of oblique hypervelocity impact test data. This data shows that the response of a multisheet structure to oblique impact is significantly different from its response to normal hypervelocity impact. It was found that obliquely incident projectiles produce ricochet debris that can severely damage panels or instrumentation located on the exterior of a space structure. Obliquity effects of high-speed impact must, therefore, be considered in the design of any structure exposed to a meteoroid or space debris environement.

Schonberg, William P.↗
NASA NTRS1989

Penetration and ricochet phenomena in oblique hypervelocity impact

An experimental investigation of phenomena associated with the oblique hypervelocity impact of spherical projectile on multisheet aluminum structures is described. A model that can be employed in the design of meteoroid and space debris protection systems for space structures is developed. The model consists of equations that relate crater and perforation damage of a multisheet structure to parameters such as projectile size, impact velocity, and trajectory obliquity. The equations are obtained through a regression analysis of oblique hypervelocity impact test data. This data shows that the response of a multisheet structure to oblique impact is significantly different from its response to normal hypervelocity impact. It was found that obliquely incident projectiles produce ricochet debris that can severely damage panels or instrumentation located on the exterior of a space structure. Obliquity effects of high-speed impact must, therefore, be considered in the design of any structure exposed to the meteoroid and space debris environment.

Schonberg, William P.↗
NASA NTRS1998

Experiments to Determine Whether Recursive Partitioning (CART) or an Artificial Neural Network Overcomes Theoretical Limitations of Cox Proportional Hazards Regression

New computationally intensive tools for medical survival analyses include recursive partitioning (also called CART) and artificial neural networks. A challenge that remains is to better understand the behavior of these techniques in effort to know when they will be effective tools. Theoretically they may overcome limitations of the traditional multivariable survival technique, the Cox proportional hazards regression model. Experiments were designed to test whether the new tools would, in practice, overcome these limitations. Two datasets in which theory suggests CART and the neural network should outperform the Cox model were selected. The first was a published leukemia dataset manipulated to have a strong interaction that CART should detect. The second was a published cirrhosis dataset with pronounced nonlinear effects that a neural network should fit. Repeated sampling of 50 training and testing subsets was applied to each technique. The concordance index C was calculated as a measure of predictive accuracy by each technique on the testing dataset. In the interaction dataset, CART outperformed Cox (P less than 0.05) with a C improvement of 0.1 (95% Cl, 0.08 to 0.12). In the nonlinear dataset, the neural network outperformed the Cox model (P less than 0.05), but by a very slight amount (0.015). As predicted by theory, CART and the neural network were able to overcome limitations of the Cox model. Experiments like these are important to increase our understanding of when one of these new techniques will outperform the standard Cox model. Further research is necessary to predict which technique will do best a priori and to assess the magnitude of superiority.

Kattan, Michael W.↗
NASA NTRS2023

Improving Tornado Casualty Predictions in the US With Population Exposure Data and A Modified Social Vulnerability Index

Tornadoes are frequent and widespread events that often account for hundreds of injuries and fatalities, and millions of dollars in damages. Multiple studies have analyzed tornado climatology and associated exposure; however, fewer have focused on predicting fatalities and injuries by coupling geospatial data on tornado characteristics and underlying social and economic vulnerability. In this study, we test the ability of negative binomial regression models to predict tornado-induced injuries and fatalities by coupling data on physical characteristics of tornadoes, exposure of populations, and underlying social vulnerability. We also present a modified spatially weighted social vulnerability index SVI* wt . We used 10-year (2005-2014) tornado data over the continental United States for this analysis. The results of this study indicate that the tornado length, magnitude and nocturnality seem to be the major hazard-related indicators of fatalities (McFadden’s Pseudo- R 2 ranged from 0.01-0.12). Population exposure and SVI* wt are positive and statistically significant in predicting tornado related fatalities and injuries (Pseudo R 2 of 0.11-0.18). Although combining SVI* wt with hazard variables does not substantially improve model fit when compared to adding population exposure, combining SVI* wt , hazard and exposure results in better predictions of both injuries and fatalities (Pseudo R 2 of 0.17) and is also an improvement on previous similar studies.

disaster↗
NASA NTRS1987

Soil moisture estimation using GOES-VISSR infrared data - A case study with a simple statistical method

Five days of clear sky observations of Kansas and Nebraska are used to examine the statistical relationship between soil moisture and infrared surface temperature observations taken from a geosynchronous satellite. Linear regression is used to relate soil moisture to surface temperature and other variables that represent wind speed, vegetation cover, and low-level temperature advection. Results show good agreement between estimated and observed soil moisture features on each of the 5 days. The average coefficient of determination for five pseudoindependent tests in which the test day is held out of the regression is 0.71. It is shown that a depletion coefficient of 0.92, when used to compute antecedent precipitation index (API), produces the best correlation between API and soil moisture as inferred from GOES thermal infrared data. By averaging daily predicted values over the 5-day rain-free case study period, 92 percent of the variance of the morning surface temperature change is explained by a simple multiple linear regression with all independent variables, or, alternatively, 85 percent of the observed variance in API is explained. It is concluded that this approach can distinguish at least four classes of soil wetness, but the necessity for measurement of surface advection may limit its usefulness in remote areas.

Wetzel, Peter J.↗
NASA NTRS2003

Experiments with Test Case Generation and Runtime Analysis

Software testing is typically an ad hoc process where human testers manually write many test inputs and expected test results, perhaps automating their execution in a regression suite. This process is cumbersome and costly. This paper reports preliminary results on an approach to further automate this process. The approach consists of combining automated test case generation based on systematically exploring the program's input domain, with runtime analysis, where execution traces are monitored and verified against temporal logic specifications, or analyzed using advanced algorithms for detecting concurrency errors such as data races and deadlocks. The approach suggests to generate specifications dynamically per input instance rather than statically once-and-for-all. The paper describes experiments with variants of this approach in the context of two examples, a planetary rover controller and a space craft fault protection system.

Artho, Cyrille↗
NASA NTRS1984

Results of the joint NASA/NOAA AMTS/HIRS2 sounding simulation test

The relative accuracies of atmospheric temperature profiles retrieved from HIRS2, the current operational infra-red temperature sounder, and AMTS, a proposed advanced high-spectral resolution infra-red sounder were compared. The sounding simulation test compared retrievals generated by GLAS, using their physical retrieval algorithm, and NESDIS, using their operational statistical regression algorithm, for both instruments under clear and cloudy conditions. Test results for both conditions are summarized in tables showing RMS temperature errors for 18 tropospheric layers, 4 stratospheric layers, and surface skin temperature. The improvement of the AMTS instrument over HIRS2, particularly for cloudy conditions is demonstrated. The GLAS retrievals are more accurate than the operational NESDIS retrieval, especially with increasing cloud cover.

Susskind, J.↗
NASA NTRS2004

Strain-Gage Loads Calibration Parametric Study

This paper documents a parametric study of various aircraft wing-load test features that affect the quality of the resultant derived shear, bending-moment, and torque strain-gage load equations. The effect of the following on derived strain-gage equation accuracy are compared: single-point loading compared with distributed loading, variation in applied test load magnitude, number of applied load cases, and wing-box-only compared with control-surface loading. The subject of this study is an extensive wing-load calibration test of the Active Aeroelastic Wing F/A-18 airplane. Selected subsets of the available test data were used to derive load equations using the linear regression method. Results show the benefit of distributed loading and the diminishing-return benefits of test load magnitudes and number of load cases. The use of independent check cases as a quality metric for the derived load equations is shown to overcome blind extrapolating beyond the load data used to derive the load equations.

Lokos, William A.↗
NASA NTRS1998

T wave alternans as a predictor of recurrent ventricular tachyarrhythmias in ICD recipients: prospective comparison with conventional risk markers

INTRODUCTION: The current standard for arrhythmic risk stratification is electrophysiologic (EP) testing, which, due to its invasive nature, is limited to patients already known to be at high risk. A number of noninvasive tests, such as determination of left ventricular ejection fraction (LVEF) or heart rate variability, have been evaluated as additional risk stratifiers. Microvolt T wave alternans (TWA) is a promising new risk marker. Prospective evaluation of noninvasive risk markers in low- or moderate-risk populations requires studies involving very large numbers of patients, and in such studies, documentation of the occurrence of ventricular tachyarrhythmias is difficult. In the present study, we identified a high-risk population, recipients of an implantable cardioverter defibrillator (ICD), and prospectively compared microvolt TWA with invasive EP testing and other risk markers with respect to their ability to predict recurrence of ventricular tachyarrhythmias as documented by ICD electrograms. METHODS AND RESULTS: Ninety-five patients with a history of ventricular tachyarrhythmias undergoing implantation of an ICD underwent EP testing, assessment of TWA, as well as determination of LVEF, baroreflex sensitivity, signal-averaged ECG, analysis of 24-hour Holter monitoring, and QT dispersion from the 12-lead surface ECG. The endpoint of the study was first appropriate ICD therapy for electrogram-documented ventricular fibrillation or tachycardia during follow-up. Kaplan-Meier survival analysis revealed that TWA (P < 0.006) and LVEF (P < 0.04) were the only significant univariate risk stratifiers. EP testing was not statistically significant (P < 0.2). Multivariate Cox regression analysis revealed that TWA was the only statistically significant independent risk factor. CONCLUSIONS: Measurement of microvolt TWA compared favorably with both invasive EP testing and other currently used noninvasive risk assessment methods in predicting recurrence of ventricular tachyarrhythmias in ICD recipients. This study suggests that TWA might also be a powerful tool for risk stratification in low- or moderate-risk patients, and needs to be prospectively evaluated in such populations.

Non-NASA Center↗
NASA NTRS1986

Satellite rainfall retrieval by logistic regression

The potential use of logistic regression in rainfall estimation from satellite measurements is investigated. Satellite measurements provide covariate information in terms of radiances from different remote sensors.The logistic regression technique can effectively accommodate many covariates and test their significance in the estimation. The outcome from the logistical model is the probability that the rainrate of a satellite pixel is above a certain threshold. By varying the thresholds, a rainrate histogram can be obtained, from which the mean and the variant can be estimated. A logistical model is developed and applied to rainfall data collected during GATE, using as covariates the fractional rain area and a radiance measurement which is deduced from a microwave temperature-rainrate relation. It is demonstrated that the fractional rain area is an important covariate in the model, consistent with the use of the so-called Area Time Integral in estimating total rain volume in other studies. To calibrate the logistical model, simulated rain fields generated by rainfield models with prescribed parameters are needed. A stringent test of the logistical model is its ability to recover the prescribed parameters of simulated rain fields. A rain field simulation model which preserves the fractional rain area and lognormality of rainrates as found in GATE is developed. A stochastic regression model of branching and immigration whose solutions are lognormally distributed in some asymptotic limits has also been developed.

Chiu, Long S.↗
NASA NTRS1993

Atmospheric moisture fields derived by satellite observations over the tropical Pacific Ocean

Values of precipitable water are retrieved over the tropical and subtropical Pacific Ocean from TOVS infrared and microwave channel brightness temperature and OLR observations by means of stepwise linear regression. The most useful temperature and moisture sensing channels are pre-selected from sensitivity tests of a radiative transfer model. Numerous models are developed and tested against collocated radiosonde observations and Nimbus-7 SMMR precipitable water estimates. For RAOB comparisons, the best estimator used 15 TOVS predictors and captured 71.1 deg percent of the variance (+0.62 g/sq cm standard error) for column precipitable water; for precipitable water of 700-500 mb bulk layer, these values were 71.7 percent and +/- 0.17 g/sq cm. Little skill of estimated precipitable water was obtained for moisture above 500 mb. Regressions were less skillful against SMMR, unless collocation parameters were tightly controlled; SMMR was less acceptable than RAOB's because of observational drift and errors. Generally, the most skillful predictors were boundary layer brightness temperatures of TOVS channels and satellite estimated stability indices. 'Moisture channels' were hardly useful except for estimating middle and upper tropospheric moisture. Additional regression models were constructed testing the sensitivity to different observational and meteorological characteristics. Models which used some in situ observations surface observations or stabilities calculated from RAOB, were the most successful. The best of these explained 87.5 percent of the variance but the regression selected almost no TOVS channels, relying instead on conventional RAOB and surface observations. A set of four regression models were developed, stratifying atmospheric characteristics on the basis of collocated OLR values. These models improved the variance explained by 5.0 percent; the model associated with the highest OLR values (275 W/sq m less than or equal to OLR; that is, no cloud) showed only marginal skill. Precipitable water fields were generated from the best TOVS-only model for seven days in January 1983 and compared with SMMR-estimated fields. OLR fields and ECMWF precipitable water analysis. The TOVS regression model compared favorably to the SMMR analysis in amplitudes and features. It revealed more evolving synoptic signal than the ECMWF analysis. In synoptically active regions, it differed with respect to the OLR analysis, primarily because of actual differences in the vertical distribution of water vapor.

Chung, Hyosang↗
NASA NTRS1981

General purpose research rotor

An analytical study, under a NASA contract, is performed on an advanced flight research rotor (four-bladed, 54 ft in diameter, with bearingless rotor retention characteristics) to determine the sensitivity of total rotor characteristics such as vibratory hub loads, rotor horsepower, and blade loads, to parametric variability of the rotor configuration. The sensitivity of the rotor to various combinations of blade planform taper, percent of blade span that is tapered, tip sweep angle, built-in-twist, and torsional frequency is determined for specific configurations by randomly selecting combinations of these parameters. Characteristics of other intermediate rotor configurations are determined by a regression analysis. The results show that a wide range of rotor total performance characteristics can be obtained for a rotor trimmed to the same flight conditions. The regression equations predict total performance of the rotor very well and appear to be a useful analytical tool for rotor design optimization. Figures showing the results of the various tests are given along with a table of the regression coefficients.

Jones, R.↗
NASA NTRS1995

Combustion of solid fuel slabs with gaseous oxygen in a hybrid motor analog

Using a high-pressure, two-dimensional hybrid motor, an experimental investigation was conducted on fundamental processes involved in hybrid rocket combustion. HTPB (Hydroxyl-terminated- Polybutadiene) fuel cross linked with diisocyanate was burned with GOX under various operating conditions. Large amplitude pressure oscillations were encountered in earlier test runs. After identifying the source of instability and decoupling the GOX feed line system and combustion chamber, the pressure oscillations were drastically reduced from +/- 20% of the localized mean pressure to an acceptable range of +/- 1.5%. Embedded fine-wire thermocouples indicated that the surface temperature of the burning fuel was around 1000 K depending upon axial locations and operating conditions. Also, except near the leading-edge region, the subsurface thermal wave profiles in the upstream locations arc thicker than those in the downstream locations since the solid-fuel regression rate, in general, increases with distance along the fuel slab. The recovered solid fuel slabs in the laminar portion of the boundary layer exhibited smooth surfaces, indicating the existence of a liquid melt layer on the burning fuel surface in the upstream region. After the transition section, which displayed distinct transverse striations, the surface roughness pattern became quite random and very pronounced in the downstream turbulent boundary-layer region. Both real time X-ray radiography and ultrasonic pulse-echo techniques were used to determine the instantaneous web thicknesses and instantaneous solid-fuel regression rates over certain portions of the fuel slabs. Globally averaged and axially dependent but time-averaged regression rates were also obtained and presented. Several tests were conducted using, simultaneously, one translucent fuel slab and one fuel slab processed with carbon black powder. The addition of carbon black did not affect the measured regression rates or surface temperatures in comparison to the translucent fuel slabs.

Chiaverini, Martin J.↗
NASA NTRS1995

Combustion of solid fuel slabs with gaseous oxygen in a hybrid motor analog

Using a high-pressure, two-dimensional hybrid motor, an experimental investigation was conducted on fundamental processes involved in hybrid rocket combustion. HTPB (Hydroxyl-terminated Polybutadiene) fuel cross-linked with diisocyanate was burned with gaseous oxygen (GOX) under various operating conditions. Large-amplitude pressure oscillations were encountered in earlier test runs. After identifying the source of instability and decoupling the GOX feed-line system and combustion chamber, the pressure oscillations were drastically reduced from plus or minus 20% of the localized mean pressure to an acceptable range of plus or minus 1.5%. Embedded fine--wire thermocouples indicated that the surface temperature of the burning fuel was around 1000 K depending upon axial locations and operating conditions. Also, except near the leading edge region, the subsurface thermal wave profiles in the upstream locations are thicker than those in the downstream locations since the solid-fuel regression rate, in general, increases with distance along the fuel slab. The recovered solid fuel slabs in the laminar portion of the boundary layer exhibited smooth surfaces, indicating the existence of a liquid melt layer on the burning fuel surface in the upstream region. After the transition section, which displayed distinct transverse striations, the surface roughness pattern became quite random and very pronounced in the downstream turbulent boundary-layer region. Both real-time X-ray radiography and ultrasonic pulse echo techniques were used to determine the instantaneous web thicknesses and instantaneous solid-fuel regression rates over certain portions of the fuel slabs. Globally averaged and axially dependent but time-averaged regression rates were also obtained and presented. Several tests were conducted using, simultaneously, one translucent fuel slab and one fuel slab processed with carbon black powder. The addition of carbon black did not affect the measured regression rates or surface temperatures in comparison to the translucent fuel slabs.

Chiaverini, Martin J.↗
NASA NTRS1990

Health monitoring system for the SSME - Program overview

This paper considers the design of a health management system (HMS) program for enhancement of the safety of SSME operations during ground tests and space missions. The fault detection techniques based on time series, nonlinear regression, and clustering algorithms were developed and were demonstrated based on data from SSME ground test failures. The fault detection algorithms of the HMS system exhibited 100 percent detection of faults and an extremely low fault alarm rate, and were robust to sensor loss. A preliminary design of hardware architecture capable of supporting real-time operation of the HMS functions is described.

Hawman, Michael W.↗
NASA NTRS1999

A Survey and Synthesis of Solar Cycle Prediction Techniques

A number of techniques for predicting solar activity on a solar cycle time scale are identified, described, and tested with historical data. Some techniques, e.g. regression and curve-fitting, work well as solar activity approaches maximum and provide a complete description of future activity, while others, e.g. geomagnetic precursors, work well near solar minimum but only provide an estimate of the amplitude of the cycle. A synthesis of different techniques is shown to provide a more accurate and useful forecast of solar cycle activity levels. A combination of two uncorrelated geomagnetic precursor techniques provides the most accurate prediction for the amplitude of a solar activity cycle at a time well before activity minimum. This Combined Precursor Method gives a smoothed sunspot number maximum of 154+/-21 at the 95% level of confidence for the next cycle maximum. A mathematical function dependent upon the time of cycle initiation and the cycle amplitude then describes the level of solar activity for the next complete cycle. As the time of cycle maximum approaches a better estimate of the cycle activity is obtained by including the fit between previous activity levels and this function. This Combined Solar Cycle Activity Forecast gives, as of January 1999, a smoothed sunspot maximum of 146+/-20 at the 95% level of confidence for the next cycle maximum. The success of the geomagnetic precursors in predicting future solar activity suggests that solar magnetic phenomena at latitudes above the sunspot activity belts are linked to solar activity which occurs many years later in the lower latitudes.

Hathaway, David H.↗
NASA NTRS1999

Solar Cycle Predictions

We currently lack a comprehensive model for the solar dynamo which might be used for predicting solar cycle activity levels. We can, nonetheless, predict these activity levels with some skill using a variety of techniques based on correlations between activity indicators at different times. A number of the techniques currently in use for predicting solar activity on a solar cycle time-scale have been tested with historical data. Some techniques, e.g., regression and curve fitting, work well as solar activity approaches maximum and provide a month by month description of future activity, while others, e.g., geomagnetic precursors, work well near solar minimum but only provide an estimate of the amplitude of the next cycle. A synthesis of different techniques is shown to provide a more accurate and useful forecast of solar cycle activity levels. The combination of two uncorrelated geomagnetic precursor techniques provides a more accurate prediction for the amplitude of a solar activity cycle of a time well before activity minimum. A mathematical function dependent on the time of cycle initiation and the cycle amplitude can then be used to describe the level of solar activity month by month for the next cycle. As the time of cycle maximum approaches a better estimate of the cycle activity is obtained by including the fit between previous activity levels and this function. The success of the geomagnetic precursors in predicting the amplitude of the next solar cycle supports the idea of extended solar cycle in which the activity cycles overlap. While the current cycle is producing sunspots and active regions in the Sun's equatorial regions the next cycle is already actively influencing the geomagnetic field, The precise nature and source of this influence remains unclear.

Hathaway, D. H.↗