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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 559 records · Page 31

The analytical representation of viscoelastic material properties using optimization techniques

This report presents a technique to model viscoelastic material properties with a function of the form of the Prony series. Generally, the method employed to determine the function constants requires assuming values for the exponential constants of the function and then resolving the remaining constants through linear least-squares techniques. The technique presented here allows all the constants to be analytically determined through optimization techniques. This technique is employed in a computer program named PRONY and makes use of commercially available optimization tool developed by VMA Engineering, Inc. The PRONY program was utilized to compare the technique against previously determined models for solid rocket motor TP-H1148 propellant and V747-75 Viton fluoroelastomer. In both cases, the optimization technique generated functions that modeled the test data with at least an order of magnitude better correlation. This technique has demonstrated the capability to use small or large data sets and to use data sets that have uniformly or nonuniformly spaced data pairs. The reduction of experimental data to accurate mathematical models is a vital part of most scientific and engineering research. This technique of regression through optimization can be applied to other mathematical models that are difficult to fit to experimental data through traditional regression techniques.

Hill, S. A.↗

The relationship between surface temperature and a spectral vegetation index of a tallgrass prairie - Effects of burning and other landscape controls

Site-to-site variability in the relation between remotely-sensed surface temperatures (Ts) and the normalized difference spectral vegetation index (NDVI) of a tallgrass prairie was investigated. The primary objective was to determine whether the proportion of burnt/unburnt area within a sub-scene affected the Ts-NDVI regression slope (SL). Regression analyses confirmed that burn treatments, particularly on steep slopes, were responsible for most of the observed variability in SL while soil moisture content and the forested areas also had a significant effect on SL.

Hope, A. S.↗

The effect of cloud type on earth's energy balance - Results for selected regions

International Satellite Cloud Climatology Project (ISCCP) C1 cloud information is compared with planetary albedo, outgoing longwave radiation (OLR), and net radiation measured at the top of the atmosphere by the Earth Radiation Budget Experiment (ERBE). Principal component analysis indicates that the day-to-day variations of the abundances of the 35 cloud types of the C1 data are correlated with each other, so that for many purposes the data set can be well represented by about five cloud types. Using stepwise multiple regression, the ISCCP C1 data can be used to predict the day-to-day variations of the energy balance measured by ERBE for 2.5-deg regions. Total fractional area coverage of cloudiness is a relatively poor predictor of radiation budget quantities. If the total fractional area coverage by clouds is divided into contributions from several distinct cloud types, the fractional coverages by these several cloud types will together form a much better prediction of radiation budget quantities than the single variable of total fractional-area cloud coverage. The regression equations can be used to estimate the net effect of clouds on the radiation balance and the contributions from particular types of clouds to albedo, OLR, and net radiation.

Ockert-Bell, Maureen E.↗

Time to detection of circulating microbubbles as a risk factor for symptoms of altitude decompression sickness

This study investigated the association between time at onset of circulating microbubbles (CMB) and symptoms of altitude decompression sickness (DCS), using Cox proportional hazard regression models. The study population consisted of 125 individuals who participated in direct ascent, simulated extravehicular activities profiles. Using individual CMB status as a time-dependent variable, we found that the hazard for symptoms increased significantly (at the end of 180 min at altitude) in the presence of CMB (Hazard Ratio = 29.59; 95 percent confidence interval (95 percent CI) = 7.66-114.27), compared to no CMB. Further examination was conducted on the subgroup of individuals who developed microbubbles during the test (n = 49), by using Cox regression. Individuals with late onset of CMB (greater than 60 min at altitude) showed a significantly reduced risk of symptoms (hazard ratio = 0.92; 95 percent CI = 0.89-0.95), compared to those with early onset (equal to or less than 60 min), while controlling for other risk factors. We conclude that time to detection of circulating microbubbles is an independent determinant of symptoms of DCS.

Kumar, K. V.↗

The effect of cloud type on Earth's energy balance - Global analysis

The role of fractional area coverage by cloud types in the energy balance of the earth is investigated through joint use of International Satellite Cloud Climatology Project (ISCCP) C1 cloud data and Earth Radiation Budget Experiment (ERBE) broadband energy flux data for the one-year period March 1985 through February 1986. Multiple linear regression is used to relate the radiation budget data to the cloud data. Comparing cloud forcing estimates obtained from the ISCCP-ERBE regression with those derived from the ERBE scene identification shows generally good agreement except over snow, in tropical convective regions, and in regions that are either nearly cloudless or always overcast. It is suggested that a substantial fraction of the disagreement in longwave cloud forcing in tropical convective regions is associated with the fact that the ERBE scene identification does not take into account variations in upper-tropospheric water vapor. On a global average basis, low clouds make the largest contribution to the net energy balance of the Earth, because they cover such a large area and because their albedo effect dominates their effect on emitted thermal radiation. High, optically thick clouds can also very effectively reduce the energy balance, however, because their very high albedos overcome their low emission temperatures.

Hartmann, Dennis L.↗

Components of interannual ozone change based on Nimbus 7 TOMS data

A multiple regression statistical model is applied to estimate the latitude and seasonal dependences of the solar cycle, quasi-biennial oscillation (QBO), and anthropogenic trend components of stratospheric total ozone change using 13.2 years of Nimbus 7 TOMS data. The characteristics of the linear trend component are in agreement with earlier studies. The QBO regression coefficient is significantly different from zero at high southern latitudes in the Austral spring supporting earlier evidence that the Antarctic ozone depletion is modulated by the QBO. The existence of a solar cycle component is indicated by empirical studies of model residuals and by the approximate agreement of the derived global mean solar coefficient amplitude with photochemical calculations. Initial estimates for the latitude dependence of the solar coefficient suggest higher amplitudes with increasing latitude, especially in the Southern Hemisphere in spring. The statistical model predicts a return to more rapid ozone depletions during the next 4 years as solar minimum is approached.

Hood, Lon L.↗

Remote sensing of submerged vegetation canopies for biomass estimation

The visible bands of the Landsat Thematic Mapper (TM) sensor were used in an empirical assessment of seagrass biomass on shallow banks near Lee Stocking Island in the Bahamas. The TM bands were transformed to minimize the depth-dependent variance in the bottom reflectance signal. Regression analyses were performed between the transformed bands and field measurements of seagrass standing crop (above-ground biomass). Regression equations using spectral data accounted for up to 80 per cent of the variability in seagrass biomass. The unexplained variance was ascribed to variations in bottom sediment color.

Armstrong, Roy A.↗

Confidence bounds on structural reliability

Different approaches for quantifying physical, statistical, and model uncertainties associated with the distribution parameters which are aimed at determining structural reliability are described. Confidence intervals on the distribution parameters of the input random variables are estimated using four algorithms to evaluate uncertainty of the response. Design intervals are evaluated using either Monte Carlo simulation or an iterative approach. A first order approach can be used to compute a first approximation of the design interval, but its accuracy is not satisfactory. The regression approach which combines the iterative approach with Monte Carlo simulation is capable of providing good results if the performance function can be accurately represented using regression analysis. It is concluded that the design interval-based approach seems to be quite general and takes into account distribution and model uncertainties.

Mehta, S. R.↗

Aeromechanical stability of helicopters with composite rotor blades in forward flight

The aeromechanical stability, including air resonance in hover, air resonance in forward flight, and ground resonance, of a helicopter with elastically tailored composite rotor blades is investigated. Five soft-inplane hingeless rotor configurations, featuring elastic pitch-lag, pitch-flap and extension-torsion couplings, are analyzed. Elastic couplings introduced through tailored composite blade spars can have a powerful effect on both air and ground resonance behavior. Elastic pitch-flap couplings (positive and negative) strongly affect body, rotor and dynamic inflow modes. Air resonance stability is diminished by elastic pitch-flap couplings in hover and forward flight. Negative pitch-lag elastic coupling has a stabilizing effect on the regressive lag mode in hover and forward flight. The negative pitch-lag coupling has a detrimental effect on ground resonance stability. Extension-torsion elastic coupling (blade pitch decreases due to tension) decreases regressive lag mode stability in both airborne and ground contact conditions. Increasing thrust levels has a beneficial influence on ground resonance stability for rotors with pitch-flap and extension-torsion coupling and is only marginally effective in improving stability of rotors with pitch-lag coupling.

Smith, Edward C.↗

Hybrid combustion with metallized fuels

A chemical method of adding certain catalysts to improve the degradation process of a solid fuel is discussed. Thermogravimetric (TGA) analysis used to study the fundamental degradation behavior of a typical hybrid fuel (HTPB) shows that high surface temperatures increase the degradation rate. Fuels were tested in a laboratory-scale experimental hybrid rocket and their behavior was compared to a baseline behavior of HTPB fuel regression rates. It was found that a small amount of metal powder added to the fuel can significantly increase the regression rates.

Yi, Jianwen↗

Hybrid rocket combustion study

The objectives of this study of 'pure' or 'classic' hybrids are to (1) extend our understanding of the boundary layer combustion process and the critical engineering parameters that define this process, (2) develop an up-to-date hybrid fuel combustion model, and (3) apply the model to correlate the regression rate and scaling properties of potential fuel candidates. Tests were carried out with a hybrid slab window motor, using several diagnostic techniques, over a range of motor pressure and oxidizer mass flux conditions. The results basically confirmed turbulent boundary layer heat and mass transfer as the rate limiting process for hybrid fuel decomposition and combustion. The measured fuel regression rates showed good agreement with the analytical model predictions. The results of model scaling calculations to Shuttle SRM size conditions are presented.

Strand, L. D.↗

Spatial structure, sampling design and scale in remotely-sensed imagery of a California savanna woodland

This article describes research related to sampling techniques for establishing linear relations between land surface parameters and remotely-sensed data. Predictive relations are estimated between percentage tree cover in a savanna environment and a normalized difference vegetation index (NDVI) derived from the Thematic Mapper sensor. Spatial autocorrelation in original measurements and regression residuals is examined using semi-variogram analysis at several spatial resolutions. Sampling schemes are then tested to examine the effects of autocorrelation on predictive linear models in cases of small sample sizes. Regression models between image and ground data are affected by the spatial resolution of analysis. Reducing the influence of spatial autocorrelation by enforcing minimum distances between samples may also improve empirical models which relate ground parameters to satellite data.

Mcgwire, K.↗

Study Of Fuels For Hybrid Rockets

Report describes experimental study of combustion and rates of regression of selected fuels for hybrid rocket engines. Part of continuing effort to develop fuels with greater rates of regression and lesser dependence on shapes of fuel grains and to maximize potential specific impulse at low cost.

Strand, Leon D.↗

Verification of a two-dimensional infiltration model for the resin transfer molding process

A two-dimensional finite element model for the infiltration of a dry textile preform by an injected resin was verified. The model, which is based on the finite element/control volume technique, determines the total infiltration time and the pressure increase at the mold inlet associated with the RTM process. Important input data for the model are the compaction and permeability behavior of the preform along with the kinetic and rheological behavior of the resin. The compaction behavior for several textile preforms was determined by experimental methods. A power law regression model was used to relate fiber volume fraction to the applied compaction pressure. Results showed a large increase in fiber volume fraction with the initial application of pressure. However, as the maximum fiber volume fraction was approached, the amount of compaction pressure required to decrease the porosity of the preform rapidly increased. Similarly, a power law regression model was used to relate permeability to the fiber volume fraction of the preform. Two methods were used to measure the permeability of the textile preform. The first, known as the steady state method, measures the permeability of a saturated preform under constant flow rate conditions. The second, denoted the advancing front method, determines the permeability of a dry preform to an infiltrating fluid. Water, corn oil, and an epoxy resin, Epon 815, were used to determine the effect of fluid type and viscosity on the steady state permeability behavior of the preform. Permeability values measured with the different fluids showed that fluid viscosity had no influence on the permeability behavior of 162 E-glass and TTI IM7/8HS preforms. Permeabilities measured from steady state and advancing front experiments for the warp direction of 162 E-glass fabric were similar. This behavior was noticed for tests conducted with corn oil and Epon 815. Comparable behavior was observed for the warp direction of the TTI IM7/8HS preform and corn oil. Mold filling and flow visualization experiments were performed to verify the analytical computer model. Frequency dependent electromagnetic sensors were used to monitor the resin flow front as a function of time. For the flow visualization tests, a video camera and high resolution tape recorder were used to record the experimental flow fronts. Comparisons between experimental and model predicted flow fronts agreed well for all tests. For the mold filling tests conducted at constant flow rate injection, the model was able to accurately predict the pressure increase at the mold inlet during the infiltration process. A kinetics model developed to predict the degree of cure as a function of time for the injected resin accurately calculated the increase in the degree of cure during the subsequent cure cycle.

Hammond, Vincent H.↗

A linear spectral matching technique for retrieving equivalent water thickness and biochemical constituents of green vegetation

Over the last decade, technological advances in airborne imaging spectrometers, having spectral resolution comparable with laboratory spectrometers, have made it possible to estimate biochemical constituents of vegetation canopies. Wessman estimated lignin concentration from data acquired with NASA's Airborne Imaging Spectrometer (AIS) over Blackhawk Island in Wisconsin. A stepwise linear regression technique was used to determine the single spectral channel or channels in the AIS data that best correlated with measured lignin contents using chemical methods. The regression technique does not take advantage of the spectral shape of the lignin reflectance feature as a diagnostic tool nor the increased discrimination among other leaf components with overlapping spectral features. A nonlinear least squares spectral matching technique was recently reported for deriving both the equivalent water thicknesses of surface vegetation and the amounts of water vapor in the atmosphere from contiguous spectra measured with the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). The same technique was applied to a laboratory reflectance spectrum of fresh, green leaves. The result demonstrates that the fresh leaf spectrum in the 1.0-2.5 microns region consists of spectral components of dry leaves and the spectral component of liquid water. A linear least squares spectral matching technique for retrieving equivalent water thickness and biochemical components of green vegetation is described.

Gao, Bo-Cai↗

Modeling and managing risk early in software development

In order to improve the quality of the software development process, we need to be able to build empirical multivariate models based on data collectable early in the software process. These models need to be both useful for prediction and easy to interpret, so that remedial actions may be taken in order to control and optimize the development process. We present an automated modeling technique which can be used as an alternative to regression techniques. We show how it can be used to facilitate the identification and aid the interpretation of the significant trends which characterize 'high risk' components in several Ada systems. Finally, we evaluate the effectiveness of our technique based on a comparison with logistic regression based models.

Briand, Lionel C.↗

Diagnostic and quality-assurance tools for low-contrast images obtained from array detectors

We investigate methods of estimating a background image frame for subtraction from a data frame for use when a more suitable measured background frame is not available. We define background as any signal component that is not attributable to the phenomenon currently under investigation. We describe a technique that is based on pixel-by-pixel least-squares regression of images for computing a background frame from available data. We argue that the same technique can be a useful quality-assurance tool for evaluating instrument performance. For example, it can help to separate image structure resulting from the reading process from structure resulting from the characteristics of the detector itself. We demonstrate that background estimation can be nontrivial by comparing the results of different background estimation procedures by using data obtained from a CCD array detector. We investigate the temperature-dependent contributions of the detector and readout electronics to the total signal as a demonstration of the diagnostic capabilities of least-squares image regression.

Hatfield, D. B.↗

Trend analysis of the long-term Swiss ozone measurements

Trend analyses, assuming a linear trend which started at 1970, were performed from total ozone measurements from Arosa (Switzerland, 1926-1991). Decreases in monthly mean values were statistically significant for October through April showing decreases of about 2.0-4 percent per decade. For the period 1947-91, total ozone trends were further investigated using a multiple regression model. Temperature of a mountain peak in Switzerland (Mt. Santis), the F10.7 solar flux series, the QBO series (quasi biennial oscillation), and the southern oscillation index (SOI) were included as explanatory variables. Trends in the monthly mean values were statistically significant for December through April. The same multiple regression model was applied to investigate the ozone trends at various altitudes using the ozone balloon soundings from Payerne (1967-1989) and the Umkehr measurements from Arosa (1947-1989). The results show four different vertical trend regimes: On a relative scale changes were largest in the troposphere (increase of about 10 percent per decade). On an absolute scale the largest trends were obtained in the lower stratosphere (decrease of approximately 6 per decade at an altitude of about 18 to 22 km). No significant trends were observed at approximately 30 km, whereas stratospheric ozone decreased in the upper stratosphere.

Staehelin, Johannes↗