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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 289 records · Page 16
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NASA NTRS1996

An Ab Initio Based Potential Energy Surface for Water

We report a new determination of the water potential energy surface. A high quality ab initio potential energy surface (PES) and dipole moment function of water have been computed. This PES is empirically adjusted to improve the agreement between the computed line positions and those from the HITRAN 92 data base. The adjustment is small, nonetheless including an estimate of core (oxygen 1s) electron correlation greatly improves the agreement with experiment. Of the 27,245 assigned transitions in the HITRAN 92 data base for H2(O-16), the overall root mean square (rms) deviation between the computed and observed line positions is 0.125/cm. However the deviations do not correspond to a normal distribution: 69% of the lines have errors less than 0.05/cm. Overall, the agreement between the line intensities computed in the present work and those contained in the data base is quite good, however there are a significant number of line strengths which differ greatly.

Partridge, Harry↗
NASA NTRS2002

Towards Comprehensive Variation Models for Designing Vehicle Monitoring Systems

When designing vehicle vibration monitoring systems for aerospace devices, it is common to use well-established models of vibration features to determine whether failures or defects exist. Most of the algorithms used for failure detection rely on these models to detect significant changes in a flight environment. In actual practice, however, most vehicle vibration monitoring systems are corrupted by high rates of false alarms and missed detections. This crucial roadblock makes their implementation in real vehicles (e.g., helicopter transmissions and aircraft engines) difficult, making their operation costly and unreliable. Research conducted at the NASA Ames Research Center has determined that a major reason for the high rates of false alarms and missed detections is the numerous sources of statistical variations that are not taken into account in the modeling assumptions. In this paper, we address one such source of variations, namely, those caused during the design and manufacturing of rotating machinery components that make up aerospace systems. We present a novel way of modeling the vibration response by including design variations via probabilistic methods. Using such models, we develop a methodology to account for design and manufacturing variations, and explore the changes in the vibration response to determine its stochastic nature. We explore the potential of the methodology using a nonlinear cam-follower model, where the spring stiffness values are assumed to follow a normal distribution. The results demonstrate initial feasibility of the method, showing great promise in developing a general methodology for designing more accurate aerospace vehicle monitoring systems.

McAdams, Daniel A.↗
NASA NTRS2002

Effect of Random Geometric Uncertainty on the Computational Design of a 3-D Flexible Wing

The effect of geometric uncertainty due to statistically independent, random, normally distributed shape parameters is demonstrated in the computational design of a 3-D flexible wing. A first-order second-moment statistical approximation method is used to propagate the assumed input uncertainty through coupled Euler CFD aerodynamic / finite element structural codes for both analysis and sensitivity analysis. First-order sensitivity derivatives obtained by automatic differentiation are used in the input uncertainty propagation. These propagated uncertainties are then used to perform a robust design of a simple 3-D flexible wing at supercritical flow conditions. The effect of the random input uncertainties is shown by comparison with conventional deterministic design results. Sample results are shown for wing planform, airfoil section, and structural sizing variables.

Gumbert, C. R.↗
NASA NTRS2002

Probabilistic and Possibilistic Analyses of the Strength of a Bonded Joint

The effects of uncertainties on the predicted strength of a single lap shear joint are examined. Probabilistic and possibilistic methods are used to account for uncertainties. A total of ten variables are assumed to be random, with normal distributions. Both Monte Carlo Simulation and the First Order Reliability Method are used to determine the probability of failure. Triangular membership functions with upper and lower bounds located at plus or minus three standard deviations are used to model uncertainty in the possibilistic analysis. The alpha cut (or vertex) method is used to evaluate the possibility of failure. Linear and geometrically nonlinear finite element analyses are used calculate the response of the joint; fracture in the adhesive and material strength failure in the strap are used to evaluate its strength. Although probabilistic and possibilistic analyses provide significantly more information than do conventional deterministic analyses, they are computationally expensive. A novel scaling approach is developed and used to substantially reduce the computational cost of the probabilistic and possibilistic analyses. The possibilistic approach for treating uncertainties appears to be viable during the conceptual and preliminary design stages when limited data are available and high accuracies are not needed. However, this viability is mixed with several cautions that are discussed herein.

Stroud, W. Jefferson↗
NASA NTRS2002

Maximum Likelihood Estimation of the Broken Power Law Spectral Parameters with Detector Design Applications

The method of Maximum Likelihood (ML) is used to estimate the spectral parameters of an assumed broken power law energy spectrum from simulated detector responses. This methodology, which requires the complete specificity of all cosmic-ray detector design parameters, is shown to provide approximately unbiased, minimum variance, and normally distributed spectra information for events detected by an instrument having a wide range of commonly used detector response functions. The ML procedure, coupled with the simulated performance of a proposed space-based detector and its planned life cycle, has proved to be of significant value in the design phase of a new science instrument. The procedure helped make important trade studies in design parameters as a function of the science objectives, which is particularly important for space-based detectors where physical parameters, such as dimension and weight, impose rigorous practical limits to the design envelope. This ML methodology is then generalized to estimate broken power law spectral parameters from real cosmic-ray data sets.

Howell, Leonard W.↗
NASA NTRS2002

Statistical Sampling of Tide Heights Study

The goal of the study was to determine if it was possible to reduce the cost of verifying computational models of tidal waves and currents. Statistical techniques were used to determine the least number of samples required, in a given situation, to remain statistically significant, and thereby reduce overall project costs. Commercial, academic, and Federal agencies could benefit by applying these techniques, without the need to 'touch' every item in the population. For example, the requirement of this project was to measure the heights and times of high and low tides at 8,000 locations for verification of computational models of tidal waves and currents. The application of the statistical techniques began with observations to determine the correctness of submitted measurement data, followed by some assumptions based on the observations. Among the assumptions were that the data were representative of data-collection techniques used at the measurement locations, that time measurements could be ignored (that is, height measurements alone would suffice), and that the height measurements were from a statistically normal distribution. Sample means and standard deviations were determined for all locations. Interval limits were determined for confidence levels of 95, 98, and 99 percent. It was found that the numbers of measurement locations needed to attain these confidence levels were 55, 78, and 96, respectively.

Source record↗
NASA NTRS2003

Stochastic Models of Tropical Rain-Rate Fields

Because of the extreme variability of rain rate in space and time and the difficulties with remote sensing methods of measuring rain rates, accurate determination of rainfall over large areas and time periods has long been a problem for hydrologists, meteorogists, and climatologists. A number of statistical models of rain have been developed in order to investigate the impact of rain variability on satellite remote sensing methods, validation of satellite rain products, and generation of rain maps with accompanying error estimates. These models may be useful in examining 'sub-grid scale' issues in representing precipitation in numerical mdoels. A stochastic model will first be described which can generate time-dependent high-resolution spatial rain fields with space and time correlations similar to those seen in rain data, as well as representing the presence of areas with zero rain rate and log-normally distributed rain rates where there is rain. A simpler model derived from this, formulated in the spectral domain, seems to imply fractal-like rain statistics at small scales when fit to rain data.

Bell, Thomas L.↗
NASA NTRS2003

Fragmentation under the Scaling Symmetry and Turbulent Cascade with Intermittency

Fragmentation plays an important role in a variety of physical, chemical, and geological processes. Examples include atomization in sprays, crushing of rocks, explosion and impact of solids, polymer degradation, etc. Although each individual action of fragmentation is a complex process, the number of these elementary actions is large. It is natural to abstract a simple 'effective' scenario of fragmentation and to represent its essential features. One of the models is the fragmentation under the scaling symmetry: each breakup action reduces the typical length of fragments, r (right arrow) alpha r, by an independent random multiplier alpha (0 < alpha < 1), which is governed by the fragmentation intensity spectrum q(alpha), integral(sup 1)(sub 0) q(alpha)d alpha = 1. This scenario has been proposed by Kolmogorov (1941), when he considered the breakup of solid carbon particle. Describing the breakup as a random discrete process, Kolmogorov stated that at latest times, such a process leads to the log-normal distribution. In Gorokhovski & Saveliev, the fragmentation under the scaling symmetry has been reviewed as a continuous evolution process with new features established. The objective of this paper is twofold. First, the paper synthesizes and completes theoretical part of Gorokhovski & Saveliev. Second, the paper shows a new application of the fragmentation theory under the scale invariance. This application concerns the turbulent cascade with intermittency. We formulate here a model describing the evolution of the velocity increment distribution along the progressively decreasing length scale. The model shows that when the turbulent length scale gets smaller, the velocity increment distribution has central growing peak and develops stretched tails. The intermittency in turbulence is manifested in the same way: large fluctuations of velocity provoke highest strain in narrow (dissipative) regions of flow.

Gorokhovski, M.↗
NASA NTRS2004

Employing Sensitivity Derivatives for Robust Optimization under Uncertainty in CFD

A robust optimization is demonstrated on a two-dimensional inviscid airfoil problem in subsonic flow. Given uncertainties in statistically independent, random, normally distributed flow parameters (input variables), an approximate first-order statistical moment method is employed to represent the Computational Fluid Dynamics (CFD) code outputs as expected values with variances. These output quantities are used to form the objective function and constraints. The constraints are cast in probabilistic terms; that is, the probability that a constraint is satisfied is greater than or equal to some desired target probability. Gradient-based robust optimization of this stochastic problem is accomplished through use of both first and second-order sensitivity derivatives. For each robust optimization, the effect of increasing both input standard deviations and target probability of constraint satisfaction are demonstrated. This method provides a means for incorporating uncertainty when considering small deviations from input mean values.

Newman, Perry A.↗
NASA NTRS2004

Employing Sensitivity Derivatives to Estimate Uncertainty Propagation in CFD

Two methods that exploit the availability of sensitivity derivatives are successfully employed to predict uncertainty propagation through Computational Fluid Dynamics (CFD) code for an inviscid airfoil problem. An approximate statistical second-moment method and a Sensitivity Derivative Enhanced Monte Carlo (SDEMC) method are successfully demonstrated on a two-dimensional problem. First- and second-order sensitivity derivatives of code output with respect to code input are obtained through an efficient incremental iterative approach. Given uncertainties in statistically independent, random, normally distributed flow parameters (input variables); these sensitivity derivatives enable one to formulate first- and second-order Taylor Series approximations for the mean and variance of CFD output quantities. Additionally, incorporation of the first-order sensitivity derivatives into the data reduction phase of a conventional Monte Carlo (MC) simulation allows for improved accuracy in determining the first moment of the CFD output. Both methods are compared to results generated using a conventional MC method. The methods that exploit the availability of sensitivity derivatives are found to be valid when considering small deviations from input mean values.

Putko, Michele M.↗
NASA NTRS2000

Analysis of cell mechanics in single vinculin-deficient cells using a magnetic tweezer

A magnetic tweezer was constructed to apply controlled tensional forces (10 pN to greater than 1 nN) to transmembrane receptors via bound ligand-coated microbeadswhile optically measuring lateral bead displacements within individual cells. Use of this system with wild-type F9 embryonic carcinoma cells and cells from a vinculin knockout mouse F9 Vin (-/-) revealed much larger differences in the stiffness of the transmembrane integrin linkages to the cytoskeleton than previously reported using related techniques that measured average mechanical properties of large cell populations. The mechanical properties measured varied widely among cells, exhibiting an approximately log-normal distribution. The median lateral bead displacement was 2-fold larger in F9 Vin (-/-) cells compared to wild-type cells whereas the arithmetic mean displacement only increased by 37%. We conclude that vinculin serves a greater mechanical role in cells than previously reported and that this magnetic tweezer device may be useful for probing the molecular basis of cell mechanics within single cells. Copyright 2000 Academic Press.

Non-NASA Center↗
NASA NTRS2004

What the Sunspot Record Tells Us About Space Climate

The records concerning the number, sizes, and positions of sunspots provide a direct means of characterizing solar activity over nearly 400 years. Sunspot numbers are strongly correlated with modem measures of solar activity including: 10.7-cm radio flux, total irradiance, x-ray flares, sunspot area, the baseline level of geomagnetic activity, and the flux of galactic cosmic rays. The Group Sunspot Number provides information on 27 sunspot cycles, far more than any of the modem measures of solar activity, and enough to provide important details about long-term variations in solar activity or Space Climate. The sunspot record shows: 1) sunspot cycles have periods of 131 plus or minus 14 months with a normal distribution; 2) sunspot cycles are asymmetric with a fast rise and slow decline; 3) the rise time from minimum to maximum decreases with cycle amplitude; 4) large amplitude cycles are preceded by short period cycles; 5 ) large amplitude cycles are preceded by high minima; 6) although the two hemispheres remain linked in phase, there are significant asymmetries in the activity in each hemisphere; 7) the rate at which the active latitudes drift toward the equator is anti-correlated with the cycle period, 8) the rate at which the active latitudes drift toward the equator is positively correlated with the amplitude of the cycle after the next; 9) there has been a significant secular increase in the amplitudes of the sunspot cycles since the end of the Maunder Minimum (1715); and 10) there is weak evidence for a quasi-periodic variation in the sunspot cycle amplitudes with a period of about 90 years. These characteristics indicate that the next solar cycle should have a maximum smoothed sunspot number of about 1.45 plus or minus 30 in 2010 while the following cycle should have a maximum of about 70 plus or minus 30 in 2023.

Hathaway, David H.↗
NASA NTRS2004

Probabilistic Analysis of a SiC/SiC Ceramic Matrix Composite Turbine Vane

To demonstrate the advanced composite materials technology under development within the Ultra-Efficient Engine Technology (UEET) Program, it was planned to fabricate, test, and analyze a turbine vane made entirely of silicon carbide-fiber-reinforced silicon carbide matrix composite (SiC/SiC CMC) material. The objective was to utilize a five-harness satin weave melt-infiltrated (MI) SiC/SiC composite material developed under this program to design and fabricate a stator vane that can endure 1000 hours of engine service conditions. The vane was designed such that the expected maximum stresses were kept within the proportional limit strength of the material. Any violation of this design requirement was considered as the failure. This report presents results of a probabilistic analysis and reliability assessment of the vane. Probability of failure to meet the design requirements was computed. In the analysis, material properties, strength, and pressure loading were considered as random variables. The pressure loads were considered normally distributed with a nominal variation. A temperature profile on the vane was obtained by performing a computational fluid dynamics (CFD) analysis and was assumed to be deterministic. The results suggest that for the current vane design, the chance of not meeting design requirements is about 1.6 percent.

Murthy, Pappu L. N.↗
NASA NTRS2002

Approach for Input Uncertainty Propagation and Robust Design in CFD Using Sensitivity Derivatives

An implementation of the approximate statistical moment method for uncertainty propagation and robust optimization for quasi 3-D Euler CFD code is presented. Given uncertainties in statistically independent, random, normally distributed input variables, first- and second-order statistical moment procedures are performed to approximate the uncertainty in the CFD output. Efficient calculation of both first- and second-order sensitivity derivatives is required. In order to assess the validity of the approximations, these moments are compared with statistical moments generated through Monte Carlo simulations. The uncertainties in the CFD input variables are also incorporated into a robust optimization procedure. For this optimization, statistical moments involving first-order sensitivity derivatives appear in the objective function and system constraints. Second-order sensitivity derivatives are used in a gradient-based search to successfully execute a robust optimization. The approximate methods used throughout the analyses are found to be valid when considering robustness about input parameter mean values.

Putko, Michele M.↗
NASA NTRS2004

Invariant Theory for Dispersed Transverse Isotropy: An Efficient Means for Modeling Fiber Splay

Most soft tissues possess an oriented architecture of collagen fiber bundles, conferring both anisotropy and nonlinearity to their elastic behavior. Transverse isotropy has often been assumed for a subset of these tissues that have a single macroscopically-identifiable preferred fiber direction. Micro-structural studies, however, suggest that, in some tissues, collagen fibers are approximately normally distributed about a mean preferred fiber direction. Structural constitutive equations that account for this dispersion of fibers have been shown to capture the mechanical complexity of these tissues quite well. Such descriptions, however, are computationally cumbersome for two-dimensional (2D) fiber distributions, let alone for fully three-dimensional (3D) fiber populations. In this paper, we develop a new constitutive law for such tissues, based on a novel invariant theory for dispersed transverse isotropy. The invariant theory is based on a novel closed-form splay invariant that can easily handle 3D fiber populations, and that only requires a single parameter in the 2D case. The model is polyconvex and fits biaxial data for aortic valve tissue as accurately as the standard structural model. Modification of the fiber stress-strain law requires no re-formulation of the constitutive tangent matrix, making the model flexible for different types of soft tissues. Most importantly, the model is computationally expedient in a finite-element analysis.

Freed, alan D.↗
NASA NTRS2005

Analysis of Multi-Scale Radiometric Data Collected during the Cold Land Processes Experiment-1 (CLPX-1)

Brightness temperature maps at 18.7 and 37 GHz collected at the Fraser and North Park Meso-Scale Areas during the Cold Land Processes Experiment by the NOAA Polarimetric Scanning Radiometer (PSWA) airborne sensor are analyzed. The Fraser site is mostly covered by forest with a typical snowpack depth of 1 m while North Park has no forest cover and is characterized by patches of shallow snow. We examine histograms of the brightness temperatures at 500 m resolution for both the Fraser and North Park areas. The histograms can be modelled by a log-normal distribution in the case of the Fraser MSA and by a bi-modal distribution in the case of the North Park MSA. The histograms of the brightness temperatures at coarser resolutions are also plotted to study the effects of sensor resolution on the shape of the distribution, on the values of the average brightness temperatures and standard deviations. Finally, the values of brightness temperatures obtained by re-sampling (aggregating) the data at 25 km resolution are compared with the values of the brightness temperatures collected by the Advanced Microwave Scanning Radiometer (AMSR-E) and Special Sensor Microwave/Imager (SSMII) satellite radiometers. The results show that in both areas for sensor footprint larger than 5000 m, the brightness temperatures show a flat distribution and the memory of the initial distribution is lost. The values of the brightness temperatures measured by the satellite radiometers are in good agreement with the values obtained averaging the airborne data, even if some discrepancies occur.

Tedesco, M.↗
NASA NTRS2008

Monte Carlo Simulation to Estimate Likelihood of Direct Lightning Strikes

A software tool has been designed to quantify the lightning exposure at launch sites of the stack at the pads under different configurations. In order to predict lightning strikes to generic structures, this model uses leaders whose origins (in the x-y plane) are obtained from a 2D random, normal distribution.

Mata, Carlos↗
NASA NTRS2011

Characterizing the Joint Effect of Diverse Test-Statistic Correlation Structures and Effect Size on False Discovery Rates in a Multiple-Comparison Study of Many Outcome Measures

In their 2009 Annals of Statistics paper, Gavrilov, Benjamini, and Sarkar report the results of a simulation assessing the robustness of their adaptive step-down procedure (GBS) for controlling the false discovery rate (FDR) when normally distributed test statistics are serially correlated. In this study we extend the investigation to the case of multiple comparisons involving correlated non-central t-statistics, in particular when several treatments or time periods are being compared to a control in a repeated-measures design with many dependent outcome measures. In addition, we consider several dependence structures other than serial correlation and illustrate how the FDR depends on the interaction between effect size and the type of correlation structure as indexed by Foerstner s distance metric from an identity. The relationship between the correlation matrix R of the original dependent variables and R~, the correlation matrix of associated t-statistics is also studied. In general R~ depends not only on R, but also on sample size and the signed effect sizes for the multiple comparisons.

Feiveson, Alan H.↗