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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

An analytic technique for statistically modeling random atomic clock errors in estimation

Minimum variance estimation requires that the statistics of random observation errors be modeled properly. If measurements are derived through the use of atomic frequency standards, then one source of error affecting the observable is random fluctuation in frequency. This is the case, for example, with range and integrated Doppler measurements from satellites of the Global Positioning and baseline determination for geodynamic applications. An analytic method is presented which approximates the statistics of this random process. The procedure starts with a model of the Allan variance for a particular oscillator and develops the statistics of range and integrated Doppler measurements. A series of five first order Markov processes is used to approximate the power spectral density obtained from the Allan variance.

Fell, P. J.↗
NASA NTRS1990

Line identification studies using traditional techniques and wavelength coincidence statistics

Traditional line identification techniques result in the assignment of individual lines to an atomic or ionic species. These methods may be supplemented by wavelength coincidence statistics (WCS). The strength and weakness of these methods are discussed using spectra of a number of normal and peculiar B and A stars that have been studied independently by both methods. The present results support the overall findings of some earlier studies. WCS would be most useful in a first survey, before traditional methods have been applied. WCS can quickly make a global search for all species and in this way may enable identifications of an unexpected spectrum that could easily be omitted entirely from a traditional study. This is illustrated by O I. WCS is a subject to well known weakness of any statistical technique, for example, a predictable number of spurious results are to be expected. The danger of small number statistics are illustrated. WCS is at its best relative to traditional methods in finding a line-rich atomic species that is only weakly present in a complicated stellar spectrum.

Cowley, Charles R.↗
NASA NTRS1990

Line identification studies using traditional techniques and wavelength coincidence statistics

Traditional line identification techniques result in the assignment of individual lines to an atomic or ionic species. These methods may be supplemented by wavelength coincidence statistics (WCS). The strength and weakness of these methods are discussed using spectra of a number of normal and peculiar B and A stars that have been studied independently by both methods. The present results support the overall findings of some earlier studies. WCS would be most useful in a first survey, before traditional methods have been applied. WCS can quickly make a global search for all species and in this way may enable identifications of an unexpected spectrum that could easily be omitted entirely from a traditional study. This is illustrated by O I. WCS is a subject to well known weakness of any statistical technique, for example, a predictable number of spurious results are to be expected. The danger of small number statistics are illustrated. WCS is at its best relative to traditional methods in finding a line-rich atomic species that is only weakly present in a complicated stellar spectrum.

Cowley, Charles R.↗
NASA NTRS1997

Metamodels for Computer-Based Engineering Design: Survey and Recommendations

The use of statistical techniques to build approximations of expensive computer analysis codes pervades much of todays engineering design. These statistical approximations, or metamodels, are used to replace the actual expensive computer analyses, facilitating multidisciplinary, multiobjective optimization and concept exploration. In this paper we review several of these techniques including design of experiments, response surface methodology, Taguchi methods, neural networks, inductive learning, and kriging. We survey their existing application in engineering design and then address the dangers of applying traditional statistical techniques to approximate deterministic computer analysis codes. We conclude with recommendations for the appropriate use of statistical approximation techniques in given situations and how common pitfalls can be avoided.

Simpson, Timothy W.↗
NASA NTRS1982

Curve fitting and modeling with splines using statistical variable selection techniques

The successful application of statistical variable selection techniques to fit splines is demonstrated. Major emphasis is given to knot selection, but order determination is also discussed. Two FORTRAN backward elimination programs, using the B-spline basis, were developed. The program for knot elimination is compared in detail with two other spline-fitting methods and several statistical software packages. An example is also given for the two-variable case using a tensor product basis, with a theoretical discussion of the difficulties of their use.

Smith, P. L.↗
DOE OSTI2016

Robust verification analysis

We introduce a new methodology for inferring the accuracy of computational simulations through the practice of solution verification. We demonstrate this methodology on examples from computational heat transfer, fluid dynamics and radiation transport. Our methodology is suited to both well- and ill-behaved sequences of simulations. Our approach to the analysis of these sequences of simulations incorporates expert judgment into the process directly via a flexible optimization framework, and the application of robust statistics. The expert judgment is systematically applied as constraints to the analysis, and together with the robust statistics guards against over-emphasis on anomalous analysis results. We have named our methodology Robust Verification. Our methodology is based on utilizing multiple constrained optimization problems to solve the verification model in a manner that varies the analysis' underlying assumptions. Constraints applied in the analysis can include expert judgment regarding convergence rates (bounds and expectations) as well as bounding values for physical quantities (e.g., positivity of energy or density). This approach then produces a number of error models, which are then analyzed through robust statistical techniques (median instead of mean statistics). This provides self-contained, data and expert informed error estimation including uncertainties for both the solution itself and order of convergence. Our method produces high quality results for the well-behaved cases relatively consistent with existing practice. The methodology can also produce reliable results for ill-behaved circumstances predicated on appropriate expert judgment. We demonstrate the method and compare the results with standard approaches used for both code and solution verification on well-behaved and ill-behaved simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1971

Fatigue failure of materials under narrow band random vibrations. I.

A novel approach for the study of fatigue failure of materials under the multifactor influence of narrow band random vibrations is developed. The approach involves the conduction of an experiment in conjunction with various statistical techniques. Three factors including two statistical properties of the excitation or response are considered and varied simultaneously. A minimum of 6 tests for 3 variables is possible for a fractional f actorial design. The four coefficients of the predicting equation can be independently estimated. A look at 3 predicting equations shows the predominant effect of the root mean square stress of the first order equation.

Huang, T. C.↗
NASA NTRS1994

The measurement of disturbance levels in the Langley Research Center 20-inch Mach 6 tunnel

Constant-temperature anemometry was used to measure the disturbance levels in the Langley Research Center 20-inch Mach 6 Tunnel over a limited range of total pressures. The measurements were made using a dual wire probe where each wire was operated at a high but different overheat. The fluctuating voltages were digitized and a system of two equations was solved to obtain the instantaneous mass flow and total temperature fluctuations as a function of time. Statistical techniques were used to obtain statistical quantities of interest.

Stainback, P. C.↗
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 NTRS1978

Statistical sampling analysis for stratospheric measurements from satellite missions

Earth orbiting satellite experiments can be designed to measure stratospheric constituents such as ozone by utilizing remote sensing techniques. Statistical analysis techniques, mission simulation and model development have been utilized to develop a method for analyzing various mission/sensor combinations. Existing and planned NASA satellite missions such as Nimbus-4 and G, and Stratospheric Aerosol and Gas Experiment-Application Explorer Mission (SAGE-AEM) have been analyzed to determine the ability of the missions to adequately sample the global field.

Drewry, J. W.↗
NASA NTRS1988

Results of a joint NOAA/NASA sounder simulation study

This paper presents the results of a joint NOAA and NASA sounder simulation study in which the accuracies of atmospheric temperature profiles and surface skin temperature measuremnents retrieved from two sounders were compared: (1) the currently used IR temperature sounder HIRS2 (High-resolution Infrared Radiation Sounder 2); and (2) the recently proposed high-spectral-resolution IR sounder AMTS (Advanced Moisture and Temperature Sounder). Simulations were conducted for both clear and partial cloud conditions. Data were analyzed at NASA using a physical inversion technique and at NOAA using a statistical technique. Results show significant improvement of AMTS compared to HIRS2 for both clear and cloudy conditions. The improvements are indicated by both methods of data analysis, but the physical retrievals outperform the statistical retrievals.

Phillips, N.↗
DOE OSTI2015

Muon Antineutrino Disappearance in the MINOS Experiment

Antineutrinos from the set of 7.09$\times 10^{20}$ Protons-on-target (POT) of $\nu_\mu\textrm{-dominant}$ and 3.40$\times 10^{20}$ POT of $\bar\nu_\mu\textrm{-enhanced}$ MINOS beam data is analysed to extract the antineutrino atmospheric-scale oscillation parameters $\left|\Delta\bar m^2\right|$ and $\sin^2\left(2\bar\theta\right)$. Using the Feldman-Cousins statistical technique to account for systematic and statistical errors, $\left|\Delta\bar m^2\right|=2.58^{+0.26}_{-0.17} \times 10^{-3}~\textrm{eV}^2$ and $\sin^2\left(2\bar\theta\right)=0.96^{+0.04}_{-0.10}$ were measured. This measurement of $\left|\Delta\bar m^2\right|$ improves on the previous world limits from Super-K by a factor of five. Any observed difference between the neutrino and antineutrino oscillation parameters could be an indication of CPT violation, or otherwise physics beyond the standard model. This measurement is consistent with the global limits on $\left|\Delta m^2\right|$ and $\sin^2\left(2\theta\right)$ for neutrinos.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2020

Threats to Resiliency of Redundant Systems Due to Destructive SEE

Destructive SEE pose serious challenges for the reliable use of COTS devices in space systems. We used system-level modeling to determine SEL rates that would likely compromise system reliability, resilience and capabilities. We then assembled a representative dataset of COTS CMOS parts and used nonparametric statistical techniques to assess the threat posed to redundant systems by destructive SEE.

single-event effects↗
NASA NTRS1973

Development of a global cloud model for simulating earth-viewing space missions.

Existing global cloud models are improved and expanded so that they might be more effectively used in planning and evaluating potential earth-viewing space missions. A relationship is developed between the ground and satellite-derived cloud-amount frequency distributions. This relationship is used to improve internal consistency between the ground-observed unconditional statistics and the satellite-derived conditional statistics as tabulated in previous models. A statistical technique is developed which permits the scaling of the conditional statistics to time and distance separations other than those for which the data base is tabulated. A new technique to increase or decrease the representative area size of the statistical data base is developed. Both the scaling and area adjustment techniques are shown to represent significant improvements over the techniques previously employed.

Greaves, J. R.↗
DOE OSTI2016

Percutaneous Renal Tumor Ablation: Radiation Exposure During Cryoablation and Radiofrequency Ablation

IntroductionOnce reserved solely for non-surgical cases, percutaneous ablation is becoming an increasingly popular treatment option for a wider array of patients with small renal masses and the radiation risk needs to be better defined as this transition continues.Materials and MethodsRetrospective review of our renal tumor ablation database revealed 425 patients who underwent percutaneous ablation for treatment of 455 renal tumors over a 5-year time period. Imparted radiation dose information was reviewed for each procedure and converted to effective patient dose and skin dose using established techniques. Statistical analysis was performed with each ablative technique.ResultsFor the 331 cryoablation procedures, the mean DLP was 6987 mGycm (SD = 2861) resulting in a mean effective dose of 104.7 mSv (SD = 43.5) and the mean CTDI{sub vol} was 558 mGy (SD = 439) resulting in a mean skin dose of 563.2 mGy (SD = 344.1). For the 124 RFA procedures, the mean DLP was 3485 mGycm (SD = 1630) resulting in a mean effective dose of 50.3 mSv (SD = 24.0) and the mean CTDI{sub vol} was 232 mGy (SD = 149) resulting in a mean skin dose of 233.2 mGy (SD = 117.4). The difference in patient radiation exposure between the two renal ablation techniques was statistically significant (p < 0.001).ConclusionBoth cryoablation and RFA imparted an average skin dose that was well below the 2 Gy deterministic threshold for appreciable sequela. Renal tumor cryoablation resulted in a mean skin and effective radiation dose more than twice that for RFA. The radiation exposure for both renal tumor ablation techniques was at the high end of the medical imaging radiation dose spectrum.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS1991

Quantitative knowledge acquisition for expert systems

A common problem in the design of expert systems is the definition of rules from data obtained in system operation or simulation. While it is relatively easy to collect data and to log the comments of human operators engaged in experiments, generalizing such information to a set of rules has not previously been a direct task. A statistical method is presented for generating rule bases from numerical data, motivated by an example based on aircraft navigation with multiple sensors. The specific objective is to design an expert system that selects a satisfactory suite of measurements from a dissimilar, redundant set, given an arbitrary navigation geometry and possible sensor failures. The systematic development is described of a Navigation Sensor Management (NSM) Expert System from Kalman Filter convariance data. The method invokes two statistical techniques: Analysis of Variance (ANOVA) and the ID3 Algorithm. The ANOVA technique indicates whether variations of problem parameters give statistically different covariance results, and the ID3 algorithms identifies the relationships between the problem parameters using probabilistic knowledge extracted from a simulation example set. Both are detailed.

Belkin, Brenda L.↗
NASA NTRS1991

Knowledge acquisition for expert systems using statistical methods

A common problem in the design of expert systems is the definition of rules from data obtained in system operation or simulation. A statistical method for generating rule bases from numerical data, motivated by an example based on aircraft navigation with multiple sensors is presented. The specific objective is to design an expert system that selects a satisfactory suite of measurements from a dissimilar, redundant set, given an arbitrary navigation geometry and possible sensor failures. The systematic development of a Navigation Sensor Management (NSM) Expert System from Kalman Filter covariance data is described. The development method invokes two statistical techniques: Analysis-of-Variance (ANOVA) and the ID3 algorithm. The ANOVA technique indicates whether variations of problem parameters give statistically different covariance results, and the ID3 algorithm identifies the relationships between the problem parameters using probabilistic knowledge extracted from a simulation example set.

Belkin, Brenda L.↗