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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

An Estimate of the Likelihood for a Climatically Significant Volcanic Eruption Within the Present Decade (2000-2009)

Since 1750, the number of cataclysmic volcanic eruptions (i.e., those having a volcanic explosivity index, or VEI, equal to 4 or larger) per decade is found to span 2-11, with 96% located in the tropics and extra-tropical Northern Hemisphere, A two-point moving average of the time series has higher values since the 1860s than before, measuring 8.00 in the 1910s (the highest value) and measuring 6.50 in the 1980s, the highest since the 18 1 0s' peak. On the basis of the usual behavior of the first difference of the two-point moving averages, one infers that the two-point moving average for the 1990s will measure about 6.50 +/- 1.00, implying that about 7 +/- 4 cataclysmic volcanic eruptions should be expected during the present decade (2000-2009). Because cataclysmic volcanic eruptions (especially, those having VEI equal to 5 or larger) nearly always have been associated with episodes of short-term global cooling, the occurrence of even one could ameliorate the effects of global warming. Poisson probability distributions reveal that the probability of one or more VEI equal to 4 or larger events occurring within the next ten years is >99%, while it is about 49% for VEI equal to 5 or larger events and 18% for VEI equal to 6 or larger events. Hence, the likelihood that a, climatically significant volcanic eruption will occur within the next 10 years appears reasonably high.

Wilson, Robert M.↗
NASA NTRS2001

An Estimation of the Likelihood of Significant Eruptions During 2000-2009 Using Poisson Statistics on Two-Point Moving Averages of the Volcanic Time Series

Since 1750, the number of cataclysmic volcanic eruptions (volcanic explosivity index (VEI)>=4) per decade spans 2-11, with 96 percent located in the tropics and extra-tropical Northern Hemisphere. A two-point moving average of the volcanic time series has higher values since the 1860's than before, being 8.00 in the 1910's (the highest value) and 6.50 in the 1980's, the highest since the 1910's peak. Because of the usual behavior of the first difference of the two-point moving averages, one infers that its value for the 1990's will measure approximately 6.50 +/- 1, implying that approximately 7 +/- 4 cataclysmic volcanic eruptions should be expected during the present decade (2000-2009). Because cataclysmic volcanic eruptions (especially those having VEI>=5) nearly always have been associated with short-term episodes of global cooling, the occurrence of even one might confuse our ability to assess the effects of global warming. Poisson probability distributions reveal that the probability of one or more events with a VEI>=4 within the next ten years is >99 percent. It is approximately 49 percent for an event with a VEI>=5, and 18 percent for an event with a VEI>=6. Hence, the likelihood that a climatically significant volcanic eruption will occur within the next ten years appears reasonably high.

Wilson, Robert M.↗
NASA NTRS2025

Time-Dependent Satellite Explosion Probabilities for Long-Term Orbital Debris Environment Modeling

On-orbit accidental explosions are a significant contributor to the growth of the orbital debris population. Certain types of satellites have been seen to exhibit different behaviors and timelines of explosions. Recent assessments of on-orbit explosions for three categories of satellites – Russian Sistema Obespecheniya Zapuska (SOZ, Proton 4th stage attitude and ullage motors) units, spacecraft, and rocket bodies – suggest that on-orbit explosions can be modeled using a continuous, time-dependent probability of explosion. This paper discusses the methodology for developing a time-dependent probability of explosion as a function of the satellite’s orbital lifetime based on historical explosions. The SOZ units are found to be best modeled by a modified Gaussian probability distribution, with the peak probability of explosion occurring around 10.4 years on-orbit. Spacecraft and rocket bodies both exhibit exponentially decaying explosion probabilities, with rocket bodies showing fast-, medium-, and slow-time modes of decay. Total cumulative probabilities of explosion are approximately 57% for SOZ units, 4% for spacecraft, and 2% for rocket bodies. Examples of implementation in a simulation of the orbital debris environment using NASA's long-term evolutionary model are given, showing the overall explosion behavior over two centuries is significantly different from that using a previously implemented constant-probability type-dependent explosion rate model and provides a better representation of the historical explosion record.

Alyssa P Manis↗
NASA NTRS1997

Probabilistic Micromechanics and Macromechanics for Ceramic Matrix Composites

The properties of ceramic matrix composites (CMC's) are known to display a considerable amount of scatter due to variations in fiber/matrix properties, interphase properties, interphase bonding, amount of matrix voids, and many geometry- or fabrication-related parameters, such as ply thickness and ply orientation. This paper summarizes preliminary studies in which formal probabilistic descriptions of the material-behavior- and fabrication-related parameters were incorporated into micromechanics and macromechanics for CMC'S. In this process two existing methodologies, namely CMC micromechanics and macromechanics analysis and a fast probability integration (FPI) technique are synergistically coupled to obtain the probabilistic composite behavior or response. Preliminary results in the form of cumulative probability distributions and information on the probability sensitivities of the response to primitive variables for a unidirectional silicon carbide/reaction-bonded silicon nitride (SiC/RBSN) CMC are presented. The cumulative distribution functions are computed for composite moduli, thermal expansion coefficients, thermal conductivities, and longitudinal tensile strength at room temperature. The variations in the constituent properties that directly affect these composite properties are accounted for via assumed probabilistic distributions. Collectively, the results show that the present technique provides valuable information about the composite properties and sensitivity factors, which is useful to design or test engineers. Furthermore, the present methodology is computationally more efficient than a standard Monte-Carlo simulation technique; and the agreement between the two solutions is excellent, as shown via select examples.

Murthy, Pappu L. N.↗
NASA NTRS1972

Jimsphere wind and turbulence exceedance statistic

Exceedance statistics of winds and gusts observed over Cape Kennedy with Jimsphere balloon sensors are described. Gust profiles containing positive and negative departures, from smoothed profiles, in the wavelength ranges 100-2500, 100-1900, 100-860, and 100-460 meters were computed from 1578 profiles with four 41 weight digital high pass filters. Extreme values of the square root of gust speed are normally distributed. Monthly and annual exceedance probability distributions of normalized rms gust speeds in three altitude bands (2-7, 6-11, and 9-14 km) are log-normal. The rms gust speeds are largest in the 100-2500 wavelength band between 9 and 14 km in late winter and early spring. A study of monthly and annual exceedance probabilities and the number of occurrences per kilometer of level crossings with positive slope indicates significant variability with season, altitude, and filter configuration. A decile sampling scheme is tested and an optimum approach is suggested for drawing a relatively small random sample that represents the characteristic extreme wind speeds and shears of a large parent population of Jimsphere wind profiles.

Adelfang, S. I.↗
NASA NTRS1986

Success potential of automated star pattern recognition

A quasi-analytical model is presented for calculating the success probability of automated star pattern recognition systems for attitude control of spacecraft. The star data is gathered by an imaging star tracker (STR) with a circular FOV capable of detecting 20 stars. The success potential is evaluated in terms of the equivalent diameters of the FOV and the target star area ('uniqueness area'). Recognition is carried out as a function of the position and brightness of selected stars in an area around each guide star. The success of the system is dependent on the resultant pointing error, and is calculated by generating a probability distribution of reaching a threshold probability of an unacceptable pointing error. The method yields data which are equivalent to data available with Monte Carlo simulatins. When applied to the recognition system intended for use on the Space IR Telescope Facility it is shown that acceptable pointing, to a level of nearly 100 percent certainty, can be obtained using a single star tracker and about 4000 guide stars.

Van Bezooijen, R. W. H.↗
NASA NTRS1966

Signal fading characteristics, Echo II

Signal fading characteristics of Echo II SATELLITE - fade duration, and fade period probability distribution and density functions at various cross section levels

COMMUNICATION SYSTEM↗
NASA NTRS2008

Determination of a Limited Scope Network's Lightning Detection Efficiency

This paper outlines a modeling technique to map lightning detection efficiency variations over a region surveyed by a sparse array of ground based detectors. A reliable flash peak current distribution (PCD) for the region serves as the technique's base. This distribution is recast as an event probability distribution function. The technique then uses the PCD together with information regarding: site signal detection thresholds, type of solution algorithm used, and range attenuation; to formulate the probability that a flash at a specified location will yield a solution. Applying this technique to the full region produces detection efficiency contour maps specific to the parameters employed. These contours facilitate a comparative analysis of each parameter's effect on the network's detection efficiency. In an alternate application, this modeling technique gives an estimate of the number, strength, and distribution of events going undetected. This approach leads to a variety of event density contour maps. This application is also illustrated. The technique's base PCD can be empirical or analytical. A process for formulating an empirical PCD specific to the region and network being studied is presented. A new method for producing an analytical representation of the empirical PCD is also introduced.

Rompala, John T.↗
DOE OSTI2024

A Eulerian three-fluid flow framework for the study of fuel dispersal behavior under loss-of-coolant accident conditions

As the nuclear industry explores new fuel designs to accommodate increased burnup, studying fuel behavior during loss-of-coolant accidents is essential for ensuring the safe operation of light-water reactors. Here, this study presents a computational model to simulate the intricate three-phase flow dynamics of fuel dispersal following cladding breach, where solid fuel particles and carrier fission gases interact with the surrounding liquid or gas medium. The model utilizes a Eulerian three-fluid framework to depict the phase interaction within interpenetrating continua, treating fragmented fuel as granular material. Closure relationships for bulk-flow properties of the solid phase and detailed interfacial exchange terms in high-temperature, high-speed gas-solid-liquid flow scenarios are proposed. The model was validated using adiabatic experimental results in the literature, focusing on characterizing fuel dispersal behavior during loss-of-coolant accidents conditions. Settlement characteristics of the solids, quantified by the probability distribution of equivalent particles, closely matched probability density functions reported in experimental studies. Key highlights of this study include the theoretical description of a coupled three-phase flow with phase change, interpretation of the high-pressure boundary conditions and insights into the transient behavior of gas-solid-liquid phase dynamics during a simulated high-speed dispersal event.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Asymptotic inconsistency of the cumulative algorithm for laser-induced damage probability analysis

The “cumulative algorithm” is a data analysis method that has been proposed to provide an objective, nonparametric determination of laser-induced damage probability as a function of fluence from experimental data that contain both damaged sites and undamaged sites (i.e., 1-on-1 or S-on-1 testing protocols). In this work, the limitations of this approach are explored by considering the asymptotic limit of a large number of test sites. It is shown that the cumulative algorithm does not converge to the true probability distribution and significantly underestimates the damage probability near the damage onset. Here, based on the results of this work, the cumulative algorithm is not recommended for accurate estimation of damage probability.

Computational methods↗
NASA NTRS1994

Stochastic decision analysis

Small space flight project design at NASA Langley Research Center goes through a multi-phase process from preliminary analysis to flight operations. The process insures that each system achieves its technical objectives with demonstrated quality and within planned budgets and schedules. A key technical component of early phases is decision analysis, which is a structure procedure for determining the best of a number of feasible concepts based upon project objectives. Feasible system concepts are generated by the designers and analyzed for schedule, cost, risk, and technical measures. Each performance measure value is normalized between the best and worst values and a weighted average score of all measures is calculated for each concept. The concept(s) with the highest scores are retained, while others are eliminated from further analysis. This project automated and enhanced the decision analysis process. Automation of the decision analysis process was done by creating a user-friendly, menu-driven, spreadsheet macro based decision analysis software program. The program contains data entry dialog boxes, automated data and output report generation, and automated output chart generation. The enhancements to the decision analysis process permit stochastic data entry and analysis. Rather than enter single measure values, the designers enter the range and most likely value for each measure and concept. The data can be entered at the system or subsystem level. System level data can be calculated as either sum, maximum, or product functions of the subsystem data. For each concept, the probability distributions are approximated for each measure and the total score for each concept as either constant, triangular, normal, or log-normal distributions. Based on these distributions, formulas are derived for the probability that the concept meets any given constraint, the probability that the concept meets all constraints, and the probability that the concept is within a given amount of the best score. Formulas are also derived for the probability that one concept's total score is within a given amount of a second concept's total score. These probabilistic calculations provide more realistic data entry and output information for designers, enabling designers to better determine which concepts to eliminate and which concepts to retain at the decision points of each design phase.

Lacksonen, Thomas A.↗