Search NASA⌕ Search

SEARCH · Search NASA

Results for “Applied Probability”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Risk-Informed Systems Analysis (RISA) Dynamic Fire PRA Roadmap

Modeling and implementing fire safety for nuclear power plants is a costly activity. Because of the complexity of fire phenomenon and multiple operational procedures, it is difficult to computationally provide assurance that the mitigation methods are adequate for critical areas using current analysis methods. An economical method to provide more accurate modeling and optimize mitigation methods is needed to improve nuclear power viability. This report describes the initial investigation into modeling and simulation tools for application of fire as part of the Risk-Informed Systems Analysis (RISA), formerly Risk-Informed Safety Margin Characterization (RISMC). The report provides a framework of how 3D modeling and simulation techniques could be combined with a dynamic Probabilistic Risk Analysis (PRA) to reduce compounding conservatism present in current Fire PRA methods. Electrical Power Research Institute has analyzed current Fire PRA practices and identified the most significant contributors to risk and areas for improving analysis. This framework describes how to apply dynamic PRA and simulation methods for key contributors/scenarios, credit missing factors of manual fire suppression, and applying conditional probabilities.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Cyber–Physical Correlation Effects in Defense Games for Large Discrete Infrastructures

In certain critical infrastructures, correlations between cyber and physical components can be exploited to launch strategic attacks, so that disruptions to one component may affect others and possibly the entire infrastructure. Such correlations must be explicitly taken into account in ensuring the survival of the infrastructure. For large discrete infrastructures characterized by the number of cyber and physical components, we characterize the cyber–physical interactions at two levels: (i) the cyber–physical failure correlation function specifies the conditional survival probability of the cyber sub-infrastructure given that of the physical sub-infrastructure (both specified by their marginal probabilities), and (ii) individual survival probabilities of both sub-infrastructures are characterized by first-order differential conditions expressed in terms of their multiplier functions. We formulate an abstract problem of ensuring the survival probability of a cyber–physical infrastructure with discrete components as a game between the provider and attacker, whose utility functions are composed of infrastructure survival probability terms and cost terms, both expressed in terms of the number of components attacked and reinforced. We derive Nash equilibrium conditions and sensitivity functions that highlight the dependence of infrastructure survival probability on cost terms, correlation functions, multiplier functions, and sub-infrastructure survival probabilities. We apply these analytical results to characterize the defense postures of simplified models of metro systems, cloud computing infrastructures, and smart power grids.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1965

Contamination analysis and monitoring

"Sterilization" is a term applied to any process or procedure that produces a condition of sterility. Sterility is an absolute concept and refers to the destruction or removal of all life. However, when sterility as an absolute concept is applied to the sterilization of space hardware, it ceases to be operational. Absolute proof of sterility of flight hardware is impossible. Hence, for an operational approach to certification of sterility of space hardware, it is necessary to apply the probability concept. The present report is concerned with the applicability of mathematics to predict the probability of achieving sterility in a complex space hardware system. As such, this approach is concerned with the manipulation of microbiological data rather than mathematical rigor.

contamination↗
NASA NTRS1969

Diffusion of rays in random media.

Fokker-Planck equation applied to probability density for finding rays larger than correlation distance during propagation in random medium

Liu, C. H.↗
NASA NTRS1985

A simplified optical model description of heavy ion fragmentation

The abrasion-ablation model of heavy-ion frgmentation by target nuclei of Townsend (1983) and the EVAP Monte Carlo computer program (Guthrie, 1970) for decay probabilities are applied to calculate the production cross sections of isotopes of S, P, Si, and Al for the fragmentation of 213-MeV/nucleon Ar-40 ions by C-12 targets and of Fe, Mn, Cr, V, Ti, Sc, and Ca for 1.88-GeV Fe-56 fragmentation by Pb-208 and by C-12. The results are presented in tables and graphs and shown to be in good agreement with the experimental data of Viyogi et al. (1979) and Westfall et al. (1979). The implications of these studies for the design of radiation shielding for long-term manned space missions are indicated.

Townsend, L. W.↗
NASA NTRS1985

Systematic analysis of EOS data system for operations

A data management analysis methodology is being proposed. The objective of the methodology is to assist mission managers by identifying a series of ordered activities to be systematically followed in order to arrive at an effective ground system design. Existing system engineering tools and concepts have been assembled into a structured framework to facilitate the work of a mission planner. It is intended that this methodology can be gainfully applied (with probable modifications and/or changes) to the EOS payloads and their associated data systems.

Moe, K. L.↗
NASA NTRS1992

Detailed analysis of low energy plasma data under the Voyager Uranus data analysis program

Research effort included the PLS data analysis program where modifications to the data fitting procedure and elimination of possible noise and electron contamination were made. The analysis code corrections were used in checking the Neptune data gathered during the Voyager 2 encounter and for analyzing selected plasma spectra from the warm Io torus. A major task accomplished was the summary of Uranus-related research in the U.S. National Report to the International Union of Geodesy and Geophysics for the 1987 - 1990 quadrennium. A limited amount of work was accomplished on assessing the Pedersen conductivity of the ionosphere and comparing it with inferred values from shielding by the Uranian ring current. Under this grant there has been a great deal of effort expended on identifying and classifying plasma waves and oscillations in the magnetosheath and solar wind downstream from Uranus. Large amplitude oscillations in plasma parameters are found in the magnetosheath, with density changes of up to a factor of ten occurring on times scales of minutes. New algorithms developed for analyzing the inbound bow shock crossing of Neptune will probably be applied to a more detailed analysis of the Uranus shock in the near future.

Mcnutt, Ralph L., Jr.↗
NASA NTRS1993

Increasing accuracy in the assessment of motion sickness: A construct methodology

The purpose is to introduce a new methodology that should improve the accuracy of the assessment of motion sickness. This construct methodology utilizes both subjective reports of motion sickness and objective measures of physiological correlates to assess motion sickness. Current techniques and methods used in the framework of a construct methodology are inadequate. Current assessment techniques for diagnosing motion sickness and space motion sickness are reviewed, and attention is called to the problems with the current methods. Further, principles of psychophysiology that when applied will probably resolve some of these problems are described in detail.

Stout, Cynthia S.↗
NASA NTRS2001

Portfolios in Stochastic Local Search: Efficiently Computing Most Probable Explanations in Bayesian Networks

Portfolio methods support the combination of different algorithms and heuristics, including stochastic local search (SLS) heuristics, and have been identified as a promising approach to solve computationally hard problems. While successful in experiments, theoretical foundations and analytical results for portfolio-based SLS heuristics are less developed. This article aims to improve the understanding of the role of portfolios of heuristics in SLS. We emphasize the problem of computing most probable explanations (MPEs) in Bayesian networks (BNs). Algorithmically, we discuss a portfolio-based SLS algorithm for MPE computation, Stochastic Greedy Search (SGS). SGS supports the integration of different initialization operators (or initialization heuristics) and different search operators (greedy and noisy heuristics), thereby enabling new analytical and experimental results. Analytically, we introduce a novel Markov chain model tailored to portfolio-based SLS algorithms including SGS, thereby enabling us to analytically form expected hitting time results that explain empirical run time results. For a specific BN, we show the benefit of using a homogenous initialization portfolio. To further illustrate the portfolio approach, we consider novel additive search heuristics for handling determinism in the form of zero entries in conditional probability tables in BNs. Our additive approach adds rather than multiplies probabilities when computing the utility of an explanation. We motivate the additive measure by studying the dramatic impact of zero entries in conditional probability tables on the number of zero-probability explanations, which again complicates the search process. We consider the relationship between MAXSAT and MPE, and show that additive utility (or gain) is a generalization, to the probabilistic setting, of MAXSAT utility (or gain) used in the celebrated GSAT and WalkSAT algorithms and their descendants. Utilizing our Markov chain framework, we show that expected hitting time is a rational function - i.e. a ratio of two polynomials - of the probability of applying an additive search operator. Experimentally, we report on synthetically generated BNs as well as BNs from applications, and compare SGSs performance to that of Hugin, which performs BN inference by compilation to and propagation in clique trees. On synthetic networks, SGS speeds up computation by approximately two orders of magnitude compared to Hugin. In application networks, our approach is highly competitive in Bayesian networks with a high degree of determinism. In addition to showing that stochastic local search can be competitive with clique tree clustering, our empirical results provide an improved understanding of the circumstances under which portfolio-based SLS outperforms clique tree clustering and vice versa.

Mengshoel, Ole J.↗
DOE OSTI2016

Game-Theoretic strategies for systems of components using product-form utilities

Many critical infrastructures are composed of multiple systems of components which are correlated so that disruptions to one may propagate to others. We consider such infrastructures with correlations characterized in two ways: (i) an aggregate failure correlation function specifies the conditional failure probability of the infrastructure given the failure of an individual system, and (ii) a pairwise correlation function between two systems specifies the failure probability of one system given the failure of the other. We formulate a game for ensuring the resilience of the infrastructure, wherein the utility functions of the provider and attacker are products of an infrastructure survival probability term and a cost term, both expressed in terms of the numbers of system components attacked and reinforced. The survival probabilities of individual systems satisfy first-order differential conditions that lead to simple Nash Equilibrium conditions. We then derive sensitivity functions that highlight the dependence of infrastructure resilience on the cost terms, correlation functions, and individual system survival probabilities. We apply these results to simplified models of distributed cloud computing and energy grid infrastructures.

Rao, Nageswara S↗
DOE OSTI2016

Defense strategies for infrastructures with multiple systems of components

In several critical infrastructures correlations between the constituent systems represent certain vulnerabilities: disruptions to one may propagate to others and possibly to the entire infrastructure. The correlations between the systems are characterized in two ways in this paper: (i) the aggregate failure correlation function specifies the conditional failure probability of the infrastructure given the failure of an individual system, and (ii) the pairwise correlation function between two systems specifies the failure probability of one system given the failure of the other. The survival probabilities of individual systems satisfy firstorder differential conditions that generalize the contest success functions and statistical independence conditions. We formulate a problem of ensuring the resilience of an infrastructure as a game between the provider and attacker; their utility functions are sums of infrastructure survival probability terms and cost terms, both expressed in terms of the numbers of system components attacked and reinforced. We derive Nash Equilibrium conditions and sensitivity functions that highlight the dependence of infrastructure resilience on the cost terms, correlation functions, and individual system survival probabilities. We apply these results to models of distributed cloud computing and energy grid infrastructures.

Rao, Nageswara S↗
DOE OSTI2020

A Mathematical Framework for Representing Cyber-Physical System Interdependencies and Resilience

U.S. critical infrastructure is increasingly composed of integrated cyber-physical systems (CPS) whose components are operationally interdependent. These interdependencies can create additional vulnerabilities beyond those that are typically evaluated through independent physical and cyber risk assessments. These additional vulnerabilities, previously undetected at the sub-system and/or component level, could cause cascading effects across both the physical and cyber domains that could lead to infrastructure disruption or failure. This paper will review an initial mathematical framework developed to help understand the dynamics of these interfacing physical and cyber components at a holistic system level. The resulting framework also provides a method for modeling and assessing the resilience of CPS in complex and adaptive systems. It frames the system in terms of mission performance and the potential effects to performance caused by attacks that are cyber, physical, or blended in nature. The framework utilizes a systems-based, state-space modeling approach to reason about risk, resilience, and interdependencies in CPS. Probabilities are applied to each CPS component regarding a threat (both man-made and natural) and the likelihood of that particular component being impacted, along with indirect impact to other interdependent components. These component-level impacts from threats then translate into mission-level impact and systemic state change.

Brigantic, Robert T.↗
NASA NTRS1984

GASP cloud encounter statistics - Implications for laminar flow control flight

The cloud observation archive from the NASA Global Atmospheric Sampling Program (GASP) is analyzed in order to derive the probability of cloud encounter at altitudes normally flown by commercial airliners, for application to a determination of the feasability of Laminar Flow Control (LFC) on long-range routes. The probability of cloud encounter is found to vary significantly with season. Several meteorological circulation features are apparent in the latitudinal distribution of cloud cover. The cloud encounter data are shown to be consistent with the classical midlatitude cyclone model with more clouds encountered in highs than in lows. Aircraft measurements of route-averaged time-in-clouds fit a gamma probability distribution model which is applied to estimate the probability of extended cloud encounter, and the associated loss of LFC effectiveness along seven high-density routes. The probability is demonstrated to be low.

Jasperson, W. H.↗
DOE OSTI2014

The stochastic model for ternary and quaternary alloys: Application of the Bernoulli relation to the phonon spectra of mixed crystals

To understand and interpret the experimental data on the phonon spectra of the solid solutions, it is necessary to describe mathematically the non-regular distribution of atoms in their lattices. It appears that such description is possible in case of the strongly stochastically homogenous distribution which requires a great number of atoms and very carefully mixed alloys. These conditions are generally fulfilled in case of high quality homogenous semiconductor solid solutions of the III–V and II–VI semiconductor compounds. In this case, we can use the Bernoulli relation describing probability of the occurrence of one n equivalent event which can be applied, to the probability of finding one from n configurations in the solid solution lattice. The results described in this paper for ternary HgCdTe and GaAsP as well as quaternary ZnCdHgTe can provide an affirmative answer to the question: whether stochastic geometry, e.g., the Bernoulli relation, is enough to describe the observed phonon spectra.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Treatment of Nonuniform Temperature Distribution by Subgroup Method

The subgroup method divides an energy group into several subgroups according to the magnitude of the cross section. The subgroup fixed source equation is formulated on the energy range of a subgroup, the ratio of which to the energy range of an energy group is defined as subgroup probability. Typically the physical probability table or the mathematical probability table is applied. However, both of the tables are not guaranteed to share the same set of subgroup probabilities for a resonant nuclide at different temperatures. This means that the subgroup fixed source equation cannot be formulated and the subgroup method will not work when the temperature distribution is nonuniform. To overcome this defect, the subgroup method based on partial cross section fit scheme (PXSFS) and the simplified partial cross section fit scheme (SPXSFS) are proposed. These methods fit the cross sections at different temperatures as partial cross sections to share a same set of subgroup probabilities. The new methods is compared to the conventional subgroup method (CSM) based on physical probability table and the preexisting methods: the correlation model (CM), the subgroup level adjustment scheme (SLAS) and the number density adjustment scheme (NDAS). The numerical results show that the new methods can better predict the spatial dependent reaction rate than preexisting methods. Within these two methods, the simplified scheme consumes less time.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Advanced Processing of Functional Magnetic Materials

Functional materials, specifically those which respond to external stimuli such as magnetic and electrical field, are increasingly important for many green energy technologies. Functional magnetic materials are increasingly been investigated from basic and applied sciences perspectives. Probably, the best-known of these are permanent magnets, they are used to supply a magnetic field and are widely applied in motors, generators, data storage, sensors, and actuators. Other examples of functional materials include soft magnets, magnetocalorics, and thermoelectrics.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Continuous-variable quantum Boltzmann machine

Here, we propose a continuous-variable quantum Boltzmann machine (CVQBM) using a powerful energy-based neural network. It can be realized experimentally on a continuous-variable (CV) photonic quantum computer. We used a CV quantum imaginary time evolution (QITE) algorithm to prepare the essential thermal state and then designed the CVQBM to proficiently generate continuous probability distributions. We applied our method to both classical and quantum data. Using real-world classical data, such as synthetic-aperture radar (SAR) images, we generated probability distributions. For quantum data, we used the output of CV quantum circuits. We obtained high fidelity and low Kullback–Leibler (KL) divergence showing that our CVQBM learns distributions from given data well and generates data sampling from that distribution efficiently. We also discussed the experimental feasibility of our proposed CVQBM. Our method can be applied to a wide range of real-world problems by choosing an appropriate target distribution (corresponding to, e.g., SAR images, medical images, and risk management in finance). Moreover, our CVQBM is versatile and could be programmed to perform tasks beyond generation, such as anomaly detection.

SAR images↗
DOE OSTI2015

Improved Sampling Algorithms in the Risk-Informed Safety Margin Characterization Toolkit

The RISMC approach is developing advanced set of methodologies and algorithms in order to perform Probabilistic Risk Analyses (PRAs). In contrast to classical PRA methods, which are based on Event-Tree and Fault-Tree methods, the RISMC approach largely employs system simulator codes applied to stochastic analysis tools. The basic idea is to randomly perturb (by employing sampling algorithms) timing and sequencing of events and internal parameters of the system codes (i.e., uncertain parameters) in order to estimate stochastic parameters such as core damage probability. This approach applied to complex systems such as nuclear power plants requires to perform a series of computationally expensive simulation runs given a large set of uncertain parameters. These types of analysis are affected by two issues. Firstly, the space of the possible solutions (a.k.a., the issue space or the response surface) can be sampled only very sparsely, and this precludes the ability to fully analyze the impact of uncertainties on the system dynamics. Secondly, large amounts of data are generated and tools to generate knowledge from such data sets are not yet available. This report focuses on the first issue and in particular employs novel methods that optimize the information generated by the sampling process by sampling unexplored and risk-significant regions of the issue space: adaptive (smart) sampling algorithms. They infer system response from surrogate models constructed from existing samples and predict the most relevant location of the next sample. It is therefore possible to understand features of the issue space with a small number of carefully selected samples. In this report, we will present how it is possible to perform adaptive sampling using the RISMC toolkit and highlight the advantages compared to more classical sampling approaches such Monte-Carlo. We will employ RAVEN to perform such statistical analyses using both analytical cases but also another RISMC code: RELAP-7.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗