Advanced Small Modular Reactor (SMR) Probabilistic Risk Assessment (PRA) Technical Exchange Meeting

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, Curtis

2013-09-01

During FY13, the INL developed an advanced SMR PRA framework which has been described in the report Small Modular Reactor (SMR) Probabilistic Risk Assessment (PRA) Detailed Technical Framework Specification, INL/EXT-13-28974 (April 2013). In this framework, the various areas are considered: Probabilistic models to provide information specific to advanced SMRs Representation of specific SMR design issues such as having co-located modules and passive safety features Use of modern open-source and readily available analysis methods Internal and external events resulting in impacts to safety All-hazards considerations Methods to support the identification of design vulnerabilities Mechanistic and probabilistic data needs to support modelingmore » and tools In order to describe this framework more fully and obtain feedback on the proposed approaches, the INL hosted a technical exchange meeting during August 2013. This report describes the outcomes of that meeting.« less

Design for Reliability and Safety Approach for the New NASA Launch Vehicle

NASA Technical Reports Server (NTRS)

Safie, Fayssal M.; Weldon, Danny M.

2007-01-01

The United States National Aeronautics and Space Administration (NASA) is in the midst of a space exploration program intended for sending crew and cargo to the international Space Station (ISS), to the moon, and beyond. This program is called Constellation. As part of the Constellation program, NASA is developing new launch vehicles aimed at significantly increase safety and reliability, reduce the cost of accessing space, and provide a growth path for manned space exploration. Achieving these goals requires a rigorous process that addresses reliability, safety, and cost upfront and throughout all the phases of the life cycle of the program. This paper discusses the "Design for Reliability and Safety" approach for the NASA new launch vehicles, the ARES I and ARES V. Specifically, the paper addresses the use of an integrated probabilistic functional analysis to support the design analysis cycle and a probabilistic risk assessment (PRA) to support the preliminary design and beyond.

Station Blackout: A case study in the interaction of mechanistic and probabilistic safety analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Curtis Smith; Diego Mandelli; Cristian Rabiti

2013-11-01

The ability to better characterize and quantify safety margins is important to improved decision making about nuclear power plant design, operation, and plant life extension. As research and development (R&D) in the light-water reactor (LWR) Sustainability (LWRS) Program and other collaborative efforts yield new data, sensors, and improved scientific understanding of physical processes that govern the aging and degradation of plant SSCs needs and opportunities to better optimize plant safety and performance will become known. The purpose of the Risk Informed Safety Margin Characterization (RISMC) Pathway R&D is to support plant decisions for risk-informed margin management with the aim tomore » improve economics, reliability, and sustain safety of current NPPs. In this paper, we describe the RISMC analysis process illustrating how mechanistic and probabilistic approaches are combined in order to estimate a safety margin. We use the scenario of a “station blackout” wherein offsite power and onsite power is lost, thereby causing a challenge to plant safety systems. We describe the RISMC approach, illustrate the station blackout modeling, and contrast this with traditional risk analysis modeling for this type of accident scenario.« less

Alternate Methods in Refining the SLS Nozzle Plug Loads

NASA Technical Reports Server (NTRS)

Burbank, Scott; Allen, Andrew

2013-01-01

Numerical analysis has shown that the SLS nozzle environmental barrier (nozzle plug) design is inadequate for the prelaunch condition, which consists of two dominant loads: 1) the main engines startup pressure and 2) an environmentally induced pressure. Efforts to reduce load conservatisms included a dynamic analysis which showed a 31% higher safety factor compared to the standard static analysis. The environmental load is typically approached with a deterministic method using the worst possible combinations of pressures and temperatures. An alternate probabilistic approach, utilizing the distributions of pressures and temperatures, resulted in a 54% reduction in the environmental pressure load. A Monte Carlo simulation of environmental load that used five years of historical pressure and temperature data supported the results of the probabilistic analysis, indicating the probabilistic load is reflective of a 3-sigma condition (1 in 370 probability). Utilizing the probabilistic load analysis eliminated excessive conservatisms and will prevent a future overdesign of the nozzle plug. Employing a similar probabilistic approach to other design and analysis activities can result in realistic yet adequately conservative solutions.

Bayesian Inference for NASA Probabilistic Risk and Reliability Analysis

NASA Technical Reports Server (NTRS)

Dezfuli, Homayoon; Kelly, Dana; Smith, Curtis; Vedros, Kurt; Galyean, William

2009-01-01

This document, Bayesian Inference for NASA Probabilistic Risk and Reliability Analysis, is intended to provide guidelines for the collection and evaluation of risk and reliability-related data. It is aimed at scientists and engineers familiar with risk and reliability methods and provides a hands-on approach to the investigation and application of a variety of risk and reliability data assessment methods, tools, and techniques. This document provides both: A broad perspective on data analysis collection and evaluation issues. A narrow focus on the methods to implement a comprehensive information repository. The topics addressed herein cover the fundamentals of how data and information are to be used in risk and reliability analysis models and their potential role in decision making. Understanding these topics is essential to attaining a risk informed decision making environment that is being sought by NASA requirements and procedures such as 8000.4 (Agency Risk Management Procedural Requirements), NPR 8705.05 (Probabilistic Risk Assessment Procedures for NASA Programs and Projects), and the System Safety requirements of NPR 8715.3 (NASA General Safety Program Requirements).

Formalizing Probabilistic Safety Claims

NASA Technical Reports Server (NTRS)

Herencia-Zapana, Heber; Hagen, George E.; Narkawicz, Anthony J.

2011-01-01

A safety claim for a system is a statement that the system, which is subject to hazardous conditions, satisfies a given set of properties. Following work by John Rushby and Bev Littlewood, this paper presents a mathematical framework that can be used to state and formally prove probabilistic safety claims. It also enables hazardous conditions, their uncertainties, and their interactions to be integrated into the safety claim. This framework provides a formal description of the probabilistic composition of an arbitrary number of hazardous conditions and their effects on system behavior. An example is given of a probabilistic safety claim for a conflict detection algorithm for aircraft in a 2D airspace. The motivation for developing this mathematical framework is that it can be used in an automated theorem prover to formally verify safety claims.

Design for Reliability and Safety Approach for the NASA New Launch Vehicle

NASA Technical Reports Server (NTRS)

Safie, Fayssal, M.; Weldon, Danny M.

2007-01-01

The United States National Aeronautics and Space Administration (NASA) is in the midst of a space exploration program intended for sending crew and cargo to the international Space Station (ISS), to the moon, and beyond. This program is called Constellation. As part of the Constellation program, NASA is developing new launch vehicles aimed at significantly increase safety and reliability, reduce the cost of accessing space, and provide a growth path for manned space exploration. Achieving these goals requires a rigorous process that addresses reliability, safety, and cost upfront and throughout all the phases of the life cycle of the program. This paper discusses the "Design for Reliability and Safety" approach for the NASA new crew launch vehicle called ARES I. The ARES I is being developed by NASA Marshall Space Flight Center (MSFC) in support of the Constellation program. The ARES I consists of three major Elements: A solid First Stage (FS), an Upper Stage (US), and liquid Upper Stage Engine (USE). Stacked on top of the ARES I is the Crew exploration vehicle (CEV). The CEV consists of a Launch Abort System (LAS), Crew Module (CM), Service Module (SM), and a Spacecraft Adapter (SA). The CEV development is being led by NASA Johnson Space Center (JSC). Designing for high reliability and safety require a good integrated working environment and a sound technical design approach. The "Design for Reliability and Safety" approach addressed in this paper discusses both the environment and the technical process put in place to support the ARES I design. To address the integrated working environment, the ARES I project office has established a risk based design group called "Operability Design and Analysis" (OD&A) group. This group is an integrated group intended to bring together the engineering, design, and safety organizations together to optimize the system design for safety, reliability, and cost. On the technical side, the ARES I project has, through the OD&A environment, implemented a probabilistic approach to analyze and evaluate design uncertainties and understand their impact on safety, reliability, and cost. This paper focuses on the use of the various probabilistic approaches that have been pursued by the ARES I project. Specifically, the paper discusses an integrated functional probabilistic analysis approach that addresses upffont some key areas to support the ARES I Design Analysis Cycle (DAC) pre Preliminary Design (PD) Phase. This functional approach is a probabilistic physics based approach that combines failure probabilities with system dynamics and engineering failure impact models to identify key system risk drivers and potential system design requirements. The paper also discusses other probabilistic risk assessment approaches planned by the ARES I project to support the PD phase and beyond.

Influences of geological parameters to probabilistic assessment of slope stability of embankment

NASA Astrophysics Data System (ADS)

Nguyen, Qui T.; Le, Tuan D.; Konečný, Petr

2018-04-01

This article considers influences of geological parameters to slope stability of the embankment in probabilistic analysis using SLOPE/W computational system. Stability of a simple slope is evaluated with and without pore–water pressure on the basis of variation of soil properties. Normal distributions of unit weight, cohesion and internal friction angle are assumed. Monte Carlo simulation technique is employed to perform analysis of critical slip surface. Sensitivity analysis is performed to observe the variation of the geological parameters and their effects on safety factors of the slope stability.

An overview of engineering concepts and current design algorithms for probabilistic structural analysis

NASA Technical Reports Server (NTRS)

Duffy, S. F.; Hu, J.; Hopkins, D. A.

1995-01-01

The article begins by examining the fundamentals of traditional deterministic design philosophy. The initial section outlines the concepts of failure criteria and limit state functions two traditional notions that are embedded in deterministic design philosophy. This is followed by a discussion regarding safety factors (a possible limit state function) and the common utilization of statistical concepts in deterministic engineering design approaches. Next the fundamental aspects of a probabilistic failure analysis are explored and it is shown that deterministic design concepts mentioned in the initial portion of the article are embedded in probabilistic design methods. For components fabricated from ceramic materials (and other similarly brittle materials) the probabilistic design approach yields the widely used Weibull analysis after suitable assumptions are incorporated. The authors point out that Weibull analysis provides the rare instance where closed form solutions are available for a probabilistic failure analysis. Since numerical methods are usually required to evaluate component reliabilities, a section on Monte Carlo methods is included to introduce the concept. The article concludes with a presentation of the technical aspects that support the numerical method known as fast probability integration (FPI). This includes a discussion of the Hasofer-Lind and Rackwitz-Fiessler approximations.

Probabilistic Design Analysis (PDA) Approach to Determine the Probability of Cross-System Failures for a Space Launch Vehicle

NASA Technical Reports Server (NTRS)

Shih, Ann T.; Lo, Yunnhon; Ward, Natalie C.

2010-01-01

Quantifying the probability of significant launch vehicle failure scenarios for a given design, while still in the design process, is critical to mission success and to the safety of the astronauts. Probabilistic risk assessment (PRA) is chosen from many system safety and reliability tools to verify the loss of mission (LOM) and loss of crew (LOC) requirements set by the NASA Program Office. To support the integrated vehicle PRA, probabilistic design analysis (PDA) models are developed by using vehicle design and operation data to better quantify failure probabilities and to better understand the characteristics of a failure and its outcome. This PDA approach uses a physics-based model to describe the system behavior and response for a given failure scenario. Each driving parameter in the model is treated as a random variable with a distribution function. Monte Carlo simulation is used to perform probabilistic calculations to statistically obtain the failure probability. Sensitivity analyses are performed to show how input parameters affect the predicted failure probability, providing insight for potential design improvements to mitigate the risk. The paper discusses the application of the PDA approach in determining the probability of failure for two scenarios from the NASA Ares I project

INTEGRATION OF RELIABILITY WITH MECHANISTIC THERMALHYDRAULICS: REPORT ON APPROACH AND TEST PROBLEM RESULTS

DOE Office of Scientific and Technical Information (OSTI.GOV)

J. S. Schroeder; R. W. Youngblood

The Risk-Informed Safety Margin Characterization (RISMC) pathway of the Light Water Reactor Sustainability Program is developing simulation-based methods and tools for analyzing safety margin from a modern perspective. [1] There are multiple definitions of 'margin.' One class of definitions defines margin in terms of the distance between a point estimate of a given performance parameter (such as peak clad temperature), and a point-value acceptance criterion defined for that parameter (such as 2200 F). The present perspective on margin is that it relates to the probability of failure, and not just the distance between a nominal operating point and a criterion.more » In this work, margin is characterized through a probabilistic analysis of the 'loads' imposed on systems, structures, and components, and their 'capacity' to resist those loads without failing. Given the probabilistic load and capacity spectra, one can assess the probability that load exceeds capacity, leading to component failure. Within the project, we refer to a plot of these probabilistic spectra as 'the logo.' Refer to Figure 1 for a notional illustration. The implications of referring to 'the logo' are (1) RISMC is focused on being able to analyze loads and spectra probabilistically, and (2) calling it 'the logo' tacitly acknowledges that it is a highly simplified picture: meaningful analysis of a given component failure mode may require development of probabilistic spectra for multiple physical parameters, and in many practical cases, 'load' and 'capacity' will not vary independently.« less

The Role of Probabilistic Design Analysis Methods in Safety and Affordability

NASA Technical Reports Server (NTRS)

Safie, Fayssal M.

2016-01-01

For the last several years, NASA and its contractors have been working together to build space launch systems to commercialize space. Developing commercial affordable and safe launch systems becomes very important and requires a paradigm shift. This paradigm shift enforces the need for an integrated systems engineering environment where cost, safety, reliability, and performance need to be considered to optimize the launch system design. In such an environment, rule based and deterministic engineering design practices alone may not be sufficient to optimize margins and fault tolerance to reduce cost. As a result, introduction of Probabilistic Design Analysis (PDA) methods to support the current deterministic engineering design practices becomes a necessity to reduce cost without compromising reliability and safety. This paper discusses the importance of PDA methods in NASA's new commercial environment, their applications, and the key role they can play in designing reliable, safe, and affordable launch systems. More specifically, this paper discusses: 1) The involvement of NASA in PDA 2) Why PDA is needed 3) A PDA model structure 4) A PDA example application 5) PDA link to safety and affordability.

Probabilistic Analysis of a Composite Crew Module

NASA Technical Reports Server (NTRS)

Mason, Brian H.; Krishnamurthy, Thiagarajan

2011-01-01

An approach for conducting reliability-based analysis (RBA) of a Composite Crew Module (CCM) is presented. The goal is to identify and quantify the benefits of probabilistic design methods for the CCM and future space vehicles. The coarse finite element model from a previous NASA Engineering and Safety Center (NESC) project is used as the baseline deterministic analysis model to evaluate the performance of the CCM using a strength-based failure index. The first step in the probabilistic analysis process is the determination of the uncertainty distributions for key parameters in the model. Analytical data from water landing simulations are used to develop an uncertainty distribution, but such data were unavailable for other load cases. The uncertainty distributions for the other load scale factors and the strength allowables are generated based on assumed coefficients of variation. Probability of first-ply failure is estimated using three methods: the first order reliability method (FORM), Monte Carlo simulation, and conditional sampling. Results for the three methods were consistent. The reliability is shown to be driven by first ply failure in one region of the CCM at the high altitude abort load set. The final predicted probability of failure is on the order of 10-11 due to the conservative nature of the factors of safety on the deterministic loads.

The European ASAMPSA_E project : towards guidance to model the impact of high amplitude natural hazards in the probabilistic safety assessment of nuclear power plants. Information on the project progress and needs from the geosciences.

NASA Astrophysics Data System (ADS)

Raimond, Emmanuel; Decker, Kurt; Guigueno, Yves; Klug, Joakim; Loeffler, Horst

2015-04-01

The Fukushima nuclear accident in Japan resulted from the combination of two correlated extreme external events (earthquake and tsunami). The consequences, in particular flooding, went beyond what was considered in the initial engineering design design of nuclear power plants (NPPs). Such situations can in theory be identified using probabilistic safety assessment (PSA) methodology. PSA results may then lead industry (system suppliers and utilities) or Safety Authorities to take appropriate decisions to reinforce the defence-in-depth of the NPP for low probability event but high amplitude consequences. In reality, the development of such PSA remains a challenging task. Definitions of the design basis of NPPs, for example, require data on events with occurrence probabilities not higher than 10-4 per year. Today, even lower probabilities, down to 10-8, are expected and typically used for probabilistic safety analyses (PSA) of NPPs and the examination of so-called design extension conditions. Modelling the combinations of natural or man-made hazards that can affect a NPP and affecting some meaningful probability of occurrence seems to be difficult. The European project ASAMPSAE (www.asampsa.eu) gathers more than 30 organizations (industry, research, safety control) from Europe, US and Japan and aims at identifying some meaningful practices to extend the scope and the quality of the existing probabilistic safety analysis developed for nuclear power plants. It offers a framework to discuss, at a technical level, how "extended PSA" can be developed efficiently and be used to verify if the robustness of Nuclear Power Plants (NPPs) in their environment is sufficient. The paper will present the objectives of this project, some first lessons and introduce which type of guidance is being developed. It will explain the need of expertise from geosciences to support the nuclear safety assessment in the different area (seismotectonic, hydrological, meteorological and biological hazards, …).

Developing Probabilistic Safety Performance Margins for Unknown and Underappreciated Risks

NASA Technical Reports Server (NTRS)

Benjamin, Allan; Dezfuli, Homayoon; Everett, Chris

2015-01-01

Probabilistic safety requirements currently formulated or proposed for space systems, nuclear reactor systems, nuclear weapon systems, and other types of systems that have a low-probability potential for high-consequence accidents depend on showing that the probability of such accidents is below a specified safety threshold or goal. Verification of compliance depends heavily upon synthetic modeling techniques such as PRA. To determine whether or not a system meets its probabilistic requirements, it is necessary to consider whether there are significant risks that are not fully considered in the PRA either because they are not known at the time or because their importance is not fully understood. The ultimate objective is to establish a reasonable margin to account for the difference between known risks and actual risks in attempting to validate compliance with a probabilistic safety threshold or goal. In this paper, we examine data accumulated over the past 60 years from the space program, from nuclear reactor experience, from aircraft systems, and from human reliability experience to formulate guidelines for estimating probabilistic margins to account for risks that are initially unknown or underappreciated. The formulation includes a review of the safety literature to identify the principal causes of such risks.

Unsteady Probabilistic Analysis of a Gas Turbine System

NASA Technical Reports Server (NTRS)

Brown, Marilyn

2003-01-01

In this work, we have considered an annular cascade configuration subjected to unsteady inflow conditions. The unsteady response calculation has been implemented into the time marching CFD code, MSUTURBO. The computed steady state results for the pressure distribution demonstrated good agreement with experimental data. We have computed results for the amplitudes of the unsteady pressure over the blade surfaces. With the increase in gas turbine engine structural complexity and performance over the past 50 years, structural engineers have created an array of safety nets to ensure against component failures in turbine engines. In order to reduce what is now considered to be excessive conservatism and yet maintain the same adequate margins of safety, there is a pressing need to explore methods of incorporating probabilistic design procedures into engine development. Probabilistic methods combine and prioritize the statistical distributions of each design variable, generate an interactive distribution and offer the designer a quantified relationship between robustness, endurance and performance. The designer can therefore iterate between weight reduction, life increase, engine size reduction, speed increase etc.

Probabilistic Causal Analysis for System Safety Risk Assessments in Commercial Air Transport

NASA Technical Reports Server (NTRS)

Luxhoj, James T.

2003-01-01

Aviation is one of the critical modes of our national transportation system. As such, it is essential that new technologies be continually developed to ensure that a safe mode of transportation becomes even safer in the future. The NASA Aviation Safety Program (AvSP) is managing the development of new technologies and interventions aimed at reducing the fatal aviation accident rate by a factor of 5 by year 2007 and by a factor of 10 by year 2022. A portfolio assessment is currently being conducted to determine the projected impact that the new technologies and/or interventions may have on reducing aviation safety system risk. This paper reports on advanced risk analytics that combine the use of a human error taxonomy, probabilistic Bayesian Belief Networks, and case-based scenarios to assess a relative risk intensity metric. A sample case is used for illustrative purposes.

Probabilistic Aeroelastic Analysis Developed for Turbomachinery Components

NASA Technical Reports Server (NTRS)

Reddy, T. S. R.; Mital, Subodh K.; Stefko, George L.; Pai, Shantaram S.

2003-01-01

Aeroelastic analyses for advanced turbomachines are being developed for use at the NASA Glenn Research Center and industry. However, these analyses at present are used for turbomachinery design with uncertainties accounted for by using safety factors. This approach may lead to overly conservative designs, thereby reducing the potential of designing higher efficiency engines. An integration of the deterministic aeroelastic analysis methods with probabilistic analysis methods offers the potential to design efficient engines with fewer aeroelastic problems and to make a quantum leap toward designing safe reliable engines. In this research, probabilistic analysis is integrated with aeroelastic analysis: (1) to determine the parameters that most affect the aeroelastic characteristics (forced response and stability) of a turbomachine component such as a fan, compressor, or turbine and (2) to give the acceptable standard deviation on the design parameters for an aeroelastically stable system. The approach taken is to combine the aeroelastic analysis of the MISER (MIStuned Engine Response) code with the FPI (fast probability integration) code. The role of MISER is to provide the functional relationships that tie the structural and aerodynamic parameters (the primitive variables) to the forced response amplitudes and stability eigenvalues (the response properties). The role of FPI is to perform probabilistic analyses by utilizing the response properties generated by MISER. The results are a probability density function for the response properties. The probabilistic sensitivities of the response variables to uncertainty in primitive variables are obtained as a byproduct of the FPI technique. The combined analysis of aeroelastic and probabilistic analysis is applied to a 12-bladed cascade vibrating in bending and torsion. Out of the total 11 design parameters, 6 are considered as having probabilistic variation. The six parameters are space-to-chord ratio (SBYC), stagger angle (GAMA), elastic axis (ELAXS), Mach number (MACH), mass ratio (MASSR), and frequency ratio (WHWB). The cascade is considered to be in subsonic flow with Mach 0.7. The results of the probabilistic aeroelastic analysis are the probability density function of predicted aerodynamic damping and frequency for flutter and the response amplitudes for forced response.

A probabilistic safety analysis of incidents in nuclear research reactors.

PubMed

Lopes, Valdir Maciel; Agostinho Angelo Sordi, Gian Maria; Moralles, Mauricio; Filho, Tufic Madi

2012-06-01

This work aims to evaluate the potential risks of incidents in nuclear research reactors. For its development, two databases of the International Atomic Energy Agency (IAEA) were used: the Research Reactor Data Base (RRDB) and the Incident Report System for Research Reactor (IRSRR). For this study, the probabilistic safety analysis (PSA) was used. To obtain the result of the probability calculations for PSA, the theory and equations in the paper IAEA TECDOC-636 were used. A specific program to analyse the probabilities was developed within the main program, Scilab 5.1.1. for two distributions, Fischer and chi-square, both with the confidence level of 90 %. Using Sordi equations, the maximum admissible doses to compare with the risk limits established by the International Commission on Radiological Protection (ICRP) were obtained. All results achieved with this probability analysis led to the conclusion that the incidents which occurred had radiation doses within the stochastic effects reference interval established by the ICRP-64.

Proceedings of the international meeting on thermal nuclear reactor safety. Vol. 1

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

Separate abstracts are included for each of the papers presented concerning current issues in nuclear power plant safety; national programs in nuclear power plant safety; radiological source terms; probabilistic risk assessment methods and techniques; non LOCA and small-break-LOCA transients; safety goals; pressurized thermal shocks; applications of reliability and risk methods to probabilistic risk assessment; human factors and man-machine interface; and data bases and special applications.

Probabilistic modeling approach for evaluating the compliance of ready-to-eat foods with new European Union safety criteria for Listeria monocytogenes.

PubMed

Koutsoumanis, Konstantinos; Angelidis, Apostolos S

2007-08-01

Among the new microbiological criteria that have been incorporated in EU Regulation 2073/2005, of particular interest are those concerning Listeria monocytogenes in ready-to eat (RTE) foods, because for certain food categories, they no longer require zero tolerance but rather specify a maximum allowable concentration of 100 CFU/g or ml. This study presents a probabilistic modeling approach for evaluating the compliance of RTE sliced meat products with the new safety criteria for L. monocytogenes. The approach was based on the combined use of (i) growth/no growth boundary models, (ii) kinetic growth models, (iii) product characteristics data (pH, a(w), shelf life) collected from 160 meat products from the Hellenic retail market, and (iv) storage temperature data recorded from 50 retail stores in Greece. This study shows that probabilistic analysis of the above components using Monte Carlo simulation, which takes into account the variability of factors affecting microbial growth, can lead to a realistic estimation of the behavior of L. monocytogenes throughout the food supply chain, and the quantitative output generated can be further used by food managers as a decision-making tool regarding the design or modification of a product's formulation or its "use-by" date in order to ensure its compliance with the new safety criteria. The study also argues that compliance of RTE foods with the new safety criteria should not be considered a parameter with a discrete and binary outcome because it depends on factors such as product characteristics, storage temperature, and initial contamination level, which display considerable variability even among different packages of the same RTE product. Rather, compliance should be expressed and therefore regulated in a more probabilistic fashion.

Use of limited data to construct Bayesian networks for probabilistic risk assessment.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Groth, Katrina M.; Swiler, Laura Painton

2013-03-01

Probabilistic Risk Assessment (PRA) is a fundamental part of safety/quality assurance for nuclear power and nuclear weapons. Traditional PRA very effectively models complex hardware system risks using binary probabilistic models. However, traditional PRA models are not flexible enough to accommodate non-binary soft-causal factors, such as digital instrumentation&control, passive components, aging, common cause failure, and human errors. Bayesian Networks offer the opportunity to incorporate these risks into the PRA framework. This report describes the results of an early career LDRD project titled %E2%80%9CUse of Limited Data to Construct Bayesian Networks for Probabilistic Risk Assessment%E2%80%9D. The goal of the work was tomore » establish the capability to develop Bayesian Networks from sparse data, and to demonstrate this capability by producing a data-informed Bayesian Network for use in Human Reliability Analysis (HRA) as part of nuclear power plant Probabilistic Risk Assessment (PRA). This report summarizes the research goal and major products of the research.« less

Interrelation Between Safety Factors and Reliability

NASA Technical Reports Server (NTRS)

Elishakoff, Isaac; Chamis, Christos C. (Technical Monitor)

2001-01-01

An evaluation was performed to establish relationships between safety factors and reliability relationships. Results obtained show that the use of the safety factor is not contradictory to the employment of the probabilistic methods. In many cases the safety factors can be directly expressed by the required reliability levels. However, there is a major difference that must be emphasized: whereas the safety factors are allocated in an ad hoc manner, the probabilistic approach offers a unified mathematical framework. The establishment of the interrelation between the concepts opens an avenue to specify safety factors based on reliability. In cases where there are several forms of failure, then the allocation of safety factors should he based on having the same reliability associated with each failure mode. This immediately suggests that by the probabilistic methods the existing over-design or under-design can be eliminated. The report includes three parts: Part 1-Random Actual Stress and Deterministic Yield Stress; Part 2-Deterministic Actual Stress and Random Yield Stress; Part 3-Both Actual Stress and Yield Stress Are Random.

Estimating and controlling workplace risk: an approach for occupational hygiene and safety professionals.

PubMed

Toffel, Michael W; Birkner, Lawrence R

2002-07-01

The protection of people and physical assets is the objective of health and safety professionals and is accomplished through the paradigm of anticipation, recognition, evaluation, and control of risks in the occupational environment. Risk assessment concepts are not only used by health and safety professionals, but also by business and financial planners. Since meeting health and safety objectives requires financial resources provided by business and governmental managers, the hypothesis addressed here is that health and safety risk decisions should be made with probabilistic processes used in financial decision-making and which are familiar and recognizable to business and government planners and managers. This article develops the processes and demonstrates the use of incident probabilities, historic outcome information, and incremental impact analysis to estimate risk of multiple alternatives in the chemical process industry. It also analyzes how the ethical aspects of decision-making can be addressed in formulating health and safety risk management plans. It is concluded that certain, easily understood, and applied probabilistic risk assessment methods used by business and government to assess financial and outcome risk have applicability to improving workplace health and safety in three ways: 1) by linking the business and health and safety risk assessment processes to securing resources, 2) by providing an additional set of tools for health and safety risk assessment, and 3) by requiring the risk assessor to consider multiple risk management alternatives.

Why is Probabilistic Seismic Hazard Analysis (PSHA) still used?

NASA Astrophysics Data System (ADS)

Mulargia, Francesco; Stark, Philip B.; Geller, Robert J.

2017-03-01

Even though it has never been validated by objective testing, Probabilistic Seismic Hazard Analysis (PSHA) has been widely used for almost 50 years by governments and industry in applications with lives and property hanging in the balance, such as deciding safety criteria for nuclear power plants, making official national hazard maps, developing building code requirements, and determining earthquake insurance rates. PSHA rests on assumptions now known to conflict with earthquake physics; many damaging earthquakes, including the 1988 Spitak, Armenia, event and the 2011 Tohoku, Japan, event, have occurred in regions relatively rated low-risk by PSHA hazard maps. No extant method, including PSHA, produces reliable estimates of seismic hazard. Earthquake hazard mitigation should be recognized to be inherently political, involving a tradeoff between uncertain costs and uncertain risks. Earthquake scientists, engineers, and risk managers can make important contributions to the hard problem of allocating limited resources wisely, but government officials and stakeholders must take responsibility for the risks of accidents due to natural events that exceed the adopted safety criteria.

Towards Real-time, On-board, Hardware-Supported Sensor and Software Health Management for Unmanned Aerial Systems

NASA Technical Reports Server (NTRS)

Schumann, Johann; Rozier, Kristin Y.; Reinbacher, Thomas; Mengshoel, Ole J.; Mbaya, Timmy; Ippolito, Corey

2013-01-01

Unmanned aerial systems (UASs) can only be deployed if they can effectively complete their missions and respond to failures and uncertain environmental conditions while maintaining safety with respect to other aircraft as well as humans and property on the ground. In this paper, we design a real-time, on-board system health management (SHM) capability to continuously monitor sensors, software, and hardware components for detection and diagnosis of failures and violations of safety or performance rules during the flight of a UAS. Our approach to SHM is three-pronged, providing: (1) real-time monitoring of sensor and/or software signals; (2) signal analysis, preprocessing, and advanced on the- fly temporal and Bayesian probabilistic fault diagnosis; (3) an unobtrusive, lightweight, read-only, low-power realization using Field Programmable Gate Arrays (FPGAs) that avoids overburdening limited computing resources or costly re-certification of flight software due to instrumentation. Our implementation provides a novel approach of combining modular building blocks, integrating responsive runtime monitoring of temporal logic system safety requirements with model-based diagnosis and Bayesian network-based probabilistic analysis. We demonstrate this approach using actual data from the NASA Swift UAS, an experimental all-electric aircraft.

Aviation Safety Risk Modeling: Lessons Learned From Multiple Knowledge Elicitation Sessions

NASA Technical Reports Server (NTRS)

Luxhoj, J. T.; Ancel, E.; Green, L. L.; Shih, A. T.; Jones, S. M.; Reveley, M. S.

2014-01-01

Aviation safety risk modeling has elements of both art and science. In a complex domain, such as the National Airspace System (NAS), it is essential that knowledge elicitation (KE) sessions with domain experts be performed to facilitate the making of plausible inferences about the possible impacts of future technologies and procedures. This study discusses lessons learned throughout the multiple KE sessions held with domain experts to construct probabilistic safety risk models for a Loss of Control Accident Framework (LOCAF), FLightdeck Automation Problems (FLAP), and Runway Incursion (RI) mishap scenarios. The intent of these safety risk models is to support a portfolio analysis of NASA's Aviation Safety Program (AvSP). These models use the flexible, probabilistic approach of Bayesian Belief Networks (BBNs) and influence diagrams to model the complex interactions of aviation system risk factors. Each KE session had a different set of experts with diverse expertise, such as pilot, air traffic controller, certification, and/or human factors knowledge that was elicited to construct a composite, systems-level risk model. There were numerous "lessons learned" from these KE sessions that deal with behavioral aggregation, conditional probability modeling, object-oriented construction, interpretation of the safety risk results, and model verification/validation that are presented in this paper.

Integration of RAMS in LCC analysis for linear transport infrastructures. A case study for railways.

NASA Astrophysics Data System (ADS)

Calle-Cordón, Álvaro; Jiménez-Redondo, Noemi; Morales-Gámiz, F. J.; García-Villena, F. A.; Garmabaki, Amir H. S.; Odelius, Johan

2017-09-01

Life-cycle cost (LCC) analysis is an economic technique used to assess the total costs associated with the lifetime of a system in order to support decision making in long term strategic planning. For complex systems, such as railway and road infrastructures, the cost of maintenance plays an important role in the LCC analysis. Costs associated with maintenance interventions can be more reliably estimated by integrating the probabilistic nature of the failures associated to these interventions in the LCC models. Reliability, Maintainability, Availability and Safety (RAMS) parameters describe the maintenance needs of an asset in a quantitative way by using probabilistic information extracted from registered maintenance activities. Therefore, the integration of RAMS in the LCC analysis allows obtaining reliable predictions of system maintenance costs and the dependencies of these costs with specific cost drivers through sensitivity analyses. This paper presents an innovative approach for a combined RAMS & LCC methodology for railway and road transport infrastructures being developed under the on-going H2020 project INFRALERT. Such RAMS & LCC analysis provides relevant probabilistic information to be used for condition and risk-based planning of maintenance activities as well as for decision support in long term strategic investment planning.

Probabilistic safety analysis of earth retaining structures during earthquakes

NASA Astrophysics Data System (ADS)

Grivas, D. A.; Souflis, C.

1982-07-01

A procedure is presented for determining the probability of failure of Earth retaining structures under static or seismic conditions. Four possible modes of failure (overturning, base sliding, bearing capacity, and overall sliding) are examined and their combined effect is evaluated with the aid of combinatorial analysis. The probability of failure is shown to be a more adequate measure of safety than the customary factor of safety. As Earth retaining structures may fail in four distinct modes, a system analysis can provide a single estimate for the possibility of failure. A Bayesian formulation of the safety retaining walls is found to provide an improved measure for the predicted probability of failure under seismic loading. The presented Bayesian analysis can account for the damage incurred to a retaining wall during an earthquake to provide an improved estimate for its probability of failure during future seismic events.

Virtues and Limitations of Risk Analysis

ERIC Educational Resources Information Center

Weatherwax, Robert K.

1975-01-01

After summarizing the Rasmussion Report, the author reviews the probabilistic portion of the report from the perspectives of engineering utility and risk assessment uncertainty. The author shows that the report may represent a significant step forward in the assurance of reactor safety and an imperfect measure of actual reactor risk. (BT)

Intelligent Hardware-Enabled Sensor and Software Safety and Health Management for Autonomous UAS

NASA Technical Reports Server (NTRS)

Rozier, Kristin Y.; Schumann, Johann; Ippolito, Corey

2015-01-01

Unmanned Aerial Systems (UAS) can only be deployed if they can effectively complete their mission and respond to failures and uncertain environmental conditions while maintaining safety with respect to other aircraft as well as humans and property on the ground. We propose to design a real-time, onboard system health management (SHM) capability to continuously monitor essential system components such as sensors, software, and hardware systems for detection and diagnosis of failures and violations of safety or performance rules during the ight of a UAS. Our approach to SHM is three-pronged, providing: (1) real-time monitoring of sensor and software signals; (2) signal analysis, preprocessing, and advanced on-the- y temporal and Bayesian probabilistic fault diagnosis; (3) an unobtrusive, lightweight, read-only, low-power hardware realization using Field Programmable Gate Arrays (FPGAs) in order to avoid overburdening limited computing resources or costly re-certi cation of ight software due to instrumentation. No currently available SHM capabilities (or combinations of currently existing SHM capabilities) come anywhere close to satisfying these three criteria yet NASA will require such intelligent, hardwareenabled sensor and software safety and health management for introducing autonomous UAS into the National Airspace System (NAS). We propose a novel approach of creating modular building blocks for combining responsive runtime monitoring of temporal logic system safety requirements with model-based diagnosis and Bayesian network-based probabilistic analysis. Our proposed research program includes both developing this novel approach and demonstrating its capabilities using the NASA Swift UAS as a demonstration platform.

Integration of Advanced Probabilistic Analysis Techniques with Multi-Physics Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cetiner, Mustafa Sacit; none,; Flanagan, George F.

2014-07-30

An integrated simulation platform that couples probabilistic analysis-based tools with model-based simulation tools can provide valuable insights for reactive and proactive responses to plant operating conditions. The objective of this work is to demonstrate the benefits of a partial implementation of the Small Modular Reactor (SMR) Probabilistic Risk Assessment (PRA) Detailed Framework Specification through the coupling of advanced PRA capabilities and accurate multi-physics plant models. Coupling a probabilistic model with a multi-physics model will aid in design, operations, and safety by providing a more accurate understanding of plant behavior. This represents the first attempt at actually integrating these two typesmore » of analyses for a control system used for operations, on a faster than real-time basis. This report documents the development of the basic communication capability to exchange data with the probabilistic model using Reliability Workbench (RWB) and the multi-physics model using Dymola. The communication pathways from injecting a fault (i.e., failing a component) to the probabilistic and multi-physics models were successfully completed. This first version was tested with prototypic models represented in both RWB and Modelica. First, a simple event tree/fault tree (ET/FT) model was created to develop the software code to implement the communication capabilities between the dynamic-link library (dll) and RWB. A program, written in C#, successfully communicates faults to the probabilistic model through the dll. A systems model of the Advanced Liquid-Metal Reactor–Power Reactor Inherently Safe Module (ALMR-PRISM) design developed under another DOE project was upgraded using Dymola to include proper interfaces to allow data exchange with the control application (ConApp). A program, written in C+, successfully communicates faults to the multi-physics model. The results of the example simulation were successfully plotted.« less

Probabilistic assessment of wildfire hazard and municipal watershed exposure

Treesearch

Joe Scott; Don Helmbrecht; Matthew P. Thompson; David E. Calkin; Kate Marcille

2012-01-01

The occurrence of wildfires within municipal watersheds can result in significant impacts to water quality and ultimately human health and safety. In this paper, we illustrate the application of geospatial analysis and burn probability modeling to assess the exposure of municipal watersheds to wildfire. Our assessment of wildfire exposure consists of two primary...

Probabilistic migration modelling focused on functional barrier efficiency and low migration concepts in support of risk assessment.

PubMed

Brandsch, Rainer

2017-10-01

Migration modelling provides reliable migration estimates from food-contact materials (FCM) to food or food simulants based on mass-transfer parameters like diffusion and partition coefficients related to individual materials. In most cases, mass-transfer parameters are not readily available from the literature and for this reason are estimated with a given uncertainty. Historically, uncertainty was accounted for by introducing upper limit concepts first, turning out to be of limited applicability due to highly overestimated migration results. Probabilistic migration modelling gives the possibility to consider uncertainty of the mass-transfer parameters as well as other model inputs. With respect to a functional barrier, the most important parameters among others are the diffusion properties of the functional barrier and its thickness. A software tool that accepts distribution as inputs and is capable of applying Monte Carlo methods, i.e., random sampling from the input distributions of the relevant parameters (i.e., diffusion coefficient and layer thickness), predicts migration results with related uncertainty and confidence intervals. The capabilities of probabilistic migration modelling are presented in the view of three case studies (1) sensitivity analysis, (2) functional barrier efficiency and (3) validation by experimental testing. Based on the predicted migration by probabilistic migration modelling and related exposure estimates, safety evaluation of new materials in the context of existing or new packaging concepts is possible. Identifying associated migration risk and potential safety concerns in the early stage of packaging development is possible. Furthermore, dedicated material selection exhibiting required functional barrier efficiency under application conditions becomes feasible. Validation of the migration risk assessment by probabilistic migration modelling through a minimum of dedicated experimental testing is strongly recommended.

Probabilistic approach for decay heat uncertainty estimation using URANIE platform and MENDEL depletion code

NASA Astrophysics Data System (ADS)

Tsilanizara, A.; Gilardi, N.; Huynh, T. D.; Jouanne, C.; Lahaye, S.; Martinez, J. M.; Diop, C. M.

2014-06-01

The knowledge of the decay heat quantity and the associated uncertainties are important issues for the safety of nuclear facilities. Many codes are available to estimate the decay heat. ORIGEN, FISPACT, DARWIN/PEPIN2 are part of them. MENDEL is a new depletion code developed at CEA, with new software architecture, devoted to the calculation of physical quantities related to fuel cycle studies, in particular decay heat. The purpose of this paper is to present a probabilistic approach to assess decay heat uncertainty due to the decay data uncertainties from nuclear data evaluation like JEFF-3.1.1 or ENDF/B-VII.1. This probabilistic approach is based both on MENDEL code and URANIE software which is a CEA uncertainty analysis platform. As preliminary applications, single thermal fission of uranium 235, plutonium 239 and PWR UOx spent fuel cell are investigated.

Risk assessment of turbine rotor failure using probabilistic ultrasonic non-destructive evaluations

NASA Astrophysics Data System (ADS)

Guan, Xuefei; Zhang, Jingdan; Zhou, S. Kevin; Rasselkorde, El Mahjoub; Abbasi, Waheed A.

2014-02-01

The study presents a method and application of risk assessment methodology for turbine rotor fatigue failure using probabilistic ultrasonic nondestructive evaluations. A rigorous probabilistic modeling for ultrasonic flaw sizing is developed by incorporating the model-assisted probability of detection, and the probability density function (PDF) of the actual flaw size is derived. Two general scenarios, namely the ultrasonic inspection with an identified flaw indication and the ultrasonic inspection without flaw indication, are considered in the derivation. To perform estimations for fatigue reliability and remaining useful life, uncertainties from ultrasonic flaw sizing and fatigue model parameters are systematically included and quantified. The model parameter PDF is estimated using Bayesian parameter estimation and actual fatigue testing data. The overall method is demonstrated using a realistic application of steam turbine rotor, and the risk analysis under given safety criteria is provided to support maintenance planning.

Probabilistic analysis on the failure of reactivity control for the PWR

NASA Astrophysics Data System (ADS)

Sony Tjahyani, D. T.; Deswandri; Sunaryo, G. R.

2018-02-01

The fundamental safety function of the power reactor is to control reactivity, to remove heat from the reactor, and to confine radioactive material. The safety analysis is used to ensure that each parameter is fulfilled during the design and is done by deterministic and probabilistic method. The analysis of reactivity control is important to be done because it will affect the other of fundamental safety functions. The purpose of this research is to determine the failure probability of the reactivity control and its failure contribution on a PWR design. The analysis is carried out by determining intermediate events, which cause the failure of reactivity control. Furthermore, the basic event is determined by deductive method using the fault tree analysis. The AP1000 is used as the object of research. The probability data of component failure or human error, which is used in the analysis, is collected from IAEA, Westinghouse, NRC and other published documents. The results show that there are six intermediate events, which can cause the failure of the reactivity control. These intermediate events are uncontrolled rod bank withdrawal at low power or full power, malfunction of boron dilution, misalignment of control rod withdrawal, malfunction of improper position of fuel assembly and ejection of control rod. The failure probability of reactivity control is 1.49E-03 per year. The causes of failures which are affected by human factor are boron dilution, misalignment of control rod withdrawal and malfunction of improper position for fuel assembly. Based on the assessment, it is concluded that the failure probability of reactivity control on the PWR is still within the IAEA criteria.

NASA Applications and Lessons Learned in Reliability Engineering

NASA Technical Reports Server (NTRS)

Safie, Fayssal M.; Fuller, Raymond P.

2011-01-01

Since the Shuttle Challenger accident in 1986, communities across NASA have been developing and extensively using quantitative reliability and risk assessment methods in their decision making process. This paper discusses several reliability engineering applications that NASA has used over the year to support the design, development, and operation of critical space flight hardware. Specifically, the paper discusses several reliability engineering applications used by NASA in areas such as risk management, inspection policies, components upgrades, reliability growth, integrated failure analysis, and physics based probabilistic engineering analysis. In each of these areas, the paper provides a brief discussion of a case study to demonstrate the value added and the criticality of reliability engineering in supporting NASA project and program decisions to fly safely. Examples of these case studies discussed are reliability based life limit extension of Shuttle Space Main Engine (SSME) hardware, Reliability based inspection policies for Auxiliary Power Unit (APU) turbine disc, probabilistic structural engineering analysis for reliability prediction of the SSME alternate turbo-pump development, impact of ET foam reliability on the Space Shuttle System risk, and reliability based Space Shuttle upgrade for safety. Special attention is given in this paper to the physics based probabilistic engineering analysis applications and their critical role in evaluating the reliability of NASA development hardware including their potential use in a research and technology development environment.

Common problems in the elicitation and analysis of expert opinion affecting probabilistic safety assessments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Meyer, M.A.; Booker, J.M.

1990-01-01

Expert opinion is frequently used in probabilistic safety assessment (PSA), particularly in estimating low probability events. In this paper, we discuss some of the common problems encountered in eliciting and analyzing expert opinion data and offer solutions or recommendations. The problems are: that experts are not naturally Bayesian. People fail to update their existing information to account for new information as it becomes available, as would be predicted by the Bayesian philosophy; that experts cannot be fully calibrated. To calibrate experts, the feedback from the known quantities must be immediate, frequent, and specific to the task; that experts are limitedmore » in the number of things that they can mentally juggle at a time to 7 {plus minus} 2; that data gatherers and analysts can introduce bias by unintentionally causing an altering of the expert's thinking or answers; that the level of detail the data, or granularity, can affect the analyses; and the conditioning effect poses difficulties in gathering and analyzing of the expert data. The data that the expert gives can be conditioned on a variety of factors that can affect the analysis and the interpretation of the results. 31 refs.« less

Dynamic event tree analysis with the SAS4A/SASSYS-1 safety analysis code

DOE PAGES

Jankovsky, Zachary K.; Denman, Matthew R.; Aldemir, Tunc

2018-02-02

The consequences of a transient in an advanced sodium-cooled fast reactor are difficult to capture with the traditional approach to probabilistic risk assessment (PRA). Numerous safety-relevant systems are passive and may have operational states that cannot be represented by binary success or failure. In addition, the specific order and timing of events may be crucial which necessitates the use of dynamic PRA tools such as ADAPT. The modifications to the SAS4A/SASSYS-1 sodium-cooled fast reactor safety analysis code for linking it to ADAPT to perform a dynamic PRA are described. A test case is used to demonstrate the linking process andmore » to illustrate the type of insights that may be gained with this process. Finally, newly-developed dynamic importance measures are used to assess the significance of reactor parameters/constituents on calculated consequences of initiating events.« less

Dynamic event tree analysis with the SAS4A/SASSYS-1 safety analysis code

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jankovsky, Zachary K.; Denman, Matthew R.; Aldemir, Tunc

The consequences of a transient in an advanced sodium-cooled fast reactor are difficult to capture with the traditional approach to probabilistic risk assessment (PRA). Numerous safety-relevant systems are passive and may have operational states that cannot be represented by binary success or failure. In addition, the specific order and timing of events may be crucial which necessitates the use of dynamic PRA tools such as ADAPT. The modifications to the SAS4A/SASSYS-1 sodium-cooled fast reactor safety analysis code for linking it to ADAPT to perform a dynamic PRA are described. A test case is used to demonstrate the linking process andmore » to illustrate the type of insights that may be gained with this process. Finally, newly-developed dynamic importance measures are used to assess the significance of reactor parameters/constituents on calculated consequences of initiating events.« less

Interim reliability evaluation program, Browns Ferry 1

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mays, S.E.; Poloski, J.P.; Sullivan, W.H.

1981-01-01

Probabilistic risk analysis techniques, i.e., event tree and fault tree analysis, were utilized to provide a risk assessment of the Browns Ferry Nuclear Plant Unit 1. Browns Ferry 1 is a General Electric boiling water reactor of the BWR 4 product line with a Mark 1 (drywell and torus) containment. Within the guidelines of the IREP Procedure and Schedule Guide, dominant accident sequences that contribute to public health and safety risks were identified and grouped according to release categories.

Modeling of a Flooding Induced Station Blackout for a Pressurized Water Reactor Using the RISMC Toolkit

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mandelli, Diego; Prescott, Steven R; Smith, Curtis L

2011-07-01

In the Risk Informed Safety Margin Characterization (RISMC) approach we want to understand not just the frequency of an event like core damage, but how close we are (or are not) to key safety-related events and how might we increase our safety margins. The RISMC Pathway uses the probabilistic margin approach to quantify impacts to reliability and safety by coupling both probabilistic (via stochastic simulation) and mechanistic (via physics models) approaches. This coupling takes place through the interchange of physical parameters and operational or accident scenarios. In this paper we apply the RISMC approach to evaluate the impact of amore » power uprate on a pressurized water reactor (PWR) for a tsunami-induced flooding test case. This analysis is performed using the RISMC toolkit: RELAP-7 and RAVEN codes. RELAP-7 is the new generation of system analysis codes that is responsible for simulating the thermal-hydraulic dynamics of PWR and boiling water reactor systems. RAVEN has two capabilities: to act as a controller of the RELAP-7 simulation (e.g., system activation) and to perform statistical analyses (e.g., run multiple RELAP-7 simulations where sequencing/timing of events have been changed according to a set of stochastic distributions). By using the RISMC toolkit, we can evaluate how power uprate affects the system recovery measures needed to avoid core damage after the PWR lost all available AC power by a tsunami induced flooding. The simulation of the actual flooding is performed by using a smooth particle hydrodynamics code: NEUTRINO.« less

An Online Risk Monitor System (ORMS) to Increase Safety and Security Levels in Industry

NASA Astrophysics Data System (ADS)

Zubair, M.; Rahman, Khalil Ur; Hassan, Mehmood Ul

2013-12-01

The main idea of this research is to develop an Online Risk Monitor System (ORMS) based on Living Probabilistic Safety Assessment (LPSA). The article highlights the essential features and functions of ORMS. The basic models and modules such as, Reliability Data Update Model (RDUM), running time update, redundant system unavailability update, Engineered Safety Features (ESF) unavailability update and general system update have been described in this study. ORMS not only provides quantitative analysis but also highlights qualitative aspects of risk measures. ORMS is capable of automatically updating the online risk models and reliability parameters of equipment. ORMS can support in the decision making process of operators and managers in Nuclear Power Plants.

Nine steps to risk-informed wellhead protection and management: Methods and application to the Burgberg Catchment

NASA Astrophysics Data System (ADS)

Nowak, W.; Enzenhoefer, R.; Bunk, T.

2013-12-01

Wellhead protection zones are commonly delineated via advective travel time analysis without considering any aspects of model uncertainty. In the past decade, research efforts produced quantifiable risk-based safety margins for protection zones. They are based on well vulnerability criteria (e.g., travel times, exposure times, peak concentrations) cast into a probabilistic setting, i.e., they consider model and parameter uncertainty. Practitioners still refrain from applying these new techniques for mainly three reasons. (1) They fear the possibly cost-intensive additional areal demand of probabilistic safety margins, (2) probabilistic approaches are allegedly complex, not readily available, and consume huge computing resources, and (3) uncertainty bounds are fuzzy, whereas final decisions are binary. The primary goal of this study is to show that these reservations are unjustified. We present a straightforward and computationally affordable framework based on a novel combination of well-known tools (e.g., MODFLOW, PEST, Monte Carlo). This framework provides risk-informed decision support for robust and transparent wellhead delineation under uncertainty. Thus, probabilistic risk-informed wellhead protection is possible with methods readily available for practitioners. As vivid proof of concept, we illustrate our key points on a pumped karstic well catchment, located in Germany. In the case study, we show that reliability levels can be increased by re-allocating the existing delineated area at no increase in delineated area. This is achieved by simply swapping delineated low-risk areas against previously non-delineated high-risk areas. Also, we show that further improvements may often be available at only low additional delineation area. Depending on the context, increases or reductions of delineated area directly translate to costs and benefits, if the land is priced, or if land owners need to be compensated for land use restrictions.

Nonlinear analysis of NPP safety against the aircraft attack

DOE Office of Scientific and Technical Information (OSTI.GOV)

Králik, Juraj, E-mail: juraj.kralik@stuba.sk; Králik, Juraj, E-mail: kralik@fa.stuba.sk

The paper presents the nonlinear probabilistic analysis of the reinforced concrete buildings of nuclear power plant under the aircraft attack. The dynamic load is defined in time on base of the airplane impact simulations considering the real stiffness, masses, direction and velocity of the flight. The dynamic response is calculated in the system ANSYS using the transient nonlinear analysis solution method. The damage of the concrete wall is evaluated in accordance with the standard NDRC considering the spalling, scabbing and perforation effects. The simple and detailed calculations of the wall damage are compared.

The ARGO Project: assessing NA-TECH risks on off-shore oil platforms

NASA Astrophysics Data System (ADS)

Capuano, Paolo; Basco, Anna; Di Ruocco, Angela; Esposito, Simona; Fusco, Giannetta; Garcia-Aristizabal, Alexander; Mercogliano, Paola; Salzano, Ernesto; Solaro, Giuseppe; Teofilo, Gianvito; Scandone, Paolo; Gasparini, Paolo

2017-04-01

ARGO (Analysis of natural and anthropogenic risks on off-shore oil platforms) is a 2 years project, funded by the DGS-UNMIG (Directorate General for Safety of Mining and Energy Activities - National Mining Office for Hydrocarbons and Georesources) of Italian Ministry of Economic Development. The project, coordinated by AMRA (Center for the Analysis and Monitoring of Environmental Risk), aims at providing technical support for the analysis of natural and anthropogenic risks on offshore oil platforms. In order to achieve this challenging objective, ARGO brings together climate experts, risk management experts, seismologists, geologists, chemical engineers, earth and coastal observation experts. ARGO has developed methodologies for the probabilistic analysis of industrial accidents triggered by natural events (NA-TECH) on offshore oil platforms in the Italian seas, including extreme events related to climate changes. Furthermore the environmental effect of offshore activities has been investigated, including: changes on seismicity and on the evolution of coastal areas close to offshore platforms. Then a probabilistic multi-risk framework has been developed for the analysis of NA-TECH events on offshore installations for hydrocarbon extraction.

A Flexible Hierarchical Bayesian Modeling Technique for Risk Analysis of Major Accidents.

PubMed

Yu, Hongyang; Khan, Faisal; Veitch, Brian

2017-09-01

Safety analysis of rare events with potentially catastrophic consequences is challenged by data scarcity and uncertainty. Traditional causation-based approaches, such as fault tree and event tree (used to model rare event), suffer from a number of weaknesses. These include the static structure of the event causation, lack of event occurrence data, and need for reliable prior information. In this study, a new hierarchical Bayesian modeling based technique is proposed to overcome these drawbacks. The proposed technique can be used as a flexible technique for risk analysis of major accidents. It enables both forward and backward analysis in quantitative reasoning and the treatment of interdependence among the model parameters. Source-to-source variability in data sources is also taken into account through a robust probabilistic safety analysis. The applicability of the proposed technique has been demonstrated through a case study in marine and offshore industry. © 2017 Society for Risk Analysis.

Study on the evaluation method for fault displacement based on characterized source model

NASA Astrophysics Data System (ADS)

Tonagi, M.; Takahama, T.; Matsumoto, Y.; Inoue, N.; Irikura, K.; Dalguer, L. A.

2016-12-01

In IAEA Specific Safety Guide (SSG) 9 describes that probabilistic methods for evaluating fault displacement should be used if no sufficient basis is provided to decide conclusively that the fault is not capable by using the deterministic methodology. In addition, International Seismic Safety Centre compiles as ANNEX to realize seismic hazard for nuclear facilities described in SSG-9 and shows the utility of the deterministic and probabilistic evaluation methods for fault displacement. In Japan, it is required that important nuclear facilities should be established on ground where fault displacement will not arise when earthquakes occur in the future. Under these situations, based on requirements, we need develop evaluation methods for fault displacement to enhance safety in nuclear facilities. We are studying deterministic and probabilistic methods with tentative analyses using observed records such as surface fault displacement and near-fault strong ground motions of inland crustal earthquake which fault displacements arose. In this study, we introduce the concept of evaluation methods for fault displacement. After that, we show parts of tentative analysis results for deterministic method as follows: (1) For the 1999 Chi-Chi earthquake, referring slip distribution estimated by waveform inversion, we construct a characterized source model (Miyake et al., 2003, BSSA) which can explain observed near-fault broad band strong ground motions. (2) Referring a characterized source model constructed in (1), we study an evaluation method for surface fault displacement using hybrid method, which combines particle method and distinct element method. At last, we suggest one of the deterministic method to evaluate fault displacement based on characterized source model. This research was part of the 2015 research project `Development of evaluating method for fault displacement` by the Secretariat of Nuclear Regulation Authority (S/NRA), Japan.

Risk-based Spacecraft Fire Safety Experiments

NASA Technical Reports Server (NTRS)

Apostolakis, G.; Catton, I.; Issacci, F.; Paulos, T.; Jones, S.; Paxton, K.; Paul, M.

1992-01-01

Viewgraphs on risk-based spacecraft fire safety experiments are presented. Spacecraft fire risk can never be reduced to a zero probability. Probabilistic risk assessment is a tool to reduce risk to an acceptable level.

Dynamic Positioning System (DPS) Risk Analysis Using Probabilistic Risk Assessment (PRA)

NASA Technical Reports Server (NTRS)

Thigpen, Eric B.; Boyer, Roger L.; Stewart, Michael A.; Fougere, Pete

2017-01-01

The National Aeronautics and Space Administration (NASA) Safety & Mission Assurance (S&MA) directorate at the Johnson Space Center (JSC) has applied its knowledge and experience with Probabilistic Risk Assessment (PRA) to projects in industries ranging from spacecraft to nuclear power plants. PRA is a comprehensive and structured process for analyzing risk in complex engineered systems and/or processes. The PRA process enables the user to identify potential risk contributors such as, hardware and software failure, human error, and external events. Recent developments in the oil and gas industry have presented opportunities for NASA to lend their PRA expertise to both ongoing and developmental projects within the industry. This paper provides an overview of the PRA process and demonstrates how this process was applied in estimating the probability that a Mobile Offshore Drilling Unit (MODU) operating in the Gulf of Mexico and equipped with a generically configured Dynamic Positioning System (DPS) loses location and needs to initiate an emergency disconnect. The PRA described in this paper is intended to be generic such that the vessel meets the general requirements of an International Maritime Organization (IMO) Maritime Safety Committee (MSC)/Circ. 645 Class 3 dynamically positioned vessel. The results of this analysis are not intended to be applied to any specific drilling vessel, although provisions were made to allow the analysis to be configured to a specific vessel if required.

Adequacy of the default values for skin surface area used for risk assessment and French anthropometric data by a probabilistic approach.

PubMed

Dornic, N; Ficheux, A S; Bernard, A; Roudot, A C

2017-08-01

The notes of guidance for the testing of cosmetic ingredients and their safety evaluation by the Scientific Committee on Consumer Safety (SCCS) is a document dedicated to ensuring the safety of European consumers. This contains useful data for risk assessment such as default values for Skin Surface Area (SSA). A more in-depth study of anthropometric data across Europe reveals considerable variations. The default SSA value was derived from a study on the Dutch population, which is known to be one of the tallest nations in the World. This value could be inadequate for shorter populations of Europe. Data were collected in a survey on cosmetic consumption in France. Probabilistic treatment of these data and analysis of the case of methylisothiazolinone, a sensitizer recently evaluated by a deterministic approach submitted to SCCS, suggest that the default value for SSA used in the quantitative risk assessment might not be relevant for a significant share of the French female population. Others female populations of Southern Europe may also be excluded. This is of importance given that some studies show an increasing risk of developping skin sensitization among women. The disparities in anthropometric data across Europe should be taken into consideration. Copyright © 2017 Elsevier Ltd. All rights reserved.

Probabilistic structural analysis methods for space propulsion system components

NASA Technical Reports Server (NTRS)

Chamis, C. C.

1986-01-01

The development of a three-dimensional inelastic analysis methodology for the Space Shuttle main engine (SSME) structural components is described. The methodology is composed of: (1) composite load spectra, (2) probabilistic structural analysis methods, (3) the probabilistic finite element theory, and (4) probabilistic structural analysis. The methodology has led to significant technical progress in several important aspects of probabilistic structural analysis. The program and accomplishments to date are summarized.

Probabilistic exposure assessment to face and oral care cosmetic products by the French population.

PubMed

Bernard, A; Dornic, N; Roudot, Ac; Ficheux, As

2018-01-01

Cosmetic exposure data for face and mouth are limited in Europe. The aim of the study was to assess the exposure to face cosmetics using recent French consumption data (Ficheux et al., 2016b, 2015). Exposure was assessed using a probabilistic method for thirty one face products from four lines of products: cleanser, care, make-up and make-up remover products and two oral care products. Probabilistic exposure was assessed for different subpopulation according to sex and age in adults and children. Pregnant women were also studied. The levels of exposure to moisturizing cream, lip balm, mascara, eyeliner, cream foundation, toothpaste and mouthwash were higher than the values currently used by the Scientific Committee on Consumer Safety (SCCS). Exposure values found for eye shadow, lipstick, lotion and milk (make-up remover) were lower than SCCS values. These new French exposure values will be useful for safety assessors and for safety agencies in order to protect the general population and the at risk populations. Copyright © 2017. Published by Elsevier Ltd.

Safety Issues at the DOE Test and Research Reactors. A Report to the U.S. Department of Energy.

ERIC Educational Resources Information Center

National Academy of Sciences - National Research Council, Washington, DC. Commission on Physical Sciences, Mathematics, and Resources.

This report provides an assessment of safety issues at the Department of Energy (DOE) test and research reactors. Part A identifies six safety issues of the reactors. These issues include the safety design philosophy, the conduct of safety reviews, the performance of probabilistic risk assessments, the reliance on reactor operators, the fragmented…

Risk analysis of Safety Service Patrol (SSP) systems in Virginia.

PubMed

Dickey, Brett D; Santos, Joost R

2011-12-01

The transportation infrastructure is a vital backbone of any regional economy as it supports workforce mobility, tourism, and a host of socioeconomic activities. In this article, we specifically examine the incident management function of the transportation infrastructure. In many metropolitan regions, incident management is handled primarily by safety service patrols (SSPs), which monitor and resolve roadway incidents. In Virginia, SSP allocation across highway networks is based typically on average vehicle speeds and incident volumes. This article implements a probabilistic network model that partitions "business as usual" traffic flow with extreme-event scenarios. Results of simulated network scenarios reveal that flexible SSP configurations can improve incident resolution times relative to predetermined SSP assignments. © 2011 Society for Risk Analysis.

Hazard Analysis and Safety Requirements for Small Drone Operations: To What Extent Do Popular Drones Embed Safety?

PubMed

Plioutsias, Anastasios; Karanikas, Nektarios; Chatzimihailidou, Maria Mikela

2018-03-01

Currently, published risk analyses for drones refer mainly to commercial systems, use data from civil aviation, and are based on probabilistic approaches without suggesting an inclusive list of hazards and respective requirements. Within this context, this article presents: (1) a set of safety requirements generated from the application of the systems theoretic process analysis (STPA) technique on a generic small drone system; (2) a gap analysis between the set of safety requirements and the ones met by 19 popular drone models; (3) the extent of the differences between those models, their manufacturers, and the countries of origin; and (4) the association of drone prices with the extent they meet the requirements derived by STPA. The application of STPA resulted in 70 safety requirements distributed across the authority, manufacturer, end user, or drone automation levels. A gap analysis showed high dissimilarities regarding the extent to which the 19 drones meet the same safety requirements. Statistical results suggested a positive correlation between drone prices and the extent that the 19 drones studied herein met the safety requirements generated by STPA, and significant differences were identified among the manufacturers. This work complements the existing risk assessment frameworks for small drones, and contributes to the establishment of a commonly endorsed international risk analysis framework. Such a framework will support the development of a holistic and methodologically justified standardization scheme for small drone flights. © 2017 Society for Risk Analysis.

Probabilistic assessment of roadway departure risk in a curve

NASA Astrophysics Data System (ADS)

Rey, G.; Clair, D.; Fogli, M.; Bernardin, F.

2011-10-01

Roadway departure while cornering constitutes a major part of car accidents and casualties in France. Even though drastic policy about overspeeding contributes to reduce accidents, there obviously exist other factors. This article presents the construction of a probabilistic strategy for the roadway departure risk assessment. A specific vehicle dynamic model is developed in which some parameters are modelled by random variables. These parameters are deduced from a sensitivity analysis to ensure an efficient representation of the inherent uncertainties of the system. Then, structural reliability methods are employed to assess the roadway departure risk in function of the initial conditions measured at the entrance of the curve. This study is conducted within the French national road safety project SARI that aims to implement a warning systems alerting the driver in case of dangerous situation.

A probabilistic bridge safety evaluation against floods.

PubMed

Liao, Kuo-Wei; Muto, Yasunori; Chen, Wei-Lun; Wu, Bang-Ho

2016-01-01

To further capture the influences of uncertain factors on river bridge safety evaluation, a probabilistic approach is adopted. Because this is a systematic and nonlinear problem, MPP-based reliability analyses are not suitable. A sampling approach such as a Monte Carlo simulation (MCS) or importance sampling is often adopted. To enhance the efficiency of the sampling approach, this study utilizes Bayesian least squares support vector machines to construct a response surface followed by an MCS, providing a more precise safety index. Although there are several factors impacting the flood-resistant reliability of a bridge, previous experiences and studies show that the reliability of the bridge itself plays a key role. Thus, the goal of this study is to analyze the system reliability of a selected bridge that includes five limit states. The random variables considered here include the water surface elevation, water velocity, local scour depth, soil property and wind load. Because the first three variables are deeply affected by river hydraulics, a probabilistic HEC-RAS-based simulation is performed to capture the uncertainties in those random variables. The accuracy and variation of our solutions are confirmed by a direct MCS to ensure the applicability of the proposed approach. The results of a numerical example indicate that the proposed approach can efficiently provide an accurate bridge safety evaluation and maintain satisfactory variation.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bucknor, Matthew; Grabaskas, David; Brunett, Acacia J.

We report that many advanced reactor designs rely on passive systems to fulfill safety functions during accident sequences. These systems depend heavily on boundary conditions to induce a motive force, meaning the system can fail to operate as intended because of deviations in boundary conditions, rather than as the result of physical failures. Furthermore, passive systems may operate in intermediate or degraded modes. These factors make passive system operation difficult to characterize within a traditional probabilistic framework that only recognizes discrete operating modes and does not allow for the explicit consideration of time-dependent boundary conditions. Argonne National Laboratory has beenmore » examining various methodologies for assessing passive system reliability within a probabilistic risk assessment for a station blackout event at an advanced small modular reactor. This paper provides an overview of a passive system reliability demonstration analysis for an external event. Considering an earthquake with the possibility of site flooding, the analysis focuses on the behavior of the passive Reactor Cavity Cooling System following potential physical damage and system flooding. The assessment approach seeks to combine mechanistic and simulation-based methods to leverage the benefits of the simulation-based approach without the need to substantially deviate from conventional probabilistic risk assessment techniques. Lastly, although this study is presented as only an example analysis, the results appear to demonstrate a high level of reliability of the Reactor Cavity Cooling System (and the reactor system in general) for the postulated transient event.« less

Initiating Event Analysis of a Lithium Fluoride Thorium Reactor

NASA Astrophysics Data System (ADS)

Geraci, Nicholas Charles

The primary purpose of this study is to perform an Initiating Event Analysis for a Lithium Fluoride Thorium Reactor (LFTR) as the first step of a Probabilistic Safety Assessment (PSA). The major objective of the research is to compile a list of key initiating events capable of resulting in failure of safety systems and release of radioactive material from the LFTR. Due to the complex interactions between engineering design, component reliability and human reliability, probabilistic safety assessments are most useful when the scope is limited to a single reactor plant. Thus, this thesis will study the LFTR design proposed by Flibe Energy. An October 2015 Electric Power Research Institute report on the Flibe Energy LFTR asked "what-if?" questions of subject matter experts and compiled a list of key hazards with the most significant consequences to the safety or integrity of the LFTR. The potential exists for unforeseen hazards to pose additional risk for the LFTR, but the scope of this thesis is limited to evaluation of those key hazards already identified by Flibe Energy. These key hazards are the starting point for the Initiating Event Analysis performed in this thesis. Engineering evaluation and technical study of the plant using a literature review and comparison to reference technology revealed four hazards with high potential to cause reactor core damage. To determine the initiating events resulting in realization of these four hazards, reference was made to previous PSAs and existing NRC and EPRI initiating event lists. Finally, fault tree and event tree analyses were conducted, completing the logical classification of initiating events. Results are qualitative as opposed to quantitative due to the early stages of system design descriptions and lack of operating experience or data for the LFTR. In summary, this thesis analyzes initiating events using previous research and inductive and deductive reasoning through traditional risk management techniques to arrive at a list of key initiating events that can be used to address vulnerabilities during the design phases of LFTR development.

Probabilistic Structural Analysis and Reliability Using NESSUS With Implemented Material Strength Degradation Model

NASA Technical Reports Server (NTRS)

Bast, Callie C.; Jurena, Mark T.; Godines, Cody R.; Chamis, Christos C. (Technical Monitor)

2001-01-01

This project included both research and education objectives. The goal of this project was to advance innovative research and education objectives in theoretical and computational probabilistic structural analysis, reliability, and life prediction for improved reliability and safety of structural components of aerospace and aircraft propulsion systems. Research and education partners included Glenn Research Center (GRC) and Southwest Research Institute (SwRI) along with the University of Texas at San Antonio (UTSA). SwRI enhanced the NESSUS (Numerical Evaluation of Stochastic Structures Under Stress) code and provided consulting support for NESSUS-related activities at UTSA. NASA funding supported three undergraduate students, two graduate students, a summer course instructor and the Principal Investigator. Matching funds from UTSA provided for the purchase of additional equipment for the enhancement of the Advanced Interactive Computational SGI Lab established during the first year of this Partnership Award to conduct the probabilistic finite element summer courses. The research portion of this report presents the cumulation of work performed through the use of the probabilistic finite element program, NESSUS, Numerical Evaluation and Structures Under Stress, and an embedded Material Strength Degradation (MSD) model. Probabilistic structural analysis provided for quantification of uncertainties associated with the design, thus enabling increased system performance and reliability. The structure examined was a Space Shuttle Main Engine (SSME) fuel turbopump blade. The blade material analyzed was Inconel 718, since the MSD model was previously calibrated for this material. Reliability analysis encompassing the effects of high temperature and high cycle fatigue, yielded a reliability value of 0.99978 using a fully correlated random field for the blade thickness. The reliability did not change significantly for a change in distribution type except for a change in distribution from Gaussian to Weibull for the centrifugal load. The sensitivity factors determined to be most dominant were the centrifugal loading and the initial strength of the material. These two sensitivity factors were influenced most by a change in distribution type from Gaussian to Weibull. The education portion of this report describes short-term and long-term educational objectives. Such objectives serve to integrate research and education components of this project resulting in opportunities for ethnic minority students, principally Hispanic. The primary vehicle to facilitate such integration was the teaching of two probabilistic finite element method courses to undergraduate engineering students in the summers of 1998 and 1999.

Is probabilistic bias analysis approximately Bayesian?

PubMed Central

MacLehose, Richard F.; Gustafson, Paul

2011-01-01

Case-control studies are particularly susceptible to differential exposure misclassification when exposure status is determined following incident case status. Probabilistic bias analysis methods have been developed as ways to adjust standard effect estimates based on the sensitivity and specificity of exposure misclassification. The iterative sampling method advocated in probabilistic bias analysis bears a distinct resemblance to a Bayesian adjustment; however, it is not identical. Furthermore, without a formal theoretical framework (Bayesian or frequentist), the results of a probabilistic bias analysis remain somewhat difficult to interpret. We describe, both theoretically and empirically, the extent to which probabilistic bias analysis can be viewed as approximately Bayesian. While the differences between probabilistic bias analysis and Bayesian approaches to misclassification can be substantial, these situations often involve unrealistic prior specifications and are relatively easy to detect. Outside of these special cases, probabilistic bias analysis and Bayesian approaches to exposure misclassification in case-control studies appear to perform equally well. PMID:22157311

Advanced Reactor Passive System Reliability Demonstration Analysis for an External Event

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bucknor, Matthew D.; Grabaskas, David; Brunett, Acacia J.

2016-01-01

Many advanced reactor designs rely on passive systems to fulfill safety functions during accident sequences. These systems depend heavily on boundary conditions to induce a motive force, meaning the system can fail to operate as intended due to deviations in boundary conditions, rather than as the result of physical failures. Furthermore, passive systems may operate in intermediate or degraded modes. These factors make passive system operation difficult to characterize within a traditional probabilistic framework that only recognizes discrete operating modes and does not allow for the explicit consideration of time-dependent boundary conditions. Argonne National Laboratory has been examining various methodologiesmore » for assessing passive system reliability within a probabilistic risk assessment for a station blackout event at an advanced small modular reactor. This paper provides an overview of a passive system reliability demonstration analysis for an external event. Centering on an earthquake with the possibility of site flooding, the analysis focuses on the behavior of the passive reactor cavity cooling system following potential physical damage and system flooding. The assessment approach seeks to combine mechanistic and simulation-based methods to leverage the benefits of the simulation-based approach without the need to substantially deviate from conventional probabilistic risk assessment techniques. While this study is presented as only an example analysis, the results appear to demonstrate a high level of reliability for the reactor cavity cooling system (and the reactor system in general) to the postulated transient event.« less

Advanced Reactor Passive System Reliability Demonstration Analysis for an External Event

DOE PAGES

Bucknor, Matthew; Grabaskas, David; Brunett, Acacia J.; ...

2017-01-24

We report that many advanced reactor designs rely on passive systems to fulfill safety functions during accident sequences. These systems depend heavily on boundary conditions to induce a motive force, meaning the system can fail to operate as intended because of deviations in boundary conditions, rather than as the result of physical failures. Furthermore, passive systems may operate in intermediate or degraded modes. These factors make passive system operation difficult to characterize within a traditional probabilistic framework that only recognizes discrete operating modes and does not allow for the explicit consideration of time-dependent boundary conditions. Argonne National Laboratory has beenmore » examining various methodologies for assessing passive system reliability within a probabilistic risk assessment for a station blackout event at an advanced small modular reactor. This paper provides an overview of a passive system reliability demonstration analysis for an external event. Considering an earthquake with the possibility of site flooding, the analysis focuses on the behavior of the passive Reactor Cavity Cooling System following potential physical damage and system flooding. The assessment approach seeks to combine mechanistic and simulation-based methods to leverage the benefits of the simulation-based approach without the need to substantially deviate from conventional probabilistic risk assessment techniques. Lastly, although this study is presented as only an example analysis, the results appear to demonstrate a high level of reliability of the Reactor Cavity Cooling System (and the reactor system in general) for the postulated transient event.« less

Probabilistic framework for product design optimization and risk management

NASA Astrophysics Data System (ADS)

Keski-Rahkonen, J. K.

2018-05-01

Probabilistic methods have gradually gained ground within engineering practices but currently it is still the industry standard to use deterministic safety margin approaches to dimensioning components and qualitative methods to manage product risks. These methods are suitable for baseline design work but quantitative risk management and product reliability optimization require more advanced predictive approaches. Ample research has been published on how to predict failure probabilities for mechanical components and furthermore to optimize reliability through life cycle cost analysis. This paper reviews the literature for existing methods and tries to harness their best features and simplify the process to be applicable in practical engineering work. Recommended process applies Monte Carlo method on top of load-resistance models to estimate failure probabilities. Furthermore, it adds on existing literature by introducing a practical framework to use probabilistic models in quantitative risk management and product life cycle costs optimization. The main focus is on mechanical failure modes due to the well-developed methods used to predict these types of failures. However, the same framework can be applied on any type of failure mode as long as predictive models can be developed.

Cost-effectiveness analysis of risk-reduction measures to reach water safety targets.

PubMed

Lindhe, Andreas; Rosén, Lars; Norberg, Tommy; Bergstedt, Olof; Pettersson, Thomas J R

2011-01-01

Identifying the most suitable risk-reduction measures in drinking water systems requires a thorough analysis of possible alternatives. In addition to the effects on the risk level, also the economic aspects of the risk-reduction alternatives are commonly considered important. Drinking water supplies are complex systems and to avoid sub-optimisation of risk-reduction measures, the entire system from source to tap needs to be considered. There is a lack of methods for quantification of water supply risk reduction in an economic context for entire drinking water systems. The aim of this paper is to present a novel approach for risk assessment in combination with economic analysis to evaluate risk-reduction measures based on a source-to-tap approach. The approach combines a probabilistic and dynamic fault tree method with cost-effectiveness analysis (CEA). The developed approach comprises the following main parts: (1) quantification of risk reduction of alternatives using a probabilistic fault tree model of the entire system; (2) combination of the modelling results with CEA; and (3) evaluation of the alternatives with respect to the risk reduction, the probability of not reaching water safety targets and the cost-effectiveness. The fault tree method and CEA enable comparison of risk-reduction measures in the same quantitative unit and consider costs and uncertainties. The approach provides a structured and thorough analysis of risk-reduction measures that facilitates transparency and long-term planning of drinking water systems in order to avoid sub-optimisation of available resources for risk reduction. Copyright © 2010 Elsevier Ltd. All rights reserved.

Probabilistic structural analysis methods for select space propulsion system components

NASA Technical Reports Server (NTRS)

Millwater, H. R.; Cruse, T. A.

1989-01-01

The Probabilistic Structural Analysis Methods (PSAM) project developed at the Southwest Research Institute integrates state-of-the-art structural analysis techniques with probability theory for the design and analysis of complex large-scale engineering structures. An advanced efficient software system (NESSUS) capable of performing complex probabilistic analysis has been developed. NESSUS contains a number of software components to perform probabilistic analysis of structures. These components include: an expert system, a probabilistic finite element code, a probabilistic boundary element code and a fast probability integrator. The NESSUS software system is shown. An expert system is included to capture and utilize PSAM knowledge and experience. NESSUS/EXPERT is an interactive menu-driven expert system that provides information to assist in the use of the probabilistic finite element code NESSUS/FEM and the fast probability integrator (FPI). The expert system menu structure is summarized. The NESSUS system contains a state-of-the-art nonlinear probabilistic finite element code, NESSUS/FEM, to determine the structural response and sensitivities. A broad range of analysis capabilities and an extensive element library is present.

Wind effects on long-span bridges: Probabilistic wind data format for buffeting and VIV load assessments

NASA Astrophysics Data System (ADS)

Hoffmann, K.; Srouji, R. G.; Hansen, S. O.

2017-12-01

The technology development within the structural design of long-span bridges in Norwegian fjords has created a need for reformulating the calculation format and the physical quantities used to describe the properties of wind and the associated wind-induced effects on bridge decks. Parts of a new probabilistic format describing the incoming, undisturbed wind is presented. It is expected that a fixed probabilistic format will facilitate a more physically consistent and precise description of the wind conditions, which in turn increase the accuracy and considerably reduce uncertainties in wind load assessments. Because the format is probabilistic, a quantification of the level of safety and uncertainty in predicted wind loads is readily accessible. A simple buffeting response calculation demonstrates the use of probabilistic wind data in the assessment of wind loads and responses. Furthermore, vortex-induced fatigue damage is discussed in relation to probabilistic wind turbulence data and response measurements from wind tunnel tests.

Safety and integrity of pipeline systems - philosophy and experience in Germany

DOT National Transportation Integrated Search

1997-01-01

The design, construction and operation of gas pipeline systems in Germany are subject to the Energy Act and associated regulations. This legal structure is based on a deterministic rather than a probabilistic safety philosophy, consisting of technica...

Johnson Space Center's Risk and Reliability Analysis Group 2008 Annual Report

NASA Technical Reports Server (NTRS)

Valentine, Mark; Boyer, Roger; Cross, Bob; Hamlin, Teri; Roelant, Henk; Stewart, Mike; Bigler, Mark; Winter, Scott; Reistle, Bruce; Heydorn,Dick

2009-01-01

The Johnson Space Center (JSC) Safety & Mission Assurance (S&MA) Directorate s Risk and Reliability Analysis Group provides both mathematical and engineering analysis expertise in the areas of Probabilistic Risk Assessment (PRA), Reliability and Maintainability (R&M) analysis, and data collection and analysis. The fundamental goal of this group is to provide National Aeronautics and Space Administration (NASA) decisionmakers with the necessary information to make informed decisions when evaluating personnel, flight hardware, and public safety concerns associated with current operating systems as well as with any future systems. The Analysis Group includes a staff of statistical and reliability experts with valuable backgrounds in the statistical, reliability, and engineering fields. This group includes JSC S&MA Analysis Branch personnel as well as S&MA support services contractors, such as Science Applications International Corporation (SAIC) and SoHaR. The Analysis Group s experience base includes nuclear power (both commercial and navy), manufacturing, Department of Defense, chemical, and shipping industries, as well as significant aerospace experience specifically in the Shuttle, International Space Station (ISS), and Constellation Programs. The Analysis Group partners with project and program offices, other NASA centers, NASA contractors, and universities to provide additional resources or information to the group when performing various analysis tasks. The JSC S&MA Analysis Group is recognized as a leader in risk and reliability analysis within the NASA community. Therefore, the Analysis Group is in high demand to help the Space Shuttle Program (SSP) continue to fly safely, assist in designing the next generation spacecraft for the Constellation Program (CxP), and promote advanced analytical techniques. The Analysis Section s tasks include teaching classes and instituting personnel qualification processes to enhance the professional abilities of our analysts as well as performing major probabilistic assessments used to support flight rationale and help establish program requirements. During 2008, the Analysis Group performed more than 70 assessments. Although all these assessments were important, some were instrumental in the decisionmaking processes for the Shuttle and Constellation Programs. Two of the more significant tasks were the Space Transportation System (STS)-122 Low Level Cutoff PRA for the SSP and the Orion Pad Abort One (PA-1) PRA for the CxP. These two activities, along with the numerous other tasks the Analysis Group performed in 2008, are summarized in this report. This report also highlights several ongoing and upcoming efforts to provide crucial statistical and probabilistic assessments, such as the Extravehicular Activity (EVA) PRA for the Hubble Space Telescope service mission and the first fully integrated PRAs for the CxP's Lunar Sortie and ISS missions.

Seismic Hazard Analysis — Quo vadis?

NASA Astrophysics Data System (ADS)

Klügel, Jens-Uwe

2008-05-01

The paper is dedicated to the review of methods of seismic hazard analysis currently in use, analyzing the strengths and weaknesses of different approaches. The review is performed from the perspective of a user of the results of seismic hazard analysis for different applications such as the design of critical and general (non-critical) civil infrastructures, technical and financial risk analysis. A set of criteria is developed for and applied to an objective assessment of the capabilities of different analysis methods. It is demonstrated that traditional probabilistic seismic hazard analysis (PSHA) methods have significant deficiencies, thus limiting their practical applications. These deficiencies have their roots in the use of inadequate probabilistic models and insufficient understanding of modern concepts of risk analysis, as have been revealed in some recent large scale studies. These deficiencies result in the lack of ability of a correct treatment of dependencies between physical parameters and finally, in an incorrect treatment of uncertainties. As a consequence, results of PSHA studies have been found to be unrealistic in comparison with empirical information from the real world. The attempt to compensate these problems by a systematic use of expert elicitation has, so far, not resulted in any improvement of the situation. It is also shown that scenario-earthquakes developed by disaggregation from the results of a traditional PSHA may not be conservative with respect to energy conservation and should not be used for the design of critical infrastructures without validation. Because the assessment of technical as well as of financial risks associated with potential damages of earthquakes need a risk analysis, current method is based on a probabilistic approach with its unsolved deficiencies. Traditional deterministic or scenario-based seismic hazard analysis methods provide a reliable and in general robust design basis for applications such as the design of critical infrastructures, especially with systematic sensitivity analyses based on validated phenomenological models. Deterministic seismic hazard analysis incorporates uncertainties in the safety factors. These factors are derived from experience as well as from expert judgment. Deterministic methods associated with high safety factors may lead to too conservative results, especially if applied for generally short-lived civil structures. Scenarios used in deterministic seismic hazard analysis have a clear physical basis. They are related to seismic sources discovered by geological, geomorphologic, geodetic and seismological investigations or derived from historical references. Scenario-based methods can be expanded for risk analysis applications with an extended data analysis providing the frequency of seismic events. Such an extension provides a better informed risk model that is suitable for risk-informed decision making.

Recent developments of the NESSUS probabilistic structural analysis computer program

NASA Technical Reports Server (NTRS)

Millwater, H.; Wu, Y.-T.; Torng, T.; Thacker, B.; Riha, D.; Leung, C. P.

1992-01-01

The NESSUS probabilistic structural analysis computer program combines state-of-the-art probabilistic algorithms with general purpose structural analysis methods to compute the probabilistic response and the reliability of engineering structures. Uncertainty in loading, material properties, geometry, boundary conditions and initial conditions can be simulated. The structural analysis methods include nonlinear finite element and boundary element methods. Several probabilistic algorithms are available such as the advanced mean value method and the adaptive importance sampling method. The scope of the code has recently been expanded to include probabilistic life and fatigue prediction of structures in terms of component and system reliability and risk analysis of structures considering cost of failure. The code is currently being extended to structural reliability considering progressive crack propagation. Several examples are presented to demonstrate the new capabilities.

Upgrading the fuel-handling machine of the Novovoronezh nuclear power plant unit no. 5

NASA Astrophysics Data System (ADS)

Terekhov, D. V.; Dunaev, V. I.

2014-02-01

The calculation of safety parameters was carried out in the process of upgrading the fuel-handling machine (FHM) of the Novovoronezh nuclear power plant (NPP) unit no. 5 based on the results of quantitative safety analysis of nuclear fuel transfer operations using a dynamic logical-and-probabilistic model of the processing procedure. Specific engineering and design concepts that made it possible to reduce the probability of damaging the fuel assemblies (FAs) when performing various technological operations by an order of magnitude and introduce more flexible algorithms into the modernized FHM control system were developed. The results of pilot operation during two refueling campaigns prove that the total reactor shutdown time is lowered.

Probabilistic Aeroelastic Analysis of Turbomachinery Components

NASA Technical Reports Server (NTRS)

Reddy, T. S. R.; Mital, S. K.; Stefko, G. L.

2004-01-01

A probabilistic approach is described for aeroelastic analysis of turbomachinery blade rows. Blade rows with subsonic flow and blade rows with supersonic flow with subsonic leading edge are considered. To demonstrate the probabilistic approach, the flutter frequency, damping and forced response of a blade row representing a compressor geometry is considered. The analysis accounts for uncertainties in structural and aerodynamic design variables. The results are presented in the form of probabilistic density function (PDF) and sensitivity factors. For subsonic flow cascade, comparisons are also made with different probabilistic distributions, probabilistic methods, and Monte-Carlo simulation. The approach shows that the probabilistic approach provides a more realistic and systematic way to assess the effect of uncertainties in design variables on the aeroelastic instabilities and response.

Probabilistic structural analysis of aerospace components using NESSUS

NASA Technical Reports Server (NTRS)

Shiao, Michael C.; Nagpal, Vinod K.; Chamis, Christos C.

1988-01-01

Probabilistic structural analysis of a Space Shuttle main engine turbopump blade is conducted using the computer code NESSUS (numerical evaluation of stochastic structures under stress). The goal of the analysis is to derive probabilistic characteristics of blade response given probabilistic descriptions of uncertainties in blade geometry, material properties, and temperature and pressure distributions. Probability densities are derived for critical blade responses. Risk assessment and failure life analysis is conducted assuming different failure models.

The Development of Dynamic Human Reliability Analysis Simulations for Inclusion in Risk Informed Safety Margin Characterization Frameworks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jeffrey C. Joe; Diego Mandelli; Ronald L. Boring

2015-07-01

The United States Department of Energy is sponsoring the Light Water Reactor Sustainability program, which has the overall objective of supporting the near-term and the extended operation of commercial nuclear power plants. One key research and development (R&D) area in this program is the Risk-Informed Safety Margin Characterization pathway, which combines probabilistic risk simulation with thermohydraulic simulation codes to define and manage safety margins. The R&D efforts to date, however, have not included robust simulations of human operators, and how the reliability of human performance or lack thereof (i.e., human errors) can affect risk-margins and plant performance. This paper describesmore » current and planned research efforts to address the absence of robust human reliability simulations and thereby increase the fidelity of simulated accident scenarios.« less

Ranking of sabotage/tampering avoidance technology alternatives

DOE Office of Scientific and Technical Information (OSTI.GOV)

Andrews, W.B.; Tabatabai, A.S.; Powers, T.B.

1986-01-01

Pacific Northwest Laboratory conducted a study to evaluate alternatives to the design and operation of nuclear power plants, emphasizing a reduction of their vulnerability to sabotage. Estimates of core melt accident frequency during normal operations and from sabotage/tampering events were used to rank the alternatives. Core melt frequency for normal operations was estimated using sensitivity analysis of results of probabilistic risk assessments. Core melt frequency for sabotage/tampering was estimated by developing a model based on probabilistic risk analyses, historic data, engineering judgment, and safeguards analyses of plant locations where core melt events could be initiated. Results indicate the most effectivemore » alternatives focus on large areas of the plant, increase safety system redundancy, and reduce reliance on single locations for mitigation of transients. Less effective options focus on specific areas of the plant, reduce reliance on some plant areas for safe shutdown, and focus on less vulnerable targets.« less

Addressing Uniqueness and Unison of Reliability and Safety for a Better Integration

NASA Technical Reports Server (NTRS)

Huang, Zhaofeng; Safie, Fayssal

2016-01-01

Over time, it has been observed that Safety and Reliability have not been clearly differentiated, which leads to confusion, inefficiency, and, sometimes, counter-productive practices in executing each of these two disciplines. It is imperative to address this situation to help Reliability and Safety disciplines improve their effectiveness and efficiency. The paper poses an important question to address, "Safety and Reliability - Are they unique or unisonous?" To answer the question, the paper reviewed several most commonly used analyses from each of the disciplines, namely, FMEA, reliability allocation and prediction, reliability design involvement, system safety hazard analysis, Fault Tree Analysis, and Probabilistic Risk Assessment. The paper pointed out uniqueness and unison of Safety and Reliability in their respective roles, requirements, approaches, and tools, and presented some suggestions for enhancing and improving the individual disciplines, as well as promoting the integration of the two. The paper concludes that Safety and Reliability are unique, but compensating each other in many aspects, and need to be integrated. Particularly, the individual roles of Safety and Reliability need to be differentiated, that is, Safety is to ensure and assure the product meets safety requirements, goals, or desires, and Reliability is to ensure and assure maximum achievability of intended design functions. With the integration of Safety and Reliability, personnel can be shared, tools and analyses have to be integrated, and skill sets can be possessed by the same person with the purpose of providing the best value to a product development.

Probabilistic Structural Analysis of the Solid Rocket Booster Aft Skirt External Fitting Modification

NASA Technical Reports Server (NTRS)

Townsend, John S.; Peck, Jeff; Ayala, Samuel

2000-01-01

NASA has funded several major programs (the Probabilistic Structural Analysis Methods Project is an example) to develop probabilistic structural analysis methods and tools for engineers to apply in the design and assessment of aerospace hardware. A probabilistic finite element software code, known as Numerical Evaluation of Stochastic Structures Under Stress, is used to determine the reliability of a critical weld of the Space Shuttle solid rocket booster aft skirt. An external bracket modification to the aft skirt provides a comparison basis for examining the details of the probabilistic analysis and its contributions to the design process. Also, analysis findings are compared with measured Space Shuttle flight data.

Landslide prediction using combined deterministic and probabilistic methods in hilly area of Mt. Medvednica in Zagreb City, Croatia

NASA Astrophysics Data System (ADS)

Wang, Chunxiang; Watanabe, Naoki; Marui, Hideaki

2013-04-01

The hilly slopes of Mt. Medvednica are stretched in the northwestern part of Zagreb City, Croatia, and extend to approximately 180km2. In this area, landslides, e.g. Kostanjek landslide and Črešnjevec landslide, have brought damage to many houses, roads, farmlands, grassland and etc. Therefore, it is necessary to predict the potential landslides and to enhance landslide inventory for hazard mitigation and security management of local society in this area. We combined deterministic method and probabilistic method to assess potential landslides including their locations, size and sliding surfaces. Firstly, this study area is divided into several slope units that have similar topographic and geological characteristics using the hydrology analysis tool in ArcGIS. Then, a GIS-based modified three-dimensional Hovland's method for slope stability analysis system is developed to identify the sliding surface and corresponding three-dimensional safety factor for each slope unit. Each sliding surface is assumed to be the lower part of each ellipsoid. The direction of inclination of the ellipsoid is considered to be the same as the main dip direction of the slope unit. The center point of the ellipsoid is randomly set to the center point of a grid cell in the slope unit. The minimum three-dimensional safety factor and corresponding critical sliding surface are also obtained for each slope unit. Thirdly, since a single value of safety factor is insufficient to evaluate the slope stability of a slope unit, the ratio of the number of calculation cases in which the three-dimensional safety factor values less than 1.0 to the total number of trial calculation is defined as the failure probability of the slope unit. If the failure probability is more than 80%, the slope unit is distinguished as 'unstable' from other slope units and the landslide hazard can be mapped for the whole study area.

An Application of the SSHAC Level 3 Process to the Probabilistic Seismic Hazard Analysis for Nuclear Facilities at the Hanford Site, Eastern Washington, USA

DOE Office of Scientific and Technical Information (OSTI.GOV)

Coppersmith , Kevin J.; Bommer, Julian J.; Bryce, Robert W.

Under the sponsorship of the US Department of Energy (DOE) and the electric utility Energy Northwest, the Pacific Northwest National Laboratory (PNNL) is conducting a probabilistic seismic hazard analysis (PSHA) within the framework of a SSHAC Level 3 procedure (Senior Seismic Hazard Analysis Committee; Budnitz et al., 1997). Specifically, the project is being conducted following the guidelines and requirements specified in NUREG-2117 (USNRC, 2012b) and consistent with approach given in the American Nuclear Standard ANSI/ANS-2.29-2008 Probabilistic Seismic Hazard Analysis. The collaboration between DOE and Energy Northwest is spawned by the needs of both organizations for an accepted PSHA with highmore » levels of regulatory assurance that can be used for the design and safety evaluation of nuclear facilities. DOE committed to this study after performing a ten-year review of the existing PSHA, as required by DOE Order 420.1C. The study will also be used by Energy Northwest as a basis for fulfilling the NRC’s 10CFR50.54(f) requirement that the western US nuclear power plants conduct PSHAs in conformance with SSHAC Level 3 procedures. The study was planned and is being carried out in conjunction with a project Work Plan, which identifies the purpose of the study, the roles and responsibilities of all participants, tasks and their associated schedules, Quality Assurance (QA) requirements, and project deliverables. New data collection and analysis activities are being conducted as a means of reducing the uncertainties in key inputs to the PSHA. It is anticipated that the results of the study will provide inputs to the site response analyses at multiple nuclear facility sites within the Hanford Site and at the Columbia Generating Station.« less

Analyzing system safety in lithium-ion grid energy storage

NASA Astrophysics Data System (ADS)

Rosewater, David; Williams, Adam

2015-12-01

As grid energy storage systems become more complex, it grows more difficult to design them for safe operation. This paper first reviews the properties of lithium-ion batteries that can produce hazards in grid scale systems. Then the conventional safety engineering technique Probabilistic Risk Assessment (PRA) is reviewed to identify its limitations in complex systems. To address this gap, new research is presented on the application of Systems-Theoretic Process Analysis (STPA) to a lithium-ion battery based grid energy storage system. STPA is anticipated to fill the gaps recognized in PRA for designing complex systems and hence be more effective or less costly to use during safety engineering. It was observed that STPA is able to capture causal scenarios for accidents not identified using PRA. Additionally, STPA enabled a more rational assessment of uncertainty (all that is not known) thereby promoting a healthy skepticism of design assumptions. We conclude that STPA may indeed be more cost effective than PRA for safety engineering in lithium-ion battery systems. However, further research is needed to determine if this approach actually reduces safety engineering costs in development, or improves industry safety standards.

Probabilistic assessment of dynamic system performance. Part 3

DOE Office of Scientific and Technical Information (OSTI.GOV)

Belhadj, Mohamed

1993-01-01

Accurate prediction of dynamic system failure behavior can be important for the reliability and risk analyses of nuclear power plants, as well as for their backfitting to satisfy given constraints on overall system reliability, or optimization of system performance. Global analysis of dynamic systems through investigating the variations in the structure of the attractors of the system and the domains of attraction of these attractors as a function of the system parameters is also important for nuclear technology in order to understand the fault-tolerance as well as the safety margins of the system under consideration and to insure a safemore » operation of nuclear reactors. Such a global analysis would be particularly relevant to future reactors with inherent or passive safety features that are expected to rely on natural phenomena rather than active components to achieve and maintain safe shutdown. Conventionally, failure and global analysis of dynamic systems necessitate the utilization of different methodologies which have computational limitations on the system size that can be handled. Using a Chapman-Kolmogorov interpretation of system dynamics, a theoretical basis is developed that unifies these methodologies as special cases and which can be used for a comprehensive safety and reliability analysis of dynamic systems.« less

Fuzzy Bayesian Network-Bow-Tie Analysis of Gas Leakage during Biomass Gasification

PubMed Central

Yan, Fang; Xu, Kaili; Yao, Xiwen; Li, Yang

2016-01-01

Biomass gasification technology has been rapidly developed recently. But fire and poisoning accidents caused by gas leakage restrict the development and promotion of biomass gasification. Therefore, probabilistic safety assessment (PSA) is necessary for biomass gasification system. Subsequently, Bayesian network-bow-tie (BN-bow-tie) analysis was proposed by mapping bow-tie analysis into Bayesian network (BN). Causes of gas leakage and the accidents triggered by gas leakage can be obtained by bow-tie analysis, and BN was used to confirm the critical nodes of accidents by introducing corresponding three importance measures. Meanwhile, certain occurrence probability of failure was needed in PSA. In view of the insufficient failure data of biomass gasification, the occurrence probability of failure which cannot be obtained from standard reliability data sources was confirmed by fuzzy methods based on expert judgment. An improved approach considered expert weighting to aggregate fuzzy numbers included triangular and trapezoidal numbers was proposed, and the occurrence probability of failure was obtained. Finally, safety measures were indicated based on the obtained critical nodes. The theoretical occurrence probabilities in one year of gas leakage and the accidents caused by it were reduced to 1/10.3 of the original values by these safety measures. PMID:27463975

MATILDA Version 2: Rough Earth TIALD Model for Laser Probabilistic Risk Assessment in Hilly Terrain - Part I

DTIC Science & Technology

2017-03-13

support of airborne laser designator use during test and training exercises on military ranges. The initial MATILDA tool, MATILDA PRO Version-1.6.1...was based on the 2007 PRA model developed to perform range safety clearances for the UK Thermal Imaging Airborne Laser Designator (TIALD) system...AFRL Technical Reports. This Technical Report, designated Part I, con- tains documentation of the computational procedures for probabilistic fault

Application of the probabilistic approximate analysis method to a turbopump blade analysis. [for Space Shuttle Main Engine

NASA Technical Reports Server (NTRS)

Thacker, B. H.; Mcclung, R. C.; Millwater, H. R.

1990-01-01

An eigenvalue analysis of a typical space propulsion system turbopump blade is presented using an approximate probabilistic analysis methodology. The methodology was developed originally to investigate the feasibility of computing probabilistic structural response using closed-form approximate models. This paper extends the methodology to structures for which simple closed-form solutions do not exist. The finite element method will be used for this demonstration, but the concepts apply to any numerical method. The results agree with detailed analysis results and indicate the usefulness of using a probabilistic approximate analysis in determining efficient solution strategies.

A look-ahead probabilistic contingency analysis framework incorporating smart sampling techniques

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Yousu; Etingov, Pavel V.; Ren, Huiying

2016-07-18

This paper describes a framework of incorporating smart sampling techniques in a probabilistic look-ahead contingency analysis application. The predictive probabilistic contingency analysis helps to reflect the impact of uncertainties caused by variable generation and load on potential violations of transmission limits.

Probabilistic structural analysis methods of hot engine structures

NASA Technical Reports Server (NTRS)

Chamis, C. C.; Hopkins, D. A.

1989-01-01

Development of probabilistic structural analysis methods for hot engine structures is a major activity at Lewis Research Center. Recent activities have focused on extending the methods to include the combined uncertainties in several factors on structural response. This paper briefly describes recent progress on composite load spectra models, probabilistic finite element structural analysis, and probabilistic strength degradation modeling. Progress is described in terms of fundamental concepts, computer code development, and representative numerical results.

75 FR 13610 - Office of New Reactors; Interim Staff Guidance on Implementation of a Seismic Margin Analysis for...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-03-22

... Staff Guidance on Implementation of a Seismic Margin Analysis for New Reactors Based on Probabilistic... Seismic Margin Analysis for New Reactors Based on Probabilistic Risk Assessment,'' (Agencywide Documents.../COL-ISG-020 ``Implementation of a Seismic Margin Analysis for New Reactors Based on Probabilistic Risk...

Landslide hazard analysis for pipelines: The case of the Simonette river crossing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grivas, D.A.; Schultz, B.C.; O`Neil, G.

1995-12-31

The overall objective of this study is to develop a probabilistic methodology to analyze landslide hazards and their effects on the safety of buried pipelines. The methodology incorporates a range of models that can accommodate differences in the ground movement modes and the amount and type of information available at various site locations. Two movement modes are considered, namely (a) instantaneous (catastrophic) slides, and (b) gradual ground movement which may result in cumulative displacements over the pipeline design life (30--40 years) that are in excess of allowable values. Probabilistic analysis is applied in each case to address the uncertainties associatedmore » with important factors that control slope stability. Availability of information ranges from relatively well studied, instrumented installations to cases where data is limited to what can be derived from topographic and geologic maps. The methodology distinguishes between procedures applied where there is little information and those that can be used when relatively extensive data is available. important aspects of the methodology are illustrated in a case study involving a pipeline located in Northern Alberta, Canada, in the Simonette river valley.« less

Constellation Probabilistic Risk Assessment (PRA): Design Consideration for the Crew Exploration Vehicle

NASA Technical Reports Server (NTRS)

Prassinos, Peter G.; Stamatelatos, Michael G.; Young, Jonathan; Smith, Curtis

2010-01-01

Managed by NASA's Office of Safety and Mission Assurance, a pilot probabilistic risk analysis (PRA) of the NASA Crew Exploration Vehicle (CEV) was performed in early 2006. The PRA methods used follow the general guidance provided in the NASA PRA Procedures Guide for NASA Managers and Practitioners'. Phased-mission based event trees and fault trees are used to model a lunar sortie mission of the CEV - involving the following phases: launch of a cargo vessel and a crew vessel; rendezvous of these two vessels in low Earth orbit; transit to th$: moon; lunar surface activities; ascension &om the lunar surface; and return to Earth. The analysis is based upon assumptions, preliminary system diagrams, and failure data that may involve large uncertainties or may lack formal validation. Furthermore, some of the data used were based upon expert judgment or extrapolated from similar componentssystemsT. his paper includes a discussion of the system-level models and provides an overview of the analysis results used to identify insights into CEV risk drivers, and trade and sensitivity studies. Lastly, the PRA model was used to determine changes in risk as the system configurations or key parameters are modified.

Probabilistic risk assessment of the Space Shuttle. Phase 3: A study of the potential of losing the vehicle during nominal operation, volume 1

NASA Technical Reports Server (NTRS)

Fragola, Joseph R.; Maggio, Gaspare; Frank, Michael V.; Gerez, Luis; Mcfadden, Richard H.; Collins, Erin P.; Ballesio, Jorge; Appignani, Peter L.; Karns, James J.

1995-01-01

This document is the Executive Summary of a technical report on a probabilistic risk assessment (PRA) of the Space Shuttle vehicle performed under the sponsorship of the Office of Space Flight of the US National Aeronautics and Space Administration. It briefly summarizes the methodology and results of the Shuttle PRA. The primary objective of this project was to support management and engineering decision-making with respect to the Shuttle program by producing (1) a quantitative probabilistic risk model of the Space Shuttle during flight, (2) a quantitative assessment of in-flight safety risk, (3) an identification and prioritization of the design and operations that principally contribute to in-flight safety risk, and (4) a mechanism for risk-based evaluation proposed modifications to the Shuttle System. Secondary objectives were to provide a vehicle for introducing and transferring PRA technology to the NASA community, and to demonstrate the value of PRA by applying it beneficially to a real program of great international importance.

Probabilistic safety analysis for urgent situations following the accidental release of a pollutant in the atmosphere

NASA Astrophysics Data System (ADS)

Armand, P.; Brocheton, F.; Poulet, D.; Vendel, F.; Dubourg, V.; Yalamas, T.

2014-10-01

This paper is an original contribution to uncertainty quantification in atmospheric transport & dispersion (AT&D) at the local scale (1-10 km). It is proposed to account for the imprecise knowledge of the meteorological and release conditions in the case of an accidental hazardous atmospheric emission. The aim is to produce probabilistic risk maps instead of a deterministic toxic load map in order to help the stakeholders making their decisions. Due to the urge attached to such situations, the proposed methodology is able to produce such maps in a limited amount of time. It resorts to a Lagrangian particle dispersion model (LPDM) using wind fields interpolated from a pre-established database that collects the results from a computational fluid dynamics (CFD) model. This enables a decoupling of the CFD simulations from the dispersion analysis, thus a considerable saving of computational time. In order to make the Monte-Carlo-sampling-based estimation of the probability field even faster, it is also proposed to recourse to the use of a vector Gaussian process surrogate model together with high performance computing (HPC) resources. The Gaussian process (GP) surrogate modelling technique is coupled with a probabilistic principal component analysis (PCA) for reducing the number of GP predictors to fit, store and predict. The design of experiments (DOE) from which the surrogate model is built, is run over a cluster of PCs for making the total production time as short as possible. The use of GP predictors is validated by comparing the results produced by this technique with those obtained by crude Monte Carlo sampling.

The analysis of probability task completion; Taxonomy of probabilistic thinking-based across gender in elementary school students

NASA Astrophysics Data System (ADS)

Sari, Dwi Ivayana; Budayasa, I. Ketut; Juniati, Dwi

2017-08-01

Formulation of mathematical learning goals now is not only oriented on cognitive product, but also leads to cognitive process, which is probabilistic thinking. Probabilistic thinking is needed by students to make a decision. Elementary school students are required to develop probabilistic thinking as foundation to learn probability at higher level. A framework of probabilistic thinking of students had been developed by using SOLO taxonomy, which consists of prestructural probabilistic thinking, unistructural probabilistic thinking, multistructural probabilistic thinking and relational probabilistic thinking. This study aimed to analyze of probability task completion based on taxonomy of probabilistic thinking. The subjects were two students of fifth grade; boy and girl. Subjects were selected by giving test of mathematical ability and then based on high math ability. Subjects were given probability tasks consisting of sample space, probability of an event and probability comparison. The data analysis consisted of categorization, reduction, interpretation and conclusion. Credibility of data used time triangulation. The results was level of boy's probabilistic thinking in completing probability tasks indicated multistructural probabilistic thinking, while level of girl's probabilistic thinking in completing probability tasks indicated unistructural probabilistic thinking. The results indicated that level of boy's probabilistic thinking was higher than level of girl's probabilistic thinking. The results could contribute to curriculum developer in developing probability learning goals for elementary school students. Indeed, teachers could teach probability with regarding gender difference.

Conceptual design study of Fusion Experimental Reactor (FY86 FER): Safety

NASA Astrophysics Data System (ADS)

Seki, Yasushi; Iida, Hiromasa; Honda, Tsutomu

1987-08-01

This report describes the study on safety for FER (Fusion Experimental Reactor) which has been designed as a next step machine to the JT-60. Though the final purpose of this study is to have an image of design base accident, maximum credible accident and to assess their risk or probability, etc., as FER plant system, the emphasis of this years study is placed on fuel-gas circulation system where the tritium inventory is maximum. The report consists of two chapters. The first chapter summarizes the FER system and describes FMEA (Failure Mode and Effect Analysis) and related accident progression sequence for FER plant system as a whole. The second chapter of this report is focused on fuel-gas circulation system including purification, isotope separation and storage. Probability of risk is assessed by the probabilistic risk analysis (PRA) procedure based on FMEA, ETA and FTA.

Probabilistic Risk Assessment Process for High-Power Laser Operations in Outdoor Environments

DTIC Science & Technology

2016-01-01

avionics data bus. In the case of a UAS-mounted laser system, the control path will additionally include a radio or satellite communications link. A remote...JBSA Fort Sam Houston, TX 78234 711 HPW/RHDO 11 . SPONSOR’S/MONITOR’S REPORT NUMBER(S) AFRL-RH-FS-JA-2015...hazard assessment pur- poses is not widespread within the laser safety community . The aim of this paper is to outline the basis of the probabilistic

Probabilistic structural analysis methods of hot engine structures

NASA Technical Reports Server (NTRS)

Chamis, C. C.; Hopkins, D. A.

1989-01-01

Development of probabilistic structural analysis methods for hot engine structures at Lewis Research Center is presented. Three elements of the research program are: (1) composite load spectra methodology; (2) probabilistic structural analysis methodology; and (3) probabilistic structural analysis application. Recent progress includes: (1) quantification of the effects of uncertainties for several variables on high pressure fuel turbopump (HPFT) turbine blade temperature, pressure, and torque of the space shuttle main engine (SSME); (2) the evaluation of the cumulative distribution function for various structural response variables based on assumed uncertainties in primitive structural variables; and (3) evaluation of the failure probability. Collectively, the results demonstrate that the structural durability of hot engine structural components can be effectively evaluated in a formal probabilistic/reliability framework.

The in-depth safety assessment (ISA) pilot projects in Ukraine.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kot, C. A.

1998-02-10

Ukraine operates pressurized water reactors of the Soviet-designed type, VVER. All Ukrainian plants are currently operating with annually renewable permits until they update their safety analysis reports (SARs). After approval of the SARS by the Ukrainian Nuclear Regulatory Authority, the plants will be granted longer-term operating licenses. In September 1995, the Nuclear Regulatory Authority and the Government Nuclear Power Coordinating Committee of Ukraine issued a new contents requirement for the safety analysis reports of VVERs in Ukraine. It contains requirements in three major areas: design basis accident (DBA) analysis, probabilistic risk assessment (PRA), and beyond design-basis accident (BDBA) analysis. Themore » DBA requirements are an expanded version of the older SAR requirements. The last two requirements, on PRA and BDBA, are new. The US Department of Energy (USDOE), through the International Nuclear Safety Program (INSP), has initiated an assistance and technology transfer program to Ukraine to assist their nuclear power stations in developing a Western-type technical basis for the new SARS. USDOE sponsored In-Depth Safety Assessments (ISAs) have been initiated at three pilot nuclear reactor units in Ukraine, South Ukraine Unit 1, Zaporizhzhya Unit 5, and Rivne Unit 1. USDOE/INSP have structured the ISA program in such a way as to provide maximum assistance and technology transfer to Ukraine while encouraging and supporting the Ukrainian plants to take the responsibility and initiative and to perform the required assessments.« less

Evaluating the safety risk of roadside features for rural two-lane roads using reliability analysis.

PubMed

Jalayer, Mohammad; Zhou, Huaguo

2016-08-01

The severity of roadway departure crashes mainly depends on the roadside features, including the sideslope, fixed-object density, offset from fixed objects, and shoulder width. Common engineering countermeasures to improve roadside safety include: cross section improvements, hazard removal or modification, and delineation. It is not always feasible to maintain an object-free and smooth roadside clear zone as recommended in design guidelines. Currently, clear zone width and sideslope are used to determine roadside hazard ratings (RHRs) to quantify the roadside safety of rural two-lane roadways on a seven-point pictorial scale. Since these two variables are continuous and can be treated as random, probabilistic analysis can be applied as an alternative method to address existing uncertainties. Specifically, using reliability analysis, it is possible to quantify roadside safety levels by treating the clear zone width and sideslope as two continuous, rather than discrete, variables. The objective of this manuscript is to present a new approach for defining the reliability index for measuring roadside safety on rural two-lane roads. To evaluate the proposed approach, we gathered five years (2009-2013) of Illinois run-off-road (ROR) crash data and identified the roadside features (i.e., clear zone widths and sideslopes) of 4500 300ft roadway segments. Based on the obtained results, we confirm that reliability indices can serve as indicators to gauge safety levels, such that the greater the reliability index value, the lower the ROR crash rate. Copyright © 2016 Elsevier Ltd. All rights reserved.

The role of PRA in the safety assessment of VVER Nuclear Power Plants in Ukraine.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kot, C.

1999-05-10

Ukraine operates thirteen (13) Soviet-designed pressurized water reactors, VVERS. All Ukrainian plants are currently operating with annually renewable permits until they update their safety analysis reports (SARs), in accordance with new SAR content requirements issued in September 1995, by the Nuclear Regulatory Authority and the Government Nuclear Power Coordinating Committee of Ukraine. The requirements are in three major areas: design basis accident (DBA) analysis, probabilistic risk assessment (PRA), and beyond design-basis accident (BDBA) analysis. The last two requirements, on PRA and BDBA, are new, and the DBA requirements are an expanded version of the older SAR requirements. The US Departmentmore » of Energy (USDOE), as part of its Soviet-Designed Reactor Safety activities, is providing assistance and technology transfer to Ukraine to support their nuclear power plants (NPPs) in developing a Western-type technical basis for the new SARs. USDOE sponsored In-Depth Safety Assessments (ISAs) are in progress at three pilot nuclear reactor units in Ukraine, South Ukraine Unit 1, Zaporizhzhya Unit 5, and Rivne Unit 1, and a follow-on study has been initiated at Khmenytskyy Unit 1. The ISA projects encompass most areas of plant safety evaluation, but the initial emphasis is on performing a detailed, plant-specific Level 1 Internal Events PRA. This allows the early definition of the plant risk profile, the identification of risk significant accident sequences and plant vulnerabilities and provides guidance for the remainder of the safety assessments.« less

Sensemaking of patient safety risks and hazards.

PubMed

Battles, James B; Dixon, Nancy M; Borotkanics, Robert J; Rabin-Fastmen, Barbara; Kaplan, Harold S

2006-08-01

In order for organizations to become learning organizations, they must make sense of their environment and learn from safety events. Sensemaking, as described by Weick (1995), literally means making sense of events. The ultimate goal of sensemaking is to build the understanding that can inform and direct actions to eliminate risk and hazards that are a threat to patient safety. True sensemaking in patient safety must use both retrospective and prospective approach to learning. Sensemaking is as an essential part of the design process leading to risk informed design. Sensemaking serves as a conceptual framework to bring together well established approaches to assessment of risk and hazards: (1) at the single event level using root cause analysis (RCA), (2) at the processes level using failure modes effects analysis (FMEA) and (3) at the system level using probabilistic risk assessment (PRA). The results of these separate or combined approaches are most effective when end users in conversation-based meetings add their expertise and knowledge to the data produced by the RCA, FMEA, and/or PRA in order to make sense of the risks and hazards. Without ownership engendered by such conversations, the possibility of effective action to eliminate or minimize them is greatly reduced.

Sensemaking of Patient Safety Risks and Hazards

PubMed Central

Battles, James B; Dixon, Nancy M; Borotkanics, Robert J; Rabin-Fastmen, Barbara; Kaplan, Harold S

2006-01-01

In order for organizations to become learning organizations, they must make sense of their environment and learn from safety events. Sensemaking, as described by Weick (1995), literally means making sense of events. The ultimate goal of sensemaking is to build the understanding that can inform and direct actions to eliminate risk and hazards that are a threat to patient safety. True sensemaking in patient safety must use both retrospective and prospective approach to learning. Sensemaking is as an essential part of the design process leading to risk informed design. Sensemaking serves as a conceptual framework to bring together well established approaches to assessment of risk and hazards: (1) at the single event level using root cause analysis (RCA), (2) at the processes level using failure modes effects analysis (FMEA) and (3) at the system level using probabilistic risk assessment (PRA). The results of these separate or combined approaches are most effective when end users in conversation-based meetings add their expertise and knowledge to the data produced by the RCA, FMEA, and/or PRA in order to make sense of the risks and hazards. Without ownership engendered by such conversations, the possibility of effective action to eliminate or minimize them is greatly reduced. PMID:16898979

A Proposed Probabilistic Extension of the Halpern and Pearl Definition of ‘Actual Cause’

PubMed Central

2017-01-01

ABSTRACT Joseph Halpern and Judea Pearl ([2005]) draw upon structural equation models to develop an attractive analysis of ‘actual cause’. Their analysis is designed for the case of deterministic causation. I show that their account can be naturally extended to provide an elegant treatment of probabilistic causation. 1Introduction2Preemption3Structural Equation Models4The Halpern and Pearl Definition of ‘Actual Cause’5Preemption Again6The Probabilistic Case7Probabilistic Causal Models8A Proposed Probabilistic Extension of Halpern and Pearl’s Definition9Twardy and Korb’s Account10Probabilistic Fizzling11Conclusion PMID:29593362

Use of evidential reasoning and AHP to assess regional industrial safety

PubMed Central

Chen, Zhichao; Chen, Tao; Qu, Zhuohua; Ji, Xuewei; Zhou, Yi; Zhang, Hui

2018-01-01

China’s fast economic growth contributes to the rapid development of its urbanization process, and also renders a series of industrial accidents, which often cause loss of life, damage to property and environment, thus requiring the associated risk analysis and safety control measures to be implemented in advance. However, incompleteness of historical failure data before the occurrence of accidents makes it difficult to use traditional risk analysis approaches such as probabilistic risk analysis in many cases. This paper aims to develop a new methodology capable of assessing regional industrial safety (RIS) in an uncertain environment. A hierarchical structure for modelling the risks influencing RIS is first constructed. The hybrid of evidential reasoning (ER) and Analytical Hierarchy Process (AHP) is then used to assess the risks in a complementary way, in which AHP is hired to evaluate the weight of each risk factor and ER is employed to synthesise the safety evaluations of the investigated region(s) against the risk factors from the bottom to the top level in the hierarchy. The successful application of the hybrid approach in a real case analysis of RIS in several major districts of Beijing (capital of China) demonstrates its feasibility as well as provides risk analysts and safety engineers with useful insights on effective solutions to comprehensive risk assessment of RIS in metropolitan cities. The contribution of this paper is made by the findings on the comparison of risk levels of RIS at different regions against various risk factors so that best practices from the good performer(s) can be used to improve the safety of the others. PMID:29795593

Use of evidential reasoning and AHP to assess regional industrial safety.

PubMed

Chen, Zhichao; Chen, Tao; Qu, Zhuohua; Yang, Zaili; Ji, Xuewei; Zhou, Yi; Zhang, Hui

2018-01-01

China's fast economic growth contributes to the rapid development of its urbanization process, and also renders a series of industrial accidents, which often cause loss of life, damage to property and environment, thus requiring the associated risk analysis and safety control measures to be implemented in advance. However, incompleteness of historical failure data before the occurrence of accidents makes it difficult to use traditional risk analysis approaches such as probabilistic risk analysis in many cases. This paper aims to develop a new methodology capable of assessing regional industrial safety (RIS) in an uncertain environment. A hierarchical structure for modelling the risks influencing RIS is first constructed. The hybrid of evidential reasoning (ER) and Analytical Hierarchy Process (AHP) is then used to assess the risks in a complementary way, in which AHP is hired to evaluate the weight of each risk factor and ER is employed to synthesise the safety evaluations of the investigated region(s) against the risk factors from the bottom to the top level in the hierarchy. The successful application of the hybrid approach in a real case analysis of RIS in several major districts of Beijing (capital of China) demonstrates its feasibility as well as provides risk analysts and safety engineers with useful insights on effective solutions to comprehensive risk assessment of RIS in metropolitan cities. The contribution of this paper is made by the findings on the comparison of risk levels of RIS at different regions against various risk factors so that best practices from the good performer(s) can be used to improve the safety of the others.

Risk-Informed Safety Assurance and Probabilistic Assessment of Mission-Critical Software-Intensive Systems

NASA Technical Reports Server (NTRS)

Guarro, Sergio B.

2010-01-01

This report validates and documents the detailed features and practical application of the framework for software intensive digital systems risk assessment and risk-informed safety assurance presented in the NASA PRA Procedures Guide for Managers and Practitioner. This framework, called herein the "Context-based Software Risk Model" (CSRM), enables the assessment of the contribution of software and software-intensive digital systems to overall system risk, in a manner which is entirely compatible and integrated with the format of a "standard" Probabilistic Risk Assessment (PRA), as currently documented and applied for NASA missions and applications. The CSRM also provides a risk-informed path and criteria for conducting organized and systematic digital system and software testing so that, within this risk-informed paradigm, the achievement of a quantitatively defined level of safety and mission success assurance may be targeted and demonstrated. The framework is based on the concept of context-dependent software risk scenarios and on the modeling of such scenarios via the use of traditional PRA techniques - i.e., event trees and fault trees - in combination with more advanced modeling devices such as the Dynamic Flowgraph Methodology (DFM) or other dynamic logic-modeling representations. The scenarios can be synthesized and quantified in a conditional logic and probabilistic formulation. The application of the CSRM method documented in this report refers to the MiniAERCam system designed and developed by the NASA Johnson Space Center.

Modification of the SAS4A Safety Analysis Code for Integration with the ADAPT Discrete Dynamic Event Tree Framework.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jankovsky, Zachary Kyle; Denman, Matthew R.

It is difficult to assess the consequences of a transient in a sodium-cooled fast reactor (SFR) using traditional probabilistic risk assessment (PRA) methods, as numerous safety-related sys- tems have passive characteristics. Often there is significant dependence on the value of con- tinuous stochastic parameters rather than binary success/failure determinations. One form of dynamic PRA uses a system simulator to represent the progression of a transient, tracking events through time in a discrete dynamic event tree (DDET). In order to function in a DDET environment, a simulator must have characteristics that make it amenable to changing physical parameters midway through themore » analysis. The SAS4A SFR system analysis code did not have these characteristics as received. This report describes the code modifications made to allow dynamic operation as well as the linking to a Sandia DDET driver code. A test case is briefly described to demonstrate the utility of the changes.« less

Development of probabilistic multimedia multipathway computer codes.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yu, C.; LePoire, D.; Gnanapragasam, E.

2002-01-01

The deterministic multimedia dose/risk assessment codes RESRAD and RESRAD-BUILD have been widely used for many years for evaluation of sites contaminated with residual radioactive materials. The RESRAD code applies to the cleanup of sites (soils) and the RESRAD-BUILD code applies to the cleanup of buildings and structures. This work describes the procedure used to enhance the deterministic RESRAD and RESRAD-BUILD codes for probabilistic dose analysis. A six-step procedure was used in developing default parameter distributions and the probabilistic analysis modules. These six steps include (1) listing and categorizing parameters; (2) ranking parameters; (3) developing parameter distributions; (4) testing parameter distributionsmore » for probabilistic analysis; (5) developing probabilistic software modules; and (6) testing probabilistic modules and integrated codes. The procedures used can be applied to the development of other multimedia probabilistic codes. The probabilistic versions of RESRAD and RESRAD-BUILD codes provide tools for studying the uncertainty in dose assessment caused by uncertain input parameters. The parameter distribution data collected in this work can also be applied to other multimedia assessment tasks and multimedia computer codes.« less

Probabilistic liquefaction hazard analysis at liquefied sites of 1956 Dunaharaszti earthquake, in Hungary

NASA Astrophysics Data System (ADS)

Győri, Erzsébet; Gráczer, Zoltán; Tóth, László; Bán, Zoltán; Horváth, Tibor

2017-04-01

Liquefaction potential evaluations are generally made to assess the hazard from specific scenario earthquakes. These evaluations may estimate the potential in a binary fashion (yes/no), define a factor of safety or predict the probability of liquefaction given a scenario event. Usually the level of ground shaking is obtained from the results of PSHA. Although it is determined probabilistically, a single level of ground shaking is selected and used within the liquefaction potential evaluation. In contrary, the fully probabilistic liquefaction potential assessment methods provide a complete picture of liquefaction hazard, namely taking into account the joint probability distribution of PGA and magnitude of earthquake scenarios; both of which are key inputs in the stress-based simplified methods. Kramer and Mayfield (2007) has developed a fully probabilistic liquefaction potential evaluation method using a performance-based earthquake engineering (PBEE) framework. The results of the procedure are the direct estimate of the return period of liquefaction and the liquefaction hazard curves in function of depth. The method combines the disaggregation matrices computed for different exceedance frequencies during probabilistic seismic hazard analysis with one of the recent models for the conditional probability of liquefaction. We have developed a software for the assessment of performance-based liquefaction triggering on the basis of Kramer and Mayfield method. Originally the SPT based probabilistic method of Cetin et al. (2004) was built-in into the procedure of Kramer and Mayfield to compute the conditional probability however there is no professional consensus about its applicability. Therefore we have included not only Cetin's method but Idriss and Boulanger (2012) SPT based moreover Boulanger and Idriss (2014) CPT based procedures into our computer program. In 1956, a damaging earthquake of magnitude 5.6 occurred in Dunaharaszti, in Hungary. Its epicenter was located about 5 km from the southern boundary of Budapest. The quake caused serious damages in the epicentral area and in the southern districts of the capital. The epicentral area of the earthquake is located along the Danube River. Sand boils were observed in some locations that indicated the occurrence of liquefaction. Because their exact locations were recorded at the time of the earthquake, in situ geotechnical measurements (CPT and SPT) could be performed at two (Dunaharaszti and Taksony) sites. The different types of measurements enabled the probabilistic liquefaction hazard computations at the two studied sites. We have compared the return periods of liquefaction that were computed using different built-in simplified stress based methods.

Probabilistic Design and Analysis Framework

NASA Technical Reports Server (NTRS)

Strack, William C.; Nagpal, Vinod K.

2010-01-01

PRODAF is a software package designed to aid analysts and designers in conducting probabilistic analysis of components and systems. PRODAF can integrate multiple analysis programs to ease the tedious process of conducting a complex analysis process that requires the use of multiple software packages. The work uses a commercial finite element analysis (FEA) program with modules from NESSUS to conduct a probabilistic analysis of a hypothetical turbine blade, disk, and shaft model. PRODAF applies the response surface method, at the component level, and extrapolates the component-level responses to the system level. Hypothetical components of a gas turbine engine are first deterministically modeled using FEA. Variations in selected geometrical dimensions and loading conditions are analyzed to determine the effects of the stress state within each component. Geometric variations include the cord length and height for the blade, inner radius, outer radius, and thickness, which are varied for the disk. Probabilistic analysis is carried out using developing software packages like System Uncertainty Analysis (SUA) and PRODAF. PRODAF was used with a commercial deterministic FEA program in conjunction with modules from the probabilistic analysis program, NESTEM, to perturb loads and geometries to provide a reliability and sensitivity analysis. PRODAF simplified the handling of data among the various programs involved, and will work with many commercial and opensource deterministic programs, probabilistic programs, or modules.

Probabilistic Structural Analysis Methods (PSAM) for Select Space Propulsion System Components

NASA Technical Reports Server (NTRS)

1999-01-01

Probabilistic Structural Analysis Methods (PSAM) are described for the probabilistic structural analysis of engine components for current and future space propulsion systems. Components for these systems are subjected to stochastic thermomechanical launch loads. Uncertainties or randomness also occurs in material properties, structural geometry, and boundary conditions. Material property stochasticity, such as in modulus of elasticity or yield strength, exists in every structure and is a consequence of variations in material composition and manufacturing processes. Procedures are outlined for computing the probabilistic structural response or reliability of the structural components. The response variables include static or dynamic deflections, strains, and stresses at one or several locations, natural frequencies, fatigue or creep life, etc. Sample cases illustrates how the PSAM methods and codes simulate input uncertainties and compute probabilistic response or reliability using a finite element model with probabilistic methods.

Probabilistic Structural Analysis Methods (PSAM) for select space propulsion systems components

NASA Technical Reports Server (NTRS)

1991-01-01

Summarized here is the technical effort and computer code developed during the five year duration of the program for probabilistic structural analysis methods. The summary includes a brief description of the computer code manuals and a detailed description of code validation demonstration cases for random vibrations of a discharge duct, probabilistic material nonlinearities of a liquid oxygen post, and probabilistic buckling of a transfer tube liner.

Probabilistic Requirements (Partial) Verification Methods Best Practices Improvement. Variables Acceptance Sampling Calculators: Derivations and Verification of Plans. Volume 1

NASA Technical Reports Server (NTRS)

Johnson, Kenneth L.; White, K, Preston, Jr.

2012-01-01

The NASA Engineering and Safety Center was requested to improve on the Best Practices document produced for the NESC assessment, Verification of Probabilistic Requirements for the Constellation Program, by giving a recommended procedure for using acceptance sampling by variables techniques. This recommended procedure would be used as an alternative to the potentially resource-intensive acceptance sampling by attributes method given in the document. This document contains the outcome of the assessment.

Superposition-Based Analysis of First-Order Probabilistic Timed Automata

NASA Astrophysics Data System (ADS)

Fietzke, Arnaud; Hermanns, Holger; Weidenbach, Christoph

This paper discusses the analysis of first-order probabilistic timed automata (FPTA) by a combination of hierarchic first-order superposition-based theorem proving and probabilistic model checking. We develop the overall semantics of FPTAs and prove soundness and completeness of our method for reachability properties. Basically, we decompose FPTAs into their time plus first-order logic aspects on the one hand, and their probabilistic aspects on the other hand. Then we exploit the time plus first-order behavior by hierarchic superposition over linear arithmetic. The result of this analysis is the basis for the construction of a reachability equivalent (to the original FPTA) probabilistic timed automaton to which probabilistic model checking is finally applied. The hierarchic superposition calculus required for the analysis is sound and complete on the first-order formulas generated from FPTAs. It even works well in practice. We illustrate the potential behind it with a real-life DHCP protocol example, which we analyze by means of tool chain support.

Probabilistic Structural Analysis of the SRB Aft Skirt External Fitting Modification

NASA Technical Reports Server (NTRS)

Townsend, John S.; Peck, J.; Ayala, S.

1999-01-01

NASA has funded several major programs (the PSAM Project is an example) to develop Probabilistic Structural Analysis Methods and tools for engineers to apply in the design and assessment of aerospace hardware. A probabilistic finite element design tool, known as NESSUS, is used to determine the reliability of the Space Shuttle Solid Rocket Booster (SRB) aft skirt critical weld. An external bracket modification to the aft skirt provides a comparison basis for examining the details of the probabilistic analysis and its contributions to the design process.

Reliability and Probabilistic Risk Assessment - How They Play Together

NASA Technical Reports Server (NTRS)

Safie, Fayssal; Stutts, Richard; Huang, Zhaofeng

2015-01-01

Since the Space Shuttle Challenger accident in 1986, NASA has extensively used probabilistic analysis methods to assess, understand, and communicate the risk of space launch vehicles. Probabilistic Risk Assessment (PRA), used in the nuclear industry, is one of the probabilistic analysis methods NASA utilizes to assess Loss of Mission (LOM) and Loss of Crew (LOC) risk for launch vehicles. PRA is a system scenario based risk assessment that uses a combination of fault trees, event trees, event sequence diagrams, and probability distributions to analyze the risk of a system, a process, or an activity. It is a process designed to answer three basic questions: 1) what can go wrong that would lead to loss or degraded performance (i.e., scenarios involving undesired consequences of interest), 2) how likely is it (probabilities), and 3) what is the severity of the degradation (consequences). Since the Challenger accident, PRA has been used in supporting decisions regarding safety upgrades for launch vehicles. Another area that was given a lot of emphasis at NASA after the Challenger accident is reliability engineering. Reliability engineering has been a critical design function at NASA since the early Apollo days. However, after the Challenger accident, quantitative reliability analysis and reliability predictions were given more scrutiny because of their importance in understanding failure mechanism and quantifying the probability of failure, which are key elements in resolving technical issues, performing design trades, and implementing design improvements. Although PRA and reliability are both probabilistic in nature and, in some cases, use the same tools, they are two different activities. Specifically, reliability engineering is a broad design discipline that deals with loss of function and helps understand failure mechanism and improve component and system design. PRA is a system scenario based risk assessment process intended to assess the risk scenarios that could lead to a major/top undesirable system event, and to identify those scenarios that are high-risk drivers. PRA output is critical to support risk informed decisions concerning system design. This paper describes the PRA process and the reliability engineering discipline in detail. It discusses their differences and similarities and how they work together as complementary analyses to support the design and risk assessment processes. Lessons learned, applications, and case studies in both areas are also discussed in the paper to demonstrate and explain these differences and similarities.

NASA System Safety Handbook. Volume 1; System Safety Framework and Concepts for Implementation

NASA Technical Reports Server (NTRS)

Dezfuli, Homayoon; Benjamin, Allan; Everett, Christopher; Smith, Curtis; Stamatelatos, Michael; Youngblood, Robert

2011-01-01

System safety assessment is defined in NPR 8715.3C, NASA General Safety Program Requirements as a disciplined, systematic approach to the analysis of risks resulting from hazards that can affect humans, the environment, and mission assets. Achievement of the highest practicable degree of system safety is one of NASA's highest priorities. Traditionally, system safety assessment at NASA and elsewhere has focused on the application of a set of safety analysis tools to identify safety risks and formulate effective controls.1 Familiar tools used for this purpose include various forms of hazard analyses, failure modes and effects analyses, and probabilistic safety assessment (commonly also referred to as probabilistic risk assessment (PRA)). In the past, it has been assumed that to show that a system is safe, it is sufficient to provide assurance that the process for identifying the hazards has been as comprehensive as possible and that each identified hazard has one or more associated controls. The NASA Aerospace Safety Advisory Panel (ASAP) has made several statements in its annual reports supporting a more holistic approach. In 2006, it recommended that "... a comprehensive risk assessment, communication and acceptance process be implemented to ensure that overall launch risk is considered in an integrated and consistent manner." In 2009, it advocated for "... a process for using a risk-informed design approach to produce a design that is optimally and sufficiently safe." As a rationale for the latter advocacy, it stated that "... the ASAP applauds switching to a performance-based approach because it emphasizes early risk identification to guide designs, thus enabling creative design approaches that might be more efficient, safer, or both." For purposes of this preface, it is worth mentioning three areas where the handbook emphasizes a more holistic type of thinking. First, the handbook takes the position that it is important to not just focus on risk on an individual basis but to consider measures of aggregate safety risk and to ensure wherever possible that there be quantitative measures for evaluating how effective the controls are in reducing these aggregate risks. The term aggregate risk, when used in this handbook, refers to the accumulation of risks from individual scenarios that lead to a shortfall in safety performance at a high level: e.g., an excessively high probability of loss of crew, loss of mission, planetary contamination, etc. Without aggregated quantitative measures such as these, it is not reasonable to expect that safety has been optimized with respect to other technical and programmatic objectives. At the same time, it is fully recognized that not all sources of risk are amenable to precise quantitative analysis and that the use of qualitative approaches and bounding estimates may be appropriate for those risk sources. Second, the handbook stresses the necessity of developing confidence that the controls derived for the purpose of achieving system safety not only handle risks that have been identified and properly characterized but also provide a general, more holistic means for protecting against unidentified or uncharacterized risks. For example, while it is not possible to be assured that all credible causes of risk have been identified, there are defenses that can provide protection against broad categories of risks and thereby increase the chances that individual causes are contained. Third, the handbook strives at all times to treat uncertainties as an integral aspect of risk and as a part of making decisions. The term "uncertainty" here does not refer to an actuarial type of data analysis, but rather to a characterization of our state of knowledge regarding results from logical and physical models that approximate reality. Uncertainty analysis finds how the output parameters of the models are related to plausible variations in the input parameters and in the modeling assumptions. The evaluation of unrtainties represents a method of probabilistic thinking wherein the analyst and decision makers recognize possible outcomes other than the outcome perceived to be "most likely." Without this type of analysis, it is not possible to determine the worth of an analysis product as a basis for making decisions related to safety and mission success. In line with these considerations the handbook does not take a hazard-analysis-centric approach to system safety. Hazard analysis remains a useful tool to facilitate brainstorming but does not substitute for a more holistic approach geared to a comprehensive identification and understanding of individual risk issues and their contributions to aggregate safety risks. The handbook strives to emphasize the importance of identifying the most critical scenarios that contribute to the risk of not meeting the agreed-upon safety objectives and requirements using all appropriate tools (including but not limited to hazard analysis). Thereafter, emphasis shifts to identifying the risk drivers that cause these scenarios to be critical and ensuring that there are controls directed toward preventing or mitigating the risk drivers. To address these and other areas, the handbook advocates a proactive, analytic-deliberative, risk-informed approach to system safety, enabling the integration of system safety activities with systems engineering and risk management processes. It emphasizes how one can systematically provide the necessary evidence to substantiate the claim that a system is safe to within an acceptable risk tolerance, and that safety has been achieved in a cost-effective manner. The methodology discussed in this handbook is part of a systems engineering process and is intended to be integral to the system safety practices being conducted by the NASA safety and mission assurance and systems engineering organizations. The handbook posits that to conclude that a system is adequately safe, it is necessary to consider a set of safety claims that derive from the safety objectives of the organization. The safety claims are developed from a hierarchy of safety objectives and are therefore hierarchical themselves. Assurance that all the claims are true within acceptable risk tolerance limits implies that all of the safety objectives have been satisfied, and therefore that the system is safe. The acceptable risk tolerance limits are provided by the authority who must make the decision whether or not to proceed to the next step in the life cycle. These tolerances are therefore referred to as the decision maker's risk tolerances. In general, the safety claims address two fundamental facets of safety: 1) whether required safety thresholds or goals have been achieved, and 2) whether the safety risk is as low as possible within reasonable impacts on cost, schedule, and performance. The latter facet includes consideration of controls that are collective in nature (i.e., apply generically to broad categories of risks) and thereby provide protection against unidentified or uncharacterized risks.

Probabilistic Structural Analysis Theory Development

NASA Technical Reports Server (NTRS)

Burnside, O. H.

1985-01-01

The objective of the Probabilistic Structural Analysis Methods (PSAM) project is to develop analysis techniques and computer programs for predicting the probabilistic response of critical structural components for current and future space propulsion systems. This technology will play a central role in establishing system performance and durability. The first year's technical activity is concentrating on probabilistic finite element formulation strategy and code development. Work is also in progress to survey critical materials and space shuttle mian engine components. The probabilistic finite element computer program NESSUS (Numerical Evaluation of Stochastic Structures Under Stress) is being developed. The final probabilistic code will have, in the general case, the capability of performing nonlinear dynamic of stochastic structures. It is the goal of the approximate methods effort to increase problem solving efficiency relative to finite element methods by using energy methods to generate trial solutions which satisfy the structural boundary conditions. These approximate methods will be less computer intensive relative to the finite element approach.

Analyzing system safety in lithium-ion grid energy storage

DOE PAGES

Rosewater, David; Williams, Adam

2015-10-08

As grid energy storage systems become more complex, it grows more di cult to design them for safe operation. This paper first reviews the properties of lithium-ion batteries that can produce hazards in grid scale systems. Then the conventional safety engineering technique Probabilistic Risk Assessment (PRA) is reviewed to identify its limitations in complex systems. To address this gap, new research is presented on the application of Systems-Theoretic Process Analysis (STPA) to a lithium-ion battery based grid energy storage system. STPA is anticipated to ll the gaps recognized in PRA for designing complex systems and hence be more e ectivemore » or less costly to use during safety engineering. It was observed that STPA is able to capture causal scenarios for accidents not identified using PRA. Additionally, STPA enabled a more rational assessment of uncertainty (all that is not known) thereby promoting a healthy skepticism of design assumptions. Lastly, we conclude that STPA may indeed be more cost effective than PRA for safety engineering in lithium-ion battery systems. However, further research is needed to determine if this approach actually reduces safety engineering costs in development, or improves industry safety standards.« less

Probabilistic Structural Analysis Methods (PSAM) for select space propulsion system components

NASA Technical Reports Server (NTRS)

1991-01-01

The fourth year of technical developments on the Numerical Evaluation of Stochastic Structures Under Stress (NESSUS) system for Probabilistic Structural Analysis Methods is summarized. The effort focused on the continued expansion of the Probabilistic Finite Element Method (PFEM) code, the implementation of the Probabilistic Boundary Element Method (PBEM), and the implementation of the Probabilistic Approximate Methods (PAppM) code. The principal focus for the PFEM code is the addition of a multilevel structural dynamics capability. The strategy includes probabilistic loads, treatment of material, geometry uncertainty, and full probabilistic variables. Enhancements are included for the Fast Probability Integration (FPI) algorithms and the addition of Monte Carlo simulation as an alternate. Work on the expert system and boundary element developments continues. The enhanced capability in the computer codes is validated by applications to a turbine blade and to an oxidizer duct.

Multimodal integration of micro-Doppler sonar and auditory signals for behavior classification with convolutional networks.

PubMed

Dura-Bernal, Salvador; Garreau, Guillaume; Georgiou, Julius; Andreou, Andreas G; Denham, Susan L; Wennekers, Thomas

2013-10-01

The ability to recognize the behavior of individuals is of great interest in the general field of safety (e.g. building security, crowd control, transport analysis, independent living for the elderly). Here we report a new real-time acoustic system for human action and behavior recognition that integrates passive audio and active micro-Doppler sonar signatures over multiple time scales. The system architecture is based on a six-layer convolutional neural network, trained and evaluated using a dataset of 10 subjects performing seven different behaviors. Probabilistic combination of system output through time for each modality separately yields 94% (passive audio) and 91% (micro-Doppler sonar) correct behavior classification; probabilistic multimodal integration increases classification performance to 98%. This study supports the efficacy of micro-Doppler sonar systems in characterizing human actions, which can then be efficiently classified using ConvNets. It also demonstrates that the integration of multiple sources of acoustic information can significantly improve the system's performance.

Probabilistic fatigue life prediction of metallic and composite materials

NASA Astrophysics Data System (ADS)

Xiang, Yibing

Fatigue is one of the most common failure modes for engineering structures, such as aircrafts, rotorcrafts and aviation transports. Both metallic materials and composite materials are widely used and affected by fatigue damage. Huge uncertainties arise from material properties, measurement noise, imperfect models, future anticipated loads and environmental conditions. These uncertainties are critical issues for accurate remaining useful life (RUL) prediction for engineering structures in service. Probabilistic fatigue prognosis considering various uncertainties is of great importance for structural safety. The objective of this study is to develop probabilistic fatigue life prediction models for metallic materials and composite materials. A fatigue model based on crack growth analysis and equivalent initial flaw size concept is proposed for metallic materials. Following this, the developed model is extended to include structural geometry effects (notch effect), environmental effects (corroded specimens) and manufacturing effects (shot peening effects). Due to the inhomogeneity and anisotropy, the fatigue model suitable for metallic materials cannot be directly applied to composite materials. A composite fatigue model life prediction is proposed based on a mixed-mode delamination growth model and a stiffness degradation law. After the development of deterministic fatigue models of metallic and composite materials, a general probabilistic life prediction methodology is developed. The proposed methodology combines an efficient Inverse First-Order Reliability Method (IFORM) for the uncertainty propogation in fatigue life prediction. An equivalent stresstransformation has been developed to enhance the computational efficiency under realistic random amplitude loading. A systematical reliability-based maintenance optimization framework is proposed for fatigue risk management and mitigation of engineering structures.

The Study of the Relationship between Probabilistic Design and Axiomatic Design Methodology. Volume 2

NASA Technical Reports Server (NTRS)

Onwubiko, Chin-Yere; Onyebueke, Landon

1996-01-01

The structural design, or the design of machine elements, has been traditionally based on deterministic design methodology. The deterministic method considers all design parameters to be known with certainty. This methodology is, therefore, inadequate to design complex structures that are subjected to a variety of complex, severe loading conditions. A nonlinear behavior that is dependent on stress, stress rate, temperature, number of load cycles, and time is observed on all components subjected to complex conditions. These complex conditions introduce uncertainties; hence, the actual factor of safety margin remains unknown. In the deterministic methodology, the contingency of failure is discounted; hence, there is a use of a high factor of safety. It may be most useful in situations where the design structures are simple. The probabilistic method is concerned with the probability of non-failure performance of structures or machine elements. It is much more useful in situations where the design is characterized by complex geometry, possibility of catastrophic failure, sensitive loads and material properties. Also included: Comparative Study of the use of AGMA Geometry Factors and Probabilistic Design Methodology in the Design of Compact Spur Gear Set.

Probabilistic Evaluation of Advanced Ceramic Matrix Composite Structures

NASA Technical Reports Server (NTRS)

Abumeri, Galib H.; Chamis, Christos C.

2003-01-01

The objective of this report is to summarize the deterministic and probabilistic structural evaluation results of two structures made with advanced ceramic composites (CMC): internally pressurized tube and uniformly loaded flange. The deterministic structural evaluation includes stress, displacement, and buckling analyses. It is carried out using the finite element code MHOST, developed for the 3-D inelastic analysis of structures that are made with advanced materials. The probabilistic evaluation is performed using the integrated probabilistic assessment of composite structures computer code IPACS. The affects of uncertainties in primitive variables related to the material, fabrication process, and loadings on the material property and structural response behavior are quantified. The primitive variables considered are: thermo-mechanical properties of fiber and matrix, fiber and void volume ratios, use temperature, and pressure. The probabilistic structural analysis and probabilistic strength results are used by IPACS to perform reliability and risk evaluation of the two structures. The results will show that the sensitivity information obtained for the two composite structures from the computational simulation can be used to alter the design process to meet desired service requirements. In addition to detailed probabilistic analysis of the two structures, the following were performed specifically on the CMC tube: (1) predicted the failure load and the buckling load, (2) performed coupled non-deterministic multi-disciplinary structural analysis, and (3) demonstrated that probabilistic sensitivities can be used to select a reduced set of design variables for optimization.

Probabilistic QoS Analysis In Wireless Sensor Networks

DTIC Science & Technology

2012-04-01

and A.O. Fapojuwo. TDMA scheduling with optimized energy efficiency and minimum delay in clustered wireless sensor networks . IEEE Trans. on Mobile...Research Computer Science and Engineering, Department of 5-1-2012 Probabilistic QoS Analysis in Wireless Sensor Networks Yunbo Wang University of...Wang, Yunbo, "Probabilistic QoS Analysis in Wireless Sensor Networks " (2012). Computer Science and Engineering: Theses, Dissertations, and Student

Process for computing geometric perturbations for probabilistic analysis

DOEpatents

Fitch, Simeon H. K. [Charlottesville, VA; Riha, David S [San Antonio, TX; Thacker, Ben H [San Antonio, TX

2012-04-10

A method for computing geometric perturbations for probabilistic analysis. The probabilistic analysis is based on finite element modeling, in which uncertainties in the modeled system are represented by changes in the nominal geometry of the model, referred to as "perturbations". These changes are accomplished using displacement vectors, which are computed for each node of a region of interest and are based on mean-value coordinate calculations.

Developing safety performance functions incorporating reliability-based risk measures.

PubMed

Ibrahim, Shewkar El-Bassiouni; Sayed, Tarek

2011-11-01

Current geometric design guides provide deterministic standards where the safety margin of the design output is generally unknown and there is little knowledge of the safety implications of deviating from these standards. Several studies have advocated probabilistic geometric design where reliability analysis can be used to account for the uncertainty in the design parameters and to provide a risk measure of the implication of deviation from design standards. However, there is currently no link between measures of design reliability and the quantification of safety using collision frequency. The analysis presented in this paper attempts to bridge this gap by incorporating a reliability-based quantitative risk measure such as the probability of non-compliance (P(nc)) in safety performance functions (SPFs). Establishing this link will allow admitting reliability-based design into traditional benefit-cost analysis and should lead to a wider application of the reliability technique in road design. The present application is concerned with the design of horizontal curves, where the limit state function is defined in terms of the available (supply) and stopping (demand) sight distances. A comprehensive collision and geometric design database of two-lane rural highways is used to investigate the effect of the probability of non-compliance on safety. The reliability analysis was carried out using the First Order Reliability Method (FORM). Two Negative Binomial (NB) SPFs were developed to compare models with and without the reliability-based risk measures. It was found that models incorporating the P(nc) provided a better fit to the data set than the traditional (without risk) NB SPFs for total, injury and fatality (I+F) and property damage only (PDO) collisions. Copyright © 2011 Elsevier Ltd. All rights reserved.

Probabilistic structural analysis using a general purpose finite element program

NASA Astrophysics Data System (ADS)

Riha, D. S.; Millwater, H. R.; Thacker, B. H.

1992-07-01

This paper presents an accurate and efficient method to predict the probabilistic response for structural response quantities, such as stress, displacement, natural frequencies, and buckling loads, by combining the capabilities of MSC/NASTRAN, including design sensitivity analysis and fast probability integration. Two probabilistic structural analysis examples have been performed and verified by comparison with Monte Carlo simulation of the analytical solution. The first example consists of a cantilevered plate with several point loads. The second example is a probabilistic buckling analysis of a simply supported composite plate under in-plane loading. The coupling of MSC/NASTRAN and fast probability integration is shown to be orders of magnitude more efficient than Monte Carlo simulation with excellent accuracy.

On the Accuracy of Probabilistic Bucking Load Prediction

NASA Technical Reports Server (NTRS)

Arbocz, Johann; Starnes, James H.; Nemeth, Michael P.

2001-01-01

The buckling strength of thin-walled stiffened or unstiffened, metallic or composite shells is of major concern in aeronautical and space applications. The difficulty to predict the behavior of axially compressed thin-walled cylindrical shells continues to worry design engineers as we enter the third millennium. Thanks to extensive research programs in the late sixties and early seventies and the contributions of many eminent scientists, it is known that buckling strength calculations are affected by the uncertainties in the definition of the parameters of the problem such as definition of loads, material properties, geometric variables, edge support conditions, and the accuracy of the engineering models and analysis tools used in the design phase. The NASA design criteria monographs from the late sixties account for these design uncertainties by the use of a lump sum safety factor. This so-called 'empirical knockdown factor gamma' usually results in overly conservative design. Recently new reliability based probabilistic design procedure for buckling critical imperfect shells have been proposed. It essentially consists of a stochastic approach which introduces an improved 'scientific knockdown factor lambda(sub a)', that is not as conservative as the traditional empirical one. In order to incorporate probabilistic methods into a High Fidelity Analysis Approach one must be able to assess the accuracy of the various steps that must be executed to complete a reliability calculation. In the present paper the effect of size of the experimental input sample on the predicted value of the scientific knockdown factor lambda(sub a) calculated by the First-Order, Second-Moment Method is investigated.

A dynamical systems model for nuclear power plant risk

NASA Astrophysics Data System (ADS)

Hess, Stephen Michael

The recent transition to an open access generation marketplace has forced nuclear plant operators to become much more cost conscious and focused on plant performance. Coincidentally, the regulatory perspective also is in a state of transition from a command and control framework to one that is risk-informed and performance-based. Due to these structural changes in the economics and regulatory system associated with commercial nuclear power plant operation, there is an increased need for plant management to explicitly manage nuclear safety risk. Application of probabilistic risk assessment techniques to model plant hardware has provided a significant contribution to understanding the potential initiating events and equipment failures that can lead to core damage accidents. Application of the lessons learned from these analyses has supported improved plant operation and safety over the previous decade. However, this analytical approach has not been nearly as successful in addressing the impact of plant processes and management effectiveness on the risks of plant operation. Thus, the research described in this dissertation presents a different approach to address this issue. Here we propose a dynamical model that describes the interaction of important plant processes among themselves and their overall impact on nuclear safety risk. We first provide a review of the techniques that are applied in a conventional probabilistic risk assessment of commercially operating nuclear power plants and summarize the typical results obtained. The limitations of the conventional approach and the status of research previously performed to address these limitations also are presented. Next, we present the case for the application of an alternative approach using dynamical systems theory. This includes a discussion of previous applications of dynamical models to study other important socio-economic issues. Next, we review the analytical techniques that are applicable to analysis of these models. Details of the development of the mathematical risk model are presented. This includes discussion of the processes included in the model and the identification of significant interprocess interactions. This is followed by analysis of the model that demonstrates that its dynamical evolution displays characteristics that have been observed at commercially operating plants. The model is analyzed using the previously described techniques from dynamical systems theory. From this analysis, several significant insights are obtained with respect to the effective control of nuclear safety risk. Finally, we present conclusions and recommendations for further research.

Probabilistic Requirements (Partial) Verification Methods Best Practices Improvement. Variables Acceptance Sampling Calculators: Empirical Testing. Volume 2

NASA Technical Reports Server (NTRS)

Johnson, Kenneth L.; White, K. Preston, Jr.

2012-01-01

The NASA Engineering and Safety Center was requested to improve on the Best Practices document produced for the NESC assessment, Verification of Probabilistic Requirements for the Constellation Program, by giving a recommended procedure for using acceptance sampling by variables techniques as an alternative to the potentially resource-intensive acceptance sampling by attributes method given in the document. In this paper, the results of empirical tests intended to assess the accuracy of acceptance sampling plan calculators implemented for six variable distributions are presented.

A comprehensive probabilistic analysis model of oil pipelines network based on Bayesian network

NASA Astrophysics Data System (ADS)

Zhang, C.; Qin, T. X.; Jiang, B.; Huang, C.

2018-02-01

Oil pipelines network is one of the most important facilities of energy transportation. But oil pipelines network accident may result in serious disasters. Some analysis models for these accidents have been established mainly based on three methods, including event-tree, accident simulation and Bayesian network. Among these methods, Bayesian network is suitable for probabilistic analysis. But not all the important influencing factors are considered and the deployment rule of the factors has not been established. This paper proposed a probabilistic analysis model of oil pipelines network based on Bayesian network. Most of the important influencing factors, including the key environment condition and emergency response are considered in this model. Moreover, the paper also introduces a deployment rule for these factors. The model can be used in probabilistic analysis and sensitive analysis of oil pipelines network accident.

Probabilistic Risk Assessment: A Bibliography

NASA Technical Reports Server (NTRS)

2000-01-01

Probabilistic risk analysis is an integration of failure modes and effects analysis (FMEA), fault tree analysis and other techniques to assess the potential for failure and to find ways to reduce risk. This bibliography references 160 documents in the NASA STI Database that contain the major concepts, probabilistic risk assessment, risk and probability theory, in the basic index or major subject terms, An abstract is included with most citations, followed by the applicable subject terms.

Probabilistic Sensitivity Analysis with Respect to Bounds of Truncated Distributions (PREPRINT)

DTIC Science & Technology

2010-04-01

AFRL-RX-WP-TP-2010-4147 PROBABILISTIC SENSITIVITY ANALYSIS WITH RESPECT TO BOUNDS OF TRUNCATED DISTRIBUTIONS (PREPRINT) H. Millwater and...5a. CONTRACT NUMBER In-house 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 62102F 6. AUTHOR(S) H. Millwater and Y. Feng 5d. PROJECT...Z39-18 1 Probabilistic Sensitivity Analysis with respect to Bounds of Truncated Distributions H. Millwater and Y. Feng Department of Mechanical

System Level Uncertainty Assessment for Collaborative RLV Design

NASA Technical Reports Server (NTRS)

Charania, A. C.; Bradford, John E.; Olds, John R.; Graham, Matthew

2002-01-01

A collaborative design process utilizing Probabilistic Data Assessment (PDA) is showcased. Given the limitation of financial resources by both the government and industry, strategic decision makers need more than just traditional point designs, they need to be aware of the likelihood of these future designs to meet their objectives. This uncertainty, an ever-present character in the design process, can be embraced through a probabilistic design environment. A conceptual design process is presented that encapsulates the major engineering disciplines for a Third Generation Reusable Launch Vehicle (RLV). Toolsets consist of aerospace industry standard tools in disciplines such as trajectory, propulsion, mass properties, cost, operations, safety, and economics. Variations of the design process are presented that use different fidelities of tools. The disciplinary engineering models are used in a collaborative engineering framework utilizing Phoenix Integration's ModelCenter and AnalysisServer environment. These tools allow the designer to join disparate models and simulations together in a unified environment wherein each discipline can interact with any other discipline. The design process also uses probabilistic methods to generate the system level output metrics of interest for a RLV conceptual design. The specific system being examined is the Advanced Concept Rocket Engine 92 (ACRE-92) RLV. Previous experience and knowledge (in terms of input uncertainty distributions from experts and modeling and simulation codes) can be coupled with Monte Carlo processes to best predict the chances of program success.

Probabilistic simulation of uncertainties in thermal structures

NASA Technical Reports Server (NTRS)

Chamis, Christos C.; Shiao, Michael

1990-01-01

Development of probabilistic structural analysis methods for hot structures is a major activity at Lewis Research Center. It consists of five program elements: (1) probabilistic loads; (2) probabilistic finite element analysis; (3) probabilistic material behavior; (4) assessment of reliability and risk; and (5) probabilistic structural performance evaluation. Recent progress includes: (1) quantification of the effects of uncertainties for several variables on high pressure fuel turbopump (HPFT) blade temperature, pressure, and torque of the Space Shuttle Main Engine (SSME); (2) the evaluation of the cumulative distribution function for various structural response variables based on assumed uncertainties in primitive structural variables; (3) evaluation of the failure probability; (4) reliability and risk-cost assessment, and (5) an outline of an emerging approach for eventual hot structures certification. Collectively, the results demonstrate that the structural durability/reliability of hot structural components can be effectively evaluated in a formal probabilistic framework. In addition, the approach can be readily extended to computationally simulate certification of hot structures for aerospace environments.

A probabilistic Hu-Washizu variational principle

NASA Technical Reports Server (NTRS)

Liu, W. K.; Belytschko, T.; Besterfield, G. H.

1987-01-01

A Probabilistic Hu-Washizu Variational Principle (PHWVP) for the Probabilistic Finite Element Method (PFEM) is presented. This formulation is developed for both linear and nonlinear elasticity. The PHWVP allows incorporation of the probabilistic distributions for the constitutive law, compatibility condition, equilibrium, domain and boundary conditions into the PFEM. Thus, a complete probabilistic analysis can be performed where all aspects of the problem are treated as random variables and/or fields. The Hu-Washizu variational formulation is available in many conventional finite element codes thereby enabling the straightforward inclusion of the probabilistic features into present codes.

Safety design approach for external events in Japan sodium-cooled fast reactor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yamano, H.; Kubo, S.; Tani, A.

2012-07-01

This paper describes a safety design approach for external events in the design study of Japan sodium-cooled fast reactor. An emphasis is introduction of a design extension external condition (DEEC). In addition to seismic design, other external events such as tsunami, strong wind, abnormal temperature, etc. were addressed in this study. From a wide variety of external events consisting of natural hazards and human-induced ones, a screening method was developed in terms of siting, consequence, frequency to select representative events. Design approaches for these events were categorized on the probabilistic, statistical and deterministic basis. External hazard conditions were considered mainlymore » for DEECs. In the probabilistic approach, the DEECs of earthquake, tsunami and strong wind were defined as 1/10 of exceedance probability of the external design bases. The other representative DEECs were also defined based on statistical or deterministic approaches. (authors)« less

Specifying design conservatism: Worst case versus probabilistic analysis

NASA Technical Reports Server (NTRS)

Miles, Ralph F., Jr.

1993-01-01

Design conservatism is the difference between specified and required performance, and is introduced when uncertainty is present. The classical approach of worst-case analysis for specifying design conservatism is presented, along with the modern approach of probabilistic analysis. The appropriate degree of design conservatism is a tradeoff between the required resources and the probability and consequences of a failure. A probabilistic analysis properly models this tradeoff, while a worst-case analysis reveals nothing about the probability of failure, and can significantly overstate the consequences of failure. Two aerospace examples will be presented that illustrate problems that can arise with a worst-case analysis.

Probabilistic margin evaluation on accidental transients for the ASTRID reactor project

NASA Astrophysics Data System (ADS)

Marquès, Michel

2014-06-01

ASTRID is a technological demonstrator of Sodium cooled Fast Reactor (SFR) under development. The conceptual design studies are being conducted in accordance with the Generation IV reactor objectives, particularly in terms of improving safety. For the hypothetical events, belonging to the accidental category "severe accident prevention situations" having a very low frequency of occurrence, the safety demonstration is no more based on a deterministic demonstration with conservative assumptions on models and parameters but on a "Best-Estimate Plus Uncertainty" (BEPU) approach. This BEPU approach ispresented in this paper for an Unprotected Loss-of-Flow (ULOF) event. The Best-Estimate (BE) analysis of this ULOFt ransient is performed with the CATHARE2 code, which is the French reference system code for SFR applications. The objective of the BEPU analysis is twofold: first evaluate the safety margin to sodium boiling in taking into account the uncertainties on the input parameters of the CATHARE2 code (twenty-two uncertain input parameters have been identified, which can be classified into five groups: reactor power, accident management, pumps characteristics, reactivity coefficients, thermal parameters and head losses); secondly quantify the contribution of each input uncertainty to the overall uncertainty of the safety margins, in order to refocusing R&D efforts on the most influential factors. This paper focuses on the methodological aspects of the evaluation of the safety margin. At least for the preliminary phase of the project (conceptual design), a probabilistic criterion has been fixed in the context of this BEPU analysis; this criterion is the value of the margin to sodium boiling, which has a probability 95% to be exceeded, obtained with a confidence level of 95% (i.e. the M5,95percentile of the margin distribution). This paper presents two methods used to assess this percentile: the Wilks method and the Bootstrap method ; the effectiveness of the two methods is compared on the basis of 500 simulations performed with theCATHARE2 code. We conclude that, with only 100 simulations performed with the CATHARE2 code, which is a number of simulations workable in the conceptual design phase of the ASTRID project where the models and the hypothesis are often modified, it is best in order to evaluate the percentile M5,95 of the margin to sodium boiling to use the bootstrap method, which will provide a slightly conservative result. On the other hand, in order to obtain an accurate estimation of the percentileM5,95, for the safety report for example, it will be necessary to perform at least 300 simulations with the CATHARE2 code. In this case, both methods (Wilks and Bootstrap) would give equivalent results.

Life Predicted in a Probabilistic Design Space for Brittle Materials With Transient Loads

NASA Technical Reports Server (NTRS)

Nemeth, Noel N.; Palfi, Tamas; Reh, Stefan

2005-01-01

Analytical techniques have progressively become more sophisticated, and now we can consider the probabilistic nature of the entire space of random input variables on the lifetime reliability of brittle structures. This was demonstrated with NASA s CARES/Life (Ceramic Analysis and Reliability Evaluation of Structures/Life) code combined with the commercially available ANSYS/Probabilistic Design System (ANSYS/PDS), a probabilistic analysis tool that is an integral part of the ANSYS finite-element analysis program. ANSYS/PDS allows probabilistic loads, component geometry, and material properties to be considered in the finite-element analysis. CARES/Life predicts the time dependent probability of failure of brittle material structures under generalized thermomechanical loading--such as that found in a turbine engine hot-section. Glenn researchers coupled ANSYS/PDS with CARES/Life to assess the effects of the stochastic variables of component geometry, loading, and material properties on the predicted life of the component for fully transient thermomechanical loading and cyclic loading.

Modeling Uncertainties in EEG Microstates: Analysis of Real and Imagined Motor Movements Using Probabilistic Clustering-Driven Training of Probabilistic Neural Networks.

PubMed

Dinov, Martin; Leech, Robert

2017-01-01

Part of the process of EEG microstate estimation involves clustering EEG channel data at the global field power (GFP) maxima, very commonly using a modified K-means approach. Clustering has also been done deterministically, despite there being uncertainties in multiple stages of the microstate analysis, including the GFP peak definition, the clustering itself and in the post-clustering assignment of microstates back onto the EEG timecourse of interest. We perform a fully probabilistic microstate clustering and labeling, to account for these sources of uncertainty using the closest probabilistic analog to KM called Fuzzy C-means (FCM). We train softmax multi-layer perceptrons (MLPs) using the KM and FCM-inferred cluster assignments as target labels, to then allow for probabilistic labeling of the full EEG data instead of the usual correlation-based deterministic microstate label assignment typically used. We assess the merits of the probabilistic analysis vs. the deterministic approaches in EEG data recorded while participants perform real or imagined motor movements from a publicly available data set of 109 subjects. Though FCM group template maps that are almost topographically identical to KM were found, there is considerable uncertainty in the subsequent assignment of microstate labels. In general, imagined motor movements are less predictable on a time point-by-time point basis, possibly reflecting the more exploratory nature of the brain state during imagined, compared to during real motor movements. We find that some relationships may be more evident using FCM than using KM and propose that future microstate analysis should preferably be performed probabilistically rather than deterministically, especially in situations such as with brain computer interfaces, where both training and applying models of microstates need to account for uncertainty. Probabilistic neural network-driven microstate assignment has a number of advantages that we have discussed, which are likely to be further developed and exploited in future studies. In conclusion, probabilistic clustering and a probabilistic neural network-driven approach to microstate analysis is likely to better model and reveal details and the variability hidden in current deterministic and binarized microstate assignment and analyses.

Modeling Uncertainties in EEG Microstates: Analysis of Real and Imagined Motor Movements Using Probabilistic Clustering-Driven Training of Probabilistic Neural Networks

PubMed Central

Dinov, Martin; Leech, Robert

2017-01-01

Part of the process of EEG microstate estimation involves clustering EEG channel data at the global field power (GFP) maxima, very commonly using a modified K-means approach. Clustering has also been done deterministically, despite there being uncertainties in multiple stages of the microstate analysis, including the GFP peak definition, the clustering itself and in the post-clustering assignment of microstates back onto the EEG timecourse of interest. We perform a fully probabilistic microstate clustering and labeling, to account for these sources of uncertainty using the closest probabilistic analog to KM called Fuzzy C-means (FCM). We train softmax multi-layer perceptrons (MLPs) using the KM and FCM-inferred cluster assignments as target labels, to then allow for probabilistic labeling of the full EEG data instead of the usual correlation-based deterministic microstate label assignment typically used. We assess the merits of the probabilistic analysis vs. the deterministic approaches in EEG data recorded while participants perform real or imagined motor movements from a publicly available data set of 109 subjects. Though FCM group template maps that are almost topographically identical to KM were found, there is considerable uncertainty in the subsequent assignment of microstate labels. In general, imagined motor movements are less predictable on a time point-by-time point basis, possibly reflecting the more exploratory nature of the brain state during imagined, compared to during real motor movements. We find that some relationships may be more evident using FCM than using KM and propose that future microstate analysis should preferably be performed probabilistically rather than deterministically, especially in situations such as with brain computer interfaces, where both training and applying models of microstates need to account for uncertainty. Probabilistic neural network-driven microstate assignment has a number of advantages that we have discussed, which are likely to be further developed and exploited in future studies. In conclusion, probabilistic clustering and a probabilistic neural network-driven approach to microstate analysis is likely to better model and reveal details and the variability hidden in current deterministic and binarized microstate assignment and analyses. PMID:29163110

A Case Study for Probabilistic Methods Validation (MSFC Center Director's Discretionary Fund, Project No. 94-26)

NASA Technical Reports Server (NTRS)

Price J. M.; Ortega, R.

1998-01-01

Probabilistic method is not a universally accepted approach for the design and analysis of aerospace structures. The validity of this approach must be demonstrated to encourage its acceptance as it viable design and analysis tool to estimate structural reliability. The objective of this Study is to develop a well characterized finite population of similar aerospace structures that can be used to (1) validate probabilistic codes, (2) demonstrate the basic principles behind probabilistic methods, (3) formulate general guidelines for characterization of material drivers (such as elastic modulus) when limited data is available, and (4) investigate how the drivers affect the results of sensitivity analysis at the component/failure mode level.

A Comparison of Probabilistic and Deterministic Campaign Analysis for Human Space Exploration

NASA Technical Reports Server (NTRS)

Merrill, R. Gabe; Andraschko, Mark; Stromgren, Chel; Cirillo, Bill; Earle, Kevin; Goodliff, Kandyce

2008-01-01

Human space exploration is by its very nature an uncertain endeavor. Vehicle reliability, technology development risk, budgetary uncertainty, and launch uncertainty all contribute to stochasticity in an exploration scenario. However, traditional strategic analysis has been done in a deterministic manner, analyzing and optimizing the performance of a series of planned missions. History has shown that exploration scenarios rarely follow such a planned schedule. This paper describes a methodology to integrate deterministic and probabilistic analysis of scenarios in support of human space exploration. Probabilistic strategic analysis is used to simulate "possible" scenario outcomes, based upon the likelihood of occurrence of certain events and a set of pre-determined contingency rules. The results of the probabilistic analysis are compared to the nominal results from the deterministic analysis to evaluate the robustness of the scenario to adverse events and to test and optimize contingency planning.

Probabilistic sensitivity analysis incorporating the bootstrap: an example comparing treatments for the eradication of Helicobacter pylori.

PubMed

Pasta, D J; Taylor, J L; Henning, J M

1999-01-01

Decision-analytic models are frequently used to evaluate the relative costs and benefits of alternative therapeutic strategies for health care. Various types of sensitivity analysis are used to evaluate the uncertainty inherent in the models. Although probabilistic sensitivity analysis is more difficult theoretically and computationally, the results can be much more powerful and useful than deterministic sensitivity analysis. The authors show how a Monte Carlo simulation can be implemented using standard software to perform a probabilistic sensitivity analysis incorporating the bootstrap. The method is applied to a decision-analytic model evaluating the cost-effectiveness of Helicobacter pylori eradication. The necessary steps are straightforward and are described in detail. The use of the bootstrap avoids certain difficulties encountered with theoretical distributions. The probabilistic sensitivity analysis provided insights into the decision-analytic model beyond the traditional base-case and deterministic sensitivity analyses and should become the standard method for assessing sensitivity.

Global/local methods for probabilistic structural analysis

NASA Technical Reports Server (NTRS)

Millwater, H. R.; Wu, Y.-T.

1993-01-01

A probabilistic global/local method is proposed to reduce the computational requirements of probabilistic structural analysis. A coarser global model is used for most of the computations with a local more refined model used only at key probabilistic conditions. The global model is used to establish the cumulative distribution function (cdf) and the Most Probable Point (MPP). The local model then uses the predicted MPP to adjust the cdf value. The global/local method is used within the advanced mean value probabilistic algorithm. The local model can be more refined with respect to the g1obal model in terms of finer mesh, smaller time step, tighter tolerances, etc. and can be used with linear or nonlinear models. The basis for this approach is described in terms of the correlation between the global and local models which can be estimated from the global and local MPPs. A numerical example is presented using the NESSUS probabilistic structural analysis program with the finite element method used for the structural modeling. The results clearly indicate a significant computer savings with minimal loss in accuracy.

Global/local methods for probabilistic structural analysis

NASA Astrophysics Data System (ADS)

Millwater, H. R.; Wu, Y.-T.

1993-04-01

A probabilistic global/local method is proposed to reduce the computational requirements of probabilistic structural analysis. A coarser global model is used for most of the computations with a local more refined model used only at key probabilistic conditions. The global model is used to establish the cumulative distribution function (cdf) and the Most Probable Point (MPP). The local model then uses the predicted MPP to adjust the cdf value. The global/local method is used within the advanced mean value probabilistic algorithm. The local model can be more refined with respect to the g1obal model in terms of finer mesh, smaller time step, tighter tolerances, etc. and can be used with linear or nonlinear models. The basis for this approach is described in terms of the correlation between the global and local models which can be estimated from the global and local MPPs. A numerical example is presented using the NESSUS probabilistic structural analysis program with the finite element method used for the structural modeling. The results clearly indicate a significant computer savings with minimal loss in accuracy.

Structural reliability methods: Code development status

NASA Astrophysics Data System (ADS)

Millwater, Harry R.; Thacker, Ben H.; Wu, Y.-T.; Cruse, T. A.

1991-05-01

The Probabilistic Structures Analysis Method (PSAM) program integrates state of the art probabilistic algorithms with structural analysis methods in order to quantify the behavior of Space Shuttle Main Engine structures subject to uncertain loadings, boundary conditions, material parameters, and geometric conditions. An advanced, efficient probabilistic structural analysis software program, NESSUS (Numerical Evaluation of Stochastic Structures Under Stress) was developed as a deliverable. NESSUS contains a number of integrated software components to perform probabilistic analysis of complex structures. A nonlinear finite element module NESSUS/FEM is used to model the structure and obtain structural sensitivities. Some of the capabilities of NESSUS/FEM are shown. A Fast Probability Integration module NESSUS/FPI estimates the probability given the structural sensitivities. A driver module, PFEM, couples the FEM and FPI. NESSUS, version 5.0, addresses component reliability, resistance, and risk.

Structural reliability methods: Code development status

NASA Technical Reports Server (NTRS)

Millwater, Harry R.; Thacker, Ben H.; Wu, Y.-T.; Cruse, T. A.

1991-01-01

The Probabilistic Structures Analysis Method (PSAM) program integrates state of the art probabilistic algorithms with structural analysis methods in order to quantify the behavior of Space Shuttle Main Engine structures subject to uncertain loadings, boundary conditions, material parameters, and geometric conditions. An advanced, efficient probabilistic structural analysis software program, NESSUS (Numerical Evaluation of Stochastic Structures Under Stress) was developed as a deliverable. NESSUS contains a number of integrated software components to perform probabilistic analysis of complex structures. A nonlinear finite element module NESSUS/FEM is used to model the structure and obtain structural sensitivities. Some of the capabilities of NESSUS/FEM are shown. A Fast Probability Integration module NESSUS/FPI estimates the probability given the structural sensitivities. A driver module, PFEM, couples the FEM and FPI. NESSUS, version 5.0, addresses component reliability, resistance, and risk.

How Can You Support RIDM/CRM/RM Through the Use of PRA

NASA Technical Reports Server (NTRS)

DoVemto. Tpmu

2011-01-01

Probabilistic Risk Assessment (PRA) is one of key Risk Informed Decision Making (RIDM) tools. It is a scenario-based methodology aimed at identifying and assessing Safety and Technical Performance risks in complex technological systems.

Probabilistic Structural Analysis Methods for select space propulsion system components (PSAM). Volume 3: Literature surveys and technical reports

NASA Technical Reports Server (NTRS)

1992-01-01

The technical effort and computer code developed during the first year are summarized. Several formulations for Probabilistic Finite Element Analysis (PFEA) are described with emphasis on the selected formulation. The strategies being implemented in the first-version computer code to perform linear, elastic PFEA is described. The results of a series of select Space Shuttle Main Engine (SSME) component surveys are presented. These results identify the critical components and provide the information necessary for probabilistic structural analysis.

NSTS Orbiter auxiliary power unit turbine wheel cracking risk assessment

NASA Technical Reports Server (NTRS)

Cruse, T. A.; Mcclung, R. C.; Torng, T. Y.

1992-01-01

The present investigation of turbine-wheel cracking problems in the hydrazine-fueled APU turbine wheel of the Space Shuttle Orbiter's Main Engines has indicated the efficacy of systematic probabilistic risk assessment in flight certification and safety resolution. Nevertheless, real crack-initiation and propagation problems do not lend themselves to purely analytical studies. The high-cycle fatigue problem is noted to generally be unsuited to probabilistic modeling, due to its extremely high degree of intrinsic scatter. In the case treated, the cracks appear to trend toward crack arrest in a low cycle fatigue mode, due to a detuning of the resonance model.

Probabilistic Sensitivity Analysis of Fretting Fatigue (Preprint)

DTIC Science & Technology

2009-04-01

AFRL-RX-WP-TP-2009-4091 PROBABILISTIC SENSITIVITY ANALYSIS OF FRETTING FATIGUE (Preprint) Patrick J. Golden, Harry R. Millwater , and...Sensitivity Analysis of Fretting Fatigue Patrick J. Golden * Air Force Research Laboratory, Wright-Patterson AFB, OH 45433 Harry R. Millwater † and

Probabilistic simulation of stress concentration in composite laminates

NASA Technical Reports Server (NTRS)

Chamis, C. C.; Murthy, P. L. N.; Liaw, L.

1993-01-01

A computational methodology is described to probabilistically simulate the stress concentration factors in composite laminates. This new approach consists of coupling probabilistic composite mechanics with probabilistic finite element structural analysis. The probabilistic composite mechanics is used to probabilistically describe all the uncertainties inherent in composite material properties while probabilistic finite element is used to probabilistically describe the uncertainties associated with methods to experimentally evaluate stress concentration factors such as loads, geometry, and supports. The effectiveness of the methodology is demonstrated by using it to simulate the stress concentration factors in composite laminates made from three different composite systems. Simulated results match experimental data for probability density and for cumulative distribution functions. The sensitivity factors indicate that the stress concentration factors are influenced by local stiffness variables, by load eccentricities and by initial stress fields.

Probabilistic load simulation: Code development status

NASA Astrophysics Data System (ADS)

Newell, J. F.; Ho, H.

1991-05-01

The objective of the Composite Load Spectra (CLS) project is to develop generic load models to simulate the composite load spectra that are included in space propulsion system components. The probabilistic loads thus generated are part of the probabilistic design analysis (PDA) of a space propulsion system that also includes probabilistic structural analyses, reliability, and risk evaluations. Probabilistic load simulation for space propulsion systems demands sophisticated probabilistic methodology and requires large amounts of load information and engineering data. The CLS approach is to implement a knowledge based system coupled with a probabilistic load simulation module. The knowledge base manages and furnishes load information and expertise and sets up the simulation runs. The load simulation module performs the numerical computation to generate the probabilistic loads with load information supplied from the CLS knowledge base.

Probabilistic boundary element method

NASA Technical Reports Server (NTRS)

Cruse, T. A.; Raveendra, S. T.

1989-01-01

The purpose of the Probabilistic Structural Analysis Method (PSAM) project is to develop structural analysis capabilities for the design analysis of advanced space propulsion system hardware. The boundary element method (BEM) is used as the basis of the Probabilistic Advanced Analysis Methods (PADAM) which is discussed. The probabilistic BEM code (PBEM) is used to obtain the structural response and sensitivity results to a set of random variables. As such, PBEM performs analogous to other structural analysis codes such as finite elements in the PSAM system. For linear problems, unlike the finite element method (FEM), the BEM governing equations are written at the boundary of the body only, thus, the method eliminates the need to model the volume of the body. However, for general body force problems, a direct condensation of the governing equations to the boundary of the body is not possible and therefore volume modeling is generally required.

Probabilistic fatigue methodology for six nines reliability

NASA Technical Reports Server (NTRS)

Everett, R. A., Jr.; Bartlett, F. D., Jr.; Elber, Wolf

1990-01-01

Fleet readiness and flight safety strongly depend on the degree of reliability that can be designed into rotorcraft flight critical components. The current U.S. Army fatigue life specification for new rotorcraft is the so-called six nines reliability, or a probability of failure of one in a million. The progress of a round robin which was established by the American Helicopter Society (AHS) Subcommittee for Fatigue and Damage Tolerance is reviewed to investigate reliability-based fatigue methodology. The participants in this cooperative effort are in the U.S. Army Aviation Systems Command (AVSCOM) and the rotorcraft industry. One phase of the joint activity examined fatigue reliability under uniquely defined conditions for which only one answer was correct. The other phases were set up to learn how the different industry methods in defining fatigue strength affected the mean fatigue life and reliability calculations. Hence, constant amplitude and spectrum fatigue test data were provided so that each participant could perform their standard fatigue life analysis. As a result of this round robin, the probabilistic logic which includes both fatigue strength and spectrum loading variability in developing a consistant reliability analysis was established. In this first study, the reliability analysis was limited to the linear cumulative damage approach. However, it is expected that superior fatigue life prediction methods will ultimately be developed through this open AHS forum. To that end, these preliminary results were useful in identifying some topics for additional study.

Advanced Reactor PSA Methodologies for System Reliability Analysis and Source Term Assessment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grabaskas, D.; Brunett, A.; Passerini, S.

Beginning in 2015, a project was initiated to update and modernize the probabilistic safety assessment (PSA) of the GE-Hitachi PRISM sodium fast reactor. This project is a collaboration between GE-Hitachi and Argonne National Laboratory (Argonne), and funded in part by the U.S. Department of Energy. Specifically, the role of Argonne is to assess the reliability of passive safety systems, complete a mechanistic source term calculation, and provide component reliability estimates. The assessment of passive system reliability focused on the performance of the Reactor Vessel Auxiliary Cooling System (RVACS) and the inherent reactivity feedback mechanisms of the metal fuel core. Themore » mechanistic source term assessment attempted to provide a sequence specific source term evaluation to quantify offsite consequences. Lastly, the reliability assessment focused on components specific to the sodium fast reactor, including electromagnetic pumps, intermediate heat exchangers, the steam generator, and sodium valves and piping.« less

Methodology for the Incorporation of Passive Component Aging Modeling into the RAVEN/ RELAP-7 Environment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mandelli, Diego; Rabiti, Cristian; Cogliati, Joshua

2014-11-01

Passive system, structure and components (SSCs) will degrade over their operation life and this degradation may cause to reduction in the safety margins of a nuclear power plant. In traditional probabilistic risk assessment (PRA) using the event-tree/fault-tree methodology, passive SSC failure rates are generally based on generic plant failure data and the true state of a specific plant is not reflected realistically. To address aging effects of passive SSCs in the traditional PRA methodology [1] does consider physics based models that account for the operating conditions in the plant, however, [1] does not include effects of surveillance/inspection. This paper representsmore » an overall methodology for the incorporation of aging modeling of passive components into the RAVEN/RELAP-7 environment which provides a framework for performing dynamic PRA. Dynamic PRA allows consideration of both epistemic and aleatory uncertainties (including those associated with maintenance activities) in a consistent phenomenological and probabilistic framework and is often needed when there is complex process/hardware/software/firmware/ human interaction [2]. Dynamic PRA has gained attention recently due to difficulties in the traditional PRA modeling of aging effects of passive components using physics based models and also in the modeling of digital instrumentation and control systems. RAVEN (Reactor Analysis and Virtual control Environment) [3] is a software package under development at the Idaho National Laboratory (INL) as an online control logic driver and post-processing tool. It is coupled to the plant transient code RELAP-7 (Reactor Excursion and Leak Analysis Program) also currently under development at INL [3], as well as RELAP 5 [4]. The overall methodology aims to: • Address multiple aging mechanisms involving large number of components in a computational feasible manner where sequencing of events is conditioned on the physical conditions predicted in a simulation environment such as RELAP-7. • Identify the risk-significant passive components, their failure modes and anticipated rates of degradation • Incorporate surveillance and maintenance activities and their effects into the plant state and into component aging progress. • Asses aging affects in a dynamic simulation environment 1. C. L. SMITH, V. N. SHAH, T. KAO, G. APOSTOLAKIS, “Incorporating Ageing Effects into Probabilistic Risk Assessment –A Feasibility Study Utilizing Reliability Physics Models,” NUREG/CR-5632, USNRC, (2001). 2. T. ALDEMIR, “A Survey of Dynamic Methodologies for Probabilistic Safety Assessment of Nuclear Power Plants, Annals of Nuclear Energy, 52, 113-124, (2013). 3. C. RABITI, A. ALFONSI, J. COGLIATI, D. MANDELLI and R. KINOSHITA “Reactor Analysis and Virtual Control Environment (RAVEN) FY12 Report,” INL/EXT-12-27351, (2012). 4. D. ANDERS et.al, "RELAP-7 Level 2 Milestone Report: Demonstration of a Steady State Single Phase PWR Simulation with RELAP-7," INL/EXT-12-25924, (2012).« less

Fuzzy-logic-based network for complex systems risk assessment: application to ship performance analysis.

PubMed

Abou, Seraphin C

2012-03-01

In this paper, a new interpretation of intuitionistic fuzzy sets in the advanced framework of the Dempster-Shafer theory of evidence is extended to monitor safety-critical systems' performance. Not only is the proposed approach more effective, but it also takes into account the fuzzy rules that deal with imperfect knowledge/information and, therefore, is different from the classical Takagi-Sugeno fuzzy system, which assumes that the rule (the knowledge) is perfect. We provide an analytical solution to the practical and important problem of the conceptual probabilistic approach for formal ship safety assessment using the fuzzy set theory that involves uncertainties associated with the reliability input data. Thus, the overall safety of the ship engine is investigated as an object of risk analysis using the fuzzy mapping structure, which considers uncertainty and partial truth in the input-output mapping. The proposed method integrates direct evidence of the frame of discernment and is demonstrated through references to examples where fuzzy set models are informative. These simple applications illustrate how to assess the conflict of sensor information fusion for a sufficient cooling power system of vessels under extreme operation conditions. It was found that propulsion engine safety systems are not only a function of many environmental and operation profiles but are also dynamic and complex. Copyright © 2011 Elsevier Ltd. All rights reserved.

Probabilistic vs linear blending approaches to shared control for wheelchair driving.

PubMed

Ezeh, Chinemelu; Trautman, Pete; Devigne, Louise; Bureau, Valentin; Babel, Marie; Carlson, Tom

2017-07-01

Some people with severe mobility impairments are unable to operate powered wheelchairs reliably and effectively, using commercially available interfaces. This has sparked a body of research into "smart wheelchairs", which assist users to drive safely and create opportunities for them to use alternative interfaces. Various "shared control" techniques have been proposed to provide an appropriate level of assistance that is satisfactory and acceptable to the user. Most shared control techniques employ a traditional strategy called linear blending (LB), where the user's commands and wheelchair's autonomous commands are combined in some proportion. In this paper, however, we implement a more generalised form of shared control called probabilistic shared control (PSC). This probabilistic formulation improves the accuracy of modelling the interaction between the user and the wheelchair by taking into account uncertainty in the interaction. In this paper, we demonstrate the practical success of PSC over LB in terms of safety, particularly for novice users.

75 FR 13 - Alternate Fracture Toughness Requirements for Protection Against Pressurized Thermal Shock Events

Federal Register 2010, 2011, 2012, 2013, 2014

2010-01-04

...The Nuclear Regulatory Commission (NRC) is amending its regulations to provide alternate fracture toughness requirements for protection against pressurized thermal shock (PTS) events for pressurized water reactor (PWR) pressure vessels. This final rule provides alternate PTS requirements based on updated analysis methods. This action is desirable because the existing requirements are based on unnecessarily conservative probabilistic fracture mechanics analyses. This action reduces regulatory burden for those PWR licensees who expect to exceed the existing requirements before the expiration of their licenses, while maintaining adequate safety, and may choose to comply with the final rule as an alternative to complying with the existing requirements.

Electromagnetic Compatibility (EMC) in Microelectronics.

DTIC Science & Technology

1983-02-01

Fault Tree Analysis", System Saftey Symposium, June 8-9, 1965, Seattle: The Boeing Company . 12. Fussell, J.B., "Fault Tree Analysis-Concepts and...procedure for assessing EMC in microelectronics and for applying DD, 1473 EOiTO OP I, NOV6 IS OESOL.ETE UNCLASSIFIED SECURITY CLASSIFICATION OF THIS...CRITERIA 2.1 Background 2 2.2 The Probabilistic Nature of EMC 2 2.3 The Probabilistic Approach 5 2.4 The Compatibility Factor 6 3 APPLYING PROBABILISTIC

NESSUS/EXPERT - An expert system for probabilistic structural analysis methods

NASA Technical Reports Server (NTRS)

Millwater, H.; Palmer, K.; Fink, P.

1988-01-01

An expert system (NESSUS/EXPERT) is presented which provides assistance in using probabilistic structural analysis methods. NESSUS/EXPERT is an interactive menu-driven expert system that provides information to assist in the use of the probabilistic finite element code NESSUS/FEM and the fast probability integrator. NESSUS/EXPERT was developed with a combination of FORTRAN and CLIPS, a C language expert system tool, to exploit the strengths of each language.

Probabilistic sizing of laminates with uncertainties

NASA Technical Reports Server (NTRS)

Shah, A. R.; Liaw, D. G.; Chamis, C. C.

1993-01-01

A reliability based design methodology for laminate sizing and configuration for a special case of composite structures is described. The methodology combines probabilistic composite mechanics with probabilistic structural analysis. The uncertainties of constituent materials (fiber and matrix) to predict macroscopic behavior are simulated using probabilistic theory. Uncertainties in the degradation of composite material properties are included in this design methodology. A multi-factor interaction equation is used to evaluate load and environment dependent degradation of the composite material properties at the micromechanics level. The methodology is integrated into a computer code IPACS (Integrated Probabilistic Assessment of Composite Structures). Versatility of this design approach is demonstrated by performing a multi-level probabilistic analysis to size the laminates for design structural reliability of random type structures. The results show that laminate configurations can be selected to improve the structural reliability from three failures in 1000, to no failures in one million. Results also show that the laminates with the highest reliability are the least sensitive to the loading conditions.

Distributed collaborative probabilistic design for turbine blade-tip radial running clearance using support vector machine of regression

NASA Astrophysics Data System (ADS)

Fei, Cheng-Wei; Bai, Guang-Chen

2014-12-01

To improve the computational precision and efficiency of probabilistic design for mechanical dynamic assembly like the blade-tip radial running clearance (BTRRC) of gas turbine, a distribution collaborative probabilistic design method-based support vector machine of regression (SR)(called as DCSRM) is proposed by integrating distribution collaborative response surface method and support vector machine regression model. The mathematical model of DCSRM is established and the probabilistic design idea of DCSRM is introduced. The dynamic assembly probabilistic design of aeroengine high-pressure turbine (HPT) BTRRC is accomplished to verify the proposed DCSRM. The analysis results reveal that the optimal static blade-tip clearance of HPT is gained for designing BTRRC, and improving the performance and reliability of aeroengine. The comparison of methods shows that the DCSRM has high computational accuracy and high computational efficiency in BTRRC probabilistic analysis. The present research offers an effective way for the reliability design of mechanical dynamic assembly and enriches mechanical reliability theory and method.

A Figure of Merit: Quantifying the Probability of a Nuclear Reactor Accident.

PubMed

Wellock, Thomas R

In recent decades, probabilistic risk assessment (PRA) has become an essential tool in risk analysis and management in many industries and government agencies. The origins of PRA date to the 1975 publication of the U.S. Nuclear Regulatory Commission's (NRC) Reactor Safety Study led by MIT professor Norman Rasmussen. The "Rasmussen Report" inspired considerable political and scholarly disputes over the motives behind it and the value of its methods and numerical estimates of risk. The Report's controversies have overshadowed the deeper technical origins of risk assessment. Nuclear experts had long sought to express risk in a "figure of merit" to verify the safety of weapons and, later, civilian reactors. By the 1970s, technical advances in PRA gave the methodology the potential to serve political ends, too. The Report, it was hoped, would prove nuclear power's safety to a growing chorus of critics. Subsequent attacks on the Report's methods and numerical estimates damaged the NRC's credibility. PRA's fortunes revived when the 1979 Three Mile Island accident demonstrated PRA's potential for improving the safety of nuclear power and other technical systems. Nevertheless, the Report's controversies endure in mistrust of PRA and its experts.

Quantifying Safety Margin Using the Risk-Informed Safety Margin Characterization (RISMC)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grabaskas, David; Bucknor, Matthew; Brunett, Acacia

2015-04-26

The Risk-Informed Safety Margin Characterization (RISMC), developed by Idaho National Laboratory as part of the Light-Water Reactor Sustainability Project, utilizes a probabilistic safety margin comparison between a load and capacity distribution, rather than a deterministic comparison between two values, as is usually done in best-estimate plus uncertainty analyses. The goal is to determine the failure probability, or in other words, the probability of the system load equaling or exceeding the system capacity. While this method has been used in pilot studies, there has been little work conducted investigating the statistical significance of the resulting failure probability. In particular, it ismore » difficult to determine how many simulations are necessary to properly characterize the failure probability. This work uses classical (frequentist) statistics and confidence intervals to examine the impact in statistical accuracy when the number of simulations is varied. Two methods are proposed to establish confidence intervals related to the failure probability established using a RISMC analysis. The confidence interval provides information about the statistical accuracy of the method utilized to explore the uncertainty space, and offers a quantitative method to gauge the increase in statistical accuracy due to performing additional simulations.« less

Response surface method in geotechnical/structural analysis, phase 1

NASA Astrophysics Data System (ADS)

Wong, F. S.

1981-02-01

In the response surface approach, an approximating function is fit to a long running computer code based on a limited number of code calculations. The approximating function, called the response surface, is then used to replace the code in subsequent repetitive computations required in a statistical analysis. The procedure of the response surface development and feasibility of the method are shown using a sample problem in slop stability which is based on data from centrifuge experiments of model soil slopes and involves five random soil parameters. It is shown that a response surface can be constructed based on as few as four code calculations and that the response surface is computationally extremely efficient compared to the code calculation. Potential applications of this research include probabilistic analysis of dynamic, complex, nonlinear soil/structure systems such as slope stability, liquefaction, and nuclear reactor safety.

Advancing Usability Evaluation through Human Reliability Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ronald L. Boring; David I. Gertman

2005-07-01

This paper introduces a novel augmentation to the current heuristic usability evaluation methodology. The SPAR-H human reliability analysis method was developed for categorizing human performance in nuclear power plants. Despite the specialized use of SPAR-H for safety critical scenarios, the method also holds promise for use in commercial off-the-shelf software usability evaluations. The SPAR-H method shares task analysis underpinnings with human-computer interaction, and it can be easily adapted to incorporate usability heuristics as performance shaping factors. By assigning probabilistic modifiers to heuristics, it is possible to arrive at the usability error probability (UEP). This UEP is not a literal probabilitymore » of error but nonetheless provides a quantitative basis to heuristic evaluation. When combined with a consequence matrix for usability errors, this method affords ready prioritization of usability issues.« less

Parallel computing for probabilistic fatigue analysis

NASA Technical Reports Server (NTRS)

Sues, Robert H.; Lua, Yuan J.; Smith, Mark D.

1993-01-01

This paper presents the results of Phase I research to investigate the most effective parallel processing software strategies and hardware configurations for probabilistic structural analysis. We investigate the efficiency of both shared and distributed-memory architectures via a probabilistic fatigue life analysis problem. We also present a parallel programming approach, the virtual shared-memory paradigm, that is applicable across both types of hardware. Using this approach, problems can be solved on a variety of parallel configurations, including networks of single or multiprocessor workstations. We conclude that it is possible to effectively parallelize probabilistic fatigue analysis codes; however, special strategies will be needed to achieve large-scale parallelism to keep large number of processors busy and to treat problems with the large memory requirements encountered in practice. We also conclude that distributed-memory architecture is preferable to shared-memory for achieving large scale parallelism; however, in the future, the currently emerging hybrid-memory architectures will likely be optimal.

Probabilistic Parameter Uncertainty Analysis of Single Input Single Output Control Systems

NASA Technical Reports Server (NTRS)

Smith, Brett A.; Kenny, Sean P.; Crespo, Luis G.

2005-01-01

The current standards for handling uncertainty in control systems use interval bounds for definition of the uncertain parameters. This approach gives no information about the likelihood of system performance, but simply gives the response bounds. When used in design, current methods of m-analysis and can lead to overly conservative controller design. With these methods, worst case conditions are weighted equally with the most likely conditions. This research explores a unique approach for probabilistic analysis of control systems. Current reliability methods are examined showing the strong areas of each in handling probability. A hybrid method is developed using these reliability tools for efficiently propagating probabilistic uncertainty through classical control analysis problems. The method developed is applied to classical response analysis as well as analysis methods that explore the effects of the uncertain parameters on stability and performance metrics. The benefits of using this hybrid approach for calculating the mean and variance of responses cumulative distribution functions are shown. Results of the probabilistic analysis of a missile pitch control system, and a non-collocated mass spring system, show the added information provided by this hybrid analysis.

Probabilistic structural analysis methods for space transportation propulsion systems

NASA Technical Reports Server (NTRS)

Chamis, C. C.; Moore, N.; Anis, C.; Newell, J.; Nagpal, V.; Singhal, S.

1991-01-01

Information on probabilistic structural analysis methods for space propulsion systems is given in viewgraph form. Information is given on deterministic certification methods, probability of failure, component response analysis, stress responses for 2nd stage turbine blades, Space Shuttle Main Engine (SSME) structural durability, and program plans. .

Probabilistic Prediction of Lifetimes of Ceramic Parts

NASA Technical Reports Server (NTRS)

Nemeth, Noel N.; Gyekenyesi, John P.; Jadaan, Osama M.; Palfi, Tamas; Powers, Lynn; Reh, Stefan; Baker, Eric H.

2006-01-01

ANSYS/CARES/PDS is a software system that combines the ANSYS Probabilistic Design System (PDS) software with a modified version of the Ceramics Analysis and Reliability Evaluation of Structures Life (CARES/Life) Version 6.0 software. [A prior version of CARES/Life was reported in Program for Evaluation of Reliability of Ceramic Parts (LEW-16018), NASA Tech Briefs, Vol. 20, No. 3 (March 1996), page 28.] CARES/Life models effects of stochastic strength, slow crack growth, and stress distribution on the overall reliability of a ceramic component. The essence of the enhancement in CARES/Life 6.0 is the capability to predict the probability of failure using results from transient finite-element analysis. ANSYS PDS models the effects of uncertainty in material properties, dimensions, and loading on the stress distribution and deformation. ANSYS/CARES/PDS accounts for the effects of probabilistic strength, probabilistic loads, probabilistic material properties, and probabilistic tolerances on the lifetime and reliability of the component. Even failure probability becomes a stochastic quantity that can be tracked as a response variable. ANSYS/CARES/PDS enables tracking of all stochastic quantities in the design space, thereby enabling more precise probabilistic prediction of lifetimes of ceramic components.

Safety Risk Knowledge Elicitation in Support of Aeronautical R and D Portfolio Management: A Case Study

NASA Technical Reports Server (NTRS)

Shih, Ann T.; Ancel, Ersin; Jones, Sharon Monica; Reveley, Mary S.; Luxhoj, James T.

2012-01-01

Aviation is a problem domain characterized by a high level of system complexity and uncertainty. Safety risk analysis in such a domain is especially challenging given the multitude of operations and diverse stakeholders. The Federal Aviation Administration (FAA) projects that by 2025 air traffic will increase by more than 50 percent with 1.1 billion passengers a year and more than 85,000 flights every 24 hours contributing to further delays and congestion in the sky (Circelli, 2011). This increased system complexity necessitates the application of structured safety risk analysis methods to understand and eliminate where possible, reduce, and/or mitigate risk factors. The use of expert judgments for probabilistic safety analysis in such a complex domain is necessary especially when evaluating the projected impact of future technologies, capabilities, and procedures for which current operational data may be scarce. Management of an R&D product portfolio in such a dynamic domain needs a systematic process to elicit these expert judgments, process modeling results, perform sensitivity analyses, and efficiently communicate the modeling results to decision makers. In this paper a case study focusing on the application of an R&D portfolio of aeronautical products intended to mitigate aircraft Loss of Control (LOC) accidents is presented. In particular, the knowledge elicitation process with three subject matter experts who contributed to the safety risk model is emphasized. The application and refinement of a verbal-numerical scale for conditional probability elicitation in a Bayesian Belief Network (BBN) is discussed. The preliminary findings from this initial step of a three-part elicitation are important to project management practitioners as they illustrate the vital contribution of systematic knowledge elicitation in complex domains.

RAVEN User Manual

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mandelli, Diego; Rabiti, Cristian; Cogliati, Joshua Joseph

2015-10-01

RAVEN is a generic software framework to perform parametric and probabilistic analysis based on the response of complex system codes. The initial development was aimed to provide dynamic risk analysis capabilities to the Thermo-Hydraulic code RELAP-7, currently under development at the Idaho National Laboratory (INL). Although the initial goal has been fully accomplished, RAVEN is now a multi-purpose probabilistic and uncertainty quantification platform, capable to agnostically communicate with any system code. This agnosticism includes providing Application Programming Interfaces (APIs). These APIs are used to allow RAVEN to interact with any code as long as all the parameters that need tomore » be perturbed are accessible by inputs files or via python interfaces. RAVEN is capable of investigating the system response, and investigating the input space using Monte Carlo, Grid, or Latin Hyper Cube sampling schemes, but its strength is focused toward system feature discovery, such as limit surfaces, separating regions of the input space leading to system failure, using dynamic supervised learning techniques. The development of RAVEN has started in 2012, when, within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the need to provide a modern risk evaluation framework became stronger. RAVEN principal assignment is to provide the necessary software and algorithms in order to employ the concept developed by the Risk Informed Safety Margin Characterization (RISMC) program. RISMC is one of the pathways defined within the Light Water Reactor Sustainability (LWRS) program. In the RISMC approach, the goal is not just the individuation of the frequency of an event potentially leading to a system failure, but the closeness (or not) to key safety-related events. Hence, the approach is interested in identifying and increasing the safety margins related to those events. A safety margin is a numerical value quantifying the probability that a safety metric (e.g. for an important process such as peak pressure in a pipe) is exceeded under certain conditions. The initial development of RAVEN has been focused on providing dynamic risk assessment capability to RELAP-7, currently under development at the INL and, likely, future replacement of the RELAP5-3D code. Most the capabilities that have been implemented having RELAP-7 as principal focus are easily deployable for other system codes. For this reason, several side activaties are currently ongoing for coupling RAVEN with software such as RELAP5-3D, etc. The aim of this document is the explanation of the input requirements, focalizing on the input structure.« less

RAVEN User Manual

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mandelli, Diego; Rabiti, Cristian; Cogliati, Joshua Joseph

2016-02-01

RAVEN is a generic software framework to perform parametric and probabilistic analysis based on the response of complex system codes. The initial development was aimed to provide dynamic risk analysis capabilities to the Thermo-Hydraulic code RELAP-7, currently under development at the Idaho National Laboratory (INL). Although the initial goal has been fully accomplished, RAVEN is now a multi-purpose probabilistic and uncertainty quantification platform, capable to agnostically communicate with any system code. This agnosticism includes providing Application Programming Interfaces (APIs). These APIs are used to allow RAVEN to interact with any code as long as all the parameters that need tomore » be perturbed are accessible by input files or via python interfaces. RAVEN is capable of investigating the system response, and investigating the input space using Monte Carlo, Grid, or Latin Hyper Cube sampling schemes, but its strength is focused toward system feature discovery, such as limit surfaces, separating regions of the input space leading to system failure, using dynamic supervised learning techniques. The development of RAVEN started in 2012, when, within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the need to provide a modern risk evaluation framework became stronger. RAVEN principal assignment is to provide the necessary software and algorithms in order to employ the concept developed by the Risk Informed Safety Margin Characterization (RISMC) program. RISMC is one of the pathways defined within the Light Water Reactor Sustainability (LWRS) program. In the RISMC approach, the goal is not just the individuation of the frequency of an event potentially leading to a system failure, but the closeness (or not) to key safety-related events. Hence, the approach is interested in identifying and increasing the safety margins related to those events. A safety margin is a numerical value quantifying the probability that a safety metric (e.g. for an important process such as peak pressure in a pipe) is exceeded under certain conditions. The initial development of RAVEN has been focused on providing dynamic risk assessment capability to RELAP-7, currently under development at the INL and, likely, future replacement of the RELAP5-3D code. Most the capabilities that have been implemented having RELAP-7 as principal focus are easily deployable for other system codes. For this reason, several side activates are currently ongoing for coupling RAVEN with software such as RELAP5-3D, etc. The aim of this document is the explanation of the input requirements, focusing on the input structure.« less

Probabilistic structural analysis methods for improving Space Shuttle engine reliability

NASA Technical Reports Server (NTRS)

Boyce, L.

1989-01-01

Probabilistic structural analysis methods are particularly useful in the design and analysis of critical structural components and systems that operate in very severe and uncertain environments. These methods have recently found application in space propulsion systems to improve the structural reliability of Space Shuttle Main Engine (SSME) components. A computer program, NESSUS, based on a deterministic finite-element program and a method of probabilistic analysis (fast probability integration) provides probabilistic structural analysis for selected SSME components. While computationally efficient, it considers both correlated and nonnormal random variables as well as an implicit functional relationship between independent and dependent variables. The program is used to determine the response of a nickel-based superalloy SSME turbopump blade. Results include blade tip displacement statistics due to the variability in blade thickness, modulus of elasticity, Poisson's ratio or density. Modulus of elasticity significantly contributed to blade tip variability while Poisson's ratio did not. Thus, a rational method for choosing parameters to be modeled as random is provided.

Probabilistic Surface Characterization for Safe Landing Hazard Detection and Avoidance (HDA)

NASA Technical Reports Server (NTRS)

Johnson, Andrew E. (Inventor); Ivanov, Tonislav I. (Inventor); Huertas, Andres (Inventor)

2015-01-01

Apparatuses, systems, computer programs and methods for performing hazard detection and avoidance for landing vehicles are provided. Hazard assessment takes into consideration the geometry of the lander. Safety probabilities are computed for a plurality of pixels in a digital elevation map. The safety probabilities are combined for pixels associated with one or more aim points and orientations. A worst case probability value is assigned to each of the one or more aim points and orientations.

Quasi-Static Probabilistic Structural Analyses Process and Criteria

NASA Technical Reports Server (NTRS)

Goldberg, B.; Verderaime, V.

1999-01-01

Current deterministic structural methods are easily applied to substructures and components, and analysts have built great design insights and confidence in them over the years. However, deterministic methods cannot support systems risk analyses, and it was recently reported that deterministic treatment of statistical data is inconsistent with error propagation laws that can result in unevenly conservative structural predictions. Assuming non-nal distributions and using statistical data formats throughout prevailing stress deterministic processes lead to a safety factor in statistical format, which integrated into the safety index, provides a safety factor and first order reliability relationship. The embedded safety factor in the safety index expression allows a historically based risk to be determined and verified over a variety of quasi-static metallic substructures consistent with the traditional safety factor methods and NASA Std. 5001 criteria.

Bayesian analysis of rare events

NASA Astrophysics Data System (ADS)

Straub, Daniel; Papaioannou, Iason; Betz, Wolfgang

2016-06-01

In many areas of engineering and science there is an interest in predicting the probability of rare events, in particular in applications related to safety and security. Increasingly, such predictions are made through computer models of physical systems in an uncertainty quantification framework. Additionally, with advances in IT, monitoring and sensor technology, an increasing amount of data on the performance of the systems is collected. This data can be used to reduce uncertainty, improve the probability estimates and consequently enhance the management of rare events and associated risks. Bayesian analysis is the ideal method to include the data into the probabilistic model. It ensures a consistent probabilistic treatment of uncertainty, which is central in the prediction of rare events, where extrapolation from the domain of observation is common. We present a framework for performing Bayesian updating of rare event probabilities, termed BUS. It is based on a reinterpretation of the classical rejection-sampling approach to Bayesian analysis, which enables the use of established methods for estimating probabilities of rare events. By drawing upon these methods, the framework makes use of their computational efficiency. These methods include the First-Order Reliability Method (FORM), tailored importance sampling (IS) methods and Subset Simulation (SuS). In this contribution, we briefly review these methods in the context of the BUS framework and investigate their applicability to Bayesian analysis of rare events in different settings. We find that, for some applications, FORM can be highly efficient and is surprisingly accurate, enabling Bayesian analysis of rare events with just a few model evaluations. In a general setting, BUS implemented through IS and SuS is more robust and flexible.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, Curtis; Mandelli, Diego; Prescott, Steven

The existing fleet of nuclear power plants is in the process of extending its lifetime and increasing the power generated from these plants via power uprates. In order to evaluate the impact of these factors on the safety of the plant, the Risk Informed Safety Margin Characterization (RISMC) project aims to provide insight to decision makers through a series of simulations of the plant dynamics for different initial conditions (e.g., probabilistic analysis and uncertainty quantification). This report focuses, in particular, on the application of a RISMC detailed demonstration case study for an emergent issue using the RAVEN and RELAP-7 tools.more » This case study looks at the impact of a couple of challenges to a hypothetical pressurized water reactor, including: (1) a power uprate, (2) a potential loss of off-site power followed by the possible loss of all diesel generators (i.e., a station black-out event), (3) and earthquake induces station-blackout, and (4) a potential earthquake induced tsunami flood. The analysis is performed by using a set of codes: a thermal-hydraulic code (RELAP-7), a flooding simulation tool (NEUTRINO) and a stochastic analysis tool (RAVEN) – these are currently under development at the Idaho National Laboratory.« less

Probabilistic Structural Analysis Methods for select space propulsion system components (PSAM). Volume 2: Literature surveys of critical Space Shuttle main engine components

NASA Technical Reports Server (NTRS)

Rajagopal, K. R.

1992-01-01

The technical effort and computer code development is summarized. Several formulations for Probabilistic Finite Element Analysis (PFEA) are described with emphasis on the selected formulation. The strategies being implemented in the first-version computer code to perform linear, elastic PFEA is described. The results of a series of select Space Shuttle Main Engine (SSME) component surveys are presented. These results identify the critical components and provide the information necessary for probabilistic structural analysis. Volume 2 is a summary of critical SSME components.

An approximate methods approach to probabilistic structural analysis

NASA Technical Reports Server (NTRS)

Mcclung, R. C.; Millwater, H. R.; Wu, Y.-T.; Thacker, B. H.; Burnside, O. H.

1989-01-01

A probabilistic structural analysis method (PSAM) is described which makes an approximate calculation of the structural response of a system, including the associated probabilistic distributions, with minimal computation time and cost, based on a simplified representation of the geometry, loads, and material. The method employs the fast probability integration (FPI) algorithm of Wu and Wirsching. Typical solution strategies are illustrated by formulations for a representative critical component chosen from the Space Shuttle Main Engine (SSME) as part of a major NASA-sponsored program on PSAM. Typical results are presented to demonstrate the role of the methodology in engineering design and analysis.

Safety analysis, risk assessment, and risk acceptance criteria

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jamali, K.; Stack, D.W.; Sullivan, L.H.

1997-08-01

This paper discusses a number of topics that relate safety analysis as documented in the Department of Energy (DOE) safety analysis reports (SARs), probabilistic risk assessments (PRA) as characterized primarily in the context of the techniques that have assumed some level of formality in commercial nuclear power plant applications, and risk acceptance criteria as an outgrowth of PRA applications. DOE SARs of interest are those that are prepared for DOE facilities under DOE Order 5480.23 and the implementing guidance in DOE STD-3009-94. It must be noted that the primary area of application for DOE STD-3009 is existing DOE facilities andmore » that certain modifications of the STD-3009 approach are necessary in SARs for new facilities. Moreover, it is the hazard analysis (HA) and accident analysis (AA) portions of these SARs that are relevant to the present discussions. Although PRAs can be qualitative in nature, PRA as used in this paper refers more generally to all quantitative risk assessments and their underlying methods. HA as used in this paper refers more generally to all qualitative risk assessments and their underlying methods that have been in use in hazardous facilities other than nuclear power plants. This discussion includes both quantitative and qualitative risk assessment methods. PRA has been used, improved, developed, and refined since the Reactor Safety Study (WASH-1400) was published in 1975 by the Nuclear Regulatory Commission (NRC). Much debate has ensued since WASH-1400 on exactly what the role of PRA should be in plant design, reactor licensing, `ensuring` plant and process safety, and a large number of other decisions that must be made for potentially hazardous activities. Of particular interest in this area is whether the risks quantified using PRA should be compared with numerical risk acceptance criteria (RACs) to determine whether a facility is `safe.` Use of RACs requires quantitative estimates of consequence frequency and magnitude.« less

Probabilistic reasoning in data analysis.

PubMed

Sirovich, Lawrence

2011-09-20

This Teaching Resource provides lecture notes, slides, and a student assignment for a lecture on probabilistic reasoning in the analysis of biological data. General probabilistic frameworks are introduced, and a number of standard probability distributions are described using simple intuitive ideas. Particular attention is focused on random arrivals that are independent of prior history (Markovian events), with an emphasis on waiting times, Poisson processes, and Poisson probability distributions. The use of these various probability distributions is applied to biomedical problems, including several classic experimental studies.

77 FR 21595 - Applications and Amendments to Facility Operating Licenses and Combined Licenses Involving...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-04-10

... must be one which, if proven, would entitle the requestor/petitioner to relief. A requestor/ petitioner..., and fire modeling calculations, have been performed to demonstrate that the performance-based... may include engineering evaluations, probabilistic safety assessments, and fire modeling calculations...

System Maturity Indices for Decision Support in the Defense Acquisition Process

DTIC Science & Technology

2008-04-23

technologies, but was to be used as ontology for contracting support (Sadin, Povinelli , & Rosen, 1989), thus TRL does not address: A complete...via probabilistic solution discovery. Reliability Engineering & System Safety. In press. Sadin, S.R., Povinelli , F.P., & Rosen, R. (1989). The NASA

Fragility Analysis of Concrete Gravity Dams

NASA Astrophysics Data System (ADS)

Tekie, Paulos B.; Ellingwood, Bruce R.

2002-09-01

Concrete gravity dams are an important part ofthe nation's infrastructure. Many dams have been in service for over 50 years, during which time important advances in the methodologies for evaluation of natural phenomena hazards have caused the design-basis events to be revised upwards, in some cases significantly. Many existing dams fail to meet these revised safety criteria and structural rehabilitation to meet newly revised criteria may be costly and difficult. A probabilistic safety analysis (PSA) provides a rational safety assessment and decision-making tool managing the various sources of uncertainty that may impact dam performance. Fragility analysis, which depicts fl%e uncertainty in the safety margin above specified hazard levels, is a fundamental tool in a PSA. This study presents a methodology for developing fragilities of concrete gravity dams to assess their performance against hydrologic and seismic hazards. Models of varying degree of complexity and sophistication were considered and compared. The methodology is illustrated using the Bluestone Dam on the New River in West Virginia, which was designed in the late 1930's. The hydrologic fragilities showed that the Eluestone Dam is unlikely to become unstable at the revised probable maximum flood (PMF), but it is likely that there will be significant cracking at the heel ofthe dam. On the other hand, the seismic fragility analysis indicated that sliding is likely, if the dam were to be subjected to a maximum credible earthquake (MCE). Moreover, there will likely be tensile cracking at the neck of the dam at this level of seismic excitation. Probabilities of relatively severe limit states appear to be only marginally affected by extremely rare events (e.g. the PMF and MCE). Moreover, the risks posed by the extreme floods and earthquakes were not balanced for the Bluestone Dam, with seismic hazard posing a relatively higher risk.

Probabilistic Simulation of Stress Concentration in Composite Laminates

NASA Technical Reports Server (NTRS)

Chamis, C. C.; Murthy, P. L. N.; Liaw, D. G.

1994-01-01

A computational methodology is described to probabilistically simulate the stress concentration factors (SCF's) in composite laminates. This new approach consists of coupling probabilistic composite mechanics with probabilistic finite element structural analysis. The composite mechanics is used to probabilistically describe all the uncertainties inherent in composite material properties, whereas the finite element is used to probabilistically describe the uncertainties associated with methods to experimentally evaluate SCF's, such as loads, geometry, and supports. The effectiveness of the methodology is demonstrated by using is to simulate the SCF's in three different composite laminates. Simulated results match experimental data for probability density and for cumulative distribution functions. The sensitivity factors indicate that the SCF's are influenced by local stiffness variables, by load eccentricities, and by initial stress fields.

Methodology for safety optimization of highway cross-sections for horizontal curves with restricted sight distance.

PubMed

Ibrahim, Shewkar E; Sayed, Tarek; Ismail, Karim

2012-11-01

Several earlier studies have noted the shortcomings with existing geometric design guides which provide deterministic standards. In these standards the safety margin of the design output is generally unknown and there is little knowledge of the safety implications of deviating from the standards. To mitigate these shortcomings, probabilistic geometric design has been advocated where reliability analysis can be used to account for the uncertainty in the design parameters and to provide a mechanism for risk measurement to evaluate the safety impact of deviations from design standards. This paper applies reliability analysis for optimizing the safety of highway cross-sections. The paper presents an original methodology to select a suitable combination of cross-section elements with restricted sight distance to result in reduced collisions and consistent risk levels. The purpose of this optimization method is to provide designers with a proactive approach to the design of cross-section elements in order to (i) minimize the risk associated with restricted sight distance, (ii) balance the risk across the two carriageways of the highway, and (iii) reduce the expected collision frequency. A case study involving nine cross-sections that are parts of two major highway developments in British Columbia, Canada, was presented. The results showed that an additional reduction in collisions can be realized by incorporating the reliability component, P(nc) (denoting the probability of non-compliance), in the optimization process. The proposed approach results in reduced and consistent risk levels for both travel directions in addition to further collision reductions. Copyright © 2012 Elsevier Ltd. All rights reserved.

The application of probabilistic fracture analysis to residual life evaluation of embrittled reactor vessels

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dickson, T.L.; Simonen, F.A.

1992-05-01

Probabilistic fracture mechanics analysis is a major element of comprehensive probabilistic methodology on which current NRC regulatory requirements for pressurized water reactor vessel integrity evaluation are based. Computer codes such as OCA-P and VISA-II perform probabilistic fracture analyses to estimate the increase in vessel failure probability that occurs as the vessel material accumulates radiation damage over the operating life of the vessel. The results of such analyses, when compared with limits of acceptable failure probabilities, provide an estimation of the residual life of a vessel. Such codes can be applied to evaluate the potential benefits of plant-specific mitigating actions designedmore » to reduce the probability of failure of a reactor vessel. 10 refs.« less

The application of probabilistic fracture analysis to residual life evaluation of embrittled reactor vessels

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dickson, T.L.; Simonen, F.A.

1992-01-01

Probabilistic fracture mechanics analysis is a major element of comprehensive probabilistic methodology on which current NRC regulatory requirements for pressurized water reactor vessel integrity evaluation are based. Computer codes such as OCA-P and VISA-II perform probabilistic fracture analyses to estimate the increase in vessel failure probability that occurs as the vessel material accumulates radiation damage over the operating life of the vessel. The results of such analyses, when compared with limits of acceptable failure probabilities, provide an estimation of the residual life of a vessel. Such codes can be applied to evaluate the potential benefits of plant-specific mitigating actions designedmore » to reduce the probability of failure of a reactor vessel. 10 refs.« less

Commercialization of NESSUS: Status

NASA Technical Reports Server (NTRS)

Thacker, Ben H.; Millwater, Harry R.

1991-01-01

A plan was initiated in 1988 to commercialize the Numerical Evaluation of Stochastic Structures Under Stress (NESSUS) probabilistic structural analysis software. The goal of the on-going commercialization effort is to begin the transfer of Probabilistic Structural Analysis Method (PSAM) developed technology into industry and to develop additional funding resources in the general area of structural reliability. The commercialization effort is summarized. The SwRI NESSUS Software System is a general purpose probabilistic finite element computer program using state of the art methods for predicting stochastic structural response due to random loads, material properties, part geometry, and boundary conditions. NESSUS can be used to assess structural reliability, to compute probability of failure, to rank the input random variables by importance, and to provide a more cost effective design than traditional methods. The goal is to develop a general probabilistic structural analysis methodology to assist in the certification of critical components in the next generation Space Shuttle Main Engine.

Rocket engine system reliability analyses using probabilistic and fuzzy logic techniques

NASA Technical Reports Server (NTRS)

Hardy, Terry L.; Rapp, Douglas C.

1994-01-01

The reliability of rocket engine systems was analyzed by using probabilistic and fuzzy logic techniques. Fault trees were developed for integrated modular engine (IME) and discrete engine systems, and then were used with the two techniques to quantify reliability. The IRRAS (Integrated Reliability and Risk Analysis System) computer code, developed for the U.S. Nuclear Regulatory Commission, was used for the probabilistic analyses, and FUZZYFTA (Fuzzy Fault Tree Analysis), a code developed at NASA Lewis Research Center, was used for the fuzzy logic analyses. Although both techniques provided estimates of the reliability of the IME and discrete systems, probabilistic techniques emphasized uncertainty resulting from randomness in the system whereas fuzzy logic techniques emphasized uncertainty resulting from vagueness in the system. Because uncertainty can have both random and vague components, both techniques were found to be useful tools in the analysis of rocket engine system reliability.

The analysis of the possibility of using 10-minute rainfall series to determine the maximum rainfall amount with 5 minutes duration

NASA Astrophysics Data System (ADS)

Kaźmierczak, Bartosz; Wartalska, Katarzyna; Wdowikowski, Marcin; Kotowski, Andrzej

2017-11-01

Modern scientific research in the area of heavy rainfall analysis regarding to the sewerage design indicates the need to develop and use probabilistic rain models. One of the issues that remains to be resolved is the length of the shortest amount of rain to be analyzed. It is commonly believed that the best time is 5 minutes, while the least rain duration measured by the national services is often 10 or even 15 minutes. Main aim of this paper is to present the difference between probabilistic rainfall models results given from rainfall time series including and excluding 5 minutes rainfall duration. Analysis were made for long-time period from 1961-2010 on polish meteorological station Legnica. To develop best fitted to measurement rainfall data probabilistic model 4 probabilistic distributions were used. Results clearly indicates that models including 5 minutes rainfall duration remains more appropriate to use.

Time Alignment as a Necessary Step in the Analysis of Sleep Probabilistic Curves

NASA Astrophysics Data System (ADS)

Rošt'áková, Zuzana; Rosipal, Roman

2018-02-01

Sleep can be characterised as a dynamic process that has a finite set of sleep stages during the night. The standard Rechtschaffen and Kales sleep model produces discrete representation of sleep and does not take into account its dynamic structure. In contrast, the continuous sleep representation provided by the probabilistic sleep model accounts for the dynamics of the sleep process. However, analysis of the sleep probabilistic curves is problematic when time misalignment is present. In this study, we highlight the necessity of curve synchronisation before further analysis. Original and in time aligned sleep probabilistic curves were transformed into a finite dimensional vector space, and their ability to predict subjects' age or daily measures is evaluated. We conclude that curve alignment significantly improves the prediction of the daily measures, especially in the case of the S2-related sleep states or slow wave sleep.

Probabilistic classifiers with high-dimensional data

PubMed Central

Kim, Kyung In; Simon, Richard

2011-01-01

For medical classification problems, it is often desirable to have a probability associated with each class. Probabilistic classifiers have received relatively little attention for small n large p classification problems despite of their importance in medical decision making. In this paper, we introduce 2 criteria for assessment of probabilistic classifiers: well-calibratedness and refinement and develop corresponding evaluation measures. We evaluated several published high-dimensional probabilistic classifiers and developed 2 extensions of the Bayesian compound covariate classifier. Based on simulation studies and analysis of gene expression microarray data, we found that proper probabilistic classification is more difficult than deterministic classification. It is important to ensure that a probabilistic classifier is well calibrated or at least not “anticonservative” using the methods developed here. We provide this evaluation for several probabilistic classifiers and also evaluate their refinement as a function of sample size under weak and strong signal conditions. We also present a cross-validation method for evaluating the calibration and refinement of any probabilistic classifier on any data set. PMID:21087946

Probabilistic Design Methodology and its Application to the Design of an Umbilical Retract Mechanism

NASA Technical Reports Server (NTRS)

Onyebueke, Landon; Ameye, Olusesan

2002-01-01

A lot has been learned from past experience with structural and machine element failures. The understanding of failure modes and the application of an appropriate design analysis method can lead to improved structural and machine element safety as well as serviceability. To apply Probabilistic Design Methodology (PDM), all uncertainties are modeled as random variables with selected distribution types, means, and standard deviations. It is quite difficult to achieve a robust design without considering the randomness of the design parameters which is the case in the use of the Deterministic Design Approach. The US Navy has a fleet of submarine-launched ballistic missiles. An umbilical plug joins the missile to the submarine in order to provide electrical and cooling water connections. As the missile leaves the submarine, an umbilical retract mechanism retracts the umbilical plug clear of the advancing missile after disengagement during launch and retrains the plug in the retracted position. The design of the current retract mechanism in use was based on the deterministic approach which puts emphasis on factor of safety. A new umbilical retract mechanism that is simpler in design, lighter in weight, more reliable, easier to adjust, and more cost effective has become desirable since this will increase the performance and efficiency of the system. This paper reports on a recent project performed at Tennessee State University for the US Navy that involved the application of PDM to the design of an umbilical retract mechanism. This paper demonstrates how the use of PDM lead to the minimization of weight and cost, and the maximization of reliability and performance.

A Methodology for the Integration of a Mechanistic Source Term Analysis in a Probabilistic Framework for Advanced Reactors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grabaskas, Dave; Brunett, Acacia J.; Bucknor, Matthew

GE Hitachi Nuclear Energy (GEH) and Argonne National Laboratory are currently engaged in a joint effort to modernize and develop probabilistic risk assessment (PRA) techniques for advanced non-light water reactors. At a high level, the primary outcome of this project will be the development of next-generation PRA methodologies that will enable risk-informed prioritization of safety- and reliability-focused research and development, while also identifying gaps that may be resolved through additional research. A subset of this effort is the development of PRA methodologies to conduct a mechanistic source term (MST) analysis for event sequences that could result in the release ofmore » radionuclides. The MST analysis seeks to realistically model and assess the transport, retention, and release of radionuclides from the reactor to the environment. The MST methods developed during this project seek to satisfy the requirements of the Mechanistic Source Term element of the ASME/ANS Non-LWR PRA standard. The MST methodology consists of separate analysis approaches for risk-significant and non-risk significant event sequences that may result in the release of radionuclides from the reactor. For risk-significant event sequences, the methodology focuses on a detailed assessment, using mechanistic models, of radionuclide release from the fuel, transport through and release from the primary system, transport in the containment, and finally release to the environment. The analysis approach for non-risk significant event sequences examines the possibility of large radionuclide releases due to events such as re-criticality or the complete loss of radionuclide barriers. This paper provides details on the MST methodology, including the interface between the MST analysis and other elements of the PRA, and provides a simplified example MST calculation for a sodium fast reactor.« less

Probabilistic Structural Analysis of SSME Turbopump Blades: Probabilistic Geometry Effects

NASA Technical Reports Server (NTRS)

Nagpal, V. K.

1985-01-01

A probabilistic study was initiated to evaluate the precisions of the geometric and material properties tolerances on the structural response of turbopump blades. To complete this study, a number of important probabilistic variables were identified which are conceived to affect the structural response of the blade. In addition, a methodology was developed to statistically quantify the influence of these probabilistic variables in an optimized way. The identified variables include random geometric and material properties perturbations, different loadings and a probabilistic combination of these loadings. Influences of these probabilistic variables are planned to be quantified by evaluating the blade structural response. Studies of the geometric perturbations were conducted for a flat plate geometry as well as for a space shuttle main engine blade geometry using a special purpose code which uses the finite element approach. Analyses indicate that the variances of the perturbations about given mean values have significant influence on the response.

77 FR 58420 - Advisory Committee On Reactor Safeguards; Notice of Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2012-09-20

... Pike, Rockville, Maryland. Thursday, October 4, 2012, Conference Room T2-B1, 11545 Rockville Pike....: Safety Evaluation Report (SER) Associated with WCAP-16793-NP, Revision 2, ``Evaluation of Long-Term..., ``Evaluation of JNES Equipment Fragility Tests for Use in Seismic Probabilistic Risk Assessments for U.S...

Development of a Probabilistic Dynamic Synthesis Method for the Analysis of Nondeterministic Structures

NASA Technical Reports Server (NTRS)

Brown, A. M.

1998-01-01

Accounting for the statistical geometric and material variability of structures in analysis has been a topic of considerable research for the last 30 years. The determination of quantifiable measures of statistical probability of a desired response variable, such as natural frequency, maximum displacement, or stress, to replace experience-based "safety factors" has been a primary goal of these studies. There are, however, several problems associated with their satisfactory application to realistic structures, such as bladed disks in turbomachinery. These include the accurate definition of the input random variables (rv's), the large size of the finite element models frequently used to simulate these structures, which makes even a single deterministic analysis expensive, and accurate generation of the cumulative distribution function (CDF) necessary to obtain the probability of the desired response variables. The research presented here applies a methodology called probabilistic dynamic synthesis (PDS) to solve these problems. The PDS method uses dynamic characteristics of substructures measured from modal test as the input rv's, rather than "primitive" rv's such as material or geometric uncertainties. These dynamic characteristics, which are the free-free eigenvalues, eigenvectors, and residual flexibility (RF), are readily measured and for many substructures, a reasonable sample set of these measurements can be obtained. The statistics for these rv's accurately account for the entire random character of the substructure. Using the RF method of component mode synthesis, these dynamic characteristics are used to generate reduced-size sample models of the substructures, which are then coupled to form system models. These sample models are used to obtain the CDF of the response variable by either applying Monte Carlo simulation or by generating data points for use in the response surface reliability method, which can perform the probabilistic analysis with an order of magnitude less computational effort. Both free- and forced-response analyses have been performed, and the results indicate that, while there is considerable room for improvement, the method produces usable and more representative solutions for the design of realistic structures with a substantial savings in computer time.

75 FR 18205 - Notice of Peer Review Meeting for the External Peer Review Drafts of Two Documents on Using...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-09

... Role of Risk Analysis in Decision-Making AGENCY: Environmental Protection Agency (EPA). ACTION: Notice... documents entitled, ``Using Probabilistic Methods to Enhance the Role of Risk Analysis in Decision- Making... Probabilistic Methods to Enhance the Role of Risk Analysis in Decision-Making, with Case Study Examples'' and...

Health economics and outcomes methods in risk-based decision-making for blood safety.

PubMed

Custer, Brian; Janssen, Mart P

2015-08-01

Analytical methods appropriate for health economic assessments of transfusion safety interventions have not previously been described in ways that facilitate their use. Within the context of risk-based decision-making (RBDM), health economics can be important for optimizing decisions among competing interventions. The objective of this review is to address key considerations and limitations of current methods as they apply to blood safety. Because a voluntary blood supply is an example of a public good, analyses should be conducted from the societal perspective when possible. Two primary study designs are recommended for most blood safety intervention assessments: budget impact analysis (BIA), which measures the cost to implement an intervention both to the blood operator but also in a broader context, and cost-utility analysis (CUA), which measures the ratio between costs and health gain achieved, in terms of reduced morbidity and mortality, by use of an intervention. These analyses often have important limitations because data that reflect specific aspects, for example, blood recipient population characteristics or complication rates, are not available. Sensitivity analyses play an important role. The impact of various uncertain factors can be studied conjointly in probabilistic sensitivity analyses. The use of BIA and CUA together provides a comprehensive assessment of the costs and benefits from implementing (or not) specific interventions. RBDM is multifaceted and impacts a broad spectrum of stakeholders. Gathering and analyzing health economic evidence as part of the RBDM process enhances the quality, completeness, and transparency of decision-making. © 2015 AABB.

ProbCD: enrichment analysis accounting for categorization uncertainty.

PubMed

Vêncio, Ricardo Z N; Shmulevich, Ilya

2007-10-12

As in many other areas of science, systems biology makes extensive use of statistical association and significance estimates in contingency tables, a type of categorical data analysis known in this field as enrichment (also over-representation or enhancement) analysis. In spite of efforts to create probabilistic annotations, especially in the Gene Ontology context, or to deal with uncertainty in high throughput-based datasets, current enrichment methods largely ignore this probabilistic information since they are mainly based on variants of the Fisher Exact Test. We developed an open-source R-based software to deal with probabilistic categorical data analysis, ProbCD, that does not require a static contingency table. The contingency table for the enrichment problem is built using the expectation of a Bernoulli Scheme stochastic process given the categorization probabilities. An on-line interface was created to allow usage by non-programmers and is available at: http://xerad.systemsbiology.net/ProbCD/. We present an analysis framework and software tools to address the issue of uncertainty in categorical data analysis. In particular, concerning the enrichment analysis, ProbCD can accommodate: (i) the stochastic nature of the high-throughput experimental techniques and (ii) probabilistic gene annotation.

The cost-effectiveness of nonoperative management versus laparoscopic appendectomy for the treatment of acute, uncomplicated appendicitis in children.

PubMed

Wu, James X; Sacks, Greg D; Dawes, Aaron J; DeUgarte, Daniel; Lee, Steven L

2017-07-01

Several studies have demonstrated the safety and short-term success of nonoperative management in children with acute, uncomplicated appendicitis. Nonoperative management spares the patients and their family the upfront cost and discomfort of surgery, but also risks recurrent appendicitis. Using decision-tree software, we evaluated the cost-effectiveness of nonoperative management versus routine laparoscopic appendectomy. Model variables were abstracted from a review of the literature, Healthcare Cost and Utilization Project, and Medicare Physician Fee schedule. Model uncertainty was assessed using both one-way and probabilistic sensitivity analyses. We used a $100,000 per quality adjusted life year (QALY) threshold for cost-effectiveness. Operative management cost $11,119 and yielded 23.56 quality-adjusted life months (QALMs). Nonoperative management cost $2277 less than operative management, but yielded 0.03 fewer QALMs. The incremental cost-to-effectiveness ratio of routine laparoscopic appendectomy was $910,800 per QALY gained. This greatly exceeds the $100,000/QALY threshold and was not cost-effective. One-way sensitivity analysis found that operative management would become cost-effective if the 1-year recurrence rate of acute appendicitis exceeded 39.8%. Probabilistic sensitivity analysis indicated that nonoperative management was cost-effective in 92% of simulations. Based on our model, nonoperative management is more cost-effective than routine laparoscopic appendectomy for children with acute, uncomplicated appendicitis. Cost-Effectiveness Study: Level II. Published by Elsevier Inc.

The Probability Heuristics Model of Syllogistic Reasoning.

ERIC Educational Resources Information Center

Chater, Nick; Oaksford, Mike

1999-01-01

Proposes a probability heuristic model for syllogistic reasoning and confirms the rationality of this heuristic by an analysis of the probabilistic validity of syllogistic reasoning that treats logical inference as a limiting case of probabilistic inference. Meta-analysis and two experiments involving 40 adult participants and using generalized…

An Instructional Module on Mokken Scale Analysis

ERIC Educational Resources Information Center

Wind, Stefanie A.

2017-01-01

Mokken scale analysis (MSA) is a probabilistic-nonparametric approach to item response theory (IRT) that can be used to evaluate fundamental measurement properties with less strict assumptions than parametric IRT models. This instructional module provides an introduction to MSA as a probabilistic-nonparametric framework in which to explore…

Probabilistic Analysis Techniques Applied to Complex Spacecraft Power System Modeling

NASA Technical Reports Server (NTRS)

Hojnicki, Jeffrey S.; Rusick, Jeffrey J.

2005-01-01

Electric power system performance predictions are critical to spacecraft, such as the International Space Station (ISS), to ensure that sufficient power is available to support all the spacecraft s power needs. In the case of the ISS power system, analyses to date have been deterministic, meaning that each analysis produces a single-valued result for power capability because of the complexity and large size of the model. As a result, the deterministic ISS analyses did not account for the sensitivity of the power capability to uncertainties in model input variables. Over the last 10 years, the NASA Glenn Research Center has developed advanced, computationally fast, probabilistic analysis techniques and successfully applied them to large (thousands of nodes) complex structural analysis models. These same techniques were recently applied to large, complex ISS power system models. This new application enables probabilistic power analyses that account for input uncertainties and produce results that include variations caused by these uncertainties. Specifically, N&R Engineering, under contract to NASA, integrated these advanced probabilistic techniques with Glenn s internationally recognized ISS power system model, System Power Analysis for Capability Evaluation (SPACE).

Probabilistic stability analysis: the way forward for stability analysis of sustainable power systems.

PubMed

Milanović, Jovica V

2017-08-13

Future power systems will be significantly different compared with their present states. They will be characterized by an unprecedented mix of a wide range of electricity generation and transmission technologies, as well as responsive and highly flexible demand and storage devices with significant temporal and spatial uncertainty. The importance of probabilistic approaches towards power system stability analysis, as a subsection of power system studies routinely carried out by power system operators, has been highlighted in previous research. However, it may not be feasible (or even possible) to accurately model all of the uncertainties that exist within a power system. This paper describes for the first time an integral approach to probabilistic stability analysis of power systems, including small and large angular stability and frequency stability. It provides guidance for handling uncertainties in power system stability studies and some illustrative examples of the most recent results of probabilistic stability analysis of uncertain power systems.This article is part of the themed issue 'Energy management: flexibility, risk and optimization'. © 2017 The Author(s).

Application of probabilistic analysis/design methods in space programs - The approaches, the status, and the needs

NASA Technical Reports Server (NTRS)

Ryan, Robert S.; Townsend, John S.

1993-01-01

The prospective improvement of probabilistic methods for space program analysis/design entails the further development of theories, codes, and tools which match specific areas of application, the drawing of lessons from previous uses of probability and statistics data bases, the enlargement of data bases (especially in the field of structural failures), and the education of engineers and managers on the advantages of these methods. An evaluation is presently made of the current limitations of probabilistic engineering methods. Recommendations are made for specific applications.

Evaluation of safety of hypobaric decompressions and EVA from positions of probabilistic theory

NASA Astrophysics Data System (ADS)

Nikolaev, V. P.

Formation and subsequent evolution of gas bubbles in blood and tissues of subjects exposed to decompression are casual processes in their nature. Such character of bubbling processes in a body predetermines probabilistic character of decompression sickness (DCS) incidence in divers, aviators and astronauts. Our original probabilistic theory of decompression safety is based on stochastic models of these processes and on the concept of critical volume of a free gas phase in body tissues. From positions of this theory, the probability of DCS incidence during single-stage decompressions and during hypobaric decompressions under EVA in particular, is defined by the distribution of possible values of nucleation efficiency in "pain" tissues and by its critical significance depended on the parameters of a concrete decompression. In the present study the following is shown: 1) the dimensionless index of critical nucleation efficiency for "pain" body tissues is a more adequate index of decompression stress in comparison with Tissue Ratio, TR; 2) a priory the decompression under EVA performed according to the Russian protocol is more safe than decompression under EVA performed in accordance with the U.S. protocol; 3) the Russian space suit operated at a higher pressure and having a higher "rigidity" induces a stronger inhibition of mechanisms of cavitation and gas bubbles formation in tissues of a subject located in it, and by that provides a more considerable reduction of the DCS risk during real EVA performance.

EXPERIENCES WITH USING PROBABILISTIC EXPOSURE ANALYSIS METHODS IN THE U.S. EPA

EPA Science Inventory

Over the past decade various Offices and Programs within the U.S. EPA have either initiated or increased the development and application of probabilistic exposure analysis models. These models have been applied to a broad range of research or regulatory problems in EPA, such as e...

Probabilistic analysis of a materially nonlinear structure

NASA Technical Reports Server (NTRS)

Millwater, H. R.; Wu, Y.-T.; Fossum, A. F.

1990-01-01

A probabilistic finite element program is used to perform probabilistic analysis of a materially nonlinear structure. The program used in this study is NESSUS (Numerical Evaluation of Stochastic Structure Under Stress), under development at Southwest Research Institute. The cumulative distribution function (CDF) of the radial stress of a thick-walled cylinder under internal pressure is computed and compared with the analytical solution. In addition, sensitivity factors showing the relative importance of the input random variables are calculated. Significant plasticity is present in this problem and has a pronounced effect on the probabilistic results. The random input variables are the material yield stress and internal pressure with Weibull and normal distributions, respectively. The results verify the ability of NESSUS to compute the CDF and sensitivity factors of a materially nonlinear structure. In addition, the ability of the Advanced Mean Value (AMV) procedure to assess the probabilistic behavior of structures which exhibit a highly nonlinear response is shown. Thus, the AMV procedure can be applied with confidence to other structures which exhibit nonlinear behavior.

An advanced probabilistic structural analysis method for implicit performance functions

NASA Technical Reports Server (NTRS)

Wu, Y.-T.; Millwater, H. R.; Cruse, T. A.

1989-01-01

In probabilistic structural analysis, the performance or response functions usually are implicitly defined and must be solved by numerical analysis methods such as finite element methods. In such cases, the most commonly used probabilistic analysis tool is the mean-based, second-moment method which provides only the first two statistical moments. This paper presents a generalized advanced mean value (AMV) method which is capable of establishing the distributions to provide additional information for reliability design. The method requires slightly more computations than the second-moment method but is highly efficient relative to the other alternative methods. In particular, the examples show that the AMV method can be used to solve problems involving non-monotonic functions that result in truncated distributions.

Performance of probabilistic method to detect duplicate individual case safety reports.

PubMed

Tregunno, Philip Michael; Fink, Dorthe Bech; Fernandez-Fernandez, Cristina; Lázaro-Bengoa, Edurne; Norén, G Niklas

2014-04-01

Individual case reports of suspected harm from medicines are fundamental for signal detection in postmarketing surveillance. Their effective analysis requires reliable data and one challenge is report duplication. These are multiple unlinked records describing the same suspected adverse drug reaction (ADR) in a particular patient. They distort statistical screening and can mislead clinical assessment. Many organisations rely on rule-based detection, but probabilistic record matching is an alternative. The aim of this study was to evaluate probabilistic record matching for duplicate detection, and to characterise the main sources of duplicate reports within each data set. vigiMatch™, a published probabilistic record matching algorithm, was applied to the WHO global individual case safety reports database, VigiBase(®), for reports submitted between 2000 and 2010. Reported drugs, ADRs, patient age, sex, country of origin, and date of onset were considered in the matching. Suspected duplicates for the UK, Denmark, and Spain were reviewed and classified by the respective national centre. This included evaluation to determine whether confirmed duplicates had already been identified by in-house, rule-based screening. Furthermore, each confirmed duplicate was classified with respect to the likely source of duplication. For each country, the proportions of suspected duplicates classified as confirmed duplicates, likely duplicates, otherwise related, and unrelated were obtained. The proportions of confirmed or likely duplicates that were not previously known by the national organisation were determined, and variations in the rates of suspected duplicates across subsets of reports were characterised. Overall, 2.5 % of the reports with sufficient information to be evaluated by vigiMatch were classified as suspected duplicates. The rates for the three countries considered in this study were 1.4 % (UK), 1.0 % (Denmark), and 0.7 % (Spain). Higher rates of suspected duplicates were observed for literature reports (11 %) and reports with fatal outcome (5 %), whereas a lower rate was observed for reports from consumers and non-health professionals (0.5 %). The predictive value for confirmed or likely duplicates among reports flagged as suspected duplicates by vigiMatch ranged from 86 % for the UK, to 64 % for Denmark and 33 % for Spain. The proportions of confirmed duplicates that were previously unknown to national centres ranged from 89 % for Spain, to 60 % for the UK and 38 % for Denmark, despite in-house duplicate detection processes in routine use. The proportion of unrelated cases among suspected duplicates were below 10 % for each national centre in the study. Probabilistic record matching, as implemented in vigiMatch, achieved good predictive value for confirmed or likely duplicates in each data source. Most of the false positives corresponded to otherwise related reports; less than 10 % were altogether unrelated. A substantial proportion of the correctly identified duplicates had not previously been detected by national centre activity. On one hand, vigiMatch highlighted duplicates that had been missed by rule-based methods, and on the other hand its lower total number of suspected duplicates to review improved the accuracy of manual review.

Probabilistic Finite Element Analysis & Design Optimization for Structural Designs

NASA Astrophysics Data System (ADS)

Deivanayagam, Arumugam

This study focuses on implementing probabilistic nature of material properties (Kevlar® 49) to the existing deterministic finite element analysis (FEA) of fabric based engine containment system through Monte Carlo simulations (MCS) and implementation of probabilistic analysis in engineering designs through Reliability Based Design Optimization (RBDO). First, the emphasis is on experimental data analysis focusing on probabilistic distribution models which characterize the randomness associated with the experimental data. The material properties of Kevlar® 49 are modeled using experimental data analysis and implemented along with an existing spiral modeling scheme (SMS) and user defined constitutive model (UMAT) for fabric based engine containment simulations in LS-DYNA. MCS of the model are performed to observe the failure pattern and exit velocities of the models. Then the solutions are compared with NASA experimental tests and deterministic results. MCS with probabilistic material data give a good prospective on results rather than a single deterministic simulation results. The next part of research is to implement the probabilistic material properties in engineering designs. The main aim of structural design is to obtain optimal solutions. In any case, in a deterministic optimization problem even though the structures are cost effective, it becomes highly unreliable if the uncertainty that may be associated with the system (material properties, loading etc.) is not represented or considered in the solution process. Reliable and optimal solution can be obtained by performing reliability optimization along with the deterministic optimization, which is RBDO. In RBDO problem formulation, in addition to structural performance constraints, reliability constraints are also considered. This part of research starts with introduction to reliability analysis such as first order reliability analysis, second order reliability analysis followed by simulation technique that are performed to obtain probability of failure and reliability of structures. Next, decoupled RBDO procedure is proposed with a new reliability analysis formulation with sensitivity analysis, which is performed to remove the highly reliable constraints in the RBDO, thereby reducing the computational time and function evaluations. Followed by implementation of the reliability analysis concepts and RBDO in finite element 2D truss problems and a planar beam problem are presented and discussed.

Challenges Ahead for Nuclear Facility Site-Specific Seismic Hazard Assessment in France: The Alternative Energies and the Atomic Energy Commission (CEA) Vision

NASA Astrophysics Data System (ADS)

Berge-Thierry, C.; Hollender, F.; Guyonnet-Benaize, C.; Baumont, D.; Ameri, G.; Bollinger, L.

2017-09-01

Seismic analysis in the context of nuclear safety in France is currently guided by a pure deterministic approach based on Basic Safety Rule ( Règle Fondamentale de Sûreté) RFS 2001-01 for seismic hazard assessment, and on the ASN/2/01 Guide that provides design rules for nuclear civil engineering structures. After the 2011 Tohohu earthquake, nuclear operators worldwide were asked to estimate the ability of their facilities to sustain extreme seismic loads. The French licensees then defined the `hard core seismic levels', which are higher than those considered for design or re-assessment of the safety of a facility. These were initially established on a deterministic basis, and they have been finally justified through state-of-the-art probabilistic seismic hazard assessments. The appreciation and propagation of uncertainties when assessing seismic hazard in France have changed considerably over the past 15 years. This evolution provided the motivation for the present article, the objectives of which are threefold: (1) to provide a description of the current practices in France to assess seismic hazard in terms of nuclear safety; (2) to discuss and highlight the sources of uncertainties and their treatment; and (3) to use a specific case study to illustrate how extended source modeling can help to constrain the key assumptions or parameters that impact upon seismic hazard assessment. This article discusses in particular seismic source characterization, strong ground motion prediction, and maximal magnitude constraints, according to the practice of the French Atomic Energy Commission. Due to increases in strong motion databases in terms of the number and quality of the records in their metadata and the uncertainty characterization, several recently published empirical ground motion prediction models are eligible for seismic hazard assessment in France. We show that propagation of epistemic and aleatory uncertainties is feasible in a deterministic approach, as in a probabilistic way. Assessment of seismic hazard in France in the framework of the safety of nuclear facilities should consider these recent advances. In this sense, the opening of discussions with all of the stakeholders in France to update the reference documents (i.e., RFS 2001-01; ASN/2/01 Guide) appears appropriate in the short term.

Probabilistic interpretation of Peelle's pertinent puzzle and its resolution

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hanson, Kenneth M.; Kawano, T.; Talou, P.

2004-01-01

Peelle's Pertinent Puzzle (PPP) states a seemingly plausible set of measurements with their covariance matrix, which produce an implausible answer. To answer the PPP question, we describe a reasonable experimental situation that is consistent with the PPP solution. The confusion surrounding the PPP arises in part because of its imprecise statement, which permits to a variety of interpretations and resulting answers, some of which seem implausible. We emphasize the importance of basing the analysis on an unambiguous probabilistic model that reflects the experimental situation. We present several different models of how the measurements quoted in the PPP problem could bemore » obtained, and interpret their solution in terms of a detailed probabilistic analysis. We suggest a probabilistic approach to handling uncertainties about which model to use.« less

Probabilistic Interpretation of Peelle's Pertinent Puzzle and its Resolution

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hanson, Kenneth M.; Kawano, Toshihiko; Talou, Patrick

2005-05-24

Peelle's Pertinent Puzzle (PPP) states a seemingly plausible set of measurements with their covariance matrix, which produce an implausible answer. To answer the PPP question, we describe a reasonable experimental situation that is consistent with the PPP solution. The confusion surrounding the PPP arises in part because of its imprecise statement, which permits to a variety of interpretations and resulting answers, some of which seem implausible. We emphasize the importance of basing the analysis on an unambiguous probabilistic model that reflects the experimental situation. We present several different models of how the measurements quoted in the PPP problem could bemore » obtained, and interpret their solution in terms of a detailed probabilistic analysis. We suggest a probabilistic approach to handling uncertainties about which model to use.« less

Structural reliability assessment capability in NESSUS

NASA Technical Reports Server (NTRS)

Millwater, H.; Wu, Y.-T.

1992-01-01

The principal capabilities of NESSUS (Numerical Evaluation of Stochastic Structures Under Stress), an advanced computer code developed for probabilistic structural response analysis, are reviewed, and its structural reliability assessed. The code combines flexible structural modeling tools with advanced probabilistic algorithms in order to compute probabilistic structural response and resistance, component reliability and risk, and system reliability and risk. An illustrative numerical example is presented.

Structural reliability assessment capability in NESSUS

NASA Astrophysics Data System (ADS)

Millwater, H.; Wu, Y.-T.

1992-07-01

The principal capabilities of NESSUS (Numerical Evaluation of Stochastic Structures Under Stress), an advanced computer code developed for probabilistic structural response analysis, are reviewed, and its structural reliability assessed. The code combines flexible structural modeling tools with advanced probabilistic algorithms in order to compute probabilistic structural response and resistance, component reliability and risk, and system reliability and risk. An illustrative numerical example is presented.

Distributed collaborative probabilistic design of multi-failure structure with fluid-structure interaction using fuzzy neural network of regression

NASA Astrophysics Data System (ADS)

Song, Lu-Kai; Wen, Jie; Fei, Cheng-Wei; Bai, Guang-Chen

2018-05-01

To improve the computing efficiency and precision of probabilistic design for multi-failure structure, a distributed collaborative probabilistic design method-based fuzzy neural network of regression (FR) (called as DCFRM) is proposed with the integration of distributed collaborative response surface method and fuzzy neural network regression model. The mathematical model of DCFRM is established and the probabilistic design idea with DCFRM is introduced. The probabilistic analysis of turbine blisk involving multi-failure modes (deformation failure, stress failure and strain failure) was investigated by considering fluid-structure interaction with the proposed method. The distribution characteristics, reliability degree, and sensitivity degree of each failure mode and overall failure mode on turbine blisk are obtained, which provides a useful reference for improving the performance and reliability of aeroengine. Through the comparison of methods shows that the DCFRM reshapes the probability of probabilistic analysis for multi-failure structure and improves the computing efficiency while keeping acceptable computational precision. Moreover, the proposed method offers a useful insight for reliability-based design optimization of multi-failure structure and thereby also enriches the theory and method of mechanical reliability design.

Long-term safety assessment of trench-type surface repository at Chernobyl, Ukraine - computer model and comparison with results from simplified models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Haverkamp, B.; Krone, J.; Shybetskyi, I.

2013-07-01

The Radioactive Waste Disposal Facility (RWDF) Buryakovka was constructed in 1986 as part of the intervention measures after the accident at Chernobyl NPP (ChNPP). Today, the surface repository for solid low and intermediate level waste (LILW) is still being operated but its maximum capacity is nearly reached. Long-existing plans for increasing the capacity of the facility shall be implemented in the framework of the European Commission INSC Programme (Instrument for Nuclear Safety Co-operation). Within the first phase of this project, DBE Technology GmbH prepared a safety analysis report of the facility in its current state (SAR) and a preliminary safetymore » analysis report (PSAR) for a future extended facility based on the planned enlargement. In addition to a detailed mathematical model, also simplified models have been developed to verify results of the former one and enhance confidence in the results. Comparison of the results show that - depending on the boundary conditions - simplifications like modeling the multi trench repository as one generic trench might have very limited influence on the overall results compared to the general uncertainties associated with respective long-term calculations. In addition to their value in regard to verification of more complex models which is important to increase confidence in the overall results, such simplified models can also offer the possibility to carry out time consuming calculations like probabilistic calculations or detailed sensitivity analysis in an economic manner. (authors)« less

Impact of refining the assessment of dietary exposure to cadmium in the European adult population.

PubMed

Ferrari, Pietro; Arcella, Davide; Heraud, Fanny; Cappé, Stefano; Fabiansson, Stefan

2013-01-01

Exposure assessment constitutes an important step in any risk assessment of potentially harmful substances present in food. The European Food Safety Authority (EFSA) first assessed dietary exposure to cadmium in Europe using a deterministic framework, resulting in mean values of exposure in the range of health-based guidance values. Since then, the characterisation of foods has been refined to better match occurrence and consumption data, and a new strategy to handle left-censoring in occurrence data was devised. A probabilistic assessment was performed and compared with deterministic estimates, using occurrence values at the European level and consumption data from 14 national dietary surveys. Mean estimates in the probabilistic assessment ranged from 1.38 (95% CI = 1.35-1.44) to 2.08 (1.99-2.23) µg kg⁻¹ bodyweight (bw) week⁻¹ across the different surveys, which were less than 10% lower than deterministic (middle bound) mean values that ranged from 1.50 to 2.20 µg kg⁻¹ bw week⁻¹. Probabilistic 95th percentile estimates of dietary exposure ranged from 2.65 (2.57-2.72) to 4.99 (4.62-5.38) µg kg⁻¹ bw week⁻¹, which were, with the exception of one survey, between 3% and 17% higher than middle-bound deterministic estimates. Overall, the proportion of subjects exceeding the tolerable weekly intake of 2.5 µg kg⁻¹ bw ranged from 14.8% (13.6-16.0%) to 31.2% (29.7-32.5%) according to the probabilistic assessment. The results of this work indicate that mean values of dietary exposure to cadmium in the European population were of similar magnitude using determinist or probabilistic assessments. For higher exposure levels, probabilistic estimates were almost consistently larger than deterministic counterparts, thus reflecting the impact of using the full distribution of occurrence values to determine exposure levels. It is considered prudent to use probabilistic methodology should exposure estimates be close to or exceeding health-based guidance values.

Integrated Risk-Informed Decision-Making for an ALMR PRISM

DOE Office of Scientific and Technical Information (OSTI.GOV)

Muhlheim, Michael David; Belles, Randy; Denning, Richard S.

Decision-making is the process of identifying decision alternatives, assessing those alternatives based on predefined metrics, selecting an alternative (i.e., making a decision), and then implementing that alternative. The generation of decisions requires a structured, coherent process, or a decision-making process. The overall objective for this work is that the generalized framework is adopted into an autonomous decision-making framework and tailored to specific requirements for various applications. In this context, automation is the use of computing resources to make decisions and implement a structured decision-making process with limited or no human intervention. The overriding goal of automation is to replace ormore » supplement human decision makers with reconfigurable decision-making modules that can perform a given set of tasks rationally, consistently, and reliably. Risk-informed decision-making requires a probabilistic assessment of the likelihood of success given the status of the plant/systems and component health, and a deterministic assessment between plant operating parameters and reactor protection parameters to prevent unnecessary trips and challenges to plant safety systems. The probabilistic portion of the decision-making engine of the supervisory control system is based on the control actions associated with an ALMR PRISM. Newly incorporated into the probabilistic models are the prognostic/diagnostic models developed by Pacific Northwest National Laboratory. These allow decisions to incorporate the health of components into the decision–making process. Once the control options are identified and ranked based on the likelihood of success, the supervisory control system transmits the options to the deterministic portion of the platform. The deterministic portion of the decision-making engine uses thermal-hydraulic modeling and components for an advanced liquid-metal reactor Power Reactor Inherently Safe Module. The deterministic multi-attribute decision-making framework uses various sensor data (e.g., reactor outlet temperature, steam generator drum level) and calculates its position within the challenge state, its trajectory, and its margin within the controllable domain using utility functions to evaluate current and projected plant state space for different control decisions. The metrics that are evaluated are based on reactor trip set points. The integration of the deterministic calculations using multi-physics analyses and probabilistic safety calculations allows for the examination and quantification of margin recovery strategies. This also provides validation of the control options identified from the probabilistic assessment. Thus, the thermalhydraulics analyses are used to validate the control options identified from the probabilistic assessment. Future work includes evaluating other possible metrics and computational efficiencies, and developing a user interface to mimic display panels at a modern nuclear power plant.« less

Bayesian analysis of rare events

DOE Office of Scientific and Technical Information (OSTI.GOV)

Straub, Daniel, E-mail: straub@tum.de; Papaioannou, Iason; Betz, Wolfgang

2016-06-01

In many areas of engineering and science there is an interest in predicting the probability of rare events, in particular in applications related to safety and security. Increasingly, such predictions are made through computer models of physical systems in an uncertainty quantification framework. Additionally, with advances in IT, monitoring and sensor technology, an increasing amount of data on the performance of the systems is collected. This data can be used to reduce uncertainty, improve the probability estimates and consequently enhance the management of rare events and associated risks. Bayesian analysis is the ideal method to include the data into themore » probabilistic model. It ensures a consistent probabilistic treatment of uncertainty, which is central in the prediction of rare events, where extrapolation from the domain of observation is common. We present a framework for performing Bayesian updating of rare event probabilities, termed BUS. It is based on a reinterpretation of the classical rejection-sampling approach to Bayesian analysis, which enables the use of established methods for estimating probabilities of rare events. By drawing upon these methods, the framework makes use of their computational efficiency. These methods include the First-Order Reliability Method (FORM), tailored importance sampling (IS) methods and Subset Simulation (SuS). In this contribution, we briefly review these methods in the context of the BUS framework and investigate their applicability to Bayesian analysis of rare events in different settings. We find that, for some applications, FORM can be highly efficient and is surprisingly accurate, enabling Bayesian analysis of rare events with just a few model evaluations. In a general setting, BUS implemented through IS and SuS is more robust and flexible.« less

Assessing emergency planning zone for new nuclear power plant considering risk of extreme external events

NASA Astrophysics Data System (ADS)

Alzbutas, Robertas

2015-04-01

In general, the Emergency Planning Zones (EPZ) are defined as well as plant site and arrangement structures are designed to minimize the potential for natural and manmade hazards external to the plant from affecting the plant safety related functions, which can affect nearby population and environment. This may include consideration of extreme winds, fires, flooding, aircraft crash, seismic activity, etc. Thus the design basis for plant and site is deeply related to the effects of any postulated external events and the limitation of the plant capability to cope with accidents i.e. perform safety functions. It has been observed that the Probabilistic Safety Assessment (PSA) methodologies to deal with EPZ and extreme external events have not reached the same level of maturity as for severe internal events. The design basis for any plant and site is deeply related to the effects of any postulated external events and the limitation of the plant capability to cope with accidents i.e. perform safety functions. As a prime example of an advanced reactor and new Nuclear Power Plant (NPP) with enhanced safety, the International Reactor Innovative and Secure (IRIS) and Site selection for New NPP in Lithuania had been considered in this work. In the used Safety-by-Design™ approach, the PSA played obviously a key role; therefore a Preliminary IRIS PSA had been developed along with the design. For the design and pre-licensing process of IRIS the external events analysis included both qualitative evaluation and quantitative assessment. As a result of preliminary qualitative analyses, the external events that were chosen for more detailed quantitative scoping evaluation were high winds and tornadoes, aircraft crash, and seismic events. For the site selection in Lithuania a detail site evaluation process was performed and related to the EPZ and risk zoning considerations. In general, applying the quantitative assessment, bounding site characteristics could be used in order to optimize potential redefinition or future restrictions on plant siting and risk zoning. It must be noticed that the use of existing regulations and installations as the basis for this redefinition will not in any way impact the high degree of conservatism inherent in current regulations. Moreover, the remapping process makes this methodology partially independent from the uncertainties still affecting probabilistic techniques. Notwithstanding these considerations, it is still expected that applying this methodology to advanced plant designs with improved safety features will allow significant changes in the emergency planning requirements, and specifically the size of the EPZ. In particular, in the case of IRIS it is expected that taking full credit of the Safety-by-Design™ approach of the IRIS reactor will allow a dramatic changes in the EPZ, while still maintaining a level of protection to the public fully consistent with existing regulations.

Probabilistic analysis of the efficiency of the damping devices against nuclear fuel container falling

NASA Astrophysics Data System (ADS)

Králik, Juraj

2017-07-01

The paper presents the probabilistic and sensitivity analysis of the efficiency of the damping devices cover of nuclear power plant under impact of the container of nuclear fuel of type TK C30 drop. The finite element idealization of nuclear power plant structure is used in space. The steel pipe damper system is proposed for dissipation of the kinetic energy of the container free fall. The experimental results of the shock-damper basic element behavior under impact loads are presented. The Newmark integration method is used for solution of the dynamic equations. The sensitivity and probabilistic analysis of damping devices was realized in the AntHILL and ANSYS software.

Development of Probabilistic Structural Analysis Integrated with Manufacturing Processes

NASA Technical Reports Server (NTRS)

Pai, Shantaram S.; Nagpal, Vinod K.

2007-01-01

An effort has been initiated to integrate manufacturing process simulations with probabilistic structural analyses in order to capture the important impacts of manufacturing uncertainties on component stress levels and life. Two physics-based manufacturing process models (one for powdered metal forging and the other for annular deformation resistance welding) have been linked to the NESSUS structural analysis code. This paper describes the methodology developed to perform this integration including several examples. Although this effort is still underway, particularly for full integration of a probabilistic analysis, the progress to date has been encouraging and a software interface that implements the methodology has been developed. The purpose of this paper is to report this preliminary development.

Fault trees for decision making in systems analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lambert, Howard E.

1975-10-09

The application of fault tree analysis (FTA) to system safety and reliability is presented within the framework of system safety analysis. The concepts and techniques involved in manual and automated fault tree construction are described and their differences noted. The theory of mathematical reliability pertinent to FTA is presented with emphasis on engineering applications. An outline of the quantitative reliability techniques of the Reactor Safety Study is given. Concepts of probabilistic importance are presented within the fault tree framework and applied to the areas of system design, diagnosis and simulation. The computer code IMPORTANCE ranks basic events and cut setsmore » according to a sensitivity analysis. A useful feature of the IMPORTANCE code is that it can accept relative failure data as input. The output of the IMPORTANCE code can assist an analyst in finding weaknesses in system design and operation, suggest the most optimal course of system upgrade, and determine the optimal location of sensors within a system. A general simulation model of system failure in terms of fault tree logic is described. The model is intended for efficient diagnosis of the causes of system failure in the event of a system breakdown. It can also be used to assist an operator in making decisions under a time constraint regarding the future course of operations. The model is well suited for computer implementation. New results incorporated in the simulation model include an algorithm to generate repair checklists on the basis of fault tree logic and a one-step-ahead optimization procedure that minimizes the expected time to diagnose system failure.« less

Applicability of risk-based management and the need for risk-based economic decision analysis at hazardous waste contaminated sites.

PubMed

Khadam, Ibrahim; Kaluarachchi, Jagath J

2003-07-01

Decision analysis in subsurface contamination management is generally carried out through a traditional engineering economic viewpoint. However, new advances in human health risk assessment, namely, the probabilistic risk assessment, and the growing awareness of the importance of soft data in the decision-making process, require decision analysis methodologies that are capable of accommodating non-technical and politically biased qualitative information. In this work, we discuss the major limitations of the currently practiced decision analysis framework, which evolves around the definition of risk and cost of risk, and its poor ability to communicate risk-related information. A demonstration using a numerical example was conducted to provide insight on these limitations of the current decision analysis framework. The results from this simple ground water contamination and remediation scenario were identical to those obtained from studies carried out on existing Superfund sites, which suggests serious flaws in the current risk management framework. In order to provide a perspective on how these limitations may be avoided in future formulation of the management framework, more matured and well-accepted approaches to decision analysis in dam safety and the utility industry, where public health and public investment are of great concern, are presented and their applicability in subsurface remediation management is discussed. Finally, in light of the success of the application of risk-based decision analysis in dam safety and the utility industry, potential options for decision analysis in subsurface contamination management are discussed.

Reliability and Maintainability Data for Lead Lithium Cooling Systems

DOE PAGES

Cadwallader, Lee

2016-11-16

This article presents component failure rate data for use in assessment of lead lithium cooling systems. Best estimate data applicable to this liquid metal coolant is presented. Repair times for similar components are also referenced in this work. These data support probabilistic safety assessment and reliability, availability, maintainability and inspectability analyses.

Overview of U.S. nuclear launch safety approval process, supporting launch vehicle databook and probabilistic risk assessment methods

NASA Technical Reports Server (NTRS)

Reinhart, L. E.

2001-01-01

This paper provides an overview of the U.S. space nuclear power system launch approval process as defined by the two separate requirements of the National Environmental Policy Act (NEPA) and Presidential Directive/National Security Council Memorandum No. 25 (PD/NSC-25).

Probabilistic sensitivity analysis for decision trees with multiple branches: use of the Dirichlet distribution in a Bayesian framework.

PubMed

Briggs, Andrew H; Ades, A E; Price, Martin J

2003-01-01

In structuring decision models of medical interventions, it is commonly recommended that only 2 branches be used for each chance node to avoid logical inconsistencies that can arise during sensitivity analyses if the branching probabilities do not sum to 1. However, information may be naturally available in an unconditional form, and structuring a tree in conditional form may complicate rather than simplify the sensitivity analysis of the unconditional probabilities. Current guidance emphasizes using probabilistic sensitivity analysis, and a method is required to provide probabilistic probabilities over multiple branches that appropriately represents uncertainty while satisfying the requirement that mutually exclusive event probabilities should sum to 1. The authors argue that the Dirichlet distribution, the multivariate equivalent of the beta distribution, is appropriate for this purpose and illustrate its use for generating a fully probabilistic transition matrix for a Markov model. Furthermore, they demonstrate that by adopting a Bayesian approach, the problem of observing zero counts for transitions of interest can be overcome.

Risk analysis of analytical validations by probabilistic modification of FMEA.

PubMed

Barends, D M; Oldenhof, M T; Vredenbregt, M J; Nauta, M J

2012-05-01

Risk analysis is a valuable addition to validation of an analytical chemistry process, enabling not only detecting technical risks, but also risks related to human failures. Failure Mode and Effect Analysis (FMEA) can be applied, using a categorical risk scoring of the occurrence, detection and severity of failure modes, and calculating the Risk Priority Number (RPN) to select failure modes for correction. We propose a probabilistic modification of FMEA, replacing the categorical scoring of occurrence and detection by their estimated relative frequency and maintaining the categorical scoring of severity. In an example, the results of traditional FMEA of a Near Infrared (NIR) analytical procedure used for the screening of suspected counterfeited tablets are re-interpretated by this probabilistic modification of FMEA. Using this probabilistic modification of FMEA, the frequency of occurrence of undetected failure mode(s) can be estimated quantitatively, for each individual failure mode, for a set of failure modes, and the full analytical procedure. Copyright © 2012 Elsevier B.V. All rights reserved.

Existential risks: exploring a robust risk reduction strategy.

PubMed

Jebari, Karim

2015-06-01

A small but growing number of studies have aimed to understand, assess and reduce existential risks, or risks that threaten the continued existence of mankind. However, most attention has been focused on known and tangible risks. This paper proposes a heuristic for reducing the risk of black swan extinction events. These events are, as the name suggests, stochastic and unforeseen when they happen. Decision theory based on a fixed model of possible outcomes cannot properly deal with this kind of event. Neither can probabilistic risk analysis. This paper will argue that the approach that is referred to as engineering safety could be applied to reducing the risk from black swan extinction events. It will also propose a conceptual sketch of how such a strategy may be implemented: isolated, self-sufficient, and continuously manned underground refuges. Some characteristics of such refuges are also described, in particular the psychosocial aspects. Furthermore, it is argued that this implementation of the engineering safety strategy safety barriers would be effective and plausible and could reduce the risk of an extinction event in a wide range of possible (known and unknown) scenarios. Considering the staggering opportunity cost of an existential catastrophe, such strategies ought to be explored more vigorously.

Development of a probabilistic analysis methodology for structural reliability estimation

NASA Technical Reports Server (NTRS)

Torng, T. Y.; Wu, Y.-T.

1991-01-01

The novel probabilistic analysis method for assessment of structural reliability presented, which combines fast-convolution with an efficient structural reliability analysis, can after identifying the most important point of a limit state proceed to establish a quadratic-performance function. It then transforms the quadratic function into a linear one, and applies fast convolution. The method is applicable to problems requiring computer-intensive structural analysis. Five illustrative examples of the method's application are given.

Structural Deterministic Safety Factors Selection Criteria and Verification

NASA Technical Reports Server (NTRS)

Verderaime, V.

1992-01-01

Though current deterministic safety factors are arbitrarily and unaccountably specified, its ratio is rooted in resistive and applied stress probability distributions. This study approached the deterministic method from a probabilistic concept leading to a more systematic and coherent philosophy and criterion for designing more uniform and reliable high-performance structures. The deterministic method was noted to consist of three safety factors: a standard deviation multiplier of the applied stress distribution; a K-factor for the A- or B-basis material ultimate stress; and the conventional safety factor to ensure that the applied stress does not operate in the inelastic zone of metallic materials. The conventional safety factor is specifically defined as the ratio of ultimate-to-yield stresses. A deterministic safety index of the combined safety factors was derived from which the corresponding reliability proved the deterministic method is not reliability sensitive. The bases for selecting safety factors are presented and verification requirements are discussed. The suggested deterministic approach is applicable to all NASA, DOD, and commercial high-performance structures under static stresses.

Reliability-Based Stability Analysis of Rock Slopes Using Numerical Analysis and Response Surface Method

NASA Astrophysics Data System (ADS)

Dadashzadeh, N.; Duzgun, H. S. B.; Yesiloglu-Gultekin, N.

2017-08-01

While advanced numerical techniques in slope stability analysis are successfully used in deterministic studies, they have so far found limited use in probabilistic analyses due to their high computation cost. The first-order reliability method (FORM) is one of the most efficient probabilistic techniques to perform probabilistic stability analysis by considering the associated uncertainties in the analysis parameters. However, it is not possible to directly use FORM in numerical slope stability evaluations as it requires definition of a limit state performance function. In this study, an integrated methodology for probabilistic numerical modeling of rock slope stability is proposed. The methodology is based on response surface method, where FORM is used to develop an explicit performance function from the results of numerical simulations. The implementation of the proposed methodology is performed by considering a large potential rock wedge in Sumela Monastery, Turkey. The accuracy of the developed performance function to truly represent the limit state surface is evaluated by monitoring the slope behavior. The calculated probability of failure is compared with Monte Carlo simulation (MCS) method. The proposed methodology is found to be 72% more efficient than MCS, while the accuracy is decreased with an error of 24%.

A preliminary cost-effectiveness analysis of hepatitis E vaccination among pregnant women in epidemic regions.

PubMed

Zhao, Yueyuan; Zhang, Xuefeng; Zhu, Fengcai; Jin, Hui; Wang, Bei

2016-08-02

Objective To estimate the cost-effectiveness of hepatitis E vaccination among pregnant women in epidemic regions. Methods A decision tree model was constructed to evaluate the cost-effectiveness of 3 hepatitis E virus vaccination strategies from societal perspectives. The model parameters were estimated on the basis of published studies and experts' experience. Sensitivity analysis was used to evaluate the uncertainties of the model. Results Vaccination was more economically effective on the basis of the incremental cost-effectiveness ratio (ICER< 3 times China's per capital gross domestic product/quality-adjusted life years); moreover, screening and vaccination had higher QALYs and lower costs compared with universal vaccination. No parameters significantly impacted ICER in one-way sensitivity analysis, and probabilistic sensitivity analysis also showed screening and vaccination to be the dominant strategy. Conclusion Screening and vaccination is the most economical strategy for pregnant women in epidemic regions; however, further studies are necessary to confirm the efficacy and safety of the hepatitis E vaccines.

Risk-Based Probabilistic Approach to Aeropropulsion System Assessment

NASA Technical Reports Server (NTRS)

Tong, Michael T.

2002-01-01

In an era of shrinking development budgets and resources, where there is also an emphasis on reducing the product development cycle, the role of system assessment, performed in the early stages of an engine development program, becomes very critical to the successful development of new aeropropulsion systems. A reliable system assessment not only helps to identify the best propulsion system concept among several candidates, it can also identify which technologies are worth pursuing. This is particularly important for advanced aeropropulsion technology development programs, which require an enormous amount of resources. In the current practice of deterministic, or point-design, approaches, the uncertainties of design variables are either unaccounted for or accounted for by safety factors. This could often result in an assessment with unknown and unquantifiable reliability. Consequently, it would fail to provide additional insight into the risks associated with the new technologies, which are often needed by decision makers to determine the feasibility and return-on-investment of a new aircraft engine. In this work, an alternative approach based on the probabilistic method was described for a comprehensive assessment of an aeropropulsion system. The statistical approach quantifies the design uncertainties inherent in a new aeropropulsion system and their influences on engine performance. Because of this, it enhances the reliability of a system assessment. A technical assessment of a wave-rotor-enhanced gas turbine engine was performed to demonstrate the methodology. The assessment used probability distributions to account for the uncertainties that occur in component efficiencies and flows and in mechanical design variables. The approach taken in this effort was to integrate the thermodynamic cycle analysis embedded in the computer code NEPP (NASA Engine Performance Program) and the engine weight analysis embedded in the computer code WATE (Weight Analysis of Turbine Engines) with the fast probability integration technique (FPI). FPI was developed by Southwest Research Institute under contract with the NASA Glenn Research Center. The results were plotted in the form of cumulative distribution functions and sensitivity analyses and were compared with results from the traditional deterministic approach. The comparison showed that the probabilistic approach provides a more realistic and systematic way to assess an aeropropulsion system. The current work addressed the application of the probabilistic approach to assess specific fuel consumption, engine thrust, and weight. Similarly, the approach can be used to assess other aspects of aeropropulsion system performance, such as cost, acoustic noise, and emissions. Additional information is included in the original extended abstract.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gougar, Hans

This document outlines the development of a high fidelity, best estimate nuclear power plant severe transient simulation capability that will complement or enhance the integral system codes historically used for licensing and analysis of severe accidents. As with other tools in the Risk Informed Safety Margin Characterization (RISMC) Toolkit, the ultimate user of Enhanced Severe Transient Analysis and Prevention (ESTAP) capability is the plant decision-maker; the deliverable to that customer is a modern, simulation-based safety analysis capability, applicable to a much broader class of safety issues than is traditional Light Water Reactor (LWR) licensing analysis. Currently, the RISMC pathway’s majormore » emphasis is placed on developing RELAP-7, a next-generation safety analysis code, and on showing how to use RELAP-7 to analyze margin from a modern point of view: that is, by characterizing margin in terms of the probabilistic spectra of the “loads” applied to systems, structures, and components (SSCs), and the “capacity” of those SSCs to resist those loads without failing. The first objective of the ESTAP task, and the focus of one task of this effort, is to augment RELAP-7 analyses with user-selected multi-dimensional, multi-phase models of specific plant components to simulate complex phenomena that may lead to, or exacerbate, severe transients and core damage. Such phenomena include: coolant crossflow between PWR assemblies during a severe reactivity transient, stratified single or two-phase coolant flow in primary coolant piping, inhomogeneous mixing of emergency coolant water or boric acid with hot primary coolant, and water hammer. These are well-documented phenomena associated with plant transients but that are generally not captured in system codes. They are, however, generally limited to specific components, structures, and operating conditions. The second ESTAP task is to similarly augment a severe (post-core damage) accident integral analyses code with high fidelity simulations that would allow investigation of multi-dimensional, multi-phase containment phenomena that are only treated approximately in established codes.« less

Probabilistic machine learning and artificial intelligence.

PubMed

Ghahramani, Zoubin

2015-05-28

How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic framework, which describes how to represent and manipulate uncertainty about models and predictions, has a central role in scientific data analysis, machine learning, robotics, cognitive science and artificial intelligence. This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and automatic model discovery.

Probabilistic machine learning and artificial intelligence

NASA Astrophysics Data System (ADS)

Ghahramani, Zoubin

2015-05-01

How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic framework, which describes how to represent and manipulate uncertainty about models and predictions, has a central role in scientific data analysis, machine learning, robotics, cognitive science and artificial intelligence. This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and automatic model discovery.

Toward a Probabilistic Phenological Model for Wheat Growing Degree Days (GDD)

NASA Astrophysics Data System (ADS)

Rahmani, E.; Hense, A.

2017-12-01

Are there deterministic relations between phenological and climate parameters? The answer is surely `No'. This answer motivated us to solve the problem through probabilistic theories. Thus, we developed a probabilistic phenological model which has the advantage of giving additional information in terms of uncertainty. To that aim, we turned to a statistical analysis named survival analysis. Survival analysis deals with death in biological organisms and failure in mechanical systems. In survival analysis literature, death or failure is considered as an event. By event, in this research we mean ripening date of wheat. We will assume only one event in this special case. By time, we mean the growing duration from sowing to ripening as lifetime for wheat which is a function of GDD. To be more precise we will try to perform the probabilistic forecast for wheat ripening. The probability value will change between 0 and 1. Here, the survivor function gives the probability that the not ripened wheat survives longer than a specific time or will survive to the end of its lifetime as a ripened crop. The survival function at each station is determined by fitting a normal distribution to the GDD as the function of growth duration. Verification of the models obtained is done using CRPS skill score (CRPSS). The positive values of CRPSS indicate the large superiority of the probabilistic phonologic survival model to the deterministic models. These results demonstrate that considering uncertainties in modeling are beneficial, meaningful and necessary. We believe that probabilistic phenological models have the potential to help reduce the vulnerability of agricultural production systems to climate change thereby increasing food security.

Application of a stochastic snowmelt model for probabilistic decisionmaking

NASA Technical Reports Server (NTRS)

Mccuen, R. H.

1983-01-01

A stochastic form of the snowmelt runoff model that can be used for probabilistic decision-making was developed. The use of probabilistic streamflow predictions instead of single valued deterministic predictions leads to greater accuracy in decisions. While the accuracy of the output function is important in decisionmaking, it is also important to understand the relative importance of the coefficients. Therefore, a sensitivity analysis was made for each of the coefficients.

Probabilistic evaluation of uncertainties and risks in aerospace components

NASA Technical Reports Server (NTRS)

Shah, A. R.; Shiao, M. C.; Nagpal, V. K.; Chamis, C. C.

1992-01-01

A methodology is presented for the computational simulation of primitive variable uncertainties, and attention is given to the simulation of specific aerospace components. Specific examples treated encompass a probabilistic material behavior model, as well as static, dynamic, and fatigue/damage analyses of a turbine blade in a mistuned bladed rotor in the SSME turbopumps. An account is given of the use of the NESSES probabilistic FEM analysis CFD code.

Incorporating psychological influences in probabilistic cost analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kujawski, Edouard; Alvaro, Mariana; Edwards, William

2004-01-08

Today's typical probabilistic cost analysis assumes an ''ideal'' project that is devoid of the human and organizational considerations that heavily influence the success and cost of real-world projects. In the real world ''Money Allocated Is Money Spent'' (MAIMS principle); cost underruns are rarely available to protect against cost overruns while task overruns are passed on to the total project cost. Realistic cost estimates therefore require a modified probabilistic cost analysis that simultaneously models the cost management strategy including budget allocation. Psychological influences such as overconfidence in assessing uncertainties and dependencies among cost elements and risks are other important considerations thatmore » are generally not addressed. It should then be no surprise that actual project costs often exceed the initial estimates and are delivered late and/or with a reduced scope. This paper presents a practical probabilistic cost analysis model that incorporates recent findings in human behavior and judgment under uncertainty, dependencies among cost elements, the MAIMS principle, and project management practices. Uncertain cost elements are elicited from experts using the direct fractile assessment method and fitted with three-parameter Weibull distributions. The full correlation matrix is specified in terms of two parameters that characterize correlations among cost elements in the same and in different subsystems. The analysis is readily implemented using standard Monte Carlo simulation tools such as {at}Risk and Crystal Ball{reg_sign}. The analysis of a representative design and engineering project substantiates that today's typical probabilistic cost analysis is likely to severely underestimate project cost for probability of success values of importance to contractors and procuring activities. The proposed approach provides a framework for developing a viable cost management strategy for allocating baseline budgets and contingencies. Given the scope and magnitude of the cost-overrun problem, the benefits are likely to be significant.« less

Reliability and Failure in NASA Missions: Blunders, Normal Accidents, High Reliability, Bad Luck

NASA Technical Reports Server (NTRS)

Jones, Harry W.

2015-01-01

NASA emphasizes crew safety and system reliability but several unfortunate failures have occurred. The Apollo 1 fire was mistakenly unanticipated. After that tragedy, the Apollo program gave much more attention to safety. The Challenger accident revealed that NASA had neglected safety and that management underestimated the high risk of shuttle. Probabilistic Risk Assessment was adopted to provide more accurate failure probabilities for shuttle and other missions. NASA's "faster, better, cheaper" initiative and government procurement reform led to deliberately dismantling traditional reliability engineering. The Columbia tragedy and Mars mission failures followed. Failures can be attributed to blunders, normal accidents, or bad luck. Achieving high reliability is difficult but possible.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ramuhalli, Pradeep; Hirt, Evelyn H.; Veeramany, Arun

This research report summaries the development and evaluation of a prototypic enhanced risk monitor (ERM) methodology (framework) that includes alternative risk metrics and uncertainty analysis. This updated ERM methodology accounts for uncertainty in the equipment condition assessment (ECA), the prognostic result, and the probabilistic risk assessment (PRA) model. It is anticipated that the ability to characterize uncertainty in the estimated risk and update the risk estimates in real time based on equipment condition assessment (ECA) will provide a mechanism for optimizing plant performance while staying within specified safety margins. These results (based on impacting active component O&M using real-time equipmentmore » condition information) are a step towards ERMs that, if integrated with AR supervisory plant control systems, can help control O&M costs and improve affordability of advanced reactors.« less

Probability and possibility-based representations of uncertainty in fault tree analysis.

PubMed

Flage, Roger; Baraldi, Piero; Zio, Enrico; Aven, Terje

2013-01-01

Expert knowledge is an important source of input to risk analysis. In practice, experts might be reluctant to characterize their knowledge and the related (epistemic) uncertainty using precise probabilities. The theory of possibility allows for imprecision in probability assignments. The associated possibilistic representation of epistemic uncertainty can be combined with, and transformed into, a probabilistic representation; in this article, we show this with reference to a simple fault tree analysis. We apply an integrated (hybrid) probabilistic-possibilistic computational framework for the joint propagation of the epistemic uncertainty on the values of the (limiting relative frequency) probabilities of the basic events of the fault tree, and we use possibility-probability (probability-possibility) transformations for propagating the epistemic uncertainty within purely probabilistic and possibilistic settings. The results of the different approaches (hybrid, probabilistic, and possibilistic) are compared with respect to the representation of uncertainty about the top event (limiting relative frequency) probability. Both the rationale underpinning the approaches and the computational efforts they require are critically examined. We conclude that the approaches relevant in a given setting depend on the purpose of the risk analysis, and that further research is required to make the possibilistic approaches operational in a risk analysis context. © 2012 Society for Risk Analysis.

Development of a First-of-a-Kind Deterministic Decision-Making Tool for Supervisory Control System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cetiner, Sacit M; Kisner, Roger A; Muhlheim, Michael David

2015-07-01

Decision-making is the process of identifying and choosing alternatives where each alternative offers a different approach or path to move from a given state or condition to a desired state or condition. The generation of consistent decisions requires that a structured, coherent process be defined, immediately leading to a decision-making framework. The overall objective of the generalized framework is for it to be adopted into an autonomous decision-making framework and tailored to specific requirements for various applications. In this context, automation is the use of computing resources to make decisions and implement a structured decision-making process with limited or nomore » human intervention. The overriding goal of automation is to replace or supplement human decision makers with reconfigurable decision- making modules that can perform a given set of tasks reliably. Risk-informed decision making requires a probabilistic assessment of the likelihood of success given the status of the plant/systems and component health, and a deterministic assessment between plant operating parameters and reactor protection parameters to prevent unnecessary trips and challenges to plant safety systems. The implementation of the probabilistic portion of the decision-making engine of the proposed supervisory control system was detailed in previous milestone reports. Once the control options are identified and ranked based on the likelihood of success, the supervisory control system transmits the options to the deterministic portion of the platform. The deterministic multi-attribute decision-making framework uses variable sensor data (e.g., outlet temperature) and calculates where it is within the challenge state, its trajectory, and margin within the controllable domain using utility functions to evaluate current and projected plant state space for different control decisions. Metrics to be evaluated include stability, cost, time to complete (action), power level, etc. The integration of deterministic calculations using multi-physics analyses (i.e., neutronics, thermal, and thermal-hydraulics) and probabilistic safety calculations allows for the examination and quantification of margin recovery strategies. This also provides validation of the control options identified from the probabilistic assessment. Thus, the thermal-hydraulics analyses are used to validate the control options identified from the probabilistic assessment. Future work includes evaluating other possible metrics and computational efficiencies.« less

Learning Probabilistic Logic Models from Probabilistic Examples

PubMed Central

Chen, Jianzhong; Muggleton, Stephen; Santos, José

2009-01-01

Abstract We revisit an application developed originally using abductive Inductive Logic Programming (ILP) for modeling inhibition in metabolic networks. The example data was derived from studies of the effects of toxins on rats using Nuclear Magnetic Resonance (NMR) time-trace analysis of their biofluids together with background knowledge representing a subset of the Kyoto Encyclopedia of Genes and Genomes (KEGG). We now apply two Probabilistic ILP (PILP) approaches - abductive Stochastic Logic Programs (SLPs) and PRogramming In Statistical modeling (PRISM) to the application. Both approaches support abductive learning and probability predictions. Abductive SLPs are a PILP framework that provides possible worlds semantics to SLPs through abduction. Instead of learning logic models from non-probabilistic examples as done in ILP, the PILP approach applied in this paper is based on a general technique for introducing probability labels within a standard scientific experimental setting involving control and treated data. Our results demonstrate that the PILP approach provides a way of learning probabilistic logic models from probabilistic examples, and the PILP models learned from probabilistic examples lead to a significant decrease in error accompanied by improved insight from the learned results compared with the PILP models learned from non-probabilistic examples. PMID:19888348

Learning Probabilistic Logic Models from Probabilistic Examples.

PubMed

Chen, Jianzhong; Muggleton, Stephen; Santos, José

2008-10-01

We revisit an application developed originally using abductive Inductive Logic Programming (ILP) for modeling inhibition in metabolic networks. The example data was derived from studies of the effects of toxins on rats using Nuclear Magnetic Resonance (NMR) time-trace analysis of their biofluids together with background knowledge representing a subset of the Kyoto Encyclopedia of Genes and Genomes (KEGG). We now apply two Probabilistic ILP (PILP) approaches - abductive Stochastic Logic Programs (SLPs) and PRogramming In Statistical modeling (PRISM) to the application. Both approaches support abductive learning and probability predictions. Abductive SLPs are a PILP framework that provides possible worlds semantics to SLPs through abduction. Instead of learning logic models from non-probabilistic examples as done in ILP, the PILP approach applied in this paper is based on a general technique for introducing probability labels within a standard scientific experimental setting involving control and treated data. Our results demonstrate that the PILP approach provides a way of learning probabilistic logic models from probabilistic examples, and the PILP models learned from probabilistic examples lead to a significant decrease in error accompanied by improved insight from the learned results compared with the PILP models learned from non-probabilistic examples.

Economic evaluation of rivaroxaban in stroke prevention for patients with atrial fibrillation in Greece

PubMed Central

2014-01-01

Background To undertake an economic evaluation of rivaroxaban relative to the standard of care for stroke prevention in patients with non-valvular atrial fibrillation (AF) in Greece. Methods An existing Markov model designed to reflect the natural progression of AF patients through different health states, in the course of three month cycles, was adapted to the Greek setting. The analysis was undertaken from a payer perspective. Baseline event rates and efficacy data were obtained from the ROCKET-AF trial for rivaroxaban and vitamin-K-antagonists (VKAs). Utility values for events were based on literature. A treatment-related disutility of 0.05 was applied to the VKA arm. Costs assigned to each health state reflect the year 2013. An incremental cost effectiveness ratio (ICER) was calculated where the outcome was quality-adjusted-life year (QALY) and life-years gained. Probabilistic analysis was undertaken to deal with uncertainty. The horizon of analysis was over patient life time and both cost and outcomes were discounted at 3.5%. Results Based on safety-on-treatment data, rivaroxaban was associated with a 0.22 increment in QALYs compared to VKA. The average total lifetime cost of rivaroxaban-treated patients was €239 lower compared to VKA. Rivaroxaban was associated with additional drug acquisition cost (€4,033) and reduced monitoring cost (-€3,929). Therefore, rivaroxaban was a dominant alternative over VKA. Probabilistic analysis revealed that there is a 100% probability of rivaroxaban being cost-effective versus VKA at a willingness to pay threshold of €30,000/QALY gained. Conclusion Rivaroxaban may represent for payers a dominant option for the prevention of thromboembolic events in moderate to high risk AF patients in Greece. PMID:24512351

Development of a Microsoft Excel tool for one-parameter Rasch model of continuous items: an application to a safety attitude survey.

PubMed

Chien, Tsair-Wei; Shao, Yang; Kuo, Shu-Chun

2017-01-10

Many continuous item responses (CIRs) are encountered in healthcare settings, but no one uses item response theory's (IRT) probabilistic modeling to present graphical presentations for interpreting CIR results. A computer module that is programmed to deal with CIRs is required. To present a computer module, validate it, and verify its usefulness in dealing with CIR data, and then to apply the model to real healthcare data in order to show how the CIR that can be applied to healthcare settings with an example regarding a safety attitude survey. Using Microsoft Excel VBA (Visual Basic for Applications), we designed a computer module that minimizes the residuals and calculates model's expected scores according to person responses across items. Rasch models based on a Wright map and on KIDMAP were demonstrated to interpret results of the safety attitude survey. The author-made CIR module yielded OUTFIT mean square (MNSQ) and person measures equivalent to those yielded by professional Rasch Winsteps software. The probabilistic modeling of the CIR module provides messages that are much more valuable to users and show the CIR advantage over classic test theory. Because of advances in computer technology, healthcare users who are familiar to MS Excel can easily apply the study CIR module to deal with continuous variables to benefit comparisons of data with a logistic distribution and model fit statistics.

A decision analytic model to investigate the cost-effectiveness of poisoning prevention practices in households with young children.

PubMed

Achana, Felix; Sutton, Alex J; Kendrick, Denise; Hayes, Mike; Jones, David R; Hubbard, Stephanie J; Cooper, Nicola J

2016-08-03

Systematic reviews and a network meta-analysis show home safety education with or without the provision of safety equipment is effective in promoting poison prevention behaviours in households with children. This paper compares the cost-effectiveness of home safety interventions to promote poison prevention practices. A probabilistic decision-analytic model simulates healthcare costs and benefits for a hypothetical cohort of under 5 year olds. The model compares the cost-effectiveness of home safety education, home safety inspections, provision of free or low cost safety equipment and fitting of equipment. Analyses are conducted from a UK National Health Service and Personal Social Services perspective and expressed in 2012 prices. Education without safety inspection, provision or fitting of equipment was the most cost-effective strategy for promoting safe storage of medicines with an incremental cost-effectiveness ratio of £2888 (95 % credible interval (CrI) £1990-£5774) per poison case avoided or £41,330 (95%CrI £20,007-£91,534) per QALY gained compared with usual care. Compared to usual care, home safety interventions were not cost-effective in promoting safe storage of other household products. Education offers better value for money than more intensive but expensive strategies for preventing medicinal poisonings, but is only likely to be cost-effective at £30,000 per QALY gained for families in disadvantaged areas and for those with more than one child. There was considerable uncertainty in cost-effectiveness estimates due to paucity of evidence on model parameters. Policy makers should consider both costs and effectiveness of competing interventions to ensure efficient use of resources.

MATILDA: A Military Laser Range Safety Tool Based on Probabilistic Risk Assessment (PRA) Techniques

DTIC Science & Technology

2014-08-01

Figure 6: MATILDA Coordinate Transformations ....................................................... 22  Figure 7: Geocentric and MICS Coordinates...Target – Range Boundary Undershoot Geometry .............. 34  Figure 19: Geocentric Overshoot Geometry and Parameters...transformed into Geocentric coordinates, a Cartesian (x,y,z) coordinate system with origin at the center of the Earth and z-axis oriented towards the

A PROBABILISTIC ARSENIC EXPOSURE ASSESSMENT FOR CHILDREN WHO CONTACT CAA - TREATED PLAYSETS AND DECKS: PART 1. MODEL METHODOLOGY, VARIABILITY RESULTS, AND MODEL EVALUATION

EPA Science Inventory

Concerns have been raised regarding the safety of young children who may contact arsenic residues while playing on and around chromated copper arsenate (CCA)-treated wood playsets and decks. Although CCA registrants voluntarily canceled the production of treated wood for residen...

Application of the Probabilistic Dynamic Synthesis Method to the Analysis of a Realistic Structure

NASA Technical Reports Server (NTRS)

Brown, Andrew M.; Ferri, Aldo A.

1998-01-01

The Probabilistic Dynamic Synthesis method is a new technique for obtaining the statistics of a desired response engineering quantity for a structure with non-deterministic parameters. The method uses measured data from modal testing of the structure as the input random variables, rather than more "primitive" quantities like geometry or material variation. This modal information is much more comprehensive and easily measured than the "primitive" information. The probabilistic analysis is carried out using either response surface reliability methods or Monte Carlo simulation. A previous work verified the feasibility of the PDS method on a simple seven degree-of-freedom spring-mass system. In this paper, extensive issues involved with applying the method to a realistic three-substructure system are examined, and free and forced response analyses are performed. The results from using the method are promising, especially when the lack of alternatives for obtaining quantitative output for probabilistic structures is considered.

Probabilistic evaluation of SSME structural components

NASA Astrophysics Data System (ADS)

Rajagopal, K. R.; Newell, J. F.; Ho, H.

1991-05-01

The application is described of Composite Load Spectra (CLS) and Numerical Evaluation of Stochastic Structures Under Stress (NESSUS) family of computer codes to the probabilistic structural analysis of four Space Shuttle Main Engine (SSME) space propulsion system components. These components are subjected to environments that are influenced by many random variables. The applications consider a wide breadth of uncertainties encountered in practice, while simultaneously covering a wide area of structural mechanics. This has been done consistent with the primary design requirement for each component. The probabilistic application studies are discussed using finite element models that have been typically used in the past in deterministic analysis studies.

Reliability and risk assessment of structures

NASA Technical Reports Server (NTRS)

Chamis, C. C.

1991-01-01

Development of reliability and risk assessment of structural components and structures is a major activity at Lewis Research Center. It consists of five program elements: (1) probabilistic loads; (2) probabilistic finite element analysis; (3) probabilistic material behavior; (4) assessment of reliability and risk; and (5) probabilistic structural performance evaluation. Recent progress includes: (1) the evaluation of the various uncertainties in terms of cumulative distribution functions for various structural response variables based on known or assumed uncertainties in primitive structural variables; (2) evaluation of the failure probability; (3) reliability and risk-cost assessment; and (4) an outline of an emerging approach for eventual certification of man-rated structures by computational methods. Collectively, the results demonstrate that the structural durability/reliability of man-rated structural components and structures can be effectively evaluated by using formal probabilistic methods.

Probabilistic Analysis and Design of a Raked Wing Tip for a Commercial Transport

NASA Technical Reports Server (NTRS)

Mason Brian H.; Chen, Tzi-Kang; Padula, Sharon L.; Ransom, Jonathan B.; Stroud, W. Jefferson

2008-01-01

An approach for conducting reliability-based design and optimization (RBDO) of a Boeing 767 raked wing tip (RWT) is presented. The goal is to evaluate the benefits of RBDO for design of an aircraft substructure. A finite-element (FE) model that includes eight critical static load cases is used to evaluate the response of the wing tip. Thirteen design variables that describe the thickness of the composite skins and stiffeners are selected to minimize the weight of the wing tip. A strain-based margin of safety is used to evaluate the performance of the structure. The randomness in the load scale factor and in the strain limits is considered. Of the 13 variables, the wing-tip design was controlled primarily by the thickness of the thickest plies in the upper skins. The report includes an analysis of the optimization results and recommendations for future reliability-based studies.

Probabilistic Structural Evaluation of Uncertainties in Radiator Sandwich Panel Design

NASA Technical Reports Server (NTRS)

Kuguoglu, Latife; Ludwiczak, Damian

2006-01-01

The Jupiter Icy Moons Orbiter (JIMO) Space System is part of the NASA's Prometheus Program. As part of the JIMO engineering team at NASA Glenn Research Center, the structural design of the JIMO Heat Rejection Subsystem (HRS) is evaluated. An initial goal of this study was to perform sensitivity analyses to determine the relative importance of the input variables on the structural responses of the radiator panel. The desire was to let the sensitivity analysis information identify the important parameters. The probabilistic analysis methods illustrated here support this objective. The probabilistic structural performance evaluation of a HRS radiator sandwich panel was performed. The radiator panel structural performance was assessed in the presence of uncertainties in the loading, fabrication process variables, and material properties. The stress and displacement contours of the deterministic structural analysis at mean probability was performed and results presented. It is followed by a probabilistic evaluation to determine the effect of the primitive variables on the radiator panel structural performance. Based on uncertainties in material properties, structural geometry and loading, the results of the displacement and stress analysis are used as an input file for the probabilistic analysis of the panel. The sensitivity of the structural responses, such as maximum displacement and maximum tensile and compressive stresses of the facesheet in x and y directions and maximum VonMises stresses of the tube, to the loading and design variables is determined under the boundary condition where all edges of the radiator panel are pinned. Based on this study, design critical material and geometric parameters of the considered sandwich panel are identified.

Correlation of Risk Analysis Method Results with Numerical and Limit Equilibrium Methods in Overall Slope Stability Analysis of Southern Wall of Chadormalu Iron Open Pit Mine-Iran / Korelacja wyników analizy ryzyka z wynikami obliczeń numerycznych oraz wynikami uzyskanymi w oparciu o metodę równowagi granicznej zastosowanych do badania stabilności wyrobiska pochyłego na południowej ścianie odkrywkowej kopalni rud żelaza w chadormalu w Iranie

NASA Astrophysics Data System (ADS)

Ahangari, Kaveh; Paji, Arman Gholinezhad; Behdani, Alireza Siami

2013-06-01

Slope stability analysis is one of the most important factors in designing open pit mines. Therefore an optimal slope design that supports both aspects of economy and safety is very significant. There are many different methods in slope stability analysis including empirical, limit equilibrium, block theory, numerical, and probabilistic methods. In this study, to analyze the overall slope stability of southern wall of Chadormalu iron open pit mine three numerical, limit equilibrium and probabilistic methods have been used. Software and methods that is used for analytical investigation in this study are FLAC software for numerical analysis, SLIDE software and circuit failure chart for limit equilibrium analysis and qualitative fault tree and semi-quantitative risk matrix for probabilistic analysis. The results of all above mentioned methods, was a circular failure occurrence in Metasomatite rock zone between 1405 to 1525 m levels. The main factors of failure occurrence in this range were heavily jointing and existing of faults. Safety factors resulted from numerical method; Circular chart method and SLIDE software are 1.16, 1.25 and 1.27 respectively. Regarding instability and safety factors in Metasomatite rock zone, in order to stabilize the given zone, some considerations such as bench angle and height reduction should be planned. In results of risk matrix method this zone was mentioned too as a high risk zone that numerical and limit equilibrium methods confirmed this. Badanie stabilności wyrobiska pochyłego jest jednym z najważniejszych czynników uwzględnianych przy projektowaniu kopalni odkrywkowych. Optymalne zaprojektowanie wyrobiska pochyłego z uwzględnieniem czynników ekonomicznych oraz bezpieczeństwa jest niezmiernie ważne. Istnieje wiele metod badania stabilności wyrobiska pochyłego, między innymi metody empiryczne, metoda równowagi granicznej, teoria bloków oraz metody numeryczne i probabilistyczne. W pracy tej omówiono zastosowanie trzech spośród tych metod: metody numerycznej, równowagi granicznej oraz metody probabilistycznej, do analizy stabilności wyrobiska pochyłego na południowej ścianie kopalni rud żelaza w Chadormalu w Iranie. Oprogramowanie wykorzystane w badaniach analitycznych to pakiet FLAK przy metodzie numerycznej, oprogramowanie SLIDE oraz wykresy kołowe przy metodzie równowagi granicznej oraz jakościowe drzewa określające występowanie uskoków i pół-jakościowe macierze ryzyka przy metodzie probabilistycznej. Wyniki uzyskane w oparciu o trzy wyżej wymienione metody wykazały wystąpienie zawalenia się skał metasomatycznych na poziomie od 1405 do 1525 m. Głównymi czynnikami warunkującymi zawalenie się skał w tym regionie była obecność licznych pęknięć oraz uskoków. Wskaźniki bezpieczeństwa uzyskane przy pomocy metod numerycznych, wykresu kołowego oraz oprogramowanie SLIDE wyniosły kolejno: 1.16, 1.25, 1.27. W odniesieniu do niestabilności w rejonie skał metasomatycznych, aby uczynić tę strefę bardziej stabilną należy uwzględnić takie czynniki jak kąt nachylenia ławy oraz obniżenie wysokości. Analiza przeprowadzona w oparciu o macierze ryzyka wykazała, że strefa ta jest strefą wysokiego ryzyka, zaś wyniki analizy numerycznej oraz wyników uzyskanych przy pomocy metody równowagi granicznej w pełni ten wniosek potwierdziły.

Probabilistic Based Modeling and Simulation Assessment

DTIC Science & Technology

2010-06-01

different crash and blast scenarios. With the integration of the high fidelity neck and head model, a methodology to calculate the probability of injury...variability, correlation, and multiple (often competing) failure metrics. Important scenarios include vehicular collisions, blast /fragment impact, and...first area of focus is to develop a methodology to integrate probabilistic analysis into finite element analysis of vehicle collisions and blast . The

Research on probabilistic information processing

NASA Technical Reports Server (NTRS)

Edwards, W.

1973-01-01

The work accomplished on probabilistic information processing (PIP) is reported. The research proposals and decision analysis are discussed along with the results of research on MSC setting, multiattribute utilities, and Bayesian research. Abstracts of reports concerning the PIP research are included.

Application of Probabilistic Analysis to Aircraft Impact Dynamics

NASA Technical Reports Server (NTRS)

Lyle, Karen H.; Padula, Sharon L.; Stockwell, Alan E.

2003-01-01

Full-scale aircraft crash simulations performed with nonlinear, transient dynamic, finite element codes can incorporate structural complexities such as: geometrically accurate models; human occupant models; and advanced material models to include nonlinear stressstrain behaviors, laminated composites, and material failure. Validation of these crash simulations is difficult due to a lack of sufficient information to adequately determine the uncertainty in the experimental data and the appropriateness of modeling assumptions. This paper evaluates probabilistic approaches to quantify the uncertainty in the simulated responses. Several criteria are used to determine that a response surface method is the most appropriate probabilistic approach. The work is extended to compare optimization results with and without probabilistic constraints.

HyRAM V1.0 User Guide

DOE Office of Scientific and Technical Information (OSTI.GOV)

Groth, Katrina M.; Zumwalt, Hannah Ruth; Clark, Andrew Jordan

2016-03-01

Hydrogen Risk Assessment Models (HyRAM) is a prototype software toolkit that integrates data and methods relevant to assessing the safety of hydrogen fueling and storage infrastructure. The HyRAM toolkit integrates deterministic and probabilistic models for quantifying accident scenarios, predicting physical effects, and characterizing the impact of hydrogen hazards, including thermal effects from jet fires and thermal pressure effects from deflagration. HyRAM version 1.0 incorporates generic probabilities for equipment failures for nine types of components, and probabilistic models for the impact of heat flux on humans and structures, with computationally and experimentally validated models of various aspects of gaseous hydrogen releasemore » and flame physics. This document provides an example of how to use HyRAM to conduct analysis of a fueling facility. This document will guide users through the software and how to enter and edit certain inputs that are specific to the user-defined facility. Description of the methodology and models contained in HyRAM is provided in [1]. This User’s Guide is intended to capture the main features of HyRAM version 1.0 (any HyRAM version numbered as 1.0.X.XXX). This user guide was created with HyRAM 1.0.1.798. Due to ongoing software development activities, newer versions of HyRAM may have differences from this guide.« less

Artificial Neural Network for Probabilistic Feature Recognition in Liquid Chromatography Coupled to High-Resolution Mass Spectrometry.

PubMed

Woldegebriel, Michael; Derks, Eduard

2017-01-17

In this work, a novel probabilistic untargeted feature detection algorithm for liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) using artificial neural network (ANN) is presented. The feature detection process is approached as a pattern recognition problem, and thus, ANN was utilized as an efficient feature recognition tool. Unlike most existing feature detection algorithms, with this approach, any suspected chromatographic profile (i.e., shape of a peak) can easily be incorporated by training the network, avoiding the need to perform computationally expensive regression methods with specific mathematical models. In addition, with this method, we have shown that the high-resolution raw data can be fully utilized without applying any arbitrary thresholds or data reduction, therefore improving the sensitivity of the method for compound identification purposes. Furthermore, opposed to existing deterministic (binary) approaches, this method rather estimates the probability of a feature being present/absent at a given point of interest, thus giving chance for all data points to be propagated down the data analysis pipeline, weighed with their probability. The algorithm was tested with data sets generated from spiked samples in forensic and food safety context and has shown promising results by detecting features for all compounds in a computationally reasonable time.

Probabilistic modeling of the fate of Listeria monocytogenes in diced bacon during the manufacturing process.

PubMed

Billoir, Elise; Denis, Jean-Baptiste; Cammeau, Natalie; Cornu, Marie; Zuliani, Veronique

2011-02-01

To assess the impact of the manufacturing process on the fate of Listeria monocytogenes, we built a generic probabilistic model intended to simulate the successive steps in the process. Contamination evolution was modeled in the appropriate units (breasts, dice, and then packaging units through the successive steps in the process). To calibrate the model, parameter values were estimated from industrial data, from the literature, and based on expert opinion. By means of simulations, the model was explored using a baseline calibration and alternative scenarios, in order to assess the impact of changes in the process and of accidental events. The results are reported as contamination distributions and as the probability that the product will be acceptable with regards to the European regulatory safety criterion. Our results are consistent with data provided by industrial partners and highlight that tumbling is a key step for the distribution of the contamination at the end of the process. Process chain models could provide an important added value for risk assessment models that basically consider only the outputs of the process in their risk mitigation strategies. Moreover, a model calibrated to correspond to a specific plant could be used to optimize surveillance. © 2010 Society for Risk Analysis.

Probabilistic and structural reliability analysis of laminated composite structures based on the IPACS code

NASA Technical Reports Server (NTRS)

Sobel, Larry; Buttitta, Claudio; Suarez, James

1993-01-01

Probabilistic predictions based on the Integrated Probabilistic Assessment of Composite Structures (IPACS) code are presented for the material and structural response of unnotched and notched, 1M6/3501-6 Gr/Ep laminates. Comparisons of predicted and measured modulus and strength distributions are given for unnotched unidirectional, cross-ply, and quasi-isotropic laminates. The predicted modulus distributions were found to correlate well with the test results for all three unnotched laminates. Correlations of strength distributions for the unnotched laminates are judged good for the unidirectional laminate and fair for the cross-ply laminate, whereas the strength correlation for the quasi-isotropic laminate is deficient because IPACS did not yet have a progressive failure capability. The paper also presents probabilistic and structural reliability analysis predictions for the strain concentration factor (SCF) for an open-hole, quasi-isotropic laminate subjected to longitudinal tension. A special procedure was developed to adapt IPACS for the structural reliability analysis. The reliability results show the importance of identifying the most significant random variables upon which the SCF depends, and of having accurate scatter values for these variables.

System Theoretic Frameworks for Mitigating Risk Complexity in the Nuclear Fuel Cycle

DOE Office of Scientific and Technical Information (OSTI.GOV)

Williams, Adam David; Mohagheghi, Amir H.; Cohn, Brian

In response to the expansion of nuclear fuel cycle (NFC) activities -- and the associated suite of risks -- around the world, this project evaluated systems-based solutions for managing such risk complexity in multimodal and multi-jurisdictional international spent nuclear fuel (SNF) transportation. By better understanding systemic risks in SNF transportation, developing SNF transportation risk assessment frameworks, and evaluating these systems-based risk assessment frameworks, this research illustrated interdependency between safety, security, and safeguards risks is inherent in NFC activities and can go unidentified when each "S" is independently evaluated. Two novel system-theoretic analysis techniques -- dynamic probabilistic risk assessment (DPRA) andmore » system-theoretic process analysis (STPA) -- provide integrated "3S" analysis to address these interdependencies and the research results suggest a need -- and provide a way -- to reprioritize United States engagement efforts to reduce global nuclear risks. Lastly, this research identifies areas where Sandia National Laboratories can spearhead technical advances to reduce global nuclear dangers.« less

Risk management at the stage of design of high-rise construction facilities

NASA Astrophysics Data System (ADS)

Politi, Violetta

2018-03-01

This paper describes the assessment of the probabilistic risk of an accident formed in the process of designing a technically complex facility. It considers values of conditional probabilities of the compliance of load-bearing structures with safety requirements, provides an approximate list of significant errors of the designer and analyzes the relationship between the degree of compliance and the level of danger of errors. It describes and proposes for implementation the regulated procedures related to the assessment of the safety level of constructive solutions and the reliability of the construction process participants.

Analysis of crash proportion by vehicle type at traffic analysis zone level: A mixed fractional split multinomial logit modeling approach with spatial effects.

PubMed

Lee, Jaeyoung; Yasmin, Shamsunnahar; Eluru, Naveen; Abdel-Aty, Mohamed; Cai, Qing

2018-02-01

In traffic safety literature, crash frequency variables are analyzed using univariate count models or multivariate count models. In this study, we propose an alternative approach to modeling multiple crash frequency dependent variables. Instead of modeling the frequency of crashes we propose to analyze the proportion of crashes by vehicle type. A flexible mixed multinomial logit fractional split model is employed for analyzing the proportions of crashes by vehicle type at the macro-level. In this model, the proportion allocated to an alternative is probabilistically determined based on the alternative propensity as well as the propensity of all other alternatives. Thus, exogenous variables directly affect all alternatives. The approach is well suited to accommodate for large number of alternatives without a sizable increase in computational burden. The model was estimated using crash data at Traffic Analysis Zone (TAZ) level from Florida. The modeling results clearly illustrate the applicability of the proposed framework for crash proportion analysis. Further, the Excess Predicted Proportion (EPP)-a screening performance measure analogous to Highway Safety Manual (HSM), Excess Predicted Average Crash Frequency is proposed for hot zone identification. Using EPP, a statewide screening exercise by the various vehicle types considered in our analysis was undertaken. The screening results revealed that the spatial pattern of hot zones is substantially different across the various vehicle types considered. Copyright © 2017 Elsevier Ltd. All rights reserved.

Ares I Static Tests Design

NASA Technical Reports Server (NTRS)

Carson, William; Lindemuth, Kathleen; Mich, John; White, K. Preston; Parker, Peter A.

2009-01-01

Probabilistic engineering design enhances safety and reduces costs by incorporating risk assessment directly into the design process. In this paper, we assess the format of the quantitative metrics for the vehicle which will replace the Space Shuttle, the Ares I rocket. Specifically, we address the metrics for in-flight measurement error in the vector position of the motor nozzle, dictated by limits on guidance, navigation, and control systems. Analyses include the propagation of error from measured to derived parameters, the time-series of dwell points for the duty cycle during static tests, and commanded versus achieved yaw angle during tests. Based on these analyses, we recommend a probabilistic template for specifying the maximum error in angular displacement and radial offset for the nozzle-position vector. Criteria for evaluating individual tests and risky decisions also are developed.

Probabilistic finite elements for fracture and fatigue analysis

NASA Technical Reports Server (NTRS)

Liu, W. K.; Belytschko, T.; Lawrence, M.; Besterfield, G. H.

1989-01-01

The fusion of the probabilistic finite element method (PFEM) and reliability analysis for probabilistic fracture mechanics (PFM) is presented. A comprehensive method for determining the probability of fatigue failure for curved crack growth was developed. The criterion for failure or performance function is stated as: the fatigue life of a component must exceed the service life of the component; otherwise failure will occur. An enriched element that has the near-crack-tip singular strain field embedded in the element is used to formulate the equilibrium equation and solve for the stress intensity factors at the crack-tip. Performance and accuracy of the method is demonstrated on a classical mode 1 fatigue problem.

Probabilistic Scenario-based Seismic Risk Analysis for Critical Infrastructures Method and Application for a Nuclear Power Plant

NASA Astrophysics Data System (ADS)

Klügel, J.

2006-12-01

Deterministic scenario-based seismic hazard analysis has a long tradition in earthquake engineering for developing the design basis of critical infrastructures like dams, transport infrastructures, chemical plants and nuclear power plants. For many applications besides of the design of infrastructures it is of interest to assess the efficiency of the design measures taken. These applications require a method allowing to perform a meaningful quantitative risk analysis. A new method for a probabilistic scenario-based seismic risk analysis has been developed based on a probabilistic extension of proven deterministic methods like the MCE- methodology. The input data required for the method are entirely based on the information which is necessary to perform any meaningful seismic hazard analysis. The method is based on the probabilistic risk analysis approach common for applications in nuclear technology developed originally by Kaplan & Garrick (1981). It is based (1) on a classification of earthquake events into different size classes (by magnitude), (2) the evaluation of the frequency of occurrence of events, assigned to the different classes (frequency of initiating events, (3) the development of bounding critical scenarios assigned to each class based on the solution of an optimization problem and (4) in the evaluation of the conditional probability of exceedance of critical design parameters (vulnerability analysis). The advantage of the method in comparison with traditional PSHA consists in (1) its flexibility, allowing to use different probabilistic models for earthquake occurrence as well as to incorporate advanced physical models into the analysis, (2) in the mathematically consistent treatment of uncertainties, and (3) in the explicit consideration of the lifetime of the critical structure as a criterion to formulate different risk goals. The method was applied for the evaluation of the risk of production interruption losses of a nuclear power plant during its residual lifetime.

Findings of a review of spacecraft fire safety needs

NASA Technical Reports Server (NTRS)

Apostolakis, G. E.; Catton, I.; Paulos, T.; Paxton, K.; Jones, S.

1992-01-01

Discussions from a workshop to guide UCLA and NASA investigators on the state of knowledge and perceived needs in spacecraft fire safety and its risk management are reviewed, for an introduction to an analytical and experimental project in this field. The report summarizes the workshop discussions and includes the visual aids used in the presentations. Probabilistic Safety Assessment (PSA) methods, which are currently not used, would be of great value to the designs and operation of future human-crew spacecraft. Key points in the discussions were the importance of understanding and testing smoldering as a likely fire scenario in space and the need for smoke damage modeling, since many fire-risk models ignore this mechanism and consider only heat damage.

Design of Critical Components

NASA Technical Reports Server (NTRS)

Hendricks, Robert C.; Zaretsky, Erwin V.

2001-01-01

Critical component design is based on minimizing product failures that results in loss of life. Potential catastrophic failures are reduced to secondary failures where components removed for cause or operating time in the system. Issues of liability and cost of component removal become of paramount importance. Deterministic design with factors of safety and probabilistic design address but lack the essential characteristics for the design of critical components. In deterministic design and fabrication there are heuristic rules and safety factors developed over time for large sets of structural/material components. These factors did not come without cost. Many designs failed and many rules (codes) have standing committees to oversee their proper usage and enforcement. In probabilistic design, not only are failures a given, the failures are calculated; an element of risk is assumed based on empirical failure data for large classes of component operations. Failure of a class of components can be predicted, yet one can not predict when a specific component will fail. The analogy is to the life insurance industry where very careful statistics are book-kept on classes of individuals. For a specific class, life span can be predicted within statistical limits, yet life-span of a specific element of that class can not be predicted.

Towards Measurement of Confidence in Safety Cases

NASA Technical Reports Server (NTRS)

Denney, Ewen; Paim Ganesh J.; Habli, Ibrahim

2011-01-01

Arguments in safety cases are predominantly qualitative. This is partly attributed to the lack of sufficient design and operational data necessary to measure the achievement of high-dependability targets, particularly for safety-critical functions implemented in software. The subjective nature of many forms of evidence, such as expert judgment and process maturity, also contributes to the overwhelming dependence on qualitative arguments. However, where data for quantitative measurements is systematically collected, quantitative arguments provide far more benefits over qualitative arguments, in assessing confidence in the safety case. In this paper, we propose a basis for developing and evaluating integrated qualitative and quantitative safety arguments based on the Goal Structuring Notation (GSN) and Bayesian Networks (BN). The approach we propose identifies structures within GSN-based arguments where uncertainties can be quantified. BN are then used to provide a means to reason about confidence in a probabilistic way. We illustrate our approach using a fragment of a safety case for an unmanned aerial system and conclude with some preliminary observations

Managing Uncertainty in Water Infrastructure Design Using Info-gap Robustness

NASA Astrophysics Data System (ADS)

Irias, X.; Cicala, D.

2013-12-01

Info-gap theory, a tool for managing deep uncertainty, can be of tremendous value for design of water systems in areas of high seismic risk. Maintaining reliable water service in those areas is subject to significant uncertainties including uncertainty of seismic loading, unknown seismic performance of infrastructure, uncertain costs of innovative seismic-resistant construction, unknown costs to repair seismic damage, unknown societal impacts from downtime, and more. Practically every major earthquake that strikes a population center reveals additional knowledge gaps. In situations of such deep uncertainty, info-gap can offer advantages over traditional approaches, whether deterministic approaches that use empirical safety factors to address the uncertainties involved, or probabilistic methods that attempt to characterize various stochastic properties and target a compromise between cost and reliability. The reason is that in situations of deep uncertainty, it may not be clear what safety factor would be reasonable, or even if any safety factor is sufficient to address the uncertainties, and we may lack data to characterize the situation probabilistically. Info-gap is a tool that recognizes up front that our best projection of the future may be wrong. Thus, rather than seeking a solution that is optimal for that projection, info-gap seeks a solution that works reasonably well for all plausible conditions. In other words, info-gap seeks solutions that are robust in the face of uncertainty. Info-gap has been used successfully across a wide range of disciplines including climate change science, project management, and structural design. EBMUD is currently using info-gap to help it gain insight into possible solutions for providing reliable water service to an island community within its service area. The island, containing about 75,000 customers, is particularly vulnerable to water supply disruption from earthquakes, since it has negligible water storage and is entirely dependent on four potentially fragile water transmission mains for its day-to-day water supply. Using info-gap analysis, EBMUD is evaluating competing strategies for providing water supply to the island, for example submarine pipelines versus tunnels. The analysis considers not only the likely or 'average' results for each strategy, but also the worst-case performance of each strategy under varying levels of uncertainty. This analysis is improving the quality of the planning process, since it can identify strategies that ensure minimal disruption of water supply following a major earthquake, even if the earthquake and resulting damage fail to conform to our expectations. Results to date are presented, including a discussion of how info-gap analysis complements existing tools for comparing alternative strategies, and how info-gap improves our ability to quantify our tolerance for uncertainty.

Climatological Observations for Maritime Prediction and Analysis Support Service (COMPASS)

NASA Astrophysics Data System (ADS)

OConnor, A.; Kirtman, B. P.; Harrison, S.; Gorman, J.

2016-02-01

Current US Navy forecasting systems cannot easily incorporate extended-range forecasts that can improve mission readiness and effectiveness; ensure safety; and reduce cost, labor, and resource requirements. If Navy operational planners had systems that incorporated these forecasts, they could plan missions using more reliable and longer-term weather and climate predictions. Further, using multi-model forecast ensembles instead of single forecasts would produce higher predictive performance. Extended-range multi-model forecast ensembles, such as those available in the North American Multi-Model Ensemble (NMME), are ideal for system integration because of their high skill predictions; however, even higher skill predictions can be produced if forecast model ensembles are combined correctly. While many methods for weighting models exist, the best method in a given environment requires expert knowledge of the models and combination methods.We present an innovative approach that uses machine learning to combine extended-range predictions from multi-model forecast ensembles and generate a probabilistic forecast for any region of the globe up to 12 months in advance. Our machine-learning approach uses 30 years of hindcast predictions to learn patterns of forecast model successes and failures. Each model is assigned a weight for each environmental condition, 100 km2 region, and day given any expected environmental information. These weights are then applied to the respective predictions for the region and time of interest to effectively stitch together a single, coherent probabilistic forecast. Our experimental results demonstrate the benefits of our approach to produce extended-range probabilistic forecasts for regions and time periods of interest that are superior, in terms of skill, to individual NMME forecast models and commonly weighted models. The probabilistic forecast leverages the strengths of three NMME forecast models to predict environmental conditions for an area spanning from San Diego, CA to Honolulu, HI, seven months in-advance. Key findings include: weighted combinations of models are strictly better than individual models; machine-learned combinations are especially better; and forecasts produced using our approach have the highest rank probability skill score most often.

RAVEN User Manual

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mandelli, Diego; Rabiti, Cristian; Cogliati, Joshua Joseph

2017-03-01

RAVEN is a generic software framework to perform parametric and probabilistic analy- sis based on the response of complex system codes. The initial development was aimed to provide dynamic risk analysis capabilities to the Thermo-Hydraulic code RELAP-7, currently under development at the Idaho National Laboratory (INL). Although the initial goal has been fully accomplished, RAVEN is now a multi-purpose probabilistic and uncer- tainty quantification platform, capable to agnostically communicate with any system code. This agnosticism includes providing Application Programming Interfaces (APIs). These APIs are used to allow RAVEN to interact with any code as long as all the parameters thatmore » need to be perturbed are accessible by inputs files or via python interfaces. RAVEN is capable of investigating the system response, and investigating the input space using Monte Carlo, Grid, or Latin Hyper Cube sampling schemes, but its strength is focused to- ward system feature discovery, such as limit surfaces, separating regions of the input space leading to system failure, using dynamic supervised learning techniques. The development of RAVEN has started in 2012, when, within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the need to provide a modern risk evaluation framework became stronger. RAVEN principal assignment is to provide the necessary software and algorithms in order to employ the concept developed by the Risk Informed Safety Margin Characterization (RISMC) program. RISMC is one of the pathways defined within the Light Water Reactor Sustainability (LWRS) program. In the RISMC approach, the goal is not just the individuation of the frequency of an event potentially leading to a system failure, but the closeness (or not) to key safety-related events. Hence, the approach is in- terested in identifying and increasing the safety margins related to those events. A safety margin is a numerical value quantifying the probability that a safety metric (e.g. for an important process such as peak pressure in a pipe) is exceeded under certain conditions. The initial development of RAVEN has been focused on providing dynamic risk assess- ment capability to RELAP-7, currently under develop-ment at the INL and, likely, future replacement of the RELAP5-3D code. Most the capabilities that have been implemented having RELAP-7 as principal focus are easily deployable for other system codes. For this reason, several side activates are currently ongoing for coupling RAVEN with soft- ware such as RELAP5-3D, etc. The aim of this document is the explaination of the input requirements, focalizing on the input structure.« less

The Study of the Relationship between Probabilistic Design and Axiomatic Design Methodology. Volume 1

NASA Technical Reports Server (NTRS)

Onwubiko, Chinyere; Onyebueke, Landon

1996-01-01

This program report is the final report covering all the work done on this project. The goal of this project is technology transfer of methodologies to improve design process. The specific objectives are: 1. To learn and understand the Probabilistic design analysis using NESSUS. 2. To assign Design Projects to either undergraduate or graduate students on the application of NESSUS. 3. To integrate the application of NESSUS into some selected senior level courses in Civil and Mechanical Engineering curricula. 4. To develop courseware in Probabilistic Design methodology to be included in a graduate level Design Methodology course. 5. To study the relationship between the Probabilistic design methodology and Axiomatic design methodology.

Probabilistic structural analysis to quantify uncertainties associated with turbopump blades

NASA Technical Reports Server (NTRS)

Nagpal, Vinod K.; Rubinstein, Robert; Chamis, Christos C.

1988-01-01

A probabilistic study of turbopump blades has been in progress at NASA Lewis Research Center for over the last two years. The objectives of this study are to evaluate the effects of uncertainties in geometry and material properties on the structural response of the turbopump blades to evaluate the tolerance limits on the design. A methodology based on probabilistic approach was developed to quantify the effects of the random uncertainties. The results indicate that only the variations in geometry have significant effects.

Cross-comparison of three surrogate safety methods to diagnose cyclist safety problems at intersections in Norway.

PubMed

Laureshyn, Aliaksei; Goede, Maartje de; Saunier, Nicolas; Fyhri, Aslak

2017-08-01

Relying on accident records as the main data source for studying cyclists' safety has many drawbacks, such as high degree of under-reporting, the lack of accident details and particularly of information about the interaction processes that led to the accident. It is also an ethical problem as one has to wait for accidents to happen in order to make a statement about cyclists' (un-)safety. In this perspective, the use of surrogate safety measures based on actual observations in traffic is very promising. In this study we used video data from three intersections in Norway that were all independently analysed using three methods: the Swedish traffic conflict technique (Swedish TCT), the Dutch conflict technique (DOCTOR) and the probabilistic surrogate measures of safety (PSMS) technique developed in Canada. The first two methods are based on manual detection and counting of critical events in traffic (traffic conflicts), while the third considers probabilities of multiple trajectories for each interaction and delivers a density map of potential collision points per site. Due to extensive use of microscopic data, PSMS technique relies heavily on automated tracking of the road users in video. Across the three sites, the methods show similarities or are at least "compatible" with the accident records. The two conflict techniques agree quite well for the number, type and location of conflicts, but some differences with no obvious explanation are also found. PSMS reports many more safety-relevant interactions including less severe events. The location of the potential collision points is compatible with what the conflict techniques suggest, but the possibly significant share of false alarms due to inaccurate trajectories extracted from video complicates the comparison. The tested techniques still require enhancement, with respect to better adjustment to analysis of the situations involving cyclists (and vulnerable road users in general) and further validation. However, we believe this to be a future direction for the road safety analysis as the number of accidents is constantly decreasing and the quality of accident data does not seem to improve. Copyright © 2016 Elsevier Ltd. All rights reserved.

Probabilistic structural analysis of space propulsion system LOX post

NASA Technical Reports Server (NTRS)

Newell, J. F.; Rajagopal, K. R.; Ho, H. W.; Cunniff, J. M.

1990-01-01

The probabilistic structural analysis program NESSUS (Numerical Evaluation of Stochastic Structures Under Stress; Cruse et al., 1988) is applied to characterize the dynamic loading and response of the Space Shuttle main engine (SSME) LOX post. The design and operation of the SSME are reviewed; the LOX post structure is described; and particular attention is given to the generation of composite load spectra, the finite-element model of the LOX post, and the steps in the NESSUS structural analysis. The results are presented in extensive tables and graphs, and it is shown that NESSUS correctly predicts the structural effects of changes in the temperature loading. The probabilistic approach also facilitates (1) damage assessments for a given failure model (based on gas temperature, heat-shield gap, and material properties) and (2) correlation of the gas temperature with operational parameters such as engine thrust.

Probabilistic Analysis of Gas Turbine Field Performance

NASA Technical Reports Server (NTRS)

Gorla, Rama S. R.; Pai, Shantaram S.; Rusick, Jeffrey J.

2002-01-01

A gas turbine thermodynamic cycle was computationally simulated and probabilistically evaluated in view of the several uncertainties in the performance parameters, which are indices of gas turbine health. Cumulative distribution functions and sensitivity factors were computed for the overall thermal efficiency and net specific power output due to the thermodynamic random variables. These results can be used to quickly identify the most critical design variables in order to optimize the design, enhance performance, increase system availability and make it cost effective. The analysis leads to the selection of the appropriate measurements to be used in the gas turbine health determination and to the identification of both the most critical measurements and parameters. Probabilistic analysis aims at unifying and improving the control and health monitoring of gas turbine aero-engines by increasing the quality and quantity of information available about the engine's health and performance.

On-Line Safe Flight Envelope Determination for Impaired Aircraft

NASA Technical Reports Server (NTRS)

Lombaerts, Thomas; Schuet, Stefan; Acosta, Diana; Kaneshige, John

2015-01-01

The design and simulation of an on-line algorithm which estimates the safe maneuvering envelope of aircraft is discussed in this paper. The trim envelope is estimated using probabilistic methods and efficient high-fidelity model based computations of attainable equilibrium sets. From this trim envelope, a robust reachability analysis provides the maneuverability limitations of the aircraft through an optimal control formulation. Both envelope limits are presented to the flight crew on the primary flight display. In the results section, scenarios are considered where this adaptive algorithm is capable of computing online changes to the maneuvering envelope due to impairment. Furthermore, corresponding updates to display features on the primary flight display are provided to potentially inform the flight crew of safety critical envelope alterations caused by the impairment.

Long-Term Marine Traffic Monitoring for Environmental Safety in the Aegean Sea

NASA Astrophysics Data System (ADS)

Giannakopoulos, T.; Gyftakis, S.; Charou, E.; Perantonis, S.; Nivolianitou, Z.; Koromila, I.; Makrygiorgos, A.

2015-04-01

The Aegean Sea is characterized by an extremely high marine safety risk, mainly due to the significant increase of the traffic of tankers from and to the Black Sea that pass through narrow straits formed by the 1600 Greek islands. Reducing the risk of a ship accident is therefore vital to all socio-economic and environmental sectors. This paper presents an online long-term marine traffic monitoring work-flow that focuses on extracting aggregated vessel risks using spatiotemporal analysis of multilayer information: vessel trajectories, vessel data, meteorological data, bathymetric / hydrographic data as well as information regarding environmentally important areas (e.g. protected high-risk areas, etc.). A web interface that enables user-friendly spatiotemporal queries is implemented at the frontend, while a series of data mining functionalities extracts aggregated statistics regarding: (a) marine risks and accident probabilities for particular areas (b) trajectories clustering information (c) general marine statistics (cargo types, etc.) and (d) correlation between spatial environmental importance and marine traffic risk. Towards this end, a set of data clustering and probabilistic graphical modelling techniques has been adopted.

Probabilistic wind/tornado/missile analyses for hazard and fragility evaluations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Park, Y.J.; Reich, M.

Detailed analysis procedures and examples are presented for the probabilistic evaluation of hazard and fragility against high wind, tornado, and tornado-generated missiles. In the tornado hazard analysis, existing risk models are modified to incorporate various uncertainties including modeling errors. A significant feature of this paper is the detailed description of the Monte-Carlo simulation analyses of tornado-generated missiles. A simulation procedure, which includes the wind field modeling, missile injection, solution of flight equations, and missile impact analysis, is described with application examples.

Costing the satellite power system

NASA Technical Reports Server (NTRS)

Hazelrigg, G. A., Jr.

1978-01-01

The paper presents a methodology for satellite power system costing, places approximate limits on the accuracy possible in cost estimates made at this time, and outlines the use of probabilistic cost information in support of the decision-making process. Reasons for using probabilistic costing or risk analysis procedures instead of standard deterministic costing procedures are considered. Components of cost, costing estimating relationships, grass roots costing, and risk analysis are discussed. Risk analysis using a Monte Carlo simulation model is used to estimate future costs.

76 FR 28102 - Notice of Issuance of Regulatory Guide

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-13

..., Probabilistic Risk Assessment Branch, Division of Risk Analysis, Office of Nuclear Regulatory Research, U.S... approaches and methods (whether quantitative or qualitative, deterministic or probabilistic), data, and... uses in evaluating specific problems or postulated accidents, and data that the staff needs in its...

Probability from a Socio-Cultural Perspective

ERIC Educational Resources Information Center

Sharma, Sashi

2016-01-01

There exists considerable and rich literature on students' misconceptions about probability; less attention has been paid to the development of students' probabilistic thinking in the classroom. Grounded in an analysis of the literature, this article offers a lesson sequence for developing students' probabilistic understanding. In particular, a…

Probabilistic Exposure Analysis for Chemical Risk Characterization

PubMed Central

Bogen, Kenneth T.; Cullen, Alison C.; Frey, H. Christopher; Price, Paul S.

2009-01-01

This paper summarizes the state of the science of probabilistic exposure assessment (PEA) as applied to chemical risk characterization. Current probabilistic risk analysis methods applied to PEA are reviewed. PEA within the context of risk-based decision making is discussed, including probabilistic treatment of related uncertainty, interindividual heterogeneity, and other sources of variability. Key examples of recent experience gained in assessing human exposures to chemicals in the environment, and other applications to chemical risk characterization and assessment, are presented. It is concluded that, although improvements continue to be made, existing methods suffice for effective application of PEA to support quantitative analyses of the risk of chemically induced toxicity that play an increasing role in key decision-making objectives involving health protection, triage, civil justice, and criminal justice. Different types of information required to apply PEA to these different decision contexts are identified, and specific PEA methods are highlighted that are best suited to exposure assessment in these separate contexts. PMID:19223660

Data analysis using scale-space filtering and Bayesian probabilistic reasoning

NASA Technical Reports Server (NTRS)

Kulkarni, Deepak; Kutulakos, Kiriakos; Robinson, Peter

1991-01-01

This paper describes a program for analysis of output curves from Differential Thermal Analyzer (DTA). The program first extracts probabilistic qualitative features from a DTA curve of a soil sample, and then uses Bayesian probabilistic reasoning to infer the mineral in the soil. The qualifier module employs a simple and efficient extension of scale-space filtering suitable for handling DTA data. We have observed that points can vanish from contours in the scale-space image when filtering operations are not highly accurate. To handle the problem of vanishing points, perceptual organizations heuristics are used to group the points into lines. Next, these lines are grouped into contours by using additional heuristics. Probabilities are associated with these contours using domain-specific correlations. A Bayes tree classifier processes probabilistic features to infer the presence of different minerals in the soil. Experiments show that the algorithm that uses domain-specific correlation to infer qualitative features outperforms a domain-independent algorithm that does not.

Probability analysis of multiple-tank-car release incidents in railway hazardous materials transportation.

PubMed

Liu, Xiang; Saat, Mohd Rapik; Barkan, Christopher P L

2014-07-15

Railroads play a key role in the transportation of hazardous materials in North America. Rail transport differs from highway transport in several aspects, an important one being that rail transport involves trains in which many railcars carrying hazardous materials travel together. By contrast to truck accidents, it is possible that a train accident may involve multiple hazardous materials cars derailing and releasing contents with consequently greater potential impact on human health, property and the environment. In this paper, a probabilistic model is developed to estimate the probability distribution of the number of tank cars releasing contents in a train derailment. Principal operational characteristics considered include train length, derailment speed, accident cause, position of the first car derailed, number and placement of tank cars in a train and tank car safety design. The effect of train speed, tank car safety design and tank car positions in a train were evaluated regarding the number of cars that release their contents in a derailment. This research provides insights regarding the circumstances affecting multiple-tank-car release incidents and potential strategies to reduce their occurrences. The model can be incorporated into a larger risk management framework to enable better local, regional and national safety management of hazardous materials transportation by rail. Copyright © 2014 Elsevier B.V. All rights reserved.

A review for identification of initiating events in event tree development process on nuclear power plants

NASA Astrophysics Data System (ADS)

Riyadi, Eko H.

2014-09-01

Initiating event is defined as any event either internal or external to the nuclear power plants (NPPs) that perturbs the steady state operation of the plant, if operating, thereby initiating an abnormal event such as transient or loss of coolant accident (LOCA) within the NPPs. These initiating events trigger sequences of events that challenge plant control and safety systems whose failure could potentially lead to core damage or large early release. Selection for initiating events consists of two steps i.e. first step, definition of possible events, such as by evaluating a comprehensive engineering, and by constructing a top level logic model. Then the second step, grouping of identified initiating event's by the safety function to be performed or combinations of systems responses. Therefore, the purpose of this paper is to discuss initiating events identification in event tree development process and to reviews other probabilistic safety assessments (PSA). The identification of initiating events also involves the past operating experience, review of other PSA, failure mode and effect analysis (FMEA), feedback from system modeling, and master logic diagram (special type of fault tree). By using the method of study for the condition of the traditional US PSA categorization in detail, could be obtained the important initiating events that are categorized into LOCA, transients and external events.

Development of a framework for the assessment of capacity and throughput technologies within the National Airspace System

NASA Astrophysics Data System (ADS)

Garcia, Elena

The demand for air travel is expanding beyond the capacity of the existing National Airspace System. Excess traffic results in delays and compromised safety. Thus, a number of initiatives to improve airspace capacity have been proposed. To assess the impact of these technologies on air traffic one must move beyond the vehicle to a system-of-systems point of view. This top-level perspective must include consideration of the aircraft, airports, air traffic control and airlines that make up the airspace system. In addition to these components and their interactions economics, safety and government regulations must also be considered. Furthermore, the air transportation system is inherently variable with changes in everything from fuel prices to the weather. The development of a modeling environment that enables a comprehensive probabilistic evaluation of technological impacts was the subject of this thesis. The final modeling environment developed used economics as the thread to tie the airspace components together. Airport capacities and delays were calculated explicitly with due consideration to the impacts of air traffic control. The delay costs were then calculated for an entire fleet, and an airline economic analysis, considering the impact of these costs, was carried out. Airline return on investment was considered the metric of choice since it brings together all costs and revenues, including the cost of delays, landing fees for airport use and aircraft financing costs. Safety was found to require a level of detail unsuitable for a system-of-systems approach and was relegated to future airspace studies. Environmental concerns were considered to be incorporated into airport regulations and procedures and were not explicitly modeled. A deterministic case study was developed to test this modeling environment. The Atlanta airport operations for the year 2000 were used for validation purposes. A 2005 baseline was used as a basis for comparing the four technologies considered: a very large aircraft, Terminal Area Productivity air traffic control technologies, smoothing of an airline schedule, and the addition of a runway. A case including all four technologies simultaneously was also considered. Unfortunately, the complexity of the system prevented full exploration of the probabilistic aspects of the National Airspace System.

Method and system for dynamic probabilistic risk assessment

NASA Technical Reports Server (NTRS)

Dugan, Joanne Bechta (Inventor); Xu, Hong (Inventor)

2013-01-01

The DEFT methodology, system and computer readable medium extends the applicability of the PRA (Probabilistic Risk Assessment) methodology to computer-based systems, by allowing DFT (Dynamic Fault Tree) nodes as pivot nodes in the Event Tree (ET) model. DEFT includes a mathematical model and solution algorithm, supports all common PRA analysis functions and cutsets. Additional capabilities enabled by the DFT include modularization, phased mission analysis, sequence dependencies, and imperfect coverage.

Latent Profile Analysis of Schizotypy and Paranormal Belief: Associations with Probabilistic Reasoning Performance

PubMed Central

Denovan, Andrew; Dagnall, Neil; Drinkwater, Kenneth; Parker, Andrew

2018-01-01

This study assessed the extent to which within-individual variation in schizotypy and paranormal belief influenced performance on probabilistic reasoning tasks. A convenience sample of 725 non-clinical adults completed measures assessing schizotypy (Oxford-Liverpool Inventory of Feelings and Experiences; O-Life brief), belief in the paranormal (Revised Paranormal Belief Scale; RPBS) and probabilistic reasoning (perception of randomness, conjunction fallacy, paranormal perception of randomness, and paranormal conjunction fallacy). Latent profile analysis (LPA) identified four distinct groups: class 1, low schizotypy and low paranormal belief (43.9% of sample); class 2, moderate schizotypy and moderate paranormal belief (18.2%); class 3, moderate schizotypy (high cognitive disorganization) and low paranormal belief (29%); and class 4, moderate schizotypy and high paranormal belief (8.9%). Identification of homogeneous classes provided a nuanced understanding of the relative contribution of schizotypy and paranormal belief to differences in probabilistic reasoning performance. Multivariate analysis of covariance revealed that groups with lower levels of paranormal belief (classes 1 and 3) performed significantly better on perception of randomness, but not conjunction problems. Schizotypy had only a negligible effect on performance. Further analysis indicated that framing perception of randomness and conjunction problems in a paranormal context facilitated performance for all groups but class 4. PMID:29434562

Latent Profile Analysis of Schizotypy and Paranormal Belief: Associations with Probabilistic Reasoning Performance.

PubMed

Denovan, Andrew; Dagnall, Neil; Drinkwater, Kenneth; Parker, Andrew

2018-01-01

This study assessed the extent to which within-individual variation in schizotypy and paranormal belief influenced performance on probabilistic reasoning tasks. A convenience sample of 725 non-clinical adults completed measures assessing schizotypy (Oxford-Liverpool Inventory of Feelings and Experiences; O-Life brief), belief in the paranormal (Revised Paranormal Belief Scale; RPBS) and probabilistic reasoning (perception of randomness, conjunction fallacy, paranormal perception of randomness, and paranormal conjunction fallacy). Latent profile analysis (LPA) identified four distinct groups: class 1, low schizotypy and low paranormal belief (43.9% of sample); class 2, moderate schizotypy and moderate paranormal belief (18.2%); class 3, moderate schizotypy (high cognitive disorganization) and low paranormal belief (29%); and class 4, moderate schizotypy and high paranormal belief (8.9%). Identification of homogeneous classes provided a nuanced understanding of the relative contribution of schizotypy and paranormal belief to differences in probabilistic reasoning performance. Multivariate analysis of covariance revealed that groups with lower levels of paranormal belief (classes 1 and 3) performed significantly better on perception of randomness, but not conjunction problems. Schizotypy had only a negligible effect on performance. Further analysis indicated that framing perception of randomness and conjunction problems in a paranormal context facilitated performance for all groups but class 4.

Probabilistic liquefaction triggering based on the cone penetration test

USGS Publications Warehouse

Moss, R.E.S.; Seed, R.B.; Kayen, R.E.; Stewart, J.P.; Tokimatsu, K.

2005-01-01

Performance-based earthquake engineering requires a probabilistic treatment of potential failure modes in order to accurately quantify the overall stability of the system. This paper is a summary of the application portions of the probabilistic liquefaction triggering correlations proposed recently proposed by Moss and co-workers. To enable probabilistic treatment of liquefaction triggering, the variables comprising the seismic load and the liquefaction resistance were treated as inherently uncertain. Supporting data from an extensive Cone Penetration Test (CPT)-based liquefaction case history database were used to develop a probabilistic correlation. The methods used to measure the uncertainty of the load and resistance variables, how the interactions of these variables were treated using Bayesian updating, and how reliability analysis was applied to produce curves of equal probability of liquefaction are presented. The normalization for effective overburden stress, the magnitude correlated duration weighting factor, and the non-linear shear mass participation factor used are also discussed.

Applying the food safety objective and related standards to thermal inactivation of Salmonella in poultry meat.

PubMed

Membré, Jeanne-Marie; Bassett, John; Gorris, Leon G M

2007-09-01

The objective of this study was to investigate the practicality of designing a heat treatment process in a food manufacturing operation for a product governed by a Food Safety Objective (FSO). Salmonella in cooked poultry meat was taken as the working example. Although there is no FSO for this product in current legislation, this may change in the (near) future. Four different process design calculations were explored by means of deterministic and probabilistic approaches to mathematical data handling and modeling. It was found that the probabilistic approach was a more objective, transparent, and quantifiable approach to establish the stringency of food safety management systems. It also allowed the introduction of specific prevalence rates. The key input analyzed in this study was the minimum time required for the heat treatment at a fixed temperature to produce a product that complied with the criterion for product safety, i.e., the FSO. By means of the four alternative process design calculations, the minimum time requirement at 70 degrees C was established and ranged from 0.26 to 0.43 min. This is comparable to the U.S. regulation recommendations and significantly less than that of 2 min at 70 degrees C used, for instance, in the United Kingdom regulation concerning vegetative microorganisms in ready-to-eat foods. However, the objective of this study was not to challenge existing regulations but to provide an illustration of how an FSO established by a competent authority can guide decisions on safe product and process designs in practical operation; it hopefully contributes to the collaborative work between regulators, academia, and industries that need to continue learning and gaining experience from each other in order to translate risk-based concepts such as the FSO into everyday operational practice.

Asymptotic approximation method of force reconstruction: Application and analysis of stationary random forces

NASA Astrophysics Data System (ADS)

Sanchez, J.

2018-06-01

In this paper, the application and analysis of the asymptotic approximation method to a single degree-of-freedom has recently been produced. The original concepts are summarized, and the necessary probabilistic concepts are developed and applied to single degree-of-freedom systems. Then, these concepts are united, and the theoretical and computational models are developed. To determine the viability of the proposed method in a probabilistic context, numerical experiments are conducted, and consist of a frequency analysis, analysis of the effects of measurement noise, and a statistical analysis. In addition, two examples are presented and discussed.

Concurrent Probabilistic Simulation of High Temperature Composite Structural Response

NASA Technical Reports Server (NTRS)

Abdi, Frank

1996-01-01

A computational structural/material analysis and design tool which would meet industry's future demand for expedience and reduced cost is presented. This unique software 'GENOA' is dedicated to parallel and high speed analysis to perform probabilistic evaluation of high temperature composite response of aerospace systems. The development is based on detailed integration and modification of diverse fields of specialized analysis techniques and mathematical models to combine their latest innovative capabilities into a commercially viable software package. The technique is specifically designed to exploit the availability of processors to perform computationally intense probabilistic analysis assessing uncertainties in structural reliability analysis and composite micromechanics. The primary objectives which were achieved in performing the development were: (1) Utilization of the power of parallel processing and static/dynamic load balancing optimization to make the complex simulation of structure, material and processing of high temperature composite affordable; (2) Computational integration and synchronization of probabilistic mathematics, structural/material mechanics and parallel computing; (3) Implementation of an innovative multi-level domain decomposition technique to identify the inherent parallelism, and increasing convergence rates through high- and low-level processor assignment; (4) Creating the framework for Portable Paralleled architecture for the machine independent Multi Instruction Multi Data, (MIMD), Single Instruction Multi Data (SIMD), hybrid and distributed workstation type of computers; and (5) Market evaluation. The results of Phase-2 effort provides a good basis for continuation and warrants Phase-3 government, and industry partnership.

Probabilistic sensitivity analysis for NICE technology assessment: not an optional extra.

PubMed

Claxton, Karl; Sculpher, Mark; McCabe, Chris; Briggs, Andrew; Akehurst, Ron; Buxton, Martin; Brazier, John; O'Hagan, Tony

2005-04-01

Recently the National Institute for Clinical Excellence (NICE) updated its methods guidance for technology assessment. One aspect of the new guidance is to require the use of probabilistic sensitivity analysis with all cost-effectiveness models submitted to the Institute. The purpose of this paper is to place the NICE guidance on dealing with uncertainty into a broader context of the requirements for decision making; to explain the general approach that was taken in its development; and to address each of the issues which have been raised in the debate about the role of probabilistic sensitivity analysis in general. The most appropriate starting point for developing guidance is to establish what is required for decision making. On the basis of these requirements, the methods and framework of analysis which can best meet these needs can then be identified. It will be argued that the guidance on dealing with uncertainty and, in particular, the requirement for probabilistic sensitivity analysis, is justified by the requirements of the type of decisions that NICE is asked to make. Given this foundation, the main issues and criticisms raised during and after the consultation process are reviewed. Finally, some of the methodological challenges posed by the need fully to characterise decision uncertainty and to inform the research agenda will be identified and discussed. Copyright (c) 2005 John Wiley & Sons, Ltd.

System reliability analysis of granular filter for protection against piping in dams

NASA Astrophysics Data System (ADS)

Srivastava, A.; Sivakumar Babu, G. L.

2015-09-01

Granular filters are provided for the safety of water retaining structure for protection against piping failure. The phenomenon of piping triggers when the base soil to be protected starts migrating in the direction of seepage flow under the influence of seepage force. To protect base soil from migration, the voids in the filter media should be small enough but it should not also be too small to block smooth passage of seeping water. Fulfilling these two contradictory design requirements at the same time is a major concern for the successful performance of granular filter media. Since Terzaghi era, conventionally, particle size distribution (PSD) of granular filters is designed based on particle size distribution characteristics of the base soil to be protected. The design approach provides a range of D15f value in which the PSD of granular filter media should fall and there exist infinite possibilities. Further, safety against the two critical design requirements cannot be ensured. Although used successfully for many decades, the existing filter design guidelines are purely empirical in nature accompanied with experience and good engineering judgment. In the present study, analytical solutions for obtaining the factor of safety with respect to base soil particle migration and soil permeability consideration as proposed by the authors are first discussed. The solution takes into consideration the basic geotechnical properties of base soil and filter media as well as existing hydraulic conditions and provides a comprehensive solution to the granular filter design with ability to assess the stability in terms of factor of safety. Considering the fact that geotechnical properties are variable in nature, probabilistic analysis is further suggested to evaluate the system reliability of the filter media that may help in risk assessment and risk management for decision making.

Reliability and validity of a scale to measure consumer attitudes regarding the private food safety certification of restaurants.

PubMed

Uggioni, Paula Lazzarin; Salay, Elisabete

2012-04-01

Validated and reliable instruments for measuring consumer attitudes regarding food quality certifications are lacking, but the measurement of consumer attitude could be an important tool for understanding consumer behavior. Thus the objective of this study was to develop an instrument for measuring consumer attitudes regarding private food safety certifications for commercial restaurants. To this end, the following steps were carried out: development of the interview items; complete pilot testing; item analyses (influence of social desirability and total-item correlation); reliability test (internal consistency and test-retest); and validity assessment (content and discriminative validity and exploratory and confirmatory factor analysis). The subjects, all over the age of 18 and drawn from six non-probabilistic samples (n=7-350) in the city of Campinas, Brazil, were all subjected to an interview. The final scale included 24 items and had a Cronbach's alpha coefficient of 0.79 and a content validation coefficient of 0.99, both within acceptable limits. The confirmatory factor analysis validated a model with five factors and the final instrument discriminated reasonably well between the groups and showed satisfactory reproducibility (r=0.955). Furthermore, the scale validity and reliability were satisfactory, suggesting it could also be applied to future studies. Copyright © 2011 Elsevier Ltd. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, Curtis L.; Prescott, Steven; Coleman, Justin

This report describes the current progress and status related to the Industry Application #2 focusing on External Hazards. For this industry application within the Light Water Reactor Sustainability (LWRS) Program Risk-Informed Safety Margin Characterization (RISMC) R&D Pathway, we will create the Risk-Informed Margin Management (RIMM) approach to represent meaningful (i.e., realistic facility representation) event scenarios and consequences by using an advanced 3D facility representation that will evaluate external hazards such as flooding and earthquakes in order to identify, model and analyze the appropriate physics that needs to be included to determine plant vulnerabilities related to external events; manage the communicationmore » and interactions between different physics modeling and analysis technologies; and develop the computational infrastructure through tools related to plant representation, scenario depiction, and physics prediction. One of the unique aspects of the RISMC approach is how it couples probabilistic approaches (the scenario) with mechanistic phenomena representation (the physics) through simulation. This simulation-based modeling allows decision makers to focus on a variety of safety, performance, or economic metrics. In this report, we describe the evaluation of various physics toolkits related to flooding representation. Ultimately, we will be coupling the flooding representation with other events such as earthquakes in order to provide coupled physics analysis for scenarios where interactions exist.« less

Coupling Legacy and Contemporary Deterministic Codes to Goldsim for Probabilistic Assessments of Potential Low-Level Waste Repository Sites

NASA Astrophysics Data System (ADS)

Mattie, P. D.; Knowlton, R. G.; Arnold, B. W.; Tien, N.; Kuo, M.

2006-12-01

Sandia National Laboratories (Sandia), a U.S. Department of Energy National Laboratory, has over 30 years experience in radioactive waste disposal and is providing assistance internationally in a number of areas relevant to the safety assessment of radioactive waste disposal systems. International technology transfer efforts are often hampered by small budgets, time schedule constraints, and a lack of experienced personnel in countries with small radioactive waste disposal programs. In an effort to surmount these difficulties, Sandia has developed a system that utilizes a combination of commercially available codes and existing legacy codes for probabilistic safety assessment modeling that facilitates the technology transfer and maximizes limited available funding. Numerous codes developed and endorsed by the United States Nuclear Regulatory Commission and codes developed and maintained by United States Department of Energy are generally available to foreign countries after addressing import/export control and copyright requirements. From a programmatic view, it is easier to utilize existing codes than to develop new codes. From an economic perspective, it is not possible for most countries with small radioactive waste disposal programs to maintain complex software, which meets the rigors of both domestic regulatory requirements and international peer review. Therefore, re-vitalization of deterministic legacy codes, as well as an adaptation of contemporary deterministic codes, provides a creditable and solid computational platform for constructing probabilistic safety assessment models. External model linkage capabilities in Goldsim and the techniques applied to facilitate this process will be presented using example applications, including Breach, Leach, and Transport-Multiple Species (BLT-MS), a U.S. NRC sponsored code simulating release and transport of contaminants from a subsurface low-level waste disposal facility used in a cooperative technology transfer project between Sandia National Laboratories and Taiwan's Institute of Nuclear Energy Research (INER) for the preliminary assessment of several candidate low-level waste repository sites. Sandia National Laboratories is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy under Contract DE AC04 94AL85000.

Modelling default and likelihood reasoning as probabilistic reasoning

NASA Technical Reports Server (NTRS)

Buntine, Wray

1990-01-01

A probabilistic analysis of plausible reasoning about defaults and about likelihood is presented. Likely and by default are in fact treated as duals in the same sense as possibility and necessity. To model these four forms probabilistically, a qualitative default probabilistic (QDP) logic and its quantitative counterpart DP are derived that allow qualitative and corresponding quantitative reasoning. Consistency and consequent results for subsets of the logics are given that require at most a quadratic number of satisfiability tests in the underlying propositional logic. The quantitative logic shows how to track the propagation error inherent in these reasoning forms. The methodology and sound framework of the system highlights their approximate nature, the dualities, and the need for complementary reasoning about relevance.

Performance Analysis of the Probabilistic Multi-Hypothesis Tracking Algorithm on the SEABAR Data Sets

DTIC Science & Technology

2009-07-01

Performance Analysis of the Probabilistic Multi- Hypothesis Tracking Algorithm On the SEABAR Data Sets Dr. Christian G . Hempel Naval...Hypothesis Tracking,” NUWC-NPT Technical Report 10,428, Naval Undersea Warfare Center Division, Newport, RI, 15 February 1995. [2] G . McLachlan, T...the 9th International Conference on Information Fusion, Florence Italy, July, 2006. [8] C. Hempel, “Track Initialization for Multi-Static Active Sonay

Probabilistic description of probable maximum precipitation

NASA Astrophysics Data System (ADS)

Ben Alaya, Mohamed Ali; Zwiers, Francis W.; Zhang, Xuebin

2017-04-01

Probable Maximum Precipitation (PMP) is the key parameter used to estimate probable Maximum Flood (PMF). PMP and PMF are important for dam safety and civil engineering purposes. Even if the current knowledge of storm mechanisms remains insufficient to properly evaluate limiting values of extreme precipitation, PMP estimation methods are still based on deterministic consideration, and give only single values. This study aims to provide a probabilistic description of the PMP based on the commonly used method, the so-called moisture maximization. To this end, a probabilistic bivariate extreme values model is proposed to address the limitations of traditional PMP estimates via moisture maximization namely: (i) the inability to evaluate uncertainty and to provide a range PMP values, (ii) the interpretation that a maximum of a data series as a physical upper limit (iii) and the assumption that a PMP event has maximum moisture availability. Results from simulation outputs of the Canadian Regional Climate Model CanRCM4 over North America reveal the high uncertainties inherent in PMP estimates and the non-validity of the assumption that PMP events have maximum moisture availability. This later assumption leads to overestimation of the PMP by an average of about 15% over North America, which may have serious implications for engineering design.

Order Under Uncertainty: Robust Differential Expression Analysis Using Probabilistic Models for Pseudotime Inference

PubMed Central

Campbell, Kieran R.

2016-01-01

Single cell gene expression profiling can be used to quantify transcriptional dynamics in temporal processes, such as cell differentiation, using computational methods to label each cell with a ‘pseudotime’ where true time series experimentation is too difficult to perform. However, owing to the high variability in gene expression between individual cells, there is an inherent uncertainty in the precise temporal ordering of the cells. Pre-existing methods for pseudotime estimation have predominantly given point estimates precluding a rigorous analysis of the implications of uncertainty. We use probabilistic modelling techniques to quantify pseudotime uncertainty and propagate this into downstream differential expression analysis. We demonstrate that reliance on a point estimate of pseudotime can lead to inflated false discovery rates and that probabilistic approaches provide greater robustness and measures of the temporal resolution that can be obtained from pseudotime inference. PMID:27870852

ANALYSIS OF CONCORDANCE OF PROBABILISTIC AGGREGATE EXPOSURE PREDICTIONS WITH OBSERVED BIOMONITORING RESULTS: AN EXAMPLE USING CTEPP DATA

EPA Science Inventory

Three key areas of scientific inquiry in the study of human exposure to environmental contaminants are 1) assessment of aggregate (i.e., multi-pathway, multi-route) exposures, 2) application of probabilistic methods to exposure prediction, and 3) the interpretation of biomarker m...

A Probabilistic Model of Phonological Relationships from Contrast to Allophony

ERIC Educational Resources Information Center

Hall, Kathleen Currie

2009-01-01

This dissertation proposes a model of phonological relationships, the Probabilistic Phonological Relationship Model (PPRM), that quantifies how predictably distributed two sounds in a relationship are. It builds on a core premise of traditional phonological analysis, that the ability to define phonological relationships such as contrast and…

Probabilistic Assessment of Cancer Risk for Astronauts on Lunar Missions

NASA Technical Reports Server (NTRS)

Kim, Myung-Hee Y.; Cucinotta, Francis A.

2009-01-01

During future lunar missions, exposure to solar particle events (SPEs) is a major safety concern for crew members during extra-vehicular activities (EVAs) on the lunar surface or Earth-to-moon transit. NASA s new lunar program anticipates that up to 15% of crew time may be on EVA, with minimal radiation shielding. For the operational challenge to respond to events of unknown size and duration, a probabilistic risk assessment approach is essential for mission planning and design. Using the historical database of proton measurements during the past 5 solar cycles, a typical hazard function for SPE occurrence was defined using a non-homogeneous Poisson model as a function of time within a non-specific future solar cycle of 4000 days duration. Distributions ranging from the 5th to 95th percentile of particle fluences for a specified mission period were simulated. Organ doses corresponding to particle fluences at the median and at the 95th percentile for a specified mission period were assessed using NASA s baryon transport model, BRYNTRN. The cancer fatality risk for astronauts as functions of age, gender, and solar cycle activity were then analyzed. The probability of exceeding the NASA 30- day limit of blood forming organ (BFO) dose inside a typical spacecraft was calculated. Future work will involve using this probabilistic risk assessment approach to SPE forecasting, combined with a probabilistic approach to the radiobiological factors that contribute to the uncertainties in projecting cancer risks.

Air traffic surveillance and control using hybrid estimation and protocol-based conflict resolution

NASA Astrophysics Data System (ADS)

Hwang, Inseok

The continued growth of air travel and recent advances in new technologies for navigation, surveillance, and communication have led to proposals by the Federal Aviation Administration (FAA) to provide reliable and efficient tools to aid Air Traffic Control (ATC) in performing their tasks. In this dissertation, we address four problems frequently encountered in air traffic surveillance and control; multiple target tracking and identity management, conflict detection, conflict resolution, and safety verification. We develop a set of algorithms and tools to aid ATC; These algorithms have the provable properties of safety, computational efficiency, and convergence. Firstly, we develop a multiple-maneuvering-target tracking and identity management algorithm which can keep track of maneuvering aircraft in noisy environments and of their identities. Secondly, we propose a hybrid probabilistic conflict detection algorithm between multiple aircraft which uses flight mode estimates as well as aircraft current state estimates. Our algorithm is based on hybrid models of aircraft, which incorporate both continuous dynamics and discrete mode switching. Thirdly, we develop an algorithm for multiple (greater than two) aircraft conflict avoidance that is based on a closed-form analytic solution and thus provides guarantees of safety. Finally, we consider the problem of safety verification of control laws for safety critical systems, with application to air traffic control systems. We approach safety verification through reachability analysis, which is a computationally expensive problem. We develop an over-approximate method for reachable set computation using polytopic approximation methods and dynamic optimization. These algorithms may be used either in a fully autonomous way, or as supporting tools to increase controllers' situational awareness and to reduce their work load.

Probabilistic structural analysis to quantify uncertainties associated with turbopump blades

NASA Technical Reports Server (NTRS)

Nagpal, Vinod K.; Rubinstein, Robert; Chamis, Christos C.

1987-01-01

A probabilistic study of turbopump blades has been in progress at NASA Lewis Research Center for over the last two years. The objectives of this study are to evaluate the effects of uncertainties in geometry and material properties on the structural response of the turbopump blades to evaluate the tolerance limits on the design. A methodology based on probabilistic approach has been developed to quantify the effects of the random uncertainties. The results of this study indicate that only the variations in geometry have significant effects.

Overview of the SAE G-11 RMSL (Reliability, Maintainability, Supportability, and Logistics) Division Activities and Technical Projects

NASA Technical Reports Server (NTRS)

Singhal, Surendra N.

2003-01-01

The SAE G-11 RMSL (Reliability, Maintainability, Supportability, and Logistics) Division activities include identification and fulfillment of joint industry, government, and academia needs for development and implementation of RMSL technologies. Four Projects in the Probabilistic Methods area and two in the area of RMSL have been identified. These are: (1) Evaluation of Probabilistic Technology - progress has been made toward the selection of probabilistic application cases. Future effort will focus on assessment of multiple probabilistic softwares in solving selected engineering problems using probabilistic methods. Relevance to Industry & Government - Case studies of typical problems encountering uncertainties, results of solutions to these problems run by different codes, and recommendations on which code is applicable for what problems; (2) Probabilistic Input Preparation - progress has been made in identifying problem cases such as those with no data, little data and sufficient data. Future effort will focus on developing guidelines for preparing input for probabilistic analysis, especially with no or little data. Relevance to Industry & Government - Too often, we get bogged down thinking we need a lot of data before we can quantify uncertainties. Not True. There are ways to do credible probabilistic analysis with little data; (3) Probabilistic Reliability - probabilistic reliability literature search has been completed along with what differentiates it from statistical reliability. Work on computation of reliability based on quantification of uncertainties in primitive variables is in progress. Relevance to Industry & Government - Correct reliability computations both at the component and system level are needed so one can design an item based on its expected usage and life span; (4) Real World Applications of Probabilistic Methods (PM) - A draft of volume 1 comprising aerospace applications has been released. Volume 2, a compilation of real world applications of probabilistic methods with essential information demonstrating application type and timehost savings by the use of probabilistic methods for generic applications is in progress. Relevance to Industry & Government - Too often, we say, 'The Proof is in the Pudding'. With help from many contributors, we hope to produce such a document. Problem is - not too many people are coming forward due to proprietary nature. So, we are asking to document only minimum information including problem description, what method used, did it result in any savings, and how much?; (5) Software Reliability - software reliability concept, program, implementation, guidelines, and standards are being documented. Relevance to Industry & Government - software reliability is a complex issue that must be understood & addressed in all facets of business in industry, government, and other institutions. We address issues, concepts, ways to implement solutions, and guidelines for maximizing software reliability; (6) Maintainability Standards - maintainability/serviceability industry standard/guidelines and industry best practices and methodologies used in performing maintainability/ serviceability tasks are being documented. Relevance to Industry & Government - Any industry or government process, project, and/or tool must be maintained and serviced to realize the life and performance it was designed for. We address issues and develop guidelines for optimum performance & life.

Fracture mechanics analysis of cracked structures using weight function and neural network method

NASA Astrophysics Data System (ADS)

Chen, J. G.; Zang, F. G.; Yang, Y.; Shi, K. K.; Fu, X. L.

2018-06-01

Stress intensity factors(SIFs) due to thermal-mechanical load has been established by using weight function method. Two reference stress states sere used to determine the coefficients in the weight function. Results were evaluated by using data from literature and show a good agreement between them. So, the SIFs can be determined quickly using the weight function obtained when cracks subjected to arbitrary loads, and presented method can be used for probabilistic fracture mechanics analysis. A probabilistic methodology considering Monte-Carlo with neural network (MCNN) has been developed. The results indicate that an accurate probabilistic characteristic of the KI can be obtained by using the developed method. The probability of failure increases with the increasing of loads, and the relationship between is nonlinear.

Probabilistic evaluation of on-line checks in fault-tolerant multiprocessor systems

NASA Technical Reports Server (NTRS)

Nair, V. S. S.; Hoskote, Yatin V.; Abraham, Jacob A.

1992-01-01

The analysis of fault-tolerant multiprocessor systems that use concurrent error detection (CED) schemes is much more difficult than the analysis of conventional fault-tolerant architectures. Various analytical techniques have been proposed to evaluate CED schemes deterministically. However, these approaches are based on worst-case assumptions related to the failure of system components. Often, the evaluation results do not reflect the actual fault tolerance capabilities of the system. A probabilistic approach to evaluate the fault detecting and locating capabilities of on-line checks in a system is developed. The various probabilities associated with the checking schemes are identified and used in the framework of the matrix-based model. Based on these probabilistic matrices, estimates for the fault tolerance capabilities of various systems are derived analytically.

Simulation of probabilistic wind loads and building analysis

NASA Technical Reports Server (NTRS)

Shah, Ashwin R.; Chamis, Christos C.

1991-01-01

Probabilistic wind loads likely to occur on a structure during its design life are predicted. Described here is a suitable multifactor interactive equation (MFIE) model and its use in the Composite Load Spectra (CLS) computer program to simulate the wind pressure cumulative distribution functions on four sides of a building. The simulated probabilistic wind pressure load was applied to a building frame, and cumulative distribution functions of sway displacements and reliability against overturning were obtained using NESSUS (Numerical Evaluation of Stochastic Structure Under Stress), a stochastic finite element computer code. The geometry of the building and the properties of building members were also considered as random in the NESSUS analysis. The uncertainties of wind pressure, building geometry, and member section property were qualified in terms of their respective sensitivities on the structural response.

Probabilistic structural analysis methods and applications

NASA Technical Reports Server (NTRS)

Cruse, T. A.; Wu, Y.-T.; Dias, B.; Rajagopal, K. R.

1988-01-01

An advanced algorithm for simulating the probabilistic distribution of structural responses due to statistical uncertainties in loads, geometry, material properties, and boundary conditions is reported. The method effectively combines an advanced algorithm for calculating probability levels for multivariate problems (fast probability integration) together with a general-purpose finite-element code for stress, vibration, and buckling analysis. Application is made to a space propulsion system turbine blade for which the geometry and material properties are treated as random variables.

Probabilistic methods for rotordynamics analysis

NASA Technical Reports Server (NTRS)

Wu, Y.-T.; Torng, T. Y.; Millwater, H. R.; Fossum, A. F.; Rheinfurth, M. H.

1991-01-01

This paper summarizes the development of the methods and a computer program to compute the probability of instability of dynamic systems that can be represented by a system of second-order ordinary linear differential equations. Two instability criteria based upon the eigenvalues or Routh-Hurwitz test functions are investigated. Computational methods based on a fast probability integration concept and an efficient adaptive importance sampling method are proposed to perform efficient probabilistic analysis. A numerical example is provided to demonstrate the methods.

Uncertainty characterization approaches for risk assessment of DBPs in drinking water: a review.

PubMed

Chowdhury, Shakhawat; Champagne, Pascale; McLellan, P James

2009-04-01

The management of risk from disinfection by-products (DBPs) in drinking water has become a critical issue over the last three decades. The areas of concern for risk management studies include (i) human health risk from DBPs, (ii) disinfection performance, (iii) technical feasibility (maintenance, management and operation) of treatment and disinfection approaches, and (iv) cost. Human health risk assessment is typically considered to be the most important phase of the risk-based decision-making or risk management studies. The factors associated with health risk assessment and other attributes are generally prone to considerable uncertainty. Probabilistic and non-probabilistic approaches have both been employed to characterize uncertainties associated with risk assessment. The probabilistic approaches include sampling-based methods (typically Monte Carlo simulation and stratified sampling) and asymptotic (approximate) reliability analysis (first- and second-order reliability methods). Non-probabilistic approaches include interval analysis, fuzzy set theory and possibility theory. However, it is generally accepted that no single method is suitable for the entire spectrum of problems encountered in uncertainty analyses for risk assessment. Each method has its own set of advantages and limitations. In this paper, the feasibility and limitations of different uncertainty analysis approaches are outlined for risk management studies of drinking water supply systems. The findings assist in the selection of suitable approaches for uncertainty analysis in risk management studies associated with DBPs and human health risk.

Probabilistic bias analysis in pharmacoepidemiology and comparative effectiveness research: a systematic review.

PubMed

Hunnicutt, Jacob N; Ulbricht, Christine M; Chrysanthopoulou, Stavroula A; Lapane, Kate L

2016-12-01

We systematically reviewed pharmacoepidemiologic and comparative effectiveness studies that use probabilistic bias analysis to quantify the effects of systematic error including confounding, misclassification, and selection bias on study results. We found articles published between 2010 and October 2015 through a citation search using Web of Science and Google Scholar and a keyword search using PubMed and Scopus. Eligibility of studies was assessed by one reviewer. Three reviewers independently abstracted data from eligible studies. Fifteen studies used probabilistic bias analysis and were eligible for data abstraction-nine simulated an unmeasured confounder and six simulated misclassification. The majority of studies simulating an unmeasured confounder did not specify the range of plausible estimates for the bias parameters. Studies simulating misclassification were in general clearer when reporting the plausible distribution of bias parameters. Regardless of the bias simulated, the probability distributions assigned to bias parameters, number of simulated iterations, sensitivity analyses, and diagnostics were not discussed in the majority of studies. Despite the prevalence and concern of bias in pharmacoepidemiologic and comparative effectiveness studies, probabilistic bias analysis to quantitatively model the effect of bias was not widely used. The quality of reporting and use of this technique varied and was often unclear. Further discussion and dissemination of the technique are warranted. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Development of a Probabilistic Tsunami Hazard Analysis in Japan

DOE Office of Scientific and Technical Information (OSTI.GOV)

Toshiaki Sakai; Tomoyoshi Takeda; Hiroshi Soraoka

2006-07-01

It is meaningful for tsunami assessment to evaluate phenomena beyond the design basis as well as seismic design. Because once we set the design basis tsunami height, we still have possibilities tsunami height may exceeds the determined design tsunami height due to uncertainties regarding the tsunami phenomena. Probabilistic tsunami risk assessment consists of estimating for tsunami hazard and fragility of structures and executing system analysis. In this report, we apply a method for probabilistic tsunami hazard analysis (PTHA). We introduce a logic tree approach to estimate tsunami hazard curves (relationships between tsunami height and probability of excess) and present anmore » example for Japan. Examples of tsunami hazard curves are illustrated, and uncertainty in the tsunami hazard is displayed by 5-, 16-, 50-, 84- and 95-percentile and mean hazard curves. The result of PTHA will be used for quantitative assessment of the tsunami risk for important facilities located on coastal area. Tsunami hazard curves are the reasonable input data for structures and system analysis. However the evaluation method for estimating fragility of structures and the procedure of system analysis is now being developed. (authors)« less

Probabilistic Cues to Grammatical Category in English Orthography and Their Influence during Reading

ERIC Educational Resources Information Center

Arciuli, Joanne; Monaghan, Padraic

2009-01-01

We investigated probabilistic cues to grammatical category (noun vs. verb) in English orthography. These cues are located in both the beginnings and endings of words--as identified in our large-scale corpus analysis. Experiment 1 tested participants' sensitivity to beginning and ending cues while making speeded grammatical classifications.…

Nonlinear probabilistic finite element models of laminated composite shells

NASA Technical Reports Server (NTRS)

Engelstad, S. P.; Reddy, J. N.

1993-01-01

A probabilistic finite element analysis procedure for laminated composite shells has been developed. A total Lagrangian finite element formulation, employing a degenerated 3-D laminated composite shell with the full Green-Lagrange strains and first-order shear deformable kinematics, forms the modeling foundation. The first-order second-moment technique for probabilistic finite element analysis of random fields is employed and results are presented in the form of mean and variance of the structural response. The effects of material nonlinearity are included through the use of a rate-independent anisotropic plasticity formulation with the macroscopic point of view. Both ply-level and micromechanics-level random variables can be selected, the latter by means of the Aboudi micromechanics model. A number of sample problems are solved to verify the accuracy of the procedures developed and to quantify the variability of certain material type/structure combinations. Experimental data is compared in many cases, and the Monte Carlo simulation method is used to check the probabilistic results. In general, the procedure is quite effective in modeling the mean and variance response of the linear and nonlinear behavior of laminated composite shells.

Scalable DB+IR Technology: Processing Probabilistic Datalog with HySpirit.

PubMed

Frommholz, Ingo; Roelleke, Thomas

2016-01-01

Probabilistic Datalog (PDatalog, proposed in 1995) is a probabilistic variant of Datalog and a nice conceptual idea to model Information Retrieval in a logical, rule-based programming paradigm. Making PDatalog work in real-world applications requires more than probabilistic facts and rules, and the semantics associated with the evaluation of the programs. We report in this paper some of the key features of the HySpirit system required to scale the execution of PDatalog programs. Firstly, there is the requirement to express probability estimation in PDatalog. Secondly, fuzzy-like predicates are required to model vague predicates (e.g. vague match of attributes such as age or price). Thirdly, to handle large data sets there are scalability issues to be addressed, and therefore, HySpirit provides probabilistic relational indexes and parallel and distributed processing . The main contribution of this paper is a consolidated view on the methods of the HySpirit system to make PDatalog applicable in real-scale applications that involve a wide range of requirements typical for data (information) management and analysis.

Dynamic Probabilistic Instability of Composite Structures

NASA Technical Reports Server (NTRS)

Chamis, Christos C.

2009-01-01

A computationally effective method is described to evaluate the non-deterministic dynamic instability (probabilistic dynamic buckling) of thin composite shells. The method is a judicious combination of available computer codes for finite element, composite mechanics and probabilistic structural analysis. The solution method is incrementally updated Lagrangian. It is illustrated by applying it to thin composite cylindrical shell subjected to dynamic loads. Both deterministic and probabilistic buckling loads are evaluated to demonstrate the effectiveness of the method. A universal plot is obtained for the specific shell that can be used to approximate buckling loads for different load rates and different probability levels. Results from this plot show that the faster the rate, the higher the buckling load and the shorter the time. The lower the probability, the lower is the buckling load for a specific time. Probabilistic sensitivity results show that the ply thickness, the fiber volume ratio and the fiber longitudinal modulus, dynamic load and loading rate are the dominant uncertainties in that order.

MATILDA Version-2: Rough Earth TIALD Model for Laser Probabilistic Risk Assessment in Hilly Terrain - Part II

DTIC Science & Technology

2017-07-28

Approved for public release; distribution unlimited. PA Case No: TSRL- PA-2017-0228 Air Force Research Laboratory 711th Human Performance Wing Airman...PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Air Force Research Laboratory Engility Corp 8. PERFORMING ORGANIZATION...United States (US) Air Force Research Laboratory (AFRL) have collaborated to develop a US-UK laser range safety tool, the Military Advanced Technology

Incremental dynamical downscaling for probabilistic analysis based on multiple GCM projections

NASA Astrophysics Data System (ADS)

Wakazuki, Y.

2015-12-01

A dynamical downscaling method for probabilistic regional scale climate change projections was developed to cover an uncertainty of multiple general circulation model (GCM) climate simulations. The climatological increments (future minus present climate states) estimated by GCM simulation results were statistically analyzed using the singular vector decomposition. Both positive and negative perturbations from the ensemble mean with the magnitudes of their standard deviations were extracted and were added to the ensemble mean of the climatological increments. The analyzed multiple modal increments were utilized to create multiple modal lateral boundary conditions for the future climate regional climate model (RCM) simulations by adding to an objective analysis data. This data handling is regarded to be an advanced method of the pseudo-global-warming (PGW) method previously developed by Kimura and Kitoh (2007). The incremental handling for GCM simulations realized approximated probabilistic climate change projections with the smaller number of RCM simulations. Three values of a climatological variable simulated by RCMs for a mode were used to estimate the response to the perturbation of the mode. For the probabilistic analysis, climatological variables of RCMs were assumed to show linear response to the multiple modal perturbations, although the non-linearity was seen for local scale rainfall. Probability of temperature was able to be estimated within two modes perturbation simulations, where the number of RCM simulations for the future climate is five. On the other hand, local scale rainfalls needed four modes simulations, where the number of the RCM simulations is nine. The probabilistic method is expected to be used for regional scale climate change impact assessment in the future.

A framework for the probabilistic analysis of meteotsunamis

USGS Publications Warehouse

Geist, Eric L.; ten Brink, Uri S.; Gove, Matthew D.

2014-01-01

A probabilistic technique is developed to assess the hazard from meteotsunamis. Meteotsunamis are unusual sea-level events, generated when the speed of an atmospheric pressure or wind disturbance is comparable to the phase speed of long waves in the ocean. A general aggregation equation is proposed for the probabilistic analysis, based on previous frameworks established for both tsunamis and storm surges, incorporating different sources and source parameters of meteotsunamis. Parameterization of atmospheric disturbances and numerical modeling is performed for the computation of maximum meteotsunami wave amplitudes near the coast. A historical record of pressure disturbances is used to establish a continuous analytic distribution of each parameter as well as the overall Poisson rate of occurrence. A demonstration study is presented for the northeast U.S. in which only isolated atmospheric pressure disturbances from squall lines and derechos are considered. For this study, Automated Surface Observing System stations are used to determine the historical parameters of squall lines from 2000 to 2013. The probabilistic equations are implemented using a Monte Carlo scheme, where a synthetic catalog of squall lines is compiled by sampling the parameter distributions. For each entry in the catalog, ocean wave amplitudes are computed using a numerical hydrodynamic model. Aggregation of the results from the Monte Carlo scheme results in a meteotsunami hazard curve that plots the annualized rate of exceedance with respect to maximum event amplitude for a particular location along the coast. Results from using multiple synthetic catalogs, resampled from the parent parameter distributions, yield mean and quantile hazard curves. Further refinements and improvements for probabilistic analysis of meteotsunamis are discussed.

Real Time Data Management for Estimating Probabilities of Incidents and Near Misses

NASA Astrophysics Data System (ADS)

Stanitsas, P. D.; Stephanedes, Y. J.

2011-08-01

Advances in real-time data collection, data storage and computational systems have led to development of algorithms for transport administrators and engineers that improve traffic safety and reduce cost of road operations. Despite these advances, problems in effectively integrating real-time data acquisition, processing, modelling and road-use strategies at complex intersections and motorways remain. These are related to increasing system performance in identification, analysis, detection and prediction of traffic state in real time. This research develops dynamic models to estimate the probability of road incidents, such as crashes and conflicts, and incident-prone conditions based on real-time data. The models support integration of anticipatory information and fee-based road use strategies in traveller information and management. Development includes macroscopic/microscopic probabilistic models, neural networks, and vector autoregressions tested via machine vision at EU and US sites.

Development of Probabilistic Life Prediction Methodologies and Testing Strategies for MEMS and CMC's

NASA Technical Reports Server (NTRS)

Jadaan, Osama

2003-01-01

This effort is to investigate probabilistic life prediction methodologies for ceramic matrix composites and MicroElectroMechanical Systems (MEMS) and to analyze designs that determine stochastic properties of MEMS. For CMC's this includes a brief literature survey regarding lifing methodologies. Also of interest for MEMS is the design of a proper test for the Weibull size effect in thin film (bulge test) specimens. The Weibull size effect is a consequence of a stochastic strength response predicted from the Weibull distribution. Confirming that MEMS strength is controlled by the Weibull distribution will enable the development of a probabilistic design methodology for MEMS - similar to the GRC developed CARES/Life program for bulk ceramics. A main objective of this effort is to further develop and verify the ability of the Ceramics Analysis and Reliability Evaluation of Structures/Life (CARES/Life) code to predict the time-dependent reliability of MEMS structures subjected to multiple transient loads. A second set of objectives is to determine the applicability/suitability of the CARES/Life methodology for CMC analysis, what changes would be needed to the methodology and software, and if feasible, run a demonstration problem. Also important is an evaluation of CARES/Life coupled to the ANSYS Probabilistic Design System (PDS) and the potential of coupling transient reliability analysis to the ANSYS PDS.

Probabilistic Harmonic Analysis on Distributed Photovoltaic Integration Considering Typical Weather Scenarios

NASA Astrophysics Data System (ADS)

Bin, Che; Ruoying, Yu; Dongsheng, Dang; Xiangyan, Wang

2017-05-01

Distributed Generation (DG) integrating to the network would cause the harmonic pollution which would cause damages on electrical devices and affect the normal operation of power system. On the other hand, due to the randomness of the wind and solar irradiation, the output of DG is random, too, which leads to an uncertainty of the harmonic generated by the DG. Thus, probabilistic methods are needed to analyse the impacts of the DG integration. In this work we studied the harmonic voltage probabilistic distribution and the harmonic distortion in distributed network after the distributed photovoltaic (DPV) system integrating in different weather conditions, mainly the sunny day, cloudy day, rainy day and the snowy day. The probabilistic distribution function of the DPV output power in different typical weather conditions could be acquired via the parameter identification method of maximum likelihood estimation. The Monte-Carlo simulation method was adopted to calculate the probabilistic distribution of harmonic voltage content at different frequency orders as well as the harmonic distortion (THD) in typical weather conditions. The case study was based on the IEEE33 system and the results of harmonic voltage content probabilistic distribution as well as THD in typical weather conditions were compared.

A probabilistic approach to aircraft design emphasizing stability and control uncertainties

NASA Astrophysics Data System (ADS)

Delaurentis, Daniel Andrew

In order to address identified deficiencies in current approaches to aerospace systems design, a new method has been developed. This new method for design is based on the premise that design is a decision making activity, and that deterministic analysis and synthesis can lead to poor, or misguided decision making. This is due to a lack of disciplinary knowledge of sufficient fidelity about the product, to the presence of uncertainty at multiple levels of the aircraft design hierarchy, and to a failure to focus on overall affordability metrics as measures of goodness. Design solutions are desired which are robust to uncertainty and are based on the maximum knowledge possible. The new method represents advances in the two following general areas. 1. Design models and uncertainty. The research performed completes a transition from a deterministic design representation to a probabilistic one through a modeling of design uncertainty at multiple levels of the aircraft design hierarchy, including: (1) Consistent, traceable uncertainty classification and representation; (2) Concise mathematical statement of the Probabilistic Robust Design problem; (3) Variants of the Cumulative Distribution Functions (CDFs) as decision functions for Robust Design; (4) Probabilistic Sensitivities which identify the most influential sources of variability. 2. Multidisciplinary analysis and design. Imbedded in the probabilistic methodology is a new approach for multidisciplinary design analysis and optimization (MDA/O), employing disciplinary analysis approximations formed through statistical experimentation and regression. These approximation models are a function of design variables common to the system level as well as other disciplines. For aircraft, it is proposed that synthesis/sizing is the proper avenue for integrating multiple disciplines. Research hypotheses are translated into a structured method, which is subsequently tested for validity. Specifically, the implementation involves the study of the relaxed static stability technology for a supersonic commercial transport aircraft. The probabilistic robust design method is exercised resulting in a series of robust design solutions based on different interpretations of "robustness". Insightful results are obtained and the ability of the method to expose trends in the design space are noted as a key advantage.

How do smoking cessation medicines compare with respect to their neuropsychiatric safety? A protocol for a systematic review, network meta-analysis and cost-effectiveness analysis.

PubMed

Thomas, Kyla H; Caldwell, Deborah; Dalili, Michael N; Gunnell, David; Munafò, Marcus R; Stevenson, Matt; Welton, Nicky J

2017-06-17

Cigarette smoking is one of the leading causes of early death in the UK and worldwide. Public health guidance recommends the use of varenicline, bupropion and nicotine replacement therapy (NRT) as smoking cessation aids in the UK. Additionally, the first electronic cigarette has been licensed for use as a smoking cessation medicine. However, there are ongoing concerns about the safety of these medicines. We present a protocol for a systematic review and network meta-analysis (NMA) to determine how these smoking cessation medicines compare to each other with respect to their neuropsychiatric safety in adult smokers. Secondary aims include updating the evidence regarding the effectiveness and cardiovascular safety of these medicines for use in a cost-effectiveness analysis. We will include randomised controlled trials and observational studies with control groups comparing monotherapy with varenicline, bupropion, NRT or electronic cigarette and combination therapies to each other, placebo or usual care. The primary composite safety outcome will be serious adverse events, defined as events that resulted in death, were life threatening, required hospitalisation or resulted in significant disability or congenital/birth defect. The preferred effectiveness outcome will be sustained smoking cessation defined as abstinence for a minimum of 6 months as determined by biochemical validation. We will include trials identified by previous reviews and search relevant databases for newly published trials as well as contacting study authors to identify unpublished information. We will conduct fixed-effect and random-effect meta-analyses for each pairwise comparison of treatments and outcome; where these estimates differ, we will consider reasons for heterogeneity, quantified using the between-study variance (τ 2 ). For each outcome, we will construct a NMA in a Bayesian framework which will be compared with the pair-wise results, allowing us to rank treatments. The effectiveness estimates from the NMA will be entered into a probabilistic economic model. Ethics approval is not required for this evidence synthesis study as it involves analysis of secondary data from randomised controlled trials and observational studies. The review will make an important contribution to the knowledge base around the effectiveness, safety and cost-effectiveness of smoking cessation medicines. Results will be disseminated to the general public, healthcare practitioners and clinicians, academics, industry and policy makers. CRD42016041302. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Methodology for assessing the safety of Hydrogen Systems: HyRAM 1.1 technical reference manual

DOE Office of Scientific and Technical Information (OSTI.GOV)

Groth, Katrina; Hecht, Ethan; Reynolds, John Thomas

The HyRAM software toolkit provides a basis for conducting quantitative risk assessment and consequence modeling for hydrogen infrastructure and transportation systems. HyRAM is designed to facilitate the use of state-of-the-art science and engineering models to conduct robust, repeatable assessments of hydrogen safety, hazards, and risk. HyRAM is envisioned as a unifying platform combining validated, analytical models of hydrogen behavior, a stan- dardized, transparent QRA approach, and engineering models and generic data for hydrogen installations. HyRAM is being developed at Sandia National Laboratories for the U. S. De- partment of Energy to increase access to technical data about hydrogen safety andmore » to enable the use of that data to support development and revision of national and international codes and standards. This document provides a description of the methodology and models contained in the HyRAM version 1.1. HyRAM 1.1 includes generic probabilities for hydrogen equipment fail- ures, probabilistic models for the impact of heat flux on humans and structures, and computa- tionally and experimentally validated analytical and first order models of hydrogen release and flame physics. HyRAM 1.1 integrates deterministic and probabilistic models for quantifying accident scenarios, predicting physical effects, and characterizing hydrogen hazards (thermal effects from jet fires, overpressure effects from deflagrations), and assessing impact on people and structures. HyRAM is a prototype software in active development and thus the models and data may change. This report will be updated at appropriate developmental intervals.« less

A new discriminative kernel from probabilistic models.

PubMed

Tsuda, Koji; Kawanabe, Motoaki; Rätsch, Gunnar; Sonnenburg, Sören; Müller, Klaus-Robert

2002-10-01

Recently, Jaakkola and Haussler (1999) proposed a method for constructing kernel functions from probabilistic models. Their so-called Fisher kernel has been combined with discriminative classifiers such as support vector machines and applied successfully in, for example, DNA and protein analysis. Whereas the Fisher kernel is calculated from the marginal log-likelihood, we propose the TOP kernel derived; from tangent vectors of posterior log-odds. Furthermore, we develop a theoretical framework on feature extractors from probabilistic models and use it for analyzing the TOP kernel. In experiments, our new discriminative TOP kernel compares favorably to the Fisher kernel.

Probabilistic assessment of uncertain adaptive hybrid composites

NASA Technical Reports Server (NTRS)

Shiao, Michael C.; Singhal, Surendra N.; Chamis, Christos C.

1994-01-01

Adaptive composite structures using actuation materials, such as piezoelectric fibers, were assessed probabilistically utilizing intraply hybrid composite mechanics in conjunction with probabilistic composite structural analysis. Uncertainties associated with the actuation material as well as the uncertainties in the regular (traditional) composite material properties were quantified and considered in the assessment. Static and buckling analyses were performed for rectangular panels with various boundary conditions and different control arrangements. The probability density functions of the structural behavior, such as maximum displacement and critical buckling load, were computationally simulated. The results of the assessment indicate that improved design and reliability can be achieved with actuation material.

On the security of a novel probabilistic signature based on bilinear square Diffie-Hellman problem and its extension.

PubMed

Zhao, Zhenguo; Shi, Wenbo

2014-01-01

Probabilistic signature scheme has been widely used in modern electronic commerce since it could provide integrity, authenticity, and nonrepudiation. Recently, Wu and Lin proposed a novel probabilistic signature (PS) scheme using the bilinear square Diffie-Hellman (BSDH) problem. They also extended it to a universal designated verifier signature (UDVS) scheme. In this paper, we analyze the security of Wu et al.'s PS scheme and UDVS scheme. Through concrete attacks, we demonstrate both of their schemes are not unforgeable. The security analysis shows that their schemes are not suitable for practical applications.

Probabilistic Fatigue Damage Prognosis Using a Surrogate Model Trained Via 3D Finite Element Analysis

NASA Technical Reports Server (NTRS)

Leser, Patrick E.; Hochhalter, Jacob D.; Newman, John A.; Leser, William P.; Warner, James E.; Wawrzynek, Paul A.; Yuan, Fuh-Gwo

2015-01-01

Utilizing inverse uncertainty quantification techniques, structural health monitoring can be integrated with damage progression models to form probabilistic predictions of a structure's remaining useful life. However, damage evolution in realistic structures is physically complex. Accurately representing this behavior requires high-fidelity models which are typically computationally prohibitive. In the present work, a high-fidelity finite element model is represented by a surrogate model, reducing computation times. The new approach is used with damage diagnosis data to form a probabilistic prediction of remaining useful life for a test specimen under mixed-mode conditions.

Probabilistic Analysis of Radiation Doses for Shore-Based Individuals in Operation Tomodachi

DTIC Science & Technology

2013-05-01

Based Upon Oxygen Consumption Rates. EPA/600/R-06/129F, U.S. Environmental Protection Agency, Washington, D.C. May. USEPA (U.S. Environmental...pascal (Pa) pound-force per square inch (psi) 6.894 757 × 103 pascal (Pa) Angle/ Temperature /Time hour (h) 3.6 × 103 second (s) degree of arc (o...equivalent and effective dose is the sievert (Sv). (1 Sv = 1 J kg–1). 1 DTRA-TR-12-002: Probabilistic Analysis of Radiation Doses for Shore-Based

Dynamic competitive probabilistic principal components analysis.

PubMed

López-Rubio, Ezequiel; Ortiz-DE-Lazcano-Lobato, Juan Miguel

2009-04-01

We present a new neural model which extends the classical competitive learning (CL) by performing a Probabilistic Principal Components Analysis (PPCA) at each neuron. The model also has the ability to learn the number of basis vectors required to represent the principal directions of each cluster, so it overcomes a drawback of most local PCA models, where the dimensionality of a cluster must be fixed a priori. Experimental results are presented to show the performance of the network with multispectral image data.

Structural system reliability calculation using a probabilistic fault tree analysis method

NASA Technical Reports Server (NTRS)

Torng, T. Y.; Wu, Y.-T.; Millwater, H. R.

1992-01-01

The development of a new probabilistic fault tree analysis (PFTA) method for calculating structural system reliability is summarized. The proposed PFTA procedure includes: developing a fault tree to represent the complex structural system, constructing an approximation function for each bottom event, determining a dominant sampling sequence for all bottom events, and calculating the system reliability using an adaptive importance sampling method. PFTA is suitable for complicated structural problems that require computer-intensive computer calculations. A computer program has been developed to implement the PFTA.

Probabilistic Survivability Versus Time Modeling

NASA Technical Reports Server (NTRS)

Joyner, James J., Sr.

2016-01-01

This presentation documents Kennedy Space Center's Independent Assessment work completed on three assessments for the Ground Systems Development and Operations (GSDO) Program to assist the Chief Safety and Mission Assurance Officer during key programmatic reviews and provided the GSDO Program with analyses of how egress time affects the likelihood of astronaut and ground worker survival during an emergency. For each assessment, a team developed probability distributions for hazard scenarios to address statistical uncertainty, resulting in survivability plots over time. The first assessment developed a mathematical model of probabilistic survivability versus time to reach a safe location using an ideal Emergency Egress System at Launch Complex 39B (LC-39B); the second used the first model to evaluate and compare various egress systems under consideration at LC-39B. The third used a modified LC-39B model to determine if a specific hazard decreased survivability more rapidly than other events during flight hardware processing in Kennedy's Vehicle Assembly Building.

NESSUS/NASTRAN Interface

NASA Technical Reports Server (NTRS)

Millwater, Harry; Riha, David

1996-01-01

The NESSUS probabilistic analysis computer program has been developed with a built-in finite element analysis program NESSUS/FEM. However, the NESSUS/FEM program is specialized for engine structures and may not contain sufficient features for other applications. In addition, users often become well acquainted with a particular finite element code and want to use that code for probabilistic structural analysis. For these reasons, this work was undertaken to develop an interface between NESSUS and NASTRAN such that NASTRAN can be used for the finite element analysis and NESSUS can be used for the probabilistic analysis. In addition, NESSUS was restructured such that other finite element codes could be more easily coupled with NESSUS. NESSUS has been enhanced such that NESSUS will modify the NASTRAN input deck for a given set of random variables, run NASTRAN and read the NASTRAN result. The coordination between the two codes is handled automatically. The work described here was implemented within NESSUS 6.2 which was delivered to NASA in September 1995. The code runs on Unix machines: Cray, HP, Sun, SGI and IBM. The new capabilities have been implemented such that a user familiar with NESSUS using NESSUS/FEM and NASTRAN can immediately use NESSUS with NASTRAN. In other words, the interface with NASTRAN has been implemented in an analogous manner to the interface with NESSUS/FEM. Only finite element specific input has been changed. This manual is written as an addendum to the existing NESSUS 6.2 manuals. We assume users have access to NESSUS manuals and are familiar with the operation of NESSUS including probabilistic finite element analysis. Update pages to the NESSUS PFEM manual are contained in Appendix E. The finite element features of the code and the probalistic analysis capabilities are summarized.

Confirming criticality safety of TRU waste with neutron measurements and risk analyses

DOE Office of Scientific and Technical Information (OSTI.GOV)

Winn, W.G.; Hochel, R.D.

1992-04-01

The criticality safety of {sup 239}Pu in 55-gallon drums stored in TRU waste containers (culverts) is confirmed using NDA neutron measurements and risk analyses. The neutron measurements yield a {sup 239}Pu mass and k{sub eff} for a culvert, which contains up to 14 drums. Conservative probabilistic risk analyses were developed for both drums and culverts. Overall {sup 239}Pu mass estimates are less than a calculated safety limit of 2800 g per culvert. The largest measured k{sub eff} is 0.904. The largest probability for a critical drum is 6.9 {times} 10{sup {minus}8} and that for a culvert is 1.72 {times} 10{supmore » {minus}7}. All examined suspect culverts, totaling 118 in number, are appraised as safe based on these observations.« less

Probabilistic analysis of preload in the abutment screw of a dental implant complex.

PubMed

Guda, Teja; Ross, Thomas A; Lang, Lisa A; Millwater, Harry R

2008-09-01

Screw loosening is a problem for a percentage of implants. A probabilistic analysis to determine the cumulative probability distribution of the preload, the probability of obtaining an optimal preload, and the probabilistic sensitivities identifying important variables is lacking. The purpose of this study was to examine the inherent variability of material properties, surface interactions, and applied torque in an implant system to determine the probability of obtaining desired preload values and to identify the significant variables that affect the preload. Using software programs, an abutment screw was subjected to a tightening torque and the preload was determined from finite element (FE) analysis. The FE model was integrated with probabilistic analysis software. Two probabilistic analysis methods (advanced mean value and Monte Carlo sampling) were applied to determine the cumulative distribution function (CDF) of preload. The coefficient of friction, elastic moduli, Poisson's ratios, and applied torque were modeled as random variables and defined by probability distributions. Separate probability distributions were determined for the coefficient of friction in well-lubricated and dry environments. The probabilistic analyses were performed and the cumulative distribution of preload was determined for each environment. A distinct difference was seen between the preload probability distributions generated in a dry environment (normal distribution, mean (SD): 347 (61.9) N) compared to a well-lubricated environment (normal distribution, mean (SD): 616 (92.2) N). The probability of obtaining a preload value within the target range was approximately 54% for the well-lubricated environment and only 0.02% for the dry environment. The preload is predominately affected by the applied torque and coefficient of friction between the screw threads and implant bore at lower and middle values of the preload CDF, and by the applied torque and the elastic modulus of the abutment screw at high values of the preload CDF. Lubrication at the threaded surfaces between the abutment screw and implant bore affects the preload developed in the implant complex. For the well-lubricated surfaces, only approximately 50% of implants will have preload values within the generally accepted range. This probability can be improved by applying a higher torque than normally recommended or a more closely controlled torque than typically achieved. It is also suggested that materials with higher elastic moduli be used in the manufacture of the abutment screw to achieve a higher preload.

Base-Rate Neglect as a Function of Base Rates in Probabilistic Contingency Learning

ERIC Educational Resources Information Center

Kutzner, Florian; Freytag, Peter; Vogel, Tobias; Fiedler, Klaus

2008-01-01

When humans predict criterion events based on probabilistic predictors, they often lend excessive weight to the predictor and insufficient weight to the base rate of the criterion event. In an operant analysis, using a matching-to-sample paradigm, Goodie and Fantino (1996) showed that humans exhibit base-rate neglect when predictors are associated…

Mixture Modeling for Background and Sources Separation in x-ray Astronomical Images

NASA Astrophysics Data System (ADS)

Guglielmetti, Fabrizia; Fischer, Rainer; Dose, Volker

2004-11-01

A probabilistic technique for the joint estimation of background and sources in high-energy astrophysics is described. Bayesian probability theory is applied to gain insight into the coexistence of background and sources through a probabilistic two-component mixture model, which provides consistent uncertainties of background and sources. The present analysis is applied to ROSAT PSPC data (0.1-2.4 keV) in Survey Mode. A background map is modelled using a Thin-Plate spline. Source probability maps are obtained for each pixel (45 arcsec) independently and for larger correlation lengths, revealing faint and extended sources. We will demonstrate that the described probabilistic method allows for detection improvement of faint extended celestial sources compared to the Standard Analysis Software System (SASS) used for the production of the ROSAT All-Sky Survey (RASS) catalogues.

Elasto-limited plastic analysis of structures for probabilistic conditions

NASA Astrophysics Data System (ADS)

Movahedi Rad, M.

2018-06-01

With applying plastic analysis and design methods, significant saving in material can be obtained. However, as a result of this benefit excessive plastic deformations and large residual displacements might develop, which in turn might lead to unserviceability and collapse of the structure. In this study, for deterministic problem the residual deformation of structures is limited by considering a constraint on the complementary strain energy of the residual forces. For probabilistic problem the constraint for the complementary strain energy of the residual forces is given randomly and critical stresses updated during the iteration. Limit curves are presented for the plastic limit load factors. The results show that these constraints have significant effects on the load factors. The formulations of the deterministic and probabilistic problems lead to mathematical programming which are solved by the use of nonlinear algorithm.

Climate and change: simulating flooding impacts on urban transport network

NASA Astrophysics Data System (ADS)

Pregnolato, Maria; Ford, Alistair; Dawson, Richard

2015-04-01

National-scale climate projections indicate that in the future there will be hotter and drier summers, warmer and wetter winters, together with rising sea levels. The frequency of extreme weather events is expected to increase, causing severe damage to the built environment and disruption of infrastructures (Dawson, 2007), whilst population growth and changed demographics are placing new demands on urban infrastructure. It is therefore essential to ensure infrastructure networks are robust to these changes. This research addresses these challenges by focussing on the development of probabilistic tools for managing risk by modelling urban transport networks within the context of extreme weather events. This paper presents a methodology to investigate the impacts of extreme weather events on urban environment, in particular infrastructure networks, through a combination of climate simulations and spatial representations. By overlaying spatial data on hazard thresholds from a flood model and a flood safety function, mitigated by potential adaptation strategies, different levels of disruption to commuting journeys on road networks are evaluated. The method follows the Catastrophe Modelling approach and it consists of a spatial model, combining deterministic loss models and probabilistic risk assessment techniques. It can be applied to present conditions as well as future uncertain scenarios, allowing the examination of the impacts alongside socio-economic and climate changes. The hazard is determined by simulating free surface water flooding, with the software CityCAT (Glenis et al., 2013). The outputs are overlapped to the spatial locations of a simple network model in GIS, which uses journey-to-work (JTW) observations, supplemented with speed and capacity information. To calculate the disruptive effect of flooding on transport networks, a function relating water depth to safe driving car speed has been developed by combining data from experimental reports (Morris et al., 2011) safety literature (Great Britain Department for Transport, 1999), analysis of videos of cars driving through floodwater, and expert judgement. A preliminary analysis has been run in the Tyne & Wear (in North-East England) region to demonstrate how the analysis can be used to assess the disruptions for commuter journeys due to flooding and will be demonstrated in this paper. The research will also investigate the effectiveness of adaptation strategies for extreme rainfall events, such as permeable surfaces and roof storages for buildings. Multiple scenarios (from the every-day-rainfall to the extreme weather phenomena) will be modelled, with different rainfall rates, rainfall durations and return periods. The comparison between the scenarios in which no interventions are adopted and those improved by one of the adaptation option will be compared to determine the cost-effectiveness of the solution considered. Integrating spatial analysis of transport use with an urban flood model and flood safety function enables the investigation of the impacts of extreme weather on infrastructure networks. Further work will develop the analysis in a number of ways (i) testing a range of flood events with different severity and frequency, (ii) exploration of the influence of climate and socio-economic change (iii) analysis of multiple hazard events and (iv) consideration of cascading disruption across different infrastructure networks.

Design for cyclic loading endurance of composites

NASA Technical Reports Server (NTRS)

Shiao, Michael C.; Murthy, Pappu L. N.; Chamis, Christos C.; Liaw, Leslie D. G.

1993-01-01

The application of the computer code IPACS (Integrated Probabilistic Assessment of Composite Structures) to aircraft wing type structures is described. The code performs a complete probabilistic analysis for composites taking into account the uncertainties in geometry, boundary conditions, material properties, laminate lay-ups, and loads. Results of the analysis are presented in terms of cumulative distribution functions (CDF) and probability density function (PDF) of the fatigue life of a wing type composite structure under different hygrothermal environments subjected to the random pressure. The sensitivity of the fatigue life to a number of critical structural/material variables is also computed from the analysis.

"What--me worry?" "Why so serious?": a personal view on the Fukushima nuclear reactor accidents.

PubMed

Gallucci, Raymond

2012-09-01

Infrequently, it seems that a significant accident precursor or, worse, an actual accident, involving a commercial nuclear power reactor occurs to remind us of the need to reexamine the safety of this important electrical power technology from a risk perspective. Twenty-five years since the major core damage accident at Chernobyl in the Ukraine, the Fukushima reactor complex in Japan experienced multiple core damages as a result of an earthquake-induced tsunami beyond either the earthquake or tsunami design basis for the site. Although the tsunami itself killed tens of thousands of people and left the area devastated and virtually uninhabitable, much concern still arose from the potential radioactive releases from the damaged reactors, even though there was little population left in the area to be affected. As a lifelong probabilistic safety analyst in nuclear engineering, even I must admit to a recurrence of the doubt regarding nuclear power safety after Fukushima that I had experienced after Three Mile Island and Chernobyl. This article is my attempt to "recover" my personal perspective on acceptable risk by examining both the domestic and worldwide history of commercial nuclear power plant accidents and attempting to quantify the risk in terms of the frequency of core damage that one might glean from a review of operational history. © 2012 Society for Risk Analysis.

A review for identification of initiating events in event tree development process on nuclear power plants

DOE Office of Scientific and Technical Information (OSTI.GOV)

Riyadi, Eko H., E-mail: e.riyadi@bapeten.go.id

2014-09-30

Initiating event is defined as any event either internal or external to the nuclear power plants (NPPs) that perturbs the steady state operation of the plant, if operating, thereby initiating an abnormal event such as transient or loss of coolant accident (LOCA) within the NPPs. These initiating events trigger sequences of events that challenge plant control and safety systems whose failure could potentially lead to core damage or large early release. Selection for initiating events consists of two steps i.e. first step, definition of possible events, such as by evaluating a comprehensive engineering, and by constructing a top level logicmore » model. Then the second step, grouping of identified initiating event's by the safety function to be performed or combinations of systems responses. Therefore, the purpose of this paper is to discuss initiating events identification in event tree development process and to reviews other probabilistic safety assessments (PSA). The identification of initiating events also involves the past operating experience, review of other PSA, failure mode and effect analysis (FMEA), feedback from system modeling, and master logic diagram (special type of fault tree). By using the method of study for the condition of the traditional US PSA categorization in detail, could be obtained the important initiating events that are categorized into LOCA, transients and external events.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grabaskas, David; Brunett, Acacia J.; Passerini, Stefano

GE Hitachi Nuclear Energy (GEH) and Argonne National Laboratory (Argonne) participated in a two year collaboration to modernize and update the probabilistic risk assessment (PRA) for the PRISM sodium fast reactor. At a high level, the primary outcome of the project was the development of a next-generation PRA that is intended to enable risk-informed prioritization of safety- and reliability-focused research and development. A central Argonne task during this project was a reliability assessment of passive safety systems, which included the Reactor Vessel Auxiliary Cooling System (RVACS) and the inherent reactivity feedbacks of the metal fuel core. Both systems were examinedmore » utilizing a methodology derived from the Reliability Method for Passive Safety Functions (RMPS), with an emphasis on developing success criteria based on mechanistic system modeling while also maintaining consistency with the Fuel Damage Categories (FDCs) of the mechanistic source term assessment. This paper provides an overview of the reliability analyses of both systems, including highlights of the FMEAs, the construction of best-estimate models, uncertain parameter screening and propagation, and the quantification of system failure probability. In particular, special focus is given to the methodologies to perform the analysis of uncertainty propagation and the determination of the likelihood of violating FDC limits. Additionally, important lessons learned are also reviewed, such as optimal sampling methodologies for the discovery of low likelihood failure events and strategies for the combined treatment of aleatory and epistemic uncertainties.« less

Systems Reliability Framework for Surface Water Sustainability and Risk Management

NASA Astrophysics Data System (ADS)

Myers, J. R.; Yeghiazarian, L.

2016-12-01

With microbial contamination posing a serious threat to the availability of clean water across the world, it is necessary to develop a framework that evaluates the safety and sustainability of water systems in respect to non-point source fecal microbial contamination. The concept of water safety is closely related to the concept of failure in reliability theory. In water quality problems, the event of failure can be defined as the concentration of microbial contamination exceeding a certain standard for usability of water. It is pertinent in watershed management to know the likelihood of such an event of failure occurring at a particular point in space and time. Microbial fate and transport are driven by environmental processes taking place in complex, multi-component, interdependent environmental systems that are dynamic and spatially heterogeneous, which means these processes and therefore their influences upon microbial transport must be considered stochastic and variable through space and time. A physics-based stochastic model of microbial dynamics is presented that propagates uncertainty using a unique sampling method based on artificial neural networks to produce a correlation between watershed characteristics and spatial-temporal probabilistic patterns of microbial contamination. These results are used to address the question of water safety through several sustainability metrics: reliability, vulnerability, resilience and a composite sustainability index. System reliability is described uniquely though the temporal evolution of risk along watershed points or pathways. Probabilistic resilience describes how long the system is above a certain probability of failure, and the vulnerability metric describes how the temporal evolution of risk changes throughout a hierarchy of failure levels. Additionally our approach allows for the identification of contributions in microbial contamination and uncertainty from specific pathways and sources. We expect that this framework will significantly improve the efficiency and precision of sustainable watershed management strategies through providing a better understanding of how watershed characteristics and environmental parameters affect surface water quality and sustainability. With microbial contamination posing a serious threat to the availability of clean water across the world, it is necessary to develop a framework that evaluates the safety and sustainability of water systems in respect to non-point source fecal microbial contamination. The concept of water safety is closely related to the concept of failure in reliability theory. In water quality problems, the event of failure can be defined as the concentration of microbial contamination exceeding a certain standard for usability of water. It is pertinent in watershed management to know the likelihood of such an event of failure occurring at a particular point in space and time. Microbial fate and transport are driven by environmental processes taking place in complex, multi-component, interdependent environmental systems that are dynamic and spatially heterogeneous, which means these processes and therefore their influences upon microbial transport must be considered stochastic and variable through space and time. A physics-based stochastic model of microbial dynamics is presented that propagates uncertainty using a unique sampling method based on artificial neural networks to produce a correlation between watershed characteristics and spatial-temporal probabilistic patterns of microbial contamination. These results are used to address the question of water safety through several sustainability metrics: reliability, vulnerability, resilience and a composite sustainability index. System reliability is described uniquely though the temporal evolution of risk along watershed points or pathways. Probabilistic resilience describes how long the system is above a certain probability of failure, and the vulnerability metric describes how the temporal evolution of risk changes throughout a hierarchy of failure levels. Additionally our approach allows for the identification of contributions in microbial contamination and uncertainty from specific pathways and sources. We expect that this framework will significantly improve the efficiency and precision of sustainable watershed management strategies through providing a better understanding of how watershed characteristics and environmental parameters affect surface water quality and sustainability.

Un regard international sur la sécurité nucléaire

NASA Astrophysics Data System (ADS)

Birkhofer, Adolf

2002-10-01

Safety has always been an important objective in nuclear technology. Starting with a set of sound physical principles and prudent design approaches, safety concepts have gradually been refined and cover now a wide range of provisions related to design, quality and operation. Research, the evaluation of operating experiences and probabilistic risk assessments constitute an essential basis and international co-operation plays a significant role in that context. Concerning future developments a major objective for new reactor concepts, such as the EPR, is to practically exclude a severe core damage accident with large scale consequences outside the plant. To cite this article: A. Birkhofer, C. R. Physique 3 (2002) 1059-1065.

Economic Analysis of a Multi-Site Prevention Program: Assessment of Program Costs and Characterizing Site-level Variability

PubMed Central

Corso, Phaedra S.; Ingels, Justin B.; Kogan, Steven M.; Foster, E. Michael; Chen, Yi-Fu; Brody, Gene H.

2013-01-01

Programmatic cost analyses of preventive interventions commonly have a number of methodological difficulties. To determine the mean total costs and properly characterize variability, one often has to deal with small sample sizes, skewed distributions, and especially missing data. Standard approaches for dealing with missing data such as multiple imputation may suffer from a small sample size, a lack of appropriate covariates, or too few details around the method used to handle the missing data. In this study, we estimate total programmatic costs for a prevention trial evaluating the Strong African American Families-Teen program. This intervention focuses on the prevention of substance abuse and risky sexual behavior. To account for missing data in the assessment of programmatic costs we compare multiple imputation to probabilistic sensitivity analysis. The latter approach uses collected cost data to create a distribution around each input parameter. We found that with the multiple imputation approach, the mean (95% confidence interval) incremental difference was $2149 ($397, $3901). With the probabilistic sensitivity analysis approach, the incremental difference was $2583 ($778, $4346). Although the true cost of the program is unknown, probabilistic sensitivity analysis may be a more viable alternative for capturing variability in estimates of programmatic costs when dealing with missing data, particularly with small sample sizes and the lack of strong predictor variables. Further, the larger standard errors produced by the probabilistic sensitivity analysis method may signal its ability to capture more of the variability in the data, thus better informing policymakers on the potentially true cost of the intervention. PMID:23299559

Economic analysis of a multi-site prevention program: assessment of program costs and characterizing site-level variability.

PubMed

Corso, Phaedra S; Ingels, Justin B; Kogan, Steven M; Foster, E Michael; Chen, Yi-Fu; Brody, Gene H

2013-10-01

Programmatic cost analyses of preventive interventions commonly have a number of methodological difficulties. To determine the mean total costs and properly characterize variability, one often has to deal with small sample sizes, skewed distributions, and especially missing data. Standard approaches for dealing with missing data such as multiple imputation may suffer from a small sample size, a lack of appropriate covariates, or too few details around the method used to handle the missing data. In this study, we estimate total programmatic costs for a prevention trial evaluating the Strong African American Families-Teen program. This intervention focuses on the prevention of substance abuse and risky sexual behavior. To account for missing data in the assessment of programmatic costs we compare multiple imputation to probabilistic sensitivity analysis. The latter approach uses collected cost data to create a distribution around each input parameter. We found that with the multiple imputation approach, the mean (95 % confidence interval) incremental difference was $2,149 ($397, $3,901). With the probabilistic sensitivity analysis approach, the incremental difference was $2,583 ($778, $4,346). Although the true cost of the program is unknown, probabilistic sensitivity analysis may be a more viable alternative for capturing variability in estimates of programmatic costs when dealing with missing data, particularly with small sample sizes and the lack of strong predictor variables. Further, the larger standard errors produced by the probabilistic sensitivity analysis method may signal its ability to capture more of the variability in the data, thus better informing policymakers on the potentially true cost of the intervention.

Probabilistic grammatical model for helix‐helix contact site classification

PubMed Central

2013-01-01

Background Hidden Markov Models power many state‐of‐the‐art tools in the field of protein bioinformatics. While excelling in their tasks, these methods of protein analysis do not convey directly information on medium‐ and long‐range residue‐residue interactions. This requires an expressive power of at least context‐free grammars. However, application of more powerful grammar formalisms to protein analysis has been surprisingly limited. Results In this work, we present a probabilistic grammatical framework for problem‐specific protein languages and apply it to classification of transmembrane helix‐helix pairs configurations. The core of the model consists of a probabilistic context‐free grammar, automatically inferred by a genetic algorithm from only a generic set of expert‐based rules and positive training samples. The model was applied to produce sequence based descriptors of four classes of transmembrane helix‐helix contact site configurations. The highest performance of the classifiers reached AUCROC of 0.70. The analysis of grammar parse trees revealed the ability of representing structural features of helix‐helix contact sites. Conclusions We demonstrated that our probabilistic context‐free framework for analysis of protein sequences outperforms the state of the art in the task of helix‐helix contact site classification. However, this is achieved without necessarily requiring modeling long range dependencies between interacting residues. A significant feature of our approach is that grammar rules and parse trees are human‐readable. Thus they could provide biologically meaningful information for molecular biologists. PMID:24350601

A Preliminary Study of the Application of Probabilistic Risk Assessment Techniques to High-Energy Laser Safety

DTIC Science & Technology

2001-12-01

32. Maxwell , J . R., & Beard, J . (1973). Bi-directional reflectance model validation and utilization. Tehnical Report AFAL-TR-73-303. Michigan... CECILIA MONTES DE OCA, Ist Lt, USAF Contract Monitor RICHARD L. MILLER, PhD Chief, Directed Energy Bioeffects Division Form Approved REPORT... J .. . a •. . . ......... ..... ... a.. •. l • • , 0.3 0.1 .. . .. . .. . . .. . . ......... ....... .. , 0.0 1 10 100 l000 Kinetic Energy, ft-ibf

Experimental Resource Allocation for Statistical Simulation of Fretting Fatigue Problem (Preprint)

DTIC Science & Technology

2012-08-01

Metals Branch Structural Materials Division Harry R. Millwater , Carolina Dubinsky, and Gulshan Singh University of Texas at San Antonio...GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 62102F 6. AUTHOR(S) Patrick Golden (AFRL/RXCM) Harry R. Millwater , Carolina Dubinsky, and Gulshan...Safety. 1996;54(2-3):133-144 [5] Golden, PJ, Millwater HR and Yang X. Probabilistic Fretting Fatigue Life Prediction of Ti-6Al-4V. International Journal

Long-term multi-hazard assessment for El Misti volcano (Peru)

NASA Astrophysics Data System (ADS)

Sandri, Laura; Thouret, Jean-Claude; Constantinescu, Robert; Biass, Sébastien; Tonini, Roberto

2014-02-01

We propose a long-term probabilistic multi-hazard assessment for El Misti Volcano, a composite cone located <20 km from Arequipa. The second largest Peruvian city is a rapidly expanding economic centre and is classified by UNESCO as World Heritage. We apply the Bayesian Event Tree code for Volcanic Hazard (BET_VH) to produce probabilistic hazard maps for the predominant volcanic phenomena that may affect c.900,000 people living around the volcano. The methodology accounts for the natural variability displayed by volcanoes in their eruptive behaviour, such as different types/sizes of eruptions and possible vent locations. For this purpose, we treat probabilistically several model runs for some of the main hazardous phenomena (lahars, pyroclastic density currents (PDCs), tephra fall and ballistic ejecta) and data from past eruptions at El Misti (tephra fall, PDCs and lahars) and at other volcanoes (PDCs). The hazard maps, although neglecting possible interactions among phenomena or cascade effects, have been produced with a homogeneous method and refer to a common time window of 1 year. The probability maps reveal that only the north and east suburbs of Arequipa are exposed to all volcanic threats except for ballistic ejecta, which are limited to the uninhabited but touristic summit cone. The probability for pyroclastic density currents reaching recently expanding urban areas and the city along ravines is around 0.05 %/year, similar to the probability obtained for roof-critical tephra loading during the rainy season. Lahars represent by far the most probable threat (around 10 %/year) because at least four radial drainage channels can convey them approximately 20 km away from the volcano across the entire city area in heavy rain episodes, even without eruption. The Río Chili Valley represents the major concern to city safety owing to the probable cascading effect of combined threats: PDCs and rockslides, dammed lake break-outs and subsequent lahars or floods. Although this study does not intend to replace the current El Misti hazard map, the quantitative results of this probabilistic multi-hazard assessment can be incorporated into a multi-risk analysis, to support decision makers in any future improvement of the current hazard evaluation, such as further land-use planning and possible emergency management.

Preliminary stochastic model for managing Vibrio parahaemolyticus and total viable bacterial counts in a Pacific oyster (Crassostrea gigas) supply chain.

PubMed

Fernandez-Piquer, Judith; Bowman, John P; Ross, Tom; Estrada-Flores, Silvia; Tamplin, Mark L

2013-07-01

Vibrio parahaemolyticus can accumulate and grow in oysters stored without refrigeration, representing a potential food safety risk. High temperatures during oyster storage can lead to an increase in total viable bacteria counts, decreasing product shelf life. Therefore, a predictive tool that allows the estimation of both V. parahaemolyticus populations and total viable bacteria counts in parallel is needed. A stochastic model was developed to quantitatively assess the populations of V. parahaemolyticus and total viable bacteria in Pacific oysters for six different supply chain scenarios. The stochastic model encompassed operations from oyster farms through consumers and was built using risk analysis software. Probabilistic distributions and predictions for the percentage of Pacific oysters containing V. parahaemolyticus and high levels of viable bacteria at the point of consumption were generated for each simulated scenario. This tool can provide valuable information about V. parahaemolyticus exposure and potential control measures and can help oyster companies and regulatory agencies evaluate the impact of product quality and safety during cold chain management. If coupled with suitable monitoring systems, such models could enable preemptive action to be taken to counteract unfavorable supply chain conditions.

A Framework for Probabilistic Evaluation of Interval Management Tolerance in the Terminal Radar Control Area

NASA Technical Reports Server (NTRS)

Hercencia-Zapana, Heber; Herencia-Zapana, Heber; Hagen, George E.; Neogi, Natasha

2012-01-01

Projections of future traffic in the national airspace show that most of the hub airports and their attendant airspace will need to undergo significant redevelopment and redesign in order to accommodate any significant increase in traffic volume. Even though closely spaced parallel approaches increase throughput into a given airport, controller workload in oversubscribed metroplexes is further taxed by these approaches that require stringent monitoring in a saturated environment. The interval management (IM) concept in the TRACON area is designed to shift some of the operational burden from the control tower to the flight deck, placing the flight crew in charge of implementing the required speed changes to maintain a relative spacing interval. The interval management tolerance is a measure of the allowable deviation from the desired spacing interval for the IM aircraft (and its target aircraft). For this complex task, Formal Methods can help to ensure better design and system implementation. In this paper, we propose a probabilistic framework to quantify the uncertainty and performance associated with the major components of the IM tolerance. The analytical basis for this framework may be used to formalize both correctness and probabilistic system safety claims in a modular fashion at the algorithmic level in a way compatible with several Formal Methods tools.

Fast probabilistic file fingerprinting for big data

PubMed Central

2013-01-01

Background Biological data acquisition is raising new challenges, both in data analysis and handling. Not only is it proving hard to analyze the data at the rate it is generated today, but simply reading and transferring data files can be prohibitively slow due to their size. This primarily concerns logistics within and between data centers, but is also important for workstation users in the analysis phase. Common usage patterns, such as comparing and transferring files, are proving computationally expensive and are tying down shared resources. Results We present an efficient method for calculating file uniqueness for large scientific data files, that takes less computational effort than existing techniques. This method, called Probabilistic Fast File Fingerprinting (PFFF), exploits the variation present in biological data and computes file fingerprints by sampling randomly from the file instead of reading it in full. Consequently, it has a flat performance characteristic, correlated with data variation rather than file size. We demonstrate that probabilistic fingerprinting can be as reliable as existing hashing techniques, with provably negligible risk of collisions. We measure the performance of the algorithm on a number of data storage and access technologies, identifying its strengths as well as limitations. Conclusions Probabilistic fingerprinting may significantly reduce the use of computational resources when comparing very large files. Utilisation of probabilistic fingerprinting techniques can increase the speed of common file-related workflows, both in the data center and for workbench analysis. The implementation of the algorithm is available as an open-source tool named pfff, as a command-line tool as well as a C library. The tool can be downloaded from http://biit.cs.ut.ee/pfff. PMID:23445565

Cost Effectiveness of Ofatumumab Plus Chlorambucil in First-Line Chronic Lymphocytic Leukaemia in Canada.

PubMed

Herring, William; Pearson, Isobel; Purser, Molly; Nakhaipour, Hamid Reza; Haiderali, Amin; Wolowacz, Sorrel; Jayasundara, Kavisha

2016-01-01

Our objective was to estimate the cost effectiveness of ofatumumab plus chlorambucil (OChl) versus chlorambucil in patients with chronic lymphocytic leukaemia for whom fludarabine-based therapies are considered inappropriate from the perspective of the publicly funded healthcare system in Canada. A semi-Markov model (3-month cycle length) used survival curves to govern progression-free survival (PFS) and overall survival (OS). Efficacy and safety data and health-state utility values were estimated from the COMPLEMENT-1 trial. Post-progression treatment patterns were based on clinical guidelines, Canadian treatment practices and published literature. Total and incremental expected lifetime costs (in Canadian dollars [$Can], year 2013 values), life-years and quality-adjusted life-years (QALYs) were computed. Uncertainty was assessed via deterministic and probabilistic sensitivity analyses. The discounted lifetime health and economic outcomes estimated by the model showed that, compared with chlorambucil, first-line treatment with OChl led to an increase in QALYs (0.41) and total costs ($Can27,866) and to an incremental cost-effectiveness ratio (ICER) of $Can68,647 per QALY gained. In deterministic sensitivity analyses, the ICER was most sensitive to the modelling time horizon and to the extrapolation of OS treatment effects beyond the trial duration. In probabilistic sensitivity analysis, the probability of cost effectiveness at a willingness-to-pay threshold of $Can100,000 per QALY gained was 59 %. Base-case results indicated that improved overall response and PFS for OChl compared with chlorambucil translated to improved quality-adjusted life expectancy. Sensitivity analysis suggested that OChl is likely to be cost effective subject to uncertainty associated with the presence of any long-term OS benefit and the model time horizon.

A PROBABILISTIC ARSENIC EXPOSURE ASSESSMENT FOR CHILDREN WHO CONTACT CHROMATED COPPER ARSENATE ( CAA )-TREATED PLAYSETS AND DECKS: PART 2 SENSITIVITY AND UNCERTAINTY ANALYSIS

EPA Science Inventory

A probabilistic model (SHEDS-Wood) was developed to examine children's exposure and dose to chromated copper arsenate (CCA)-treated wood, as described in Part 1 of this two part paper. This Part 2 paper discusses sensitivity and uncertainty analyses conducted to assess the key m...

Development of probabilistic emission inventories of air toxics for Jacksonville, Florida, USA.

PubMed

Zhao, Yuchao; Frey, H Christopher

2004-11-01

Probabilistic emission inventories were developed for 1,3-butadiene, mercury (Hg), arsenic (As), benzene, formaldehyde, and lead for Jacksonville, FL. To quantify inter-unit variability in empirical emission factor data, the Maximum Likelihood Estimation (MLE) method or the Method of Matching Moments was used to fit parametric distributions. For data sets that contain nondetected measurements, a method based upon MLE was used for parameter estimation. To quantify the uncertainty in urban air toxic emission factors, parametric bootstrap simulation and empirical bootstrap simulation were applied to uncensored and censored data, respectively. The probabilistic emission inventories were developed based on the product of the uncertainties in the emission factors and in the activity factors. The uncertainties in the urban air toxics emission inventories range from as small as -25 to +30% for Hg to as large as -83 to +243% for As. The key sources of uncertainty in the emission inventory for each toxic are identified based upon sensitivity analysis. Typically, uncertainty in the inventory of a given pollutant can be attributed primarily to a small number of source categories. Priorities for improving the inventories and for refining the probabilistic analysis are discussed.

Shear-wave velocity-based probabilistic and deterministic assessment of seismic soil liquefaction potential

USGS Publications Warehouse

Kayen, R.; Moss, R.E.S.; Thompson, E.M.; Seed, R.B.; Cetin, K.O.; Der Kiureghian, A.; Tanaka, Y.; Tokimatsu, K.

2013-01-01

Shear-wave velocity (Vs) offers a means to determine the seismic resistance of soil to liquefaction by a fundamental soil property. This paper presents the results of an 11-year international project to gather new Vs site data and develop probabilistic correlations for seismic soil liquefaction occurrence. Toward that objective, shear-wave velocity test sites were identified, and measurements made for 301 new liquefaction field case histories in China, Japan, Taiwan, Greece, and the United States over a decade. The majority of these new case histories reoccupy those previously investigated by penetration testing. These new data are combined with previously published case histories to build a global catalog of 422 case histories of Vs liquefaction performance. Bayesian regression and structural reliability methods facilitate a probabilistic treatment of the Vs catalog for performance-based engineering applications. Where possible, uncertainties of the variables comprising both the seismic demand and the soil capacity were estimated and included in the analysis, resulting in greatly reduced overall model uncertainty relative to previous studies. The presented data set and probabilistic analysis also help resolve the ancillary issues of adjustment for soil fines content and magnitude scaling factors.

CPT-based probabilistic and deterministic assessment of in situ seismic soil liquefaction potential

USGS Publications Warehouse

Moss, R.E.S.; Seed, R.B.; Kayen, R.E.; Stewart, J.P.; Der Kiureghian, A.; Cetin, K.O.

2006-01-01

This paper presents a complete methodology for both probabilistic and deterministic assessment of seismic soil liquefaction triggering potential based on the cone penetration test (CPT). A comprehensive worldwide set of CPT-based liquefaction field case histories were compiled and back analyzed, and the data then used to develop probabilistic triggering correlations. Issues investigated in this study include improved normalization of CPT resistance measurements for the influence of effective overburden stress, and adjustment to CPT tip resistance for the potential influence of "thin" liquefiable layers. The effects of soil type and soil character (i.e., "fines" adjustment) for the new correlations are based on a combination of CPT tip and sleeve resistance. To quantify probability for performancebased engineering applications, Bayesian "regression" methods were used, and the uncertainties of all variables comprising both the seismic demand and the liquefaction resistance were estimated and included in the analysis. The resulting correlations were developed using a Bayesian framework and are presented in both probabilistic and deterministic formats. The results are compared to previous probabilistic and deterministic correlations. ?? 2006 ASCE.

Developing a Methodology for Eliciting Subjective Probability Estimates During Expert Evaluations of Safety Interventions: Application for Bayesian Belief Networks

NASA Technical Reports Server (NTRS)

Wiegmann, Douglas A.a

2005-01-01

The NASA Aviation Safety Program (AvSP) has defined several products that will potentially modify airline and/or ATC operations, enhance aircraft systems, and improve the identification of potential hazardous situations within the National Airspace System (NAS). Consequently, there is a need to develop methods for evaluating the potential safety benefit of each of these intervention products so that resources can be effectively invested to produce the judgments to develop Bayesian Belief Networks (BBN's) that model the potential impact that specific interventions may have. Specifically, the present report summarizes methodologies for improving the elicitation of probability estimates during expert evaluations of AvSP products for use in BBN's. The work involved joint efforts between Professor James Luxhoj from Rutgers University and researchers at the University of Illinois. The Rutgers' project to develop BBN's received funding by NASA entitled "Probabilistic Decision Support for Evaluating Technology Insertion and Assessing Aviation Safety System Risk." The proposed project was funded separately but supported the existing Rutgers' program.

On the Security of a Novel Probabilistic Signature Based on Bilinear Square Diffie-Hellman Problem and Its Extension

PubMed Central

Zhao, Zhenguo; Shi, Wenbo

2014-01-01

Probabilistic signature scheme has been widely used in modern electronic commerce since it could provide integrity, authenticity, and nonrepudiation. Recently, Wu and Lin proposed a novel probabilistic signature (PS) scheme using the bilinear square Diffie-Hellman (BSDH) problem. They also extended it to a universal designated verifier signature (UDVS) scheme. In this paper, we analyze the security of Wu et al.'s PS scheme and UDVS scheme. Through concrete attacks, we demonstrate both of their schemes are not unforgeable. The security analysis shows that their schemes are not suitable for practical applications. PMID:25025083

A generative, probabilistic model of local protein structure.

PubMed

Boomsma, Wouter; Mardia, Kanti V; Taylor, Charles C; Ferkinghoff-Borg, Jesper; Krogh, Anders; Hamelryck, Thomas

2008-07-01

Despite significant progress in recent years, protein structure prediction maintains its status as one of the prime unsolved problems in computational biology. One of the key remaining challenges is an efficient probabilistic exploration of the structural space that correctly reflects the relative conformational stabilities. Here, we present a fully probabilistic, continuous model of local protein structure in atomic detail. The generative model makes efficient conformational sampling possible and provides a framework for the rigorous analysis of local sequence-structure correlations in the native state. Our method represents a significant theoretical and practical improvement over the widely used fragment assembly technique by avoiding the drawbacks associated with a discrete and nonprobabilistic approach.

Probabilistic Analysis of Large-Scale Composite Structures Using the IPACS Code

NASA Technical Reports Server (NTRS)

Lemonds, Jeffrey; Kumar, Virendra

1995-01-01

An investigation was performed to ascertain the feasibility of using IPACS (Integrated Probabilistic Assessment of Composite Structures) for probabilistic analysis of a composite fan blade, the development of which is being pursued by various industries for the next generation of aircraft engines. A model representative of the class of fan blades used in the GE90 engine has been chosen as the structural component to be analyzed with IPACS. In this study, typical uncertainties are assumed in the level, and structural responses for ply stresses and frequencies are evaluated in the form of cumulative probability density functions. Because of the geometric complexity of the blade, the number of plies varies from several hundred at the root to about a hundred at the tip. This represents a extremely complex composites application for the IPACS code. A sensitivity study with respect to various random variables is also performed.

Guided SAR image despeckling with probabilistic non local weights

NASA Astrophysics Data System (ADS)

Gokul, Jithin; Nair, Madhu S.; Rajan, Jeny

2017-12-01

SAR images are generally corrupted by granular disturbances called speckle, which makes visual analysis and detail extraction a difficult task. Non Local despeckling techniques with probabilistic similarity has been a recent trend in SAR despeckling. To achieve effective speckle suppression without compromising detail preservation, we propose an improvement for the existing Generalized Guided Filter with Bayesian Non-Local Means (GGF-BNLM) method. The proposed method (Guided SAR Image Despeckling with Probabilistic Non Local Weights) replaces parametric constants based on heuristics in GGF-BNLM method with dynamically derived values based on the image statistics for weight computation. Proposed changes make GGF-BNLM method adaptive and as a result, significant improvement is achieved in terms of performance. Experimental analysis on SAR images shows excellent speckle reduction without compromising feature preservation when compared to GGF-BNLM method. Results are also compared with other state-of-the-art and classic SAR depseckling techniques to demonstrate the effectiveness of the proposed method.

Probabilistic Structural Analysis Methods (PSAM) for select space propulsion system components, part 2

NASA Technical Reports Server (NTRS)

1991-01-01

The technical effort and computer code enhancements performed during the sixth year of the Probabilistic Structural Analysis Methods program are summarized. Various capabilities are described to probabilistically combine structural response and structural resistance to compute component reliability. A library of structural resistance models is implemented in the Numerical Evaluations of Stochastic Structures Under Stress (NESSUS) code that included fatigue, fracture, creep, multi-factor interaction, and other important effects. In addition, a user interface was developed for user-defined resistance models. An accurate and efficient reliability method was developed and was successfully implemented in the NESSUS code to compute component reliability based on user-selected response and resistance models. A risk module was developed to compute component risk with respect to cost, performance, or user-defined criteria. The new component risk assessment capabilities were validated and demonstrated using several examples. Various supporting methodologies were also developed in support of component risk assessment.

Probabilistic analysis of the torsional effects on the tall building resistance due to earthquake even

NASA Astrophysics Data System (ADS)

Králik, Juraj; Králik, Juraj

2017-07-01

The paper presents the results from the deterministic and probabilistic analysis of the accidental torsional effect of reinforced concrete tall buildings due to earthquake even. The core-column structural system was considered with various configurations in plane. The methodology of the seismic analysis of the building structures in Eurocode 8 and JCSS 2000 is discussed. The possibilities of the utilization the LHS method to analyze the extensive and robust tasks in FEM is presented. The influence of the various input parameters (material, geometry, soil, masses and others) is considered. The deterministic and probability analysis of the seismic resistance of the structure was calculated in the ANSYS program.

Task Decomposition in Human Reliability Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boring, Ronald Laurids; Joe, Jeffrey Clark

2014-06-01

In the probabilistic safety assessments (PSAs) used in the nuclear industry, human failure events (HFEs) are determined as a subset of hardware failures, namely those hardware failures that could be triggered by human action or inaction. This approach is top-down, starting with hardware faults and deducing human contributions to those faults. Elsewhere, more traditionally human factors driven approaches would tend to look at opportunities for human errors first in a task analysis and then identify which of those errors is risk significant. The intersection of top-down and bottom-up approaches to defining HFEs has not been carefully studied. Ideally, both approachesmore » should arrive at the same set of HFEs. This question remains central as human reliability analysis (HRA) methods are generalized to new domains like oil and gas. The HFEs used in nuclear PSAs tend to be top-down— defined as a subset of the PSA—whereas the HFEs used in petroleum quantitative risk assessments (QRAs) are more likely to be bottom-up—derived from a task analysis conducted by human factors experts. The marriage of these approaches is necessary in order to ensure that HRA methods developed for top-down HFEs are also sufficient for bottom-up applications.« less

Probabilistic Sizing and Verification of Space Ceramic Structures

NASA Astrophysics Data System (ADS)

Denaux, David; Ballhause, Dirk; Logut, Daniel; Lucarelli, Stefano; Coe, Graham; Laine, Benoit

2012-07-01

Sizing of ceramic parts is best optimised using a probabilistic approach which takes into account the preexisting flaw distribution in the ceramic part to compute a probability of failure of the part depending on the applied load, instead of a maximum allowable load as for a metallic part. This requires extensive knowledge of the material itself but also an accurate control of the manufacturing process. In the end, risk reduction approaches such as proof testing may be used to lower the final probability of failure of the part. Sizing and verification of ceramic space structures have been performed by Astrium for more than 15 years, both with Zerodur and SiC: Silex telescope structure, Seviri primary mirror, Herschel telescope, Formosat-2 instrument, and other ceramic structures flying today. Throughout this period of time, Astrium has investigated and developed experimental ceramic analysis tools based on the Weibull probabilistic approach. In the scope of the ESA/ESTEC study: “Mechanical Design and Verification Methodologies for Ceramic Structures”, which is to be concluded in the beginning of 2012, existing theories, technical state-of-the-art from international experts, and Astrium experience with probabilistic analysis tools have been synthesized into a comprehensive sizing and verification method for ceramics. Both classical deterministic and more optimised probabilistic methods are available, depending on the criticality of the item and on optimisation needs. The methodology, based on proven theory, has been successfully applied to demonstration cases and has shown its practical feasibility.

Airline Safety Improvement Through Experience with Near-Misses: A Cautionary Tale.

PubMed

Madsen, Peter; Dillon, Robin L; Tinsley, Catherine H

2016-05-01

In recent years, the U.S. commercial airline industry has achieved unprecedented levels of safety, with the statistical risk associated with U.S. commercial aviation falling to 0.003 fatalities per 100 million passengers. But decades of research on organizational learning show that success often breeds complacency and failure inspires improvement. With accidents as rare events, can the airline industry continue safety advancements? This question is complicated by the complex system in which the industry operates where chance combinations of multiple factors contribute to what are largely probabilistic (rather than deterministic) outcomes. Thus, some apparent successes are realized because of good fortune rather than good processes, and this research intends to bring attention to these events, the near-misses. The processes that create these near-misses could pose a threat if multiple contributing factors combine in adverse ways without the intervention of good fortune. Yet, near-misses (if recognized as such) can, theoretically, offer a mechanism for continuing safety improvements, above and beyond learning gleaned from observable failure. We test whether or not this learning is apparent in the airline industry. Using data from 1990 to 2007, fixed effects Poisson regressions show that airlines learn from accidents (their own and others), and from one category of near-misses-those where the possible dangers are salient. Unfortunately, airlines do not improve following near-miss incidents when the focal event has no clear warnings of significant danger. Therefore, while airlines need to and can learn from certain near-misses, we conclude with recommendations for improving airline learning from all near-misses. © 2015 Society for Risk Analysis.

Probabilistic/Fracture-Mechanics Model For Service Life

NASA Technical Reports Server (NTRS)

Watkins, T., Jr.; Annis, C. G., Jr.

1991-01-01

Computer program makes probabilistic estimates of lifetime of engine and components thereof. Developed to fill need for more accurate life-assessment technique that avoids errors in estimated lives and provides for statistical assessment of levels of risk created by engineering decisions in designing system. Implements mathematical model combining techniques of statistics, fatigue, fracture mechanics, nondestructive analysis, life-cycle cost analysis, and management of engine parts. Used to investigate effects of such engine-component life-controlling parameters as return-to-service intervals, stresses, capabilities for nondestructive evaluation, and qualities of materials.

Application of the Probabilistic Dynamic Synthesis Method to Realistic Structures

NASA Technical Reports Server (NTRS)

Brown, Andrew M.; Ferri, Aldo A.

1998-01-01

The Probabilistic Dynamic Synthesis method is a technique for obtaining the statistics of a desired response engineering quantity for a structure with non-deterministic parameters. The method uses measured data from modal testing of the structure as the input random variables, rather than more "primitive" quantities like geometry or material variation. This modal information is much more comprehensive and easily measured than the "primitive" information. The probabilistic analysis is carried out using either response surface reliability methods or Monte Carlo simulation. In previous work, the feasibility of the PDS method applied to a simple seven degree-of-freedom spring-mass system was verified. In this paper, extensive issues involved with applying the method to a realistic three-substructure system are examined, and free and forced response analyses are performed. The results from using the method are promising, especially when the lack of alternatives for obtaining quantitative output for probabilistic structures is considered.

Global assessment of predictability of water availability: A bivariate probabilistic Budyko analysis

NASA Astrophysics Data System (ADS)

Wang, Weiguang; Fu, Jianyu

2018-02-01

Estimating continental water availability is of great importance for water resources management, in terms of maintaining ecosystem integrity and sustaining society development. To more accurately quantify the predictability of water availability, on the basis of univariate probabilistic Budyko framework, a bivariate probabilistic Budyko approach was developed using copula-based joint distribution model for considering the dependence between parameter ω of Wang-Tang's equation and the Normalized Difference Vegetation Index (NDVI), and was applied globally. The results indicate the predictive performance in global water availability is conditional on the climatic condition. In comparison with simple univariate distribution, the bivariate one produces the lower interquartile range under the same global dataset, especially in the regions with higher NDVI values, highlighting the importance of developing the joint distribution by taking into account the dependence structure of parameter ω and NDVI, which can provide more accurate probabilistic evaluation of water availability.

Preclinical QT safety assessment: cross-species comparisons and human translation from an industry consortium.

PubMed

Holzgrefe, Henry; Ferber, Georg; Champeroux, Pascal; Gill, Michael; Honda, Masaki; Greiter-Wilke, Andrea; Baird, Theodore; Meyer, Olivier; Saulnier, Muriel

2014-01-01

In vivo models have been required to demonstrate relative cardiac safety, but model sensitivity has not been systematically investigated. Cross-species and human translation of repolarization delay, assessed as QT/QTc prolongation, has not been compared employing common methodologies across multiple species and sites. Therefore, the accurate translation of repolarization results within and between preclinical species, and to man, remains problematic. Six pharmaceutical companies entered into an informal consortium designed to collect high-resolution telemetered data in multiple species (dog; n=34, cynomolgus; n=37, minipig; n=12, marmoset; n=14, guinea pig; n=5, and man; n=57). All animals received vehicle and varying doses of moxifloxacin (3-100 mg/kg, p.o.) with telemetered ECGs (≥500 Hz) obtained for 20-24h post-dose. Individual probabilistic QT-RR relationships were derived for each subject. The rate-correction efficacies of the individual (QTca) and generic correction formulae (Bazett, Fridericia, and Van de Water) were objectively assessed as the mean squared slopes of the QTc-RR relationships. Normalized moxifloxacin QTca responses (Veh Δ%/μM) were derived for 1h centered on the moxifloxacin Tmax. All QT-RR ranges demonstrated probabilistic uncertainty; slopes varied distinctly by species where dog and human exhibited the lowest QT rate-dependence, which was much steeper in the cynomolgus and guinea pig. Incorporating probabilistic uncertainty, the normalized QTca-moxifloxacin responses were similarly conserved across all species, including man. The current results provide the first unambiguous evidence that all preclinical in vivo repolarization assays, when accurately modeled and evaluated, yield results that are consistent with the conservation of moxifloxacin-induced QT prolongation across all common preclinical species. Furthermore, these outcomes are directly transferable across all species including man. The consortium results indicate that the implementation of standardized QTc data presentation, QTc reference cycle lengths, and rate-correction coefficients can markedly improve the concordance of preclinical and clinical outcomes in most preclinical species. Copyright © 2013 Elsevier Inc. All rights reserved.

Fault displacement hazard assessment for nuclear installations based on IAEA safety standards

NASA Astrophysics Data System (ADS)

Fukushima, Y.

2016-12-01

In the IAEA Safety NS-R-3, surface fault displacement hazard assessment (FDHA) is required for the siting of nuclear installations. If any capable faults exist in the candidate site, IAEA recommends the consideration of alternative sites. However, due to the progress in palaeoseismological investigations, capable faults may be found in existing site. In such a case, IAEA recommends to evaluate the safety using probabilistic FDHA (PFDHA), which is an empirical approach based on still quite limited database. Therefore a basic and crucial improvement is to increase the database. In 2015, IAEA produced a TecDoc-1767 on Palaeoseismology as a reference for the identification of capable faults. Another IAEA Safety Report 85 on ground motion simulation based on fault rupture modelling provides an annex introducing recent PFDHAs and fault displacement simulation methodologies. The IAEA expanded the project of FDHA for the probabilistic approach and the physics based fault rupture modelling. The first approach needs a refinement of the empirical methods by building a world wide database, and the second approach needs to shift from kinematic to the dynamic scheme. Both approaches can complement each other, since simulated displacement can fill the gap of a sparse database and geological observations can be useful to calibrate the simulations. The IAEA already supported a workshop in October 2015 to discuss the existing databases with the aim of creating a common worldwide database. A consensus of a unified database was reached. The next milestone is to fill the database with as many fault rupture data sets as possible. Another IAEA work group had a WS in November 2015 to discuss the state-of-the-art PFDHA as well as simulation methodologies. Two groups jointed a consultancy meeting in February 2016, shared information, identified issues, discussed goals and outputs, and scheduled future meetings. Now we may aim at coordinating activities for the whole FDHA tasks jointly.

Probabilistic Sensitivity Analysis for Launch Vehicles with Varying Payloads and Adapters for Structural Dynamics and Loads

NASA Technical Reports Server (NTRS)

McGhee, David S.; Peck, Jeff A.; McDonald, Emmett J.

2012-01-01

This paper examines Probabilistic Sensitivity Analysis (PSA) methods and tools in an effort to understand their utility in vehicle loads and dynamic analysis. Specifically, this study addresses how these methods may be used to establish limits on payload mass and cg location and requirements on adaptor stiffnesses while maintaining vehicle loads and frequencies within established bounds. To this end, PSA methods and tools are applied to a realistic, but manageable, integrated launch vehicle analysis where payload and payload adaptor parameters are modeled as random variables. This analysis is used to study both Regional Response PSA (RRPSA) and Global Response PSA (GRPSA) methods, with a primary focus on sampling based techniques. For contrast, some MPP based approaches are also examined.

Fully Closed-Loop Multiple Model Probabilistic Predictive Controller Artificial Pancreas Performance in Adolescents and Adults in a Supervised Hotel Setting.

PubMed

Forlenza, Gregory P; Cameron, Faye M; Ly, Trang T; Lam, David; Howsmon, Daniel P; Baysal, Nihat; Kulina, Georgia; Messer, Laurel; Clinton, Paula; Levister, Camilla; Patek, Stephen D; Levy, Carol J; Wadwa, R Paul; Maahs, David M; Bequette, B Wayne; Buckingham, Bruce A

2018-05-01

Initial Food and Drug Administration-approved artificial pancreas (AP) systems will be hybrid closed-loop systems that require prandial meal announcements and will not eliminate the burden of premeal insulin dosing. Multiple model probabilistic predictive control (MMPPC) is a fully closed-loop system that uses probabilistic estimation of meals to allow for automated meal detection. In this study, we describe the safety and performance of the MMPPC system with announced and unannounced meals in a supervised hotel setting. The Android phone-based AP system with remote monitoring was tested for 72 h in six adults and four adolescents across three clinical sites with daily exercise and meal challenges involving both three announced (manual bolus by patient) and six unannounced (no bolus by patient) meals. Safety criteria were predefined. Controller aggressiveness was adapted daily based on prior hypoglycemic events. Mean 24-h continuous glucose monitor (CGM) was 157.4 ± 14.4 mg/dL, with 63.6 ± 9.2% of readings between 70 and 180 mg/dL, 2.9 ± 2.3% of readings <70 mg/dL, and 9.0 ± 3.9% of readings >250 mg/dL. Moderate hyperglycemia was relatively common with 24.6 ± 6.2% of readings between 180 and 250 mg/dL, primarily within 3 h after a meal. Overnight mean CGM was 139.6 ± 27.6 mg/dL, with 77.9 ± 16.4% between 70 and 180 mg/dL, 3.0 ± 4.5% <70 mg/dL, 17.1 ± 14.9% between 180 and 250 mg/dL, and 2.0 ± 4.5%> 250 mg/dL. Postprandial hyperglycemia was more common for unannounced meals compared with announced meals (4-h postmeal CGM 197.8 ± 44.1 vs. 140.6 ± 35.0 mg/dL; P < 0.001). No participants met safety stopping criteria. MMPPC was safe in a supervised setting despite meal and exercise challenges. Further studies are needed in a less supervised environment.

[Use of the prenosology approach for attaining the objectives of pilot medical expertise].

PubMed

Ushakov, I B; Simakova, T G; Zipa, O M; Chernikova, A G; Baevskij, R M

2014-01-01

Early diagnostics of senior pilots for diseases and conditions undesirable in terms of flight safety is tightly linked with evaluation of risks of their development. Prenosology diagnostics is focused on borderline states that may pass from health to disease (prenosology and premorbidity) and, vice versa, from disease to recovery (postnosology). Regarding health as a vital adaptation reserve, prenosology diagnostics is concerned with the ability of organism to adapt to an environment rather than probability of disease. Constant drain of adaptation reserves may become a reason for increased risks of disease. Heart rate variability analysis is one of the instruments of prenosology diagnostics. Authors of the paper discuss applicability of the space medicine oriented probabilistic approach to evaluation of adaptation risks by medical expertise boards certifying civil pilots. Results of 2 series of investigations showed increased adaptation risks and reduced functional reserves in pilots found unfit to continue career.

A Computational Framework to Control Verification and Robustness Analysis

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Kenny, Sean P.; Giesy, Daniel P.

2010-01-01

This paper presents a methodology for evaluating the robustness of a controller based on its ability to satisfy the design requirements. The framework proposed is generic since it allows for high-fidelity models, arbitrary control structures and arbitrary functional dependencies between the requirements and the uncertain parameters. The cornerstone of this contribution is the ability to bound the region of the uncertain parameter space where the degradation in closed-loop performance remains acceptable. The size of this bounding set, whose geometry can be prescribed according to deterministic or probabilistic uncertainty models, is a measure of robustness. The robustness metrics proposed herein are the parametric safety margin, the reliability index, the failure probability and upper bounds to this probability. The performance observed at the control verification setting, where the assumptions and approximations used for control design may no longer hold, will fully determine the proposed control assessment.

A human reliability based usability evaluation method for safety-critical software

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boring, R. L.; Tran, T. Q.; Gertman, D. I.

2006-07-01

Boring and Gertman (2005) introduced a novel method that augments heuristic usability evaluation methods with that of the human reliability analysis method of SPAR-H. By assigning probabilistic modifiers to individual heuristics, it is possible to arrive at the usability error probability (UEP). Although this UEP is not a literal probability of error, it nonetheless provides a quantitative basis to heuristic evaluation. This method allows one to seamlessly prioritize and identify usability issues (i.e., a higher UEP requires more immediate fixes). However, the original version of this method required the usability evaluator to assign priority weights to the final UEP, thusmore » allowing the priority of a usability issue to differ among usability evaluators. The purpose of this paper is to explore an alternative approach to standardize the priority weighting of the UEP in an effort to improve the method's reliability. (authors)« less

Probabilistic model of bridge vehicle loads in port area based on in-situ load testing

NASA Astrophysics Data System (ADS)

Deng, Ming; Wang, Lei; Zhang, Jianren; Wang, Rei; Yan, Yanhong

2017-11-01

Vehicle load is an important factor affecting the safety and usability of bridges. An statistical analysis is carried out in this paper to investigate the vehicle load data of Tianjin Haibin highway in Tianjin port of China, which are collected by the Weigh-in- Motion (WIM) system. Following this, the effect of the vehicle load on test bridge is calculated, and then compared with the calculation result according to HL-93(AASHTO LRFD). Results show that the overall vehicle load follows a distribution with a weighted sum of four normal distributions. The maximum vehicle load during the design reference period follows a type I extremum distribution. The vehicle load effect also follows a weighted sum of four normal distributions, and the standard value of the vehicle load is recommended as 1.8 times that of the calculated value according to HL-93.

[Theoretical evaluation of the risk of decompression illness during simulated extravehicular activity].

PubMed

Nikolaev, V P

2008-01-01

Theoretical analysis of the risk of decompression illness (DI) during extravehicular activity following the Russian and NASA decompression protocols (D-R and D-US, respectively) was performed. In contrast to the tradition approach to decompression stress evaluation by the factor of tissue supersaturation with nitrogen, our probabilistic theory of decompression safety provides a completely reasoned evaluation and comparison of the levels of hazard of these decompression protocols. According to this theory, the function of cumulative DI risk is equal to the sum of functions of cumulative risk of lesion of all body tissues by gas bubbles and their supersaturation by solute gases. Based on modeling of dynamics of these functions, growth of the DI cumulative risk in the course of D-R and D-US follows essentially similar trajectories within the time-frame of up to 330 minutes. However, further extension of D-US but not D-R raises the risk of DI drastically.

Integrated software health management for aerospace guidance, navigation, and control systems: A probabilistic reasoning approach

NASA Astrophysics Data System (ADS)

Mbaya, Timmy

Embedded Aerospace Systems have to perform safety and mission critical operations in a real-time environment where timing and functional correctness are extremely important. Guidance, Navigation, and Control (GN&C) systems substantially rely on complex software interfacing with hardware in real-time; any faults in software or hardware, or their interaction could result in fatal consequences. Integrated Software Health Management (ISWHM) provides an approach for detection and diagnosis of software failures while the software is in operation. The ISWHM approach is based on probabilistic modeling of software and hardware sensors using a Bayesian network. To meet memory and timing constraints of real-time embedded execution, the Bayesian network is compiled into an Arithmetic Circuit, which is used for on-line monitoring. This type of system monitoring, using an ISWHM, provides automated reasoning capabilities that compute diagnoses in a timely manner when failures occur. This reasoning capability enables time-critical mitigating decisions and relieves the human agent from the time-consuming and arduous task of foraging through a multitude of isolated---and often contradictory---diagnosis data. For the purpose of demonstrating the relevance of ISWHM, modeling and reasoning is performed on a simple simulated aerospace system running on a real-time operating system emulator, the OSEK/Trampoline platform. Models for a small satellite and an F-16 fighter jet GN&C (Guidance, Navigation, and Control) system have been implemented. Analysis of the ISWHM is then performed by injecting faults and analyzing the ISWHM's diagnoses.

Probabilistic biosphere modeling for the long-term safety assessment of geological disposal facilities for radioactive waste using first- and second-order Monte Carlo simulation.

PubMed

Ciecior, Willy; Röhlig, Klaus-Jürgen; Kirchner, Gerald

2018-10-01

In the present paper, deterministic as well as first- and second-order probabilistic biosphere modeling approaches are compared. Furthermore, the sensitivity of the influence of the probability distribution function shape (empirical distribution functions and fitted lognormal probability functions) representing the aleatory uncertainty (also called variability) of a radioecological model parameter as well as the role of interacting parameters are studied. Differences in the shape of the output distributions for the biosphere dose conversion factor from first-order Monte Carlo uncertainty analysis using empirical and fitted lognormal distribution functions for input parameters suggest that a lognormal approximation is possibly not always an adequate representation of the aleatory uncertainty of a radioecological parameter. Concerning the comparison of the impact of aleatory and epistemic parameter uncertainty on the biosphere dose conversion factor, the latter here is described using uncertain moments (mean, variance) while the distribution itself represents the aleatory uncertainty of the parameter. From the results obtained, the solution space of second-order Monte Carlo simulation is much larger than that from first-order Monte Carlo simulation. Therefore, the influence of epistemic uncertainty of a radioecological parameter on the output result is much larger than that one caused by its aleatory uncertainty. Parameter interactions are only of significant influence in the upper percentiles of the distribution of results as well as only in the region of the upper percentiles of the model parameters. Copyright © 2018 Elsevier Ltd. All rights reserved.

Aggregate exposure modelling of zinc pyrithione in rinse-off personal cleansing products using a person-orientated approach with market share refinement.

PubMed

Tozer, Sarah A; Kelly, Seamus; O'Mahony, Cian; Daly, E J; Nash, J F

2015-09-01

Realistic estimates of chemical aggregate exposure are needed to ensure consumer safety. As exposure estimates are a critical part of the equation used to calculate acceptable "safe levels" and conduct quantitative risk assessments, methods are needed to produce realistic exposure estimations. To this end, a probabilistic aggregate exposure model was developed to estimate consumer exposure from several rinse off personal cleansing products containing the anti-dandruff preservative zinc pyrithione. The model incorporates large habits and practices surveys, containing data on frequency of use, amount applied, co-use along with market share, and combines these data at the level of the individual based on subject demographics to better estimate exposure. The daily-applied exposure (i.e., amount applied to the skin) was 3.79 mg/kg/day for the 95th percentile consumer. The estimated internal dose for the 95th percentile exposure ranged from 0.01-1.29 μg/kg/day after accounting for retention following rinsing and dermal penetration of ZnPt. This probabilistic aggregate exposure model can be used in the human safety assessment of ingredients in multiple rinse-off technologies (e.g., shampoo, bar soap, body wash, and liquid hand soap). In addition, this model may be used in other situations where refined exposure assessment is required to support a chemical risk assessment. Copyright © 2015 Elsevier Ltd. All rights reserved.

Precursor Analysis for Flight- and Ground-Based Anomaly Risk Significance Determination

NASA Technical Reports Server (NTRS)

Groen, Frank

2010-01-01

This slide presentation reviews the precursor analysis for flight and ground based anomaly risk significance. It includes information on accident precursor analysis, real models vs. models, and probabilistic analysis.

A probabilistic framework for assessing vulnerability to climate variability and change: The case of the US water supply system

Treesearch

Romano Foti; Jorge A. Ramirez; Thomas C. Brown

2014-01-01

We introduce a probabilistic framework for vulnerability analysis and use it to quantify current and future vulnerability of the US water supply system. We also determine the contributions of hydro-climatic and socio-economic drivers to the changes in projected vulnerability. For all scenarios and global climatemodels examined, the US Southwest including California and...

Flood Risk and Probabilistic Benefit Assessment to Support Management of Flood-Prone Lands: Evidence From Candaba Floodplains, Philippines

NASA Astrophysics Data System (ADS)

Juarez, A. M.; Kibler, K. M.; Sayama, T.; Ohara, M.

2016-12-01

Flood management decision-making is often supported by risk assessment, which may overlook the role of coping capacity and the potential benefits derived from direct use of flood-prone land. Alternatively, risk-benefit analysis can support floodplain management to yield maximum socio-ecological benefits for the minimum flood risk. We evaluate flood risk-probabilistic benefit tradeoffs of livelihood practices compatible with direct human use of flood-prone land (agriculture/wild fisheries) and nature conservation (wild fisheries only) in Candaba, Philippines. Located north-west to Metro Manila, Candaba area is a multi-functional landscape that provides a temporally-variable mix of possible land uses, benefits and ecosystem services of local and regional value. To characterize inundation from 1.3- to 100-year recurrence intervals we couple frequency analysis with rainfall-runoff-inundation modelling and remotely-sensed data. By combining simulated probabilistic floods with both damage and benefit functions (e.g. fish capture and rice yield with flood intensity) we estimate potential damages and benefits over varying probabilistic flood hazards. We find that although direct human uses of flood-prone land are associated with damages, for all the investigated magnitudes of flood events with different frequencies, the probabilistic benefits ( 91 million) exceed risks by a large margin ( 33 million). Even considering risk, probabilistic livelihood benefits of direct human uses far exceed benefits provided by scenarios that exclude direct "risky" human uses (difference of 85 million). In addition, we find that individual coping strategies, such as adapting crop planting periods to the flood pulse or fishing rather than cultivating rice in the wet season, minimize flood losses ( 6 million) while allowing for valuable livelihood benefits ($ 125 million) in flood-prone land. Analysis of societal benefits and local capacities to cope with regular floods demonstrate the relevance of accounting for the full range of flood events and their relation to both potential damages and benefits in risk assessments. Management measures may thus be designed to reflect local contexts and support benefits of natural hydrologic processes, while minimizing flood damage.

Comparison of bias analysis strategies applied to a large data set.

PubMed

Lash, Timothy L; Abrams, Barbara; Bodnar, Lisa M

2014-07-01

Epidemiologic data sets continue to grow larger. Probabilistic-bias analyses, which simulate hundreds of thousands of replications of the original data set, may challenge desktop computational resources. We implemented a probabilistic-bias analysis to evaluate the direction, magnitude, and uncertainty of the bias arising from misclassification of prepregnancy body mass index when studying its association with early preterm birth in a cohort of 773,625 singleton births. We compared 3 bias analysis strategies: (1) using the full cohort, (2) using a case-cohort design, and (3) weighting records by their frequency in the full cohort. Underweight and overweight mothers were more likely to deliver early preterm. A validation substudy demonstrated misclassification of prepregnancy body mass index derived from birth certificates. Probabilistic-bias analyses suggested that the association between underweight and early preterm birth was overestimated by the conventional approach, whereas the associations between overweight categories and early preterm birth were underestimated. The 3 bias analyses yielded equivalent results and challenged our typical desktop computing environment. Analyses applied to the full cohort, case cohort, and weighted full cohort required 7.75 days and 4 terabytes, 15.8 hours and 287 gigabytes, and 8.5 hours and 202 gigabytes, respectively. Large epidemiologic data sets often include variables that are imperfectly measured, often because data were collected for other purposes. Probabilistic-bias analysis allows quantification of errors but may be difficult in a desktop computing environment. Solutions that allow these analyses in this environment can be achieved without new hardware and within reasonable computational time frames.

Demonstration of the Application of Composite Load Spectra (CLS) and Probabilistic Structural Analysis (PSAM) Codes to SSME Heat Exchanger Turnaround Vane

NASA Technical Reports Server (NTRS)

Rajagopal, Kadambi R.; DebChaudhury, Amitabha; Orient, George

2000-01-01

This report describes a probabilistic structural analysis performed to determine the probabilistic structural response under fluctuating random pressure loads for the Space Shuttle Main Engine (SSME) turnaround vane. It uses a newly developed frequency and distance dependent correlation model that has features to model the decay phenomena along the flow and across the flow with the capability to introduce a phase delay. The analytical results are compared using two computer codes SAFER (Spectral Analysis of Finite Element Responses) and NESSUS (Numerical Evaluation of Stochastic Structures Under Stress) and with experimentally observed strain gage data. The computer code NESSUS with an interface to a sub set of Composite Load Spectra (CLS) code is used for the probabilistic analysis. A Fatigue code was used to calculate fatigue damage due to the random pressure excitation. The random variables modeled include engine system primitive variables that influence the operating conditions, convection velocity coefficient, stress concentration factor, structural damping, and thickness of the inner and outer vanes. The need for an appropriate correlation model in addition to magnitude of the PSD is emphasized. The study demonstrates that correlation characteristics even under random pressure loads are capable of causing resonance like effects for some modes. The study identifies the important variables that contribute to structural alternate stress response and drive the fatigue damage for the new design. Since the alternate stress for the new redesign is less than the endurance limit for the material, the damage due high cycle fatigue is negligible.

Probabilistic objective functions for margin-less IMRT planning

NASA Astrophysics Data System (ADS)

Bohoslavsky, Román; Witte, Marnix G.; Janssen, Tomas M.; van Herk, Marcel

2013-06-01

We present a method to implement probabilistic treatment planning of intensity-modulated radiation therapy using custom software plugins in a commercial treatment planning system. Our method avoids the definition of safety-margins by directly including the effect of geometrical uncertainties during optimization when objective functions are evaluated. Because the shape of the resulting dose distribution implicitly defines the robustness of the plan, the optimizer has much more flexibility than with a margin-based approach. We expect that this added flexibility helps to automatically strike a better balance between target coverage and dose reduction for surrounding healthy tissue, especially for cases where the planning target volume overlaps organs at risk. Prostate cancer treatment planning was chosen to develop our method, including a novel technique to include rotational uncertainties. Based on population statistics, translations and rotations are simulated independently following a marker-based IGRT correction strategy. The effects of random and systematic errors are incorporated by first blurring and then shifting the dose distribution with respect to the clinical target volume. For simplicity and efficiency, dose-shift invariance and a rigid-body approximation are assumed. Three prostate cases were replanned using our probabilistic objective functions. To compare clinical and probabilistic plans, an evaluation tool was used that explicitly incorporates geometric uncertainties using Monte-Carlo methods. The new plans achieved similar or better dose distributions than the original clinical plans in terms of expected target coverage and rectum wall sparing. Plan optimization times were only about a factor of two higher than in the original clinical system. In conclusion, we have developed a practical planning tool that enables margin-less probability-based treatment planning with acceptable planning times, achieving the first system that is feasible for clinical implementation.

Computation of probabilistic hazard maps and source parameter estimation for volcanic ash transport and dispersion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Madankan, R.; Pouget, S.; Singla, P., E-mail: psingla@buffalo.edu

Volcanic ash advisory centers are charged with forecasting the movement of volcanic ash plumes, for aviation, health and safety preparation. Deterministic mathematical equations model the advection and dispersion of these plumes. However initial plume conditions – height, profile of particle location, volcanic vent parameters – are known only approximately at best, and other features of the governing system such as the windfield are stochastic. These uncertainties make forecasting plume motion difficult. As a result of these uncertainties, ash advisories based on a deterministic approach tend to be conservative, and many times over/under estimate the extent of a plume. This papermore » presents an end-to-end framework for generating a probabilistic approach to ash plume forecasting. This framework uses an ensemble of solutions, guided by Conjugate Unscented Transform (CUT) method for evaluating expectation integrals. This ensemble is used to construct a polynomial chaos expansion that can be sampled cheaply, to provide a probabilistic model forecast. The CUT method is then combined with a minimum variance condition, to provide a full posterior pdf of the uncertain source parameters, based on observed satellite imagery. The April 2010 eruption of the Eyjafjallajökull volcano in Iceland is employed as a test example. The puff advection/dispersion model is used to hindcast the motion of the ash plume through time, concentrating on the period 14–16 April 2010. Variability in the height and particle loading of that eruption is introduced through a volcano column model called bent. Output uncertainty due to the assumed uncertain input parameter probability distributions, and a probabilistic spatial-temporal estimate of ash presence are computed.« less

Predicting Rib Fracture Risk With Whole-Body Finite Element Models: Development and Preliminary Evaluation of a Probabilistic Analytical Framework

PubMed Central

Forman, Jason L.; Kent, Richard W.; Mroz, Krystoffer; Pipkorn, Bengt; Bostrom, Ola; Segui-Gomez, Maria

2012-01-01

This study sought to develop a strain-based probabilistic method to predict rib fracture risk with whole-body finite element (FE) models, and to describe a method to combine the results with collision exposure information to predict injury risk and potential intervention effectiveness in the field. An age-adjusted ultimate strain distribution was used to estimate local rib fracture probabilities within an FE model. These local probabilities were combined to predict injury risk and severity within the whole ribcage. The ultimate strain distribution was developed from a literature dataset of 133 tests. Frontal collision simulations were performed with the THUMS (Total HUman Model for Safety) model with four levels of delta-V and two restraints: a standard 3-point belt and a progressive 3.5–7 kN force-limited, pretensioned (FL+PT) belt. The results of three simulations (29 km/h standard, 48 km/h standard, and 48 km/h FL+PT) were compared to matched cadaver sled tests. The numbers of fractures predicted for the comparison cases were consistent with those observed experimentally. Combining these results with field exposure informantion (ΔV, NASS-CDS 1992–2002) suggests a 8.9% probability of incurring AIS3+ rib fractures for a 60 year-old restrained by a standard belt in a tow-away frontal collision with this restraint, vehicle, and occupant configuration, compared to 4.6% for the FL+PT belt. This is the first study to describe a probabilistic framework to predict rib fracture risk based on strains observed in human-body FE models. Using this analytical framework, future efforts may incorporate additional subject or collision factors for multi-variable probabilistic injury prediction. PMID:23169122

A Probabilistic Risk Analysis (PRA) of Human Space Missions for the Advanced Integration Matrix (AIM)

NASA Technical Reports Server (NTRS)

Jones, Harry W.; Dillon-Merrill, Robin L.; Thomas, Gretchen A.

2003-01-01

The Advanced Integration Matrix (AIM) Project u7ill study and solve systems-level integration issues for exploration missions beyond Low Earth Orbit (LEO), through the design and development of a ground-based facility for developing revolutionary integrated systems for joint human-robotic missions. This paper describes a Probabilistic Risk Analysis (PRA) of human space missions that was developed to help define the direction and priorities for AIM. Risk analysis is required for all major NASA programs and has been used for shuttle, station, and Mars lander programs. It is a prescribed part of early planning and is necessary during concept definition, even before mission scenarios and system designs exist. PRA cm begin when little failure data are available, and be continually updated and refined as detail becomes available. PRA provides a basis for examining tradeoffs among safety, reliability, performance, and cost. The objective of AIM's PRA is to indicate how risk can be managed and future human space missions enabled by the AIM Project. Many critical events can cause injuries and fatalities to the crew without causing loss of vehicle or mission. Some critical systems are beyond AIM's scope, such as propulsion and guidance. Many failure-causing events can be mitigated by conducting operational tests in AIM, such as testing equipment and evaluating operational procedures, especially in the areas of communications and computers, autonomous operations, life support, thermal design, EVA and rover activities, physiological factors including habitation, medical equipment, and food, and multifunctional tools and repairable systems. AIM is well suited to test and demonstrate the habitat, life support, crew operations, and human interface. Because these account for significant crew, systems performance, and science risks, AIM will help reduce mission risk, and missions beyond LEO are far enough in the future that AIM can have significant impact.

Probabilistic Analysis of Space Shuttle Body Flap Actuator Ball Bearings

NASA Technical Reports Server (NTRS)

Oswald, Fred B.; Jett, Timothy R.; Predmore, Roamer E.; Zaretsky, Erin V.

2007-01-01

A probabilistic analysis, using the 2-parameter Weibull-Johnson method, was performed on experimental life test data from space shuttle actuator bearings. Experiments were performed on a test rig under simulated conditions to determine the life and failure mechanism of the grease lubricated bearings that support the input shaft of the space shuttle body flap actuators. The failure mechanism was wear that can cause loss of bearing preload. These tests established life and reliability data for both shuttle flight and ground operation. Test data were used to estimate the failure rate and reliability as a function of the number of shuttle missions flown. The Weibull analysis of the test data for a 2-bearing shaft assembly in each body flap actuator established a reliability level of 99.6 percent for a life of 12 missions. A probabilistic system analysis for four shuttles, each of which has four actuators, predicts a single bearing failure in one actuator of one shuttle after 22 missions (a total of 88 missions for a 4-shuttle fleet). This prediction is comparable with actual shuttle flight history in which a single actuator bearing was found to have failed by wear at 20 missions.

Probabilistic Analysis of Space Shuttle Body Flap Actuator Ball Bearings

NASA Technical Reports Server (NTRS)

Oswald, Fred B.; Jett, Timothy R.; Predmore, Roamer E.; Zaretsky, Erwin V.

2008-01-01

A probabilistic analysis, using the 2-parameter Weibull-Johnson method, was performed on experimental life test data from space shuttle actuator bearings. Experiments were performed on a test rig under simulated conditions to determine the life and failure mechanism of the grease lubricated bearings that support the input shaft of the space shuttle body flap actuators. The failure mechanism was wear that can cause loss of bearing preload. These tests established life and reliability data for both shuttle flight and ground operation. Test data were used to estimate the failure rate and reliability as a function of the number of shuttle missions flown. The Weibull analysis of the test data for the four actuators on one shuttle, each with a 2-bearing shaft assembly, established a reliability level of 96.9 percent for a life of 12 missions. A probabilistic system analysis for four shuttles, each of which has four actuators, predicts a single bearing failure in one actuator of one shuttle after 22 missions (a total of 88 missions for a 4-shuttle fleet). This prediction is comparable with actual shuttle flight history in which a single actuator bearing was found to have failed by wear at 20 missions.

Probabilistic Common Spatial Patterns for Multichannel EEG Analysis

PubMed Central

Chen, Zhe; Gao, Xiaorong; Li, Yuanqing; Brown, Emery N.; Gao, Shangkai

2015-01-01

Common spatial patterns (CSP) is a well-known spatial filtering algorithm for multichannel electroencephalogram (EEG) analysis. In this paper, we cast the CSP algorithm in a probabilistic modeling setting. Specifically, probabilistic CSP (P-CSP) is proposed as a generic EEG spatio-temporal modeling framework that subsumes the CSP and regularized CSP algorithms. The proposed framework enables us to resolve the overfitting issue of CSP in a principled manner. We derive statistical inference algorithms that can alleviate the issue of local optima. In particular, an efficient algorithm based on eigendecomposition is developed for maximum a posteriori (MAP) estimation in the case of isotropic noise. For more general cases, a variational algorithm is developed for group-wise sparse Bayesian learning for the P-CSP model and for automatically determining the model size. The two proposed algorithms are validated on a simulated data set. Their practical efficacy is also demonstrated by successful applications to single-trial classifications of three motor imagery EEG data sets and by the spatio-temporal pattern analysis of one EEG data set recorded in a Stroop color naming task. PMID:26005228

Modelling default and likelihood reasoning as probabilistic

NASA Technical Reports Server (NTRS)

Buntine, Wray

1990-01-01

A probabilistic analysis of plausible reasoning about defaults and about likelihood is presented. 'Likely' and 'by default' are in fact treated as duals in the same sense as 'possibility' and 'necessity'. To model these four forms probabilistically, a logic QDP and its quantitative counterpart DP are derived that allow qualitative and corresponding quantitative reasoning. Consistency and consequence results for subsets of the logics are given that require at most a quadratic number of satisfiability tests in the underlying propositional logic. The quantitative logic shows how to track the propagation error inherent in these reasoning forms. The methodology and sound framework of the system highlights their approximate nature, the dualities, and the need for complementary reasoning about relevance.

The application of probabilistic design theory to high temperature low cycle fatigue

NASA Technical Reports Server (NTRS)

Wirsching, P. H.

1981-01-01

Metal fatigue under stress and thermal cycling is a principal mode of failure in gas turbine engine hot section components such as turbine blades and disks and combustor liners. Designing for fatigue is subject to considerable uncertainty, e.g., scatter in cycles to failure, available fatigue test data and operating environment data, uncertainties in the models used to predict stresses, etc. Methods of analyzing fatigue test data for probabilistic design purposes are summarized. The general strain life as well as homo- and hetero-scedastic models are considered. Modern probabilistic design theory is reviewed and examples are presented which illustrate application to reliability analysis of gas turbine engine components.

Probabilistic micromechanics for metal matrix composites

NASA Astrophysics Data System (ADS)

Engelstad, S. P.; Reddy, J. N.; Hopkins, Dale A.

A probabilistic micromechanics-based nonlinear analysis procedure is developed to predict and quantify the variability in the properties of high temperature metal matrix composites. Monte Carlo simulation is used to model the probabilistic distributions of the constituent level properties including fiber, matrix, and interphase properties, volume and void ratios, strengths, fiber misalignment, and nonlinear empirical parameters. The procedure predicts the resultant ply properties and quantifies their statistical scatter. Graphite copper and Silicon Carbide Titanlum Aluminide (SCS-6 TI15) unidirectional plies are considered to demonstrate the predictive capabilities. The procedure is believed to have a high potential for use in material characterization and selection to precede and assist in experimental studies of new high temperature metal matrix composites.

Transient flow conditions in probabilistic wellhead protection: importance and ways to manage spatial and temporal uncertainty in capture zone delineation

NASA Astrophysics Data System (ADS)

Enzenhoefer, R.; Rodriguez-Pretelin, A.; Nowak, W.

2012-12-01

"From an engineering standpoint, the quantification of uncertainty is extremely important not only because it allows estimating risk but mostly because it allows taking optimal decisions in an uncertain framework" (Renard, 2007). The most common way to account for uncertainty in the field of subsurface hydrology and wellhead protection is to randomize spatial parameters, e.g. the log-hydraulic conductivity or porosity. This enables water managers to take robust decisions in delineating wellhead protection zones with rationally chosen safety margins in the spirit of probabilistic risk management. Probabilistic wellhead protection zones are commonly based on steady-state flow fields. However, several past studies showed that transient flow conditions may substantially influence the shape and extent of catchments. Therefore, we believe they should be accounted for in the probabilistic assessment and in the delineation process. The aim of our work is to show the significance of flow transients and to investigate the interplay between spatial uncertainty and flow transients in wellhead protection zone delineation. To this end, we advance our concept of probabilistic capture zone delineation (Enzenhoefer et al., 2012) that works with capture probabilities and other probabilistic criteria for delineation. The extended framework is able to evaluate the time fraction that any point on a map falls within a capture zone. In short, we separate capture probabilities into spatial/statistical and time-related frequencies. This will provide water managers additional information on how to manage a well catchment in the light of possible hazard conditions close to the capture boundary under uncertain and time-variable flow conditions. In order to save computational costs, we take advantage of super-positioned flow components with time-variable coefficients. We assume an instantaneous development of steady-state flow conditions after each temporal change in driving forces, following an idea by Festger and Walter, 2002. These quasi steady-state flow fields are cast into a geostatistical Monte Carlo framework to admit and evaluate the influence of parameter uncertainty on the delineation process. Furthermore, this framework enables conditioning on observed data with any conditioning scheme, such as rejection sampling, Ensemble Kalman Filters, etc. To further reduce the computational load, we use the reverse formulation of advective-dispersive transport. We simulate the reverse transport by particle tracking random walk in order to avoid numerical dispersion to account for well arrival times.

Probabilistic analysis of tsunami hazards

USGS Publications Warehouse

Geist, E.L.; Parsons, T.

2006-01-01

Determining the likelihood of a disaster is a key component of any comprehensive hazard assessment. This is particularly true for tsunamis, even though most tsunami hazard assessments have in the past relied on scenario or deterministic type models. We discuss probabilistic tsunami hazard analysis (PTHA) from the standpoint of integrating computational methods with empirical analysis of past tsunami runup. PTHA is derived from probabilistic seismic hazard analysis (PSHA), with the main difference being that PTHA must account for far-field sources. The computational methods rely on numerical tsunami propagation models rather than empirical attenuation relationships as in PSHA in determining ground motions. Because a number of source parameters affect local tsunami runup height, PTHA can become complex and computationally intensive. Empirical analysis can function in one of two ways, depending on the length and completeness of the tsunami catalog. For site-specific studies where there is sufficient tsunami runup data available, hazard curves can primarily be derived from empirical analysis, with computational methods used to highlight deficiencies in the tsunami catalog. For region-wide analyses and sites where there are little to no tsunami data, a computationally based method such as Monte Carlo simulation is the primary method to establish tsunami hazards. Two case studies that describe how computational and empirical methods can be integrated are presented for Acapulco, Mexico (site-specific) and the U.S. Pacific Northwest coastline (region-wide analysis).

A novel probabilistic framework for event-based speech recognition

NASA Astrophysics Data System (ADS)

Juneja, Amit; Espy-Wilson, Carol

2003-10-01

One of the reasons for unsatisfactory performance of the state-of-the-art automatic speech recognition (ASR) systems is the inferior acoustic modeling of low-level acoustic-phonetic information in the speech signal. An acoustic-phonetic approach to ASR, on the other hand, explicitly targets linguistic information in the speech signal, but such a system for continuous speech recognition (CSR) is not known to exist. A probabilistic and statistical framework for CSR based on the idea of the representation of speech sounds by bundles of binary valued articulatory phonetic features is proposed. Multiple probabilistic sequences of linguistically motivated landmarks are obtained using binary classifiers of manner phonetic features-syllabic, sonorant and continuant-and the knowledge-based acoustic parameters (APs) that are acoustic correlates of those features. The landmarks are then used for the extraction of knowledge-based APs for source and place phonetic features and their binary classification. Probabilistic landmark sequences are constrained using manner class language models for isolated or connected word recognition. The proposed method could overcome the disadvantages encountered by the early acoustic-phonetic knowledge-based systems that led the ASR community to switch to systems highly dependent on statistical pattern analysis methods and probabilistic language or grammar models.

Learning Probabilistic Inference through Spike-Timing-Dependent Plasticity.

PubMed

Pecevski, Dejan; Maass, Wolfgang

2016-01-01

Numerous experimental data show that the brain is able to extract information from complex, uncertain, and often ambiguous experiences. Furthermore, it can use such learnt information for decision making through probabilistic inference. Several models have been proposed that aim at explaining how probabilistic inference could be performed by networks of neurons in the brain. We propose here a model that can also explain how such neural network could acquire the necessary information for that from examples. We show that spike-timing-dependent plasticity in combination with intrinsic plasticity generates in ensembles of pyramidal cells with lateral inhibition a fundamental building block for that: probabilistic associations between neurons that represent through their firing current values of random variables. Furthermore, by combining such adaptive network motifs in a recursive manner the resulting network is enabled to extract statistical information from complex input streams, and to build an internal model for the distribution p (*) that generates the examples it receives. This holds even if p (*) contains higher-order moments. The analysis of this learning process is supported by a rigorous theoretical foundation. Furthermore, we show that the network can use the learnt internal model immediately for prediction, decision making, and other types of probabilistic inference.

Learning Probabilistic Inference through Spike-Timing-Dependent Plasticity123

PubMed Central

Pecevski, Dejan

2016-01-01

Abstract Numerous experimental data show that the brain is able to extract information from complex, uncertain, and often ambiguous experiences. Furthermore, it can use such learnt information for decision making through probabilistic inference. Several models have been proposed that aim at explaining how probabilistic inference could be performed by networks of neurons in the brain. We propose here a model that can also explain how such neural network could acquire the necessary information for that from examples. We show that spike-timing-dependent plasticity in combination with intrinsic plasticity generates in ensembles of pyramidal cells with lateral inhibition a fundamental building block for that: probabilistic associations between neurons that represent through their firing current values of random variables. Furthermore, by combining such adaptive network motifs in a recursive manner the resulting network is enabled to extract statistical information from complex input streams, and to build an internal model for the distribution p* that generates the examples it receives. This holds even if p* contains higher-order moments. The analysis of this learning process is supported by a rigorous theoretical foundation. Furthermore, we show that the network can use the learnt internal model immediately for prediction, decision making, and other types of probabilistic inference. PMID:27419214

Development of Probabilistic Rigid Pavement Design Methodologies for Military Airfields.

DTIC Science & Technology

1983-12-01

4A161102AT22, Task AO, Work Unit 009, "Methodology for Considering Material Variability in Pavement Design." OCE Project Monitor was Mr. S. S. Gillespie. The...PREFACE. .. ............................. VOLUME 1: STATE OF THE ART VARIABILITY OF AIRFIELD PAVEMENT MATERIALS VOLUME 11: MATHEMATICAL FORMULATION OF...VOLUME IV: PROBABILISTIC ANALYSIS OF RIGID AIRFIELD DESIGN BY ELASTIC LAYERED THEORY VOLUME I STATE OF THE ART VARIABILITY OF AIRFIELD PAVEMENT MATERIALS

Automated Text Data Mining Analysis of Five Decades of Educational Leadership Research Literature: Probabilistic Topic Modeling of "EAQ" Articles From 1965 to 2014

ERIC Educational Resources Information Center

Wang, Yinying; Bowers, Alex J.; Fikis, David J.

2017-01-01

Purpose: The purpose of this study is to describe the underlying topics and the topic evolution in the 50-year history of educational leadership research literature. Method: We used automated text data mining with probabilistic latent topic models to examine the full text of the entire publication history of all 1,539 articles published in…

A Logical Approach to Multilevel Security of Probabilistic Systems

DTIC Science & Technology

1998-01-01

their usefulness in security analysis. Key Words: Formal modeling, Veri cation, Knowledge, Security, Probabilistic Systems Supported by grant HKUST 608...94E from the Hong Kong Research Grants Council. yAuthor for correspondence (syverson@itd.nrl.navy.mil). Supported by ONR. 1 Report Documentation Page...Form ApprovedOMB No. 0704-0188 Public reporting burden for the collection of information is estimated to average 1 hour per response, including the

Probabilistic durability assessment of concrete structures in marine environments: Reliability and sensitivity analysis

NASA Astrophysics Data System (ADS)

Yu, Bo; Ning, Chao-lie; Li, Bing

2017-03-01

A probabilistic framework for durability assessment of concrete structures in marine environments was proposed in terms of reliability and sensitivity analysis, which takes into account the uncertainties under the environmental, material, structural and executional conditions. A time-dependent probabilistic model of chloride ingress was established first to consider the variations in various governing parameters, such as the chloride concentration, chloride diffusion coefficient, and age factor. Then the Nataf transformation was adopted to transform the non-normal random variables from the original physical space into the independent standard Normal space. After that the durability limit state function and its gradient vector with respect to the original physical parameters were derived analytically, based on which the first-order reliability method was adopted to analyze the time-dependent reliability and parametric sensitivity of concrete structures in marine environments. The accuracy of the proposed method was verified by comparing with the second-order reliability method and the Monte Carlo simulation. Finally, the influences of environmental conditions, material properties, structural parameters and execution conditions on the time-dependent reliability of concrete structures in marine environments were also investigated. The proposed probabilistic framework can be implemented in the decision-making algorithm for the maintenance and repair of deteriorating concrete structures in marine environments.

Probabilistic finite elements for fatigue and fracture analysis

NASA Astrophysics Data System (ADS)

Belytschko, Ted; Liu, Wing Kam

Attenuation is focused on the development of Probabilistic Finite Element Method (PFEM), which combines the finite element method with statistics and reliability methods, and its application to linear, nonlinear structural mechanics problems and fracture mechanics problems. The computational tool based on the Stochastic Boundary Element Method is also given for the reliability analysis of a curvilinear fatigue crack growth. The existing PFEM's have been applied to solve for two types of problems: (1) determination of the response uncertainty in terms of the means, variance and correlation coefficients; and (2) determination the probability of failure associated with prescribed limit states.

Probabilistic finite elements for fatigue and fracture analysis

NASA Technical Reports Server (NTRS)

Belytschko, Ted; Liu, Wing Kam

1992-01-01

Attenuation is focused on the development of Probabilistic Finite Element Method (PFEM), which combines the finite element method with statistics and reliability methods, and its application to linear, nonlinear structural mechanics problems and fracture mechanics problems. The computational tool based on the Stochastic Boundary Element Method is also given for the reliability analysis of a curvilinear fatigue crack growth. The existing PFEM's have been applied to solve for two types of problems: (1) determination of the response uncertainty in terms of the means, variance and correlation coefficients; and (2) determination the probability of failure associated with prescribed limit states.

Programming Probabilistic Structural Analysis for Parallel Processing Computer

NASA Technical Reports Server (NTRS)

Sues, Robert H.; Chen, Heh-Chyun; Twisdale, Lawrence A.; Chamis, Christos C.; Murthy, Pappu L. N.

1991-01-01

The ultimate goal of this research program is to make Probabilistic Structural Analysis (PSA) computationally efficient and hence practical for the design environment by achieving large scale parallelism. The paper identifies the multiple levels of parallelism in PSA, identifies methodologies for exploiting this parallelism, describes the development of a parallel stochastic finite element code, and presents results of two example applications. It is demonstrated that speeds within five percent of those theoretically possible can be achieved. A special-purpose numerical technique, the stochastic preconditioned conjugate gradient method, is also presented and demonstrated to be extremely efficient for certain classes of PSA problems.

Probabilistic analysis of bladed turbine disks and the effect of mistuning

NASA Technical Reports Server (NTRS)

Shah, A. R.; Nagpal, V. K.; Chamis, Christos C.

1990-01-01

Probabilistic assessment of the maximum blade response on a mistuned rotor disk is performed using the computer code NESSUS. The uncertainties in natural frequency, excitation frequency, amplitude of excitation and damping are included to obtain the cumulative distribution function (CDF) of blade responses. Advanced mean value first order analysis is used to compute CDF. The sensitivities of different random variables are identified. Effect of the number of blades on a rotor on mistuning is evaluated. It is shown that the uncertainties associated with the forcing function parameters have significant effect on the response distribution of the bladed rotor.

Probabilistic analysis of bladed turbine disks and the effect of mistuning

NASA Technical Reports Server (NTRS)

Shah, Ashwin; Nagpal, V. K.; Chamis, C. C.

1990-01-01

Probabilistic assessment of the maximum blade response on a mistuned rotor disk is performed using the computer code NESSUS. The uncertainties in natural frequency, excitation frequency, amplitude of excitation and damping have been included to obtain the cumulative distribution function (CDF) of blade responses. Advanced mean value first order analysis is used to compute CDF. The sensitivities of different random variables are identified. Effect of the number of blades on a rotor on mistuning is evaluated. It is shown that the uncertainties associated with the forcing function parameters have significant effect on the response distribution of the bladed rotor.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Coleman, Justin; Slaughter, Andrew; Veeraraghavan, Swetha

Multi-hazard Analysis for STOchastic time-DOmaiN phenomena (MASTODON) is a finite element application that aims at analyzing the response of 3-D soil-structure systems to natural and man-made hazards such as earthquakes, floods and fire. MASTODON currently focuses on the simulation of seismic events and has the capability to perform extensive ‘source-to-site’ simulations including earthquake fault rupture, nonlinear wave propagation and nonlinear soil-structure interaction (NLSSI) analysis. MASTODON is being developed to be a dynamic probabilistic risk assessment framework that enables analysts to not only perform deterministic analyses, but also easily perform probabilistic or stochastic simulations for the purpose of risk assessment.

Probabilistic Analysis of Solid Oxide Fuel Cell Based Hybrid Gas Turbine System

NASA Technical Reports Server (NTRS)

Gorla, Rama S. R.; Pai, Shantaram S.; Rusick, Jeffrey J.

2003-01-01

The emergence of fuel cell systems and hybrid fuel cell systems requires the evolution of analysis strategies for evaluating thermodynamic performance. A gas turbine thermodynamic cycle integrated with a fuel cell was computationally simulated and probabilistically evaluated in view of the several uncertainties in the thermodynamic performance parameters. Cumulative distribution functions and sensitivity factors were computed for the overall thermal efficiency and net specific power output due to the uncertainties in the thermodynamic random variables. These results can be used to quickly identify the most critical design variables in order to optimize the design and make it cost effective. The analysis leads to the selection of criteria for gas turbine performance.

Probabilistic analysis of structures involving random stress-strain behavior

NASA Technical Reports Server (NTRS)

Millwater, H. R.; Thacker, B. H.; Harren, S. V.

1991-01-01

The present methodology for analysis of structures with random stress strain behavior characterizes the uniaxial stress-strain curve in terms of (1) elastic modulus, (2) engineering stress at initial yield, (3) initial plastic-hardening slope, (4) engineering stress at point of ultimate load, and (5) engineering strain at point of ultimate load. The methodology is incorporated into the Numerical Evaluation of Stochastic Structures Under Stress code for probabilistic structural analysis. The illustrative problem of a thick cylinder under internal pressure, where both the internal pressure and the stress-strain curve are random, is addressed by means of the code. The response value is the cumulative distribution function of the equivalent plastic strain at the inner radius.

Revealing the ISO/IEC 9126-1 Clique Tree for COTS Software Evaluation

NASA Technical Reports Server (NTRS)

Morris, A. Terry

2007-01-01

Previous research has shown that acyclic dependency models, if they exist, can be extracted from software quality standards and that these models can be used to assess software safety and product quality. In the case of commercial off-the-shelf (COTS) software, the extracted dependency model can be used in a probabilistic Bayesian network context for COTS software evaluation. Furthermore, while experts typically employ Bayesian networks to encode domain knowledge, secondary structures (clique trees) from Bayesian network graphs can be used to determine the probabilistic distribution of any software variable (attribute) using any clique that contains that variable. Secondary structures, therefore, provide insight into the fundamental nature of graphical networks. This paper will apply secondary structure calculations to reveal the clique tree of the acyclic dependency model extracted from the ISO/IEC 9126-1 software quality standard. Suggestions will be provided to describe how the clique tree may be exploited to aid efficient transformation of an evaluation model.

Quantitative Risk Modeling of Fire on the International Space Station

NASA Technical Reports Server (NTRS)

Castillo, Theresa; Haught, Megan

2014-01-01

The International Space Station (ISS) Program has worked to prevent fire events and to mitigate their impacts should they occur. Hardware is designed to reduce sources of ignition, oxygen systems are designed to control leaking, flammable materials are prevented from flying to ISS whenever possible, the crew is trained in fire response, and fire response equipment improvements are sought out and funded. Fire prevention and mitigation are a top ISS Program priority - however, programmatic resources are limited; thus, risk trades are made to ensure an adequate level of safety is maintained onboard the ISS. In support of these risk trades, the ISS Probabilistic Risk Assessment (PRA) team has modeled the likelihood of fire occurring in the ISS pressurized cabin, a phenomenological event that has never before been probabilistically modeled in a microgravity environment. This paper will discuss the genesis of the ISS PRA fire model, its enhancement in collaboration with fire experts, and the results which have informed ISS programmatic decisions and will continue to be used throughout the life of the program.

Reliability assessment of slender concrete columns at the stability failure

NASA Astrophysics Data System (ADS)

Valašík, Adrián; Benko, Vladimír; Strauss, Alfred; Täubling, Benjamin

2018-01-01

The European Standard for designing concrete columns within the use of non-linear methods shows deficiencies in terms of global reliability, in case that the concrete columns fail by the loss of stability. The buckling failure is a brittle failure which occurs without warning and the probability of its formation depends on the columns slenderness. Experiments with slender concrete columns were carried out in cooperation with STRABAG Bratislava LTD in Central Laboratory of Faculty of Civil Engineering SUT in Bratislava. The following article aims to compare the global reliability of slender concrete columns with slenderness of 90 and higher. The columns were designed according to methods offered by EN 1992-1-1 [1]. The mentioned experiments were used as basis for deterministic nonlinear modelling of the columns and subsequent the probabilistic evaluation of structural response variability. Final results may be utilized as thresholds for loading of produced structural elements and they aim to present probabilistic design as less conservative compared to classic partial safety factor based design and alternative ECOV method.

Development of Maximum Considered Earthquake Ground Motion Maps

USGS Publications Warehouse

Leyendecker, E.V.; Hunt, R.J.; Frankel, A.D.; Rukstales, K.S.

2000-01-01

The 1997 NEHRP Recommended Provisions for Seismic Regulations for New Buildings use a design procedure that is based on spectral response acceleration rather than the traditional peak ground acceleration, peak ground velocity, or zone factors. The spectral response accelerations are obtained from maps prepared following the recommendations of the Building Seismic Safety Council's (BSSC) Seismic Design Procedures Group (SDPG). The SDPG-recommended maps, the Maximum Considered Earthquake (MCE) Ground Motion Maps, are based on the U.S. Geological Survey (USGS) probabilistic hazard maps with additional modifications incorporating deterministic ground motions in selected areas and the application of engineering judgement. The MCE ground motion maps included with the 1997 NEHRP Provisions also serve as the basis for the ground motion maps used in the seismic design portions of the 2000 International Building Code and the 2000 International Residential Code. Additionally the design maps prepared for the 1997 NEHRP Provisions, combined with selected USGS probabilistic maps, are used with the 1997 NEHRP Guidelines for the Seismic Rehabilitation of Buildings.

A Passive System Reliability Analysis for a Station Blackout

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brunett, Acacia; Bucknor, Matthew; Grabaskas, David

2015-05-03

The latest iterations of advanced reactor designs have included increased reliance on passive safety systems to maintain plant integrity during unplanned sequences. While these systems are advantageous in reducing the reliance on human intervention and availability of power, the phenomenological foundations on which these systems are built require a novel approach to a reliability assessment. Passive systems possess the unique ability to fail functionally without failing physically, a result of their explicit dependency on existing boundary conditions that drive their operating mode and capacity. Argonne National Laboratory is performing ongoing analyses that demonstrate various methodologies for the characterization of passivemore » system reliability within a probabilistic framework. Two reliability analysis techniques are utilized in this work. The first approach, the Reliability Method for Passive Systems, provides a mechanistic technique employing deterministic models and conventional static event trees. The second approach, a simulation-based technique, utilizes discrete dynamic event trees to treat time- dependent phenomena during scenario evolution. For this demonstration analysis, both reliability assessment techniques are used to analyze an extended station blackout in a pool-type sodium fast reactor (SFR) coupled with a reactor cavity cooling system (RCCS). This work demonstrates the entire process of a passive system reliability analysis, including identification of important parameters and failure metrics, treatment of uncertainties and analysis of results.« less

Behavioral economics and regulatory analysis.

PubMed

Robinson, Lisa A; Hammitt, James K

2011-09-01

Behavioral economics has captured the interest of scholars and the general public by demonstrating ways in which individuals make decisions that appear irrational. While increasing attention is being focused on the implications of this research for the design of risk-reducing policies, less attention has been paid to how it affects the economic valuation of policy consequences. This article considers the latter issue, reviewing the behavioral economics literature and discussing its implications for the conduct of benefit-cost analysis, particularly in the context of environmental, health, and safety regulations. We explore three concerns: using estimates of willingness to pay or willingness to accept compensation for valuation, considering the psychological aspects of risk when valuing mortality-risk reductions, and discounting future consequences. In each case, we take the perspective that analysts should avoid making judgments about whether values are "rational" or "irrational." Instead, they should make every effort to rely on well-designed studies, using ranges, sensitivity analysis, or probabilistic modeling to reflect uncertainty. More generally, behavioral research has led some to argue for a more paternalistic approach to policy analysis. We argue instead for continued focus on describing the preferences of those affected, while working to ensure that these preferences are based on knowledge and careful reflection. © 2011 Society for Risk Analysis.

Probabilistic Analysis and Density Parameter Estimation Within Nessus

NASA Astrophysics Data System (ADS)

Godines, Cody R.; Manteufel, Randall D.

2002-12-01

This NASA educational grant has the goal of promoting probabilistic analysis methods to undergraduate and graduate UTSA engineering students. Two undergraduate-level and one graduate-level course were offered at UTSA providing a large number of students exposure to and experience in probabilistic techniques. The grant provided two research engineers from Southwest Research Institute the opportunity to teach these courses at UTSA, thereby exposing a large number of students to practical applications of probabilistic methods and state-of-the-art computational methods. In classroom activities, students were introduced to the NESSUS computer program, which embodies many algorithms in probabilistic simulation and reliability analysis. Because the NESSUS program is used at UTSA in both student research projects and selected courses, a student version of a NESSUS manual has been revised and improved, with additional example problems being added to expand the scope of the example application problems. This report documents two research accomplishments in the integration of a new sampling algorithm into NESSUS and in the testing of the new algorithm. The new Latin Hypercube Sampling (LHS) subroutines use the latest NESSUS input file format and specific files for writing output. The LHS subroutines are called out early in the program so that no unnecessary calculations are performed. Proper correlation between sets of multidimensional coordinates can be obtained by using NESSUS' LHS capabilities. Finally, two types of correlation are written to the appropriate output file. The program enhancement was tested by repeatedly estimating the mean, standard deviation, and 99th percentile of four different responses using Monte Carlo (MC) and LHS. These test cases, put forth by the Society of Automotive Engineers, are used to compare probabilistic methods. For all test cases, it is shown that LHS has a lower estimation error than MC when used to estimate the mean, standard deviation, and 99th percentile of the four responses at the 50 percent confidence level and using the same number of response evaluations for each method. In addition, LHS requires fewer calculations than MC in order to be 99.7 percent confident that a single mean, standard deviation, or 99th percentile estimate will be within at most 3 percent of the true value of the each parameter. Again, this is shown for all of the test cases studied. For that reason it can be said that NESSUS is an important reliability tool that has a variety of sound probabilistic methods a user can employ; furthermore, the newest LHS module is a valuable new enhancement of the program.

Probabilistic Analysis and Density Parameter Estimation Within Nessus

NASA Technical Reports Server (NTRS)

Godines, Cody R.; Manteufel, Randall D.; Chamis, Christos C. (Technical Monitor)

2002-01-01

This NASA educational grant has the goal of promoting probabilistic analysis methods to undergraduate and graduate UTSA engineering students. Two undergraduate-level and one graduate-level course were offered at UTSA providing a large number of students exposure to and experience in probabilistic techniques. The grant provided two research engineers from Southwest Research Institute the opportunity to teach these courses at UTSA, thereby exposing a large number of students to practical applications of probabilistic methods and state-of-the-art computational methods. In classroom activities, students were introduced to the NESSUS computer program, which embodies many algorithms in probabilistic simulation and reliability analysis. Because the NESSUS program is used at UTSA in both student research projects and selected courses, a student version of a NESSUS manual has been revised and improved, with additional example problems being added to expand the scope of the example application problems. This report documents two research accomplishments in the integration of a new sampling algorithm into NESSUS and in the testing of the new algorithm. The new Latin Hypercube Sampling (LHS) subroutines use the latest NESSUS input file format and specific files for writing output. The LHS subroutines are called out early in the program so that no unnecessary calculations are performed. Proper correlation between sets of multidimensional coordinates can be obtained by using NESSUS' LHS capabilities. Finally, two types of correlation are written to the appropriate output file. The program enhancement was tested by repeatedly estimating the mean, standard deviation, and 99th percentile of four different responses using Monte Carlo (MC) and LHS. These test cases, put forth by the Society of Automotive Engineers, are used to compare probabilistic methods. For all test cases, it is shown that LHS has a lower estimation error than MC when used to estimate the mean, standard deviation, and 99th percentile of the four responses at the 50 percent confidence level and using the same number of response evaluations for each method. In addition, LHS requires fewer calculations than MC in order to be 99.7 percent confident that a single mean, standard deviation, or 99th percentile estimate will be within at most 3 percent of the true value of the each parameter. Again, this is shown for all of the test cases studied. For that reason it can be said that NESSUS is an important reliability tool that has a variety of sound probabilistic methods a user can employ; furthermore, the newest LHS module is a valuable new enhancement of the program.

Medical statistics and hospital medicine: the case of the smallpox vaccination.

PubMed

Rusnock, Andrea

2007-01-01

Between 1799 and 1806, trials of vaccination to determine its safety and efficacy were undertaken in hospitals in London, Paris, Vienna, and Boston. These trials were among the first instances of formal hospital evaluations of a medical procedure and signal a growing acceptance of a relatively new approach to medical practice. These early evaluations of smallpox vaccination also relied on descriptive and quantitative accounts, as well as probabilistic analyses, and thus occupy a significant, yet hitherto unexamined, place in the history of medical statistics.

Modelling and analysis of the sugar cataract development process using stochastic hybrid systems.

PubMed

Riley, D; Koutsoukos, X; Riley, K

2009-05-01

Modelling and analysis of biochemical systems such as sugar cataract development (SCD) are critical because they can provide new insights into systems, which cannot be easily tested with experiments; however, they are challenging problems due to the highly coupled chemical reactions that are involved. The authors present a stochastic hybrid system (SHS) framework for modelling biochemical systems and demonstrate the approach for the SCD process. A novel feature of the framework is that it allows modelling the effect of drug treatment on the system dynamics. The authors validate the three sugar cataract models by comparing trajectories computed by two simulation algorithms. Further, the authors present a probabilistic verification method for computing the probability of sugar cataract formation for different chemical concentrations using safety and reachability analysis methods for SHSs. The verification method employs dynamic programming based on a discretisation of the state space and therefore suffers from the curse of dimensionality. To analyse the SCD process, a parallel dynamic programming implementation that can handle large, realistic systems was developed. Although scalability is a limiting factor, this work demonstrates that the proposed method is feasible for realistic biochemical systems.

Radioactive dispersion analysis for hypothetical nuclear power plant (NPP) candidate site in Perak state, Malaysia

NASA Astrophysics Data System (ADS)

Shamsuddin, Shazmeen Daniar; Basri, Nor Afifah; Omar, Nurlyana; Koh, Meng-Hock; Ramli, Ahmad Termizi; Saridan Wan Hassan, Wan Muhamad

2017-10-01

Malaysia is planning to build a nuclear power plant (NPP) by 2030 to diversify the national electricity supply and resources. Selection of an NPP site must consider various factors, especially nuclear safety consideration to fulfil the nuclear safety objectives. Environmental Risk Assessment Analysis is a part of safety requirements by the International Atomic Energy Agency (IAEA) prior to the NPP commissioning process. Risk Assessments Analysis (RIA) is compulsory for the NPP site evaluation. One of RIA methods are Radioactive Dispersion Analysis using probabilistic risk analysis software. It is also important to perform studies to estimate the impact to the neighbouring population in the case of a nuclear accident at the power plant. In the present work, aimed to study the impact of a hypothetical nuclear accident by simulating the dispersion pattern of radionuclides originated from a candidate site at Manjung, Perak. The work has been performed using the HotSpot Health Physics codes. Two types of radionuclides have been considered namely 137Cs and 131I. In calculations, the initial concentration of radioactive materials of Fukushima Daiichi accident data are used which are 2.06 x 1016 Bq and 1.68 x 1017 Bq respectively for the two radionuclides. The result shows that the dispersion distance obtained from both software are not the same. It shows that 137Cs and 131I can be dispersed as far as 16 km and 80 km away from the site during radiological accident respectively, reaching major towns in Perak. Using HOTSPOT, the estimated total effective dose equivalent (TEDE) for 137Cs and 131I at major towns in Perak such as Lumut and Sitiawan are 1.2 mSv and 9.9 mSv. As for Taiping, Ipoh, Kampar, and Teluk Intan the estimated TEDE is around 0.2 mSv and 1.6 mSv respectively. In conclusion, the dispersion can reach as far as 80 km from the site. However, estimated annual effective dose is not more than 1 mSv limit, which is considered acceptable in the point of view of radiological health risk for human and the environment.

Probabilistic Inference in General Graphical Models through Sampling in Stochastic Networks of Spiking Neurons

PubMed Central

Pecevski, Dejan; Buesing, Lars; Maass, Wolfgang

2011-01-01

An important open problem of computational neuroscience is the generic organization of computations in networks of neurons in the brain. We show here through rigorous theoretical analysis that inherent stochastic features of spiking neurons, in combination with simple nonlinear computational operations in specific network motifs and dendritic arbors, enable networks of spiking neurons to carry out probabilistic inference through sampling in general graphical models. In particular, it enables them to carry out probabilistic inference in Bayesian networks with converging arrows (“explaining away”) and with undirected loops, that occur in many real-world tasks. Ubiquitous stochastic features of networks of spiking neurons, such as trial-to-trial variability and spontaneous activity, are necessary ingredients of the underlying computational organization. We demonstrate through computer simulations that this approach can be scaled up to neural emulations of probabilistic inference in fairly large graphical models, yielding some of the most complex computations that have been carried out so far in networks of spiking neurons. PMID:22219717

Stability analysis for discrete-time stochastic memristive neural networks with both leakage and probabilistic delays.

PubMed

Liu, Hongjian; Wang, Zidong; Shen, Bo; Huang, Tingwen; Alsaadi, Fuad E

2018-06-01

This paper is concerned with the globally exponential stability problem for a class of discrete-time stochastic memristive neural networks (DSMNNs) with both leakage delays as well as probabilistic time-varying delays. For the probabilistic delays, a sequence of Bernoulli distributed random variables is utilized to determine within which intervals the time-varying delays fall at certain time instant. The sector-bounded activation function is considered in the addressed DSMNN. By taking into account the state-dependent characteristics of the network parameters and choosing an appropriate Lyapunov-Krasovskii functional, some sufficient conditions are established under which the underlying DSMNN is globally exponentially stable in the mean square. The derived conditions are made dependent on both the leakage and the probabilistic delays, and are therefore less conservative than the traditional delay-independent criteria. A simulation example is given to show the effectiveness of the proposed stability criterion. Copyright © 2018 Elsevier Ltd. All rights reserved.

Automated liver segmentation using a normalized probabilistic atlas

NASA Astrophysics Data System (ADS)

Linguraru, Marius George; Li, Zhixi; Shah, Furhawn; Chin, See; Summers, Ronald M.

2009-02-01

Probabilistic atlases of anatomical organs, especially the brain and the heart, have become popular in medical image analysis. We propose the construction of probabilistic atlases which retain structural variability by using a size-preserving modified affine registration. The organ positions are modeled in the physical space by normalizing the physical organ locations to an anatomical landmark. In this paper, a liver probabilistic atlas is constructed and exploited to automatically segment liver volumes from abdominal CT data. The atlas is aligned with the patient data through a succession of affine and non-linear registrations. The overlap and correlation with manual segmentations are 0.91 (0.93 DICE coefficient) and 0.99 respectively. Little work has taken place on the integration of volumetric measures of liver abnormality to clinical evaluations, which rely on linear estimates of liver height. Our application measures the liver height at the mid-hepatic line (0.94 correlation with manual measurements) and indicates that its combination with volumetric estimates could assist the development of a noninvasive tool to assess hepatomegaly.

Non-Deterministic Dynamic Instability of Composite Shells

NASA Technical Reports Server (NTRS)

Chamis, Christos C.; Abumeri, Galib H.

2004-01-01

A computationally effective method is described to evaluate the non-deterministic dynamic instability (probabilistic dynamic buckling) of thin composite shells. The method is a judicious combination of available computer codes for finite element, composite mechanics, and probabilistic structural analysis. The solution method is incrementally updated Lagrangian. It is illustrated by applying it to thin composite cylindrical shell subjected to dynamic loads. Both deterministic and probabilistic buckling loads are evaluated to demonstrate the effectiveness of the method. A universal plot is obtained for the specific shell that can be used to approximate buckling loads for different load rates and different probability levels. Results from this plot show that the faster the rate, the higher the buckling load and the shorter the time. The lower the probability, the lower is the buckling load for a specific time. Probabilistic sensitivity results show that the ply thickness, the fiber volume ratio and the fiber longitudinal modulus, dynamic load and loading rate are the dominant uncertainties, in that order.

Probabilistic analysis for fatigue strength degradation of materials

NASA Technical Reports Server (NTRS)

Royce, Lola

1989-01-01

This report presents the results of the first year of a research program conducted for NASA-LeRC by the University of Texas at San Antonio. The research included development of methodology that provides a probabilistic treatment of lifetime prediction of structural components of aerospace propulsion systems subjected to fatigue. Material strength degradation models, based on primitive variables, include both a fatigue strength reduction model and a fatigue crack growth model. Linear elastic fracture mechanics is utilized in the latter model. Probabilistic analysis is based on simulation, and both maximum entropy and maximum penalized likelihood methods are used for the generation of probability density functions. The resulting constitutive relationships are included in several computer programs, RANDOM2, RANDOM3, and RANDOM4. These programs determine the random lifetime of an engine component, in mechanical load cycles, to reach a critical fatigue strength or crack size. The material considered was a cast nickel base superalloy, one typical of those used in the Space Shuttle Main Engine.

ORNL Pre-test Analyses of A Large-scale Experiment in STYLE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Williams, Paul T; Yin, Shengjun; Klasky, Hilda B

Oak Ridge National Laboratory (ORNL) is conducting a series of numerical analyses to simulate a large scale mock-up experiment planned within the European Network for Structural Integrity for Lifetime Management non-RPV Components (STYLE). STYLE is a European cooperative effort to assess the structural integrity of (non-reactor pressure vessel) reactor coolant pressure boundary components relevant to ageing and life-time management and to integrate the knowledge created in the project into mainstream nuclear industry assessment codes. ORNL contributes work-in-kind support to STYLE Work Package 2 (Numerical Analysis/Advanced Tools) and Work Package 3 (Engineering Assessment Methods/LBB Analyses). This paper summarizes the current statusmore » of ORNL analyses of the STYLE Mock-Up3 large-scale experiment to simulate and evaluate crack growth in a cladded ferritic pipe. The analyses are being performed in two parts. In the first part, advanced fracture mechanics models are being developed and performed to evaluate several experiment designs taking into account the capabilities of the test facility while satisfying the test objectives. Then these advanced fracture mechanics models will be utilized to simulate the crack growth in the large scale mock-up test. For the second part, the recently developed ORNL SIAM-PFM open-source, cross-platform, probabilistic computational tool will be used to generate an alternative assessment for comparison with the advanced fracture mechanics model results. The SIAM-PFM probabilistic analysis of the Mock-Up3 experiment will utilize fracture modules that are installed into a general probabilistic framework. The probabilistic results of the Mock-Up3 experiment obtained from SIAM-PFM will be compared to those results generated using the deterministic 3D nonlinear finite-element modeling approach. The objective of the probabilistic analysis is to provide uncertainty bounds that will assist in assessing the more detailed 3D finite-element solutions and to also assess the level of confidence that can be placed in the best-estimate finiteelement solutions.« less

[Uncertainty characterization approaches for ecological risk assessment of polycyclic aromatic hydrocarbon in Taihu Lake].

PubMed

Guo, Guang-Hui; Wu, Feng-Chang; He, Hong-Ping; Feng, Cheng-Lian; Zhang, Rui-Qing; Li, Hui-Xian

2012-04-01

Probabilistic approaches, such as Monte Carlo Sampling (MCS) and Latin Hypercube Sampling (LHS), and non-probabilistic approaches, such as interval analysis, fuzzy set theory and variance propagation, were used to characterize uncertainties associated with risk assessment of sigma PAH8 in surface water of Taihu Lake. The results from MCS and LHS were represented by probability distributions of hazard quotients of sigma PAH8 in surface waters of Taihu Lake. The probabilistic distribution of hazard quotient were obtained from the results of MCS and LHS based on probabilistic theory, which indicated that the confidence intervals of hazard quotient at 90% confidence level were in the range of 0.000 18-0.89 and 0.000 17-0.92, with the mean of 0.37 and 0.35, respectively. In addition, the probabilities that the hazard quotients from MCS and LHS exceed the threshold of 1 were 9.71% and 9.68%, respectively. The sensitivity analysis suggested the toxicity data contributed the most to the resulting distribution of quotients. The hazard quotient of sigma PAH8 to aquatic organisms ranged from 0.000 17 to 0.99 using interval analysis. The confidence interval was (0.001 5, 0.016 3) at the 90% confidence level calculated using fuzzy set theory, and the confidence interval was (0.000 16, 0.88) at the 90% confidence level based on the variance propagation. These results indicated that the ecological risk of sigma PAH8 to aquatic organisms were low. Each method has its own set of advantages and limitations, which was based on different theory; therefore, the appropriate method should be selected on a case-by-case to quantify the effects of uncertainties on the ecological risk assessment. Approach based on the probabilistic theory was selected as the most appropriate method to assess the risk of sigma PAH8 in surface water of Taihu Lake, which provided an important scientific foundation of risk management and control for organic pollutants in water.

A Tutorial in Bayesian Potential Outcomes Mediation Analysis.

PubMed

Miočević, Milica; Gonzalez, Oscar; Valente, Matthew J; MacKinnon, David P

2018-01-01

Statistical mediation analysis is used to investigate intermediate variables in the relation between independent and dependent variables. Causal interpretation of mediation analyses is challenging because randomization of subjects to levels of the independent variable does not rule out the possibility of unmeasured confounders of the mediator to outcome relation. Furthermore, commonly used frequentist methods for mediation analysis compute the probability of the data given the null hypothesis, which is not the probability of a hypothesis given the data as in Bayesian analysis. Under certain assumptions, applying the potential outcomes framework to mediation analysis allows for the computation of causal effects, and statistical mediation in the Bayesian framework gives indirect effects probabilistic interpretations. This tutorial combines causal inference and Bayesian methods for mediation analysis so the indirect and direct effects have both causal and probabilistic interpretations. Steps in Bayesian causal mediation analysis are shown in the application to an empirical example.

A Research Roadmap for Computation-Based Human Reliability Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boring, Ronald; Mandelli, Diego; Joe, Jeffrey

2015-08-01

The United States (U.S.) Department of Energy (DOE) is sponsoring research through the Light Water Reactor Sustainability (LWRS) program to extend the life of the currently operating fleet of commercial nuclear power plants. The Risk Informed Safety Margin Characterization (RISMC) research pathway within LWRS looks at ways to maintain and improve the safety margins of these plants. The RISMC pathway includes significant developments in the area of thermalhydraulics code modeling and the development of tools to facilitate dynamic probabilistic risk assessment (PRA). PRA is primarily concerned with the risk of hardware systems at the plant; yet, hardware reliability is oftenmore » secondary in overall risk significance to human errors that can trigger or compound undesirable events at the plant. This report highlights ongoing efforts to develop a computation-based approach to human reliability analysis (HRA). This computation-based approach differs from existing static and dynamic HRA approaches in that it: (i) interfaces with a dynamic computation engine that includes a full scope plant model, and (ii) interfaces with a PRA software toolset. The computation-based HRA approach presented in this report is called the Human Unimodels for Nuclear Technology to Enhance Reliability (HUNTER) and incorporates in a hybrid fashion elements of existing HRA methods to interface with new computational tools developed under the RISMC pathway. The goal of this research effort is to model human performance more accurately than existing approaches, thereby minimizing modeling uncertainty found in current plant risk models.« less

The DOZZ formula from the path integral

NASA Astrophysics Data System (ADS)

Kupiainen, Antti; Rhodes, Rémi; Vargas, Vincent

2018-05-01

We present a rigorous proof of the Dorn, Otto, Zamolodchikov, Zamolodchikov formula (the DOZZ formula) for the 3 point structure constants of Liouville Conformal Field Theory (LCFT) starting from a rigorous probabilistic construction of the functional integral defining LCFT given earlier by the authors and David. A crucial ingredient in our argument is a probabilistic derivation of the reflection relation in LCFT based on a refined tail analysis of Gaussian multiplicative chaos measures.

ORAM-SENTINEL{trademark} demonstration at Fitzpatrick. Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, L.K.; Anderson, V.M.; Mohammadi, K.

1998-06-01

New York Power Authority, in cooperation with EPRI, installed the ORAM-SENTINEL{trademark} software at James A. Fitzpatrick (JAF) Nuclear Power Plant. This software incorporates models of safety systems and support systems that are used for defense-in-depth in the plant during outage and on-line periods. A secondary goal was to include some pre-analyzed risk results to validate the methodology for quantitative assessment of the plant risks during proposed on-line maintenance. During the past year, New York Power Authority personnel have become familiar with the formal computerized Safety Assessment process associated with on-line and outage maintenance. The report describes techniques and lessons learnedmore » during development of the ORAM-SENTINEL model at JAF. It overviews the systems important to the Safety Function Assessment Process and provides details on development of the Plant Transient Assessment process using the station emergency operating procedures. The assessment results are displayed by color (green, yellow, orange, red) to show decreasing safety conditions. The report describes use of the JAF Probabilistic Safety Assessment within the ORAM-SENTINEL code to calculate an instantaneous core damage frequency and the criteria by which this frequency is translated to a color indicator.« less

Model based inference from microvascular measurements: Combining experimental measurements and model predictions using a Bayesian probabilistic approach

PubMed Central

Rasmussen, Peter M.; Smith, Amy F.; Sakadžić, Sava; Boas, David A.; Pries, Axel R.; Secomb, Timothy W.; Østergaard, Leif

2017-01-01

Objective In vivo imaging of the microcirculation and network-oriented modeling have emerged as powerful means of studying microvascular function and understanding its physiological significance. Network-oriented modeling may provide the means of summarizing vast amounts of data produced by high-throughput imaging techniques in terms of key, physiological indices. To estimate such indices with sufficient certainty, however, network-oriented analysis must be robust to the inevitable presence of uncertainty due to measurement errors as well as model errors. Methods We propose the Bayesian probabilistic data analysis framework as a means of integrating experimental measurements and network model simulations into a combined and statistically coherent analysis. The framework naturally handles noisy measurements and provides posterior distributions of model parameters as well as physiological indices associated with uncertainty. Results We applied the analysis framework to experimental data from three rat mesentery networks and one mouse brain cortex network. We inferred distributions for more than five hundred unknown pressure and hematocrit boundary conditions. Model predictions were consistent with previous analyses, and remained robust when measurements were omitted from model calibration. Conclusion Our Bayesian probabilistic approach may be suitable for optimizing data acquisition and for analyzing and reporting large datasets acquired as part of microvascular imaging studies. PMID:27987383

Assessment of flood susceptible areas using spatially explicit, probabilistic multi-criteria decision analysis

NASA Astrophysics Data System (ADS)

Tang, Zhongqian; Zhang, Hua; Yi, Shanzhen; Xiao, Yangfan

2018-03-01

GIS-based multi-criteria decision analysis (MCDA) is increasingly used to support flood risk assessment. However, conventional GIS-MCDA methods fail to adequately represent spatial variability and are accompanied with considerable uncertainty. It is, thus, important to incorporate spatial variability and uncertainty into GIS-based decision analysis procedures. This research develops a spatially explicit, probabilistic GIS-MCDA approach for the delineation of potentially flood susceptible areas. The approach integrates the probabilistic and the local ordered weighted averaging (OWA) methods via Monte Carlo simulation, to take into account the uncertainty related to criteria weights, spatial heterogeneity of preferences and the risk attitude of the analyst. The approach is applied to a pilot study for the Gucheng County, central China, heavily affected by the hazardous 2012 flood. A GIS database of six geomorphological and hydrometeorological factors for the evaluation of susceptibility was created. Moreover, uncertainty and sensitivity analysis were performed to investigate the robustness of the model. The results indicate that the ensemble method improves the robustness of the model outcomes with respect to variation in criteria weights and identifies which criteria weights are most responsible for the variability of model outcomes. Therefore, the proposed approach is an improvement over the conventional deterministic method and can provides a more rational, objective and unbiased tool for flood susceptibility evaluation.

Towards high-speed autonomous navigation of unknown environments

NASA Astrophysics Data System (ADS)

Richter, Charles; Roy, Nicholas

2015-05-01

In this paper, we summarize recent research enabling high-speed navigation in unknown environments for dynamic robots that perceive the world through onboard sensors. Many existing solutions to this problem guarantee safety by making the conservative assumption that any unknown portion of the map may contain an obstacle, and therefore constrain planned motions to lie entirely within known free space. In this work, we observe that safety constraints may significantly limit performance and that faster navigation is possible if the planner reasons about collision with unobserved obstacles probabilistically. Our overall approach is to use machine learning to approximate the expected costs of collision using the current state of the map and the planned trajectory. Our contribution is to demonstrate fast but safe planning using a learned function to predict future collision probabilities.

Analysis of the French insurance market exposure to floods: a stochastic model combining river overflow and surface runoff

NASA Astrophysics Data System (ADS)

Moncoulon, D.; Labat, D.; Ardon, J.; Onfroy, T.; Leblois, E.; Poulard, C.; Aji, S.; Rémy, A.; Quantin, A.

2013-07-01

The analysis of flood exposure at a national scale for the French insurance market must combine the generation of a probabilistic event set of all possible but not yet occurred flood situations with hazard and damage modeling. In this study, hazard and damage models are calibrated on a 1995-2012 historical event set, both for hazard results (river flow, flooded areas) and loss estimations. Thus, uncertainties in the deterministic estimation of a single event loss are known before simulating a probabilistic event set. To take into account at least 90% of the insured flood losses, the probabilistic event set must combine the river overflow (small and large catchments) with the surface runoff due to heavy rainfall, on the slopes of the watershed. Indeed, internal studies of CCR claim database has shown that approximately 45% of the insured flood losses are located inside the floodplains and 45% outside. 10% other percent are due to seasurge floods and groundwater rise. In this approach, two independent probabilistic methods are combined to create a single flood loss distribution: generation of fictive river flows based on the historical records of the river gauge network and generation of fictive rain fields on small catchments, calibrated on the 1958-2010 Météo-France rain database SAFRAN. All the events in the probabilistic event sets are simulated with the deterministic model. This hazard and damage distribution is used to simulate the flood losses at the national scale for an insurance company (MACIF) and to generate flood areas associated with hazard return periods. The flood maps concern river overflow and surface water runoff. Validation of these maps is conducted by comparison with the address located claim data on a small catchment (downstream Argens).

Probabilistic Tsunami Hazard Analysis

NASA Astrophysics Data System (ADS)

Thio, H. K.; Ichinose, G. A.; Somerville, P. G.; Polet, J.

2006-12-01

The recent tsunami disaster caused by the 2004 Sumatra-Andaman earthquake has focused our attention to the hazard posed by large earthquakes that occur under water, in particular subduction zone earthquakes, and the tsunamis that they generate. Even though these kinds of events are rare, the very large loss of life and material destruction caused by this earthquake warrant a significant effort towards the mitigation of the tsunami hazard. For ground motion hazard, Probabilistic Seismic Hazard Analysis (PSHA) has become a standard practice in the evaluation and mitigation of seismic hazard to populations in particular with respect to structures, infrastructure and lifelines. Its ability to condense the complexities and variability of seismic activity into a manageable set of parameters greatly facilitates the design of effective seismic resistant buildings but also the planning of infrastructure projects. Probabilistic Tsunami Hazard Analysis (PTHA) achieves the same goal for hazards posed by tsunami. There are great advantages of implementing such a method to evaluate the total risk (seismic and tsunami) to coastal communities. The method that we have developed is based on the traditional PSHA and therefore completely consistent with standard seismic practice. Because of the strong dependence of tsunami wave heights on bathymetry, we use a full waveform tsunami waveform computation in lieu of attenuation relations that are common in PSHA. By pre-computing and storing the tsunami waveforms at points along the coast generated for sets of subfaults that comprise larger earthquake faults, we can efficiently synthesize tsunami waveforms for any slip distribution on those faults by summing the individual subfault tsunami waveforms (weighted by their slip). This efficiency make it feasible to use Green's function summation in lieu of attenuation relations to provide very accurate estimates of tsunami height for probabilistic calculations, where one typically computes thousands of earthquake scenarios. We have carried out preliminary tsunami hazard calculations for different return periods for western North America and Hawaii based on thousands of earthquake scenarios around the Pacific rim and along the coast of North America. We will present tsunami hazard maps for several return periods and also discuss how to use these results for probabilistic inundation and runup mapping. Our knowledge of certain types of tsunami sources is very limited (e.g. submarine landslides), but a probabilistic framework for tsunami hazard evaluation can include even such sources and their uncertainties and present the overall hazard in a meaningful and consistent way.

Application of Non-Deterministic Methods to Assess Modeling Uncertainties for Reinforced Carbon-Carbon Debris Impacts

NASA Technical Reports Server (NTRS)

Lyle, Karen H.; Fasanella, Edwin L.; Melis, Matthew; Carney, Kelly; Gabrys, Jonathan

2004-01-01

The Space Shuttle Columbia Accident Investigation Board (CAIB) made several recommendations for improving the NASA Space Shuttle Program. An extensive experimental and analytical program has been developed to address two recommendations related to structural impact analysis. The objective of the present work is to demonstrate the application of probabilistic analysis to assess the effect of uncertainties on debris impacts on Space Shuttle Reinforced Carbon-Carbon (RCC) panels. The probabilistic analysis is used to identify the material modeling parameters controlling the uncertainty. A comparison of the finite element results with limited experimental data provided confidence that the simulations were adequately representing the global response of the material. Five input parameters were identified as significantly controlling the response.

Durability reliability analysis for corroding concrete structures under uncertainty

NASA Astrophysics Data System (ADS)

Zhang, Hao

2018-02-01

This paper presents a durability reliability analysis of reinforced concrete structures subject to the action of marine chloride. The focus is to provide insight into the role of epistemic uncertainties on durability reliability. The corrosion model involves a number of variables whose probabilistic characteristics cannot be fully determined due to the limited availability of supporting data. All sources of uncertainty, both aleatory and epistemic, should be included in the reliability analysis. Two methods are available to formulate the epistemic uncertainty: the imprecise probability-based method and the purely probabilistic method in which the epistemic uncertainties are modeled as random variables. The paper illustrates how the epistemic uncertainties are modeled and propagated in the two methods, and shows how epistemic uncertainties govern the durability reliability.

Comparative study of stock trend prediction using time delay, recurrent and probabilistic neural networks.

PubMed

Saad, E W; Prokhorov, D V; Wunsch, D C

1998-01-01

Three networks are compared for low false alarm stock trend predictions. Short-term trends, particularly attractive for neural network analysis, can be used profitably in scenarios such as option trading, but only with significant risk. Therefore, we focus on limiting false alarms, which improves the risk/reward ratio by preventing losses. To predict stock trends, we exploit time delay, recurrent, and probabilistic neural networks (TDNN, RNN, and PNN, respectively), utilizing conjugate gradient and multistream extended Kalman filter training for TDNN and RNN. We also discuss different predictability analysis techniques and perform an analysis of predictability based on a history of daily closing price. Our results indicate that all the networks are feasible, the primary preference being one of convenience.

Dependence in probabilistic modeling Dempster-Shafer theory and probability bounds analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ferson, Scott; Nelsen, Roger B.; Hajagos, Janos

2015-05-01

This report summarizes methods to incorporate information (or lack of information) about inter-variable dependence into risk assessments that use Dempster-Shafer theory or probability bounds analysis to address epistemic and aleatory uncertainty. The report reviews techniques for simulating correlated variates for a given correlation measure and dependence model, computation of bounds on distribution functions under a specified dependence model, formulation of parametric and empirical dependence models, and bounding approaches that can be used when information about the intervariable dependence is incomplete. The report also reviews several of the most pervasive and dangerous myths among risk analysts about dependence in probabilistic models.

Probabilistic Analysis of Structural Member from Recycled Aggregate Concrete

NASA Astrophysics Data System (ADS)

Broukalová, I.; Šeps, K.

2017-09-01

The paper aims at the topic of sustainable building concerning recycling of waste rubble concrete from demolition. Considering demands of maximising recycled aggregate use and minimising of cement consumption, composite from recycled concrete aggregate was proposed. The objective of the presented investigations was to verify feasibility of the recycled aggregate cement based fibre reinforced composite in a structural member. Reliability of wall from recycled aggregate fibre reinforced composite was assessed in a probabilistic analysis of a load-bearing capacity of the wall. The applicability of recycled aggregate fibre reinforced concrete in structural applications was demonstrated. The outcomes refer to issue of high scatter of material parameters of recycled aggregate concretes.

Stochastic methods for analysis of power flow in electric networks

NASA Astrophysics Data System (ADS)

1982-09-01

The modeling and effects of probabilistic behavior on steady state power system operation were analyzed. A solution to the steady state network flow equations which adhere both to Kirchoff's Laws and probabilistic laws, using either combinatorial or functional approximation techniques was obtained. The development of sound techniques for producing meaningful data to serve as input is examined. Electric demand modeling, equipment failure analysis, and algorithm development are investigated. Two major development areas are described: a decomposition of stochastic processes which gives stationarity, ergodicity, and even normality; and a powerful surrogate probability approach using proportions of time which allows the calculation of joint events from one dimensional probability spaces.

Hazard function analysis for flood planning under nonstationarity

NASA Astrophysics Data System (ADS)

Read, Laura K.; Vogel, Richard M.

2016-05-01

The field of hazard function analysis (HFA) involves a probabilistic assessment of the "time to failure" or "return period," T, of an event of interest. HFA is used in epidemiology, manufacturing, medicine, actuarial statistics, reliability engineering, economics, and elsewhere. For a stationary process, the probability distribution function (pdf) of the return period always follows an exponential distribution, the same is not true for nonstationary processes. When the process of interest, X, exhibits nonstationary behavior, HFA can provide a complementary approach to risk analysis with analytical tools particularly useful for hydrological applications. After a general introduction to HFA, we describe a new mathematical linkage between the magnitude of the flood event, X, and its return period, T, for nonstationary processes. We derive the probabilistic properties of T for a nonstationary one-parameter exponential model of X, and then use both Monte-Carlo simulation and HFA to generalize the behavior of T when X arises from a nonstationary two-parameter lognormal distribution. For this case, our findings suggest that a two-parameter Weibull distribution provides a reasonable approximation for the pdf of T. We document how HFA can provide an alternative approach to characterize the probabilistic properties of both nonstationary flood series and the resulting pdf of T.

Stochastic Simulation and Forecast of Hydrologic Time Series Based on Probabilistic Chaos Expansion

NASA Astrophysics Data System (ADS)

Li, Z.; Ghaith, M.

2017-12-01

Hydrological processes are characterized by many complex features, such as nonlinearity, dynamics and uncertainty. How to quantify and address such complexities and uncertainties has been a challenging task for water engineers and managers for decades. To support robust uncertainty analysis, an innovative approach for the stochastic simulation and forecast of hydrologic time series is developed is this study. Probabilistic Chaos Expansions (PCEs) are established through probabilistic collocation to tackle uncertainties associated with the parameters of traditional hydrological models. The uncertainties are quantified in model outputs as Hermite polynomials with regard to standard normal random variables. Sequentially, multivariate analysis techniques are used to analyze the complex nonlinear relationships between meteorological inputs (e.g., temperature, precipitation, evapotranspiration, etc.) and the coefficients of the Hermite polynomials. With the established relationships between model inputs and PCE coefficients, forecasts of hydrologic time series can be generated and the uncertainties in the future time series can be further tackled. The proposed approach is demonstrated using a case study in China and is compared to a traditional stochastic simulation technique, the Markov-Chain Monte-Carlo (MCMC) method. Results show that the proposed approach can serve as a reliable proxy to complicated hydrological models. It can provide probabilistic forecasting in a more computationally efficient manner, compared to the traditional MCMC method. This work provides technical support for addressing uncertainties associated with hydrological modeling and for enhancing the reliability of hydrological modeling results. Applications of the developed approach can be extended to many other complicated geophysical and environmental modeling systems to support the associated uncertainty quantification and risk analysis.

User perception and interpretation of tornado probabilistic hazard information: Comparison of four graphical designs.

PubMed

Miran, Seyed M; Ling, Chen; James, Joseph J; Gerard, Alan; Rothfusz, Lans

2017-11-01

Effective design for presenting severe weather information is important to reduce devastating consequences of severe weather. The Probabilistic Hazard Information (PHI) system for severe weather is being developed by NOAA National Severe Storms Laboratory (NSSL) to communicate probabilistic hazardous weather information. This study investigates the effects of four PHI graphical designs for tornado threat, namely, "four-color"," red-scale", "grayscale" and "contour", on users' perception, interpretation, and reaction to threat information. PHI is presented on either a map background or a radar background. Analysis showed that the accuracy was significantly higher and response time faster when PHI was displayed on map background as compared to radar background due to better contrast. When displayed on a radar background, "grayscale" design resulted in a higher accuracy of responses. Possibly due to familiarity, participants reported four-color design as their favorite design, which also resulted in the fastest recognition of probability levels on both backgrounds. Our study shows the importance of using intuitive color-coding and sufficient contrast in conveying probabilistic threat information via graphical design. We also found that users follows a rational perceiving-judging-feeling-and acting approach in processing probabilistic hazard information for tornado. Copyright © 2017 Elsevier Ltd. All rights reserved.

Selective Estrogen Receptor Modulation Increases Hippocampal Activity during Probabilistic Association Learning in Schizophrenia

PubMed Central

Kindler, Jochen; Weickert, Cynthia Shannon; Skilleter, Ashley J; Catts, Stanley V; Lenroot, Rhoshel; Weickert, Thomas W

2015-01-01

People with schizophrenia show probabilistic association learning impairment in conjunction with abnormal neural activity. The selective estrogen receptor modulator (SERM) raloxifene preserves neural activity during memory in healthy older men and improves memory in schizophrenia. Here, we tested the extent to which raloxifene modifies neural activity during learning in schizophrenia. Nineteen people with schizophrenia participated in a twelve-week randomized, double-blind, placebo-controlled, cross-over adjunctive treatment trial of the SERM raloxifene administered orally at 120 mg daily to assess brain activity during probabilistic association learning using functional magnetic resonance imaging (fMRI). Raloxifene improved probabilistic association learning and significantly increased fMRI BOLD activity in the hippocampus and parahippocampal gyrus relative to placebo. A separate region of interest confirmatory analysis in 21 patients vs 36 healthy controls showed a positive association between parahippocampal neural activity and learning in patients, but no such relationship in the parahippocampal gyrus of healthy controls. Thus, selective estrogen receptor modulation by raloxifene concurrently increases activity in the parahippocampal gyrus and improves probabilistic association learning in schizophrenia. These results support a role for estrogen receptor modulation of mesial temporal lobe neural activity in the remediation of learning disabilities in both men and women with schizophrenia. PMID:25829142

Latin American Clinical Epidemiology Network Series - Paper 8: Ticagrelor was cost-effective vs. clopidogrel in acute coronary syndrome in Chile.

PubMed

De la Puente, Catherine; Vallejos, Carlos; Bustos, Luis; Zaror, Carlos; Velasquez, Monica; Lanas, Fernando

2017-06-01

To evaluate the incremental cost-effectiveness ratio (ICER) of the use of ticagrelor as a substitute for clopidogrel for secondary prevention of acute coronary syndrome in Chile. Cost-effectiveness analysis based on a Markov model: Safety and effectiveness data of ticagrelor were obtained from a systematic review of the literature. Costs are expressed in Chilean pesos (CLP) as of 2013. The evaluation was conducted from the payer standpoint. A probabilistic sensitivity analysis comprising discount rates and national cost variability was done. A budget impact analysis estimated for 2015 was conducted to calculate the total cost for both treatments. The ICER with a discount rate of 6% for ticagrelor vs. clopidogrel was CLP 4,893,126 per quality-adjusted life-year (QALY) gained (=9,689 US$). In the budget impact analysis for the baseline scenario, considering 100% of treatment, coverage, and adherence, ticagrelor represented an additional cost of CLP 5,233,854,272, for 979 QALYs gained compared with clopidogrel. Ticagrelor is cost-effective in comparison with clopidogrel for the secondary prevention of acute coronary syndrome. These findings are similar to those reported in other international cost-effectiveness studies. Copyright © 2016 Elsevier Inc. All rights reserved.

Assessment of the transportation route of oversize and excessive loads in relation to the load-bearing capacity of existing bridges

NASA Astrophysics Data System (ADS)

Doležel, Jiří; Novák, Drahomír; Petrů, Jan

2017-09-01

Transportation routes of oversize and excessive loads are currently planned in relation to ensure the transit of a vehicle through critical points on the road. Critical points are level-intersection of roads, bridges etc. This article presents a comprehensive procedure to determine a reliability and a load-bearing capacity level of the existing bridges on highways and roads using the advanced methods of reliability analysis based on simulation techniques of Monte Carlo type in combination with nonlinear finite element method analysis. The safety index is considered as a main criterion of the reliability level of the existing construction structures and the index is described in current structural design standards, e.g. ISO and Eurocode. An example of a single-span slab bridge made of precast prestressed concrete girders of the 60 year current time and its load bearing capacity is set for the ultimate limit state and serviceability limit state. The structure’s design load capacity was estimated by the full probability nonlinear MKP analysis using a simulation technique Latin Hypercube Sampling (LHS). Load-bearing capacity values based on a fully probabilistic analysis are compared with the load-bearing capacity levels which were estimated by deterministic methods of a critical section of the most loaded girders.

Trastuzumab in early stage breast cancer: a cost-effectiveness analysis for Belgium.

PubMed

Neyt, Mattias; Huybrechts, Michel; Hulstaert, Frank; Vrijens, France; Ramaekers, Dirk

2008-08-01

Although trastuzumab is traditionally used in metastatic breast cancer treatment, studies reported on the efficacy and safety of trastuzumab in adjuvant setting for the treatment of early stage breast cancer in HER2+ tumors. We estimated the cost-effectiveness and budget impact of reimbursing trastuzumab in this indication from a payer's perspective. We constructed a health economic model. Long-term consequences of preventing patients to progress to metastatic breast cancer and side effects such as congestive heart failure were taken into account. Uncertainty was handled applying probabilistic modeling and through probabilistic sensitivity analyses. In the HERA scenario, applying an arbitrary threshold of euro30000 per life-year gained, early stage breast cancer treatment with trastuzumab is cost-effective for 9 out of 15 analyzed subgroups (according to age and stage). In contrast, treatment according to the FinHer scenario is cost-effective in 14 subgroups. Furthermore, the FinHer regimen is most of the times cost saving with an average incremental cost of euro668, euro-1045, and euro-6869 for respectively stages I, II and III breast cancer patients whereas the HERA regimen is never cost saving due to the higher initial treatment costs. The model shows better cost-effectiveness for the 9-week initial treatment (FinHer) compared to no trastuzumab treatment than for the 1-year post-chemotherapy treatment (HERA). Both from a medical and an economic point of view, the 9-week initial treatment regimen with trastuzumab shows promising results and justifies the initiation of a large comparative trial with a 1-year regimen.

Experiences with Probabilistic Analysis Applied to Controlled Systems

NASA Technical Reports Server (NTRS)

Kenny, Sean P.; Giesy, Daniel P.

2004-01-01

This paper presents a semi-analytic method for computing frequency dependent means, variances, and failure probabilities for arbitrarily large-order closed-loop dynamical systems possessing a single uncertain parameter or with multiple highly correlated uncertain parameters. The approach will be shown to not suffer from the same computational challenges associated with computing failure probabilities using conventional FORM/SORM techniques. The approach is demonstrated by computing the probabilistic frequency domain performance of an optimal feed-forward disturbance rejection scheme.