A probabilistic asteroid impact risk model: assessment of sub-300 m impacts

NASA Astrophysics Data System (ADS)

Mathias, Donovan L.; Wheeler, Lorien F.; Dotson, Jessie L.

2017-06-01

A comprehensive asteroid threat assessment requires the quantification of both the impact likelihood and resulting consequence across the range of possible events. This paper presents a probabilistic asteroid impact risk (PAIR) assessment model developed for this purpose. The model incorporates published impact frequency rates with state-of-the-art consequence assessment tools, applied within a Monte Carlo framework that generates sets of impact scenarios from uncertain input parameter distributions. Explicit treatment of atmospheric entry is included to produce energy deposition rates that account for the effects of thermal ablation and object fragmentation. These energy deposition rates are used to model the resulting ground damage, and affected populations are computed for the sampled impact locations. The results for each scenario are aggregated into a distribution of potential outcomes that reflect the range of uncertain impact parameters, population densities, and strike probabilities. As an illustration of the utility of the PAIR model, the results are used to address the question of what minimum size asteroid constitutes a threat to the population. To answer this question, complete distributions of results are combined with a hypothetical risk tolerance posture to provide the minimum size, given sets of initial assumptions for objects up to 300 m in diameter. Model outputs demonstrate how such questions can be answered and provide a means for interpreting the effect that input assumptions and uncertainty can have on final risk-based decisions. Model results can be used to prioritize investments to gain knowledge in critical areas or, conversely, to identify areas where additional data have little effect on the metrics of interest.

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 volcanic hazard assessments of Pyroclastic Density Currents: ongoing practices and future perspectives

NASA Astrophysics Data System (ADS)

Tierz, Pablo; Sandri, Laura; Ramona Stefanescu, Elena; Patra, Abani; Marzocchi, Warner; Costa, Antonio; Sulpizio, Roberto

2014-05-01

Explosive volcanoes and, especially, Pyroclastic Density Currents (PDCs) pose an enormous threat to populations living in the surroundings of volcanic areas. Difficulties in the modeling of PDCs are related to (i) very complex and stochastic physical processes, intrinsic to their occurrence, and (ii) to a lack of knowledge about how these processes actually form and evolve. This means that there are deep uncertainties (namely, of aleatory nature due to point (i) above, and of epistemic nature due to point (ii) above) associated to the study and forecast of PDCs. Consequently, the assessment of their hazard is better described in terms of probabilistic approaches rather than by deterministic ones. What is actually done to assess probabilistic hazard from PDCs is to couple deterministic simulators with statistical techniques that can, eventually, supply probabilities and inform about the uncertainties involved. In this work, some examples of both PDC numerical simulators (Energy Cone and TITAN2D) and uncertainty quantification techniques (Monte Carlo sampling -MC-, Polynomial Chaos Quadrature -PCQ- and Bayesian Linear Emulation -BLE-) are presented, and their advantages, limitations and future potential are underlined. The key point in choosing a specific method leans on the balance between its related computational cost, the physical reliability of the simulator and the pursued target of the hazard analysis (type of PDCs considered, time-scale selected for the analysis, particular guidelines received from decision-making agencies, etc.). Although current numerical and statistical techniques have brought important advances in probabilistic volcanic hazard assessment from PDCs, some of them may be further applicable to more sophisticated simulators. In addition, forthcoming improvements could be focused on three main multidisciplinary directions: 1) Validate the simulators frequently used (through comparison with PDC deposits and other simulators), 2) Decrease simulator runtimes (whether by increasing the knowledge about the physical processes or by doing more efficient programming, parallelization, ...) and 3) Improve uncertainty quantification techniques.

Quantifying uncertainty in health impact assessment: a case-study example on indoor housing ventilation.

PubMed

Mesa-Frias, Marco; Chalabi, Zaid; Foss, Anna M

2014-01-01

Quantitative health impact assessment (HIA) is increasingly being used to assess the health impacts attributable to an environmental policy or intervention. As a consequence, there is a need to assess uncertainties in the assessments because of the uncertainty in the HIA models. In this paper, a framework is developed to quantify the uncertainty in the health impacts of environmental interventions and is applied to evaluate the impacts of poor housing ventilation. The paper describes the development of the framework through three steps: (i) selecting the relevant exposure metric and quantifying the evidence of potential health effects of the exposure; (ii) estimating the size of the population affected by the exposure and selecting the associated outcome measure; (iii) quantifying the health impact and its uncertainty. The framework introduces a novel application for the propagation of uncertainty in HIA, based on fuzzy set theory. Fuzzy sets are used to propagate parametric uncertainty in a non-probabilistic space and are applied to calculate the uncertainty in the morbidity burdens associated with three indoor ventilation exposure scenarios: poor, fair and adequate. The case-study example demonstrates how the framework can be used in practice, to quantify the uncertainty in health impact assessment where there is insufficient information to carry out a probabilistic uncertainty analysis. © 2013.

Evaluation of severe accident risks: Quantification of major input parameters: MAACS (MELCOR Accident Consequence Code System) input

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

Sprung, J.L.; Jow, H-N; Rollstin, J.A.

1990-12-01

Estimation of offsite accident consequences is the customary final step in a probabilistic assessment of the risks of severe nuclear reactor accidents. Recently, the Nuclear Regulatory Commission reassessed the risks of severe accidents at five US power reactors (NUREG-1150). Offsite accident consequences for NUREG-1150 source terms were estimated using the MELCOR Accident Consequence Code System (MACCS). Before these calculations were performed, most MACCS input parameters were reviewed, and for each parameter reviewed, a best-estimate value was recommended. This report presents the results of these reviews. Specifically, recommended values and the basis for their selection are presented for MACCS atmospheric andmore » biospheric transport, emergency response, food pathway, and economic input parameters. Dose conversion factors and health effect parameters are not reviewed in this report. 134 refs., 15 figs., 110 tabs.« less

Probabilistic accident consequence uncertainty analysis: Dispersion and deposition uncertainty assessment, appendices A and B

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

Harper, F.T.; Young, M.L.; Miller, L.A.

The development of two new probabilistic accident consequence codes, MACCS and COSYMA, completed in 1990, estimate the risks presented by nuclear installations based on postulated frequencies and magnitudes of potential accidents. In 1991, the US Nuclear Regulatory Commission (NRC) and the Commission of the European Communities (CEC) began a joint uncertainty analysis of the two codes. The objective was to develop credible and traceable uncertainty distributions for the input variables of the codes. Expert elicitation, developed independently, was identified as the best technology available for developing a library of uncertainty distributions for the selected consequence parameters. The study was formulatedmore » jointly and was limited to the current code models and to physical quantities that could be measured in experiments. To validate the distributions generated for the wet deposition input variables, samples were taken from these distributions and propagated through the wet deposition code model along with the Gaussian plume model (GPM) implemented in the MACCS and COSYMA codes. Resulting distributions closely replicated the aggregated elicited wet deposition distributions. Project teams from the NRC and CEC cooperated successfully to develop and implement a unified process for the elaboration of uncertainty distributions on consequence code input parameters. Formal expert judgment elicitation proved valuable for synthesizing the best available information. Distributions on measurable atmospheric dispersion and deposition parameters were successfully elicited from experts involved in the many phenomenological areas of consequence analysis. This volume is the second of a three-volume document describing the project and contains two appendices describing the rationales for the dispersion and deposition data along with short biographies of the 16 experts who participated in the project.« less

Think twice: Impulsivity and decision making in obsessive-compulsive disorder.

PubMed

Grassi, Giacomo; Pallanti, Stefano; Righi, Lorenzo; Figee, Martijn; Mantione, Mariska; Denys, Damiaan; Piccagliani, Daniele; Rossi, Alessandro; Stratta, Paolo

2015-12-01

Recent studies have challenged the anxiety-avoidance model of obsessive-compulsive disorder (OCD), linking OCD to impulsivity, risky-decision-making and reward-system dysfunction, which can also be found in addiction and might support the conceptualization of OCD as a behavioral addiction. Here, we conducted an exploratory investigation of the behavioral addiction model of OCD by assessing whether OCD patients are more impulsive, have impaired decision-making, and biased probabilistic reasoning, three core dimensions of addiction, in a sample of OCD patients and healthy controls. We assessed these dimensions on 38 OCD patients and 39 healthy controls with the Barratt Impulsiveness Scale (BIS-11), the Iowa Gambling Task (IGT) and the Beads Task. OCD patients had significantly higher BIS-11 scores than controls, in particular on the cognitive subscales. They performed significantly worse than controls on the IGT preferring immediate reward despite negative future consequences, and did not learn from losses. Finally, OCD patients demonstrated biased probabilistic reasoning as reflected by significantly fewer draws to decision than controls on the Beads Task. OCD patients are more impulsive than controls and demonstrate risky decision-making and biased probabilistic reasoning. These results might suggest that other conceptualizations of OCD, such as the behavioral addiction model, may be more suitable than the anxiety-avoidance one. However, further studies directly comparing OCD and behavioral addiction patients are needed in order to scrutinize this model.

Probabilistic retinal vessel segmentation

NASA Astrophysics Data System (ADS)

Wu, Chang-Hua; Agam, Gady

2007-03-01

Optic fundus assessment is widely used for diagnosing vascular and non-vascular pathology. Inspection of the retinal vasculature may reveal hypertension, diabetes, arteriosclerosis, cardiovascular disease and stroke. Due to various imaging conditions retinal images may be degraded. Consequently, the enhancement of such images and vessels in them is an important task with direct clinical applications. We propose a novel technique for vessel enhancement in retinal images that is capable of enhancing vessel junctions in addition to linear vessel segments. This is an extension of vessel filters we have previously developed for vessel enhancement in thoracic CT scans. The proposed approach is based on probabilistic models which can discern vessels and junctions. Evaluation shows the proposed filter is better than several known techniques and is comparable to the state of the art when evaluated on a standard dataset. A ridge-based vessel tracking process is applied on the enhanced image to demonstrate the effectiveness of the enhancement filter.

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

Probalistic Assessment of Radiation Risk for Solar Particle Events

NASA Technical Reports Server (NTRS)

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

2008-01-01

For long duration missions outside of the protection of the Earth's magnetic field, 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 or Earth-to-Mars transit. The large majority (90%) of SPEs have small or no health consequences because the doses are low and the particles do not penetrate to organ depths. However, there is an operational challenge to respond to events of unknown size and duration. We have developed a probabilistic approach to SPE risk assessment in support of mission design and operational planning. Using the historical database of proton measurements during the past 5 solar cycles, the functional form of hazard function of SPE occurrence per cycle was found for nonhomogeneous Poisson model. A typical hazard function was defined as a function of time within a non-specific future solar cycle of 4000 days duration. Distributions of particle fluences for a specified mission period were simulated ranging from its 5th to 95th percentile. Organ doses from large SPEs were assessed using NASA's Baryon transport model, BRYNTRN. The SPE risk was analyzed with the organ dose distribution for the given particle fluences during a mission period. In addition to the total particle fluences of SPEs, the detailed energy spectra of protons, especially at high energy levels, were recognized as extremely important for assessing the cancer risk associated with energetic particles for large events. The probability of exceeding the NASA 30-day limit of blood forming organ (BFO) dose inside a typical spacecraft was calculated for various SPE sizes. This probabilistic approach to SPE protection will be combined with a probabilistic approach to the radiobiological factors that contribute to the uncertainties in projecting cancer risks in future work.

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.

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.

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.

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

An Alternative Perspective on von Winterfeldt et al.'s (1997) Test of Consequence Monotonicity

ERIC Educational Resources Information Center

Ho, Moon-Ho R.; Regenwetter, Michel; Niederee, Reinhard; Heyer, Dieter

2005-01-01

D. von Winterfeldt, N.-K. Chung, R. D. Luce, and Y. Cho (see record 1997-03378-008) provided several tests for consequence monotonicity of choice or judgment, using certainty equivalents of gambles. The authors reaxiomatized consequence monotonicity in a probabilistic framework and reanalyzed von Winterfeldt et al.'s main experiment via a…

Think twice: Impulsivity and decision making in obsessive–compulsive disorder

PubMed Central

Grassi, Giacomo; Pallanti, Stefano; Righi, Lorenzo; Figee, Martijn; Mantione, Mariska; Denys, Damiaan; Piccagliani, Daniele; Rossi, Alessandro; Stratta, Paolo

2015-01-01

Background and Aims Recent studies have challenged the anxiety-avoidance model of obsessive–compulsive disorder (OCD), linking OCD to impulsivity, risky-decision-making and reward-system dysfunction, which can also be found in addiction and might support the conceptualization of OCD as a behavioral addiction. Here, we conducted an exploratory investigation of the behavioral addiction model of OCD by assessing whether OCD patients are more impulsive, have impaired decision-making, and biased probabilistic reasoning, three core dimensions of addiction, in a sample of OCD patients and healthy controls. Methods We assessed these dimensions on 38 OCD patients and 39 healthy controls with the Barratt Impulsiveness Scale (BIS-11), the Iowa Gambling Task (IGT) and the Beads Task. Results OCD patients had significantly higher BIS-11 scores than controls, in particular on the cognitive subscales. They performed significantly worse than controls on the IGT preferring immediate reward despite negative future consequences, and did not learn from losses. Finally, OCD patients demonstrated biased probabilistic reasoning as reflected by significantly fewer draws to decision than controls on the Beads Task. Conclusions OCD patients are more impulsive than controls and demonstrate risky decision-making and biased probabilistic reasoning. These results might suggest that other conceptualizations of OCD, such as the behavioral addiction model, may be more suitable than the anxiety-avoidance one. However, further studies directly comparing OCD and behavioral addiction patients are needed in order to scrutinize this model. PMID:26690621

Probabilistic risk assessment of the Space Shuttle. Phase 3: A study of the potential of losing the vehicle during nominal operation. Volume 5: Auxiliary shuttle risk analyses

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

Volume 5 is Appendix C, Auxiliary Shuttle Risk Analyses, and contains the following reports: Probabilistic Risk Assessment of Space Shuttle Phase 1 - Space Shuttle Catastrophic Failure Frequency Final Report; Risk Analysis Applied to the Space Shuttle Main Engine - Demonstration Project for the Main Combustion Chamber Risk Assessment; An Investigation of the Risk Implications of Space Shuttle Solid Rocket Booster Chamber Pressure Excursions; Safety of the Thermal Protection System of the Space Shuttle Orbiter - Quantitative Analysis and Organizational Factors; Space Shuttle Main Propulsion Pressurization System Probabilistic Risk Assessment, Final Report; and Space Shuttle Probabilistic Risk Assessment Proof-of-Concept Study - Auxiliary Power Unit and Hydraulic Power Unit Analysis Report.

A Bayesian approach to assessing the uncertainty in estimating bioconcentration factors in earthworms--the example of quinoxyfen.

PubMed

Fragoulis, George; Merli, Annalisa; Reeves, Graham; Meregalli, Giovanna; Stenberg, Kristofer; Tanaka, Taku; Capri, Ettore

2011-06-01

Quinoxyfen is a fungicide of the phenoxyquinoline class used to control powdery mildew, Uncinula necator (Schw.) Burr. Owing to its high persistence and strong sorption in soil, it could represent a risk for soil organisms if they are exposed at ecologically relevant concentrations. The objective of this paper is to predict the bioconcentration factors (BCFs) of quinoxyfen in earthworms, selected as a representative soil organism, and to assess the uncertainty in the estimation of this parameter. Three fields in each of four vineyards in southern and northern Italy were sampled over two successive years. The measured BCFs varied over time, possibly owing to seasonal changes and the consequent changes in behaviour and ecology of earthworms. Quinoxyfen did not accumulate in soil, as the mean soil concentrations at the end of the 2 year monitoring period ranged from 9.16 to 16.0 µg kg⁻¹ dw for the Verona province and from 23.9 to 37.5 µg kg⁻¹ dw for the Taranto province, with up to eight applications per season. To assess the uncertainty of the BCF in earthworms, a probabilistic approach was used, firstly by building with weighted bootstrapping techniques a generic probabilistic density function (PDF) accounting for variability and incompleteness of knowledge. The generic PDF was then used to derive prior distribution functions, which, by application of Bayes' theorem, were updated with the new measurements and a posterior distribution was finally created. The study is a good example of probabilistic risk assessment. The means of mean and SD posterior estimates of log BCFworm (2.06, 0.91) are the 'best estimate values'. Further risk assessment of quinoxyfen and other phenoxyquinoline fungicides and realistic representative scenarios for modelling exercises required for future authorization and post-authorization requirements can now use this value as input. Copyright © 2011 Society of Chemical Industry.

A Unified Probabilistic Framework for Dose–Response Assessment of Human Health Effects

PubMed Central

Slob, Wout

2015-01-01

Background When chemical health hazards have been identified, probabilistic dose–response assessment (“hazard characterization”) quantifies uncertainty and/or variability in toxicity as a function of human exposure. Existing probabilistic approaches differ for different types of endpoints or modes-of-action, lacking a unifying framework. Objectives We developed a unified framework for probabilistic dose–response assessment. Methods We established a framework based on four principles: a) individual and population dose responses are distinct; b) dose–response relationships for all (including quantal) endpoints can be recast as relating to an underlying continuous measure of response at the individual level; c) for effects relevant to humans, “effect metrics” can be specified to define “toxicologically equivalent” sizes for this underlying individual response; and d) dose–response assessment requires making adjustments and accounting for uncertainty and variability. We then derived a step-by-step probabilistic approach for dose–response assessment of animal toxicology data similar to how nonprobabilistic reference doses are derived, illustrating the approach with example non-cancer and cancer datasets. Results Probabilistically derived exposure limits are based on estimating a “target human dose” (HDMI), which requires risk management–informed choices for the magnitude (M) of individual effect being protected against, the remaining incidence (I) of individuals with effects ≥ M in the population, and the percent confidence. In the example datasets, probabilistically derived 90% confidence intervals for HDMI values span a 40- to 60-fold range, where I = 1% of the population experiences ≥ M = 1%–10% effect sizes. Conclusions Although some implementation challenges remain, this unified probabilistic framework can provide substantially more complete and transparent characterization of chemical hazards and support better-informed risk management decisions. Citation Chiu WA, Slob W. 2015. A unified probabilistic framework for dose–response assessment of human health effects. Environ Health Perspect 123:1241–1254; http://dx.doi.org/10.1289/ehp.1409385 PMID:26006063

Template-based protein structure modeling using the RaptorX web server.

PubMed

Källberg, Morten; Wang, Haipeng; Wang, Sheng; Peng, Jian; Wang, Zhiyong; Lu, Hui; Xu, Jinbo

2012-07-19

A key challenge of modern biology is to uncover the functional role of the protein entities that compose cellular proteomes. To this end, the availability of reliable three-dimensional atomic models of proteins is often crucial. This protocol presents a community-wide web-based method using RaptorX (http://raptorx.uchicago.edu/) for protein secondary structure prediction, template-based tertiary structure modeling, alignment quality assessment and sophisticated probabilistic alignment sampling. RaptorX distinguishes itself from other servers by the quality of the alignment between a target sequence and one or multiple distantly related template proteins (especially those with sparse sequence profiles) and by a novel nonlinear scoring function and a probabilistic-consistency algorithm. Consequently, RaptorX delivers high-quality structural models for many targets with only remote templates. At present, it takes RaptorX ~35 min to finish processing a sequence of 200 amino acids. Since its official release in August 2011, RaptorX has processed ~6,000 sequences submitted by ~1,600 users from around the world.

Template-based protein structure modeling using the RaptorX web server

PubMed Central

Källberg, Morten; Wang, Haipeng; Wang, Sheng; Peng, Jian; Wang, Zhiyong; Lu, Hui; Xu, Jinbo

2016-01-01

A key challenge of modern biology is to uncover the functional role of the protein entities that compose cellular proteomes. To this end, the availability of reliable three-dimensional atomic models of proteins is often crucial. This protocol presents a community-wide web-based method using RaptorX (http://raptorx.uchicago.edu/) for protein secondary structure prediction, template-based tertiary structure modeling, alignment quality assessment and sophisticated probabilistic alignment sampling. RaptorX distinguishes itself from other servers by the quality of the alignment between a target sequence and one or multiple distantly related template proteins (especially those with sparse sequence profiles) and by a novel nonlinear scoring function and a probabilistic-consistency algorithm. Consequently, RaptorX delivers high-quality structural models for many targets with only remote templates. At present, it takes RaptorX ~35 min to finish processing a sequence of 200 amino acids. Since its official release in August 2011, RaptorX has processed ~6,000 sequences submitted by ~1,600 users from around the world. PMID:22814390

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.

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.

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

Long-period amplification in deep alluvial basins and consequences for site-specific probabilistic seismic-hazard: the case of Castelleone in the Po Plain (Northern Italy)

NASA Astrophysics Data System (ADS)

Barani, S.; Mascandola, C.; Massa, M.; Spallarossa, D.

2017-12-01

The recent Emilia seismic sequence (Northern Italy) occurred at the end of the first half of 2012 with main shock of Mw6.1 highlighted the importance of studying site effects in the Po Plain, the larger and deeper sedimentary basin in Italy. As has long been known, long-period amplification related to deep sedimentary basins can significantly affect the characteristics of the ground-motion induced by strong earthquakes. It follows that the effects of deep sedimentary deposits on ground shaking require special attention during the definition of the design seismic action. The work presented here analyzes the impact of deep-soil discontinuities on ground-motion amplification, with particular focus on long-period probabilistic seismic-hazard assessment. The study focuses on the site of Castelleone, where a seismic station of the Italian National Seismic Network has been recording since 2009. Our study includes both experimental and numerical site response analyses. Specifically, extensive active and passive geophysical measurements were carried out in order to define a detailed shear-wave velocity (VS) model to be used in the numerical analyses. These latter are needed to assess the site-specific ground-motion hazard. Besides classical seismic refraction profiles and multichannel analysis of surface waves, we analyzed ambient vibration measurements in both single and array configurations. The VS profile was determined via joint inversion of the experimental phase-velocity dispersion curve with the ellipticity curve derived from horizontal-to-vertical spectral ratios. The profile shows two main discontinuities at depths of around 160 and 1350 m, respectively. The probabilistic site-specific hazard was assessed in terms of both spectral acceleration and displacement. A partially non-ergodic approach was adopted. We have found that the spectral acceleration hazard is barely sensitive to long-period (up to 10 s) amplification related to the deeper discontinuity whereas the displacement hazard is strongly affected. Our results show that neglecting the effects of the deeper discontinuity implies an underestimation of the hazard of up to about 49% for a mean return period (MRP) of 475 years and 57% for an MRP of 2475 years, with possible consequences on the design of very tall buildings and large bridges.

An Approach to Risk-Based Design Incorporating Damage Tolerance Analyses

NASA Technical Reports Server (NTRS)

Knight, Norman F., Jr.; Glaessgen, Edward H.; Sleight, David W.

2002-01-01

Incorporating risk-based design as an integral part of spacecraft development is becoming more and more common. Assessment of uncertainties associated with design parameters and environmental aspects such as loading provides increased knowledge of the design and its performance. Results of such studies can contribute to mitigating risk through a system-level assessment. Understanding the risk of an event occurring, the probability of its occurrence, and the consequences of its occurrence can lead to robust, reliable designs. This paper describes an approach to risk-based structural design incorporating damage-tolerance analysis. The application of this approach to a candidate Earth-entry vehicle is described. The emphasis of the paper is on describing an approach for establishing damage-tolerant structural response inputs to a system-level probabilistic risk assessment.

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

A Unified Probabilistic Framework for Dose-Response Assessment of Human Health Effects.

PubMed

Chiu, Weihsueh A; Slob, Wout

2015-12-01

When chemical health hazards have been identified, probabilistic dose-response assessment ("hazard characterization") quantifies uncertainty and/or variability in toxicity as a function of human exposure. Existing probabilistic approaches differ for different types of endpoints or modes-of-action, lacking a unifying framework. We developed a unified framework for probabilistic dose-response assessment. We established a framework based on four principles: a) individual and population dose responses are distinct; b) dose-response relationships for all (including quantal) endpoints can be recast as relating to an underlying continuous measure of response at the individual level; c) for effects relevant to humans, "effect metrics" can be specified to define "toxicologically equivalent" sizes for this underlying individual response; and d) dose-response assessment requires making adjustments and accounting for uncertainty and variability. We then derived a step-by-step probabilistic approach for dose-response assessment of animal toxicology data similar to how nonprobabilistic reference doses are derived, illustrating the approach with example non-cancer and cancer datasets. Probabilistically derived exposure limits are based on estimating a "target human dose" (HDMI), which requires risk management-informed choices for the magnitude (M) of individual effect being protected against, the remaining incidence (I) of individuals with effects ≥ M in the population, and the percent confidence. In the example datasets, probabilistically derived 90% confidence intervals for HDMI values span a 40- to 60-fold range, where I = 1% of the population experiences ≥ M = 1%-10% effect sizes. Although some implementation challenges remain, this unified probabilistic framework can provide substantially more complete and transparent characterization of chemical hazards and support better-informed risk management decisions.

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.

Multi-parametric variational data assimilation for hydrological forecasting

NASA Astrophysics Data System (ADS)

Alvarado-Montero, R.; Schwanenberg, D.; Krahe, P.; Helmke, P.; Klein, B.

2017-12-01

Ensemble forecasting is increasingly applied in flow forecasting systems to provide users with a better understanding of forecast uncertainty and consequently to take better-informed decisions. A common practice in probabilistic streamflow forecasting is to force deterministic hydrological model with an ensemble of numerical weather predictions. This approach aims at the representation of meteorological uncertainty but neglects uncertainty of the hydrological model as well as its initial conditions. Complementary approaches use probabilistic data assimilation techniques to receive a variety of initial states or represent model uncertainty by model pools instead of single deterministic models. This paper introduces a novel approach that extends a variational data assimilation based on Moving Horizon Estimation to enable the assimilation of observations into multi-parametric model pools. It results in a probabilistic estimate of initial model states that takes into account the parametric model uncertainty in the data assimilation. The assimilation technique is applied to the uppermost area of River Main in Germany. We use different parametric pools, each of them with five parameter sets, to assimilate streamflow data, as well as remotely sensed data from the H-SAF project. We assess the impact of the assimilation in the lead time performance of perfect forecasts (i.e. observed data as forcing variables) as well as deterministic and probabilistic forecasts from ECMWF. The multi-parametric assimilation shows an improvement of up to 23% for CRPS performance and approximately 20% in Brier Skill Scores with respect to the deterministic approach. It also improves the skill of the forecast in terms of rank histogram and produces a narrower ensemble spread.

Probabilistic regional climate projection in Japan using a regression model with CMIP5 multi-model ensemble experiments

NASA Astrophysics Data System (ADS)

Ishizaki, N. N.; Dairaku, K.; Ueno, G.

2016-12-01

We have developed a statistical downscaling method for estimating probabilistic climate projection using CMIP5 multi general circulation models (GCMs). A regression model was established so that the combination of weights of GCMs reflects the characteristics of the variation of observations at each grid point. Cross validations were conducted to select GCMs and to evaluate the regression model to avoid multicollinearity. By using spatially high resolution observation system, we conducted statistically downscaled probabilistic climate projections with 20-km horizontal grid spacing. Root mean squared errors for monthly mean air surface temperature and precipitation estimated by the regression method were the smallest compared with the results derived from a simple ensemble mean of GCMs and a cumulative distribution function based bias correction method. Projected changes in the mean temperature and precipitation were basically similar to those of the simple ensemble mean of GCMs. Mean precipitation was generally projected to increase associated with increased temperature and consequent increased moisture content in the air. Weakening of the winter monsoon may affect precipitation decrease in some areas. Temperature increase in excess of 4 K was expected in most areas of Japan in the end of 21st century under RCP8.5 scenario. The estimated probability of monthly precipitation exceeding 300 mm would increase around the Pacific side during the summer and the Japan Sea side during the winter season. This probabilistic climate projection based on the statistical method can be expected to bring useful information to the impact studies and risk assessments.

Great Balls of Fire: A probabilistic approach to quantify the hazard related to ballistics - A case study at La Fossa volcano, Vulcano Island, Italy

NASA Astrophysics Data System (ADS)

Biass, Sébastien; Falcone, Jean-Luc; Bonadonna, Costanza; Di Traglia, Federico; Pistolesi, Marco; Rosi, Mauro; Lestuzzi, Pierino

2016-10-01

We present a probabilistic approach to quantify the hazard posed by volcanic ballistic projectiles (VBP) and their potential impact on the built environment. A model named Great Balls of Fire (GBF) is introduced to describe ballistic trajectories of VBPs accounting for a variable drag coefficient and topography. It relies on input parameters easily identifiable in the field and is designed to model large numbers of VBPs stochastically. Associated functions come with the GBF code to post-process model outputs into a comprehensive probabilistic hazard assessment for VBP impacts. Outcomes include probability maps to exceed given thresholds of kinetic energies at impact, hazard curves and probabilistic isoenergy maps. Probabilities are calculated either on equally-sized pixels or zones of interest. The approach is calibrated, validated and applied to La Fossa volcano, Vulcano Island (Italy). We constructed a generic eruption scenario based on stratigraphic studies and numerical inversions of the 1888-1890 long-lasting Vulcanian cycle of La Fossa. Results suggest a ~ 10- 2% probability of occurrence of VBP impacts with kinetic energies ≤ 104 J at the touristic locality of Porto. In parallel, the vulnerability to roof perforation was estimated by combining field observations and published literature, allowing for a first estimate of the potential impact of VBPs during future Vulcanian eruptions. Results indicate a high physical vulnerability to the VBP hazard, and, consequently, half of the building stock having a ≥ 2.5 × 10- 3% probability of roof perforation.

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.

Significance testing as perverse probabilistic reasoning

PubMed Central

2011-01-01

Truth claims in the medical literature rely heavily on statistical significance testing. Unfortunately, most physicians misunderstand the underlying probabilistic logic of significance tests and consequently often misinterpret their results. This near-universal misunderstanding is highlighted by means of a simple quiz which we administered to 246 physicians at two major academic hospitals, on which the proportion of incorrect responses exceeded 90%. A solid understanding of the fundamental concepts of probability theory is becoming essential to the rational interpretation of medical information. This essay provides a technically sound review of these concepts that is accessible to a medical audience. We also briefly review the debate in the cognitive sciences regarding physicians' aptitude for probabilistic inference. PMID:21356064

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 ASSESSMENT OF BENTHIC CONDITION OF CALIFORNIA ESTUARIES: RESULTS FROM THE NATIONAL COASTAL ASSESSMENT 1999

EPA Science Inventory

As part of the National Coastal Assessment, the Environmental Monitoring and Assessment Program of EPA is conducting a three year evaluation of benthic habitat condition of California estuaries. In 1999, probabilistic sampling for a variety of biotic and abiotic condition indica...

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.

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.

The effect of the sea on hazard assessment for tephra fallout at Campi Flegrei: a preliminary approach through the use of pyPHaz, an open tool to analyze and visualize probabilistic hazards

NASA Astrophysics Data System (ADS)

Tonini, Roberto; Sandri, Laura; Costa, Antonio; Selva, Jacopo

2014-05-01

Campi Flegrei (CF) is a large volcanic field located west of the Gulf of Naples, characterized by a wide and almost circular caldera which is partially submerged beneath the Gulf of Pozzuoli. It is known that the magma-water interaction is a key element to determine the character of submarine eruptions and their impact on the surrounding areas, but this phenomenon is still not well understood and it is rarely considered in hazard assessment. The aim of the present work is to present a preliminary study of the effect of the sea on the tephra fall hazard from CF on the municipality of Naples, by introducing a variability in the probability of tephra production according to the eruptive scale (defined on the basis of the erupted volume) and the depth of the opening submerged vents. Four different Probabilistic Volcanic Hazard Assessment (PVHA) models have been defined through the application of the model BET_VH at CF, by accounting for different modeling procedures and assumptions for the submerged part of the caldera. In particular, we take into account: 1) the effect of the sea as null, i.e. as if the water were not present; 2) the effect of the sea as a cap that totally blocks the explosivity of eruptions and consequently the tephra production; 3) an ensemble model between the two models described at the previous points 1) and 2); 4) a variable probability of tephra production depending on the depth of the submerged vent. The PVHA models are then input to pyPHaz, a tool developed and designed at INGV to visualize, analyze and merge into ensemble models PVHA's results and, potentially, any other kind of probabilistic hazard assessment, both natural and anthropic, in order to evaluate the importance of considering a variability among subaerial and submerged vents on tephra fallout hazard from CF in Naples. The analysis is preliminary and does not pretend to be exhaustive, but on one hand it represents a starting point for future works; on the other hand, it is a good case study to show the potentiality of the pyPHaz tool that, thanks to a dedicated Graphical User Interface (GUI), allows to interactively manage and visualize results of probabilistic hazards (hazard curves together with probability and hazard maps for different levels of uncertainties), and to compare or merge different hazard models producing ensemble models. This work has been developed in the framework of two Italian projects, "ByMuR (Bayesian Multi-Risk Assessment: a case study for natural risks in the city of Naples)" funded by the Italian Ministry of Education, Universities and Research (MIUR), and "V1: Probabilistic Volcanic Hazard Assessments" funded by the Italian Department of Civil Protection (DPC).

A PROBABILISTIC ASSESSMENT OF BENTHIC CONDITION OF WEST COAST ESTUARIES: RESULTS FROM THE NATIONAL COASTAL ASSESSMENT 1999-2000

EPA Science Inventory

As part of the National Coastal Assessment, the Environmental Monitoring and Assessment Program of EPA is conducting a six year evaluation of benthic habitat condition for coastal waters of the western U.S. In 1999, probabilistic sampling for a range of biotic and abiotic conditi...

Integrated probabilistic risk assessment for nanoparticles: the case of nanosilica in food.

PubMed

Jacobs, Rianne; van der Voet, Hilko; Ter Braak, Cajo J F

Insight into risks of nanotechnology and the use of nanoparticles is an essential condition for the social acceptance and safe use of nanotechnology. One of the problems with which the risk assessment of nanoparticles is faced is the lack of data, resulting in uncertainty in the risk assessment. We attempt to quantify some of this uncertainty by expanding a previous deterministic study on nanosilica (5-200 nm) in food into a fully integrated probabilistic risk assessment. We use the integrated probabilistic risk assessment method in which statistical distributions and bootstrap methods are used to quantify uncertainty and variability in the risk assessment. Due to the large amount of uncertainty present, this probabilistic method, which separates variability from uncertainty, contributed to a better understandable risk assessment. We found that quantifying the uncertainties did not increase the perceived risk relative to the outcome of the deterministic study. We pinpointed particular aspects of the hazard characterization that contributed most to the total uncertainty in the risk assessment, suggesting that further research would benefit most from obtaining more reliable data on those aspects.

Stimulus discriminability may bias value-based probabilistic learning.

PubMed

Schutte, Iris; Slagter, Heleen A; Collins, Anne G E; Frank, Michael J; Kenemans, J Leon

2017-01-01

Reinforcement learning tasks are often used to assess participants' tendency to learn more from the positive or more from the negative consequences of one's action. However, this assessment often requires comparison in learning performance across different task conditions, which may differ in the relative salience or discriminability of the stimuli associated with more and less rewarding outcomes, respectively. To address this issue, in a first set of studies, participants were subjected to two versions of a common probabilistic learning task. The two versions differed with respect to the stimulus (Hiragana) characters associated with reward probability. The assignment of character to reward probability was fixed within version but reversed between versions. We found that performance was highly influenced by task version, which could be explained by the relative perceptual discriminability of characters assigned to high or low reward probabilities, as assessed by a separate discrimination experiment. Participants were more reliable in selecting rewarding characters that were more discriminable, leading to differences in learning curves and their sensitivity to reward probability. This difference in experienced reinforcement history was accompanied by performance biases in a test phase assessing ability to learn from positive vs. negative outcomes. In a subsequent large-scale web-based experiment, this impact of task version on learning and test measures was replicated and extended. Collectively, these findings imply a key role for perceptual factors in guiding reward learning and underscore the need to control stimulus discriminability when making inferences about individual differences in reinforcement learning.

Building an ecosystem model using mismatched and fragmented data: A probabilistic network of early marine survival for coho salmon Oncorhynchus kisutch in the Strait of Georgia

NASA Astrophysics Data System (ADS)

Andres Araujo, H.; Holt, Carrie; Curtis, Janelle M. R.; Perry, R. I.; Irvine, James R.; Michielsens, Catherine G. J.

2013-08-01

We evaluated the effects of biophysical conditions and hatchery production on the early marine survival of coho salmon Oncorhynchus kisutch in the Strait of Georgia, British Columbia, Canada. Due to a paucity of balanced multivariate ecosystem data, we developed a probabilistic network that integrated physical and ecological data and information from literature, expert opinion, oceanographic models, and in situ observations. This approach allowed us to evaluate alternate hypotheses about drivers of early marine survival while accounting for uncertainties in relationships among variables. Probabilistic networks allow users to explore multiple environmental settings and evaluate the consequences of management decisions under current and projected future states. We found that the zooplankton biomass anomaly, calanoid copepod biomass, and herring biomass were the best indicators of early marine survival. It also appears that concentrating hatchery supplementation during periods of negative PDO and ENSO (Pacific Decadal and El Niño Southern Oscillation respectively), indicative of generally favorable ocean conditions for salmon, tends to increase survival of hatchery coho salmon while minimizing negative impacts on the survival of wild juveniles. Scientists and managers can benefit from the approach presented here by exploring multiple scenarios, providing a basis for open and repeatable ecosystem-based risk assessments when data are limited.

Single, Complete, Probability Spaces Consistent With EPR-Bohm-Bell Experimental Data

NASA Astrophysics Data System (ADS)

Avis, David; Fischer, Paul; Hilbert, Astrid; Khrennikov, Andrei

2009-03-01

We show that paradoxical consequences of violations of Bell's inequality are induced by the use of an unsuitable probabilistic description for the EPR-Bohm-Bell experiment. The conventional description (due to Bell) is based on a combination of statistical data collected for different settings of polarization beam splitters (PBSs). In fact, such data consists of some conditional probabilities which only partially define a probability space. Ignoring this conditioning leads to apparent contradictions in the classical probabilistic model (due to Kolmogorov). We show how to make a completely consistent probabilistic model by taking into account the probabilities of selecting the settings of the PBSs. Our model matches both the experimental data and is consistent with classical probability theory.

Methodology for prediction and estimation of consequences of possible atmospheric releases of hazardous matter: "Kursk" submarine study

NASA Astrophysics Data System (ADS)

Baklanov, A.; Mahura, A.; Sørensen, J. H.

2003-06-01

There are objects with some periods of higher than normal levels of risk of accidental atmospheric releases (nuclear, chemical, biological, etc.). Such accidents or events may occur due to natural hazards, human errors, terror acts, and during transportation of waste or various operations at high risk. A methodology for risk assessment is suggested and it includes two approaches: 1) probabilistic analysis of possible atmospheric transport patterns using long-term trajectory and dispersion modelling, and 2) forecast and evaluation of possible contamination and consequences for the environment and population using operational dispersion modelling. The first approach could be applied during the preparation stage, and the second - during the operation stage. The suggested methodology is applied on an example of the most important phases (lifting, transportation, and decommissioning) of the ``Kursk" nuclear submarine operation. It is found that the temporal variability of several probabilistic indicators (fast transport probability fields, maximum reaching distance, maximum possible impact zone, and average integral concentration of 137Cs) showed that the fall of 2001 was the most appropriate time for the beginning of the operation. These indicators allowed to identify the hypothetically impacted geographical regions and territories. In cases of atmospheric transport toward the most populated areas, the forecasts of possible consequences during phases of the high and medium potential risk levels based on a unit hypothetical release (e.g. 1 Bq) are performed. The analysis showed that the possible deposition fractions of 10-11 (Bq/m2) over the Kola Peninsula, and 10-12 - 10-13 (Bq/m2) for the remote areas of the Scandinavia and Northwest Russia could be observed. The suggested methodology may be used successfully for any potentially dangerous object involving risk of atmospheric release of hazardous materials of nuclear, chemical or biological nature.

Methodology for prediction and estimation of consequences of possible atmospheric releases of hazardous matter: "Kursk"? submarine study

NASA Astrophysics Data System (ADS)

Baklanov, A.; Mahura, A.; Sørensen, J. H.

2003-03-01

There are objects with some periods of higher than normal levels of risk of accidental atmospheric releases (nuclear, chemical, biological, etc.). Such accidents or events may occur due to natural hazards, human errors, terror acts, and during transportation of waste or various operations at high risk. A methodology for risk assessment is suggested and it includes two approaches: 1) probabilistic analysis of possible atmospheric transport patterns using long-term trajectory and dispersion modelling, and 2) forecast and evaluation of possible contamination and consequences for the environment and population using operational dispersion modelling. The first approach could be applied during the preparation stage, and the second - during the operation stage. The suggested methodology is applied on an example of the most important phases (lifting, transportation, and decommissioning) of the "Kursk" nuclear submarine operation. It is found that the temporal variability of several probabilistic indicators (fast transport probability fields, maximum reaching distance, maximum possible impact zone, and average integral concentration of 137Cs) showed that the fall of 2001 was the most appropriate time for the beginning of the operation. These indicators allowed to identify the hypothetically impacted geographical regions and territories. In cases of atmospheric transport toward the most populated areas, the forecasts of possible consequences during phases of the high and medium potential risk levels based on a unit hypothetical release are performed. The analysis showed that the possible deposition fractions of 1011 over the Kola Peninsula, and 10-12 - 10-13 for the remote areas of the Scandinavia and Northwest Russia could be observed. The suggested methodology may be used successfully for any potentially dangerous object involving risk of atmospheric release of hazardous materials of nuclear, chemical or biological nature.

Lessons from the conviction of the L'Aquila seven: The standard probabilistic earthquake hazard and risk assessment is ineffective

NASA Astrophysics Data System (ADS)

Wyss, Max

2013-04-01

An earthquake of M6.3 killed 309 people in L'Aquila, Italy, on 6 April 2011. Subsequently, a judge in L'Aquila convicted seven who had participated in an emergency meeting on March 30, assessing the probability of a major event to follow the ongoing earthquake swarm. The sentence was six years in prison, a combine fine of 2 million Euros, loss of job, loss of retirement rent, and lawyer's costs. The judge followed the prosecution's accusation that the review by the Commission of Great Risks had conveyed a false sense of security to the population, which consequently did not take their usual precautionary measures before the deadly earthquake. He did not consider the facts that (1) one of the convicted was not a member of the commission and had merrily obeyed orders to bring the latest seismological facts to the discussion, (2) another was an engineer who was not required to have any expertise regarding the probability of earthquakes, (3) and two others were seismologists not invited to speak to the public at a TV interview and a press conference. This exaggerated judgment was the consequence of an uproar in the population, who felt misinformed and even mislead. Faced with a population worried by an earthquake swarm, the head of the Italian Civil Defense is on record ordering that the population be calmed, and the vice head executed this order in a TV interview one hour before the meeting of the Commission by stating "the scientific community continues to tell me that the situation is favorable and that there is a discharge of energy." The first lesson to be learned is that communications to the public about earthquake hazard and risk must not be left in the hands of someone who has gross misunderstandings about seismology. They must be carefully prepared by experts. The more significant lesson is that the approach to calm the population and the standard probabilistic hazard and risk assessment, as practiced by GSHAP, are misleading. The later has been criticized as being incorrect for scientific reasons and here I argue that it is also ineffective for psychological reasons. Instead of calming the people or by underestimating the hazard in strongly active areas by the GSHAP approach, they should be told quantitatively the consequences of the reasonably worst case and be motivated to prepare for it, whether or not it may hit the present or the next generation. In a worst case scenario for L'Aquila, the number of expected fatalities and injured should have been calculated for an event in the range of M6.5 to M7, as I did for a civil defense exercise in Umbria, Italy. With the prospect that approximately 500 people may die in an earthquake in the immediate or distant future, some residents might have built themselves an earthquake closet (similar to a simple tornado shelter) in a corner of their apartment, into which they might have dashed to safety at the onset of the P-wave before the destructive S-wave arrived. I conclude that in earthquake prone areas quantitative loss estimates due to a reasonable worst case earthquake should replace probabilistic hazard and risk estimates. This is a service, which experts owe the community. Insurance companies and academics may still find use for probabilistic estimates of losses, especially in areas of low seismic hazard, where the worst case scenario approach is less appropriate.

Probabilistic inversion of expert assessments to inform projections about Antarctic ice sheet responses.

PubMed

Fuller, Robert William; Wong, Tony E; Keller, Klaus

2017-01-01

The response of the Antarctic ice sheet (AIS) to changing global temperatures is a key component of sea-level projections. Current projections of the AIS contribution to sea-level changes are deeply uncertain. This deep uncertainty stems, in part, from (i) the inability of current models to fully resolve key processes and scales, (ii) the relatively sparse available data, and (iii) divergent expert assessments. One promising approach to characterizing the deep uncertainty stemming from divergent expert assessments is to combine expert assessments, observations, and simple models by coupling probabilistic inversion and Bayesian inversion. Here, we present a proof-of-concept study that uses probabilistic inversion to fuse a simple AIS model and diverse expert assessments. We demonstrate the ability of probabilistic inversion to infer joint prior probability distributions of model parameters that are consistent with expert assessments. We then confront these inferred expert priors with instrumental and paleoclimatic observational data in a Bayesian inversion. These additional constraints yield tighter hindcasts and projections. We use this approach to quantify how the deep uncertainty surrounding expert assessments affects the joint probability distributions of model parameters and future projections.

Seismic Risk Assessment for the Kyrgyz Republic

NASA Astrophysics Data System (ADS)

Pittore, Massimiliano; Sousa, Luis; Grant, Damian; Fleming, Kevin; Parolai, Stefano; Fourniadis, Yannis; Free, Matthew; Moldobekov, Bolot; Takeuchi, Ko

2017-04-01

The Kyrgyz Republic is one of the most socially and economically dynamic countries in Central Asia, and one of the most endangered by earthquake hazard in the region. In order to support the government of the Kyrgyz Republic in the development of a country-level Disaster Risk Reduction strategy, a comprehensive seismic risk study has been developed with the support of the World Bank. As part of this project, state-of-the-art hazard, exposure and vulnerability models have been developed and combined into the assessment of direct physical and economic risk on residential, educational and transportation infrastructure. The seismic hazard has been modelled with three different approaches, in order to provide a comprehensive overview of the possible consequences. A probabilistic seismic hazard assessment (PSHA) approach has been used to quantitatively evaluate the distribution of expected ground shaking intensity, as constrained by the compiled earthquake catalogue and associated seismic source model. A set of specific seismic scenarios based on events generated from known fault systems have been also considered, in order to provide insight on the expected consequences in case of strong events in proximity of densely inhabited areas. Furthermore, long-span catalogues of events have been generated stochastically and employed in the probabilistic analysis of expected losses over the territory of the Kyrgyz Republic. Damage and risk estimates have been computed by using an exposure model recently developed for the country, combined with the assignment of suitable fragility/vulnerability models. The risk estimation has been carried out with spatial aggregation at the district (rayon) level. The obtained results confirm the high level of seismic risk throughout the country, also pinpointing the location of several risk hotspots, particularly in the southern districts, in correspondence with the Ferghana valley. The outcome of this project will further support the local decision makers in implementing specific prevention and mitigation measures that are consistent with a broad risk reduction strategy.

Probabilistic Assessment of Planet Habitability and Biosignatures

NASA Astrophysics Data System (ADS)

Bixel, A.; Apai, D.

2017-11-01

We have computed probabilistic constraints on the bulk properties of Proxima Cen b informed by priors from Kepler and RV follow-up. We will extend this approach into a Bayesian framework to assess the habitability of directly imaged planets.

Probabilistic Risk Assessment to Inform Decision Making: Frequently Asked Questions

EPA Pesticide Factsheets

General concepts and principles of Probabilistic Risk Assessment (PRA), describe how PRA can improve the bases of Agency decisions, and provide illustrations of how PRA has been used in risk estimation and in describing the uncertainty in decision making.

Risks from Solar Particle Events for Long Duration Space Missions Outside Low Earth Orbit

NASA Technical Reports Server (NTRS)

Over, S.; Myers, J.; Ford, J.

2016-01-01

The Integrated Medical Model (IMM) simulates the medical occurrences and mission outcomes for various mission profiles using probabilistic risk assessment techniques. As part of the work with the Integrated Medical Model (IMM), this project focuses on radiation risks from acute events during extended human missions outside low Earth orbit (LEO). Of primary importance in acute risk assessment are solar particle events (SPEs), which are low probability, high consequence events that could adversely affect mission outcomes through acute radiation damage to astronauts. SPEs can be further classified into coronal mass ejections (CMEs) and solar flares/impulsive events (Fig. 1). CMEs are an eruption of solar material and have shock enhancements that contribute to make these types of events higher in total fluence than impulsive events.

Finite element probabilistic risk assessment of transmission line insulation flashovers caused by lightning strokes

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

Bacvarov, D.C.

1981-01-01

A new method for probabilistic risk assessment of transmission line insulation flashovers caused by lightning strokes is presented. The utilized approach of applying the finite element method for probabilistic risk assessment is demonstrated to be very powerful. The reasons for this are two. First, the finite element method is inherently suitable for analysis of three dimensional spaces where the parameters, such as three variate probability densities of the lightning currents, are non-uniformly distributed. Second, the finite element method permits non-uniform discretization of the three dimensional probability spaces thus yielding high accuracy in critical regions, such as the area of themore » low probability events, while at the same time maintaining coarse discretization in the non-critical areas to keep the number of grid points and the size of the problem to a manageable low level. The finite element probabilistic risk assessment method presented here is based on a new multidimensional search algorithm. It utilizes an efficient iterative technique for finite element interpolation of the transmission line insulation flashover criteria computed with an electro-magnetic transients program. Compared to other available methods the new finite element probabilistic risk assessment method is significantly more accurate and approximately two orders of magnitude computationally more efficient. The method is especially suited for accurate assessment of rare, very low probability events.« less

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 ASSESSMENT OF GROUNDWATER VULNERABILITY TO NONPOINT SOURCE POLLUTION IN AGRICULTURAL WATERSHEDS

EPA Science Inventory

This paper presents a probabilistic framework for the assessment of groundwater pollution potential by pesticides in two adjacent agricultural watersheds in the Mid-Altantic Coastal Plain. Indices for estimating streams vulnerability to pollutants' load from the surficial aquifer...

PROBABILISTIC MONITORING FOR TRIBAL AQUATIC RESOURCE: EPA'S NATIONAL COASTAL ASSESSMENT TRIBAL TRAINING

EPA Science Inventory

Harvey, James, David Lawes, Vincent Cooke and Tom Heitmuller. In press. Probabilistic Monitoring for Tribal Aquatic Resources: EPA's National Coastal Assessment Tribal Training (Abstract). To be presented at the Monitoring Science and Technology Symposium, 20-24 September 2004, D...

Overview of Future of Probabilistic Methods and RMSL Technology and the Probabilistic Methods Education Initiative for the US Army at the SAE G-11 Meeting

NASA Technical Reports Server (NTRS)

Singhal, Surendra N.

2003-01-01

The SAE G-11 RMSL Division and Probabilistic Methods Committee meeting sponsored by the Picatinny Arsenal during March 1-3, 2004 at Westin Morristown, will report progress on projects for probabilistic assessment of Army system and launch an initiative for probabilistic education. The meeting features several Army and industry Senior executives and Ivy League Professor to provide an industry/government/academia forum to review RMSL technology; reliability and probabilistic technology; reliability-based design methods; software reliability; and maintainability standards. With over 100 members including members with national/international standing, the mission of the G-11s Probabilistic Methods Committee is to enable/facilitate rapid deployment of probabilistic technology to enhance the competitiveness of our industries by better, faster, greener, smarter, affordable and reliable product development.

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.

Fragment Impact Toolkit (FIT)

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

Shevitz, Daniel Wolf; Key, Brian P.; Garcia, Daniel B.

2017-09-05

The Fragment Impact Toolkit (FIT) is a software package used for probabilistic consequence evaluation of fragmenting sources. The typical use case for FIT is to simulate an exploding shell and evaluate the consequence on nearby objects. FIT is written in the programming language Python and is designed as a collection of interacting software modules. Each module has a function that interacts with the other modules to produce desired results.

Scientific assessment of accuracy, skill and reliability of ocean probabilistic forecast products.

NASA Astrophysics Data System (ADS)

Wei, M.; Rowley, C. D.; Barron, C. N.; Hogan, P. J.

2016-02-01

As ocean operational centers are increasingly adopting and generating probabilistic forecast products for their customers with valuable forecast uncertainties, how to assess and measure these complicated probabilistic forecast products objectively is challenging. The first challenge is how to deal with the huge amount of the data from the ensemble forecasts. The second one is how to describe the scientific quality of probabilistic products. In fact, probabilistic forecast accuracy, skills, reliability, resolutions are different attributes of a forecast system. We briefly introduce some of the fundamental metrics such as the Reliability Diagram, Reliability, Resolution, Brier Score (BS), Brier Skill Score (BSS), Ranked Probability Score (RPS), Ranked Probability Skill Score (RPSS), Continuous Ranked Probability Score (CRPS), and Continuous Ranked Probability Skill Score (CRPSS). The values and significance of these metrics are demonstrated for the forecasts from the US Navy's regional ensemble system with different ensemble members. The advantages and differences of these metrics are studied and clarified.

Exploration Health Risks: Probabilistic Risk Assessment

NASA Technical Reports Server (NTRS)

Rhatigan, Jennifer; Charles, John; Hayes, Judith; Wren, Kiley

2006-01-01

Maintenance of human health on long-duration exploration missions is a primary challenge to mission designers. Indeed, human health risks are currently the largest risk contributors to the risks of evacuation or loss of the crew on long-duration International Space Station missions. We describe a quantitative assessment of the relative probabilities of occurrence of the individual risks to human safety and efficiency during space flight to augment qualitative assessments used in this field to date. Quantitative probabilistic risk assessments will allow program managers to focus resources on those human health risks most likely to occur with undesirable consequences. Truly quantitative assessments are common, even expected, in the engineering and actuarial spheres, but that capability is just emerging in some arenas of life sciences research, such as identifying and minimize the hazards to astronauts during future space exploration missions. Our expectation is that these results can be used to inform NASA mission design trade studies in the near future with the objective of preventing the higher among the human health risks. We identify and discuss statistical techniques to provide this risk quantification based on relevant sets of astronaut biomedical data from short and long duration space flights as well as relevant analog populations. We outline critical assumptions made in the calculations and discuss the rationale for these. Our efforts to date have focussed on quantifying the probabilities of medical risks that are qualitatively perceived as relatively high risks of radiation sickness, cardiac dysrhythmias, medically significant renal stone formation due to increased calcium mobilization, decompression sickness as a result of EVA (extravehicular activity), and bone fracture due to loss of bone mineral density. We present these quantitative probabilities in order-of-magnitude comparison format so that relative risk can be gauged. We address the effects of conservative and nonconservative assumptions on the probability results. We discuss the methods necessary to assess mission risks once exploration mission scenarios are characterized. Preliminary efforts have produced results that are commensurate with earlier qualitative estimates of risk probabilities in this and other operational contexts, indicating that our approach may be usefully applied in support of the development of human health and performance standards for long-duration space exploration missions. This approach will also enable mission-specific probabilistic risk assessments for space exploration missions.

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.

Probabilistic inversion of expert assessments to inform projections about Antarctic ice sheet responses

PubMed Central

Wong, Tony E.; Keller, Klaus

2017-01-01

The response of the Antarctic ice sheet (AIS) to changing global temperatures is a key component of sea-level projections. Current projections of the AIS contribution to sea-level changes are deeply uncertain. This deep uncertainty stems, in part, from (i) the inability of current models to fully resolve key processes and scales, (ii) the relatively sparse available data, and (iii) divergent expert assessments. One promising approach to characterizing the deep uncertainty stemming from divergent expert assessments is to combine expert assessments, observations, and simple models by coupling probabilistic inversion and Bayesian inversion. Here, we present a proof-of-concept study that uses probabilistic inversion to fuse a simple AIS model and diverse expert assessments. We demonstrate the ability of probabilistic inversion to infer joint prior probability distributions of model parameters that are consistent with expert assessments. We then confront these inferred expert priors with instrumental and paleoclimatic observational data in a Bayesian inversion. These additional constraints yield tighter hindcasts and projections. We use this approach to quantify how the deep uncertainty surrounding expert assessments affects the joint probability distributions of model parameters and future projections. PMID:29287095

Assessing Probabilistic Reasoning in Verbal-Numerical and Graphical-Pictorial Formats: An Evaluation of the Psychometric Properties of an Instrument

ERIC Educational Resources Information Center

Agus, Mirian; Penna, Maria Pietronilla; Peró-Cebollero, Maribel; Guàrdia-Olmos, Joan

2016-01-01

Research on the graphical facilitation of probabilistic reasoning has been characterised by the effort expended to identify valid assessment tools. The authors developed an assessment instrument to compare reasoning performances when problems were presented in verbal-numerical and graphical-pictorial formats. A sample of undergraduate psychology…

Extravehicular Activity Probabilistic Risk Assessment Overview for Thermal Protection System Repair on the Hubble Space Telescope Servicing Mission

NASA Technical Reports Server (NTRS)

Bigler, Mark; Canga, Michael A.; Duncan, Gary

2010-01-01

The Shuttle Program initiated an Extravehicular Activity (EVA) Probabilistic Risk Assessment (PRA) to assess the risks associated with performing a Shuttle Thermal Protection System (TPS) repair during the Space Transportation System (STS)-125 Hubble repair mission as part of risk trades between TPS repair and crew rescue.

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

Environmental probabilistic quantitative assessment methodologies

USGS Publications Warehouse

Crovelli, R.A.

1995-01-01

In this paper, four petroleum resource assessment methodologies are presented as possible pollution assessment methodologies, even though petroleum as a resource is desirable, whereas pollution is undesirable. A methodology is defined in this paper to consist of a probability model and a probabilistic method, where the method is used to solve the model. The following four basic types of probability models are considered: 1) direct assessment, 2) accumulation size, 3) volumetric yield, and 4) reservoir engineering. Three of the four petroleum resource assessment methodologies were written as microcomputer systems, viz. TRIAGG for direct assessment, APRAS for accumulation size, and FASPU for reservoir engineering. A fourth microcomputer system termed PROBDIST supports the three assessment systems. The three assessment systems have different probability models but the same type of probabilistic method. The type of advantages of the analytic method are in computational speed and flexibility, making it ideal for a microcomputer. -from Author

PRA (Probabilistic Risk Assessments) Participation versus Validation

NASA Technical Reports Server (NTRS)

DeMott, Diana; Banke, Richard

2013-01-01

Probabilistic Risk Assessments (PRAs) are performed for projects or programs where the consequences of failure are highly undesirable. PRAs primarily address the level of risk those projects or programs posed during operations. PRAs are often developed after the design has been completed. Design and operational details used to develop models include approved and accepted design information regarding equipment, components, systems and failure data. This methodology basically validates the risk parameters of the project or system design. For high risk or high dollar projects, using PRA methodologies during the design process provides new opportunities to influence the design early in the project life cycle to identify, eliminate or mitigate potential risks. Identifying risk drivers before the design has been set allows the design engineers to understand the inherent risk of their current design and consider potential risk mitigation changes. This can become an iterative process where the PRA model can be used to determine if the mitigation technique is effective in reducing risk. This can result in more efficient and cost effective design changes. PRA methodology can be used to assess the risk of design alternatives and can demonstrate how major design changes or program modifications impact the overall program or project risk. PRA has been used for the last two decades to validate risk predictions and acceptability. Providing risk information which can positively influence final system and equipment design the PRA tool can also participate in design development, providing a safe and cost effective product.

A methodology for post-mainshock probabilistic assessment of building collapse risk

USGS Publications Warehouse

Luco, N.; Gerstenberger, M.C.; Uma, S.R.; Ryu, H.; Liel, A.B.; Raghunandan, M.

2011-01-01

This paper presents a methodology for post-earthquake probabilistic risk (of damage) assessment that we propose in order to develop a computational tool for automatic or semi-automatic assessment. The methodology utilizes the same so-called risk integral which can be used for pre-earthquake probabilistic assessment. The risk integral couples (i) ground motion hazard information for the location of a structure of interest with (ii) knowledge of the fragility of the structure with respect to potential ground motion intensities. In the proposed post-mainshock methodology, the ground motion hazard component of the risk integral is adapted to account for aftershocks which are deliberately excluded from typical pre-earthquake hazard assessments and which decrease in frequency with the time elapsed since the mainshock. Correspondingly, the structural fragility component is adapted to account for any damage caused by the mainshock, as well as any uncertainty in the extent of this damage. The result of the adapted risk integral is a fully-probabilistic quantification of post-mainshock seismic risk that can inform emergency response mobilization, inspection prioritization, and re-occupancy decisions.

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

ASSESSING THE ECOLOGICAL CONDITION OF A COASTAL PLAIN WATERSHED USING A PROBABILISTIC SURVEY DESIGN

EPA Science Inventory

Using a probabilistic survey design, we assessed the ecological condition of the Florida (USA) portion of the Escambia River watershed using selected environmental and benthic macroinvertebrate data. Macroinvertebrates were sampled at 28 sites during July-August 1996, and 3414 i...

A probabilistic analysis of cumulative carbon emissions and long-term planetary warming

DOE PAGES

Fyke, Jeremy Garmeson; Matthews, H. Damon

2015-11-16

Efforts to mitigate and adapt to long-term climate change could benefit greatly from probabilistic estimates of cumulative carbon emissions due to fossil fuel burning and resulting CO 2-induced planetary warming. Here we demonstrate the use of a reduced-form model to project these variables. We performed simulations using a large-ensemble framework with parametric uncertainty sampled to produce distributions of future cumulative emissions and consequent planetary warming. A hind-cast ensemble of simulations captured 1980–2012 historical CO 2 emissions trends and an ensemble of future projection simulations generated a distribution of emission scenarios that qualitatively resembled the suite of Representative and Extended Concentrationmore » Pathways. The resulting cumulative carbon emission and temperature change distributions are characterized by 5–95th percentile ranges of 0.96–4.9 teratonnes C (Tt C) and 1.4 °C–8.5 °C, respectively, with 50th percentiles at 3.1 Tt C and 4.7 °C. Within the wide range of policy-related parameter combinations that produced these distributions, we found that low-emission simulations were characterized by both high carbon prices and low costs of non-fossil fuel energy sources, suggesting the importance of these two policy levers in particular for avoiding dangerous levels of climate warming. With this analysis we demonstrate a probabilistic approach to the challenge of identifying strategies for limiting cumulative carbon emissions and assessing likelihoods of surpassing dangerous temperature thresholds.« less

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...

Using probabilistic criteria in an assessment of the potential radiological consequences of the decommissioning of a nuclear research reactor

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

Wallner, Christian; Rall, Anna-Maria; Thummerer, Severin

In order to assess the risk of radiological consequences of incidents and accidents in nuclear facilities it is important to contemplate their frequency of occurrence. It has to be shown that incidents and accidents occur sufficiently seldom according to their radiological consequences i. e. the occurrence frequency of radiological doses has to be limited. This is even demanded by the German radiation protection ordinance (StrlSchV), which says that in nuclear facilities other than nuclear power plants (NPP) in operation and for decommissioning, the occurrence frequency of incidents and accidents shall be contemplated in order to prove the design of safetymore » measures and safety installations. Based on the ideas of the ICRP64, we developed a risk based assessment concept for nuclear facilities, which fulfils the requirements of the German regulations concerning dose limits in normal operation and design basis accidents. The general use of the concept is dedicated to nuclear facilities other than nuclear power plants (NPP) in operation and for decommissioning, where the regulation of risk assessment is less sophisticated. The concept specifies occurrence frequency limits for radiation exposure dose ranges, i. e. the occurrence frequency of incidents and accidents has to be limited according to their radiological effects. To apply this concept, scenarios of incidents and accidents are grouped in exposition classes according to their resulting potential effective dose to members of the general public. The occurrence frequencies of the incidents and accidents are summarized in each exposition class whereas the sum must not exceed the frequency limits mentioned above. In the following we introduce the application of this concept in the assessment of the potential radiological consequences of the decommissioning of a nuclear research reactor. We carried out this assessment for the licensing process of the decommissioning on behalf of German authorities. (authors)« less

Integrated deterministic and probabilistic safety analysis for safety assessment of nuclear power plants

DOE PAGES

Di Maio, Francesco; Zio, Enrico; Smith, Curtis; ...

2015-07-06

The present special issue contains an overview of the research in the field of Integrated Deterministic and Probabilistic Safety Assessment (IDPSA) of Nuclear Power Plants (NPPs). Traditionally, safety regulation for NPPs design and operation has been based on Deterministic Safety Assessment (DSA) methods to verify criteria that assure plant safety in a number of postulated Design Basis Accident (DBA) scenarios. Referring to such criteria, it is also possible to identify those plant Structures, Systems, and Components (SSCs) and activities that are most important for safety within those postulated scenarios. Then, the design, operation, and maintenance of these “safety-related” SSCs andmore » activities are controlled through regulatory requirements and supported by Probabilistic Safety Assessment (PSA).« less

The Terrestrial Investigation Model: A probabilistic risk assessment model for birds exposed to pesticides

EPA Science Inventory

One of the major recommendations of the National Academy of Science to the USEPA, NMFS and USFWS was to utilize probabilistic methods when assessing the risks of pesticides to federally listed endangered and threatened species. The Terrestrial Investigation Model (TIM, version 3....

Climate change risk analysis framework (CCRAF) a probabilistic tool for analyzing climate change uncertainties

NASA Astrophysics Data System (ADS)

Legget, J.; Pepper, W.; Sankovski, A.; Smith, J.; Tol, R.; Wigley, T.

2003-04-01

Potential risks of human-induced climate change are subject to a three-fold uncertainty associated with: the extent of future anthropogenic and natural GHG emissions; global and regional climatic responses to emissions; and impacts of climatic changes on economies and the biosphere. Long-term analyses are also subject to uncertainty regarding how humans will respond to actual or perceived changes, through adaptation or mitigation efforts. Explicitly addressing these uncertainties is a high priority in the scientific and policy communities Probabilistic modeling is gaining momentum as a technique to quantify uncertainties explicitly and use decision analysis techniques that take advantage of improved risk information. The Climate Change Risk Assessment Framework (CCRAF) presented here a new integrative tool that combines the probabilistic approaches developed in population, energy and economic sciences with empirical data and probabilistic results of climate and impact models. The main CCRAF objective is to assess global climate change as a risk management challenge and to provide insights regarding robust policies that address the risks, by mitigating greenhouse gas emissions and by adapting to climate change consequences. The CCRAF endogenously simulates to 2100 or beyond annual region-specific changes in population; GDP; primary (by fuel) and final energy (by type) use; a wide set of associated GHG emissions; GHG concentrations; global temperature change and sea level rise; economic, health, and biospheric impacts; costs of mitigation and adaptation measures and residual costs or benefits of climate change. Atmospheric and climate components of CCRAF are formulated based on the latest version of Wigley's and Raper's MAGICC model and impacts are simulated based on a modified version of Tol's FUND model. The CCRAF is based on series of log-linear equations with deterministic and random components and is implemented using a Monte-Carlo method with up to 5000 variants per set of fixed input parameters. The shape and coefficients of CCRAF equations are derived from regression analyses of historic data and expert assessments. There are two types of random components in CCRAF - one reflects a year-to-year fluctuations around the expected value of a given variable (e.g., standard error of the annual GDP growth) and another is fixed within each CCRAF variant and represents some essential constants within a "world" represented by that variant (e.g., the value of climate sensitivity). Both types of random components are drawn from pre-defined probability distributions functions developed based on historic data or expert assessments. Preliminary CCRAF results emphasize the relative importance of uncertainties associated with the conversion of GHG and particulate emissions into radiative forcing and quantifying climate change effects at the regional level. A separates analysis involves an "adaptive decision-making", which optimizes the expected future policy effects given the estimated probabilistic uncertainties. As uncertainty for some variables evolve over the time steps, the decisions also adapt. This modeling approach is feasible only with explicit modeling of uncertainties.

Global scanning assessment of calcium channel blockers in the environment: Review and analysis of occurrence, ecotoxicology and hazards in aquatic systems.

PubMed

Saari, Gavin N; Scott, W Casan; Brooks, Bryan W

2017-12-01

As an urban water cycle is increasingly realized, aquatic systems are influenced by sewage and wastewater effluent discharges of variable quality. Such urbanization results in exposures of non-target aquatic organisms to medicines and other contaminants. In the present study, we performed a unique global hazard assessment of calcium channel blockers (CCB) in multiple environmental matrices. Effluent and freshwater observations were primarily from North America (62% and 76%, respectively) and Europe (21% and 10%, respectively) with limited-to-no information from rapidly urbanizing regions of developing countries in Asia-Pacific, South America, and Africa. Only 9% and 18% of occurrence data were from influent sewage and marine systems, though developing countries routinely discharge poorly treated wastewater to heavily populated coastal regions. Probabilistic environmental exposure distribution (EED) 5th and 95th percentiles for all CCBs were 1.5 and 309.1 ng/L in influent, 5.0 and 448.7 ng/L for effluent, 1.3 and 202.3 ng/L in freshwater, and 0.17 and 12.9 ng/L in saltwater, respectively. Unfortunately, global hazards and risks of CCBs to non-target organisms remain poorly understood, particularly for sublethal exposures. Thus, therapeutic hazard values (THV) were calculated and employed during probabilistic hazard assessments with EEDs when sufficient data was available. Amlodipine and verapamil in effluents and freshwater systems exceeded THVs 28% of the time, highlighting the need to understand ecological consequences of these CCBs. This global scanning approach demonstrated the utility of global assessments to identify specific CCBs, chemical mixtures with common mechanisms of action, and geographic locations for which environmental assessment efforts appear warranted. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

Effects of varying the step particle distribution on a probabilistic transport model

NASA Astrophysics Data System (ADS)

Bouzat, S.; Farengo, R.

2005-12-01

The consequences of varying the step particle distribution on a probabilistic transport model, which captures the basic features of transport in plasmas and was recently introduced in Ref. 1 [B. Ph. van Milligen et al., Phys. Plasmas 11, 2272 (2004)], are studied. Different superdiffusive transport mechanisms generated by a family of distributions with algebraic decays (Tsallis distributions) are considered. It is observed that the possibility of changing the superdiffusive transport mechanism improves the flexibility of the model for describing different situations. The use of the model to describe the low (L) and high (H) confinement modes is also analyzed.

Probabilistic assessment of smart composite structures

NASA Technical Reports Server (NTRS)

Chamis, Christos C.; Shiao, Michael C.

1994-01-01

A composite wing with spars and bulkheads is used to demonstrate the effectiveness of probabilistic assessment of smart composite structures to control uncertainties in distortions and stresses. Results show that a smart composite wing can be controlled to minimize distortions and to have specified stress levels in the presence of defects. Structural responses such as changes in angle of attack, vertical displacements, and stress in the control and controlled plies are probabilistically assessed to quantify their respective uncertainties. Sensitivity factors are evaluated to identify those parameters that have the greatest influence on a specific structural response. Results show that smart composite structures can be configured to control both distortions and ply stresses to satisfy specified design requirements.

Protocol and Demonstrations of Probabilistic Reliability Assessment for Structural Health Monitoring Systems (Preprint)

DTIC Science & Technology

2011-11-01

assessment to quality of localization/characterization estimates. This protocol includes four critical components: (1) a procedure to identify the...critical factors impacting SHM system performance; (2) a multistage or hierarchical approach to SHM system validation; (3) a model -assisted evaluation...Lindgren, E. A ., Buynak, C. F., Steffes, G., Derriso, M., “ Model -assisted Probabilistic Reliability Assessment for Structural Health Monitoring

76 FR 11525 - Advisory Committee on Reactor Safeguards (ACRS) Meeting of the ACRS Subcommittee on Reliability...

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2011-03-02

... NUCLEAR REGULATORY COMMISSION Advisory Committee on Reactor Safeguards (ACRS) Meeting of the ACRS Subcommittee on Reliability and Probabilistic Risk Assessment (PRA); Notice of Meeting The ACRS Subcommittee on Reliability and Probabilistic Risk Assessment (PRA), Room T-2B1, 11545 Rockville Pike, Rockville, Maryland...

76 FR 22934 - Advisory Committee on Reactor Safeguards (ACRS), Meeting of the ACRS Subcommittee on Reliability...

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2011-04-25

... NUCLEAR REGULATORY COMMISSION Advisory Committee on Reactor Safeguards (ACRS), Meeting of the ACRS Subcommittee on Reliability and Probabilistic Risk Assessment; Notice of Meeting The ACRS Subcommittee on Reliability and Probabilistic Risk Assessment (PRA) will hold a meeting on May 11, 2011, Room T-2B3, 11545...

76 FR 71609 - Advisory Committee on Reactor Safeguards (ACRS), Meeting of the ACRS Subcommittee on Reliability...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-18

... NUCLEAR REGULATORY COMMISSION Advisory Committee on Reactor Safeguards (ACRS), Meeting of the ACRS Subcommittee on Reliability and Probabilistic Risk Assessment; Notice of Meeting The ACRS Subcommittee on Reliability and Probabilistic Risk Assessment (PRA) will hold a meeting on December 14, 2011, Room T-2B3...

Probabilistic Assessment of National Wind Tunnel

NASA Technical Reports Server (NTRS)

Shah, A. R.; Shiao, M.; Chamis, C. C.

1996-01-01

A preliminary probabilistic structural assessment of the critical section of National Wind Tunnel (NWT) is performed using NESSUS (Numerical Evaluation of Stochastic Structures Under Stress) computer code. Thereby, the capabilities of NESSUS code have been demonstrated to address reliability issues of the NWT. Uncertainties in the geometry, material properties, loads and stiffener location on the NWT are considered to perform the reliability assessment. Probabilistic stress, frequency, buckling, fatigue and proof load analyses are performed. These analyses cover the major global and some local design requirements. Based on the assumed uncertainties, the results reveal the assurance of minimum 0.999 reliability for the NWT. Preliminary life prediction analysis results show that the life of the NWT is governed by the fatigue of welds. Also, reliability based proof test assessment is performed.

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.

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

Nuclear power and probabilistic safety assessment (PSA): past through future applications

NASA Astrophysics Data System (ADS)

Stamatelatos, M. G.; Moieni, P.; Everline, C. J.

1995-03-01

Nuclear power reactor safety in the United States is about to enter a new era -- an era of risk- based management and risk-based regulation. First, there was the age of `prescribed safety assessment,' during which a series of design-basis accidents in eight categories of severity, or classes, were postulated and analyzed. Toward the end of that era, it was recognized that `Class 9,' or `beyond design basis,' accidents would need special attention because of the potentially severe health and financial consequences of these accidents. The accident at Three Mile Island showed that sequences of low-consequence, high-frequency events and human errors can be much more risk dominant than the Class 9 accidents. A different form of safety assessment, PSA, emerged and began to gain ground against the deterministic safety establishment. Eventually, this led to the current regulatory requirements for individual plant examinations (IPEs). The IPEs can serve as a basis for risk-based regulation and management, a concept that may ultimately transform the U.S. regulatory process from its traditional deterministic foundations to a process predicated upon PSA. Beyond the possibility of a regulatory environment predicated upon PSA lies the possibility of using PSA as the foundation for managing daily nuclear power plant operations.

Fast, noise-free memory for photon synchronization at room temperature.

PubMed

Finkelstein, Ran; Poem, Eilon; Michel, Ohad; Lahad, Ohr; Firstenberg, Ofer

2018-01-01

Future quantum photonic networks require coherent optical memories for synchronizing quantum sources and gates of probabilistic nature. We demonstrate a fast ladder memory (FLAME) mapping the optical field onto the superposition between electronic orbitals of rubidium vapor. Using a ladder-level system of orbital transitions with nearly degenerate frequencies simultaneously enables high bandwidth, low noise, and long memory lifetime. We store and retrieve 1.7-ns-long pulses, containing 0.5 photons on average, and observe short-time external efficiency of 25%, memory lifetime (1/ e ) of 86 ns, and below 10 -4 added noise photons. Consequently, coupling this memory to a probabilistic source would enhance the on-demand photon generation probability by a factor of 12, the highest number yet reported for a noise-free, room temperature memory. This paves the way toward the controlled production of large quantum states of light from probabilistic photon sources.

Probabilistic vs. non-probabilistic approaches to the neurobiology of perceptual decision-making

PubMed Central

Drugowitsch, Jan; Pouget, Alexandre

2012-01-01

Optimal binary perceptual decision making requires accumulation of evidence in the form of a probability distribution that specifies the probability of the choices being correct given the evidence so far. Reward rates can then be maximized by stopping the accumulation when the confidence about either option reaches a threshold. Behavioral and neuronal evidence suggests that humans and animals follow such a probabilitistic decision strategy, although its neural implementation has yet to be fully characterized. Here we show that that diffusion decision models and attractor network models provide an approximation to the optimal strategy only under certain circumstances. In particular, neither model type is sufficiently flexible to encode the reliability of both the momentary and the accumulated evidence, which is a pre-requisite to accumulate evidence of time-varying reliability. Probabilistic population codes, in contrast, can encode these quantities and, as a consequence, have the potential to implement the optimal strategy accurately. PMID:22884815

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.

Multicriteria Decision Framework for Cybersecurity Risk Assessment and Management.

PubMed

Ganin, Alexander A; Quach, Phuoc; Panwar, Mahesh; Collier, Zachary A; Keisler, Jeffrey M; Marchese, Dayton; Linkov, Igor

2017-09-05

Risk assessors and managers face many difficult challenges related to novel cyber systems. Among these challenges are the constantly changing nature of cyber systems caused by technical advances, their distribution across the physical, information, and sociocognitive domains, and the complex network structures often including thousands of nodes. Here, we review probabilistic and risk-based decision-making techniques applied to cyber systems and conclude that existing approaches typically do not address all components of the risk assessment triplet (threat, vulnerability, consequence) and lack the ability to integrate across multiple domains of cyber systems to provide guidance for enhancing cybersecurity. We present a decision-analysis-based approach that quantifies threat, vulnerability, and consequences through a set of criteria designed to assess the overall utility of cybersecurity management alternatives. The proposed framework bridges the gap between risk assessment and risk management, allowing an analyst to ensure a structured and transparent process of selecting risk management alternatives. The use of this technique is illustrated for a hypothetical, but realistic, case study exemplifying the process of evaluating and ranking five cybersecurity enhancement strategies. The approach presented does not necessarily eliminate biases and subjectivity necessary for selecting countermeasures, but provides justifiable methods for selecting risk management actions consistent with stakeholder and decisionmaker values and technical data. Published 2017. This article is a U.S. Government work and is in the public domain in the U.S.A.

Probabilistic Simulation of Multi-Scale Composite Behavior

NASA Technical Reports Server (NTRS)

Chamis, Christos C.

2012-01-01

A methodology is developed to computationally assess the non-deterministic composite response at all composite scales (from micro to structural) due to the uncertainties in the constituent (fiber and matrix) properties, in the fabrication process and in structural variables (primitive variables). The methodology is computationally efficient for simulating the probability distributions of composite behavior, such as material properties, laminate and structural responses. Bi-products of the methodology are probabilistic sensitivities of the composite primitive variables. The methodology has been implemented into the computer codes PICAN (Probabilistic Integrated Composite ANalyzer) and IPACS (Integrated Probabilistic Assessment of Composite Structures). The accuracy and efficiency of this methodology are demonstrated by simulating the uncertainties in composite typical laminates and comparing the results with the Monte Carlo simulation method. Available experimental data of composite laminate behavior at all scales fall within the scatters predicted by PICAN. Multi-scaling is extended to simulate probabilistic thermo-mechanical fatigue and to simulate the probabilistic design of a composite redome in order to illustrate its versatility. Results show that probabilistic fatigue can be simulated for different temperature amplitudes and for different cyclic stress magnitudes. Results also show that laminate configurations can be selected to increase the redome reliability by several orders of magnitude without increasing the laminate thickness--a unique feature of structural composites. The old reference denotes that nothing fundamental has been done since that time.

The Gain-Loss Model: A Probabilistic Skill Multimap Model for Assessing Learning Processes

ERIC Educational Resources Information Center

Robusto, Egidio; Stefanutti, Luca; Anselmi, Pasquale

2010-01-01

Within the theoretical framework of knowledge space theory, a probabilistic skill multimap model for assessing learning processes is proposed. The learning process of a student is modeled as a function of the student's knowledge and of an educational intervention on the attainment of specific skills required to solve problems in a knowledge…

76 FR 18586 - Advisory Committee on Reactor Safeguards (ACRS); Meeting of the ACRS Subcommittee on Reliability...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-04-04

... NUCLEAR REGULATORY COMMISSION Advisory Committee on Reactor Safeguards (ACRS); Meeting of the ACRS Subcommittee on Reliability and Probabilistic Risk Assessment (PRA); Notice of Meeting The ACRS Subcommittee on Reliability and Probabilistic Risk Assessment (PRA) will hold a meeting on April 20, 2011, Room T-2B1, 11545...

76 FR 55717 - Advisory Committee on Reactor Safeguards (ACRS); Meeting of the ACRS Subcommittee on Reliability...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-08

... Subcommittee on Reliability and Probabilistic Risk Assessment The ACRS Subcommittee on Reliability and Probabilistic Risk Assessment (PRA) will hold a meeting on September 20, 2011, Room T-2B1, 11545 Rockville Pike... Memorandum on Modifying the Risk-Informed Regulatory Guidance for New Reactors. The Subcommittee will hear...

COMMUNICATING PROBABILISTIC RISK OUTCOMES TO RISK MANAGERS

EPA Science Inventory

Increasingly, risk assessors are moving away from simple deterministic assessments to probabilistic approaches that explicitly incorporate ecological variability, measurement imprecision, and lack of knowledge (collectively termed "uncertainty"). While the new methods provide an...

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.

A regional-scale ecological risk framework for environmental flow evaluations

NASA Astrophysics Data System (ADS)

O'Brien, Gordon C.; Dickens, Chris; Hines, Eleanor; Wepener, Victor; Stassen, Retha; Quayle, Leo; Fouchy, Kelly; MacKenzie, James; Graham, P. Mark; Landis, Wayne G.

2018-02-01

Environmental flow (E-flow) frameworks advocate holistic, regional-scale, probabilistic E-flow assessments that consider flow and non-flow drivers of change in a socio-ecological context as best practice. Regional-scale ecological risk assessments of multiple stressors to social and ecological endpoints, which address ecosystem dynamism, have been undertaken internationally at different spatial scales using the relative-risk model since the mid-1990s. With the recent incorporation of Bayesian belief networks into the relative-risk model, a robust regional-scale ecological risk assessment approach is available that can contribute to achieving the best practice recommendations of E-flow frameworks. PROBFLO is a holistic E-flow assessment method that incorporates the relative-risk model and Bayesian belief networks (BN-RRM) into a transparent probabilistic modelling tool that addresses uncertainty explicitly. PROBFLO has been developed to evaluate the socio-ecological consequences of historical, current and future water resource use scenarios and generate E-flow requirements on regional spatial scales. The approach has been implemented in two regional-scale case studies in Africa where its flexibility and functionality has been demonstrated. In both case studies the evidence-based outcomes facilitated informed environmental management decision making, with trade-off considerations in the context of social and ecological aspirations. This paper presents the PROBFLO approach as applied to the Senqu River catchment in Lesotho and further developments and application in the Mara River catchment in Kenya and Tanzania. The 10 BN-RRM procedural steps incorporated in PROBFLO are demonstrated with examples from both case studies. PROBFLO can contribute to the adaptive management of water resources and contribute to the allocation of resources for sustainable use of resources and address protection requirements.

On the complex quantification of risk: systems-based perspective on terrorism.

PubMed

Haimes, Yacov Y

2011-08-01

This article highlights the complexity of the quantification of the multidimensional risk function, develops five systems-based premises on quantifying the risk of terrorism to a threatened system, and advocates the quantification of vulnerability and resilience through the states of the system. The five premises are: (i) There exists interdependence between a specific threat to a system by terrorist networks and the states of the targeted system, as represented through the system's vulnerability, resilience, and criticality-impact. (ii) A specific threat, its probability, its timing, the states of the targeted system, and the probability of consequences can be interdependent. (iii) The two questions in the risk assessment process: "What is the likelihood?" and "What are the consequences?" can be interdependent. (iv) Risk management policy options can reduce both the likelihood of a threat to a targeted system and the associated likelihood of consequences by changing the states (including both vulnerability and resilience) of the system. (v) The quantification of risk to a vulnerable system from a specific threat must be built on a systemic and repeatable modeling process, by recognizing that the states of the system constitute an essential step to construct quantitative metrics of the consequences based on intelligence gathering, expert evidence, and other qualitative information. The fact that the states of all systems are functions of time (among other variables) makes the time frame pivotal in each component of the process of risk assessment, management, and communication. Thus, risk to a system, caused by an initiating event (e.g., a threat) is a multidimensional function of the specific threat, its probability and time frame, the states of the system (representing vulnerability and resilience), and the probabilistic multidimensional consequences. © 2011 Society for Risk Analysis.

Assessment of food intake input distributions for use in probabilistic exposure assessments of food additives.

PubMed

Gilsenan, M B; Lambe, J; Gibney, M J

2003-11-01

A key component of a food chemical exposure assessment using probabilistic analysis is the selection of the most appropriate input distribution to represent exposure variables. The study explored the type of parametric distribution that could be used to model variability in food consumption data likely to be included in a probabilistic exposure assessment of food additives. The goodness-of-fit of a range of continuous distributions to observed data of 22 food categories expressed as average daily intakes among consumers from the North-South Ireland Food Consumption Survey was assessed using the BestFit distribution fitting program. The lognormal distribution was most commonly accepted as a plausible parametric distribution to represent food consumption data when food intakes were expressed as absolute intakes (16/22 foods) and as intakes per kg body weight (18/22 foods). Results from goodness-of-fit tests were accompanied by lognormal probability plots for a number of food categories. The influence on food additive intake of using a lognormal distribution to model food consumption input data was assessed by comparing modelled intake estimates with observed intakes. Results from the present study advise some level of caution about the use of a lognormal distribution as a mode of input for food consumption data in probabilistic food additive exposure assessments and the results highlight the need for further research in this area.

The Use of the Direct Optimized Probabilistic Calculation Method in Design of Bolt Reinforcement for Underground and Mining Workings

PubMed Central

Krejsa, Martin; Janas, Petr; Yilmaz, Işık; Marschalko, Marian; Bouchal, Tomas

2013-01-01

The load-carrying system of each construction should fulfill several conditions which represent reliable criteria in the assessment procedure. It is the theory of structural reliability which determines probability of keeping required properties of constructions. Using this theory, it is possible to apply probabilistic computations based on the probability theory and mathematic statistics. Development of those methods has become more and more popular; it is used, in particular, in designs of load-carrying structures with the required level or reliability when at least some input variables in the design are random. The objective of this paper is to indicate the current scope which might be covered by the new method—Direct Optimized Probabilistic Calculation (DOProC) in assessments of reliability of load-carrying structures. DOProC uses a purely numerical approach without any simulation techniques. This provides more accurate solutions to probabilistic tasks, and, in some cases, such approach results in considerably faster completion of computations. DOProC can be used to solve efficiently a number of probabilistic computations. A very good sphere of application for DOProC is the assessment of the bolt reinforcement in the underground and mining workings. For the purposes above, a special software application—“Anchor”—has been developed. PMID:23935412

Rats bred for high alcohol drinking are more sensitive to delayed and probabilistic outcomes.

PubMed

Wilhelm, C J; Mitchell, S H

2008-10-01

Alcoholics and heavy drinkers score higher on measures of impulsivity than nonalcoholics and light drinkers. This may be because of factors that predate drug exposure (e.g. genetics). This study examined the role of genetics by comparing impulsivity measures in ethanol-naive rats selectively bred based on their high [high alcohol drinking (HAD)] or low [low alcohol drinking (LAD)] consumption of ethanol. Replicates 1 and 2 of the HAD and LAD rats, developed by the University of Indiana Alcohol Research Center, completed two different discounting tasks. Delay discounting examines sensitivity to rewards that are delayed in time and is commonly used to assess 'choice' impulsivity. Probability discounting examines sensitivity to the uncertain delivery of rewards and has been used to assess risk taking and risk assessment. High alcohol drinking rats discounted delayed and probabilistic rewards more steeply than LAD rats. Discount rates associated with probabilistic and delayed rewards were weakly correlated, while bias was strongly correlated with discount rate in both delay and probability discounting. The results suggest that selective breeding for high alcohol consumption selects for animals that are more sensitive to delayed and probabilistic outcomes. Sensitivity to delayed or probabilistic outcomes may be predictive of future drinking in genetically predisposed individuals.

From cyclone tracks to the costs of European winter storms: A probabilistic loss assessment model

NASA Astrophysics Data System (ADS)

Renggli, Dominik; Corti, Thierry; Reese, Stefan; Wueest, Marc; Viktor, Elisabeth; Zimmerli, Peter

2014-05-01

The quantitative assessment of the potential losses of European winter storms is essential for the economic viability of a global reinsurance company. For this purpose, reinsurance companies generally use probabilistic loss assessment models. This work presents an innovative approach to develop physically meaningful probabilistic events for Swiss Re's new European winter storm loss model. The meteorological hazard component of the new model is based on cyclone and windstorm tracks identified in the 20th Century Reanalysis data. The knowledge of the evolution of winter storms both in time and space allows the physically meaningful perturbation of properties of historical events (e.g. track, intensity). The perturbation includes a random element but also takes the local climatology and the evolution of the historical event into account. The low-resolution wind footprints taken from 20th Century Reanalysis are processed by a statistical-dynamical downscaling to generate high-resolution footprints of the historical and probabilistic winter storm events. Downscaling transfer functions are generated using ENSEMBLES regional climate model data. The result is a set of reliable probabilistic events representing thousands of years. The event set is then combined with country- and risk-specific vulnerability functions and detailed market- or client-specific exposure information to compute (re-)insurance risk premiums.

Probabilistic Assessment of Cancer Risk from Solar Particle Events

NASA Astrophysics Data System (ADS)

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

For long duration missions outside of the protection of the Earth's magnetic field, space radi-ation presents significant health risks including cancer mortality. Space radiation consists of solar particle events (SPEs), comprised largely of medium energy protons (less than several hundred MeV); and galactic cosmic ray (GCR), which include high energy protons and heavy ions. While the frequency distribution of SPEs depends strongly upon the phase within the solar activity cycle, the individual SPE occurrences themselves are random in nature. We es-timated the probability of SPE occurrence using a non-homogeneous Poisson model to fit the historical database of proton measurements. Distributions of particle fluences of SPEs for a specified mission period were simulated ranging from its 5th to 95th percentile to assess the cancer risk distribution. Spectral variability of SPEs was also examined, because the detailed energy spectra of protons are important especially at high energy levels for assessing the cancer risk associated with energetic particles for large events. We estimated the overall cumulative probability of GCR environment for a specified mission period using a solar modulation model for the temporal characterization of the GCR environment represented by the deceleration po-tential (φ). Probabilistic assessment of cancer fatal risk was calculated for various periods of lunar and Mars missions. This probabilistic approach to risk assessment from space radiation is in support of mission design and operational planning for future manned space exploration missions. In future work, this probabilistic approach to the space radiation will be combined with a probabilistic approach to the radiobiological factors that contribute to the uncertainties in projecting cancer risks.

Probabilistic Assessment of Cancer Risk from Solar Particle Events

NASA Technical Reports Server (NTRS)

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

2010-01-01

For long duration missions outside of the protection of the Earth s magnetic field, space radiation presents significant health risks including cancer mortality. Space radiation consists of solar particle events (SPEs), comprised largely of medium energy protons (less than several hundred MeV); and galactic cosmic ray (GCR), which include high energy protons and heavy ions. While the frequency distribution of SPEs depends strongly upon the phase within the solar activity cycle, the individual SPE occurrences themselves are random in nature. We estimated the probability of SPE occurrence using a non-homogeneous Poisson model to fit the historical database of proton measurements. Distributions of particle fluences of SPEs for a specified mission period were simulated ranging from its 5 th to 95th percentile to assess the cancer risk distribution. Spectral variability of SPEs was also examined, because the detailed energy spectra of protons are important especially at high energy levels for assessing the cancer risk associated with energetic particles for large events. We estimated the overall cumulative probability of GCR environment for a specified mission period using a solar modulation model for the temporal characterization of the GCR environment represented by the deceleration potential (^). Probabilistic assessment of cancer fatal risk was calculated for various periods of lunar and Mars missions. This probabilistic approach to risk assessment from space radiation is in support of mission design and operational planning for future manned space exploration missions. In future work, this probabilistic approach to the space radiation will be combined with a probabilistic approach to the radiobiological factors that contribute to the uncertainties in projecting cancer risks.

A PROBABILISTIC EXPOSURE ASSESSMENT FOR CHILDREN WHO CONTACT CCA-TREATED PLAYSETS AND DECKS USING THE STOCHASTIC HUMAN EXPOSURE AND DOSE SIMULATION (SHEDS) MODEL FOR THE WOOD PRESERVATIVE EXPOSURE SCENARIO

EPA Science Inventory

The U.S. Environmental Protection Agency has conducted a probabilistic exposure and dose assessment on the arsenic (As) and chromium (Cr) components of Chromated Copper Arsenate (CCA) using the Stochastic Human Exposure and Dose Simulation model for wood preservatives (SHEDS-Wood...

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...

Methodology for assessing quantities of water and proppant injection, and water production associated with development of continuous petroleum accumulations

USGS Publications Warehouse

Haines, Seth S.

2015-07-13

The quantities of water and hydraulic fracturing proppant required for producing petroleum (oil, gas, and natural gas liquids) from continuous accumulations, and the quantities of water extracted during petroleum production, can be quantitatively assessed using a probabilistic approach. The water and proppant assessment methodology builds on the U.S. Geological Survey methodology for quantitative assessment of undiscovered technically recoverable petroleum resources in continuous accumulations. The U.S. Geological Survey assessment methodology for continuous petroleum accumulations includes fundamental concepts such as geologically defined assessment units, and probabilistic input values including well-drainage area, sweet- and non-sweet-spot areas, and success ratio within the untested area of each assessment unit. In addition to petroleum-related information, required inputs for the water and proppant assessment methodology include probabilistic estimates of per-well water usage for drilling, cementing, and hydraulic-fracture stimulation; the ratio of proppant to water for hydraulic fracturing; the percentage of hydraulic fracturing water that returns to the surface as flowback; and the ratio of produced water to petroleum over the productive life of each well. Water and proppant assessments combine information from recent or current petroleum assessments with water- and proppant-related input values for the assessment unit being studied, using Monte Carlo simulation, to yield probabilistic estimates of the volume of water for drilling, cementing, and hydraulic fracture stimulation; the quantity of proppant for hydraulic fracture stimulation; and the volumes of water produced as flowback shortly after well completion, and produced over the life of the well.

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.

PROBABILISTIC MODELING FOR ADVANCED HUMAN EXPOSURE ASSESSMENT

EPA Science Inventory

Human exposures to environmental pollutants widely vary depending on the emission patterns that result in microenvironmental pollutant concentrations, as well as behavioral factors that determine the extent of an individual's contact with these pollutants. Probabilistic human exp...

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

Warning systems in risk management.

PubMed

Paté-Cornell, M E

1986-06-01

A method is presented here that allows probabilistic evaluation and optimization of warning systems, and comparison of their performance and cost-effectiveness with those of other means of risk management. The model includes an assessment of the signals, and of human response, given the memory that people have kept of the quality of previous alerts. The trade-off between the rate of false alerts and the length of the lead time is studied to account for the long-term effects of "crying wolf" and the effectiveness of emergency actions. An explicit formulation of the system's benefits, including inputs from a signal model, a response model, and a consequence model, is given to allow optimization of the warning threshold and of the system's sensitivity.

Tsunamis: stochastic models of occurrence and generation mechanisms

USGS Publications Warehouse

Geist, Eric L.; Oglesby, David D.

2014-01-01

The devastating consequences of the 2004 Indian Ocean and 2011 Japan tsunamis have led to increased research into many different aspects of the tsunami phenomenon. In this entry, we review research related to the observed complexity and uncertainty associated with tsunami generation, propagation, and occurrence described and analyzed using a variety of stochastic methods. In each case, seismogenic tsunamis are primarily considered. Stochastic models are developed from the physical theories that govern tsunami evolution combined with empirical models fitted to seismic and tsunami observations, as well as tsunami catalogs. These stochastic methods are key to providing probabilistic forecasts and hazard assessments for tsunamis. The stochastic methods described here are similar to those described for earthquakes (Vere-Jones 2013) and volcanoes (Bebbington 2013) in this encyclopedia.

Integrated Campaign Probabilistic Cost, Schedule, Performance, and Value for Program Office Support

NASA Technical Reports Server (NTRS)

Cornelius, David; Sasamoto, Washito; Daugherty, Kevin; Deacon, Shaun

2012-01-01

This paper describes an integrated assessment tool developed at NASA Langley Research Center that incorporates probabilistic analysis of life cycle cost, schedule, launch performance, on-orbit performance, and value across a series of planned space-based missions, or campaign. Originally designed as an aid in planning the execution of missions to accomplish the National Research Council 2007 Earth Science Decadal Survey, it utilizes Monte Carlo simulation of a series of space missions for assessment of resource requirements and expected return on investment. Interactions between simulated missions are incorporated, such as competition for launch site manifest, to capture unexpected and non-linear system behaviors. A novel value model is utilized to provide an assessment of the probabilistic return on investment. A demonstration case is discussed to illustrate the tool utility.

Optimization of Systems with Uncertainty: Initial Developments for Performance, Robustness and Reliability Based Designs

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Bushnell, Dennis M. (Technical Monitor)

2002-01-01

This paper presents a study on the optimization of systems with structured uncertainties, whose inputs and outputs can be exhaustively described in the probabilistic sense. By propagating the uncertainty from the input to the output in the space of the probability density functions and the moments, optimization problems that pursue performance, robustness and reliability based designs are studied. Be specifying the desired outputs in terms of desired probability density functions and then in terms of meaningful probabilistic indices, we settle a computationally viable framework for solving practical optimization problems. Applications to static optimization and stability control are used to illustrate the relevance of incorporating uncertainty in the early stages of the design. Several examples that admit a full probabilistic description of the output in terms of the design variables and the uncertain inputs are used to elucidate the main features of the generic problem and its solution. Extensions to problems that do not admit closed form solutions are also evaluated. Concrete evidence of the importance of using a consistent probabilistic formulation of the optimization problem and a meaningful probabilistic description of its solution is provided in the examples. In the stability control problem the analysis shows that standard deterministic approaches lead to designs with high probability of running into instability. The implementation of such designs can indeed have catastrophic consequences.

Global assessment of human losses due to earthquakes

USGS Publications Warehouse

Silva, Vitor; Jaiswal, Kishor; Weatherill, Graeme; Crowley, Helen

2014-01-01

Current studies have demonstrated a sharp increase in human losses due to earthquakes. These alarming levels of casualties suggest the need for large-scale investment in seismic risk mitigation, which, in turn, requires an adequate understanding of the extent of the losses, and location of the most affected regions. Recent developments in global and uniform datasets such as instrumental and historical earthquake catalogues, population spatial distribution and country-based vulnerability functions, have opened an unprecedented possibility for a reliable assessment of earthquake consequences at a global scale. In this study, a uniform probabilistic seismic hazard assessment (PSHA) model was employed to derive a set of global seismic hazard curves, using the open-source software OpenQuake for seismic hazard and risk analysis. These results were combined with a collection of empirical fatality vulnerability functions and a population dataset to calculate average annual human losses at the country level. The results from this study highlight the regions/countries in the world with a higher seismic risk, and thus where risk reduction measures should be prioritized.

Judgment under uncertainty; a probabilistic evaluation framework for decision-making about sanitation systems in low-income countries.

PubMed

Malekpour, Shirin; Langeveld, Jeroen; Letema, Sammy; Clemens, François; van Lier, Jules B

2013-03-30

This paper introduces the probabilistic evaluation framework, to enable transparent and objective decision-making in technology selection for sanitation solutions in low-income countries. The probabilistic framework recognizes the often poor quality of the available data for evaluations. Within this framework, the evaluations will be done based on the probabilities that the expected outcomes occur in practice, considering the uncertainties in evaluation parameters. Consequently, the outcome of evaluations will not be single point estimates; but there exists a range of possible outcomes. A first trial application of this framework for evaluation of sanitation options in the Nyalenda settlement in Kisumu, Kenya, showed how the range of values that an evaluation parameter may obtain in practice would influence the evaluation outcomes. In addition, as the probabilistic evaluation requires various site-specific data, sensitivity analysis was performed to determine the influence of each data set quality on the evaluation outcomes. Based on that, data collection activities could be (re)directed, in a trade-off between the required investments in those activities and the resolution of the decisions that are to be made. Copyright © 2013 Elsevier Ltd. All rights reserved.

Probabilistic record linkage

PubMed Central

Sayers, Adrian; Ben-Shlomo, Yoav; Blom, Ashley W; Steele, Fiona

2016-01-01

Abstract Studies involving the use of probabilistic record linkage are becoming increasingly common. However, the methods underpinning probabilistic record linkage are not widely taught or understood, and therefore these studies can appear to be a ‘black box’ research tool. In this article, we aim to describe the process of probabilistic record linkage through a simple exemplar. We first introduce the concept of deterministic linkage and contrast this with probabilistic linkage. We illustrate each step of the process using a simple exemplar and describe the data structure required to perform a probabilistic linkage. We describe the process of calculating and interpreting matched weights and how to convert matched weights into posterior probabilities of a match using Bayes theorem. We conclude this article with a brief discussion of some of the computational demands of record linkage, how you might assess the quality of your linkage algorithm, and how epidemiologists can maximize the value of their record-linked research using robust record linkage methods. PMID:26686842

Application of Medium and Seasonal Flood Forecasts for Agriculture Damage Assessment

NASA Astrophysics Data System (ADS)

Fakhruddin, Shamsul; Ballio, Francesco; Menoni, Scira

2015-04-01

Early warning is a key element for disaster risk reduction. In recent decades, major advancements have been made in medium range and seasonal flood forecasting. This progress provides a great opportunity to reduce agriculture damage and improve advisories for early action and planning for flood hazards. This approach can facilitate proactive rather than reactive management of the adverse consequences of floods. In the agricultural sector, for instance, farmers can take a diversity of options such as changing cropping patterns, applying fertilizer, irrigating and changing planting timing. An experimental medium range (1-10 day) and seasonal (20-25 days) flood forecasting model has been developed for Thailand and Bangladesh. It provides 51 sets of discharge ensemble forecasts of 1-10 days with significant persistence and high certainty and qualitative outlooks for 20-25 days. This type of forecast could assist farmers and other stakeholders for differential preparedness activities. These ensembles probabilistic flood forecasts have been customized based on user-needs for community-level application focused on agriculture system. The vulnerabilities of agriculture system were calculated based on exposure, sensitivity and adaptive capacity. Indicators for risk and vulnerability assessment were conducted through community consultations. The forecast lead time requirement, user-needs, impacts and management options for crops were identified through focus group discussions, informal interviews and community surveys. This paper illustrates potential applications of such ensembles for probabilistic medium range and seasonal flood forecasts in a way that is not commonly practiced globally today.

Probabilistic fault tree analysis of a radiation treatment system.

PubMed

Ekaette, Edidiong; Lee, Robert C; Cooke, David L; Iftody, Sandra; Craighead, Peter

2007-12-01

Inappropriate administration of radiation for cancer treatment can result in severe consequences such as premature death or appreciably impaired quality of life. There has been little study of vulnerable treatment process components and their contribution to the risk of radiation treatment (RT). In this article, we describe the application of probabilistic fault tree methods to assess the probability of radiation misadministration to patients at a large cancer treatment center. We conducted a systematic analysis of the RT process that identified four process domains: Assessment, Preparation, Treatment, and Follow-up. For the Preparation domain, we analyzed possible incident scenarios via fault trees. For each task, we also identified existing quality control measures. To populate the fault trees we used subjective probabilities from experts and compared results with incident report data. Both the fault tree and the incident report analysis revealed simulation tasks to be most prone to incidents, and the treatment prescription task to be least prone to incidents. The probability of a Preparation domain incident was estimated to be in the range of 0.1-0.7% based on incident reports, which is comparable to the mean value of 0.4% from the fault tree analysis using probabilities from the expert elicitation exercise. In conclusion, an analysis of part of the RT system using a fault tree populated with subjective probabilities from experts was useful in identifying vulnerable components of the system, and provided quantitative data for risk management.

Review of methods for developing regional probabilistic risk assessments, part 2: modeling invasive plant, insect, and pathogen species

Treesearch

P. B. Woodbury; D. A. Weinstein

2010-01-01

We reviewed probabilistic regional risk assessment methodologies to identify the methods that are currently in use and are capable of estimating threats to ecosystems from fire and fuels, invasive species, and their interactions with stressors. In a companion chapter, we highlight methods useful for evaluating risks from fire. In this chapter, we highlight methods...

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

Monitoring and exposure assessment of pesticide residues in cowpea (Vigna unguiculata L. Walp) from five provinces of southern China.

PubMed

Huan, Zhibo; Xu, Zhi; Luo, Jinhui; Xie, Defang

2016-11-01

Residues of 14 pesticides were determined in 150 cowpea samples collected in five southern Chinese provinces in 2013 and 2014.70% samples were detected one or more residues. 61.3% samples were illegal mainly because of detection of unauthorized pesticides. 14.0% samples contained more than three pesticides. Deterministic and probabilistic methods were used to assess the chronic and acute risk of pesticides in cowpea to eight subgroups of people. Deterministic assessment showed that the estimated short-term intakes (ESTIs) of carbofuran were 1199.4%-2621.9% of the acute reference doses (ARfD) while the rates were 985.9%-4114.7% using probabilistic assessment. Probabilistic assessment showed 4.2%-7.8% subjects may suffer from unacceptable acute risk from carbofuran contaminated cowpeas from the five provinces (especially children). But undue concern is not necessary, because all the estimations are based on conservative assumption. Copyright © 2016 Elsevier Inc. All rights reserved.

The benefits of probabilistic exposure assessment: three case studies involving contaminated air, water, and soil.

PubMed

Finley, B; Paustenbach, D

1994-02-01

Probabilistic risk assessments are enjoying increasing popularity as a tool to characterize the health hazards associated with exposure to chemicals in the environment. Because probabilistic analyses provide much more information to the risk manager than standard "point" risk estimates, this approach has generally been heralded as one which could significantly improve the conduct of health risk assessments. The primary obstacles to replacing point estimates with probabilistic techniques include a general lack of familiarity with the approach and a lack of regulatory policy and guidance. This paper discusses some of the advantages and disadvantages of the point estimate vs. probabilistic approach. Three case studies are presented which contrast and compare the results of each. The first addresses the risks associated with household exposure to volatile chemicals in tapwater. The second evaluates airborne dioxin emissions which can enter the food-chain. The third illustrates how to derive health-based cleanup levels for dioxin in soil. It is shown that, based on the results of Monte Carlo analyses of probability density functions (PDFs), the point estimate approach required by most regulatory agencies will nearly always overpredict the risk for the 95th percentile person by a factor of up to 5. When the assessment requires consideration of 10 or more exposure variables, the point estimate approach will often predict risks representative of the 99.9th percentile person rather than the 50th or 95th percentile person. This paper recommends a number of data distributions for various exposure variables that we believe are now sufficiently well understood to be used with confidence in most exposure assessments. A list of exposure variables that may require additional research before adequate data distributions can be developed are also discussed.

Probabilistic simulation of the human factor in structural reliability

NASA Technical Reports Server (NTRS)

Chamis, C. C.

1993-01-01

A formal approach is described in an attempt to computationally simulate the probable ranges of uncertainties of the human factor in structural probabilistic assessments. A multi-factor interaction equation (MFIE) model has been adopted for this purpose. Human factors such as marital status, professional status, home life, job satisfaction, work load and health, are considered to demonstrate the concept. Parametric studies in conjunction with judgment are used to select reasonable values for the participating factors (primitive variables). Suitability of the MFIE in the subsequently probabilistic sensitivity studies are performed to assess the validity of the whole approach. Results obtained show that the uncertainties for no error range from five to thirty percent for the most optimistic case.

Probabilistic simulation of the human factor in structural reliability

NASA Astrophysics Data System (ADS)

Chamis, Christos C.; Singhal, Surendra N.

1994-09-01

The formal approach described herein computationally simulates the probable ranges of uncertainties for the human factor in probabilistic assessments of structural reliability. Human factors such as marital status, professional status, home life, job satisfaction, work load, and health are studied by using a multifactor interaction equation (MFIE) model to demonstrate the approach. Parametric studies in conjunction with judgment are used to select reasonable values for the participating factors (primitive variables). Subsequently performed probabilistic sensitivity studies assess the suitability of the MFIE as well as the validity of the whole approach. Results show that uncertainties range from 5 to 30 percent for the most optimistic case, assuming 100 percent for no error (perfect performance).

Probabilistic Simulation of the Human Factor in Structural Reliability

NASA Technical Reports Server (NTRS)

Chamis, Christos C.; Singhal, Surendra N.

1994-01-01

The formal approach described herein computationally simulates the probable ranges of uncertainties for the human factor in probabilistic assessments of structural reliability. Human factors such as marital status, professional status, home life, job satisfaction, work load, and health are studied by using a multifactor interaction equation (MFIE) model to demonstrate the approach. Parametric studies in conjunction with judgment are used to select reasonable values for the participating factors (primitive variables). Subsequently performed probabilistic sensitivity studies assess the suitability of the MFIE as well as the validity of the whole approach. Results show that uncertainties range from 5 to 30 percent for the most optimistic case, assuming 100 percent for no error (perfect performance).

Influence Diagrams as Decision-Making Tools for Pesticide Risk Management

EPA Science Inventory

The pesticide policy arena is filled with discussion of probabilistic approaches to assess ecological risk, however, similar discussions about implementing formal probabilistic methods in pesticide risk decision making are less common. An influence diagram approach is proposed f...

A PROBABILISTIC MODELING FRAMEWORK FOR PREDICTING POPULATION EXPOSURES TO BENZENE

EPA Science Inventory

The US Environmental Protection Agency (EPA) is modifying their probabilistic Stochastic Human Exposure Dose Simulation (SHEDS) model to assess aggregate exposures to air toxics. Air toxics include urban Hazardous Air Pollutants (HAPS) such as benzene from mobile sources, part...

INTEGRATING PROBABILISTIC AND FIXED-SITE MONITORING FOR ROBUST WATER QUALITY ASSESSMENTS

EPA Science Inventory

Determining the extent of water-quality degradation, controlling nonpoint sources, and defining allowable amounts of contaminants are important water-quality issues defined in the Clean Water Act that require new monitoring data. Probabilistic, randomized stream water-quality mon...

Frontal and Parietal Contributions to Probabilistic Association Learning

PubMed Central

Rushby, Jacqueline A.; Vercammen, Ans; Loo, Colleen; Short, Brooke

2011-01-01

Neuroimaging studies have shown both dorsolateral prefrontal (DLPFC) and inferior parietal cortex (iPARC) activation during probabilistic association learning. Whether these cortical brain regions are necessary for probabilistic association learning is presently unknown. Participants' ability to acquire probabilistic associations was assessed during disruptive 1 Hz repetitive transcranial magnetic stimulation (rTMS) of the left DLPFC, left iPARC, and sham using a crossover single-blind design. On subsequent sessions, performance improved relative to baseline except during DLPFC rTMS that disrupted the early acquisition beneficial effect of prior exposure. A second experiment examining rTMS effects on task-naive participants showed that neither DLPFC rTMS nor sham influenced naive acquisition of probabilistic associations. A third experiment examining consecutive administration of the probabilistic association learning test revealed early trial interference from previous exposure to different probability schedules. These experiments, showing disrupted acquisition of probabilistic associations by rTMS only during subsequent sessions with an intervening night's sleep, suggest that the DLPFC may facilitate early access to learned strategies or prior task-related memories via consolidation. Although neuroimaging studies implicate DLPFC and iPARC in probabilistic association learning, the present findings suggest that early acquisition of the probabilistic cue-outcome associations in task-naive participants is not dependent on either region. PMID:21216842

System Risk Assessment and Allocation in Conceptual Design

NASA Technical Reports Server (NTRS)

Mahadevan, Sankaran; Smith, Natasha L.; Zang, Thomas A. (Technical Monitor)

2003-01-01

As aerospace systems continue to evolve in addressing newer challenges in air and space transportation, there exists a heightened priority for significant improvement in system performance, cost effectiveness, reliability, and safety. Tools, which synthesize multidisciplinary integration, probabilistic analysis, and optimization, are needed to facilitate design decisions allowing trade-offs between cost and reliability. This study investigates tools for probabilistic analysis and probabilistic optimization in the multidisciplinary design of aerospace systems. A probabilistic optimization methodology is demonstrated for the low-fidelity design of a reusable launch vehicle at two levels, a global geometry design and a local tank design. Probabilistic analysis is performed on a high fidelity analysis of a Navy missile system. Furthermore, decoupling strategies are introduced to reduce the computational effort required for multidisciplinary systems with feedback coupling.

Probabilistic Tsunami Hazard Assessment: the Seaside, Oregon Pilot Study

NASA Astrophysics Data System (ADS)

Gonzalez, F. I.; Geist, E. L.; Synolakis, C.; Titov, V. V.

2004-12-01

A pilot study of Seaside, Oregon is underway, to develop methodologies for probabilistic tsunami hazard assessments that can be incorporated into Flood Insurance Rate Maps (FIRMs) developed by FEMA's National Flood Insurance Program (NFIP). Current NFIP guidelines for tsunami hazard assessment rely on the science, technology and methodologies developed in the 1970s; although generally regarded as groundbreaking and state-of-the-art for its time, this approach is now superseded by modern methods that reflect substantial advances in tsunami research achieved in the last two decades. In particular, post-1990 technical advances include: improvements in tsunami source specification; improved tsunami inundation models; better computational grids by virtue of improved bathymetric and topographic databases; a larger database of long-term paleoseismic and paleotsunami records and short-term, historical earthquake and tsunami records that can be exploited to develop improved probabilistic methodologies; better understanding of earthquake recurrence and probability models. The NOAA-led U.S. National Tsunami Hazard Mitigation Program (NTHMP), in partnership with FEMA, USGS, NSF and Emergency Management and Geotechnical agencies of the five Pacific States, incorporates these advances into site-specific tsunami hazard assessments for coastal communities in Alaska, California, Hawaii, Oregon and Washington. NTHMP hazard assessment efforts currently focus on developing deterministic, "credible worst-case" scenarios that provide valuable guidance for hazard mitigation and emergency management. The NFIP focus, on the other hand, is on actuarial needs that require probabilistic hazard assessments such as those that characterize 100- and 500-year flooding events. There are clearly overlaps in NFIP and NTHMP objectives. NTHMP worst-case scenario assessments that include an estimated probability of occurrence could benefit the NFIP; NFIP probabilistic assessments of 100- and 500-yr events could benefit the NTHMP. The joint NFIP/NTHMP pilot study at Seaside, Oregon is organized into three closely related components: Probabilistic, Modeling, and Impact studies. Probabilistic studies (Geist, et al., this session) are led by the USGS and include the specification of near- and far-field seismic tsunami sources and their associated probabilities. Modeling studies (Titov, et al., this session) are led by NOAA and include the development and testing of a Seaside tsunami inundation model and an associated database of computed wave height and flow velocity fields. Impact studies (Synolakis, et al., this session) are led by USC and include the computation and analyses of indices for the categorization of hazard zones. The results of each component study will be integrated to produce a Seaside tsunami hazard map. This presentation will provide a brief overview of the project and an update on progress, while the above-referenced companion presentations will provide details on the methods used and the preliminary results obtained by each project component.

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.

Statistical surrogate models for prediction of high-consequence climate change.

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

Constantine, Paul; Field, Richard V., Jr.; Boslough, Mark Bruce Elrick

2011-09-01

In safety engineering, performance metrics are defined using probabilistic risk assessments focused on the low-probability, high-consequence tail of the distribution of possible events, as opposed to best estimates based on central tendencies. We frame the climate change problem and its associated risks in a similar manner. To properly explore the tails of the distribution requires extensive sampling, which is not possible with existing coupled atmospheric models due to the high computational cost of each simulation. We therefore propose the use of specialized statistical surrogate models (SSMs) for the purpose of exploring the probability law of various climate variables of interest.more » A SSM is different than a deterministic surrogate model in that it represents each climate variable of interest as a space/time random field. The SSM can be calibrated to available spatial and temporal data from existing climate databases, e.g., the Program for Climate Model Diagnosis and Intercomparison (PCMDI), or to a collection of outputs from a General Circulation Model (GCM), e.g., the Community Earth System Model (CESM) and its predecessors. Because of its reduced size and complexity, the realization of a large number of independent model outputs from a SSM becomes computationally straightforward, so that quantifying the risk associated with low-probability, high-consequence climate events becomes feasible. A Bayesian framework is developed to provide quantitative measures of confidence, via Bayesian credible intervals, in the use of the proposed approach to assess these risks.« less

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.

Using probabilistic theory to develop interpretation guidelines for Y-STR profiles.

PubMed

Taylor, Duncan; Bright, Jo-Anne; Buckleton, John

2016-03-01

Y-STR profiling makes up a small but important proportion of forensic DNA casework. Often Y-STR profiles are used when autosomal profiling has failed to yield an informative result. Consequently Y-STR profiles are often from the most challenging samples. In addition to these points, Y-STR loci are linked, meaning that evaluation of haplotype probabilities are either based on overly simplified counting methods or computationally costly genetic models, neither of which extend well to the evaluation of mixed Y-STR data. For all of these reasons Y-STR data analysis has not seen the same advances as autosomal STR data. We present here a probabilistic model for the interpretation of Y-STR data. Due to the fact that probabilistic systems for Y-STR data are still some way from reaching active casework, we also describe how data can be analysed in a continuous way to generate interpretational thresholds and guidelines. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Spatial planning using probabilistic flood maps

NASA Astrophysics Data System (ADS)

Alfonso, Leonardo; Mukolwe, Micah; Di Baldassarre, Giuliano

2015-04-01

Probabilistic flood maps account for uncertainty in flood inundation modelling and convey a degree of certainty in the outputs. Major sources of uncertainty include input data, topographic data, model structure, observation data and parametric uncertainty. Decision makers prefer less ambiguous information from modellers; this implies that uncertainty is suppressed to yield binary flood maps. Though, suppressing information may potentially lead to either surprise or misleading decisions. Inclusion of uncertain information in the decision making process is therefore desirable and transparent. To this end, we utilise the Prospect theory and information from a probabilistic flood map to evaluate potential decisions. Consequences related to the decisions were evaluated using flood risk analysis. Prospect theory explains how choices are made given options for which probabilities of occurrence are known and accounts for decision makers' characteristics such as loss aversion and risk seeking. Our results show that decision making is pronounced when there are high gains and loss, implying higher payoffs and penalties, therefore a higher gamble. Thus the methodology may be appropriately considered when making decisions based on uncertain information.

Using a probabilistic approach in an ecological risk assessment simulation tool: test case for depleted uranium (DU).

PubMed

Fan, Ming; Thongsri, Tepwitoon; Axe, Lisa; Tyson, Trevor A

2005-06-01

A probabilistic approach was applied in an ecological risk assessment (ERA) to characterize risk and address uncertainty employing Monte Carlo simulations for assessing parameter and risk probabilistic distributions. This simulation tool (ERA) includes a Window's based interface, an interactive and modifiable database management system (DBMS) that addresses a food web at trophic levels, and a comprehensive evaluation of exposure pathways. To illustrate this model, ecological risks from depleted uranium (DU) exposure at the US Army Yuma Proving Ground (YPG) and Aberdeen Proving Ground (APG) were assessed and characterized. Probabilistic distributions showed that at YPG, a reduction in plant root weight is considered likely to occur (98% likelihood) from exposure to DU; for most terrestrial animals, likelihood for adverse reproduction effects ranges from 0.1% to 44%. However, for the lesser long-nosed bat, the effects are expected to occur (>99% likelihood) through the reduction in size and weight of offspring. Based on available DU data for the firing range at APG, DU uptake will not likely affect survival of aquatic plants and animals (<0.1% likelihood). Based on field and laboratory studies conducted at APG and YPG on pocket mice, kangaroo rat, white-throated woodrat, deer, and milfoil, body burden concentrations observed fall into the distributions simulated at both sites.

Development of Probabilistic Flood Inundation Mapping For Flooding Induced by Dam Failure

NASA Astrophysics Data System (ADS)

Tsai, C.; Yeh, J. J. J.

2017-12-01

A primary function of flood inundation mapping is to forecast flood hazards and assess potential losses. However, uncertainties limit the reliability of inundation hazard assessments. Major sources of uncertainty should be taken into consideration by an optimal flood management strategy. This study focuses on the 20km reach downstream of the Shihmen Reservoir in Taiwan. A dam failure induced flood herein provides the upstream boundary conditions of flood routing. The two major sources of uncertainty that are considered in the hydraulic model and the flood inundation mapping herein are uncertainties in the dam break model and uncertainty of the roughness coefficient. The perturbance moment method is applied to a dam break model and the hydro system model to develop probabilistic flood inundation mapping. Various numbers of uncertain variables can be considered in these models and the variability of outputs can be quantified. The probabilistic flood inundation mapping for dam break induced floods can be developed with consideration of the variability of output using a commonly used HEC-RAS model. Different probabilistic flood inundation mappings are discussed and compared. Probabilistic flood inundation mappings are hoped to provide new physical insights in support of the evaluation of concerning reservoir flooded areas.

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

NASA Technical Reports Server (NTRS)

Cruse, T. A.

1987-01-01

The objective is the development of several modular structural analysis packages capable of predicting the probabilistic response distribution for key structural variables such as maximum stress, natural frequencies, transient response, etc. The structural analysis packages are to include stochastic modeling of loads, material properties, geometry (tolerances), and boundary conditions. The solution is to be in terms of the cumulative probability of exceedance distribution (CDF) and confidence bounds. Two methods of probability modeling are to be included as well as three types of structural models - probabilistic finite-element method (PFEM); probabilistic approximate analysis methods (PAAM); and probabilistic boundary element methods (PBEM). The purpose in doing probabilistic structural analysis is to provide the designer with a more realistic ability to assess the importance of uncertainty in the response of a high performance structure. Probabilistic Structural Analysis Method (PSAM) tools will estimate structural safety and reliability, while providing the engineer with information on the confidence that should be given to the predicted behavior. Perhaps most critically, the PSAM results will directly provide information on the sensitivity of the design response to those variables which are seen to be uncertain.

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

NASA Technical Reports Server (NTRS)

Cruse, T. A.; Burnside, O. H.; Wu, Y.-T.; Polch, E. Z.; Dias, J. B.

1988-01-01

The objective is the development of several modular structural analysis packages capable of predicting the probabilistic response distribution for key structural variables such as maximum stress, natural frequencies, transient response, etc. The structural analysis packages are to include stochastic modeling of loads, material properties, geometry (tolerances), and boundary conditions. The solution is to be in terms of the cumulative probability of exceedance distribution (CDF) and confidence bounds. Two methods of probability modeling are to be included as well as three types of structural models - probabilistic finite-element method (PFEM); probabilistic approximate analysis methods (PAAM); and probabilistic boundary element methods (PBEM). The purpose in doing probabilistic structural analysis is to provide the designer with a more realistic ability to assess the importance of uncertainty in the response of a high performance structure. Probabilistic Structural Analysis Method (PSAM) tools will estimate structural safety and reliability, while providing the engineer with information on the confidence that should be given to the predicted behavior. Perhaps most critically, the PSAM results will directly provide information on the sensitivity of the design response to those variables which are seen to be uncertain.

A Probabilistic Tsunami Hazard Study of the Auckland Region, Part II: Inundation Modelling and Hazard Assessment

NASA Astrophysics Data System (ADS)

Lane, E. M.; Gillibrand, P. A.; Wang, X.; Power, W.

2013-09-01

Regional source tsunamis pose a potentially devastating hazard to communities and infrastructure on the New Zealand coast. But major events are very uncommon. This dichotomy of infrequent but potentially devastating hazards makes realistic assessment of the risk challenging. Here, we describe a method to determine a probabilistic assessment of the tsunami hazard by regional source tsunamis with an "Average Recurrence Interval" of 2,500-years. The method is applied to the east Auckland region of New Zealand. From an assessment of potential regional tsunamigenic events over 100,000 years, the inundation of the Auckland region from the worst 100 events is modelled using a hydrodynamic model and probabilistic inundation depths on a 2,500-year time scale were determined. Tidal effects on the potential inundation were included by coupling the predicted wave heights with the probability density function of tidal heights at the inundation site. Results show that the more exposed northern section of the east coast and outer islands in the Hauraki Gulf face the greatest hazard from regional tsunamis in the Auckland region. Incorporating tidal effects into predictions of inundation reduced the predicted hazard compared to modelling all the tsunamis arriving at high tide giving a more accurate hazard assessment on the specified time scale. This study presents the first probabilistic analysis of dynamic modelling of tsunami inundation for the New Zealand coast and as such provides the most comprehensive assessment of tsunami inundation of the Auckland region from regional source tsunamis available to date.

Probabilistic forecasts based on radar rainfall uncertainty

NASA Astrophysics Data System (ADS)

Liguori, S.; Rico-Ramirez, M. A.

2012-04-01

The potential advantages resulting from integrating weather radar rainfall estimates in hydro-meteorological forecasting systems is limited by the inherent uncertainty affecting radar rainfall measurements, which is due to various sources of error [1-3]. The improvement of quality control and correction techniques is recognized to play a role for the future improvement of radar-based flow predictions. However, the knowledge of the uncertainty affecting radar rainfall data can also be effectively used to build a hydro-meteorological forecasting system in a probabilistic framework. This work discusses the results of the implementation of a novel probabilistic forecasting system developed to improve ensemble predictions over a small urban area located in the North of England. An ensemble of radar rainfall fields can be determined as the sum of a deterministic component and a perturbation field, the latter being informed by the knowledge of the spatial-temporal characteristics of the radar error assessed with reference to rain-gauges measurements. This approach is similar to the REAL system [4] developed for use in the Southern-Alps. The radar uncertainty estimate can then be propagated with a nowcasting model, used to extrapolate an ensemble of radar rainfall forecasts, which can ultimately drive hydrological ensemble predictions. A radar ensemble generator has been calibrated using radar rainfall data made available from the UK Met Office after applying post-processing and corrections algorithms [5-6]. One hour rainfall accumulations from 235 rain gauges recorded for the year 2007 have provided the reference to determine the radar error. Statistics describing the spatial characteristics of the error (i.e. mean and covariance) have been computed off-line at gauges location, along with the parameters describing the error temporal correlation. A system has then been set up to impose the space-time error properties to stochastic perturbations, generated in real-time at gauges location, and then interpolated back onto the radar domain, in order to obtain probabilistic radar rainfall fields in real time. The deterministic nowcasting model integrated in the STEPS system [7-8] has been used for the purpose of propagating the uncertainty and assessing the benefit of implementing the radar ensemble generator for probabilistic rainfall forecasts and ultimately sewer flow predictions. For this purpose, events representative of different types of precipitation (i.e. stratiform/convective) and significant at the urban catchment scale (i.e. in terms of sewer overflow within the urban drainage system) have been selected. As high spatial/temporal resolution is required to the forecasts for their use in urban areas [9-11], the probabilistic nowcasts have been set up to be produced at 1 km resolution and 5 min intervals. The forecasting chain is completed by a hydrodynamic model of the urban drainage network. The aim of this work is to discuss the implementation of this probabilistic system, which takes into account the radar error to characterize the forecast uncertainty, with consequent potential benefits in the management of urban systems. It will also allow a comparison with previous findings related to the analysis of different approaches to uncertainty estimation and quantification in terms of rainfall [12] and flows at the urban scale [13]. Acknowledgements The authors would like to acknowledge the BADC, the UK Met Office and Dr. Alan Seed from the Australian Bureau of Meteorology for providing the radar data and the nowcasting model. The authors acknowledge the support from the Engineering and Physical Sciences Research Council (EPSRC) via grant EP/I012222/1.

Sensitivity of Asteroid Impact Risk to Uncertainty in Asteroid Properties and Entry Parameters

NASA Astrophysics Data System (ADS)

Wheeler, Lorien; Mathias, Donovan; Dotson, Jessie L.; NASA Asteroid Threat Assessment Project

2017-10-01

A central challenge in assessing the threat posed by asteroids striking Earth is the large amount of uncertainty inherent throughout all aspects of the problem. Many asteroid properties are not well characterized and can range widely from strong, dense, monolithic irons to loosely bound, highly porous rubble piles. Even for an object of known properties, the specific entry velocity, angle, and impact location can swing the potential consequence from no damage to causing millions of casualties. Due to the extreme rarity of large asteroid strikes, there are also large uncertainties in how different types of asteroids will interact with the atmosphere during entry, how readily they may break up or ablate, and how much surface damage will be caused by the resulting airbursts or impacts.In this work, we use our Probabilistic Asteroid Impact Risk (PAIR) model to investigate the sensitivity of asteroid impact damage to uncertainties in key asteroid properties, entry parameters, or modeling assumptions. The PAIR model combines physics-based analytic models of asteroid entry and damage in a probabilistic Monte Carlo framework to assess the risk posed by a wide range of potential impacts. The model samples from uncertainty distributions of asteroid properties and entry parameters to generate millions of specific impact cases, and models the atmospheric entry and damage for each case, including blast overpressure, thermal radiation, tsunami inundation, and global effects. To assess the risk sensitivity, we alternately fix and vary the different input parameters and compare the effect on the resulting range of damage produced. The goal of these studies is to help guide future efforts in asteroid characterization and model refinement by determining which properties most significantly affect the potential risk.

Two approaches to incorporate clinical data uncertainty into multiple criteria decision analysis for benefit-risk assessment of medicinal products.

PubMed

Wen, Shihua; Zhang, Lanju; Yang, Bo

2014-07-01

The Problem formulation, Objectives, Alternatives, Consequences, Trade-offs, Uncertainties, Risk attitude, and Linked decisions (PrOACT-URL) framework and multiple criteria decision analysis (MCDA) have been recommended by the European Medicines Agency for structured benefit-risk assessment of medicinal products undergoing regulatory review. The objective of this article was to provide solutions to incorporate the uncertainty from clinical data into the MCDA model when evaluating the overall benefit-risk profiles among different treatment options. Two statistical approaches, the δ-method approach and the Monte-Carlo approach, were proposed to construct the confidence interval of the overall benefit-risk score from the MCDA model as well as other probabilistic measures for comparing the benefit-risk profiles between treatment options. Both approaches can incorporate the correlation structure between clinical parameters (criteria) in the MCDA model and are straightforward to implement. The two proposed approaches were applied to a case study to evaluate the benefit-risk profile of an add-on therapy for rheumatoid arthritis (drug X) relative to placebo. It demonstrated a straightforward way to quantify the impact of the uncertainty from clinical data to the benefit-risk assessment and enabled statistical inference on evaluating the overall benefit-risk profiles among different treatment options. The δ-method approach provides a closed form to quantify the variability of the overall benefit-risk score in the MCDA model, whereas the Monte-Carlo approach is more computationally intensive but can yield its true sampling distribution for statistical inference. The obtained confidence intervals and other probabilistic measures from the two approaches enhance the benefit-risk decision making of medicinal products. Copyright © 2014 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Selective effects of 5-HT2C receptor modulation on performance of a novel valence-probe visual discrimination task and probabilistic reversal learning in mice.

PubMed

Phillips, Benjamin U; Dewan, Sigma; Nilsson, Simon R O; Robbins, Trevor W; Heath, Christopher J; Saksida, Lisa M; Bussey, Timothy J; Alsiö, Johan

2018-04-22

Dysregulation of the serotonin (5-HT) system is a pathophysiological component in major depressive disorder (MDD), a condition closely associated with abnormal emotional responsivity to positive and negative feedback. However, the precise mechanism through which 5-HT tone biases feedback responsivity remains unclear. 5-HT2C receptors (5-HT2CRs) are closely linked with aspects of depressive symptomatology, including abnormalities in reinforcement processes and response to stress. Thus, we aimed to determine the impact of 5-HT2CR function on response to feedback in biased reinforcement learning. We used two touchscreen assays designed to assess the impact of positive and negative feedback on probabilistic reinforcement in mice, including a novel valence-probe visual discrimination (VPVD) and a probabilistic reversal learning procedure (PRL). Systemic administration of a 5-HT2CR agonist and antagonist resulted in selective changes in the balance of feedback sensitivity bias on these tasks. Specifically, on VPVD, SB 242084, the 5-HT2CR antagonist, impaired acquisition of a discrimination dependent on appropriate integration of positive and negative feedback. On PRL, SB 242084 at 1 mg/kg resulted in changes in behaviour consistent with reduced sensitivity to positive feedback. In contrast, WAY 163909, the 5-HT2CR agonist, resulted in changes associated with increased sensitivity to positive feedback and decreased sensitivity to negative feedback. These results suggest that 5-HT2CRs tightly regulate feedback sensitivity bias in mice with consequent effects on learning and cognitive flexibility and specify a framework for the influence of 5-HT2CRs on sensitivity to reinforcement.

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...

Global forecasting of thermal health hazards: the skill of probabilistic predictions of the Universal Thermal Climate Index (UTCI).

PubMed

Pappenberger, F; Jendritzky, G; Staiger, H; Dutra, E; Di Giuseppe, F; Richardson, D S; Cloke, H L

2015-03-01

Although over a hundred thermal indices can be used for assessing thermal health hazards, many ignore the human heat budget, physiology and clothing. The Universal Thermal Climate Index (UTCI) addresses these shortcomings by using an advanced thermo-physiological model. This paper assesses the potential of using the UTCI for forecasting thermal health hazards. Traditionally, such hazard forecasting has had two further limitations: it has been narrowly focused on a particular region or nation and has relied on the use of single 'deterministic' forecasts. Here, the UTCI is computed on a global scale, which is essential for international health-hazard warnings and disaster preparedness, and it is provided as a probabilistic forecast. It is shown that probabilistic UTCI forecasts are superior in skill to deterministic forecasts and that despite global variations, the UTCI forecast is skilful for lead times up to 10 days. The paper also demonstrates the utility of probabilistic UTCI forecasts on the example of the 2010 heat wave in Russia.

Site-specific probabilistic ecological risk assessment of a volatile chlorinated hydrocarbon-contaminated tidal estuary.

PubMed

Hunt, James; Birch, Gavin; Warne, Michael St J

2010-05-01

Groundwater contaminated with volatile chlorinated hydrocarbons (VCHs) was identified as discharging to Penrhyn Estuary, an intertidal embayment of Botany Bay, New South Wales, Australia. A screening-level hazard assessment of surface water in Penrhyn Estuary identified an unacceptable hazard to marine organisms posed by VCHs. Given the limitations of hazard assessments, the present study conducted a higher-tier, quantitative probabilistic risk assessment using the joint probability curve (JPC) method that accounted for variability in exposure and toxicity profiles to quantify risk (delta). Risk was assessed for 24 scenarios, including four areas of the estuary based on three exposure scenarios (low tide, high tide, and both low and high tides) and two toxicity scenarios (chronic no-observed-effect concentrations [NOEC] and 50% effect concentrations [EC50]). Risk (delta) was greater at low tide than at high tide and varied throughout the tidal cycle. Spatial distributions of risk in the estuary were similar using both NOEC and EC50 data. The exposure scenario including data combined from both tides was considered the most accurate representation of the ecological risk in the estuary. When assessing risk using data across both tides, the greatest risk was identified in the Springvale tributary (delta=25%)-closest to the source area-followed by the inner estuary (delta=4%) and the Floodvale tributary (delta=2%), with the lowest risk in the outer estuary (delta=0.1%), farthest from the source area. Going from the screening level ecological risk assessment (ERA) to the probabilistic ERA changed the risk from unacceptable to acceptable in 50% of exposure scenarios in two of the four areas within the estuary. The probabilistic ERA provided a more realistic assessment of risk than the screening-level hazard assessment. Copyright (c) 2010 SETAC.

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.

E-Area LLWF Vadose Zone Model: Probabilistic Model for Estimating Subsided-Area Infiltration Rates

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

Dyer, J.; Flach, G.

A probabilistic model employing a Monte Carlo sampling technique was developed in Python to generate statistical distributions of the upslope-intact-area to subsided-area ratio (Area UAi/Area SAi) for closure cap subsidence scenarios that differ in assumed percent subsidence and the total number of intact plus subsided compartments. The plan is to use this model as a component in the probabilistic system model for the E-Area Performance Assessment (PA), contributing uncertainty in infiltration estimates.

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

Quantification of uncertainties in the performance of smart composite structures

NASA Technical Reports Server (NTRS)

Shiao, Michael C.; Chamis, Christos C.

1993-01-01

A composite wing with spars, bulkheads, and built-in control devices is evaluated using a method for the probabilistic assessment of smart composite structures. Structural responses (such as change in angle of attack, vertical displacements, and stresses in regular plies with traditional materials and in control plies with mixed traditional and actuation materials) are probabilistically assessed to quantify their respective scatter. Probabilistic sensitivity factors are computed to identify those parameters that have a significant influence on a specific structural response. Results show that the uncertainties in the responses of smart composite structures can be quantified. Responses such as structural deformation, ply stresses, frequencies, and buckling loads in the presence of defects can be reliably controlled to satisfy specified design requirements.

Probabilistic Assessment of Fracture Progression in Composite Structures

NASA Technical Reports Server (NTRS)

Chamis, Christos C.; Minnetyan, Levon; Mauget, Bertrand; Huang, Dade; Addi, Frank

1999-01-01

This report describes methods and corresponding computer codes that are used to evaluate progressive damage and fracture and to perform probabilistic assessment in built-up composite structures. Structural response is assessed probabilistically, during progressive fracture. The effects of design variable uncertainties on structural fracture progression are quantified. The fast probability integrator (FPI) is used to assess the response scatter in the composite structure at damage initiation. The sensitivity of the damage response to design variables is computed. The methods are general purpose and are applicable to stitched and unstitched composites in all types of structures and fracture processes starting from damage initiation to unstable propagation and to global structure collapse. The methods are demonstrated for a polymer matrix composite stiffened panel subjected to pressure. The results indicated that composite constituent properties, fabrication parameters, and respective uncertainties have a significant effect on structural durability and reliability. Design implications with regard to damage progression, damage tolerance, and reliability of composite structures are examined.

Probabilistic Risk Model for Organ Doses and Acute Health Effects of Astronauts on Lunar Missions

NASA Technical Reports Server (NTRS)

Kim, Myung-Hee Y.; Hu, Shaowen; Nounu, Hatem N.; Cucinotta, Francis A.

2009-01-01

Exposure to large solar particle events (SPEs) is a major concern during EVAs on the lunar surface and in Earth-to-Lunar transit. 15% of crew times may be on EVA with minimal radiation shielding. Therefore, an accurate assessment of SPE occurrence probability is required for the mission planning by NASA. We apply probabilistic risk assessment (PRA) for radiation protection of crews and optimization of lunar mission planning.

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.

The use of belief-based probabilistic methods in volcanology: Scientists' views and implications for risk assessments

NASA Astrophysics Data System (ADS)

Donovan, Amy; Oppenheimer, Clive; Bravo, Michael

2012-12-01

This paper constitutes a philosophical and social scientific study of expert elicitation in the assessment and management of volcanic risk on Montserrat during the 1995-present volcanic activity. It outlines the broader context of subjective probabilistic methods and then uses a mixed-method approach to analyse the use of these methods in volcanic crises. Data from a global survey of volcanologists regarding the use of statistical methods in hazard assessment are presented. Detailed qualitative data from Montserrat are then discussed, particularly concerning the expert elicitation procedure that was pioneered during the eruptions. These data are analysed and conclusions about the use of these methods in volcanology are drawn. The paper finds that while many volcanologists are open to the use of these methods, there are still some concerns, which are similar to the concerns encountered in the literature on probabilistic and determinist approaches to seismic hazard analysis.

What's in a Name? Probabilistic Inference of Religious Community from South Asian Names

ERIC Educational Resources Information Center

Susewind, Raphael

2015-01-01

Fine-grained data on religious communities are often considered sensitive in South Asia and consequently remain inaccessible. Yet without such data, statistical research on communal relations and group-based inequality remains superficial, hampering the development of appropriate policy measures to prevent further social exclusion on the basis of…

Functional Topography of Early Periventricular Brain Lesions in Relation to Cytoarchitectonic Probabilistic Maps

ERIC Educational Resources Information Center

Staudt, Martin; Ticini, Luca F.; Grodd, Wolfgang; Krageloh-Mann, Ingeborg; Karnath, Hans-Otto

2008-01-01

Early periventricular brain lesions can not only cause cerebral palsy, but can also induce a reorganization of language. Here, we asked whether these different functional consequences can be attributed to topographically distinct portions of the periventricular white matter damage. Eight patients with pre- and perinatally acquired left-sided…

Developmental and Gender Related Differences in Response Switches after Nonrepresentative Negative Feedback

ERIC Educational Resources Information Center

Jansen, Brenda R. J.; van Duijvenvoorde, Anna C. K.; Huizenga, Hilde M.

2014-01-01

In many decision making tasks negative feedback is probabilistic and, as a consequence, may be given when the decision is actually correct. This feedback can be referred to as nonrepresentative negative feedback. In the current study, we investigated developmental and gender related differences in such switching after nonrepresentative negative…

Probabilistic Description of the Hydrologic Risk in Agriculture

NASA Astrophysics Data System (ADS)

Vico, G.; Porporato, A. M.

2011-12-01

Supplemental irrigation represents one of the main strategies to mitigate the effects of climatic variability on agroecosystems productivity and profitability, at the expenses of increasing water requirements for irrigation purposes. Optimizing water allocation for crop yield preservation and sustainable development needs to account for hydro-climatic variability, which is by far the main source of uncertainty affecting crop yields and irrigation water requirements. In this contribution, a widely applicable probabilistic framework is proposed to quantitatively define the hydrologic risk of yield reduction for both rainfed and irrigated agriculture. The occurrence of rainfall events and irrigation applications are linked probabilistically to crop development during the growing season. Based on these linkages, long-term and real-time yield reduction risk indices are defined as a function of climate, soil and crop parameters, as well as irrigation strategy. The former risk index is suitable for long-term irrigation strategy assessment and investment planning, while the latter risk index provides a rigorous probabilistic quantification of the emergence of drought conditions during a single growing season. This probabilistic framework allows also assessing the impact of limited water availability on crop yield, thus guiding the optimal allocation of water resources for human and environmental needs. Our approach employs relatively few parameters and is thus easily and broadly applicable to different crops and sites, under current and future climate scenarios, thus facilitating the assessment of the impact of increasingly frequent water shortages on agricultural productivity, profitability, and sustainability.

A Systems-Based Risk Assessment Framework for Intentional Electromagnetic Interference (IEMI) on Critical Infrastructures.

PubMed

Oakes, Benjamin Donald; Mattsson, Lars-Göran; Näsman, Per; Glazunov, Andrés Alayón

2018-06-01

Modern infrastructures are becoming increasingly dependent on electronic systems, leaving them more vulnerable to electrical surges or electromagnetic interference. Electromagnetic disturbances appear in nature, e.g., lightning and solar wind; however, they may also be generated by man-made technology to maliciously damage or disturb electronic equipment. This article presents a systematic risk assessment framework for identifying possible, consequential, and plausible intentional electromagnetic interference (IEMI) attacks on an arbitrary distribution network infrastructure. In the absence of available data on IEMI occurrences, we find that a systems-based risk assessment is more useful than a probabilistic approach. We therefore modify the often applied definition of risk, i.e., a set of triplets containing scenario, probability, and consequence, to a set of quadruplets: scenario, resource requirements, plausibility, and consequence. Probability is "replaced" by resource requirements and plausibility, where the former is the minimum amount and type of equipment necessary to successfully carry out an attack scenario and the latter is a subjective assessment of the extent of the existence of attackers who possess the motivation, knowledge, and resources necessary to carry out the scenario. We apply the concept of intrusion areas and classify electromagnetic source technology according to key attributes. Worst-case scenarios are identified for different quantities of attacker resources. The most plausible and consequential of these are deemed the most important scenarios and should provide useful decision support in a countermeasures effort. Finally, an example of the proposed risk assessment framework, based on notional data, is provided on a hypothetical water distribution network. © 2017 Society for Risk Analysis.

Probability in reasoning: a developmental test on conditionals.

PubMed

Barrouillet, Pierre; Gauffroy, Caroline

2015-04-01

Probabilistic theories have been claimed to constitute a new paradigm for the psychology of reasoning. A key assumption of these theories is captured by what they call the Equation, the hypothesis that the meaning of the conditional is probabilistic in nature and that the probability of If p then q is the conditional probability, in such a way that P(if p then q)=P(q|p). Using the probabilistic truth-table task in which participants are required to evaluate the probability of If p then q sentences, the present study explored the pervasiveness of the Equation through ages (from early adolescence to adulthood), types of conditionals (basic, causal, and inducements) and contents. The results reveal that the Equation is a late developmental achievement only endorsed by a narrow majority of educated adults for certain types of conditionals depending on the content they involve. Age-related changes in evaluating the probability of all the conditionals studied closely mirror the development of truth-value judgements observed in previous studies with traditional truth-table tasks. We argue that our modified mental model theory can account for this development, and hence for the findings related with the probability task, which do not consequently support the probabilistic approach of human reasoning over alternative theories. Copyright © 2014 Elsevier B.V. All rights reserved.

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.

Uncertainty Analysis of Consequence Management (CM) Data Products.

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

Hunt, Brian D.; Eckert-Gallup, Aubrey Celia; Cochran, Lainy Dromgoole

The goal of this project is to develop and execute methods for characterizing uncertainty in data products that are deve loped and distributed by the DOE Consequence Management (CM) Program. A global approach to this problem is necessary because multiple sources of error and uncertainty from across the CM skill sets contribute to the ultimate p roduction of CM data products. This report presents the methods used to develop a probabilistic framework to characterize this uncertainty and provides results for an uncertainty analysis for a study scenario analyzed using this framework.

A probabilistic tsunami hazard assessment for Indonesia

NASA Astrophysics Data System (ADS)

Horspool, N.; Pranantyo, I.; Griffin, J.; Latief, H.; Natawidjaja, D. H.; Kongko, W.; Cipta, A.; Bustaman, B.; Anugrah, S. D.; Thio, H. K.

2014-11-01

Probabilistic hazard assessments are a fundamental tool for assessing the threats posed by hazards to communities and are important for underpinning evidence-based decision-making regarding risk mitigation activities. Indonesia has been the focus of intense tsunami risk mitigation efforts following the 2004 Indian Ocean tsunami, but this has been largely concentrated on the Sunda Arc with little attention to other tsunami prone areas of the country such as eastern Indonesia. We present the first nationally consistent probabilistic tsunami hazard assessment (PTHA) for Indonesia. This assessment produces time-independent forecasts of tsunami hazards at the coast using data from tsunami generated by local, regional and distant earthquake sources. The methodology is based on the established monte carlo approach to probabilistic seismic hazard assessment (PSHA) and has been adapted to tsunami. We account for sources of epistemic and aleatory uncertainty in the analysis through the use of logic trees and sampling probability density functions. For short return periods (100 years) the highest tsunami hazard is the west coast of Sumatra, south coast of Java and the north coast of Papua. For longer return periods (500-2500 years), the tsunami hazard is highest along the Sunda Arc, reflecting the larger maximum magnitudes. The annual probability of experiencing a tsunami with a height of > 0.5 m at the coast is greater than 10% for Sumatra, Java, the Sunda islands (Bali, Lombok, Flores, Sumba) and north Papua. The annual probability of experiencing a tsunami with a height of > 3.0 m, which would cause significant inundation and fatalities, is 1-10% in Sumatra, Java, Bali, Lombok and north Papua, and 0.1-1% for north Sulawesi, Seram and Flores. The results of this national-scale hazard assessment provide evidence for disaster managers to prioritise regions for risk mitigation activities and/or more detailed hazard or risk assessment.

A PROBABILISTIC SURVEY OF FISH TISSUE CONTAMINATION FROM THE CONTINENTAL SHELF OF THE US WEST COAST

EPA Science Inventory

A probabilistic survey of environmental condition of the continental shelf of the US West Coast was conducted in 2003 by the US EPA National Coastal Assessment (NCA), with collaboration by the NOAA National Marine Fisheries Service. Metals and organic contaminants were analyzed ...

WV R-EMAP SMALL WATERSHED CHARACTERIZATION, CLASSIFICATION, AND ASSESSMENT FOR WEST VIRGINIA UTILIZING EMAP DESIGN AND TOOLS

EPA Science Inventory

A probabilistic watershed-based framework was developed to encompass wadeable streams within all three ecoregions of West Virginia, with the exclusion noted below. In Phase I of the project (year 2001), we developed and applied a probabilistic watershed-based sampling framework ...

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...

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 tsunami hazard assessment at Seaside, Oregon, for near-and far-field seismic sources

USGS Publications Warehouse

Gonzalez, F.I.; Geist, E.L.; Jaffe, B.; Kanoglu, U.; Mofjeld, H.; Synolakis, C.E.; Titov, V.V.; Areas, D.; Bellomo, D.; Carlton, D.; Horning, T.; Johnson, J.; Newman, J.; Parsons, T.; Peters, R.; Peterson, C.; Priest, G.; Venturato, A.; Weber, J.; Wong, F.; Yalciner, A.

2009-01-01

The first probabilistic tsunami flooding maps have been developed. The methodology, called probabilistic tsunami hazard assessment (PTHA), integrates tsunami inundation modeling with methods of probabilistic seismic hazard assessment (PSHA). Application of the methodology to Seaside, Oregon, has yielded estimates of the spatial distribution of 100- and 500-year maximum tsunami amplitudes, i.e., amplitudes with 1% and 0.2% annual probability of exceedance. The 100-year tsunami is generated most frequently by far-field sources in the Alaska-Aleutian Subduction Zone and is characterized by maximum amplitudes that do not exceed 4 m, with an inland extent of less than 500 m. In contrast, the 500-year tsunami is dominated by local sources in the Cascadia Subduction Zone and is characterized by maximum amplitudes in excess of 10 m and an inland extent of more than 1 km. The primary sources of uncertainty in these results include those associated with interevent time estimates, modeling of background sea level, and accounting for temporal changes in bathymetry and topography. Nonetheless, PTHA represents an important contribution to tsunami hazard assessment techniques; viewed in the broader context of risk analysis, PTHA provides a method for quantifying estimates of the likelihood and severity of the tsunami hazard, which can then be combined with vulnerability and exposure to yield estimates of tsunami risk. Copyright 2009 by the American Geophysical Union.

Are there Benefits to Combining Regional Probabalistic Survey and Historic Targeted Environmental Monitoring Data to Improve Our Understanding of Overall Regional Estuary Environmental Status?

NASA Astrophysics Data System (ADS)

Dasher, D. H.; Lomax, T. J.; Bethe, A.; Jewett, S.; Hoberg, M.

2016-02-01

A regional probabilistic survey of 20 randomly selected stations, where water and sediments were sampled, was conducted over an area of Simpson Lagoon and Gwydyr Bay in the Beaufort Sea adjacent Prudhoe Bay, Alaska, in 2014. Sampling parameters included water column for temperature, salinity, dissolved oxygen, chlorophyll a, nutrients and sediments for macroinvertebrates, chemistry, i.e., trace metals and hydrocarbons, and grain size. The 2014 probabilistic survey design allows for inferences to be made of environmental status, for instance the spatial or aerial distribution of sediment trace metals within the design area sampled. Historically, since the 1970's a number of monitoring studies have been conducted in this estuary area using a targeted rather than regional probabilistic design. Targeted non-random designs were utilized to assess specific points of interest and cannot be used to make inferences to distributions of environmental parameters. Due to differences in the environmental monitoring objectives between probabilistic and targeted designs there has been limited assessment see if benefits exist to combining the two approaches. This study evaluates if a combined approach using the 2014 probabilistic survey sediment trace metal and macroinvertebrate results and historical targeted monitoring data can provide a new perspective on better understanding the environmental status of these estuaries.

Principles for identification of High Potency Category Chemicals for which the Dermal Sensitisation Threshold (DST) approach should not be applied.

PubMed

Roberts, David W; Api, Anne Marie; Safford, Robert J; Lalko, Jon F

2015-08-01

An essential step in ensuring the toxicological safety of chemicals used in consumer products is the evaluation of their skin sensitising potential. The sensitising potency, coupled with information on exposure levels, can be used in a Quantitative Risk Assessment (QRA) to determine an acceptable level of a given chemical in a given product. Where consumer skin exposure is low, a risk assessment can be conducted using the Dermal Sensitisation Threshold (DST) approach, avoiding the need to determine potency experimentally. Since skin sensitisation involves chemical reaction with skin proteins, the first step in the DST approach is to assess, on the basis of the chemical structure, whether the chemical is expected to be reactive or not. Our accompanying publication describes the probabilistic derivation of a DST of 64 μg/cm(2) for chemicals assessed as reactive. This would protect against 95% of chemicals assessed as reactive, but the remaining 5% would include chemicals with very high potency. Here we discuss the chemical properties and structural features of high potency sensitisers, and derive an approach whereby they can be identified and consequently excluded from application of the DST. Copyright © 2015 Elsevier Inc. All rights reserved.

Comparative Probabilistic Assessment of Occupational Pesticide Exposures Based on Regulatory Assessments

PubMed Central

Pouzou, Jane G.; Cullen, Alison C.; Yost, Michael G.; Kissel, John C.; Fenske, Richard A.

2018-01-01

Implementation of probabilistic analyses in exposure assessment can provide valuable insight into the risks of those at the extremes of population distributions, including more vulnerable or sensitive subgroups. Incorporation of these analyses into current regulatory methods for occupational pesticide exposure is enabled by the exposure data sets and associated data currently used in the risk assessment approach of the Environmental Protection Agency (EPA). Monte Carlo simulations were performed on exposure measurements from the Agricultural Handler Exposure Database and the Pesticide Handler Exposure Database along with data from the Exposure Factors Handbook and other sources to calculate exposure rates for three different neurotoxic compounds (azinphos methyl, acetamiprid, emamectin benzoate) across four pesticide-handling scenarios. Probabilistic estimates of doses were compared with the no observable effect levels used in the EPA occupational risk assessments. Some percentage of workers were predicted to exceed the level of concern for all three compounds: 54% for azinphos methyl, 5% for acetamiprid, and 20% for emamectin benzoate. This finding has implications for pesticide risk assessment and offers an alternative procedure that may be more protective of those at the extremes of exposure than the current approach. PMID:29105804

Comparative Probabilistic Assessment of Occupational Pesticide Exposures Based on Regulatory Assessments.

PubMed

Pouzou, Jane G; Cullen, Alison C; Yost, Michael G; Kissel, John C; Fenske, Richard A

2017-11-06

Implementation of probabilistic analyses in exposure assessment can provide valuable insight into the risks of those at the extremes of population distributions, including more vulnerable or sensitive subgroups. Incorporation of these analyses into current regulatory methods for occupational pesticide exposure is enabled by the exposure data sets and associated data currently used in the risk assessment approach of the Environmental Protection Agency (EPA). Monte Carlo simulations were performed on exposure measurements from the Agricultural Handler Exposure Database and the Pesticide Handler Exposure Database along with data from the Exposure Factors Handbook and other sources to calculate exposure rates for three different neurotoxic compounds (azinphos methyl, acetamiprid, emamectin benzoate) across four pesticide-handling scenarios. Probabilistic estimates of doses were compared with the no observable effect levels used in the EPA occupational risk assessments. Some percentage of workers were predicted to exceed the level of concern for all three compounds: 54% for azinphos methyl, 5% for acetamiprid, and 20% for emamectin benzoate. This finding has implications for pesticide risk assessment and offers an alternative procedure that may be more protective of those at the extremes of exposure than the current approach. © 2017 Society for Risk Analysis.

Risk assessment for construction projects of transport infrastructure objects

NASA Astrophysics Data System (ADS)

Titarenko, Boris

2017-10-01

The paper analyzes and compares different methods of risk assessment for construction projects of transport objects. The management of such type of projects demands application of special probabilistic methods due to large level of uncertainty of their implementation. Risk management in the projects requires the use of probabilistic and statistical methods. The aim of the work is to develop a methodology for using traditional methods in combination with robust methods that allow obtaining reliable risk assessments in projects. The robust approach is based on the principle of maximum likelihood and in assessing the risk allows the researcher to obtain reliable results in situations of great uncertainty. The application of robust procedures allows to carry out a quantitative assessment of the main risk indicators of projects when solving the tasks of managing innovation-investment projects. Calculation of damage from the onset of a risky event is possible by any competent specialist. And an assessment of the probability of occurrence of a risky event requires the involvement of special probabilistic methods based on the proposed robust approaches. Practice shows the effectiveness and reliability of results. The methodology developed in the article can be used to create information technologies and their application in automated control systems for complex projects.

Probabilistic Risk Assessment Procedures Guide for NASA Managers and Practitioners (Second Edition)

NASA Technical Reports Server (NTRS)

Stamatelatos,Michael; Dezfuli, Homayoon; Apostolakis, George; Everline, Chester; Guarro, Sergio; Mathias, Donovan; Mosleh, Ali; Paulos, Todd; Riha, David; Smith, Curtis;

Assessing performance and validating finite element simulations using probabilistic knowledge

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

Dolin, Ronald M.; Rodriguez, E. A.

Two probabilistic approaches for assessing performance are presented. The first approach assesses probability of failure by simultaneously modeling all likely events. The probability each event causes failure along with the event's likelihood of occurrence contribute to the overall probability of failure. The second assessment method is based on stochastic sampling using an influence diagram. Latin-hypercube sampling is used to stochastically assess events. The overall probability of failure is taken as the maximum probability of failure of all the events. The Likelihood of Occurrence simulation suggests failure does not occur while the Stochastic Sampling approach predicts failure. The Likelihood of Occurrencemore » results are used to validate finite element predictions.« less

Solving probability reasoning based on DNA strand displacement and probability modules.

PubMed

Zhang, Qiang; Wang, Xiaobiao; Wang, Xiaojun; Zhou, Changjun

2017-12-01

In computation biology, DNA strand displacement technology is used to simulate the computation process and has shown strong computing ability. Most researchers use it to solve logic problems, but it is only rarely used in probabilistic reasoning. To process probabilistic reasoning, a conditional probability derivation model and total probability model based on DNA strand displacement were established in this paper. The models were assessed through the game "read your mind." It has been shown to enable the application of probabilistic reasoning in genetic diagnosis. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

Preliminary risks associated with postulated tritium release from production reactor operation

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

O'Kula, K.R.; Horton, W.H.

1988-01-01

The Probabilistic Risk Assessment (PRA) of Savannah River Plant (SRP) reactor operation is assessing the off-site risk due to tritium releases during postulated full or partial loss of heavy water moderator accidents. Other sources of tritium in the reactor are less likely to contribute to off-site risk in non-fuel melting accident scenarios. Preliminary determination of the frequency of average partial moderator loss (including incidents with leaks as small as .5 kg) yields an estimate of /approximately/1 per reactor year. The full moderator loss frequency is conservatively chosen as 5 /times/ 10/sup /minus/3/ per reactor year. Conditional consequences, determined with amore » version of the MACCS code modified to handle tritium, are found to be insignificant. The 95th percentile individual cancer risk is 4 /times/ 10/sup /minus/8/ per reactor year within 16 km of the release point. The full moderator loss accident contributes about 75% of the evaluated risks. 13 refs., 4 figs., 5 tabs.« less

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.

A Probabilistic Assessment of Failure for Air Force Building Systems

DTIC Science & Technology

2015-03-26

Rain Water Drainage System 1.000 0.225 0.085 0.424 0.800 0.968 0.998 4.449 D209001 Special Piping Systems 0.436 0.088 0.289 0.881 0.998 1.000 1.000...Rain Water Drainage 0.522 D2090 Other Plumbing Systems 0.303 D 30 H V A C D3010 Energy Supply 0.316 D3020 Heat Generating Systems 0.636 D3030...A PROBABILISTIC ASSESSMENT OF FAILURE FOR AIR FORCE BUILDING SYSTEMS THESIS Stephanie L

Probabilistic performance assessment of complex energy process systems - The case of a self-sustained sanitation system.

PubMed

Kolios, Athanasios; Jiang, Ying; Somorin, Tosin; Sowale, Ayodeji; Anastasopoulou, Aikaterini; Anthony, Edward J; Fidalgo, Beatriz; Parker, Alison; McAdam, Ewan; Williams, Leon; Collins, Matt; Tyrrel, Sean

2018-05-01

A probabilistic modelling approach was developed and applied to investigate the energy and environmental performance of an innovative sanitation system, the "Nano-membrane Toilet" (NMT). The system treats human excreta via an advanced energy and water recovery island with the aim of addressing current and future sanitation demands. Due to the complex design and inherent characteristics of the system's input material, there are a number of stochastic variables which may significantly affect the system's performance. The non-intrusive probabilistic approach adopted in this study combines a finite number of deterministic thermodynamic process simulations with an artificial neural network (ANN) approximation model and Monte Carlo simulations (MCS) to assess the effect of system uncertainties on the predicted performance of the NMT system. The joint probability distributions of the process performance indicators suggest a Stirling Engine (SE) power output in the range of 61.5-73 W with a high confidence interval (CI) of 95%. In addition, there is high probability (with 95% CI) that the NMT system can achieve positive net power output between 15.8 and 35 W. A sensitivity study reveals the system power performance is mostly affected by SE heater temperature. Investigation into the environmental performance of the NMT design, including water recovery and CO 2 /NO x emissions, suggests significant environmental benefits compared to conventional systems. Results of the probabilistic analysis can better inform future improvements on the system design and operational strategy and this probabilistic assessment framework can also be applied to similar complex engineering systems.

Water body and riparian buffer strip characteristics in a vineyard area to support aquatic pesticide exposure assessment.

PubMed

Ohliger, Renja; Schulz, Ralf

2010-10-15

The implementation of a geodata-based probabilistic pesticide exposure assessment for surface waters in Germany offers the opportunity to base the exposure estimation on more differentiated assumptions including detailed landscape characteristics. Since these characteristics can only be estimated using field surveys, water body width and depth, hydrology, riparian buffer strip width, ground vegetation cover, existence of concentrated flow paths, and riparian vegetation were characterised at 104 water body segments in the vineyard region Palatinate (south-west Germany). Water body segments classified as permanent (n=43) had median values of water body width and depth of 0.9m and 0.06m, respectively, and the determined median width:depth ratio was 15. Thus, the deterministic water body model (width=1m; depth=0.3m) assumed in regulatory exposure assessment seems unsuitable for small water bodies in the study area. Only 25% of investigated buffer strips had a dense vegetation cover (>70%) and allow a laminar sheet flow as required to include them as an effective pesticide runoff reduction landscape characteristic. At 77 buffer strips, bordering field paths and erosion rills leading into the water body were present, concentrating pesticide runoff and consequently decreasing buffer strip efficiency. The vegetation type shrubbery (height>1.5m) was present at 57 (29%) investigated riparian buffer strips. According to their median optical vegetation density of 75%, shrubberies may provide a spray drift reduction of 72±29%. Implementing detailed knowledge in an overall assessment revealed that exposure via drift might be 2.4 and via runoff up to 1.6 fold higher than assumed by the deterministic approach. Furthermore, considering vegetated buffer strips only by their width leads to an underestimation of exposure by a factor of as much as four. Our data highlight that the deterministic model assumptions neither represent worst-case nor median values and therefore cannot simply be adopted in a probabilistic approach. Copyright © 2010 Elsevier B.V. All rights reserved.

Life Span Differences in Electrophysiological Correlates of Monitoring Gains and Losses during Probabilistic Reinforcement Learning

ERIC Educational Resources Information Center

Hammerer, Dorothea; Li, Shu-Chen; Muller, Viktor; Lindenberger, Ulman

2011-01-01

By recording the feedback-related negativity (FRN) in response to gains and losses, we investigated the contribution of outcome monitoring mechanisms to age-associated differences in probabilistic reinforcement learning. Specifically, we assessed the difference of the monitoring reactions to gains and losses to investigate the monitoring of…

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.

Development of optimization-based probabilistic earthquake scenarios for the city of Tehran

NASA Astrophysics Data System (ADS)

Zolfaghari, M. R.; Peyghaleh, E.

2016-01-01

This paper presents the methodology and practical example for the application of optimization process to select earthquake scenarios which best represent probabilistic earthquake hazard in a given region. The method is based on simulation of a large dataset of potential earthquakes, representing the long-term seismotectonic characteristics in a given region. The simulation process uses Monte-Carlo simulation and regional seismogenic source parameters to generate a synthetic earthquake catalogue consisting of a large number of earthquakes, each characterized with magnitude, location, focal depth and fault characteristics. Such catalogue provides full distributions of events in time, space and size; however, demands large computation power when is used for risk assessment, particularly when other sources of uncertainties are involved in the process. To reduce the number of selected earthquake scenarios, a mixed-integer linear program formulation is developed in this study. This approach results in reduced set of optimization-based probabilistic earthquake scenario, while maintaining shape of hazard curves and full probabilistic picture by minimizing the error between hazard curves driven by full and reduced sets of synthetic earthquake scenarios. To test the model, the regional seismotectonic and seismogenic characteristics of northern Iran are used to simulate a set of 10,000-year worth of events consisting of some 84,000 earthquakes. The optimization model is then performed multiple times with various input data, taking into account probabilistic seismic hazard for Tehran city as the main constrains. The sensitivity of the selected scenarios to the user-specified site/return period error-weight is also assessed. The methodology could enhance run time process for full probabilistic earthquake studies like seismic hazard and risk assessment. The reduced set is the representative of the contributions of all possible earthquakes; however, it requires far less computation power. The authors have used this approach for risk assessment towards identification of effectiveness-profitability of risk mitigation measures, using optimization model for resource allocation. Based on the error-computation trade-off, 62-earthquake scenarios are chosen to be used for this purpose.

A quantitative model of optimal data selection in Wason's selection task.

PubMed

Hattori, Masasi

2002-10-01

The optimal data selection model proposed by Oaksford and Chater (1994) successfully formalized Wason's selection task (Wason, 1966). The model, however, involved some questionable assumptions and was also not sufficient as a model of the task because it could not provide quantitative predictions of the card selection frequencies. In this paper, the model was revised to provide quantitative fits to the data. The model can predict the selection frequencies of cards based on a selection tendency function (STF), or conversely, it enables the estimation of subjective probabilities from data. Past experimental data were first re-analysed based on the model. In Experiment 1, the superiority of the revised model was shown. However, when the relationship between antecedent and consequent was forced to deviate from the biconditional form, the model was not supported. In Experiment 2, it was shown that sufficient emphasis on probabilistic information can affect participants' performance. A detailed experimental method to sort participants by probabilistic strategies was introduced. Here, the model was supported by a subgroup of participants who used the probabilistic strategy. Finally, the results were discussed from the viewpoint of adaptive rationality.

New ShakeMaps for Georgia Resulting from Collaboration with EMME

NASA Astrophysics Data System (ADS)

Kvavadze, N.; Tsereteli, N. S.; Varazanashvili, O.; Alania, V.

2015-12-01

Correct assessment of probabilistic seismic hazard and risks maps are first step for advance planning and action to reduce seismic risk. Seismic hazard maps for Georgia were calculated based on modern approach that was developed in the frame of EMME (Earthquake Modl for Middle east region) project. EMME was one of GEM's successful endeavors at regional level. With EMME and GEM assistance, regional models were analyzed to identify the information and additional work needed for the preparation national hazard models. Probabilistic seismic hazard map (PSH) provides the critical bases for improved building code and construction. The most serious deficiency in PSH assessment for the territory of Georgia is the lack of high-quality ground motion data. Due to this an initial hybrid empirical ground motion model is developed for PGA and SA at selected periods. An application of these coefficients for ground motion models have been used in probabilistic seismic hazard assessment. Obtained results of seismic hazard maps show evidence that there were gaps in seismic hazard assessment and the present normative seismic hazard map needed a careful recalculation.

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.

Estimating the economic impact of seismic activity in Kyrgyzstan

NASA Astrophysics Data System (ADS)

Pittore, Massimiliano; Sousa, Luis; Grant, Damian; Fleming, Kevin; Parolai, Stefano; Free, Matthew; Moldobekov, Bolot; Takeuchi, Ko

2017-04-01

Estimating the short and long-term economical impact of large-scale damaging events such as earthquakes, tsunamis or tropical storms is an important component of risk assessment, whose outcomes are routinely used to improve risk awareness, optimize investments in prevention and mitigation actions, as well as to customize insurance and reinsurance rates to specific geographical regions or single countries. Such estimations can be carried out by modeling the whole causal process, from hazard assessment to the estimation of loss for specific categories of assets. This approach allows a precise description of the various physical mechanisms contributing to direct seismic losses. However, it should reflect the underlying epistemic and random uncertainties in all involved components in a meaningful way. Within a project sponsored by the World Bank, a seismic risk study for the Kyrgyz Republic has been conducted, focusing on the assessment of social and economical impacts assessed in terms of direct losses of the residential and public building stocks. Probabilistic estimates based on stochastic event catalogs have been computed and integrated with the simulation of specific earthquake scenarios. Although very few relevant data are available in the region on the economic consequences of past damaging events, the proposed approach sets a benchmark for decision makers and policy holders to better understand the short and long term consequences of earthquakes in the region. The presented results confirm the high level of seismic risk of the Kyrgyz Republic territory, outlining the most affected regions; thus advocating for significant Disaster Risk Reduction (DRR) measures to be implemented by local decision- and policy-makers.

A probabilistic assessment of health risks associated with short-term exposure to tropospheric ozone

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

Whitfield, R.G; Biller, W.F.; Jusko, M.J.

1996-06-01

The work described in this report is part of a larger risk assessment sponsored by the U.S. Environmental Protection Agency. Earlier efforts developed exposure-response relationships for acute health effects among populations engaged in heavy exertion. Those efforts also developed a probabilistic national ambient air quality standards exposure model and a general methodology for integrating probabilistic exposure-response relation- ships and exposure estimates to calculate overall risk results. Recently published data make it possible to model additional health endpoints (for exposure at moderate exertion), including hospital admissions. New air quality and exposure estimates for alternative national ambient air quality standards for ozonemore » are combined with exposure-response models to produce the risk results for hospital admissions and acute health effects. Sample results explain the methodology and introduce risk output formats.« less

Probabilistic failure assessment with application to solid rocket motors

NASA Technical Reports Server (NTRS)

Jan, Darrell L.; Davidson, Barry D.; Moore, Nicholas R.

1990-01-01

A quantitative methodology is being developed for assessment of risk of failure of solid rocket motors. This probabilistic methodology employs best available engineering models and available information in a stochastic framework. The framework accounts for incomplete knowledge of governing parameters, intrinsic variability, and failure model specification error. Earlier case studies have been conducted on several failure modes of the Space Shuttle Main Engine. Work in progress on application of this probabilistic approach to large solid rocket boosters such as the Advanced Solid Rocket Motor for the Space Shuttle is described. Failure due to debonding has been selected as the first case study for large solid rocket motors (SRMs) since it accounts for a significant number of historical SRM failures. Impact of incomplete knowledge of governing parameters and failure model specification errors is expected to be important.

Medium Range Flood Forecasting for Agriculture Damage Reduction

NASA Astrophysics Data System (ADS)

Fakhruddin, S. H. M.

2014-12-01

Early warning is a key element for disaster risk reduction. In recent decades, major advancements have been made in medium range and seasonal flood forecasting. This progress provides a great opportunity to reduce agriculture damage and improve advisories for early action and planning for flood hazards. This approach can facilitate proactive rather than reactive management of the adverse consequences of floods. In the agricultural sector, for instance, farmers can take a diversity of options such as changing cropping patterns, applying fertilizer, irrigating and changing planting timing. An experimental medium range (1-10 day) flood forecasting model has been developed for Bangladesh and Thailand. It provides 51 sets of discharge ensemble forecasts of 1-10 days with significant persistence and high certainty. This type of forecast could assist farmers and other stakeholders for differential preparedness activities. These ensembles probabilistic flood forecasts have been customized based on user-needs for community-level application focused on agriculture system. The vulnerabilities of agriculture system were calculated based on exposure, sensitivity and adaptive capacity. Indicators for risk and vulnerability assessment were conducted through community consultations. The forecast lead time requirement, user-needs, impacts and management options for crops were identified through focus group discussions, informal interviews and community surveys. This paper illustrates potential applications of such ensembles for probabilistic medium range flood forecasts in a way that is not commonly practiced globally today.

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.

Transactional problem content in cost discounting: parallel effects for probability and delay.

PubMed

Jones, Stephen; Oaksford, Mike

2011-05-01

Four experiments investigated the effects of transactional content on temporal and probabilistic discounting of costs. Kusev, van Schaik, Ayton, Dent, and Chater (2009) have shown that content other than gambles can alter decision-making behavior even when associated value and probabilities are held constant. Transactions were hypothesized to lead to similar effects because the cost to a purchaser always has a linked gain, the purchased commodity. Gain amount has opposite effects on delay and probabilistic discounting (e.g., Benzion, Rapoport, & Yagil, 1989; Green, Myerson, & Ostaszewski, 1999), a finding that is not consistent with descriptive decision theory (Kahneman & Tversky, 1979; Loewenstein & Prelec, 1992). However, little or no effect on discounting has been observed for losses or costs. Experiment 1, using transactions, showed parallel effects for temporal and probabilistic discounting: Smaller amounts were discounted more than large amounts. As the cost rises, people value the commodity more, and they consequently discount less. Experiment 2 ruled out a possible methodological cause for this effect. Experiment 3 replicated Experiment 1. Experiment 4, using gambles, showed no effect for temporal discounting, because of the absence of the linked gain, but the same effect for probabilistic discounting, because prospects implicitly introduce a linked gain (Green et al., 1999; Prelec & Loewenstein, 1991). As found by Kusev et al. (2009), these findings are not consistent with decision theory and suggest closer attention should be paid to the effects of content on decision making.

Chapter 8: US geological survey Circum-Arctic Resource Appraisal (CARA): Introduction and summary of organization and methods

USGS Publications Warehouse

Charpentier, R.R.; Gautier, D.L.

2011-01-01

The USGS has assessed undiscovered petroleum resources in the Arctic through geological mapping, basin analysis and quantitative assessment. The new map compilation provided the base from which geologists subdivided the Arctic for burial history modelling and quantitative assessment. The CARA was a probabilistic, geologically based study that used existing USGS methodology, modified somewhat for the circumstances of the Arctic. The assessment relied heavily on analogue modelling, with numerical input as lognormal distributions of sizes and numbers of undiscovered accumulations. Probabilistic results for individual assessment units were statistically aggregated taking geological dependencies into account. Fourteen papers in this Geological Society volume present summaries of various aspects of the CARA. ?? 2011 The Geological Society of London.

Asteroid-Generated Tsunami and Impact Risk

NASA Astrophysics Data System (ADS)

Boslough, M.; Aftosmis, M.; Berger, M. J.; Ezzedine, S. M.; Gisler, G.; Jennings, B.; LeVeque, R. J.; Mathias, D.; McCoy, C.; Robertson, D.; Titov, V. V.; Wheeler, L.

2016-12-01

The justification for planetary defense comes from a cost/benefit analysis, which includes risk assessment. The contribution from ocean impacts and airbursts is difficult to quantify and represents a significant uncertainty in our assessment of the overall risk. Our group is currently working toward improved understanding of impact scenarios that can generate dangerous tsunami. The importance of asteroid-generated tsunami research has increased because a new Science Definition Team, at the behest of NASA's Planetary Defense Coordinating Office, is now updating the results of a 2003 study on which our current planetary defense policy is based Our group was formed to address this question on many fronts, including asteroid entry modeling, tsunami generation and propagation simulations, modeling of coastal run-ups, inundation, and consequences, infrastructure damage estimates, and physics-based probabilistic impact risk assessment. We also organized the Second International Workshop on Asteroid Threat Assessment, focused on asteroid-generated tsunami and associated risk (Aug. 23-24, 2016). We will summarize our progress and present the highlights of our workshop, emphasizing its relevance to earth and planetary science. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy under Contract DE-AC04-94AL85000.

What is the Value Added to Adaptation Planning by Probabilistic Projections of Climate Change?

NASA Astrophysics Data System (ADS)

Wilby, R. L.

2008-12-01

Probabilistic projections of climate change offer new sources of risk information to support regional impacts assessment and adaptation options appraisal. However, questions continue to surround how best to apply these scenarios in a practical context, and whether the added complexity and computational burden leads to more robust decision-making. This paper provides an overview of recent efforts in the UK to 'bench-test' frameworks for employing probabilistic projections ahead of the release of the next generation, UKCIP08 projections (in November 2008). This is involving close collaboration between government agencies, research and stakeholder communities. Three examples will be cited to illustrate how probabilistic projections are already informing decisions about future flood risk management in London, water resource planning in trial river basins, and assessments of risks from rising water temperatures to Atlantic salmon stocks in southern England. When compared with conventional deterministic scenarios, ensemble projections allow exploration of a wider range of management options and highlight timescales for implementing adaptation measures. Users of probabilistic scenarios must keep in mind that other uncertainties (e.g., due to impacts model structure and parameterisation) should be handled in an equally rigorous way to those arising from climate models and emission scenarios. Finally, it is noted that a commitment to long-term monitoring is also critical for tracking environmental change, testing model projections, and for evaluating the success (or not) of any scenario-led interventions.

Effect of Examinee Certainty on Probabilistic Test Scores and a Comparison of Scoring Methods for Probabilistic Responses.

DTIC Science & Technology

1983-07-01

be a useful tool for assessing kowledge , but there are several problems with this item format. These problems include the possibility of an examinee...1959. -Kane, M. T., & Moloney, J. M. The effect of SSM grading on reliability when residual items have no discriminating power . Paper presented at

Decision Support System For Management Of Low-Level Radioactive Waste Disposal At The Nevada Test Site

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

Shott, G.; Yucel, V.; Desotell, L.

2006-07-01

The long-term safety of U.S. Department of Energy (DOE) low-level radioactive disposal facilities is assessed by conducting a performance assessment -- a systematic analysis that compares estimated risks to the public and the environment with performance objectives contained in DOE Manual 435.1-1, Radioactive Waste Management Manual. Before site operations, facilities design features such as final inventory, waste form characteristics, and closure cover design may be uncertain. Site operators need a modeling tool that can be used throughout the operational life of the disposal site to guide decisions regarding the acceptance of problematic waste streams, new disposal cell design, environmental monitoringmore » program design, and final site closure. In response to these needs the National Nuclear Security Administration Nevada Site Office (NNSA/NSO) has developed a decision support system for the Area 5 Radioactive Waste Management Site in Frenchman Flat on the Nevada Test Site. The core of the system is a probabilistic inventory and performance assessment model implemented in the GoldSim{sup R} simulation platform. The modeling platform supports multiple graphic capabilities that allow clear documentation of the model data sources, conceptual model, mathematical implementation, and results. The combined models have the capability to estimate disposal site inventory, contaminant concentrations in environmental media, and radiological doses to members of the public engaged in various activities at multiple locations. The model allows rapid assessment and documentation of the consequences of waste management decisions using the most current site characterization information, radionuclide inventory, and conceptual model. The model is routinely used to provide annual updates of site performance, evaluate the consequences of disposal of new waste streams, develop waste concentration limits, optimize the design of new disposal cells, and assess the adequacy of environmental monitoring programs. (authors)« less

A comparison of geospatially modeled fire behavior and fire management utility of three data sources in the southeastern United States

Treesearch

LaWen T. Hollingsworth; Laurie L. Kurth; Bernard R. Parresol; Roger D. Ottmar; Susan J. Prichard

2012-01-01

Landscape-scale fire behavior analyses are important to inform decisions on resource management projects that meet land management objectives and protect values from adverse consequences of fire. Deterministic and probabilistic geospatial fire behavior analyses are conducted with various modeling systems including FARSITE, FlamMap, FSPro, and Large Fire Simulation...

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.

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.

Probabilistic safety assessment of the design of a tall buildings under the extreme load

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

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

2016-06-08

The paper describes some experiences from the deterministic and probabilistic analysis of the safety of the tall building structure. There are presented the methods and requirements of Eurocode EN 1990, standard ISO 2394 and JCSS. The uncertainties of the model and resistance of the structures are considered using the simulation methods. The MONTE CARLO, LHS and RSM probabilistic methods are compared with the deterministic results. On the example of the probability analysis of the safety of the tall buildings is demonstrated the effectiveness of the probability design of structures using Finite Element Methods.

Probabilistic safety assessment of the design of a tall buildings under the extreme load

NASA Astrophysics Data System (ADS)

Králik, Juraj

2016-06-01

The paper describes some experiences from the deterministic and probabilistic analysis of the safety of the tall building structure. There are presented the methods and requirements of Eurocode EN 1990, standard ISO 2394 and JCSS. The uncertainties of the model and resistance of the structures are considered using the simulation methods. The MONTE CARLO, LHS and RSM probabilistic methods are compared with the deterministic results. On the example of the probability analysis of the safety of the tall buildings is demonstrated the effectiveness of the probability design of structures using Finite Element Methods.

Methodological framework for the probabilistic risk assessment of multi-hazards at a municipal scale: a case study in the Fella river valley, Eastern Italian Alps

NASA Astrophysics Data System (ADS)

Hussin, Haydar; van Westen, Cees; Reichenbach, Paola

2013-04-01

Local and regional authorities in mountainous areas that deal with hydro-meteorological hazards like landslides and floods try to set aside budgets for emergencies and risk mitigation. However, future losses are often not calculated in a probabilistic manner when allocating budgets or determining how much risk is acceptable. The absence of probabilistic risk estimates can create a lack of preparedness for reconstruction and risk reduction costs and a deficiency in promoting risk mitigation and prevention in an effective way. The probabilistic risk of natural hazards at local scale is usually ignored all together due to the difficulty in acknowledging, processing and incorporating uncertainties in the estimation of losses (e.g. physical damage, fatalities and monetary loss). This study attempts to set up a working framework for a probabilistic risk assessment (PRA) of landslides and floods at a municipal scale using the Fella river valley (Eastern Italian Alps) as a multi-hazard case study area. The emphasis is on the evaluation and determination of the uncertainty in the estimation of losses from multi-hazards. To carry out this framework some steps are needed: (1) by using physically based stochastic landslide and flood models we aim to calculate the probability of the physical impact on individual elements at risk, (2) this is then combined with a statistical analysis of the vulnerability and monetary value of the elements at risk in order to include their uncertainty in the risk assessment, (3) finally the uncertainty from each risk component is propagated into the loss estimation. The combined effect of landslides and floods on the direct risk to communities in narrow alpine valleys is also one of important aspects that needs to be studied.

Adequacy assessment of composite generation and transmission systems incorporating wind energy conversion systems

NASA Astrophysics Data System (ADS)

Gao, Yi

The development and utilization of wind energy for satisfying electrical demand has received considerable attention in recent years due to its tremendous environmental, social and economic benefits, together with public support and government incentives. Electric power generation from wind energy behaves quite differently from that of conventional sources. The fundamentally different operating characteristics of wind energy facilities therefore affect power system reliability in a different manner than those of conventional systems. The reliability impact of such a highly variable energy source is an important aspect that must be assessed when the wind power penetration is significant. The focus of the research described in this thesis is on the utilization of state sampling Monte Carlo simulation in wind integrated bulk electric system reliability analysis and the application of these concepts in system planning and decision making. Load forecast uncertainty is an important factor in long range planning and system development. This thesis describes two approximate approaches developed to reduce the number of steps in a load duration curve which includes load forecast uncertainty, and to provide reasonably accurate generating and bulk system reliability index predictions. The developed approaches are illustrated by application to two composite test systems. A method of generating correlated random numbers with uniform distributions and a specified correlation coefficient in the state sampling method is proposed and used to conduct adequacy assessment in generating systems and in bulk electric systems containing correlated wind farms in this thesis. The studies described show that it is possible to use the state sampling Monte Carlo simulation technique to quantitatively assess the reliability implications associated with adding wind power to a composite generation and transmission system including the effects of multiple correlated wind sites. This is an important development as it permits correlated wind farms to be incorporated in large practical system studies without requiring excessive increases in computer solution time. The procedures described in this thesis for creating monthly and seasonal wind farm models should prove useful in situations where time period models are required to incorporate scheduled maintenance of generation and transmission facilities. There is growing interest in combining deterministic considerations with probabilistic assessment in order to evaluate the quantitative system risk and conduct bulk power system planning. A relatively new approach that incorporates deterministic and probabilistic considerations in a single risk assessment framework has been designated as the joint deterministic-probabilistic approach. The research work described in this thesis illustrates that the joint deterministic-probabilistic approach can be effectively used to integrate wind power in bulk electric system planning. The studies described in this thesis show that the application of the joint deterministic-probabilistic method provides more stringent results for a system with wind power than the traditional deterministic N-1 method because the joint deterministic-probabilistic technique is driven by the deterministic N-1 criterion with an added probabilistic perspective which recognizes the power output characteristics of a wind turbine generator.

A~probabilistic tsunami hazard assessment for Indonesia

NASA Astrophysics Data System (ADS)

Horspool, N.; Pranantyo, I.; Griffin, J.; Latief, H.; Natawidjaja, D. H.; Kongko, W.; Cipta, A.; Bustaman, B.; Anugrah, S. D.; Thio, H. K.

2014-05-01

Probabilistic hazard assessments are a fundamental tool for assessing the threats posed by hazards to communities and are important for underpinning evidence based decision making on risk mitigation activities. Indonesia has been the focus of intense tsunami risk mitigation efforts following the 2004 Indian Ocean Tsunami, but this has been largely concentrated on the Sunda Arc, with little attention to other tsunami prone areas of the country such as eastern Indonesia. We present the first nationally consistent Probabilistic Tsunami Hazard Assessment (PTHA) for Indonesia. This assessment produces time independent forecasts of tsunami hazard at the coast from tsunami generated by local, regional and distant earthquake sources. The methodology is based on the established monte-carlo approach to probabilistic seismic hazard assessment (PSHA) and has been adapted to tsunami. We account for sources of epistemic and aleatory uncertainty in the analysis through the use of logic trees and through sampling probability density functions. For short return periods (100 years) the highest tsunami hazard is the west coast of Sumatra, south coast of Java and the north coast of Papua. For longer return periods (500-2500 years), the tsunami hazard is highest along the Sunda Arc, reflecting larger maximum magnitudes along the Sunda Arc. The annual probability of experiencing a tsunami with a height at the coast of > 0.5 m is greater than 10% for Sumatra, Java, the Sunda Islands (Bali, Lombok, Flores, Sumba) and north Papua. The annual probability of experiencing a tsunami with a height of >3.0 m, which would cause significant inundation and fatalities, is 1-10% in Sumatra, Java, Bali, Lombok and north Papua, and 0.1-1% for north Sulawesi, Seram and Flores. The results of this national scale hazard assessment provide evidence for disaster managers to prioritise regions for risk mitigation activities and/or more detailed hazard or risk assessment.

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.

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.

[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.

Bayesian Networks Improve Causal Environmental Assessments for Evidence-Based Policy.

PubMed

Carriger, John F; Barron, Mace G; Newman, Michael C

2016-12-20

Rule-based weight of evidence approaches to ecological risk assessment may not account for uncertainties and generally lack probabilistic integration of lines of evidence. Bayesian networks allow causal inferences to be made from evidence by including causal knowledge about the problem, using this knowledge with probabilistic calculus to combine multiple lines of evidence, and minimizing biases in predicting or diagnosing causal relationships. Too often, sources of uncertainty in conventional weight of evidence approaches are ignored that can be accounted for with Bayesian networks. Specifying and propagating uncertainties improve the ability of models to incorporate strength of the evidence in the risk management phase of an assessment. Probabilistic inference from a Bayesian network allows evaluation of changes in uncertainty for variables from the evidence. The network structure and probabilistic framework of a Bayesian approach provide advantages over qualitative approaches in weight of evidence for capturing the impacts of multiple sources of quantifiable uncertainty on predictions of ecological risk. Bayesian networks can facilitate the development of evidence-based policy under conditions of uncertainty by incorporating analytical inaccuracies or the implications of imperfect information, structuring and communicating causal issues through qualitative directed graph formulations, and quantitatively comparing the causal power of multiple stressors on valued ecological resources. These aspects are demonstrated through hypothetical problem scenarios that explore some major benefits of using Bayesian networks for reasoning and making inferences in evidence-based policy.

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

What do we gain with Probabilistic Flood Loss Models?

NASA Astrophysics Data System (ADS)

Schroeter, K.; Kreibich, H.; Vogel, K.; Merz, B.; Lüdtke, S.

2015-12-01

The reliability of flood loss models is a prerequisite for their practical usefulness. Oftentimes, traditional uni-variate damage models as for instance depth-damage curves fail to reproduce the variability of observed flood damage. Innovative multi-variate probabilistic modelling approaches are promising to capture and quantify the uncertainty involved and thus to improve the basis for decision making. In this study we compare the predictive capability of two probabilistic modelling approaches, namely Bagging Decision Trees and Bayesian Networks and traditional stage damage functions which are cast in a probabilistic framework. For model evaluation we use empirical damage data which are available from computer aided telephone interviews that were respectively compiled after the floods in 2002, 2005, 2006 and 2013 in the Elbe and Danube catchments in Germany. We carry out a split sample test by sub-setting the damage records. One sub-set is used to derive the models and the remaining records are used to evaluate the predictive performance of the model. Further we stratify the sample according to catchments which allows studying model performance in a spatial transfer context. Flood damage estimation is carried out on the scale of the individual buildings in terms of relative damage. The predictive performance of the models is assessed in terms of systematic deviations (mean bias), precision (mean absolute error) as well as in terms of reliability which is represented by the proportion of the number of observations that fall within the 95-quantile and 5-quantile predictive interval. The reliability of the probabilistic predictions within validation runs decreases only slightly and achieves a very good coverage of observations within the predictive interval. Probabilistic models provide quantitative information about prediction uncertainty which is crucial to assess the reliability of model predictions and improves the usefulness of model results.

A meta-analytic review of two modes of learning and the description-experience gap.

PubMed

Wulff, Dirk U; Mergenthaler-Canseco, Max; Hertwig, Ralph

2018-02-01

People can learn about the probabilistic consequences of their actions in two ways: One is by consulting descriptions of an action's consequences and probabilities (e.g., reading up on a medication's side effects). The other is by personally experiencing the probabilistic consequences of an action (e.g., beta testing software). In principle, people taking each route can reach analogous states of knowledge and consequently make analogous decisions. In the last dozen years, however, research has demonstrated systematic discrepancies between description- and experienced-based choices. This description-experience gap has been attributed to factors including reliance on a small set of experience, the impact of recency, and different weighting of probability information in the two decision types. In this meta-analysis focusing on studies using the sampling paradigm of decisions from experience, we evaluated these and other determinants of the decision-experience gap by reference to more than 70,000 choices made by more than 6,000 participants. We found, first, a robust description-experience gap but also a key moderator, namely, problem structure. Second, the largest determinant of the gap was reliance on small samples and the associated sampling error: free to terminate search, individuals explored too little to experience all possible outcomes. Third, the gap persisted when sampling error was basically eliminated, suggesting other determinants. Fourth, the occurrence of recency was contingent on decision makers' autonomy to terminate search, consistent with the notion of optional stopping. Finally, we found indications of different probability weighting in decisions from experience versus decisions from description when the problem structure involved a risky and a safe option. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Probabilistic performance-assessment modeling of the mixed waste landfill at Sandia National Laboratories.

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

Peace, Gerald; Goering, Timothy James; Miller, Mark Laverne

2007-01-01

A probabilistic performance assessment has been conducted to evaluate the fate and transport of radionuclides (americium-241, cesium-137, cobalt-60, plutonium-238, plutonium-239, radium-226, radon-222, strontium-90, thorium-232, tritium, uranium-238), heavy metals (lead and cadmium), and volatile organic compounds (VOCs) at the Mixed Waste Landfill (MWL). Probabilistic analyses were performed to quantify uncertainties inherent in the system and models for a 1,000-year period, and sensitivity analyses were performed to identify parameters and processes that were most important to the simulated performance metrics. Comparisons between simulated results and measured values at the MWL were made to gain confidence in the models and perform calibrations whenmore » data were available. In addition, long-term monitoring requirements and triggers were recommended based on the results of the quantified uncertainty and sensitivity analyses.« less

A Control Variate Method for Probabilistic Performance Assessment. Improved Estimates for Mean Performance Quantities of Interest

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

MacKinnon, Robert J.; Kuhlman, Kristopher L

2016-05-01

We present a method of control variates for calculating improved estimates for mean performance quantities of interest, E(PQI) , computed from Monte Carlo probabilistic simulations. An example of a PQI is the concentration of a contaminant at a particular location in a problem domain computed from simulations of transport in porous media. To simplify the presentation, the method is described in the setting of a one- dimensional elliptical model problem involving a single uncertain parameter represented by a probability distribution. The approach can be easily implemented for more complex problems involving multiple uncertain parameters and in particular for application tomore » probabilistic performance assessment of deep geologic nuclear waste repository systems. Numerical results indicate the method can produce estimates of E(PQI)having superior accuracy on coarser meshes and reduce the required number of simulations needed to achieve an acceptable estimate.« less

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.

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.

The subjective value of probabilistic outcomes: Impact of reward magnitude on choice with uncertain rewards in rats.

PubMed

Zoratto, Francesca; Laviola, Giovanni; Adriani, Walter

2016-03-23

Interest is rising for animal modelling of Gambling disorder (GD), which is rapidly emerging as a mental health concern. In the present study, we assessed gambling proneness in male Wistar-Han rats using the "Probabilistic Delivery Task" (PDT). This operant protocol is based on choice between either certain, small amounts of food (SS) or larger amounts of food (LLL) delivered (or not) depending on a given (and progressively decreasing) probability. Here, we manipulated the ratio between large and small reward size to assess the impact of different magnitudes on rats' performance. Specifically, we drew a comparison between threefold (2 vs 6 pellets) and fivefold (1 vs 5 pellets) sizes. As a consequence, the "indifferent point" (IP, at which either choice is mathematically equivalent in terms of total foraging) was at 33% and 20% probability of delivery, respectively. Animals tested with the sharper contrast (i.e. fivefold ratio) exhibited sustained preference for LLL far beyond the IP, despite high uncertainty and low payoff, which rendered LLL a sub-optimal option. By contrast, animals facing a slighter contrast (i.e. threefold ratio) were increasingly disturbed by progressive rarefaction of rewards, as expressed by enhanced inadequate nose-poking: this was in accordance with their prompt shift in preference to SS, already shown around the IP. In conclusion, a five-folded LLL-to-SS ratio was not only more attractive, but also less frustrating than a three-folded one. Thus, a profile of gambling proneness in the PDT is more effectively induced by marked contrast between alternative options. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

A probabilistic assessment of waste water injection induced seismicity in central California

NASA Astrophysics Data System (ADS)

Goebel, T.; Hauksson, E.; Ampuero, J. P.; Aminzadeh, F.; Cappa, F.; Saleeby, J.

2014-12-01

The recent, large increase in seismic activity within the central and eastern U.S. may be connected to an increase in fluid injection activity since ~2001. Anomalous seismic sequences can easily be identified in regions with low background seismicity rates. Here, we analyze seismicity in plate boundary regions where tectonically-driven earthquake sequences are common, potentially masking injection-induced events. We show results from a comprehensive analysis of waste water disposal wells in Kern county, the largest oil-producing county in California. We focus on spatial-temporal correlations between seismic and injection activity and seismicity-density changes due to injection. We perform a probabilistic assessment of induced vs. tectonic earthquakes, which can be applied to different regions independent of background rates and may provide insights into the probability of inducing earthquakes as a function of injection parameters and local geological conditions. Our results show that most earthquakes are caused by tectonic forcing, however, waste water injection contributes to seismic activity in four different regions with several events above M4. The seismicity shows different migration characteristics relative to the injection sites, including linear and non-linear trends. The latter is indicative of diffusive processes which take advantage of reservoir properties and fault structures and can induce earthquakes at distances of up to 10 km. Our results suggest that injection-related triggering processes are complex, possibly involving creep, and delayed triggering. Pore-pressure diffusion may be more extensive in the presence of active faults and high-permeability damage zones thus altering the local seismic hazard in a non-linear fashion. As a consequence, generic "best-practices" for fluid injections like a maximum distance from the nearest active fault may not be sufficient to mitigate a potential seismic hazard increase.

Effects of sample survey design on the accuracy of classification tree models in species distribution models

Treesearch

Thomas C. Edwards; D. Richard Cutler; Niklaus E. Zimmermann; Linda Geiser; Gretchen G. Moisen

2006-01-01

We evaluated the effects of probabilistic (hereafter DESIGN) and non-probabilistic (PURPOSIVE) sample surveys on resultant classification tree models for predicting the presence of four lichen species in the Pacific Northwest, USA. Models derived from both survey forms were assessed using an independent data set (EVALUATION). Measures of accuracy as gauged by...

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

Effects of delay and probability combinations on discounting in humans

PubMed Central

Cox, David J.; Dallery, Jesse

2017-01-01

To determine discount rates, researchers typically adjust the amount of an immediate or certain option relative to a delayed or uncertain option. Because this adjusting amount method can be relatively time consuming, researchers have developed more efficient procedures. One such procedure is a 5-trial adjusting delay procedure, which measures the delay at which an amount of money loses half of its value (e.g., $1000 is valued at $500 with a 10-year delay to its receipt). Experiment 1 (n = 212) used 5-trial adjusting delay or probability tasks to measure delay discounting of losses, probabilistic gains, and probabilistic losses. Experiment 2 (n = 98) assessed combined probabilistic and delayed alternatives. In both experiments, we compared results from 5-trial adjusting delay or probability tasks to traditional adjusting amount procedures. Results suggest both procedures produced similar rates of probability and delay discounting in six out of seven comparisons. A magnitude effect consistent with previous research was observed for probabilistic gains and losses, but not for delayed losses. Results also suggest that delay and probability interact to determine the value of money. Five-trial methods may allow researchers to assess discounting more efficiently as well as study more complex choice scenarios. PMID:27498073

Bayesian networks improve causal environmental ...

EPA Pesticide Factsheets

Rule-based weight of evidence approaches to ecological risk assessment may not account for uncertainties and generally lack probabilistic integration of lines of evidence. Bayesian networks allow causal inferences to be made from evidence by including causal knowledge about the problem, using this knowledge with probabilistic calculus to combine multiple lines of evidence, and minimizing biases in predicting or diagnosing causal relationships. Too often, sources of uncertainty in conventional weight of evidence approaches are ignored that can be accounted for with Bayesian networks. Specifying and propagating uncertainties improve the ability of models to incorporate strength of the evidence in the risk management phase of an assessment. Probabilistic inference from a Bayesian network allows evaluation of changes in uncertainty for variables from the evidence. The network structure and probabilistic framework of a Bayesian approach provide advantages over qualitative approaches in weight of evidence for capturing the impacts of multiple sources of quantifiable uncertainty on predictions of ecological risk. Bayesian networks can facilitate the development of evidence-based policy under conditions of uncertainty by incorporating analytical inaccuracies or the implications of imperfect information, structuring and communicating causal issues through qualitative directed graph formulations, and quantitatively comparing the causal power of multiple stressors on value

Evaluation of a Stratified National Breast Screening Program in the United Kingdom: An Early Model-Based Cost-Effectiveness Analysis.

PubMed

Gray, Ewan; Donten, Anna; Karssemeijer, Nico; van Gils, Carla; Evans, D Gareth; Astley, Sue; Payne, Katherine

2017-09-01

To identify the incremental costs and consequences of stratified national breast screening programs (stratified NBSPs) and drivers of relative cost-effectiveness. A decision-analytic model (discrete event simulation) was conceptualized to represent four stratified NBSPs (risk 1, risk 2, masking [supplemental screening for women with higher breast density], and masking and risk 1) compared with the current UK NBSP and no screening. The model assumed a lifetime horizon, the health service perspective to identify costs (£, 2015), and measured consequences in quality-adjusted life-years (QALYs). Multiple data sources were used: systematic reviews of effectiveness and utility, published studies reporting costs, and cohort studies embedded in existing NBSPs. Model parameter uncertainty was assessed using probabilistic sensitivity analysis and one-way sensitivity analysis. The base-case analysis, supported by probabilistic sensitivity analysis, suggested that the risk stratified NBSPs (risk 1 and risk-2) were relatively cost-effective when compared with the current UK NBSP, with incremental cost-effectiveness ratios of £16,689 per QALY and £23,924 per QALY, respectively. Stratified NBSP including masking approaches (supplemental screening for women with higher breast density) was not a cost-effective alternative, with incremental cost-effectiveness ratios of £212,947 per QALY (masking) and £75,254 per QALY (risk 1 and masking). When compared with no screening, all stratified NBSPs could be considered cost-effective. Key drivers of cost-effectiveness were discount rate, natural history model parameters, mammographic sensitivity, and biopsy rates for recalled cases. A key assumption was that the risk model used in the stratification process was perfectly calibrated to the population. This early model-based cost-effectiveness analysis provides indicative evidence for decision makers to understand the key drivers of costs and QALYs for exemplar stratified NBSP. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Comparison of numerical weather prediction based deterministic and probabilistic wind resource assessment methods

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

Zhang, Jie; Draxl, Caroline; Hopson, Thomas

Numerical weather prediction (NWP) models have been widely used for wind resource assessment. Model runs with higher spatial resolution are generally more accurate, yet extremely computational expensive. An alternative approach is to use data generated by a low resolution NWP model, in conjunction with statistical methods. In order to analyze the accuracy and computational efficiency of different types of NWP-based wind resource assessment methods, this paper performs a comparison of three deterministic and probabilistic NWP-based wind resource assessment methodologies: (i) a coarse resolution (0.5 degrees x 0.67 degrees) global reanalysis data set, the Modern-Era Retrospective Analysis for Research and Applicationsmore » (MERRA); (ii) an analog ensemble methodology based on the MERRA, which provides both deterministic and probabilistic predictions; and (iii) a fine resolution (2-km) NWP data set, the Wind Integration National Dataset (WIND) Toolkit, based on the Weather Research and Forecasting model. Results show that: (i) as expected, the analog ensemble and WIND Toolkit perform significantly better than MERRA confirming their ability to downscale coarse estimates; (ii) the analog ensemble provides the best estimate of the multi-year wind distribution at seven of the nine sites, while the WIND Toolkit is the best at one site; (iii) the WIND Toolkit is more accurate in estimating the distribution of hourly wind speed differences, which characterizes the wind variability, at five of the available sites, with the analog ensemble being best at the remaining four locations; and (iv) the analog ensemble computational cost is negligible, whereas the WIND Toolkit requires large computational resources. Future efforts could focus on the combination of the analog ensemble with intermediate resolution (e.g., 10-15 km) NWP estimates, to considerably reduce the computational burden, while providing accurate deterministic estimates and reliable probabilistic assessments.« less

Rock Slide Risk Assessment: A Semi-Quantitative Approach

NASA Astrophysics Data System (ADS)

Duzgun, H. S. B.

2009-04-01

Rock slides can be better managed by systematic risk assessments. Any risk assessment methodology for rock slides involves identification of rock slide risk components, which are hazard, elements at risk and vulnerability. For a quantitative/semi-quantitative risk assessment for rock slides, a mathematical value the risk has to be computed and evaluated. The quantitative evaluation of risk for rock slides enables comparison of the computed risk with the risk of other natural and/or human-made hazards and providing better decision support and easier communication for the decision makers. A quantitative/semi-quantitative risk assessment procedure involves: Danger Identification, Hazard Assessment, Elements at Risk Identification, Vulnerability Assessment, Risk computation, Risk Evaluation. On the other hand, the steps of this procedure require adaptation of existing or development of new implementation methods depending on the type of landslide, data availability, investigation scale and nature of consequences. In study, a generic semi-quantitative risk assessment (SQRA) procedure for rock slides is proposed. The procedure has five consecutive stages: Data collection and analyses, hazard assessment, analyses of elements at risk and vulnerability and risk assessment. The implementation of the procedure for a single rock slide case is illustrated for a rock slope in Norway. Rock slides from mountain Ramnefjell to lake Loen are considered to be one of the major geohazards in Norway. Lake Loen is located in the inner part of Nordfjord in Western Norway. Ramnefjell Mountain is heavily jointed leading to formation of vertical rock slices with height between 400-450 m and width between 7-10 m. These slices threaten the settlements around Loen Valley and tourists visiting the fjord during summer season, as the released slides have potential of creating tsunami. In the past, several rock slides had been recorded from the Mountain Ramnefjell between 1905 and 1950. Among them, four of the slides caused formation of tsunami waves which washed up to 74 m above the lake level. Two of the slides resulted in many fatalities in the inner part of the Loen Valley as well as great damages. There are three predominant joint structures in Ramnefjell Mountain, which controls failure and the geometry of the slides. The first joint set is a foliation plane striking northeast-southwest and dipping 35˚ -40˚ to the east-southeast. The second and the third joint sets are almost perpendicular and parallel to the mountain side and scarp, respectively. These three joint sets form slices of rock columns with width ranging between 7-10 m and height of 400-450 m. It is stated that the joints in set II are opened between 1-2 m, which may bring about collection of water during heavy rainfall or snow melt causing the slices to be pressed out. It is estimated that water in the vertical joints both reduces the shear strength of sliding plane and causes reduction of normal stress on the sliding plane due to formation of uplift force. Hence rock slides in Ramnefjell mountain occur in plane failure mode. The quantitative evaluation of rock slide risk requires probabilistic analysis of rock slope stability and identification of consequences if the rock slide occurs. In this study failure probability of a rock slice is evaluated by first-order reliability method (FORM). Then in order to use the calculated probability of failure value (Pf) in risk analyses, it is required to associate this Pf with frequency based probabilities (i.ePf / year) since the computed failure probabilities is a measure of hazard and not a measure of risk unless they are associated with the consequences of the failure. This can be done by either considering the time dependent behavior of the basic variables in the probabilistic models or associating the computed Pf with frequency of the failures in the region. In this study, the frequency of previous rock slides in the previous century in Remnefjell is used for evaluation of frequency based probability to be used in risk assessment. The major consequence of a rock slide is generation of a tsunami in the lake Loen, causing inundation of residential areas around the lake. Risk is assessed by adapting damage probability matrix approach, which is originally developed for risk assessment for buildings in case of earthquake.

Consequences of biodiversity loss diverge from expectation due to post-extinction compensatory responses

NASA Astrophysics Data System (ADS)

Thomsen, Matthias S.; Garcia, Clement; Bolam, Stefan G.; Parker, Ruth; Godbold, Jasmin A.; Solan, Martin

2017-03-01

Consensus has been reached that global biodiversity loss impairs ecosystem functioning and the sustainability of services beneficial to humanity. However, the ecosystem consequences of extinction in natural communities are moderated by compensatory species dynamics, yet these processes are rarely accounted for in impact assessments and seldom considered in conservation programmes. Here, we use marine invertebrate communities to parameterise numerical models of sediment bioturbation - a key mediator of biogeochemical cycling - to determine whether post-extinction compensatory mechanisms alter biodiversity-ecosystem function relations following non-random extinctions. We find that compensatory dynamics lead to trajectories of sediment mixing that diverge from those without compensation, and that the form, magnitude and variance of each probabilistic distribution is highly influenced by the type of compensation and the functional composition of surviving species. Our findings indicate that the generalized biodiversity-function relation curve, as derived from multiple empirical investigations of random species loss, is unlikely to yield representative predictions for ecosystem properties in natural systems because the influence of post-extinction community dynamics are under-represented. Recognition of this problem is fundamental to management and conservation efforts, and will be necessary to ensure future plans and adaptation strategies minimize the adverse impacts of the biodiversity crisis.

Assessment of undiscovered sandstone copper deposits of the Kodar-Udokan area, Russia: Chapter M in Global mineral resource assessment

USGS Publications Warehouse

Zientek, Michael L.; Chechetkin, Vladimir S.; Parks, Heather L.; Box, Stephen E.; Briggs, Deborah A.; Cossette, Pamela M.; Dolgopolova, Alla; Hayes, Timothy S.; Seltmann, Reimar; Syusyura, Boris; Taylor, Cliff D.; Wintzer, Niki E.

2014-01-01

This probabilistic assessment indicates that a significant amount of undiscovered copper is associated with sediment-hosted stratabound copper deposits in the Kodar-Udokan Trough. In the assessment, a mean of 21 undiscovered deposits is estimated to occur within the Kodar-Udokan area. There are two known deposits in the area that contain drill-identified resources of 19.6 million metric tons of copper. Using Monte Carlo simulation, probabilistic estimates of the numbers of undiscovered sandstone copper deposits for these tracts were combined with tonnage and grade distributions of sandstone copper deposits to forecast an arithmetic mean of 20.6 million metric tons of undiscovered copper. Significant value can be expected from associated metals, particularly silver.

Using Probabilistic Methods in Water Scarcity Assessments: A First Step Towards a Water Scarcity Risk Assessment Framework

NASA Technical Reports Server (NTRS)

Veldkamp, Ted; Wada, Yoshihide; Aerts, Jeroen; Ward, Phillip

2016-01-01

Water scarcity -driven by climate change, climate variability, and socioeconomic developments- is recognized as one of the most important global risks, both in terms of likelihood and impact. Whilst a wide range of studies have assessed the role of long term climate change and socioeconomic trends on global water scarcity, the impact of variability is less well understood. Moreover, the interactions between different forcing mechanisms, and their combined effect on changes in water scarcity conditions, are often neglected. Therefore, we provide a first step towards a framework for global water scarcity risk assessments, applying probabilistic methods to estimate water scarcity risks for different return periods under current and future conditions while using multiple climate and socioeconomic scenarios.

Probabilistic TSUnami Hazard MAPS for the NEAM Region: The TSUMAPS-NEAM Project

NASA Astrophysics Data System (ADS)

Basili, Roberto; Babeyko, Andrey Y.; Hoechner, Andreas; Baptista, Maria Ana; Ben Abdallah, Samir; Canals, Miquel; El Mouraouah, Azelarab; Bonnevie Harbitz, Carl; Ibenbrahim, Aomar; Lastras, Galderic; Lorito, Stefano; Løvholt, Finn; Matias, Luis Manuel; Omira, Rachid; Papadopoulos, Gerassimos A.; Pekcan, Onur; Nmiri, Abdelwaheb; Selva, Jacopo; Yalciner, Ahmet C.; Thio, Hong K.

2017-04-01

As global awareness of tsunami hazard and risk grows, the North-East Atlantic, the Mediterranean, and connected Seas (NEAM) region still lacks a thorough probabilistic tsunami hazard assessment. The TSUMAPS-NEAM project aims to fill this gap in the NEAM region by 1) producing the first region-wide long-term homogenous Probabilistic Tsunami Hazard Assessment (PTHA) from earthquake sources, and by 2) triggering a common tsunami risk management strategy. The specific objectives of the project are tackled by the following four consecutive actions: 1) Conduct a state-of-the-art, standardized, and updatable PTHA with full uncertainty treatment; 2) Review the entire process with international experts; 3) Produce the PTHA database, with documentation of the entire hazard assessment process; and 4) Publicize the results through an awareness raising and education phase, and a capacity building phase. This presentation will illustrate the project layout, summarize its current status of advancement including the firs preliminary release of the assessment, and outline its connections with similar initiatives in the international context. The TSUMAPS-NEAM Project (http://www.tsumaps-neam.eu/) is co-financed by the European Union Civil Protection Mechanism, Agreement Number: ECHO/SUB/2015/718568/PREV26.

Aggregate exposure approaches for parabens in personal care products: a case assessment for children between 0 and 3 years old

PubMed Central

Gosens, Ilse; Delmaar, Christiaan J E; ter Burg, Wouter; de Heer, Cees; Schuur, A Gerlienke

2014-01-01

In the risk assessment of chemical substances, aggregation of exposure to a substance from different sources via different pathways is not common practice. Focusing the exposure assessment on a substance from a single source can lead to a significant underestimation of the risk. To gain more insight on how to perform an aggregate exposure assessment, we applied a deterministic (tier 1) and a person-oriented probabilistic approach (tier 2) for exposure to the four most common parabens through personal care products in children between 0 and 3 years old. Following a deterministic approach, a worst-case exposure estimate is calculated for methyl-, ethyl-, propyl- and butylparaben. As an illustration for risk assessment, Margins of Exposure (MoE) are calculated. These are 991 and 4966 for methyl- and ethylparaben, and 8 and 10 for propyl- and butylparaben, respectively. In tier 2, more detailed information on product use has been obtained from a small survey on product use of consumers. A probabilistic exposure assessment is performed to estimate the variability and uncertainty of exposure in a population. Results show that the internal exposure for each paraben is below the level determined in tier 1. However, for propyl- and butylparaben, the percentile of the population with an exposure probability above the assumed “safe” MoE of 100, is 13% and 7%, respectively. In conclusion, a tier 1 approach can be performed using simple equations and default point estimates, and serves as a starting point for exposure and risk assessment. If refinement is warranted, the more data demanding person-oriented probabilistic approach should be used. This probabilistic approach results in a more realistic exposure estimate, including the uncertainty, and allows determining the main drivers of exposure. Furthermore, it allows to estimate the percentage of the population for which the exposure is likely to be above a specific value. PMID:23801276

Architecture for Integrated Medical Model Dynamic Probabilistic Risk Assessment

NASA Technical Reports Server (NTRS)

Jaworske, D. A.; Myers, J. G.; Goodenow, D.; Young, M.; Arellano, J. D.

2016-01-01

Probabilistic Risk Assessment (PRA) is a modeling tool used to predict potential outcomes of a complex system based on a statistical understanding of many initiating events. Utilizing a Monte Carlo method, thousands of instances of the model are considered and outcomes are collected. PRA is considered static, utilizing probabilities alone to calculate outcomes. Dynamic Probabilistic Risk Assessment (dPRA) is an advanced concept where modeling predicts the outcomes of a complex system based not only on the probabilities of many initiating events, but also on a progression of dependencies brought about by progressing down a time line. Events are placed in a single time line, adding each event to a queue, as managed by a planner. Progression down the time line is guided by rules, as managed by a scheduler. The recently developed Integrated Medical Model (IMM) summarizes astronaut health as governed by the probabilities of medical events and mitigation strategies. Managing the software architecture process provides a systematic means of creating, documenting, and communicating a software design early in the development process. The software architecture process begins with establishing requirements and the design is then derived from the requirements.

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.

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

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

Risk Assessment Guidance for Superfund (RAGS) Volume III: Part A

EPA Pesticide Factsheets

EPA's Risk Assessment Guidance for Superfund (RAGS) Volume 3A provides policies and guiding principles on the application of probabilistic risk assessment (PRA) methods to human health and ecological risk assessment in the EPA Superfund Program.

Tornado wind-loading requirements based on risk assessment techniques

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

Deobald, T.L.; Coles, G.A.; Smith, G.L.

Regulations require that nuclear power plants be protected from tornado winds. If struck by a tornado, a plant must be capable of safely shutting down and removing decay heat. Probabilistic techniques are used to show that risk to the public from the US Department of Energy (DOE) SP-100 reactor is acceptable without tornado hardening parts of the secondary system. Relaxed requirements for design wind loadings will result in significant cost savings. To demonstrate an acceptable level of risk, this document examines tornado-initiated accidents. The two tornado-initiated accidents examined in detail are loss of cooling resulting in core damage and lossmore » of secondary system boundary integrity leading to sodium release. Loss of core cooling is analyzed using fault/event tree models. Loss of secondary system boundary integrity is analyzed by comparing the consequences to acceptance criteria for the release of radioactive material or alkali metal aerosol. 4 refs., 4 figs.« less

Decision making generalized by a cumulative probability weighting function

NASA Astrophysics Data System (ADS)

dos Santos, Lindomar Soares; Destefano, Natália; Martinez, Alexandre Souto

2018-01-01

Typical examples of intertemporal decision making involve situations in which individuals must choose between a smaller reward, but more immediate, and a larger one, delivered later. Analogously, probabilistic decision making involves choices between options whose consequences differ in relation to their probability of receiving. In Economics, the expected utility theory (EUT) and the discounted utility theory (DUT) are traditionally accepted normative models for describing, respectively, probabilistic and intertemporal decision making. A large number of experiments confirmed that the linearity assumed by the EUT does not explain some observed behaviors, as nonlinear preference, risk-seeking and loss aversion. That observation led to the development of new theoretical models, called non-expected utility theories (NEUT), which include a nonlinear transformation of the probability scale. An essential feature of the so-called preference function of these theories is that the probabilities are transformed by decision weights by means of a (cumulative) probability weighting function, w(p) . We obtain in this article a generalized function for the probabilistic discount process. This function has as particular cases mathematical forms already consecrated in the literature, including discount models that consider effects of psychophysical perception. We also propose a new generalized function for the functional form of w. The limiting cases of this function encompass some parametric forms already proposed in the literature. Far beyond a mere generalization, our function allows the interpretation of probabilistic decision making theories based on the assumption that individuals behave similarly in the face of probabilities and delays and is supported by phenomenological models.

Feedback-related negativity is enhanced in adolescence during a gambling task with and without probabilistic reinforcement learning.

PubMed

Martínez-Velázquez, Eduardo S; Ramos-Loyo, Julieta; González-Garrido, Andrés A; Sequeira, Henrique

2015-01-21

Feedback-related negativity (FRN) is a negative deflection that appears around 250 ms after the gain or loss of feedback to chosen alternatives in a gambling task in frontocentral regions following outcomes. Few studies have reported FRN enhancement in adolescents compared with adults in a gambling task without probabilistic reinforcement learning, despite the fact that learning from positive or negative consequences is crucial for decision-making during adolescence. Therefore, the aim of the present research was to identify differences in FRN amplitude and latency between adolescents and adults on a gambling task with favorable and unfavorable probabilistic reinforcement learning conditions, in addition to a nonlearning condition with monetary gains and losses. Higher rate scores of high-magnitude choices during the final 30 trials compared with the first 30 trials were observed during the favorable condition, whereas lower rates were observed during the unfavorable condition in both groups. Higher FRN amplitude in all conditions and longer latency in the nonlearning condition were observed in adolescents compared with adults and in relation to losses. Results indicate that both the adolescents and the adults improved their performance in relation to positive and negative feedback. However, the FRN findings suggest an increased sensitivity to external feedback to losses in adolescents compared with adults, irrespective of the presence or absence of probabilistic reinforcement learning. These results reflect processing differences on the neural monitoring system and provide new perspectives on the dynamic development of an adolescent's brain.

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.

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.

Probabilistic simulation of multi-scale composite behavior

NASA Technical Reports Server (NTRS)

Liaw, D. G.; Shiao, M. C.; Singhal, S. N.; Chamis, Christos C.

1993-01-01

A methodology is developed to computationally assess the probabilistic composite material properties at all composite scale levels due to the uncertainties in the constituent (fiber and matrix) properties and in the fabrication process variables. The methodology is computationally efficient for simulating the probability distributions of material properties. The sensitivity of the probabilistic composite material property to each random variable is determined. This information can be used to reduce undesirable uncertainties in material properties at the macro scale of the composite by reducing the uncertainties in the most influential random variables at the micro scale. This methodology was implemented into the computer code PICAN (Probabilistic Integrated Composite ANalyzer). The accuracy and efficiency of this methodology are demonstrated by simulating the uncertainties in the material properties of a typical laminate and comparing the results with the Monte Carlo simulation method. The experimental data of composite material properties at all scales fall within the scatters predicted by PICAN.

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 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.

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.

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 Asteroid Impact Risk Assessment for the Hypothetical PDC17 Impact Exercise

NASA Technical Reports Server (NTRS)

Wheeler, Lorien; Mathias, Donovan

2017-01-01

Performing impact risk assessment for the 2017 Planetary Defense Conference (PDC17) hypothetical impact exercise, to take place at the PDC17 conference, May 15-20, 2017. Impact scenarios and trajectories are developed and provided by NASA's Near Earth Objects Office at JPL (Paul Chodas). These results represent purely hypothetical impact scenarios, and do not reflect any known asteroid threat. Risk assessment was performed using the Probabilistic Asteroid Impact Risk (PAIR) model developed by the Asteroid Threat Assessment Project (ATAP) at NASA Ames Research Center. This presentation includes sample results that may be presented or used in discussions during the various stages of the impact exercisecenter dot Some cases represent alternate scenario options that may not be used during the actual impact exercise at the PDC17 conference. Updates to these initial assessments and/or additional scenario assessments may be performed throughout the impact exercise as different scenario options unfold.

Mapping flood hazards under uncertainty through probabilistic flood inundation maps

NASA Astrophysics Data System (ADS)

Stephens, T.; Bledsoe, B. P.; Miller, A. J.; Lee, G.

2017-12-01

Changing precipitation, rapid urbanization, and population growth interact to create unprecedented challenges for flood mitigation and management. Standard methods for estimating risk from flood inundation maps generally involve simulations of floodplain hydraulics for an established regulatory discharge of specified frequency. Hydraulic model results are then geospatially mapped and depicted as a discrete boundary of flood extents and a binary representation of the probability of inundation (in or out) that is assumed constant over a project's lifetime. Consequently, existing methods utilized to define flood hazards and assess risk management are hindered by deterministic approaches that assume stationarity in a nonstationary world, failing to account for spatio-temporal variability of climate and land use as they translate to hydraulic models. This presentation outlines novel techniques for portraying flood hazards and the results of multiple flood inundation maps spanning hydroclimatic regions. Flood inundation maps generated through modeling of floodplain hydraulics are probabilistic reflecting uncertainty quantified through Monte-Carlo analyses of model inputs and parameters under current and future scenarios. The likelihood of inundation and range of variability in flood extents resulting from Monte-Carlo simulations are then compared with deterministic evaluations of flood hazards from current regulatory flood hazard maps. By facilitating alternative approaches of portraying flood hazards, the novel techniques described in this presentation can contribute to a shifting paradigm in flood management that acknowledges the inherent uncertainty in model estimates and the nonstationary behavior of land use and climate.

A physical model for dementia

NASA Astrophysics Data System (ADS)

Sotolongo-Costa, O.; Gaggero-Sager, L. M.; Becker, J. T.; Maestu, F.; Sotolongo-Grau, O.

2017-04-01

Aging associated brain decline often result in some kind of dementia. Even when this is a complex brain disorder a physical model can be used in order to describe its general behavior. A probabilistic model for the development of dementia is obtained and fitted to some experimental data obtained from the Alzheimer's Disease Neuroimaging Initiative. It is explained how dementia appears as a consequence of aging and why it is irreversible.

Exposure Assessment Tools by Tiers and Types - Deterministic and Probabilistic Assessments

EPA Pesticide Factsheets

EPA ExpoBox is a toolbox for exposure assessors. Its purpose is to provide a compendium of exposure assessment and risk characterization tools that will present comprehensive step-by-step guidance and links to relevant exposure assessment data bases

Effects of delay and probability combinations on discounting in humans.

PubMed

Cox, David J; Dallery, Jesse

2016-10-01

To determine discount rates, researchers typically adjust the amount of an immediate or certain option relative to a delayed or uncertain option. Because this adjusting amount method can be relatively time consuming, researchers have developed more efficient procedures. One such procedure is a 5-trial adjusting delay procedure, which measures the delay at which an amount of money loses half of its value (e.g., $1000 is valued at $500 with a 10-year delay to its receipt). Experiment 1 (n=212) used 5-trial adjusting delay or probability tasks to measure delay discounting of losses, probabilistic gains, and probabilistic losses. Experiment 2 (n=98) assessed combined probabilistic and delayed alternatives. In both experiments, we compared results from 5-trial adjusting delay or probability tasks to traditional adjusting amount procedures. Results suggest both procedures produced similar rates of probability and delay discounting in six out of seven comparisons. A magnitude effect consistent with previous research was observed for probabilistic gains and losses, but not for delayed losses. Results also suggest that delay and probability interact to determine the value of money. Five-trial methods may allow researchers to assess discounting more efficiently as well as study more complex choice scenarios. Copyright © 2016 Elsevier B.V. All rights reserved.

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

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.

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.

Numeracy of multiple sclerosis patients: A comparison of patients from the PERCEPT study to a German probabilistic sample.

PubMed

Gaissmaier, Wolfgang; Giese, Helge; Galesic, Mirta; Garcia-Retamero, Rocio; Kasper, Juergen; Kleiter, Ingo; Meuth, Sven G; Köpke, Sascha; Heesen, Christoph

2018-01-01

A shared decision-making approach is suggested for multiple sclerosis (MS) patients. To properly evaluate benefits and risks of different treatment options accordingly, MS patients require sufficient numeracy - the ability to understand quantitative information. It is unknown whether MS affects numeracy. Therefore, we investigated whether patients' numeracy was impaired compared to a probabilistic national sample. As part of the larger prospective, observational, multicenter study PERCEPT, we assessed numeracy for a clinical study sample of German MS patients (N=725) with a standard test and compared them to a German probabilistic sample (N=1001), controlling for age, sex, and education. Within patients, we assessed whether disease variables (disease duration, disability, annual relapse rate, cognitive impairment) predicted numeracy beyond these demographics. MS patients showed a comparable level of numeracy as the probabilistic national sample (68.9% vs. 68.5% correct answers, P=0.831). In both samples, numeracy was higher for men and the highly educated. Disease variables did not predict numeracy beyond demographics within patients, and predictability was generally low. This sample of MS patients understood quantitative information on the same level as the general population. There is no reason to withhold quantitative information from MS patients. Copyright © 2017 Elsevier B.V. All rights reserved.

Effect of time dependence on probabilistic seismic-hazard maps and deaggregation for the central Apennines, Italy

USGS Publications Warehouse

Akinci, A.; Galadini, F.; Pantosti, D.; Petersen, M.; Malagnini, L.; Perkins, D.

2009-01-01

We produce probabilistic seismic-hazard assessments for the central Apennines, Italy, using time-dependent models that are characterized using a Brownian passage time recurrence model. Using aperiodicity parameters, ?? of 0.3, 0.5, and 0.7, we examine the sensitivity of the probabilistic ground motion and its deaggregation to these parameters. For the seismic source model we incorporate both smoothed historical seismicity over the area and geological information on faults. We use the maximum magnitude model for the fault sources together with a uniform probability of rupture along the fault (floating fault model) to model fictitious faults to account for earthquakes that cannot be correlated with known geologic structural segmentation.

Development of Advanced Life Cycle Costing Methods for Technology Benefit/Cost/Risk Assessment

NASA Technical Reports Server (NTRS)

Yackovetsky, Robert (Technical Monitor)

2002-01-01

The overall objective of this three-year grant is to provide NASA Langley's System Analysis Branch with improved affordability tools and methods based on probabilistic cost assessment techniques. In order to accomplish this objective, the Aerospace Systems Design Laboratory (ASDL) needs to pursue more detailed affordability, technology impact, and risk prediction methods and to demonstrate them on variety of advanced commercial transports. The affordability assessment, which is a cornerstone of ASDL methods, relies on the Aircraft Life Cycle Cost Analysis (ALCCA) program originally developed by NASA Ames Research Center and enhanced by ASDL. This grant proposed to improve ALCCA in support of the project objective by updating the research, design, test, and evaluation cost module, as well as the engine development cost module. Investigations into enhancements to ALCCA include improved engine development cost, process based costing, supportability cost, and system reliability with airline loss of revenue for system downtime. A probabilistic, stand-alone version of ALCCA/FLOPS will also be developed under this grant in order to capture the uncertainty involved in technology assessments. FLOPS (FLight Optimization System program) is an aircraft synthesis and sizing code developed by NASA Langley Research Center. This probabilistic version of the coupled program will be used within a Technology Impact Forecasting (TIF) method to determine what types of technologies would have to be infused in a system in order to meet customer requirements. A probabilistic analysis of the CER's (cost estimating relationships) within ALCCA will also be carried out under this contract in order to gain some insight as to the most influential costs and the impact that code fidelity could have on future RDS (Robust Design Simulation) studies.

Applying probabilistic temporal and multisite data quality control methods to a public health mortality registry in Spain: a systematic approach to quality control of repositories.

PubMed

Sáez, Carlos; Zurriaga, Oscar; Pérez-Panadés, Jordi; Melchor, Inma; Robles, Montserrat; García-Gómez, Juan M

2016-11-01

To assess the variability in data distributions among data sources and over time through a case study of a large multisite repository as a systematic approach to data quality (DQ). Novel probabilistic DQ control methods based on information theory and geometry are applied to the Public Health Mortality Registry of the Region of Valencia, Spain, with 512 143 entries from 2000 to 2012, disaggregated into 24 health departments. The methods provide DQ metrics and exploratory visualizations for (1) assessing the variability among multiple sources and (2) monitoring and exploring changes with time. The methods are suited to big data and multitype, multivariate, and multimodal data. The repository was partitioned into 2 probabilistically separated temporal subgroups following a change in the Spanish National Death Certificate in 2009. Punctual temporal anomalies were noticed due to a punctual increment in the missing data, along with outlying and clustered health departments due to differences in populations or in practices. Changes in protocols, differences in populations, biased practices, or other systematic DQ problems affected data variability. Even if semantic and integration aspects are addressed in data sharing infrastructures, probabilistic variability may still be present. Solutions include fixing or excluding data and analyzing different sites or time periods separately. A systematic approach to assessing temporal and multisite variability is proposed. Multisite and temporal variability in data distributions affects DQ, hindering data reuse, and an assessment of such variability should be a part of systematic DQ procedures. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Perception of Risk and Terrorism-Related Behavior Change: Dual Influences of Probabilistic Reasoning and Reality Testing.

PubMed

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

2017-01-01

The present study assessed the degree to which probabilistic reasoning performance and thinking style influenced perception of risk and self-reported levels of terrorism-related behavior change. A sample of 263 respondents, recruited via convenience sampling, completed a series of measures comprising probabilistic reasoning tasks (perception of randomness, base rate, probability, and conjunction fallacy), the Reality Testing subscale of the Inventory of Personality Organization (IPO-RT), the Domain-Specific Risk-Taking Scale, and a terrorism-related behavior change scale. Structural equation modeling examined three progressive models. Firstly, the Independence Model assumed that probabilistic reasoning, perception of risk and reality testing independently predicted terrorism-related behavior change. Secondly, the Mediation Model supposed that probabilistic reasoning and reality testing correlated, and indirectly predicted terrorism-related behavior change through perception of risk. Lastly, the Dual-Influence Model proposed that probabilistic reasoning indirectly predicted terrorism-related behavior change via perception of risk, independent of reality testing. Results indicated that performance on probabilistic reasoning tasks most strongly predicted perception of risk, and preference for an intuitive thinking style (measured by the IPO-RT) best explained terrorism-related behavior change. The combination of perception of risk with probabilistic reasoning ability in the Dual-Influence Model enhanced the predictive power of the analytical-rational route, with conjunction fallacy having a significant indirect effect on terrorism-related behavior change via perception of risk. The Dual-Influence Model possessed superior fit and reported similar predictive relations between intuitive-experiential and analytical-rational routes and terrorism-related behavior change. The discussion critically examines these findings in relation to dual-processing frameworks. This includes considering the limitations of current operationalisations and recommendations for future research that align outcomes and subsequent work more closely to specific dual-process models.

Perception of Risk and Terrorism-Related Behavior Change: Dual Influences of Probabilistic Reasoning and Reality Testing

PubMed Central

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

2017-01-01

The present study assessed the degree to which probabilistic reasoning performance and thinking style influenced perception of risk and self-reported levels of terrorism-related behavior change. A sample of 263 respondents, recruited via convenience sampling, completed a series of measures comprising probabilistic reasoning tasks (perception of randomness, base rate, probability, and conjunction fallacy), the Reality Testing subscale of the Inventory of Personality Organization (IPO-RT), the Domain-Specific Risk-Taking Scale, and a terrorism-related behavior change scale. Structural equation modeling examined three progressive models. Firstly, the Independence Model assumed that probabilistic reasoning, perception of risk and reality testing independently predicted terrorism-related behavior change. Secondly, the Mediation Model supposed that probabilistic reasoning and reality testing correlated, and indirectly predicted terrorism-related behavior change through perception of risk. Lastly, the Dual-Influence Model proposed that probabilistic reasoning indirectly predicted terrorism-related behavior change via perception of risk, independent of reality testing. Results indicated that performance on probabilistic reasoning tasks most strongly predicted perception of risk, and preference for an intuitive thinking style (measured by the IPO-RT) best explained terrorism-related behavior change. The combination of perception of risk with probabilistic reasoning ability in the Dual-Influence Model enhanced the predictive power of the analytical-rational route, with conjunction fallacy having a significant indirect effect on terrorism-related behavior change via perception of risk. The Dual-Influence Model possessed superior fit and reported similar predictive relations between intuitive-experiential and analytical-rational routes and terrorism-related behavior change. The discussion critically examines these findings in relation to dual-processing frameworks. This includes considering the limitations of current operationalisations and recommendations for future research that align outcomes and subsequent work more closely to specific dual-process models. PMID:29062288

Comparision of the different probability distributions for earthquake hazard assessment in the North Anatolian Fault Zone

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

Yilmaz, Şeyda, E-mail: seydayilmaz@ktu.edu.tr; Bayrak, Erdem, E-mail: erdmbyrk@gmail.com; Bayrak, Yusuf, E-mail: bayrak@ktu.edu.tr

In this study we examined and compared the three different probabilistic distribution methods for determining the best suitable model in probabilistic assessment of earthquake hazards. We analyzed a reliable homogeneous earthquake catalogue between a time period 1900-2015 for magnitude M ≥ 6.0 and estimated the probabilistic seismic hazard in the North Anatolian Fault zone (39°-41° N 30°-40° E) using three distribution methods namely Weibull distribution, Frechet distribution and three-parameter Weibull distribution. The distribution parameters suitability was evaluated Kolmogorov-Smirnov (K-S) goodness-of-fit test. We also compared the estimated cumulative probability and the conditional probabilities of occurrence of earthquakes for different elapsed timemore » using these three distribution methods. We used Easyfit and Matlab software to calculate these distribution parameters and plotted the conditional probability curves. We concluded that the Weibull distribution method was the most suitable than other distribution methods in this region.« 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 modeling of percutaneous absorption for risk-based exposure assessments and transdermal drug delivery.

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

Ho, Clifford Kuofei

Chemical transport through human skin can play a significant role in human exposure to toxic chemicals in the workplace, as well as to chemical/biological warfare agents in the battlefield. The viability of transdermal drug delivery also relies on chemical transport processes through the skin. Models of percutaneous absorption are needed for risk-based exposure assessments and drug-delivery analyses, but previous mechanistic models have been largely deterministic. A probabilistic, transient, three-phase model of percutaneous absorption of chemicals has been developed to assess the relative importance of uncertain parameters and processes that may be important to risk-based assessments. Penetration routes through the skinmore » that were modeled include the following: (1) intercellular diffusion through the multiphase stratum corneum; (2) aqueous-phase diffusion through sweat ducts; and (3) oil-phase diffusion through hair follicles. Uncertainty distributions were developed for the model parameters, and a Monte Carlo analysis was performed to simulate probability distributions of mass fluxes through each of the routes. Sensitivity analyses using stepwise linear regression were also performed to identify model parameters that were most important to the simulated mass fluxes at different times. This probabilistic analysis of percutaneous absorption (PAPA) method has been developed to improve risk-based exposure assessments and transdermal drug-delivery analyses, where parameters and processes can be highly uncertain.« less

Toward Probabilistic Risk Analyses - Development of a Probabilistic Tsunami Hazard Assessment of Crescent City, CA

NASA Astrophysics Data System (ADS)

González, F. I.; Leveque, R. J.; Hatheway, D.; Metzger, N.

2011-12-01

Risk is defined in many ways, but most are consistent with Crichton's [1999] definition based on the ''risk triangle'' concept and the explicit identification of three risk elements: ''Risk is the probability of a loss, and this depends on three elements: hazard, vulnerability, and exposure. If any of these three elements in risk increases or decreases, then the risk increases or decreases respectively." The World Meteorological Organization, for example, cites Crichton [1999] and then defines risk as [WMO, 2008] Risk = function (Hazard x Vulnerability x Exposure) while the Asian Disaster Reduction Center adopts the more general expression [ADRC, 2005] Risk = function (Hazard, Vulnerability, Exposure) In practice, probabilistic concepts are invariably invoked, and at least one of the three factors are specified as probabilistic in nature. The Vulnerability and Exposure factors are defined in multiple ways in the relevant literature; but the Hazard factor, which is the focus of our presentation, is generally understood to deal only with the physical aspects of the phenomena and, in particular, the ability of the phenomena to inflict harm [Thywissen, 2006]. A Hazard factor can be estimated by a methodology known as Probabilistic Tsunami Hazard Assessment (PTHA) [González, et al., 2009]. We will describe the PTHA methodology and provide an example -- the results of a previous application to Seaside, OR. We will also present preliminary results for a PTHA of Crescent City, CA -- a pilot project and coastal modeling/mapping effort funded by the Federal Emergency Management Agency (FEMA) Region IX office as part of the new California Coastal Analysis and Mapping Project (CCAMP). CCAMP and the PTHA in Crescent City are being conducted under the nationwide FEMA Risk Mapping, Assessment, and Planning (Risk MAP) Program which focuses on providing communities with flood information and tools they can use to enhance their mitigation plans and better protect their citizens.

‘Particle genetics’: treating every cell as unique

PubMed Central

Yvert, Gaël

2014-01-01

Genotype-phenotype relations are usually inferred from a deterministic point of view. For example, quantitative trait loci (QTL), which describe regions of the genome associated with a particular phenotype, are based on a mean trait difference between genotype categories. However, living systems comprise huge numbers of cells (the ‘particles’ of biology). Each cell can exhibit substantial phenotypic individuality, which can have dramatic consequences at the organismal level. Now, with technology capable of interrogating individual cells, it is time to consider how genotypes shape the probability laws of single cell traits. The possibility of mapping single cell probabilistic trait loci (PTL), which link genomic regions to probabilities of cellular traits, is a promising step in this direction. This approach requires thinking about phenotypes in probabilistic terms, a concept that statistical physicists have been applying to particles for a century. Here, I describe PTL and discuss their potential to enlarge our understanding of genotype-phenotype relations. PMID:24315431

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

NasoNet, modeling the spread of nasopharyngeal cancer with networks of probabilistic events in discrete time.

PubMed

Galán, S F; Aguado, F; Díez, F J; Mira, J

2002-07-01

The spread of cancer is a non-deterministic dynamic process. As a consequence, the design of an assistant system for the diagnosis and prognosis of the extent of a cancer should be based on a representation method that deals with both uncertainty and time. The ultimate goal is to know the stage of development of a cancer in a patient before selecting the appropriate treatment. A network of probabilistic events in discrete time (NPEDT) is a type of Bayesian network for temporal reasoning that models the causal mechanisms associated with the time evolution of a process. This paper describes NasoNet, a system that applies NPEDTs to the diagnosis and prognosis of nasopharyngeal cancer. We have made use of temporal noisy gates to model the dynamic causal interactions that take place in the domain. The methodology we describe is general enough to be applied to any other type of cancer.

Probabilistic risk assessment of the Space Shuttle. Phase 3: A study of the potential of losing the vehicle during nominal operation. Volume 2: Integrated loss of vehicle model

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

The application of the probabilistic risk assessment methodology to a Space Shuttle environment, particularly to the potential of losing the Shuttle during nominal operation is addressed. The different related concerns are identified and combined to determine overall program risks. A fault tree model is used to allocate system probabilities to the subsystem level. The loss of the vehicle due to failure to contain energetic gas and debris, to maintain proper propulsion and configuration is analyzed, along with the loss due to Orbiter, external tank failure, and landing failure or error.

USING SPARROW MODEL RESULTS TO ASSIST WITH COASTAL WATER ASSESSMENT

EPA Science Inventory

The National Coastal Assessment (NCA) has proposed a national strategy for research and monitoring in support of coastal water assessment that involves three tiers: Problem Characterization (Tier 1), involving probabilistic surveys to document broad-scale response properties; D...

Probabilistic assessment method of the non-monotonic dose-responses-Part I: Methodological approach.

PubMed

Chevillotte, Grégoire; Bernard, Audrey; Varret, Clémence; Ballet, Pascal; Bodin, Laurent; Roudot, Alain-Claude

2017-08-01

More and more studies aim to characterize non-monotonic dose response curves (NMDRCs). The greatest difficulty is to assess the statistical plausibility of NMDRCs from previously conducted dose response studies. This difficulty is linked to the fact that these studies present (i) few doses tested, (ii) a low sample size per dose, and (iii) the absence of any raw data. In this study, we propose a new methodological approach to probabilistically characterize NMDRCs. The methodology is composed of three main steps: (i) sampling from summary data to cover all the possibilities that may be presented by the responses measured by dose and to obtain a new raw database, (ii) statistical analysis of each sampled dose-response curve to characterize the slopes and their signs, and (iii) characterization of these dose-response curves according to the variation of the sign in the slope. This method allows characterizing all types of dose-response curves and can be applied both to continuous data and to discrete data. The aim of this study is to present the general principle of this probabilistic method which allows to assess the non-monotonic dose responses curves, and to present some results. Copyright © 2017 Elsevier Ltd. All rights reserved.

Probabilistic TSUnami Hazard MAPS for the NEAM Region: The TSUMAPS-NEAM Project

NASA Astrophysics Data System (ADS)

Basili, R.; Babeyko, A. Y.; Baptista, M. A.; Ben Abdallah, S.; Canals, M.; El Mouraouah, A.; Harbitz, C. B.; Ibenbrahim, A.; Lastras, G.; Lorito, S.; Løvholt, F.; Matias, L. M.; Omira, R.; Papadopoulos, G. A.; Pekcan, O.; Nmiri, A.; Selva, J.; Yalciner, A. C.

2016-12-01

As global awareness of tsunami hazard and risk grows, the North-East Atlantic, the Mediterranean, and connected Seas (NEAM) region still lacks a thorough probabilistic tsunami hazard assessment. The TSUMAPS-NEAM project aims to fill this gap in the NEAM region by 1) producing the first region-wide long-term homogenous Probabilistic Tsunami Hazard Assessment (PTHA) from earthquake sources, and by 2) triggering a common tsunami risk management strategy. The specific objectives of the project are tackled by the following four consecutive actions: 1) Conduct a state-of-the-art, standardized, and updatable PTHA with full uncertainty treatment; 2) Review the entire process with international experts; 3) Produce the PTHA database, with documentation of the entire hazard assessment process; and 4) Publicize the results through an awareness raising and education phase, and a capacity building phase. This presentation will illustrate the project layout, summarize its current status of advancement and prospective results, and outline its connections with similar initiatives in the international context. The TSUMAPS-NEAM Project (http://www.tsumaps-neam.eu/) is co-financed by the European Union Civil Protection Mechanism, Agreement Number: ECHO/SUB/2015/718568/PREV26.

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.

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

Efficient Sensitivity Methods for Probabilistic Lifing and Engine Prognostics

DTIC Science & Technology

2010-09-01

AFRL-RX-WP-TR-2010-4297 EFFICIENT SENSITIVITY METHODS FOR PROBABILISTIC LIFING AND ENGINE PROGNOSTICS Harry Millwater , Ronald Bagley, Jose...5c. PROGRAM ELEMENT NUMBER 62102F 6. AUTHOR(S) Harry Millwater , Ronald Bagley, Jose Garza, D. Wagner, Andrew Bates, and Andy Voorhees 5d...Reliability Assessment, MIL-HDBK-1823, 30 April 1999. 9. Leverant GR, Millwater HR, McClung RC, Enright MP, A New Tool for Design and Certification of

A Framework for Quantitative Assessment of Impacts Related to Energy and Mineral Resource Development

DOE PAGES

Haines, Seth S.; Diffendorfer, Jay E.; Balistrieri, Laurie; ...

2013-05-15

Natural resource planning at all scales demands methods for assessing the impacts of resource development and use, and in particular it requires standardized methods that yield robust and unbiased results. Building from existing probabilistic methods for assessing the volumes of energy and mineral resources, we provide an algorithm for consistent, reproducible, quantitative assessment of resource development impacts. The approach combines probabilistic input data with Monte Carlo statistical methods to determine probabilistic outputs that convey the uncertainties inherent in the data. For example, one can utilize our algorithm to combine data from a natural gas resource assessment with maps of sagemore » grouse leks and pinon-juniper woodlands in the same area to estimate possible future habitat impacts due to possible future gas development. As another example: one could combine geochemical data and maps of lynx habitat with data from a mineral deposit assessment in the same area to determine possible future mining impacts on water resources and lynx habitat. The approach can be applied to a broad range of positive and negative resource development impacts, such as water quantity or quality, economic benefits, or air quality, limited only by the availability of necessary input data and quantified relationships among geologic resources, development alternatives, and impacts. In conclusion, the framework enables quantitative evaluation of the trade-offs inherent in resource management decision-making, including cumulative impacts, to address societal concerns and policy aspects of resource development.« less

A framework for quantitative assessment of impacts related to energy and mineral resource development

USGS Publications Warehouse

Haines, Seth S.; Diffendorfer, James; Balistrieri, Laurie S.; Berger, Byron R.; Cook, Troy A.; Gautier, Donald L.; Gallegos, Tanya J.; Gerritsen, Margot; Graffy, Elisabeth; Hawkins, Sarah; Johnson, Kathleen; Macknick, Jordan; McMahon, Peter; Modde, Tim; Pierce, Brenda; Schuenemeyer, John H.; Semmens, Darius; Simon, Benjamin; Taylor, Jason; Walton-Day, Katherine

2013-01-01

Natural resource planning at all scales demands methods for assessing the impacts of resource development and use, and in particular it requires standardized methods that yield robust and unbiased results. Building from existing probabilistic methods for assessing the volumes of energy and mineral resources, we provide an algorithm for consistent, reproducible, quantitative assessment of resource development impacts. The approach combines probabilistic input data with Monte Carlo statistical methods to determine probabilistic outputs that convey the uncertainties inherent in the data. For example, one can utilize our algorithm to combine data from a natural gas resource assessment with maps of sage grouse leks and piñon-juniper woodlands in the same area to estimate possible future habitat impacts due to possible future gas development. As another example: one could combine geochemical data and maps of lynx habitat with data from a mineral deposit assessment in the same area to determine possible future mining impacts on water resources and lynx habitat. The approach can be applied to a broad range of positive and negative resource development impacts, such as water quantity or quality, economic benefits, or air quality, limited only by the availability of necessary input data and quantified relationships among geologic resources, development alternatives, and impacts. The framework enables quantitative evaluation of the trade-offs inherent in resource management decision-making, including cumulative impacts, to address societal concerns and policy aspects of resource development.

Longitudinal Temporal and Probabilistic Prediction of Survival in a Cohort of Patients With Advanced Cancer

PubMed Central

Perez-Cruz, Pedro E.; dos Santos, Renata; Silva, Thiago Buosi; Crovador, Camila Souza; Nascimento, Maria Salete de Angelis; Hall, Stacy; Fajardo, Julieta; Bruera, Eduardo; Hui, David

2014-01-01

Context Survival prognostication is important during end-of-life. The accuracy of clinician prediction of survival (CPS) over time has not been well characterized. Objectives To examine changes in prognostication accuracy during the last 14 days of life in a cohort of patients with advanced cancer admitted to two acute palliative care units and to compare the accuracy between the temporal and probabilistic approaches. Methods Physicians and nurses prognosticated survival daily for cancer patients in two hospitals until death/discharge using two prognostic approaches: temporal and probabilistic. We assessed accuracy for each method daily during the last 14 days of life comparing accuracy at day −14 (baseline) with accuracy at each time point using a test of proportions. Results 6718 temporal and 6621 probabilistic estimations were provided by physicians and nurses for 311 patients, respectively. Median (interquartile range) survival was 8 (4, 20) days. Temporal CPS had low accuracy (10–40%) and did not change over time. In contrast, probabilistic CPS was significantly more accurate (p<.05 at each time point) but decreased close to death. Conclusion Probabilistic CPS was consistently more accurate than temporal CPS over the last 14 days of life; however, its accuracy decreased as patients approached death. Our findings suggest that better tools to predict impending death are necessary. PMID:24746583

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 probabilistic method for testing and estimating selection differences between populations

PubMed Central

He, Yungang; Wang, Minxian; Huang, Xin; Li, Ran; Xu, Hongyang; Xu, Shuhua; Jin, Li

2015-01-01

Human populations around the world encounter various environmental challenges and, consequently, develop genetic adaptations to different selection forces. Identifying the differences in natural selection between populations is critical for understanding the roles of specific genetic variants in evolutionary adaptation. Although numerous methods have been developed to detect genetic loci under recent directional selection, a probabilistic solution for testing and quantifying selection differences between populations is lacking. Here we report the development of a probabilistic method for testing and estimating selection differences between populations. By use of a probabilistic model of genetic drift and selection, we showed that logarithm odds ratios of allele frequencies provide estimates of the differences in selection coefficients between populations. The estimates approximate a normal distribution, and variance can be estimated using genome-wide variants. This allows us to quantify differences in selection coefficients and to determine the confidence intervals of the estimate. Our work also revealed the link between genetic association testing and hypothesis testing of selection differences. It therefore supplies a solution for hypothesis testing of selection differences. This method was applied to a genome-wide data analysis of Han and Tibetan populations. The results confirmed that both the EPAS1 and EGLN1 genes are under statistically different selection in Han and Tibetan populations. We further estimated differences in the selection coefficients for genetic variants involved in melanin formation and determined their confidence intervals between continental population groups. Application of the method to empirical data demonstrated the outstanding capability of this novel approach for testing and quantifying differences in natural selection. PMID:26463656

Multi-Hazard Advanced Seismic Probabilistic Risk Assessment Tools and Applications

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

Coleman, Justin L.; Bolisetti, Chandu; Veeraraghavan, Swetha

Design of nuclear power plant (NPP) facilities to resist natural hazards has been a part of the regulatory process from the beginning of the NPP industry in the United States (US), but has evolved substantially over time. The original set of approaches and methods was entirely deterministic in nature and focused on a traditional engineering margins-based approach. However, over time probabilistic and risk-informed approaches were also developed and implemented in US Nuclear Regulatory Commission (NRC) guidance and regulation. A defense-in-depth framework has also been incorporated into US regulatory guidance over time. As a result, today, the US regulatory framework incorporatesmore » deterministic and probabilistic approaches for a range of different applications and for a range of natural hazard considerations. This framework will continue to evolve as a result of improved knowledge and newly identified regulatory needs and objectives, most notably in response to the NRC activities developed in response to the 2011 Fukushima accident in Japan. Although the US regulatory framework has continued to evolve over time, the tools, methods and data available to the US nuclear industry to meet the changing requirements have not kept pace. Notably, there is significant room for improvement in the tools and methods available for external event probabilistic risk assessment (PRA), which is the principal assessment approach used in risk-informed regulations and risk-informed decision-making applied to natural hazard assessment and design. This is particularly true if PRA is applied to natural hazards other than seismic loading. Development of a new set of tools and methods that incorporate current knowledge, modern best practice, and state-of-the-art computational resources would lead to more reliable assessment of facility risk and risk insights (e.g., the SSCs and accident sequences that are most risk-significant), with less uncertainty and reduced conservatisms.« less

Developing an event-tree probabilistic tsunami inundation model for NE Atlantic coasts: Application to case studies

NASA Astrophysics Data System (ADS)

Omira, Rachid; Baptista, Maria Ana; Matias, Luis

2015-04-01

This study constitutes the first assessment of probabilistic tsunami inundation in the NE Atlantic region, using an event-tree approach. It aims to develop a probabilistic tsunami inundation approach for the NE Atlantic coast with an application to two test sites of ASTARTE project, Tangier-Morocco and Sines-Portugal. Only tsunamis of tectonic origin are considered here, taking into account near-, regional- and far-filed sources. The multidisciplinary approach, proposed here, consists of an event-tree method that gathers seismic hazard assessment, tsunami numerical modelling, and statistical methods. It presents also a treatment of uncertainties related to source location and tidal stage in order to derive the likelihood of tsunami flood occurrence and exceedance of a specific near-shore wave height during a given return period. We derive high-resolution probabilistic maximum wave heights and flood distributions for both test-sites Tangier and Sines considering 100-, 500-, and 1000-year return periods. We find that the probability that a maximum wave height exceeds 1 m somewhere along the Sines coasts reaches about 55% for 100-year return period, and is up to 100% for 1000-year return period. Along Tangier coast, the probability of inundation occurrence (flow depth > 0m) is up to 45% for 100-year return period and reaches 96% in some near-shore costal location for 500-year return period. Acknowledgements: This work is funded by project ASTARTE - Assessment, STrategy And Risk Reduction for Tsunamis in Europe. Grant 603839, 7th FP (ENV.2013.6.4-3 ENV.2013.6.4-3).

An Integrated Probabilistic-Fuzzy Assessment of Uncertainty Associated with Human Health Risk to MSW Landfill Leachate Contamination

NASA Astrophysics Data System (ADS)

Mishra, H.; Karmakar, S.; Kumar, R.

2016-12-01

Risk assessment will not remain simple when it involves multiple uncertain variables. Uncertainties in risk assessment majorly results from (1) the lack of knowledge of input variable (mostly random), and (2) data obtained from expert judgment or subjective interpretation of available information (non-random). An integrated probabilistic-fuzzy health risk approach has been proposed for simultaneous treatment of random and non-random uncertainties associated with input parameters of health risk model. The LandSim 2.5, a landfill simulator, has been used to simulate the Turbhe landfill (Navi Mumbai, India) activities for various time horizons. Further the LandSim simulated six heavy metals concentration in ground water have been used in the health risk model. The water intake, exposure duration, exposure frequency, bioavailability and average time are treated as fuzzy variables, while the heavy metals concentration and body weight are considered as probabilistic variables. Identical alpha-cut and reliability level are considered for fuzzy and probabilistic variables respectively and further, uncertainty in non-carcinogenic human health risk is estimated using ten thousand Monte-Carlo simulations (MCS). This is the first effort in which all the health risk variables have been considered as non-deterministic for the estimation of uncertainty in risk output. The non-exceedance probability of Hazard Index (HI), summation of hazard quotients, of heavy metals of Co, Cu, Mn, Ni, Zn and Fe for male and female population have been quantified and found to be high (HI>1) for all the considered time horizon, which evidently shows possibility of adverse health effects on the population residing near Turbhe landfill.

Seismic hazard assessment: Issues and alternatives

USGS Publications Warehouse

Wang, Z.

2011-01-01

Seismic hazard and risk are two very important concepts in engineering design and other policy considerations. Although seismic hazard and risk have often been used inter-changeably, they are fundamentally different. Furthermore, seismic risk is more important in engineering design and other policy considerations. Seismic hazard assessment is an effort by earth scientists to quantify seismic hazard and its associated uncertainty in time and space and to provide seismic hazard estimates for seismic risk assessment and other applications. Although seismic hazard assessment is more a scientific issue, it deserves special attention because of its significant implication to society. Two approaches, probabilistic seismic hazard analysis (PSHA) and deterministic seismic hazard analysis (DSHA), are commonly used for seismic hazard assessment. Although PSHA has been pro-claimed as the best approach for seismic hazard assessment, it is scientifically flawed (i.e., the physics and mathematics that PSHA is based on are not valid). Use of PSHA could lead to either unsafe or overly conservative engineering design or public policy, each of which has dire consequences to society. On the other hand, DSHA is a viable approach for seismic hazard assessment even though it has been labeled as unreliable. The biggest drawback of DSHA is that the temporal characteristics (i.e., earthquake frequency of occurrence and the associated uncertainty) are often neglected. An alternative, seismic hazard analysis (SHA), utilizes earthquake science and statistics directly and provides a seismic hazard estimate that can be readily used for seismic risk assessment and other applications. ?? 2010 Springer Basel AG.

Probabilistic Modeling of the Renal Stone Formation Module

NASA Technical Reports Server (NTRS)

Best, Lauren M.; Myers, Jerry G.; Goodenow, Debra A.; McRae, Michael P.; Jackson, Travis C.

2013-01-01

The Integrated Medical Model (IMM) is a probabilistic tool, used in mission planning decision making and medical systems risk assessments. The IMM project maintains a database of over 80 medical conditions that could occur during a spaceflight, documenting an incidence rate and end case scenarios for each. In some cases, where observational data are insufficient to adequately define the inflight medical risk, the IMM utilizes external probabilistic modules to model and estimate the event likelihoods. One such medical event of interest is an unpassed renal stone. Due to a high salt diet and high concentrations of calcium in the blood (due to bone depletion caused by unloading in the microgravity environment) astronauts are at a considerable elevated risk for developing renal calculi (nephrolithiasis) while in space. Lack of observed incidences of nephrolithiasis has led HRP to initiate the development of the Renal Stone Formation Module (RSFM) to create a probabilistic simulator capable of estimating the likelihood of symptomatic renal stone presentation in astronauts on exploration missions. The model consists of two major parts. The first is the probabilistic component, which utilizes probability distributions to assess the range of urine electrolyte parameters and a multivariate regression to transform estimated crystal density and size distributions to the likelihood of the presentation of nephrolithiasis symptoms. The second is a deterministic physical and chemical model of renal stone growth in the kidney developed by Kassemi et al. The probabilistic component of the renal stone model couples the input probability distributions describing the urine chemistry, astronaut physiology, and system parameters with the physical and chemical outputs and inputs to the deterministic stone growth model. These two parts of the model are necessary to capture the uncertainty in the likelihood estimate. The model will be driven by Monte Carlo simulations, continuously randomly sampling the probability distributions of the electrolyte concentrations and system parameters that are inputs into the deterministic model. The total urine chemistry concentrations are used to determine the urine chemistry activity using the Joint Expert Speciation System (JESS), a biochemistry model. Information used from JESS is then fed into the deterministic growth model. Outputs from JESS and the deterministic model are passed back to the probabilistic model where a multivariate regression is used to assess the likelihood of a stone forming and the likelihood of a stone requiring clinical intervention. The parameters used to determine to quantify these risks include: relative supersaturation (RS) of calcium oxalate, citrate/calcium ratio, crystal number density, total urine volume, pH, magnesium excretion, maximum stone width, and ureteral location. Methods and Validation: The RSFM is designed to perform a Monte Carlo simulation to generate probability distributions of clinically significant renal stones, as well as provide an associated uncertainty in the estimate. Initially, early versions will be used to test integration of the components and assess component validation and verification (V&V), with later versions used to address questions regarding design reference mission scenarios. Once integrated with the deterministic component, the credibility assessment of the integrated model will follow NASA STD 7009 requirements.

Lossed in translation: an off-the-shelf method to recover probabilistic beliefs from loss-averse agents.

PubMed

Offerman, Theo; Palley, Asa B

2016-01-01

Strictly proper scoring rules are designed to truthfully elicit subjective probabilistic beliefs from risk neutral agents. Previous experimental studies have identified two problems with this method: (i) risk aversion causes agents to bias their reports toward the probability of [Formula: see text], and (ii) for moderate beliefs agents simply report [Formula: see text]. Applying a prospect theory model of risk preferences, we show that loss aversion can explain both of these behavioral phenomena. Using the insights of this model, we develop a simple off-the-shelf probability assessment mechanism that encourages loss-averse agents to report true beliefs. In an experiment, we demonstrate the effectiveness of this modification in both eliminating uninformative reports and eliciting true probabilistic beliefs.

A Tutorial on Probablilistic Risk Assessement and its Role in Risk-Informed Decision Making

NASA Technical Reports Server (NTRS)

Dezfuli, Homayoon

2010-01-01

This slide presentation reviews risk assessment and its role in risk-informed decision making. It includes information on probabilistic risk assessment, typical risk management process, origins of risk matrix, performance measures, performance objectives and Bayes theorem.

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.

Probabilistic Modeling of High-Temperature Material Properties of a 5-Harness 0/90 Sylramic Fiber/ CVI-SiC/ MI-SiC Woven Composite

NASA Technical Reports Server (NTRS)

Nagpal, Vinod K.; Tong, Michael; Murthy, P. L. N.; Mital, Subodh

1998-01-01

An integrated probabilistic approach has been developed to assess composites for high temperature applications. This approach was used to determine thermal and mechanical properties and their probabilistic distributions of a 5-harness 0/90 Sylramic fiber/CVI-SiC/Mi-SiC woven Ceramic Matrix Composite (CMC) at high temperatures. The purpose of developing this approach was to generate quantitative probabilistic information on this CMC to help complete the evaluation for its potential application for HSCT combustor liner. This approach quantified the influences of uncertainties inherent in constituent properties called primitive variables on selected key response variables of the CMC at 2200 F. The quantitative information is presented in the form of Cumulative Density Functions (CDFs). Probability Density Functions (PDFS) and primitive variable sensitivities on response. Results indicate that the scatters in response variables were reduced by 30-50% when the uncertainties in the primitive variables, which showed the most influence, were reduced by 50%.

Tailoring a Human Reliability Analysis to Your Industry Needs

NASA Technical Reports Server (NTRS)

DeMott, D. L.

2016-01-01

Companies at risk of accidents caused by human error that result in catastrophic consequences include: airline industry mishaps, medical malpractice, medication mistakes, aerospace failures, major oil spills, transportation mishaps, power production failures and manufacturing facility incidents. Human Reliability Assessment (HRA) is used to analyze the inherent risk of human behavior or actions introducing errors into the operation of a system or process. These assessments can be used to identify where errors are most likely to arise and the potential risks involved if they do occur. Using the basic concepts of HRA, an evolving group of methodologies are used to meet various industry needs. Determining which methodology or combination of techniques will provide a quality human reliability assessment is a key element to developing effective strategies for understanding and dealing with risks caused by human errors. There are a number of concerns and difficulties in "tailoring" a Human Reliability Assessment (HRA) for different industries. Although a variety of HRA methodologies are available to analyze human error events, determining the most appropriate tools to provide the most useful results can depend on industry specific cultures and requirements. Methodology selection may be based on a variety of factors that include: 1) how people act and react in different industries, 2) expectations based on industry standards, 3) factors that influence how the human errors could occur such as tasks, tools, environment, workplace, support, training and procedure, 4) type and availability of data, 5) how the industry views risk & reliability, and 6) types of emergencies, contingencies and routine tasks. Other considerations for methodology selection should be based on what information is needed from the assessment. If the principal concern is determination of the primary risk factors contributing to the potential human error, a more detailed analysis method may be employed versus a requirement to provide a numerical value as part of a probabilistic risk assessment. Industries involved with humans operating large equipment or transport systems (ex. railroads or airlines) would have more need to address the man machine interface than medical workers administering medications. Human error occurs in every industry; in most cases the consequences are relatively benign and occasionally beneficial. In cases where the results can have disastrous consequences, the use of Human Reliability techniques to identify and classify the risk of human errors allows a company more opportunities to mitigate or eliminate these types of risks and prevent costly tragedies.

Cyber Risk Management for Critical Infrastructure: A Risk Analysis Model and Three Case Studies.

PubMed

Paté-Cornell, M-Elisabeth; Kuypers, Marshall; Smith, Matthew; Keller, Philip

2018-02-01

Managing cyber security in an organization involves allocating the protection budget across a spectrum of possible options. This requires assessing the benefits and the costs of these options. The risk analyses presented here are statistical when relevant data are available, and system-based for high-consequence events that have not happened yet. This article presents, first, a general probabilistic risk analysis framework for cyber security in an organization to be specified. It then describes three examples of forward-looking analyses motivated by recent cyber attacks. The first one is the statistical analysis of an actual database, extended at the upper end of the loss distribution by a Bayesian analysis of possible, high-consequence attack scenarios that may happen in the future. The second is a systems analysis of cyber risks for a smart, connected electric grid, showing that there is an optimal level of connectivity. The third is an analysis of sequential decisions to upgrade the software of an existing cyber security system or to adopt a new one to stay ahead of adversaries trying to find their way in. The results are distributions of losses to cyber attacks, with and without some considered countermeasures in support of risk management decisions based both on past data and anticipated incidents. © 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.

Porphyry copper assessment of the Tethys region of western and southern Asia: Chapter V in Global mineral resource assessment

USGS Publications Warehouse

Zürcher, Lukas; Bookstrom, Arthur A.; Hammarstrom, Jane M.; Mars, John C.; Ludington, Stephen; Zientek, Michael L.; Dunlap, Pamela; Wallis, John C.; Drew, Lawrence J.; Sutphin, David M.; Berger, Byron R.; Herrington, Richard J.; Billa, Mario; Kuşcu, Ilkay; Moon, Charles J.; Richards, Jeremy P.; Zientek, Michael L.; Hammarstrom, Jane M.; Johnson, Kathleen M.

2015-11-18

The assessment estimates that the Tethys region contains 47 undiscovered deposits within 1 kilometer of the surface. Probabilistic estimates of numbers of undiscovered deposits were combined with grade and tonnage models in a Monte Carlo simulation to estimate probable amounts of contained metal. The 47 undiscovered deposits are estimated to contain a mean of 180 million metric tons (Mt) of copper distributed among the 18 tracts for which probabilistic estimates were made, in addition to the 62 Mt of copper already identified in the 42 known porphyry deposits in the study area. Results of Monte Carlo simulations show that 80 percent of the estimated undiscovered porphyry copper resources in the Tethys region are located in four tracts or sub-tracts.

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.

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

Seismic, high wind, tornado, and probabilistic risk assessments of the High Flux Isotope Reactor

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

Harris, S.P.; Stover, R.L.; Hashimoto, P.S.

1989-01-01

Natural phenomena analyses were performed on the High Flux Isotope Reactor (HFIR) Deterministic and probabilistic evaluations were made to determine the risks resulting from earthquakes, high winds, and tornadoes. Analytic methods in conjunction with field evaluations and an earthquake experience data base evaluation methods were used to provide more realistic results in a shorter amount of time. Plant modifications completed in preparation for HFIR restart and potential future enhancements are discussed. 5 figs.

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.

Development of probabilistic internal dosimetry computer code

NASA Astrophysics Data System (ADS)

Noh, Siwan; Kwon, Tae-Eun; Lee, Jai-Ki

2017-02-01

Internal radiation dose assessment involves biokinetic models, the corresponding parameters, measured data, and many assumptions. Every component considered in the internal dose assessment has its own uncertainty, which is propagated in the intake activity and internal dose estimates. For research or scientific purposes, and for retrospective dose reconstruction for accident scenarios occurring in workplaces having a large quantity of unsealed radionuclides, such as nuclear power plants, nuclear fuel cycle facilities, and facilities in which nuclear medicine is practiced, a quantitative uncertainty assessment of the internal dose is often required. However, no calculation tools or computer codes that incorporate all the relevant processes and their corresponding uncertainties, i.e., from the measured data to the committed dose, are available. Thus, the objective of the present study is to develop an integrated probabilistic internal-dose-assessment computer code. First, the uncertainty components in internal dosimetry are identified, and quantitative uncertainty data are collected. Then, an uncertainty database is established for each component. In order to propagate these uncertainties in an internal dose assessment, a probabilistic internal-dose-assessment system that employs the Bayesian and Monte Carlo methods. Based on the developed system, we developed a probabilistic internal-dose-assessment code by using MATLAB so as to estimate the dose distributions from the measured data with uncertainty. Using the developed code, we calculated the internal dose distribution and statistical values ( e.g. the 2.5th, 5th, median, 95th, and 97.5th percentiles) for three sample scenarios. On the basis of the distributions, we performed a sensitivity analysis to determine the influence of each component on the resulting dose in order to identify the major component of the uncertainty in a bioassay. The results of this study can be applied to various situations. In cases of severe internal exposure, the causation probability of a deterministic health effect can be derived from the dose distribution, and a high statistical value ( e.g., the 95th percentile of the distribution) can be used to determine the appropriate intervention. The distribution-based sensitivity analysis can also be used to quantify the contribution of each factor to the dose uncertainty, which is essential information for reducing and optimizing the uncertainty in the internal dose assessment. Therefore, the present study can contribute to retrospective dose assessment for accidental internal exposure scenarios, as well as to internal dose monitoring optimization and uncertainty reduction.

DESIGNING ENVIRONMENTAL MONITORING DATABASES FOR STATISTIC ASSESSMENT

EPA Science Inventory

Databases designed for statistical analyses have characteristics that distinguish them from databases intended for general use. EMAP uses a probabilistic sampling design to collect data to produce statistical assessments of environmental conditions. In addition to supporting the ...

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.

SCAP: a new methodology for safety management based on feedback from credible accident-probabilistic fault tree analysis system.

PubMed

Khan, F I; Iqbal, A; Ramesh, N; Abbasi, S A

2001-10-12

As it is conventionally done, strategies for incorporating accident--prevention measures in any hazardous chemical process industry are developed on the basis of input from risk assessment. However, the two steps-- risk assessment and hazard reduction (or safety) measures--are not linked interactively in the existing methodologies. This prevents a quantitative assessment of the impacts of safety measures on risk control. We have made an attempt to develop a methodology in which risk assessment steps are interactively linked with implementation of safety measures. The resultant system tells us the extent of reduction of risk by each successive safety measure. It also tells based on sophisticated maximum credible accident analysis (MCAA) and probabilistic fault tree analysis (PFTA) whether a given unit can ever be made 'safe'. The application of the methodology has been illustrated with a case study.

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.

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

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

Longitudinal temporal and probabilistic prediction of survival in a cohort of patients with advanced cancer.

PubMed

Perez-Cruz, Pedro E; Dos Santos, Renata; Silva, Thiago Buosi; Crovador, Camila Souza; Nascimento, Maria Salete de Angelis; Hall, Stacy; Fajardo, Julieta; Bruera, Eduardo; Hui, David

2014-11-01

Survival prognostication is important during the end of life. The accuracy of clinician prediction of survival (CPS) over time has not been well characterized. The aims of the study were to examine changes in prognostication accuracy during the last 14 days of life in a cohort of patients with advanced cancer admitted to two acute palliative care units and to compare the accuracy between the temporal and probabilistic approaches. Physicians and nurses prognosticated survival daily for cancer patients in two hospitals until death/discharge using two prognostic approaches: temporal and probabilistic. We assessed accuracy for each method daily during the last 14 days of life comparing accuracy at Day -14 (baseline) with accuracy at each time point using a test of proportions. A total of 6718 temporal and 6621 probabilistic estimations were provided by physicians and nurses for 311 patients, respectively. Median (interquartile range) survival was 8 days (4-20 days). Temporal CPS had low accuracy (10%-40%) and did not change over time. In contrast, probabilistic CPS was significantly more accurate (P < .05 at each time point) but decreased close to death. Probabilistic CPS was consistently more accurate than temporal CPS over the last 14 days of life; however, its accuracy decreased as patients approached death. Our findings suggest that better tools to predict impending death are necessary. Copyright © 2014 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

A study of discrete control signal fault conditions in the shuttle DPS

NASA Technical Reports Server (NTRS)

Reddi, S. S.; Retter, C. T.

1976-01-01

An analysis of the effects of discrete failures on the data processing subsystem is presented. A functional description of each discrete together with a list of software modules that use this discrete are included. A qualitative description of the consequences that may ensue due to discrete failures is given followed by a probabilistic reliability analysis of the data processing subsystem. Based on the investigation conducted, recommendations were made to improve the reliability of the subsystem.

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).

Spatially explicit risk assessment of an estuarine fish in Barataria Bay, Louisiana, following the Deepwater Horizon Oil spill: evaluating tradeoffs in model complexity and parsimony

EPA Science Inventory

As ecological risk assessments (ERA) move beyond organism-based determinations towards probabilistic population-level assessments, model complexity must be evaluated against the goals of the assessment, the information available to parameterize components with minimal dependence ...

Using water quality to assess ecological condition in the St. Marys River and Huron-Erie Corridor

EPA Science Inventory

The St. Marys River and Huron-Erie-Corridor were assessed by EPA for the first time in 2014-2016 as part of the National Coastal Condition Assessment (NCCA). NCCA uses a probabilistic survey design to allow unbiased assessment of ecological condition across the entire Great Lakes...

Population viability assessment of salmonids by using probabilistic networks

Treesearch

Danny C. Lee; Bruce E. Rieman

1997-01-01

Public agencies are being asked to quantitatively assess the impact of land management activities on sensitive populations of salmonids. To aid in these assessments, we developed a Bayesian viability assessment procedure (BayVAM) to help characterize land use risks to salmonids in the Pacific Northwest. This procedure incorporates a hybrid approach to viability...

Trait-Dependent Biogeography: (Re)Integrating Biology into Probabilistic Historical Biogeographical Models.

PubMed

Sukumaran, Jeet; Knowles, L Lacey

2018-06-01

The development of process-based probabilistic models for historical biogeography has transformed the field by grounding it in modern statistical hypothesis testing. However, most of these models abstract away biological differences, reducing species to interchangeable lineages. We present here the case for reintegration of biology into probabilistic historical biogeographical models, allowing a broader range of questions about biogeographical processes beyond ancestral range estimation or simple correlation between a trait and a distribution pattern, as well as allowing us to assess how inferences about ancestral ranges themselves might be impacted by differential biological traits. We show how new approaches to inference might cope with the computational challenges resulting from the increased complexity of these trait-based historical biogeographical models. Copyright © 2018 Elsevier Ltd. All rights reserved.

Lung Cancer Assistant: a hybrid clinical decision support application for lung cancer care.

PubMed

Sesen, M Berkan; Peake, Michael D; Banares-Alcantara, Rene; Tse, Donald; Kadir, Timor; Stanley, Roz; Gleeson, Fergus; Brady, Michael

2014-09-06

Multidisciplinary team (MDT) meetings are becoming the model of care for cancer patients worldwide. While MDTs have improved the quality of cancer care, the meetings impose substantial time pressure on the members, who generally attend several such MDTs. We describe Lung Cancer Assistant (LCA), a clinical decision support (CDS) prototype designed to assist the experts in the treatment selection decisions in the lung cancer MDTs. A novel feature of LCA is its ability to provide rule-based and probabilistic decision support within a single platform. The guideline-based CDS is based on clinical guideline rules, while the probabilistic CDS is based on a Bayesian network trained on the English Lung Cancer Audit Database (LUCADA). We assess rule-based and probabilistic recommendations based on their concordances with the treatments recorded in LUCADA. Our results reveal that the guideline rule-based recommendations perform well in simulating the recorded treatments with exact and partial concordance rates of 0.57 and 0.79, respectively. On the other hand, the exact and partial concordance rates achieved with probabilistic results are relatively poorer with 0.27 and 0.76. However, probabilistic decision support fulfils a complementary role in providing accurate survival estimations. Compared to recorded treatments, both CDS approaches promote higher resection rates and multimodality treatments.

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

The Global Tsunami Model (GTM)

NASA Astrophysics Data System (ADS)

Thio, H. K.; Løvholt, F.; Harbitz, C. B.; Polet, J.; Lorito, S.; Basili, R.; Volpe, M.; Romano, F.; Selva, J.; Piatanesi, A.; Davies, G.; Griffin, J.; Baptista, M. A.; Omira, R.; Babeyko, A. Y.; Power, W. L.; Salgado Gálvez, M.; Behrens, J.; Yalciner, A. C.; Kanoglu, U.; Pekcan, O.; Ross, S.; Parsons, T.; LeVeque, R. J.; Gonzalez, F. I.; Paris, R.; Shäfer, A.; Canals, M.; Fraser, S. A.; Wei, Y.; Weiss, R.; Zaniboni, F.; Papadopoulos, G. A.; Didenkulova, I.; Necmioglu, O.; Suppasri, A.; Lynett, P. J.; Mokhtari, M.; Sørensen, M.; von Hillebrandt-Andrade, C.; Aguirre Ayerbe, I.; Aniel-Quiroga, Í.; Guillas, S.; Macias, J.

2016-12-01

The large tsunami disasters of the last two decades have highlighted the need for a thorough understanding of the risk posed by relatively infrequent but disastrous tsunamis and the importance of a comprehensive and consistent methodology for quantifying the hazard. In the last few years, several methods for probabilistic tsunami hazard analysis have been developed and applied to different parts of the world. In an effort to coordinate and streamline these activities and make progress towards implementing the Sendai Framework of Disaster Risk Reduction (SFDRR) we have initiated a Global Tsunami Model (GTM) working group with the aim of i) enhancing our understanding of tsunami hazard and risk on a global scale and developing standards and guidelines for it, ii) providing a portfolio of validated tools for probabilistic tsunami hazard and risk assessment at a range of scales, and iii) developing a global tsunami hazard reference model. This GTM initiative has grown out of the tsunami component of the Global Assessment of Risk (GAR15), which has resulted in an initial global model of probabilistic tsunami hazard and risk. Started as an informal gathering of scientists interested in advancing tsunami hazard analysis, the GTM is currently in the process of being formalized through letters of interest from participating institutions. The initiative has now been endorsed by the United Nations International Strategy for Disaster Reduction (UNISDR) and the World Bank's Global Facility for Disaster Reduction and Recovery (GFDRR). We will provide an update on the state of the project and the overall technical framework, and discuss the technical issues that are currently being addressed, including earthquake source recurrence models, the use of aleatory variability and epistemic uncertainty, and preliminary results for a probabilistic global hazard assessment, which is an update of the model included in UNISDR GAR15.

The Global Tsunami Model (GTM)

NASA Astrophysics Data System (ADS)

Lorito, S.; Basili, R.; Harbitz, C. B.; Løvholt, F.; Polet, J.; Thio, H. K.

2017-12-01

The tsunamis occurred worldwide in the last two decades have highlighted the need for a thorough understanding of the risk posed by relatively infrequent but often disastrous tsunamis and the importance of a comprehensive and consistent methodology for quantifying the hazard. In the last few years, several methods for probabilistic tsunami hazard analysis have been developed and applied to different parts of the world. In an effort to coordinate and streamline these activities and make progress towards implementing the Sendai Framework of Disaster Risk Reduction (SFDRR) we have initiated a Global Tsunami Model (GTM) working group with the aim of i) enhancing our understanding of tsunami hazard and risk on a global scale and developing standards and guidelines for it, ii) providing a portfolio of validated tools for probabilistic tsunami hazard and risk assessment at a range of scales, and iii) developing a global tsunami hazard reference model. This GTM initiative has grown out of the tsunami component of the Global Assessment of Risk (GAR15), which has resulted in an initial global model of probabilistic tsunami hazard and risk. Started as an informal gathering of scientists interested in advancing tsunami hazard analysis, the GTM is currently in the process of being formalized through letters of interest from participating institutions. The initiative has now been endorsed by the United Nations International Strategy for Disaster Reduction (UNISDR) and the World Bank's Global Facility for Disaster Reduction and Recovery (GFDRR). We will provide an update on the state of the project and the overall technical framework, and discuss the technical issues that are currently being addressed, including earthquake source recurrence models, the use of aleatory variability and epistemic uncertainty, and preliminary results for a probabilistic global hazard assessment, which is an update of the model included in UNISDR GAR15.

The Global Tsunami Model (GTM)

NASA Astrophysics Data System (ADS)

Løvholt, Finn

2017-04-01

The large tsunami disasters of the last two decades have highlighted the need for a thorough understanding of the risk posed by relatively infrequent but disastrous tsunamis and the importance of a comprehensive and consistent methodology for quantifying the hazard. In the last few years, several methods for probabilistic tsunami hazard analysis have been developed and applied to different parts of the world. In an effort to coordinate and streamline these activities and make progress towards implementing the Sendai Framework of Disaster Risk Reduction (SFDRR) we have initiated a Global Tsunami Model (GTM) working group with the aim of i) enhancing our understanding of tsunami hazard and risk on a global scale and developing standards and guidelines for it, ii) providing a portfolio of validated tools for probabilistic tsunami hazard and risk assessment at a range of scales, and iii) developing a global tsunami hazard reference model. This GTM initiative has grown out of the tsunami component of the Global Assessment of Risk (GAR15), which has resulted in an initial global model of probabilistic tsunami hazard and risk. Started as an informal gathering of scientists interested in advancing tsunami hazard analysis, the GTM is currently in the process of being formalized through letters of interest from participating institutions. The initiative has now been endorsed by the United Nations International Strategy for Disaster Reduction (UNISDR) and the World Bank's Global Facility for Disaster Reduction and Recovery (GFDRR). We will provide an update on the state of the project and the overall technical framework, and discuss the technical issues that are currently being addressed, including earthquake source recurrence models, the use of aleatory variability and epistemic uncertainty, and preliminary results for a probabilistic global hazard assessment, which is an update of the model included in UNISDR GAR15.

The Use of Probabilistic Methods to Evaluate the Systems Impact of Component Design Improvements on Large Turbofan Engines

NASA Technical Reports Server (NTRS)

Packard, Michael H.

2002-01-01

Probabilistic Structural Analysis (PSA) is now commonly used for predicting the distribution of time/cycles to failure of turbine blades and other engine components. These distributions are typically based on fatigue/fracture and creep failure modes of these components. Additionally, reliability analysis is used for taking test data related to particular failure modes and calculating failure rate distributions of electronic and electromechanical components. How can these individual failure time distributions of structural, electronic and electromechanical component failure modes be effectively combined into a top level model for overall system evaluation of component upgrades, changes in maintenance intervals, or line replaceable unit (LRU) redesign? This paper shows an example of how various probabilistic failure predictions for turbine engine components can be evaluated and combined to show their effect on overall engine performance. A generic model of a turbofan engine was modeled using various Probabilistic Risk Assessment (PRA) tools (Quantitative Risk Assessment Software (QRAS) etc.). Hypothetical PSA results for a number of structural components along with mitigation factors that would restrict the failure mode from propagating to a Loss of Mission (LOM) failure were used in the models. The output of this program includes an overall failure distribution for LOM of the system. The rank and contribution to the overall Mission Success (MS) is also given for each failure mode and each subsystem. This application methodology demonstrates the effectiveness of PRA for assessing the performance of large turbine engines. Additionally, the effects of system changes and upgrades, the application of different maintenance intervals, inclusion of new sensor detection of faults and other upgrades were evaluated in determining overall turbine engine reliability.

Framework for modelling the cost-effectiveness of systemic interventions aimed to reduce youth delinquency.

PubMed

Schawo, Saskia J; van Eeren, Hester; Soeteman, Djira I; van der Veldt, Marie-Christine; Noom, Marc J; Brouwer, Werner; Busschbach, Jan J V; Hakkaart, Leona

2012-12-01

Many interventions initiated within and financed from the health care sector are not necessarily primarily aimed at improving health. This poses important questions regarding the operationalisation of economic evaluations in such contexts. We investigated whether assessing cost-effectiveness using state-of-the-art methods commonly applied in health care evaluations is feasible and meaningful when evaluating interventions aimed at reducing youth delinquency. A probabilistic Markov model was constructed to create a framework for the assessment of the cost-effectiveness of systemic interventions in delinquent youth. For illustrative purposes, Functional Family Therapy (FFT), a systemic intervention aimed at improving family functioning and, primarily, reducing delinquent activity in youths, was compared to Treatment as Usual (TAU). "Criminal activity free years" (CAFYs) were introduced as central outcome measure. Criminal activity may e.g. be based on police contacts or committed crimes. In absence of extensive data and for illustrative purposes the current study based criminal activity on available literature on recidivism. Furthermore, a literature search was performed to deduce the model's structure and parameters. Common cost-effectiveness methodology could be applied to interventions for youth delinquency. Model characteristics and parameters were derived from literature and ongoing trial data. The model resulted in an estimate of incremental costs/CAFY and included long-term effects. Illustrative model results point towards dominance of FFT compared to TAU. Using a probabilistic model and the CAFY outcome measure to assess cost-effectiveness of systemic interventions aimed to reduce delinquency is feasible. However, the model structure is limited to three states and the CAFY measure was defined rather crude. Moreover, as the model parameters are retrieved from literature the model results are illustrative in the absence of empirical data. The current model provides a framework to assess the cost-effectiveness of systemic interventions, while taking into account parameter uncertainty and long-term effectiveness. The framework of the model could be used to assess the cost-effectiveness of systemic interventions alongside (clinical) trial data. Consequently, it is suitable to inform reimbursement decisions, since the value for money of systemic interventions can be demonstrated using a decision analytic model. Future research could be focussed on testing the current model based on extensive empirical data, improving the outcome measure and finding appropriate values for that outcome.

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.

Low-Probability High-Consequence (LPHC) Failure Events in Geologic Carbon Sequestration Pipelines and Wells: Framework for LPHC Risk Assessment Incorporating Spatial Variability of Risk

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

Oldenburg, Curtis M.; Budnitz, Robert J.

If Carbon dioxide Capture and Storage (CCS) is to be effective in mitigating climate change, it will need to be carried out on a very large scale. This will involve many thousands of miles of dedicated high-pressure pipelines in order to transport many millions of tonnes of CO 2 annually, with the CO 2 delivered to many thousands of wells that will inject the CO 2 underground. The new CCS infrastructure could rival in size the current U.S. upstream natural gas pipeline and well infrastructure. This new infrastructure entails hazards for life, health, animals, the environment, and natural resources. Pipelinesmore » are known to rupture due to corrosion, from external forces such as impacts by vehicles or digging equipment, by defects in construction, or from the failure of valves and seals. Similarly, wells are vulnerable to catastrophic failure due to corrosion, cement degradation, or operational mistakes. While most accidents involving pipelines and wells will be minor, there is the inevitable possibility of accidents with very high consequences, especially to public health. The most important consequence of concern is CO 2 release to the environment in concentrations sufficient to cause death by asphyxiation to nearby populations. Such accidents are thought to be very unlikely, but of course they cannot be excluded, even if major engineering effort is devoted (as it will be) to keeping their probability low and their consequences minimized. This project has developed a methodology for analyzing the risks of these rare but high-consequence accidents, using a step-by-step probabilistic methodology. A key difference between risks for pipelines and wells is that the former are spatially distributed along the pipe whereas the latter are confined to the vicinity of the well. Otherwise, the methodology we develop for risk assessment of pipeline and well failures is similar and provides an analysis both of the annual probabilities of accident sequences of concern and of their consequences, and crucially the methodology provides insights into what measures might be taken to mitigate those accident sequences identified as of concern. Mitigating strategies could address reducing the likelihood of an accident sequence of concern, or reducing the consequences, or some combination. The methodology elucidates both local and integrated risks along the pipeline or at the well providing information useful to decision makers at various levels including local (e.g., property owners and town councils), regional (e.g., county and state representatives), and national levels (federal regulators and corporate proponents).« less

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

A probabilistic method for testing and estimating selection differences between populations.

PubMed

He, Yungang; Wang, Minxian; Huang, Xin; Li, Ran; Xu, Hongyang; Xu, Shuhua; Jin, Li

2015-12-01

Human populations around the world encounter various environmental challenges and, consequently, develop genetic adaptations to different selection forces. Identifying the differences in natural selection between populations is critical for understanding the roles of specific genetic variants in evolutionary adaptation. Although numerous methods have been developed to detect genetic loci under recent directional selection, a probabilistic solution for testing and quantifying selection differences between populations is lacking. Here we report the development of a probabilistic method for testing and estimating selection differences between populations. By use of a probabilistic model of genetic drift and selection, we showed that logarithm odds ratios of allele frequencies provide estimates of the differences in selection coefficients between populations. The estimates approximate a normal distribution, and variance can be estimated using genome-wide variants. This allows us to quantify differences in selection coefficients and to determine the confidence intervals of the estimate. Our work also revealed the link between genetic association testing and hypothesis testing of selection differences. It therefore supplies a solution for hypothesis testing of selection differences. This method was applied to a genome-wide data analysis of Han and Tibetan populations. The results confirmed that both the EPAS1 and EGLN1 genes are under statistically different selection in Han and Tibetan populations. We further estimated differences in the selection coefficients for genetic variants involved in melanin formation and determined their confidence intervals between continental population groups. Application of the method to empirical data demonstrated the outstanding capability of this novel approach for testing and quantifying differences in natural selection. © 2015 He et al.; Published by Cold Spring Harbor Laboratory Press.

Accounting for Uncertainties in Strengths of SiC MEMS Parts

NASA Technical Reports Server (NTRS)

Nemeth, Noel; Evans, Laura; Beheim, Glen; Trapp, Mark; Jadaan, Osama; Sharpe, William N., Jr.

2007-01-01

A methodology has been devised for accounting for uncertainties in the strengths of silicon carbide structural components of microelectromechanical systems (MEMS). The methodology enables prediction of the probabilistic strengths of complexly shaped MEMS parts using data from tests of simple specimens. This methodology is intended to serve as a part of a rational basis for designing SiC MEMS, supplementing methodologies that have been borrowed from the art of designing macroscopic brittle material structures. The need for this or a similar methodology arises as a consequence of the fundamental nature of MEMS and the brittle silicon-based materials of which they are typically fabricated. When tested to fracture, MEMS and structural components thereof show wide part-to-part scatter in strength. The methodology involves the use of the Ceramics Analysis and Reliability Evaluation of Structures Life (CARES/Life) software in conjunction with the ANSYS Probabilistic Design System (PDS) software to simulate or predict the strength responses of brittle material components while simultaneously accounting for the effects of variability of geometrical features on the strength responses. As such, the methodology involves the use of an extended version of the ANSYS/CARES/PDS software system described in Probabilistic Prediction of Lifetimes of Ceramic Parts (LEW-17682-1/4-1), Software Tech Briefs supplement to NASA Tech Briefs, Vol. 30, No. 9 (September 2006), page 10. The ANSYS PDS software enables the ANSYS finite-element-analysis program to account for uncertainty in the design-and analysis process. The ANSYS PDS software accounts for uncertainty in material properties, dimensions, and loading by assigning probabilistic distributions to user-specified model parameters and performing simulations using various sampling techniques.

Risk assessment for furan contamination through the food chain in Belgian children.

PubMed

Scholl, Georges; Huybrechts, Inge; Humblet, Marie-France; Scippo, Marie-Louise; De Pauw, Edwin; Eppe, Gauthier; Saegerman, Claude

2012-08-01

Young, old, pregnant and immuno-compromised persons are of great concern for risk assessors as they represent the sub-populations most at risk. The present paper focuses on risk assessment linked to furan exposure in children. Only the Belgian population was considered because individual contamination and consumption data that are required for accurate risk assessment were available for Belgian children only. Two risk assessment approaches, the so-called deterministic and probabilistic, were applied and the results were compared for the estimation of daily intake. A significant difference between the average Estimated Daily Intake (EDI) was underlined between the deterministic (419 ng kg⁻¹ body weight (bw) day⁻¹) and the probabilistic (583 ng kg⁻¹ bw day⁻¹) approaches, which results from the mathematical treatment of the null consumption and contamination data. The risk was characterised by two ways: (1) the classical approach by comparison of the EDI to a reference dose (RfD(chronic-oral)) and (2) the most recent approach, namely the Margin of Exposure (MoE) approach. Both reached similar conclusions: the risk level is not of a major concern, but is neither negligible. In the first approach, only 2.7 or 6.6% (respectively in the deterministic and in the probabilistic way) of the studied population presented an EDI above the RfD(chronic-oral). In the second approach, the percentage of children displaying a MoE above 10,000 and below 100 is 3-0% and 20-0.01% in the deterministic and probabilistic modes, respectively. In addition, children were compared to adults and significant differences between the contamination patterns were highlighted. While major contamination was linked to coffee consumption in adults (55%), no item predominantly contributed to the contamination in children. The most important were soups (19%), dairy products (17%), pasta and rice (11%), fruit and potatoes (9% each).

Analytical resource assessment method for continuous (unconventional) oil and gas accumulations - The "ACCESS" Method

USGS Publications Warehouse

Crovelli, Robert A.; revised by Charpentier, Ronald R.

2012-01-01

The U.S. Geological Survey (USGS) periodically assesses petroleum resources of areas within the United States and the world. The purpose of this report is to explain the development of an analytic probabilistic method and spreadsheet software system called Analytic Cell-Based Continuous Energy Spreadsheet System (ACCESS). The ACCESS method is based upon mathematical equations derived from probability theory. The ACCESS spreadsheet can be used to calculate estimates of the undeveloped oil, gas, and NGL (natural gas liquids) resources in a continuous-type assessment unit. An assessment unit is a mappable volume of rock in a total petroleum system. In this report, the geologic assessment model is defined first, the analytic probabilistic method is described second, and the spreadsheet ACCESS is described third. In this revised version of Open-File Report 00-044 , the text has been updated to reflect modifications that were made to the ACCESS program. Two versions of the program are added as appendixes.

Assessing the Ecological Condition of Streams in a Southeastern Brazilian Basin using a Probabilistic Monitoring Design

EPA Science Inventory

Prompt assessment and management actions are required if we are to reduce the current rapid loss of habitat and biodiversity worldwide. Statistically valid quantification of the biota and habitat condition in water bodies are prerequisites for rigorous assessment of aquatic biodi...

Review of methods for developing probabilistic risk assessments

Treesearch

D. A. Weinstein; P.B. Woodbury

2010-01-01

We describe methodologies currently in use or those under development containing features for estimating fire occurrence risk assessment. We describe two major categories of fire risk assessment tools: those that predict fire under current conditions, assuming that vegetation, climate, and the interactions between them and fire remain relatively similar to their...

Risk assessment for biodiversity conservation planning in Pacific Northwest forests

Treesearch

Becky K. Kerns; Alan Ager

2007-01-01

Risk assessment can provide a robust strategy for landscape-scale planning challenges associated with species conservation and habitat protection in Pacific Northwest forests. We provide an overview of quantitative and probabilistic ecological risk assessment with focus on the application of approaches and influences from the actuarial, financial, and technical...

Using Visual Aids to Improve Communication of Risks about Health: A Review

PubMed Central

Garcia-Retamero, Rocio; Okan, Yasmina; Cokely, Edward T.

2012-01-01

Recent research has shown that patients frequently experience difficulties understanding health-relevant numerical concepts. A prominent example is denominator neglect, or the tendency to pay too much attention to numerators in ratios (e.g., number of treated patients who died) with insufficient attention to denominators (e.g., overall number of treated patients). Denominator neglect can lead to inaccurate assessments of treatment risk reduction and thus can have important consequences for decisions about health. Here, we reviewed a series of studies investigating (1) different factors that can influence patients' susceptibility to denominator neglect in medical decision making—including numerical or language-related abilities; (2) the extent to which denominator neglect can be attenuated by using visual aids; and (3) a factor that moderates the effectiveness of such aids (i.e., graph literacy). The review spans probabilistic national U.S. and German samples, as well as immigrant (i.e., Polish people living in the United Kingdom) and undergraduate samples in Spain. Theoretical and prescriptive implications are discussed. PMID:22629146

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.

Using visual aids to improve communication of risks about health: a review.

PubMed

Garcia-Retamero, Rocio; Okan, Yasmina; Cokely, Edward T

2012-01-01

Recent research has shown that patients frequently experience difficulties understanding health-relevant numerical concepts. A prominent example is denominator neglect, or the tendency to pay too much attention to numerators in ratios (e.g., number of treated patients who died) with insufficient attention to denominators (e.g., overall number of treated patients). Denominator neglect can lead to inaccurate assessments of treatment risk reduction and thus can have important consequences for decisions about health. Here, we reviewed a series of studies investigating (1) different factors that can influence patients' susceptibility to denominator neglect in medical decision making--including numerical or language-related abilities; (2) the extent to which denominator neglect can be attenuated by using visual aids; and (3) a factor that moderates the effectiveness of such aids (i.e., graph literacy). The review spans probabilistic national U.S. and German samples, as well as immigrant (i.e., Polish people living in the United Kingdom) and undergraduate samples in Spain. Theoretical and prescriptive implications are discussed.

Evaluation of power system security and development of transmission pricing method

NASA Astrophysics Data System (ADS)

Kim, Hyungchul

The electric power utility industry is presently undergoing a change towards the deregulated environment. This has resulted in unbundling of generation, transmission and distribution services. The introduction of competition into unbundled electricity services may lead system operation closer to its security boundaries resulting in smaller operating safety margins. The competitive environment is expected to lead to lower price rates for customers and higher efficiency for power suppliers in the long run. Under this deregulated environment, security assessment and pricing of transmission services have become important issues in power systems. This dissertation provides new methods for power system security assessment and transmission pricing. In power system security assessment, the following issues are discussed (1) The description of probabilistic methods for power system security assessment; (2) The computation time of simulation methods; (3) on-line security assessment for operation. A probabilistic method using Monte-Carlo simulation is proposed for power system security assessment. This method takes into account dynamic and static effects corresponding to contingencies. Two different Kohonen networks, Self-Organizing Maps and Learning Vector Quantization, are employed to speed up the probabilistic method. The combination of Kohonen networks and Monte-Carlo simulation can reduce computation time in comparison with straight Monte-Carlo simulation. A technique for security assessment employing Bayes classifier is also proposed. This method can be useful for system operators to make security decisions during on-line power system operation. This dissertation also suggests an approach for allocating transmission transaction costs based on reliability benefits in transmission services. The proposed method shows the transmission transaction cost of reliability benefits when transmission line capacities are considered. The ratio between allocation by transmission line capacity-use and allocation by reliability benefits is computed using the probability of system failure.

Integrated Technology Assessment Center (ITAC) Update

NASA Technical Reports Server (NTRS)

Taylor, J. L.; Neely, M. A.; Curran, F. M.; Christensen, E. R.; Escher, D.; Lovell, N.; Morris, Charles (Technical Monitor)

2002-01-01

The Integrated Technology Assessment Center (ITAC) has developed a flexible systems analysis framework to identify long-term technology needs, quantify payoffs for technology investments, and assess the progress of ASTP-sponsored technology programs in the hypersonics area. For this, ITAC has assembled an experienced team representing a broad sector of the aerospace community and developed a systematic assessment process complete with supporting tools. Concepts for transportation systems are selected based on relevance to the ASTP and integrated concept models (ICM) of these concepts are developed. Key technologies of interest are identified and projections are made of their characteristics with respect to their impacts on key aspects of the specific concepts of interest. Both the models and technology projections are then fed into the ITAC's probabilistic systems analysis framework in ModelCenter. This framework permits rapid sensitivity analysis, single point design assessment, and a full probabilistic assessment of each concept with respect to both embedded and enhancing technologies. Probabilistic outputs are weighed against metrics of interest to ASTP using a multivariate decision making process to provide inputs for technology prioritization within the ASTP. ITAC program is currently finishing the assessment of a two-stage-to-orbit (TSTO), rocket-based combined cycle (RBCC) concept and a TSTO turbine-based combined cycle (TBCC) concept developed by the team with inputs from NASA. A baseline all rocket TSTO concept is also being developed for comparison. Boeing has recently submitted a performance model for their Flexible Aerospace System Solution for Tomorrow (FASST) concept and the ISAT program will provide inputs for a single-stage-to-orbit (SSTO) TBCC based concept in the near-term. Both of these latter concepts will be analyzed within the ITAC framework over the summer. This paper provides a status update of the ITAC program.

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.

Chemical stimulation in unconventional hydrocarbons extraction in the USA: a preliminary environmental risk assessment.

NASA Astrophysics Data System (ADS)

Sutra, Emilie; Spada, Matteo; Burgherr, Peter

2016-04-01

While the exploitation of unconventional resources recently shows an extensive development, the stimulation techniques in use in this domain arouse growing public concerns. Often in the shadow of the disputed hydraulic fracturing process, the matrix acidizing is however a complementary or alternative procedure to enhance the reservoir connectivity. Although acidizing processes are widespread within the traditional hydrocarbons sources exploration, the matrix acidizing does not appear to be commonly used in unconventional hydrocarbons formations due to their low permeability. Nonetheless, this process has been recently applied to the Monterey formation, a shale oil play in California. These stimulation fluids are composed by various chemicals, what represents a matter of concern for public as well as for authorities. As a consequence, a risk assessment implying an exposure and toxicity analysis is needed. Focusing on site surface accidents, e.g., leak of a chemical from a storage tank, we develop in this study concentration scenarios for different exposure pathways to estimate the potential environmental risk associated with the use of specific hazardous substances in the matrix acidizing process for unconventional hydrocarbon reservoirs in the USA. Primary, information about the usage of different hazardous substances have been collected in order to extract the most frequently used chemicals. Afterwards, a probabilistic estimation of the environmental risk associated with the use of these chemicals is carried out by comparing the Predicted Environmental Concentrations (PEC) distribution with the Predicted No Effect Concentrations (PNEC) value. The latter is collected from a literature review, whereas the PEC is estimated as probability distribution concentrations in different environmental compartments (e.g., soil) built upon various predefined accident scenarios. By applying a probabilistic methodology for the concentrations, the level at which the used chemicals could become risky for the environment can be determined. Additionally, these concentration levels are converted into corresponding quantities of hazardous substances in order to discuss implications in terms of safety measures and policy decisions.

Landslide susceptibility mapping along PLUS expressways in Malaysia using probabilistic based model in GIS

NASA Astrophysics Data System (ADS)

Yusof, Norbazlan M.; Pradhan, Biswajeet

2014-06-01

PLUS Berhad holds the concession for a total of 987 km of toll expressways in Malaysia, the longest of which is the North-South Expressway or NSE. Acting as the backbone' of the west coast of the peninsula, the NSE stretches from the Malaysian-Thai border in the north to the border with neighbouring Singapore in the south, linking several major cities and towns along the way. North-South Expressway in Malaysia contributes to the country economic development through trade, social and tourism sector. Presently, the highway is good in terms of its condition and connection to every state but some locations need urgent attention. Stability of slopes at these locations is of most concern as any instability can cause danger to the motorist. In this paper, two study locations have been analysed; they are Gua Tempurung (soil slope) and Jelapang (rock slope) which are obviously having two different characteristics. These locations passed through undulating terrain with steep slopes where landslides are common and the probability of slope instability due to human activities in surrounding areas is high. A combination of twelve (12) landslide conditioning factors database on slope stability such as slope degree and slope aspect were extracted from IFSAR (interoferometric synthetic aperture radar) while landuse, lithology and structural geology were constructed from interpretation of high resolution satellite data from World View II, Quickbird and Ikonos. All this information was analysed in geographic information system (GIS) environment for landslide susceptibility mapping using probabilistic based frequency ratio model. Consequently, information on the slopes such as inventories, condition assessments and maintenance records were assessed through total expressway maintenance management system or better known as TEMAN. The above mentioned system is used by PLUS as an asset management and decision support tools for maintenance activities along the highways as well as for data quality checking and integrity. In this study, TEMAN data were further analysed and subsequently integrated with landslide susceptible map for Gua Tempurung and Jelapang area in Perak.

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

Krier, D. J.; Perry, F. V.

Location, timing, volume, and eruptive style of post-Miocene volcanoes have defined the volcanic hazard significant to a proposed high-level radioactive waste (HLW) and spent nuclear fuel (SNF) repository at Yucca Mountain, Nevada, as a low-probability, high-consequence event. Examination of eruptive centers in the region that may be analogueues to possible future volcanic activity at Yucca Mountain have aided in defining and evaluating the consequence scenarios for intrusion into and eruption above a repository. The probability of a future event intersecting a repository at Yucca Mountain has a mean value of 1.7 x 10{sup -8} per year. This probability comes frommore » the Probabilistic Volcanic Hazard Assessment (PVHA) completed in 1996 and updated to reflect change in repository layout. Since that time, magnetic anomalies representing potential buried volcanic centers have been identified fiom magnetic surveys; however these potential buried centers only slightly increase the probability of an event intersecting the repository. The proposed repository will be located in its central portion of Yucca Mountain at approximately 300m depth. The process for assessing performance of a repository at Yucca Mountain has identified two scenarios for igneous activity that, although having a very low probability of occurrence, could have a significant consequence should an igneous event occur. Either a dike swarm intersecting repository drifts containing waste packages, or a volcanic eruption through the repository could result in release of radioactive material to the accessible environment. Ongoing investigations are assessing the mechanisms and significance of the consequence scenarios. Lathrop Wells Cone ({approx}80,000 yrs), a key analogue for estimating potential future volcanic activity, is the youngest surface expression of apparent waning basaltic volcanism in the region. Cone internal structure, lavas, and ash-fall tephra have been examined to estimate eruptive volume, eruption type, and subsurface disturbance accompanying conduit growth and eruption. The Lathrop Wells volcanic complex has a total volume estimate of approximately 0.1 km{sup 3}. The eruptive products indicate a sequence of initial magmatic fissure fountaining, early Strombolian activity, and a brief hydrovolcanic phase, and violent Strombolian phase(s). Lava flows adjacent to the Lathrop Wells Cone probably were emplaced during the mid-eruptive sequence. Ongoing investigations continue to address the potential hazards of a volcanic event at Yucca Mountain.« less

Altered subjective reward valuation among female heavy marijuana users.

PubMed

Hefner, Kathryn R; Starr, Mark J

2017-02-01

Maladaptive decision-making is a cardinal feature of drug use, contributing to ongoing use, and reflecting alterations in how drug users assess uncertain reward value. Accumulating evidence indicates the consequences of heavy marijuana use are worse for female versus male animals and humans, but research assessing sex differences in reward-related decision-making among marijuana users remains scarce. We examined sex differences in the subjective valuation of certain and uncertain rewards among heavy marijuana users (52; 26 male and 26 female) and controls (52; 26 male and 26 female). We offered male and female heavy marijuana users and controls monetary rewards of certain and uncertain (probabilistic) values. We measured how preferences for uncertain rewards varied by the objective value of those rewards, moderators of reward uncertainty, Marijuana Group and Sex. Men were more sensitive to changes in the objective value of uncertain rewards than women. However, this effect of Sex differed by Marijuana Group. Female heavy marijuana users were more sensitive to changes in uncertain reward value, particularly when the "stakes" were high (i.e., greater difference between potential uncertain rewards), than female controls. Female heavy marijuana users' sensitivity to changes in the value of high stakes uncertain rewards was comparable to male marijuana users and controls. In contrast, male marijuana users' sensitivity to changes in the value of high stakes uncertain rewards did not differ from male controls. These results suggest sex differences in sensitivity to high risk rewards may be one pathway contributing to severer consequences of heavy marijuana use among women. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Altered subjective reward valuation among female heavy marijuana users

PubMed Central

Hefner, Kathryn R.; Starr, Mark. J.

2016-01-01

Maladaptive decision-making is a cardinal feature of drug use, contributing to ongoing use, and reflecting alterations in how drug users assess uncertain reward value. Accumulating evidence indicates the consequences of heavy marijuana use are worse for female versus male animals and humans, but research assessing sex differences in reward-related decision-making among marijuana users remains scarce. We examined sex differences in the subjective valuation of certain and uncertain rewards among heavy marijuana users (52; 26 male and 26 female) and controls (52; 26 male and 26 female). We offered male and female heavy marijuana users and controls monetary rewards of certain and uncertain (probabilistic) values. We measured how preferences for uncertain rewards varied by the objective value of those rewards, moderators of reward uncertainty, marijuana use, and sex. Men were more sensitive to changes in the objective value of uncertain rewards than women. However, this effect of sex differed by marijuana group. Female heavy marijuana users were more sensitive to changes in uncertain reward value, particularly when the ‘stakes’ were high (i.e., greater difference between potential uncertain rewards), than female controls. Female heavy marijuana users’ sensitivity to changes in the value of high stakes uncertain rewards was comparable to male marijuana users and controls. In contrast, male marijuana users’ sensitivity to changes in the value of high stakes uncertain rewards did not differ from male controls. These results suggest sex differences in sensitivity to high risk rewards may be one pathway contributing to severer consequences of heavy marijuana use among women. PMID:27936816

Modeling the effectiveness of oil combating from an ecological perspective--a Bayesian network for the Gulf of Finland; the Baltic Sea.

PubMed

Helle, Inari; Lecklin, Tiina; Jolma, Ari; Kuikka, Sakari

2011-01-15

Maritime traffic poses a major threat to marine ecosystems in the form of oil spills. The Gulf of Finland, the easternmost part of the Baltic Sea, has witnessed a rapid increase in oil transportation during the last 15 years. Should a spill occur, the negative ecological impacts may be reduced by oil combating, the effectiveness of which is, however, strongly dependent on prevailing environmental conditions and available technical resources. This poses increased uncertainty related to ecological consequences of future spills. We developed a probabilistic Bayesian network model that can be used to assess the effectiveness of different oil combating strategies in minimizing the negative effects of oil on six species living in the Gulf of Finland. The model can be used for creating different accident scenarios and assessing the performance of various oil combating actions under uncertainty, which enables its use as a supportive tool in decision-making. While the model is confined to the western Gulf of Finland, the methodology is adaptable to other marine areas facing similar risks and challenges related to oil spills. Copyright © 2010 Elsevier B.V. All rights reserved.

Comparing listeriosis risks in at-risk populations using a user-friendly quantitative microbial risk assessment tool and epidemiological data.

PubMed

Falk, L E; Fader, K A; Cui, D S; Totton, S C; Fazil, A M; Lammerding, A M; Smith, B A

2016-10-01

Although infection by the pathogenic bacterium Listeria monocytogenes is relatively rare, consequences can be severe, with a high case-fatality rate in vulnerable populations. A quantitative, probabilistic risk assessment tool was developed to compare estimates of the number of invasive listeriosis cases in vulnerable Canadian subpopulations given consumption of contaminated ready-to-eat delicatessen meats and hot dogs, under various user-defined scenarios. The model incorporates variability and uncertainty through Monte Carlo simulation. Processes considered within the model include cross-contamination, growth, risk factor prevalence, subpopulation susceptibilities, and thermal inactivation. Hypothetical contamination events were simulated. Results demonstrated varying risk depending on the consumer risk factors and implicated product (turkey delicatessen meat without growth inhibitors ranked highest for this scenario). The majority (80%) of listeriosis cases were predicted in at-risk subpopulations comprising only 20% of the total Canadian population, with the greatest number of predicted cases in the subpopulation with dialysis and/or liver disease. This tool can be used to simulate conditions and outcomes under different scenarios, such as a contamination event and/or outbreak, to inform public health interventions.

III: Use of biomarkers as Risk Indicators in Environmental Risk Assessment of oil based discharges offshore.

PubMed

Sanni, Steinar; Lyng, Emily; Pampanin, Daniela M

2017-06-01

Offshore oil and gas activities are required not to cause adverse environmental effects, and risk based management has been established to meet environmental standards. In some risk assessment schemes, Risk Indicators (RIs) are parameters to monitor the development of risk affecting factors. RIs have not yet been established in the Environmental Risk Assessment procedures for management of oil based discharges offshore. This paper evaluates the usefulness of biomarkers as RIs, based on their properties, existing laboratory biomarker data and assessment methods. Data shows several correlations between oil concentrations and biomarker responses, and assessment principles exist that qualify biomarkers for integration into risk procedures. Different ways that these existing biomarkers and methods can be applied as RIs in a probabilistic risk assessment system when linked with whole organism responses are discussed. This can be a useful approach to integrate biomarkers into probabilistic risk assessment related to oil based discharges, representing a potential supplement to information that biomarkers already provide about environmental impact and risk related to these kind of discharges. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Spatial Assessment of the Current Seismic Hazard State for Hard Rock Underground Mines

NASA Astrophysics Data System (ADS)

Wesseloo, Johan

2018-06-01

Mining-induced seismic hazard assessment is an important component in the management of safety and financial risk in mines. As the seismic hazard is a response to the mining activity, it is non-stationary and variable both in space and time. This paper presents an approach for implementing a probabilistic seismic hazard assessment to assess the current hazard state of a mine. Each of the components of the probabilistic seismic hazard assessment is considered within the context of hard rock underground mines. The focus of this paper is the assessment of the in-mine hazard distribution and does not consider the hazard to nearby public or structures. A rating system and methodologies to present hazard maps, for the purpose of communicating to different stakeholders in the mine, i.e. mine managers, technical personnel and the work force, are developed. The approach allows one to update the assessment with relative ease and within short time periods as new data become available, enabling the monitoring of the spatial and temporal change in the seismic hazard.

Ecohydrology of agroecosystems: probabilistic description of yield reduction risk under limited water availability

NASA Astrophysics Data System (ADS)

Vico, Giulia; Porporato, Amilcare

2013-04-01

Supplemental irrigation represents one of the main strategies to mitigate the effects of climate variability and stabilize yields. Irrigated agriculture currently provides 40% of food production and its relevance is expected to further increase in the near future, in face of the projected alterations of rainfall patterns and increase in food, fiber, and biofuel demand. Because of the significant investments and water requirements involved in irrigation, strategic choices are needed to preserve productivity and profitability, while maintaining a sustainable water management - a nontrivial task given the unpredictability of the rainfall forcing. To facilitate decision making under uncertainty, a widely applicable probabilistic framework is proposed. The occurrence of rainfall events and irrigation applications are linked probabilistically to crop development during the growing season and yields at harvest. Based on these linkages, the probability density function of yields and corresponding probability density function of required irrigation volumes, as well as the probability density function of yields under the most common case of limited water availability are obtained analytically, as a function of irrigation strategy, climate, soil and crop parameters. The full probabilistic description of the frequency of occurrence of yields and water requirements is a crucial tool for decision making under uncertainty, e.g., via expected utility analysis. Furthermore, the knowledge of the probability density function of yield allows us to quantify the yield reduction hydrologic risk. Two risk indices are defined and quantified: the long-term risk index, suitable for long-term irrigation strategy assessment and investment planning, and the real-time risk index, providing a rigorous probabilistic quantification of the emergence of drought conditions during a single growing season in an agricultural setting. Our approach employs relatively few parameters and is thus easily and broadly applicable to different crops and sites, under current and future climate scenarios. Hence, the proposed probabilistic framework provides a quantitative tool to assess the impact of irrigation strategy and water allocation on the risk of not meeting a certain target yield, thus guiding the optimal allocation of water resources for human and environmental needs.

A PROBABILISTIC SURVEY OF SEDIMENT TOXICITY IN WEST COAST ESTUARIES

EPA Science Inventory

A probabalistic survey of coastal condition assessment was conducted in 1999 by participants in US EPA's Environmental Monitoring and Assessment Program (EMAP). The survey targeted estuaries along the outer coasts of Washington, Oregon and California, including the lower Columbi...

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.

Development of probabilistic regional climate scenario in East Asia

NASA Astrophysics Data System (ADS)

Dairaku, K.; Ueno, G.; Ishizaki, N. N.

2015-12-01

Climate information and services for Impacts, Adaptation and Vulnerability (IAV) Assessments are of great concern. In order to develop probabilistic regional climate information that represents the uncertainty in climate scenario experiments in East Asia (CORDEX-EA and Japan), the probability distribution of 2m air temperature was estimated by using developed regression model. The method can be easily applicable to other regions and other physical quantities, and also to downscale to finer-scale dependent on availability of observation dataset. Probabilistic climate information in present (1969-1998) and future (2069-2098) climate was developed using CMIP3 SRES A1b scenarios 21 models and the observation data (CRU_TS3.22 & University of Delaware in CORDEX-EA, NIAES AMeDAS mesh data in Japan). The prototype of probabilistic information in CORDEX-EA and Japan represent the quantified structural uncertainties of multi-model ensemble experiments of climate change scenarios. Appropriate combination of statistical methods and optimization of climate ensemble experiments using multi-General Circulation Models (GCMs) and multi-regional climate models (RCMs) ensemble downscaling experiments are investigated.

Applicability of a neuroprobabilistic integral risk index for the environmental management of polluted areas: a case study.

PubMed

Nadal, Martí; Kumar, Vikas; Schuhmacher, Marta; Domingo, José L

2008-04-01

Recently, we developed a GIS-Integrated Integral Risk Index (IRI) to assess human health risks in areas with presence of environmental pollutants. Contaminants were previously ranked by applying a self-organizing map (SOM) to their characteristics of persistence, bioaccumulation, and toxicity in order to obtain the Hazard Index (HI). In the present study, the original IRI was substantially improved by allowing the entrance of probabilistic data. A neuroprobabilistic HI was developed by combining SOM and Monte Carlo analysis. In general terms, the deterministic and probabilistic HIs followed a similar pattern: polychlorinated biphenyls (PCBs) and light polycyclic aromatic hydrocarbons (PAHs) were the pollutants showing the highest and lowest values of HI, respectively. However, the bioaccumulation value of heavy metals notably increased after considering a probability density function to explain the bioaccumulation factor. To check its applicability, a case study was investigated. The probabilistic integral risk was calculated in the chemical/petrochemical industrial area of Tarragona (Catalonia, Spain), where an environmental program has been carried out since 2002. The risk change between 2002 and 2005 was evaluated on the basis of probabilistic data of the levels of various pollutants in soils. The results indicated that the risk of the chemicals under study did not follow a homogeneous tendency. However, the current levels of pollution do not mean a relevant source of health risks for the local population. Moreover, the neuroprobabilistic HI seems to be an adequate tool to be taken into account in risk assessment processes.

Feasibility study on the use of probabilistic migration modeling in support of exposure assessment from food contact materials.

PubMed

Poças, Maria F; Oliveira, Jorge C; Brandsch, Rainer; Hogg, Timothy

2010-07-01

The use of probabilistic approaches in exposure assessments of contaminants migrating from food packages is of increasing interest but the lack of concentration or migration data is often referred as a limitation. Data accounting for the variability and uncertainty that can be expected in migration, for example, due to heterogeneity in the packaging system, variation of the temperature along the distribution chain, and different time of consumption of each individual package, are required for probabilistic analysis. The objective of this work was to characterize quantitatively the uncertainty and variability in estimates of migration. A Monte Carlo simulation was applied to a typical solution of the Fick's law with given variability in the input parameters. The analysis was performed based on experimental data of a model system (migration of Irgafos 168 from polyethylene into isooctane) and illustrates how important sources of variability and uncertainty can be identified in order to refine analyses. For long migration times and controlled conditions of temperature the affinity of the migrant to the food can be the major factor determining the variability in the migration values (more than 70% of variance). In situations where both the time of consumption and temperature can vary, these factors can be responsible, respectively, for more than 60% and 20% of the variance in the migration estimates. The approach presented can be used with databases from consumption surveys to yield a true probabilistic estimate of exposure.

Verification of recursive probabilistic integration (RPI) method for fatigue life management using non-destructive inspections

NASA Astrophysics Data System (ADS)

Chen, Tzikang J.; Shiao, Michael

2016-04-01

This paper verified a generic and efficient assessment concept for probabilistic fatigue life management. The concept is developed based on an integration of damage tolerance methodology, simulations methods1, 2, and a probabilistic algorithm RPI (recursive probability integration)3-9 considering maintenance for damage tolerance and risk-based fatigue life management. RPI is an efficient semi-analytical probabilistic method for risk assessment subjected to various uncertainties such as the variability in material properties including crack growth rate, initial flaw size, repair quality, random process modeling of flight loads for failure analysis, and inspection reliability represented by probability of detection (POD). In addition, unlike traditional Monte Carlo simulations (MCS) which requires a rerun of MCS when maintenance plan is changed, RPI can repeatedly use a small set of baseline random crack growth histories excluding maintenance related parameters from a single MCS for various maintenance plans. In order to fully appreciate the RPI method, a verification procedure was performed. In this study, MC simulations in the orders of several hundred billions were conducted for various flight conditions, material properties, and inspection scheduling, POD and repair/replacement strategies. Since the MC simulations are time-consuming methods, the simulations were conducted parallelly on DoD High Performance Computers (HPC) using a specialized random number generator for parallel computing. The study has shown that RPI method is several orders of magnitude more efficient than traditional Monte Carlo simulations.

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.

ECOFRAM Terrestrial Draft Report

EPA Pesticide Factsheets

ECOFRAM report describing the concepts for moving from deterministic to probabilistic ecological risk assessments. ECOFRAM included scientific experts from government, academia, contract laboratories, environmental advocacy groups and industry.

Decision-making and evacuation planning for flood risk management in the Netherlands.

PubMed

Kolen, Bas; Helsloot, Ira

2014-07-01

A traditional view of decision-making for evacuation planning is that, given an uncertain threat, there is a deterministic way of defining the best decision. In other words, there is a linear relation between threat, decision, and execution consequences. Alternatives and the impact of uncertainties are not taken into account. This study considers the 'top strategic decision-making' for mass evacuation owing to flooding in the Netherlands. It reveals that the top strategic decision-making process itself is probabilistic because of the decision-makers involved and their crisis managers (as advisers). The paper concludes that deterministic planning is not sufficient, and it recommends probabilistic planning that considers uncertainties in the decision-making process itself as well as other uncertainties, such as forecasts, citizens responses, and the capacity of infrastructure. This results in less optimistic, but more realistic, strategies and a need to pay attention to alternative strategies. © 2014 The Author(s). Disasters © Overseas Development Institute, 2014.

Knowledge-based probabilistic representations of branching ratios in chemical networks: The case of dissociative recombinations

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

Plessis, Sylvain; Carrasco, Nathalie; Pernot, Pascal

Experimental data about branching ratios for the products of dissociative recombination of polyatomic ions are presently the unique information source available to modelers of natural or laboratory chemical plasmas. Yet, because of limitations in the measurement techniques, data for many ions are incomplete. In particular, the repartition of hydrogen atoms among the fragments of hydrocarbons ions is often not available. A consequence is that proper implementation of dissociative recombination processes in chemical models is difficult, and many models ignore invaluable data. We propose a novel probabilistic approach based on Dirichlet-type distributions, enabling modelers to fully account for the available information.more » As an application, we consider the production rate of radicals through dissociative recombination in an ionospheric chemistry model of Titan, the largest moon of Saturn. We show how the complete scheme of dissociative recombination products derived with our method dramatically affects these rates in comparison with the simplistic H-loss mechanism implemented by default in all recent models.« less

The probability heuristics model of syllogistic reasoning.

PubMed

Chater, N; Oaksford, M

1999-03-01

A probability heuristic model (PHM) for syllogistic reasoning is proposed. An informational ordering over quantified statements suggests simple probability based heuristics for syllogistic reasoning. The most important is the "min-heuristic": choose the type of the least informative premise as the type of the conclusion. The rationality of this heuristic is confirmed by an analysis of the probabilistic validity of syllogistic reasoning which treats logical inference as a limiting case of probabilistic inference. A meta-analysis of past experiments reveals close fits with PHM. PHM also compares favorably with alternative accounts, including mental logics, mental models, and deduction as verbal reasoning. Crucially, PHM extends naturally to generalized quantifiers, such as Most and Few, which have not been characterized logically and are, consequently, beyond the scope of current mental logic and mental model theories. Two experiments confirm the novel predictions of PHM when generalized quantifiers are used in syllogistic arguments. PHM suggests that syllogistic reasoning performance may be determined by simple but rational informational strategies justified by probability theory rather than by logic. Copyright 1999 Academic Press.

Knowledge-based probabilistic representations of branching ratios in chemical networks: the case of dissociative recombinations.

PubMed

Plessis, Sylvain; Carrasco, Nathalie; Pernot, Pascal

2010-10-07

Experimental data about branching ratios for the products of dissociative recombination of polyatomic ions are presently the unique information source available to modelers of natural or laboratory chemical plasmas. Yet, because of limitations in the measurement techniques, data for many ions are incomplete. In particular, the repartition of hydrogen atoms among the fragments of hydrocarbons ions is often not available. A consequence is that proper implementation of dissociative recombination processes in chemical models is difficult, and many models ignore invaluable data. We propose a novel probabilistic approach based on Dirichlet-type distributions, enabling modelers to fully account for the available information. As an application, we consider the production rate of radicals through dissociative recombination in an ionospheric chemistry model of Titan, the largest moon of Saturn. We show how the complete scheme of dissociative recombination products derived with our method dramatically affects these rates in comparison with the simplistic H-loss mechanism implemented by default in all recent models.

Relevance and Reason Relations.

PubMed

Skovgaard-Olsen, Niels; Singmann, Henrik; Klauer, Karl Christoph

2017-05-01

This paper examines precursors and consequents of perceived relevance of a proposition A for a proposition C. In Experiment 1, we test Spohn's (2012) assumption that ∆P = P(C|A) - P(C|~A) is a good predictor of ratings of perceived relevance and reason relations, and we examine whether it is a better predictor than the difference measure (P(C|A) - P(C)). In Experiment 2, we examine the effects of relevance on probabilistic coherence in Cruz, Baratgin, Oaksford, and Over's (2015) uncertain "and-to-if" inferences. The results suggest that ∆P predicts perceived relevance and reason relations better than the difference measure and that participants are either less probabilistically coherent in "and-to-if" inferences than initially assumed or that they do not follow P(if A, then C) = P(C|A) ("the Equation"). Results are discussed in light of recent results suggesting that the Equation may not hold under conditions of irrelevance or negative relevance. Copyright © 2016 Cognitive Science Society, Inc.

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.

The $10 trillion value of better information about the transient climate response.

PubMed

Hope, Chris

2015-11-13

How much is better information about climate change worth? Here, I use PAGE09, a probabilistic integrated assessment model, to find the optimal paths of CO(2) emissions over time and to calculate the value of better information about one aspect of climate change, the transient climate response (TCR). Approximately halving the uncertainty range for TCR has a net present value of about $10.3 trillion (year 2005 US$) if accomplished in time for emissions to be adjusted in 2020, falling to $9.7 trillion if accomplished by 2030. Probabilistic integrated assessment modelling is the only method we have for making estimates like these for the value of better information about the science and impacts of climate change. © 2015 The Author(s).

A Model-Based Probabilistic Inversion Framework for Wire Fault Detection Using TDR

NASA Technical Reports Server (NTRS)

Schuet, Stefan R.; Timucin, Dogan A.; Wheeler, Kevin R.

2010-01-01

Time-domain reflectometry (TDR) is one of the standard methods for diagnosing faults in electrical wiring and interconnect systems, with a long-standing history focused mainly on hardware development of both high-fidelity systems for laboratory use and portable hand-held devices for field deployment. While these devices can easily assess distance to hard faults such as sustained opens or shorts, their ability to assess subtle but important degradation such as chafing remains an open question. This paper presents a unified framework for TDR-based chafing fault detection in lossy coaxial cables by combining an S-parameter based forward modeling approach with a probabilistic (Bayesian) inference algorithm. Results are presented for the estimation of nominal and faulty cable parameters from laboratory data.

Safety Issues with Hydrogen as a Vehicle Fuel

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

Cadwallader, Lee Charles; Herring, James Stephen

1999-10-01

This report is an initial effort to identify and evaluate safety issues associated with the use of hydrogen as a vehicle fuel in automobiles. Several forms of hydrogen have been considered: gas, liquid, slush, and hydrides. The safety issues have been discussed, beginning with properties of hydrogen and the phenomenology of hydrogen combustion. Safety-related operating experiences with hydrogen vehicles have been summarized to identify concerns that must be addressed in future design activities and to support probabilistic risk assessment. Also, applicable codes, standards, and regulations pertaining to hydrogen usage and refueling have been identified and are briefly discussed. This reportmore » serves as a safety foundation for any future hydrogen safety work, such as a safety analysis or a probabilistic risk assessment.« less

Safety Issues with Hydrogen as a Vehicle Fuel

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

L. C. Cadwallader; J. S. Herring

1999-09-01

This report is an initial effort to identify and evaluate safety issues associated with the use of hydrogen as a vehicle fuel in automobiles. Several forms of hydrogen have been considered: gas, liquid, slush, and hydrides. The safety issues have been discussed, beginning with properties of hydrogen and the phenomenology of hydrogen combustion. Safety-related operating experiences with hydrogen vehicles have been summarized to identify concerns that must be addressed in future design activities and to support probabilistic risk assessment. Also, applicable codes, standards, and regulations pertaining to hydrogen usage and refueling have been identified and are briefly discussed. This reportmore » serves as a safety foundation for any future hydrogen safety work, such as a safety analysis or a probabilistic risk assessment.« less

Towards a robust framework for Probabilistic Tsunami Hazard Assessment (PTHA) for local and regional tsunami in New Zealand

NASA Astrophysics Data System (ADS)

Mueller, Christof; Power, William; Fraser, Stuart; Wang, Xiaoming

2013-04-01

Probabilistic Tsunami Hazard Assessment (PTHA) is conceptually closely related to Probabilistic Seismic Hazard Assessment (PSHA). The main difference is that PTHA needs to simulate propagation of tsunami waves through the ocean and cannot rely on attenuation relationships, which makes PTHA computationally more expensive. The wave propagation process can be assumed to be linear as long as water depth is much larger than the wave amplitude of the tsunami. Beyond this limit a non-linear scheme has to be employed with significantly higher algorithmic run times. PTHA considering far-field tsunami sources typically uses unit source simulations, and relies on the linearity of the process by later scaling and combining the wave fields of individual simulations to represent the intended earthquake magnitude and rupture area. Probabilistic assessments are typically made for locations offshore but close to the coast. Inundation is calculated only for significantly contributing events (de-aggregation). For local and regional tsunami it has been demonstrated that earthquake rupture complexity has a significant effect on the tsunami amplitude distribution offshore and also on inundation. In this case PTHA has to take variable slip distributions and non-linearity into account. A unit source approach cannot easily be applied. Rupture complexity is seen as an aleatory uncertainty and can be incorporated directly into the rate calculation. We have developed a framework that manages the large number of simulations required for local PTHA. As an initial case study the effect of rupture complexity on tsunami inundation and the statistics of the distribution of wave heights have been investigated for plate-interface earthquakes in the Hawke's Bay region in New Zealand. Assessing the probability that water levels will be in excess of a certain threshold requires the calculation of empirical cumulative distribution functions (ECDF). We compare our results with traditional estimates for tsunami inundation simulations that do not consider rupture complexity. De-aggregation based on moment magnitude alone might not be appropriate, because the hazard posed by any individual event can be underestimated locally if rupture complexity is ignored.

Demonstration of a Probabilistic Technique for the Determination of Economic Viability of Very Large Transport Configurations

NASA Technical Reports Server (NTRS)

Mavris, Dimitri N.

1998-01-01

Over the past few years, modem aircraft design has experienced a paradigm shift from designing for performance to designing for affordability. This report contains a probabilistic approach that will allow traditional deterministic design methods to be extended to account for disciplinary, economic, and technological uncertainty. The probabilistic approach was facilitated by the Fast Probability Integration (FPI) technique; a technique which allows the designer to gather valuable information about the vehicle's behavior in the design space. This technique is efficient for assessing multi-attribute, multi-constraint problems in a more realistic fashion. For implementation purposes, this technique is applied to illustrate how both economic and technological uncertainty associated with a Very Large Transport aircraft concept may be assessed. The assessment is evaluated with the FPI technique to determine the cumulative probability distributions of the design space, as bound by economic objectives and performance constraints. These distributions were compared to established targets for a comparable large capacity aircraft, similar in size to the Boeing 747-400. The conventional baseline configuration design space was determined to be unfeasible and marginally viable, motivating the infusion of advanced technologies, including reductions in drag, specific fuel consumption, wing weight, and Research, Development, Testing, and Evaluation costs. The resulting system design space was qualitatively assessed with technology metric "k" factors. The infusion of technologies shifted the VLT design into regions of feasibility and greater viability. The study also demonstrated a method and relationship by which the impact of new technologies may be assessed in a more system focused approach.

Bayesian networks improve causal environmental assessments for evidence-based policy

EPA Science Inventory

Rule-based weight of evidence approaches to ecological risk assessment may not account for uncertainties and generally lack probabilistic integration of lines of evidence. Bayesian networks allow causal inferences to be made from evidence by including causal knowledge about the p...

Human Reliability Analysis in Support of Risk Assessment for Positive Train Control

DOT National Transportation Integrated Search

2003-06-01

This report describes an approach to evaluating the reliability of human actions that are modeled in a probabilistic risk assessment : (PRA) of train control operations. This approach to human reliability analysis (HRA) has been applied in the case o...

Probabilistic Seismic Risk Model for Western Balkans

NASA Astrophysics Data System (ADS)

Stejskal, Vladimir; Lorenzo, Francisco; Pousse, Guillaume; Radovanovic, Slavica; Pekevski, Lazo; Dojcinovski, Dragi; Lokin, Petar; Petronijevic, Mira; Sipka, Vesna

2010-05-01

A probabilistic seismic risk model for insurance and reinsurance purposes is presented for an area of Western Balkans, covering former Yugoslavia and Albania. This territory experienced many severe earthquakes during past centuries producing significant damage to many population centres in the region. The highest hazard is related to external Dinarides, namely to the collision zone of the Adriatic plate. The model is based on a unified catalogue for the region and a seismic source model consisting of more than 30 zones covering all the three main structural units - Southern Alps, Dinarides and the south-western margin of the Pannonian Basin. A probabilistic methodology using Monte Carlo simulation was applied to generate the hazard component of the model. Unique set of damage functions based on both loss experience and engineering assessments is used to convert the modelled ground motion severity into the monetary loss.

Probability or Reasoning: Current Thinking and Realistic Strategies for Improved Medical Decisions

PubMed Central

2017-01-01

A prescriptive model approach in decision making could help achieve better diagnostic accuracy in clinical practice through methods that are less reliant on probabilistic assessments. Various prescriptive measures aimed at regulating factors that influence heuristics and clinical reasoning could support clinical decision-making process. Clinicians could avoid time-consuming decision-making methods that require probabilistic calculations. Intuitively, they could rely on heuristics to obtain an accurate diagnosis in a given clinical setting. An extensive literature review of cognitive psychology and medical decision-making theory was performed to illustrate how heuristics could be effectively utilized in daily practice. Since physicians often rely on heuristics in realistic situations, probabilistic estimation might not be a useful tool in everyday clinical practice. Improvements in the descriptive model of decision making (heuristics) may allow for greater diagnostic accuracy. PMID:29209469

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.

Evaluation of Horizontal Seismic Hazard of Shahrekord, Iran

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

Amiri, G. Ghodrati; Dehkordi, M. Raeisi; Amrei, S. A. Razavian

2008-07-08

This paper presents probabilistic horizontal seismic hazard assessment of Shahrekord, Iran. It displays the probabilistic estimate of Peak Ground Horizontal Acceleration (PGHA) for the return period of 75, 225, 475 and 2475 years. The output of the probabilistic seismic hazard analysis is based on peak ground acceleration (PGA), which is the most common criterion in designing of buildings. A catalogue of seismic events that includes both historical and instrumental events was developed and covers the period from 840 to 2007. The seismic sources that affect the hazard in Shahrekord were identified within the radius of 150 km and the recurrencemore » relationships of these sources were generated. Finally four maps have been prepared to indicate the earthquake hazard of Shahrekord in the form of iso-acceleration contour lines for different hazard levels by using SEISRISK III software.« less

Probability or Reasoning: Current Thinking and Realistic Strategies for Improved Medical Decisions.

PubMed

Nantha, Yogarabindranath Swarna

2017-11-01

A prescriptive model approach in decision making could help achieve better diagnostic accuracy in clinical practice through methods that are less reliant on probabilistic assessments. Various prescriptive measures aimed at regulating factors that influence heuristics and clinical reasoning could support clinical decision-making process. Clinicians could avoid time-consuming decision-making methods that require probabilistic calculations. Intuitively, they could rely on heuristics to obtain an accurate diagnosis in a given clinical setting. An extensive literature review of cognitive psychology and medical decision-making theory was performed to illustrate how heuristics could be effectively utilized in daily practice. Since physicians often rely on heuristics in realistic situations, probabilistic estimation might not be a useful tool in everyday clinical practice. Improvements in the descriptive model of decision making (heuristics) may allow for greater diagnostic accuracy.

Young children do not succeed in choice tasks that imply evaluating chances.

PubMed

Girotto, Vittorio; Fontanari, Laura; Gonzalez, Michel; Vallortigara, Giorgio; Blaye, Agnès

2016-07-01

Preverbal infants manifest probabilistic intuitions in their reactions to the outcomes of simple physical processes and in their choices. Their ability conflicts with the evidence that, before the age of about 5years, children's verbal judgments do not reveal probability understanding. To assess these conflicting results, three studies tested 3-5-year-olds on choice tasks on which infants perform successfully. The results showed that children of all age groups made optimal choices in tasks that did not require forming probabilistic expectations. In probabilistic tasks, however, only 5-year-olds made optimal choices. Younger children performed at random and/or were guided by superficial heuristics. These results suggest caution in interpreting infants' ability to evaluate chance, and indicate that the development of this ability may not follow a linear trajectory. Copyright © 2016 Elsevier B.V. All rights reserved.

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

Probabilistic health risk assessment for arsenic intake through drinking groundwater in Taiwan's Pingtung Plain

NASA Astrophysics Data System (ADS)

Liang, C. P.; Chen, J. S.

2017-12-01

An abundant and inexpensive supply of groundwater is used to meet drinking, agriculture and aquaculture requirements of the residents in the Pingtung Plain. Long-term groundwater quality monitoring data indicate that the As content in groundwater in the Pingtung Plain exceeds the maximum level of 10 g/L recommended by the World Health Organization (WHO). The situation is further complicated by the fact that only 46.89% of population in the Pingtung Plain has been served with tap water, far below the national average of 92.93%. Considering there is a considerable variation in the measured concentrations, from below the detection limit (<0.1 g/L) to the maximum value of 544 g/L and the consumption rate and body weight of the individual, the conventional approach to conducting a human health risk assessment may be insufficient for health risk management. This study presents a probabilistic risk assessment for inorganic As intake through the consumption of the drinking groundwater by local residents in the Pingtung Plain. The probabilistic risk assessment for inorganic As intake through the consumption of the drinking groundwater is achieved using Monte Carlo simulation technique based on the hazard quotient (HQ) and target cancer risk (TR) established by the U.S. Environmental Protection Agency. This study demonstrates the importance of the individual variability of inorganic As intake through drinking groundwater consumption when evaluating a high exposure sub-group of the population who drink high As content groundwater.

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

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.

Probabilistic risk assessment for CO2 storage in geological formations: robust design and support for decision making under uncertainty

NASA Astrophysics Data System (ADS)

Oladyshkin, Sergey; Class, Holger; Helmig, Rainer; Nowak, Wolfgang

2010-05-01

CO2 storage in geological formations is currently being discussed intensively as a technology for mitigating CO2 emissions. However, any large-scale application requires a thorough analysis of the potential risks. Current numerical simulation models are too expensive for probabilistic risk analysis and for stochastic approaches based on brute-force repeated simulation. Even single deterministic simulations may require parallel high-performance computing. The multiphase flow processes involved are too non-linear for quasi-linear error propagation and other simplified stochastic tools. As an alternative approach, we propose a massive stochastic model reduction based on the probabilistic collocation method. The model response is projected onto a orthogonal basis of higher-order polynomials to approximate dependence on uncertain parameters (porosity, permeability etc.) and design parameters (injection rate, depth etc.). This allows for a non-linear propagation of model uncertainty affecting the predicted risk, ensures fast computation and provides a powerful tool for combining design variables and uncertain variables into one approach based on an integrative response surface. Thus, the design task of finding optimal injection regimes explicitly includes uncertainty, which leads to robust designs of the non-linear system that minimize failure probability and provide valuable support for risk-informed management decisions. We validate our proposed stochastic approach by Monte Carlo simulation using a common 3D benchmark problem (Class et al. Computational Geosciences 13, 2009). A reasonable compromise between computational efforts and precision was reached already with second-order polynomials. In our case study, the proposed approach yields a significant computational speedup by a factor of 100 compared to Monte Carlo simulation. We demonstrate that, due to the non-linearity of the flow and transport processes during CO2 injection, including uncertainty in the analysis leads to a systematic and significant shift of predicted leakage rates towards higher values compared with deterministic simulations, affecting both risk estimates and the design of injection scenarios. This implies that, neglecting uncertainty can be a strong simplification for modeling CO2 injection, and the consequences can be stronger than when neglecting several physical phenomena (e.g. phase transition, convective mixing, capillary forces etc.). The authors would like to thank the German Research Foundation (DFG) for financial support of the project within the Cluster of Excellence in Simulation Technology (EXC 310/1) at the University of Stuttgart. Keywords: polynomial chaos; CO2 storage; multiphase flow; porous media; risk assessment; uncertainty; integrative response surfaces

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...

The Integrated Medical Model - A Risk Assessment and Decision Support Tool for Human Space Flight Missions

NASA Technical Reports Server (NTRS)

Kerstman, Eric; Minard, Charles G.; Saile, Lynn; FreiredeCarvalho, Mary; Myers, Jerry; Walton, Marlei; Butler, Douglas; Lopez, Vilma

2010-01-01

The Integrated Medical Model (IMM) is a decision support tool that is useful to space flight mission planners and medical system designers in assessing risks and optimizing medical systems. The IMM employs an evidence-based, probabilistic risk assessment (PRA) approach within the operational constraints of space flight.

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.

Geological, geomechanical and geostatistical assessment of rockfall hazard in San Quirico Village (Abruzzo, Italy)

NASA Astrophysics Data System (ADS)

Chiessi, Vittorio; D'Orefice, Maurizio; Scarascia Mugnozza, Gabriele; Vitale, Valerio; Cannese, Christian

2010-07-01

This paper describes the results of a rockfall hazard assessment for the village of San Quirico (Abruzzo region, Italy) based on an engineering-geological model. After the collection of geological, geomechanical, and geomorphological data, the rockfall hazard assessment was performed based on two separate approaches: i) simulation of detachment of rock blocks and their downhill movement using a GIS; and ii) application of geostatistical techniques to the analysis of georeferenced observations of previously fallen blocks, in order to assess the probability of arrival of blocks due to potential future collapses. The results show that the trajectographic analysis is significantly influenced by the input parameters, with particular reference to the coefficients of restitution values. In order to solve this problem, the model was calibrated based on repeated field observations. The geostatistical approach is useful because it gives the best estimation of point-source phenomena such as rockfalls; however, the sensitivity of results to basic assumptions, e.g. assessment of variograms and choice of a threshold value, may be problematic. Consequently, interpolations derived from different variograms have been used and compared among them; hence, those showing the lowest errors were adopted. The data sets which were statistically analysed are relevant to both kinetic energy and surveyed rock blocks in the accumulation area. The obtained maps highlight areas susceptible to rock block arrivals, and show that the area accommodating the new settlement of S. Quirico Village has the highest level of hazard according to both probabilistic and deterministic methods.

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.

Potential Future Igneous Activity at Yucca Mountain, Nevada

NASA Astrophysics Data System (ADS)

Cline, M.; Perry, F. V.; Valentine, G. A.; Smistad, E.

2005-12-01

Location, timing, and volumes of post-Miocene volcanic activity, along with expert judgement, provide the basis for assessing the probability of future volcanism intersecting a proposed repository for nuclear waste at Yucca Mountain, Nevada. Analog studies of eruptive centers in the region that may represent the style and extent of possible future igneous activity at Yucca Mountain have aided in defining the consequence scenarios for intrusion into and eruption through a proposed repository. Modeling of magmatic processes related to magma/proposed repository interactions has been used to assess the potential consequences of a future igneous event through a proposed repository at Yucca Mountain. Results of work to date indicate future igneous activity in the Yucca Mountain region has a very low probability of intersecting the proposed repository. Probability of a future event intersecting a proposed repository at Yucca Mountain is approximately 1.7 X 10-8 per year. Since completion of the Probabilistic Volcanic Hazard Assessment (PVHA) in 1996, anomalies representing potential buried volcanic centers have been identified from aeromagnetic surveys. A re-assessment of the hazard is currently underway to evaluate the probability of intersection in light of new information and to estimate the probability of one or more volcanic conduits located in the proposed repository along a dike that intersects the proposed repository. U.S. Nuclear Regulatory Commission regulations for siting and licensing a proposed repository require that the consequences of a disruptive event (igneous event) with annual probability greater than 1 X 10-8 be evaluated. Two consequence scenarios are considered; 1) igneous intrusion-groundwater transport case and 2) volcanic eruptive case. These scenarios equate to a dike or dike swarm intersecting repository drifts containing waste packages, formation of a conduit leading to a volcanic eruption through the repository that carries the contents of the waste packages into the atmosphere, deposition of a tephra sheet, and redistribution of the contaminated ash. In both cases radioactive material is released to the accessible environment either through groundwater transport or through the atmospheric dispersal and deposition. Six Quaternary volcanic centers exist within 20 km of Yucca Mountain. Lathrop Wells cone (LWC), the youngest (approximately 75,000 yrs), is a well-preserved cinder cone with associated flows and tephra sheet that provides an excellent analogue for consequence studies related to future volcanism. Cone, lavas, hydrovolcanic ash, and ash-fall tephra have been examined to estimate eruptive volume and eruption type. LWC ejecta volumes suggest basaltic volcanism may be waning in the Yucca Mountain region.. The eruptive products indicate a sequence of initial fissure fountaining, early Strombolian ash and lapilli deposition forming the scoria cone, a brief hydrovolcanic pulse (possibly limited to the NW sector), and a violent Strombolian phase. Mathematical models have been developed to represent magmatic processes and their consequences on proposed repository performance. These models address dike propagation, magma interaction and flow into drifts, eruption through the proposed repository, and post intrusion/eruption effects. These models continue to be refined to reduce the uncertainty associated with the consequences from a possible future igneous event.

ASSESSING THE ECOLOGICAL CONDITION OF SOUTHEAST U. S. ESTUARIES

EPA Science Inventory

As a means to assess ecological condition, 151 stations located in southeastern estuaries from Cape Henry, Virginia to Biscayne Bay, Florida were sampled by state agencies during the summer of 2000 using a probabilistic design. The design used 8 size classes of estuaries ranging ...

DESIGNING MONITORING AND ASSESSMENT STRATEGIES TO INCLUDE NEARSHORE ECOSYSTEMS OF THE GREAT LAKES

EPA Science Inventory

An expectation for monitoring and assessment of very large aquatic systems is that we can develop a strategy that recognizes and reports on ecologically-important subareas using spatially-stratified, probabilistic sampling designs. Ongoing efforts monitor the main-body, offshore ...

USEPA SHEDS MODEL: METHODOLOGY FOR EXPOSURE ASSESSMENT FOR WOOD PRESERVATIVES

EPA Science Inventory

A physically-based, Monte Carlo probabilistic model (SHEDS-Wood: Stochastic Human Exposure and Dose Simulation model for wood preservatives) has been applied to assess the exposure and dose of children to arsenic (As) and chromium (Cr) from contact with chromated copper arsenat...

Finding Useful Questions: On Bayesian Diagnosticity, Probability, Impact, and Information Gain

ERIC Educational Resources Information Center

Nelson, Jonathan D.

2005-01-01

Several norms for how people should assess a question's usefulness have been proposed, notably Bayesian diagnosticity, information gain (mutual information), Kullback-Liebler distance, probability gain (error minimization), and impact (absolute change). Several probabilistic models of previous experiments on categorization, covariation assessment,…

Use of risk quotient and probabilistic approaches to assess risks of pesticides to birds

EPA Science Inventory

When conducting ecological risk assessments for pesticides, the United States Environmental Protection Agency typically relies upon the risk quotient (RQ). This approach is intended to be conservative in nature, making assumptions related to exposure and effects that are intended...

MODELED ESTIMATES OF CHLORPYRIFOS EXPOSURE AND DOSE FOR THE MINNESOTA AND ARIZONA NHEXAS POPULATIONS

EPA Science Inventory

This paper presents a probabilistic, multimedia, multipathway exposure model and assessment for chlorpyrifos developed as part of the National Human Exposure Assessment Survey (NHEXAS). The model was constructed using available information prior to completion of the NHEXAS stu...

Risk and benefit assessment of potential neurodevelopmental effect resulting from consumption of marine fish from a coastal archipelago in China.

PubMed

Gao, Yi-Xiong; Zhang, Hongxia; Yu, Xinwei; He, Jia-lu; Shang, Xiaohong; Li, Xiaowei; Zhao, Yunfeng; Wu, Yongning

2014-06-04

The aim of this study was to assess net neurodevelopmental effect via maternal consumption of marine fish. A total of thirty-one species were collected from Zhoushan, China. The net IQ point gain was assessed by FAO/WHO deterministic approach and probabilistic computation (if necessary). Results of the deterministic assessment of two samples belonging to Scoliodon sorrakowah showed negative IQ point gain in both common and extreme consumption scenarios (175 and 450 g/week, respectively); the net IQ gain caused by both consumption scenarios of other species were positive. Both consumption scenarios of Scoliodon sorrakowah showed beneficial neurodevelopmental effect according to probabilistic computation (95% CI for mean of net IQ gain: 0.0536-0.0554 and 0.1377-0.1425, respectively). Except for Scoliodon sorrakowah, this study indicates that both consumption scenarios of other studied species would be recommended according to the FAO/WHO approach. There would be no recommendation of consumption scenarios of Scoliodon sorrakowah for the reason for carefulness.

Short Course Introduction to Quantitative Mineral Resource Assessments

USGS Publications Warehouse

Singer, Donald A.

2007-01-01

This is an abbreviated text supplementing the content of three sets of slides used in a short course that has been presented by the author at several workshops. The slides should be viewed in the order of (1) Introduction and models, (2) Delineation and estimation, and (3) Combining estimates and summary. References cited in the slides are listed at the end of this text. The purpose of the three-part form of mineral resource assessments discussed in the accompanying slides is to make unbiased quantitative assessments in a format needed in decision-support systems so that consequences of alternative courses of action can be examined. The three-part form of mineral resource assessments was developed to assist policy makers evaluate the consequences of alternative courses of action with respect to land use and mineral-resource development. The audience for three-part assessments is a governmental or industrial policy maker, a manager of exploration, a planner of regional development, or similar decision-maker. Some of the tools and models presented here will be useful for selection of exploration sites, but that is a side benefit, not the goal. To provide unbiased information, we recommend the three-part form of mineral resource assessments where general locations of undiscovered deposits are delineated from a deposit type's geologic setting, frequency distributions of tonnages and grades of well-explored deposits serve as models of grades and tonnages of undiscovered deposits, and number of undiscovered deposits are estimated probabilistically by type. The internally consistent descriptive, grade and tonnage, deposit density, and economic models used in the design of the three-part form of assessments reduce the chances of biased estimates of the undiscovered resources. What and why quantitative resource assessments: The kind of assessment recommended here is founded in decision analysis in order to provide a framework for making decisions concerning mineral resources under conditions of uncertainty. What this means is that we start with the question of what kinds of questions is the decision maker trying to resolve and what forms of information would aid in resolving these questions. Some applications of mineral resource assessments: To plan and guide exploration programs, to assist in land use planning, to plan the location of infrastructure, to estimate mineral endowment, and to identify deposits that present special environmental challenges. Why not just rank prospects / areas? Need for financial analysis, need for comparison with other land uses, need for comparison with distant tracts of land, need to know how uncertain the estimates are, need for consideration of economic and environmental consequences of possible development. Our goal is to provide unbiased information useful to decision-makers.

Probabilistic, meso-scale flood loss modelling

NASA Astrophysics Data System (ADS)

Kreibich, Heidi; Botto, Anna; Schröter, Kai; Merz, Bruno

2016-04-01

Flood risk analyses are an important basis for decisions on flood risk management and adaptation. However, such analyses are associated with significant uncertainty, even more if changes in risk due to global change are expected. Although uncertainty analysis and probabilistic approaches have received increased attention during the last years, they are still not standard practice for flood risk assessments and even more for flood loss modelling. State of the art in flood loss modelling is still the use of simple, deterministic approaches like stage-damage functions. Novel probabilistic, multi-variate flood loss models have been developed and validated on the micro-scale using a data-mining approach, namely bagging decision trees (Merz et al. 2013). In this presentation we demonstrate and evaluate the upscaling of the approach to the meso-scale, namely on the basis of land-use units. The model is applied in 19 municipalities which were affected during the 2002 flood by the River Mulde in Saxony, Germany (Botto et al. submitted). The application of bagging decision tree based loss models provide a probability distribution of estimated loss per municipality. Validation is undertaken on the one hand via a comparison with eight deterministic loss models including stage-damage functions as well as multi-variate models. On the other hand the results are compared with official loss data provided by the Saxon Relief Bank (SAB). The results show, that uncertainties of loss estimation remain high. Thus, the significant advantage of this probabilistic flood loss estimation approach is that it inherently provides quantitative information about the uncertainty of the prediction. References: Merz, B.; Kreibich, H.; Lall, U. (2013): Multi-variate flood damage assessment: a tree-based data-mining approach. NHESS, 13(1), 53-64. Botto A, Kreibich H, Merz B, Schröter K (submitted) Probabilistic, multi-variable flood loss modelling on the meso-scale with BT-FLEMO. Risk Analysis.

Initial Probabilistic Evaluation of Reactor Pressure Vessel Fracture with Grizzly and Raven

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

Spencer, Benjamin; Hoffman, William; Sen, Sonat

2015-10-01

The Grizzly code is being developed with the goal of creating a general tool that can be applied to study a variety of degradation mechanisms in nuclear power plant components. The first application of Grizzly has been to study fracture in embrittled reactor pressure vessels (RPVs). Grizzly can be used to model the thermal/mechanical response of an RPV under transient conditions that would be observed in a pressurized thermal shock (PTS) scenario. The global response of the vessel provides boundary conditions for local models of the material in the vicinity of a flaw. Fracture domain integrals are computed to obtainmore » stress intensity factors, which can in turn be used to assess whether a fracture would initiate at a pre-existing flaw. These capabilities have been demonstrated previously. A typical RPV is likely to contain a large population of pre-existing flaws introduced during the manufacturing process. This flaw population is characterized stastistically through probability density functions of the flaw distributions. The use of probabilistic techniques is necessary to assess the likelihood of crack initiation during a transient event. This report documents initial work to perform probabilistic analysis of RPV fracture during a PTS event using a combination of the RAVEN risk analysis code and Grizzly. This work is limited in scope, considering only a single flaw with deterministic geometry, but with uncertainty introduced in the parameters that influence fracture toughness. These results are benchmarked against equivalent models run in the FAVOR code. When fully developed, the RAVEN/Grizzly methodology for modeling probabilistic fracture in RPVs will provide a general capability that can be used to consider a wider variety of vessel and flaw conditions that are difficult to consider with current tools. In addition, this will provide access to advanced probabilistic techniques provided by RAVEN, including adaptive sampling and parallelism, which can dramatically decrease run times.« less

Probabilistic maturation reaction norms assessed from mark–recaptures of wild fish in their natural habitat

PubMed Central

Olsen, Esben M; Serbezov, Dimitar; Vøllestad, Leif A

2014-01-01

Reaction norms are a valuable tool in evolutionary biology. Lately, the probabilistic maturation reaction norm approach, describing probabilities of maturing at combinations of age and body size, has been much applied for testing whether phenotypic changes in exploited populations of fish are mainly plastic or involving an evolutionary component. However, due to typical field data limitations, with imperfect knowledge about individual life histories, this demographic method still needs to be assessed. Using 13 years of direct mark–recapture observations on individual growth and maturation in an intensively sampled population of brown trout (Salmo trutta), we show that the probabilistic maturation reaction norm approach may perform well even if the assumption of equal survival of juvenile and maturing fish does not hold. Earlier studies have pointed out that growth effects may confound the interpretation of shifts in maturation reaction norms, because this method in its basic form deals with body size rather than growth. In our case, however, we found that juvenile body size, rather than annual growth, was more strongly associated with maturation. Viewed against earlier studies, our results also underscore the challenges of generalizing life-history patterns among species and populations. PMID:24967078

Developing and Implementing the Data Mining Algorithms in RAVEN

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

Sen, Ramazan Sonat; Maljovec, Daniel Patrick; Alfonsi, Andrea

The RAVEN code is becoming a comprehensive tool to perform probabilistic risk assessment, uncertainty quantification, and verification and validation. The RAVEN code is being developed to support many programs and to provide a set of methodologies and algorithms for advanced analysis. Scientific computer codes can generate enormous amounts of data. To post-process and analyze such data might, in some cases, take longer than the initial software runtime. Data mining algorithms/methods help in recognizing and understanding patterns in the data, and thus discover knowledge in databases. The methodologies used in the dynamic probabilistic risk assessment or in uncertainty and error quantificationmore » analysis couple system/physics codes with simulation controller codes, such as RAVEN. RAVEN introduces both deterministic and stochastic elements into the simulation while the system/physics code model the dynamics deterministically. A typical analysis is performed by sampling values of a set of parameter values. A major challenge in using dynamic probabilistic risk assessment or uncertainty and error quantification analysis for a complex system is to analyze the large number of scenarios generated. Data mining techniques are typically used to better organize and understand data, i.e. recognizing patterns in the data. This report focuses on development and implementation of Application Programming Interfaces (APIs) for different data mining algorithms, and the application of these algorithms to different databases.« less

A Robust Approach to Risk Assessment Based on Species Sensitivity Distributions.

PubMed

Monti, Gianna S; Filzmoser, Peter; Deutsch, Roland C

2018-05-03

The guidelines for setting environmental quality standards are increasingly based on probabilistic risk assessment due to a growing general awareness of the need for probabilistic procedures. One of the commonly used tools in probabilistic risk assessment is the species sensitivity distribution (SSD), which represents the proportion of species affected belonging to a biological assemblage as a function of exposure to a specific toxicant. Our focus is on the inverse use of the SSD curve with the aim of estimating the concentration, HCp, of a toxic compound that is hazardous to p% of the biological community under study. Toward this end, we propose the use of robust statistical methods in order to take into account the presence of outliers or apparent skew in the data, which may occur without any ecological basis. A robust approach exploits the full neighborhood of a parametric model, enabling the analyst to account for the typical real-world deviations from ideal models. We examine two classic HCp estimation approaches and consider robust versions of these estimators. In addition, we also use data transformations in conjunction with robust estimation methods in case of heteroscedasticity. Different scenarios using real data sets as well as simulated data are presented in order to illustrate and compare the proposed approaches. These scenarios illustrate that the use of robust estimation methods enhances HCp estimation. © 2018 Society for Risk Analysis.

Probabilistic Multi-Hazard Assessment of Dry Cask Structures

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

Bencturk, Bora; Padgett, Jamie; Uddin, Rizwan

systems the concrete shall not only provide shielding but insures stability of the upright canister, facilitates anchoring, allows ventilation, and provides physical protection against theft, severe weather and natural (seismic) as well as man-made events (blast incidences). Given the need to remain functional for 40 years or even longer in case of interim storage, the concrete outerpack and the internal canister components need to be evaluated with regard to their long-term ability to perform their intended design functions. Just as evidenced by deteriorating concrete bridges, there are reported visible degradation mechanisms of dry storage systems especially when high corrosive environmentsmore » are considered in maritime locations. The degradation of reinforced concrete is caused by multiple physical and chemical mechanisms, which may be summarized under the heading of environmental aging. The underlying hygro-thermal transport processes are accelerated by irradiation effects, hence creep and shrinkage need to include the effect of chloride penetration, alkali aggregate reaction as well as corrosion of the reinforcing steel. In light of the above, the two main objectives of this project are to (1) develop a probabilistic multi-hazard assessment framework, and (2) through experimental and numerical research perform a comprehensive assessment under combined earthquake loads and aging induced deterioration, which will also provide data for the development and validation of the probabilistic framework.« less

Probabilistic dietary exposure assessment taking into account variability in both amount and frequency of consumption.

PubMed

Slob, Wout

2006-07-01

Probabilistic dietary exposure assessments that are fully based on Monte Carlo sampling from the raw intake data may not be appropriate. This paper shows that the data should first be analysed by using a statistical model that is able to take the various dimensions of food consumption patterns into account. A (parametric) model is discussed that takes into account the interindividual variation in (daily) consumption frequencies, as well as in amounts consumed. Further, the model can be used to include covariates, such as age, sex, or other individual attributes. Some illustrative examples show how this model may be used to estimate the probability of exceeding an (acute or chronic) exposure limit. These results are compared with the results based on directly counting the fraction of observed intakes exceeding the limit value. This comparison shows that the latter method is not adequate, in particular for the acute exposure situation. A two-step approach for probabilistic (acute) exposure assessment is proposed: first analyse the consumption data by a (parametric) statistical model as discussed in this paper, and then use Monte Carlo techniques for combining the variation in concentrations with the variation in consumption (by sampling from the statistical model). This approach results in an estimate of the fraction of the population as a function of the fraction of days at which the exposure limit is exceeded by the individual.

Failed rib region prediction in a human body model during crash events with precrash braking.

PubMed

Guleyupoglu, B; Koya, B; Barnard, R; Gayzik, F S

2018-02-28

The objective of this study is 2-fold. We used a validated human body finite element model to study the predicted chest injury (focusing on rib fracture as a function of element strain) based on varying levels of simulated precrash braking. Furthermore, we compare deterministic and probabilistic methods of rib injury prediction in the computational model. The Global Human Body Models Consortium (GHBMC) M50-O model was gravity settled in the driver position of a generic interior equipped with an advanced 3-point belt and airbag. Twelve cases were investigated with permutations for failure, precrash braking system, and crash severity. The severities used were median (17 kph), severe (34 kph), and New Car Assessment Program (NCAP; 56.4 kph). Cases with failure enabled removed rib cortical bone elements once 1.8% effective plastic strain was exceeded. Alternatively, a probabilistic framework found in the literature was used to predict rib failure. Both the probabilistic and deterministic methods take into consideration location (anterior, lateral, and posterior). The deterministic method is based on a rubric that defines failed rib regions dependent on a threshold for contiguous failed elements. The probabilistic method depends on age-based strain and failure functions. Kinematics between both methods were similar (peak max deviation: ΔX head = 17 mm; ΔZ head = 4 mm; ΔX thorax = 5 mm; ΔZ thorax = 1 mm). Seat belt forces at the time of probabilistic failed region initiation were lower than those at deterministic failed region initiation. The probabilistic method for rib fracture predicted more failed regions in the rib (an analog for fracture) than the deterministic method in all but 1 case where they were equal. The failed region patterns between models are similar; however, there are differences that arise due to stress reduced from element elimination that cause probabilistic failed regions to continue to rise after no deterministic failed region would be predicted. Both the probabilistic and deterministic methods indicate similar trends with regards to the effect of precrash braking; however, there are tradeoffs. The deterministic failed region method is more spatially sensitive to failure and is more sensitive to belt loads. The probabilistic failed region method allows for increased capability in postprocessing with respect to age. The probabilistic failed region method predicted more failed regions than the deterministic failed region method due to force distribution differences.

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.

Global sensitivity analysis, probabilistic calibration, and predictive assessment for the data assimilation linked ecosystem carbon model

DOE PAGES

Safta, C.; Ricciuto, Daniel M.; Sargsyan, Khachik; ...

2015-07-01

In this paper we propose a probabilistic framework for an uncertainty quantification (UQ) study of a carbon cycle model and focus on the comparison between steady-state and transient simulation setups. A global sensitivity analysis (GSA) study indicates the parameters and parameter couplings that are important at different times of the year for quantities of interest (QoIs) obtained with the data assimilation linked ecosystem carbon (DALEC) model. We then employ a Bayesian approach and a statistical model error term to calibrate the parameters of DALEC using net ecosystem exchange (NEE) observations at the Harvard Forest site. The calibration results are employedmore » in the second part of the paper to assess the predictive skill of the model via posterior predictive checks.« less

Probabilistic confidence for decisions based on uncertain reliability estimates

NASA Astrophysics Data System (ADS)

Reid, Stuart G.

2013-05-01

Reliability assessments are commonly carried out to provide a rational basis for risk-informed decisions concerning the design or maintenance of engineering systems and structures. However, calculated reliabilities and associated probabilities of failure often have significant uncertainties associated with the possible estimation errors relative to the 'true' failure probabilities. For uncertain probabilities of failure, a measure of 'probabilistic confidence' has been proposed to reflect the concern that uncertainty about the true probability of failure could result in a system or structure that is unsafe and could subsequently fail. The paper describes how the concept of probabilistic confidence can be applied to evaluate and appropriately limit the probabilities of failure attributable to particular uncertainties such as design errors that may critically affect the dependability of risk-acceptance decisions. This approach is illustrated with regard to the dependability of structural design processes based on prototype testing with uncertainties attributable to sampling variability.

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.

Combining MLC and SVM Classifiers for Learning Based Decision Making: Analysis and Evaluations

PubMed Central

Zhang, Yi; Ren, Jinchang; Jiang, Jianmin

2015-01-01

Maximum likelihood classifier (MLC) and support vector machines (SVM) are two commonly used approaches in machine learning. MLC is based on Bayesian theory in estimating parameters of a probabilistic model, whilst SVM is an optimization based nonparametric method in this context. Recently, it is found that SVM in some cases is equivalent to MLC in probabilistically modeling the learning process. In this paper, MLC and SVM are combined in learning and classification, which helps to yield probabilistic output for SVM and facilitate soft decision making. In total four groups of data are used for evaluations, covering sonar, vehicle, breast cancer, and DNA sequences. The data samples are characterized in terms of Gaussian/non-Gaussian distributed and balanced/unbalanced samples which are then further used for performance assessment in comparing the SVM and the combined SVM-MLC classifier. Interesting results are reported to indicate how the combined classifier may work under various conditions. PMID:26089862

Combining MLC and SVM Classifiers for Learning Based Decision Making: Analysis and Evaluations.

PubMed

Zhang, Yi; Ren, Jinchang; Jiang, Jianmin

2015-01-01

Maximum likelihood classifier (MLC) and support vector machines (SVM) are two commonly used approaches in machine learning. MLC is based on Bayesian theory in estimating parameters of a probabilistic model, whilst SVM is an optimization based nonparametric method in this context. Recently, it is found that SVM in some cases is equivalent to MLC in probabilistically modeling the learning process. In this paper, MLC and SVM are combined in learning and classification, which helps to yield probabilistic output for SVM and facilitate soft decision making. In total four groups of data are used for evaluations, covering sonar, vehicle, breast cancer, and DNA sequences. The data samples are characterized in terms of Gaussian/non-Gaussian distributed and balanced/unbalanced samples which are then further used for performance assessment in comparing the SVM and the combined SVM-MLC classifier. Interesting results are reported to indicate how the combined classifier may work under various conditions.

Assessing the empirical validity of the "take-the-best" heuristic as a model of human probabilistic inference.

PubMed

Bröder, A

2000-09-01

The boundedly rational 'Take-The-Best" heuristic (TTB) was proposed by G. Gigerenzer, U. Hoffrage, and H. Kleinbölting (1991) as a model of fast and frugal probabilistic inferences. Although the simple lexicographic rule proved to be successful in computer simulations, direct empirical demonstrations of its adequacy as a psychological model are lacking because of several methodical problems. In 4 experiments with a total of 210 participants, this question was addressed. Whereas Experiment 1 showed that TTB is not valid as a universal hypothesis about probabilistic inferences, up to 28% of participants in Experiment 2 and 53% of participants in Experiment 3 were classified as TTB users. Experiment 4 revealed that investment costs for information seem to be a relevant factor leading participants to switch to a noncompensatory TTB strategy. The observed individual differences in strategy use imply the recommendation of an idiographic approach to decision-making research.

Grid Inertial Response-Based Probabilistic Determination of Energy Storage System Capacity Under High Solar Penetration

DOE PAGES

Yue, Meng; Wang, Xiaoyu

2015-07-01

It is well-known that responsive battery energy storage systems (BESSs) are an effective means to improve the grid inertial response to various disturbances including the variability of the renewable generation. One of the major issues associated with its implementation is the difficulty in determining the required BESS capacity mainly due to the large amount of inherent uncertainties that cannot be accounted for deterministically. In this study, a probabilistic approach is proposed to properly size the BESS from the perspective of the system inertial response, as an application of probabilistic risk assessment (PRA). The proposed approach enables a risk-informed decision-making processmore » regarding (1) the acceptable level of solar penetration in a given system and (2) the desired BESS capacity (and minimum cost) to achieve an acceptable grid inertial response with a certain confidence level.« less

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.

An analytical probabilistic model of the quality efficiency of a sewer tank

NASA Astrophysics Data System (ADS)

Balistrocchi, Matteo; Grossi, Giovanna; Bacchi, Baldassare

2009-12-01

The assessment of the efficiency of a storm water storage facility devoted to the sewer overflow control in urban areas strictly depends on the ability to model the main features of the rainfall-runoff routing process and the related wet weather pollution delivery. In this paper the possibility of applying the analytical probabilistic approach for developing a tank design method, whose potentials are similar to the continuous simulations, is proved. In the model derivation the quality issues of such devices were implemented. The formulation is based on a Weibull probabilistic model of the main characteristics of the rainfall process and on a power law describing the relationship between the dimensionless storm water cumulative runoff volume and the dimensionless cumulative pollutograph. Following this approach, efficiency indexes were established. The proposed model was verified by comparing its results to those obtained by continuous simulations; satisfactory agreement is shown for the proposed efficiency indexes.

Probabilistic modelling of human exposure to intense sweeteners in Italian teenagers: validation and sensitivity analysis of a probabilistic model including indicators of market share and brand loyalty.

PubMed

Arcella, D; Soggiu, M E; Leclercq, C

2003-10-01

For the assessment of exposure to food-borne chemicals, the most commonly used methods in the European Union follow a deterministic approach based on conservative assumptions. Over the past few years, to get a more realistic view of exposure to food chemicals, risk managers are getting more interested in the probabilistic approach. Within the EU-funded 'Monte Carlo' project, a stochastic model of exposure to chemical substances from the diet and a computer software program were developed. The aim of this paper was to validate the model with respect to the intake of saccharin from table-top sweeteners and cyclamate from soft drinks by Italian teenagers with the use of the software and to evaluate the impact of the inclusion/exclusion of indicators on market share and brand loyalty through a sensitivity analysis. Data on food consumption and the concentration of sweeteners were collected. A food frequency questionnaire aimed at identifying females who were high consumers of sugar-free soft drinks and/or of table top sweeteners was filled in by 3982 teenagers living in the District of Rome. Moreover, 362 subjects participated in a detailed food survey by recording, at brand level, all foods and beverages ingested over 12 days. Producers were asked to provide the intense sweeteners' concentration of sugar-free products. Results showed that consumer behaviour with respect to brands has an impact on exposure assessments. Only probabilistic models that took into account indicators of market share and brand loyalty met the validation criteria.

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.

Maximizing Statistical Power When Verifying Probabilistic Forecasts of Hydrometeorological Events

NASA Astrophysics Data System (ADS)

DeChant, C. M.; Moradkhani, H.

2014-12-01

Hydrometeorological events (i.e. floods, droughts, precipitation) are increasingly being forecasted probabilistically, owing to the uncertainties in the underlying causes of the phenomenon. In these forecasts, the probability of the event, over some lead time, is estimated based on some model simulations or predictive indicators. By issuing probabilistic forecasts, agencies may communicate the uncertainty in the event occurring. Assuming that the assigned probability of the event is correct, which is referred to as a reliable forecast, the end user may perform some risk management based on the potential damages resulting from the event. Alternatively, an unreliable forecast may give false impressions of the actual risk, leading to improper decision making when protecting resources from extreme events. Due to this requisite for reliable forecasts to perform effective risk management, this study takes a renewed look at reliability assessment in event forecasts. Illustrative experiments will be presented, showing deficiencies in the commonly available approaches (Brier Score, Reliability Diagram). Overall, it is shown that the conventional reliability assessment techniques do not maximize the ability to distinguish between a reliable and unreliable forecast. In this regard, a theoretical formulation of the probabilistic event forecast verification framework will be presented. From this analysis, hypothesis testing with the Poisson-Binomial distribution is the most exact model available for the verification framework, and therefore maximizes one's ability to distinguish between a reliable and unreliable forecast. Application of this verification system was also examined within a real forecasting case study, highlighting the additional statistical power provided with the use of the Poisson-Binomial distribution.

Probabilistic Climate Scenario Information for Risk Assessment

NASA Astrophysics Data System (ADS)

Dairaku, K.; Ueno, G.; Takayabu, I.

2014-12-01

Climate information and services for Impacts, Adaptation and Vulnerability (IAV) Assessments are of great concern. In order to develop probabilistic regional climate information that represents the uncertainty in climate scenario experiments in Japan, we compared the physics ensemble experiments using the 60km global atmospheric model of the Meteorological Research Institute (MRI-AGCM) with multi-model ensemble experiments with global atmospheric-ocean coupled models (CMIP3) of SRES A1b scenario experiments. The MRI-AGCM shows relatively good skills particularly in tropics for temperature and geopotential height. Variability in surface air temperature of physical ensemble experiments with MRI-AGCM was within the range of one standard deviation of the CMIP3 model in the Asia region. On the other hand, the variability of precipitation was relatively well represented compared with the variation of the CMIP3 models. Models which show the similar reproducibility in the present climate shows different future climate change. We couldn't find clear relationships between present climate and future climate change in temperature and precipitation. We develop a new method to produce probabilistic information of climate change scenarios by weighting model ensemble experiments based on a regression model (Krishnamurti et al., Science, 1999). The method can be easily applicable to other regions and other physical quantities, and also to downscale to finer-scale dependent on availability of observation dataset. The prototype of probabilistic information in Japan represents the quantified structural uncertainties of multi-model ensemble experiments of climate change scenarios. Acknowledgments: This study was supported by the SOUSEI Program, funded by Ministry of Education, Culture, Sports, Science and Technology, Government of Japan.

On the Mathematical Consequences of Binning Spike Trains.

PubMed

Cessac, Bruno; Le Ny, Arnaud; Löcherbach, Eva

2017-01-01

We initiate a mathematical analysis of hidden effects induced by binning spike trains of neurons. Assuming that the original spike train has been generated by a discrete Markov process, we show that binning generates a stochastic process that is no longer Markov but is instead a variable-length Markov chain (VLMC) with unbounded memory. We also show that the law of the binned raster is a Gibbs measure in the DLR (Dobrushin-Lanford-Ruelle) sense coined in mathematical statistical mechanics. This allows the derivation of several important consequences on statistical properties of binned spike trains. In particular, we introduce the DLR framework as a natural setting to mathematically formalize anticipation, that is, to tell "how good" our nervous system is at making predictions. In a probabilistic sense, this corresponds to condition a process by its future, and we discuss how binning may affect our conclusions on this ability. We finally comment on the possible consequences of binning in the detection of spurious phase transitions or in the detection of incorrect evidence of criticality.

Taiwan industrial cooperation program technology transfer for low-level radioactive waste final disposal - phase I.

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

Knowlton, Robert G.; Cochran, John Russell; Arnold, Bill Walter

2007-01-01

Sandia National Laboratories and the Institute of Nuclear Energy Research, Taiwan have collaborated in a technology transfer program related to low-level radioactive waste (LLW) disposal in Taiwan. Phase I of this program included regulatory analysis of LLW final disposal, development of LLW disposal performance assessment capabilities, and preliminary performance assessments of two potential disposal sites. Performance objectives were based on regulations in Taiwan and comparisons to those in the United States. Probabilistic performance assessment models were constructed based on limited site data using software including GoldSim, BLT-MS, FEHM, and HELP. These software codes provided the probabilistic framework, container degradation, waste-formmore » leaching, groundwater flow, radionuclide transport, and cover infiltration simulation capabilities in the performance assessment. Preliminary performance assessment analyses were conducted for a near-surface disposal system and a mined cavern disposal system at two representative sites in Taiwan. Results of example calculations indicate peak simulated concentrations to a receptor within a few hundred years of LLW disposal, primarily from highly soluble, non-sorbing radionuclides.« less

A performance-based approach to landslide risk analysis

NASA Astrophysics Data System (ADS)

Romeo, R. W.

2009-04-01

An approach for the risk assessment based on a probabilistic analysis of the performance of structures threatened by landslides is shown and discussed. The risk is a possible loss due to the occurrence of a potentially damaging event. Analytically the risk is the probability convolution of hazard, which defines the frequency of occurrence of the event (i.e., the demand), and fragility that defines the capacity of the system to withstand the event given its characteristics (i.e., severity) and those of the exposed goods (vulnerability), that is: Risk=p(D>=d|S,V) The inequality sets a damage (or loss) threshold beyond which the system's performance is no longer met. Therefore a consistent approach to risk assessment should: 1) adopt a probabilistic model which takes into account all the uncertainties of the involved variables (capacity and demand), 2) follow a performance approach based on given loss or damage thresholds. The proposed method belongs to the category of the semi-empirical ones: the theoretical component is given by the probabilistic capacity-demand model; the empirical component is given by the observed statistical behaviour of structures damaged by landslides. Two landslide properties alone are required: the area-extent and the type (or kinematism). All other properties required to determine the severity of landslides (such as depth, speed and frequency) are derived via probabilistic methods. The severity (or intensity) of landslides, in terms of kinetic energy, is the demand of resistance; the resistance capacity is given by the cumulative distribution functions of the limit state performance (fragility functions) assessed via damage surveys and cards compilation. The investigated limit states are aesthetic (of nominal concern alone), functional (interruption of service) and structural (economic and social losses). The damage probability is the probabilistic convolution of hazard (the probability mass function of the frequency of occurrence of given severities) and vulnerability (the probability of a limit state performance be reached, given a certain severity). Then, for each landslide all the exposed goods (structures and infrastructures) within the landslide area and within a buffer (representative of the maximum extension of a landslide given a reactivation), are counted. The risk is the product of the damage probability and the ratio of the exposed goods of each landslide to the whole assets exposed to the same type of landslides. Since the risk is computed numerically and by the same procedure applied to all landslides, it is free from any subjective assessment such as those implied in the qualitative methods.

U.S. Geological Survery Oil and Gas Resource Assessment of the Russian Arctic

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

Donald Gautier; Timothy Klett

2008-12-31

The U.S. Geological Survey (USGS) recently completed a study of undiscovered petroleum resources in the Russian Arctic as a part of its Circum-Arctic Resource Appraisal (CARA), which comprised three broad areas of work: geological mapping, basin analysis, and quantitative assessment. The CARA was a probabilistic, geologically based study that used existing USGS methodology, modified somewhat for the circumstances of the Arctic. New map compilation was used to identify assessment units. The CARA relied heavily on geological analysis and analog modeling, with numerical input consisting of lognormal distributions of sizes and numbers of undiscovered accumulations. Probabilistic results for individual assessment unitsmore » were statistically aggregated, taking geological dependencies into account. The U.S. Department of Energy (DOE) funds were used to support the purchase of crucial seismic data collected in the Barents Sea, East Siberian Sea, and Chukchi Sea for use by USGS in its assessment of the Russian Arctic. DOE funds were also used to purchase a commercial study, which interpreted seismic data from the northern Kara Sea, and for geographic information system (GIS) support of USGS mapping of geological features, province boundaries, total petroleum systems, and assessment units used in the USGS assessment.« less

An integrated modeling approach to support management decisions of coupled groundwater-agricultural systems under multiple uncertainties

NASA Astrophysics Data System (ADS)

Hagos Subagadis, Yohannes; Schütze, Niels; Grundmann, Jens

2015-04-01

The planning and implementation of effective water resources management strategies need an assessment of multiple (physical, environmental, and socio-economic) issues, and often requires new research in which knowledge of diverse disciplines are combined in a unified methodological and operational frameworks. Such integrative research to link different knowledge domains faces several practical challenges. Such complexities are further compounded by multiple actors frequently with conflicting interests and multiple uncertainties about the consequences of potential management decisions. A fuzzy-stochastic multiple criteria decision analysis tool was developed in this study to systematically quantify both probabilistic and fuzzy uncertainties associated with complex hydrosystems management. It integrated physical process-based models, fuzzy logic, expert involvement and stochastic simulation within a general framework. Subsequently, the proposed new approach is applied to a water-scarce coastal arid region water management problem in northern Oman, where saltwater intrusion into a coastal aquifer due to excessive groundwater extraction for irrigated agriculture has affected the aquifer sustainability, endangering associated socio-economic conditions as well as traditional social structure. Results from the developed method have provided key decision alternatives which can serve as a platform for negotiation and further exploration. In addition, this approach has enabled to systematically quantify both probabilistic and fuzzy uncertainties associated with the decision problem. Sensitivity analysis applied within the developed tool has shown that the decision makers' risk aversion and risk taking attitude may yield in different ranking of decision alternatives. The developed approach can be applied to address the complexities and uncertainties inherent in water resources systems to support management decisions, while serving as a platform for stakeholder participation.

Probabilistic eruption forecasting at short and long time scales

NASA Astrophysics Data System (ADS)

Marzocchi, Warner; Bebbington, Mark S.

2012-10-01

Any effective volcanic risk mitigation strategy requires a scientific assessment of the future evolution of a volcanic system and its eruptive behavior. Some consider the onus should be on volcanologists to provide simple but emphatic deterministic forecasts. This traditional way of thinking, however, does not deal with the implications of inherent uncertainties, both aleatoric and epistemic, that are inevitably present in observations, monitoring data, and interpretation of any natural system. In contrast to deterministic predictions, probabilistic eruption forecasting attempts to quantify these inherent uncertainties utilizing all available information to the extent that it can be relied upon and is informative. As with many other natural hazards, probabilistic eruption forecasting is becoming established as the primary scientific basis for planning rational risk mitigation actions: at short-term (hours to weeks or months), it allows decision-makers to prioritize actions in a crisis; and at long-term (years to decades), it is the basic component for land use and emergency planning. Probabilistic eruption forecasting consists of estimating the probability of an eruption event and where it sits in a complex multidimensional time-space-magnitude framework. In this review, we discuss the key developments and features of models that have been used to address the problem.

A Probabilistic Design Method Applied to Smart Composite Structures

NASA Technical Reports Server (NTRS)

Shiao, Michael C.; Chamis, Christos C.

1995-01-01

A probabilistic design method is described and demonstrated using a smart composite wing. Probabilistic structural design incorporates naturally occurring uncertainties including those in constituent (fiber/matrix) material properties, fabrication variables, structure geometry and control-related parameters. Probabilistic sensitivity factors are computed to identify those parameters that have a great influence on a specific structural reliability. Two performance criteria are used to demonstrate this design methodology. The first criterion requires that the actuated angle at the wing tip be bounded by upper and lower limits at a specified reliability. The second criterion requires that the probability of ply damage due to random impact load be smaller than an assigned value. When the relationship between reliability improvement and the sensitivity factors is assessed, the results show that a reduction in the scatter of the random variable with the largest sensitivity factor (absolute value) provides the lowest failure probability. An increase in the mean of the random variable with a negative sensitivity factor will reduce the failure probability. Therefore, the design can be improved by controlling or selecting distribution parameters associated with random variables. This can be implemented during the manufacturing process to obtain maximum benefit with minimum alterations.

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.

75 FR 78777 - Advisory Committee On Reactor Safeguards; Renewal

Federal Register 2010, 2011, 2012, 2013, 2014

2010-12-16

... Committee includes individuals experienced in reactor operations, management; probabilistic risk assessment...: December 10, 2010. Andrew L. Bates, Advisory Committee Management Officer. [FR Doc. 2010-31590 Filed 12-15...

Comparing models for quantitative risk assessment: an application to the European Registry of foreign body injuries in children.

PubMed

Berchialla, Paola; Scarinzi, Cecilia; Snidero, Silvia; Gregori, Dario

2016-08-01

Risk Assessment is the systematic study of decisions subject to uncertain consequences. An increasing interest has been focused on modeling techniques like Bayesian Networks since their capability of (1) combining in the probabilistic framework different type of evidence including both expert judgments and objective data; (2) overturning previous beliefs in the light of the new information being received and (3) making predictions even with incomplete data. In this work, we proposed a comparison among Bayesian Networks and other classical Quantitative Risk Assessment techniques such as Neural Networks, Classification Trees, Random Forests and Logistic Regression models. Hybrid approaches, combining both Classification Trees and Bayesian Networks, were also considered. Among Bayesian Networks, a clear distinction between purely data-driven approach and combination of expert knowledge with objective data is made. The aim of this paper consists in evaluating among this models which best can be applied, in the framework of Quantitative Risk Assessment, to assess the safety of children who are exposed to the risk of inhalation/insertion/aspiration of consumer products. The issue of preventing injuries in children is of paramount importance, in particular where product design is involved: quantifying the risk associated to product characteristics can be of great usefulness in addressing the product safety design regulation. Data of the European Registry of Foreign Bodies Injuries formed the starting evidence for risk assessment. Results showed that Bayesian Networks appeared to have both the ease of interpretability and accuracy in making prediction, even if simpler models like logistic regression still performed well. © The Author(s) 2013.

In-situ monitoring and assessment of post barge-bridge collision damage for minimizing traffic delay and detour : final report.

DOT National Transportation Integrated Search

2016-07-31

This report presents a novel framework for promptly assessing the probability of barge-bridge : collision damage of piers based on probabilistic-based classification through machine learning. The main : idea of the presented framework is to divide th...

A WHOLE-LAKE WATER QUALITY SURVEY OF LAKE OAHE BASED ON A SPATIALLY-BALANCED PROBABILISTIC DESIGN

EPA Science Inventory

Assessing conditions on large bodies of water presets multiple statistical and logistical challenges. As part of the Upper Missouri River Program of the Environmental Monitoring and Assessment Project (EMAP) we surveyed water quality of Lake Oahe in July-August, 2002 using a spat...

CONDITION OF ESTUARIES AND BAYS OF HAWAII FOR 2002: A STATISTICAL SUMMARY

EPA Science Inventory

The National Coastal Assessment (NCA) of US EPA conducted the first probabilistic assessment of the condition of estuarine resources of the main islands of Hawaii in 2002. The study provided condition estimates for both the estuaries and bays of the Hawaiian Island chain, as wel...

Framework for probabilistic flood risk assessment in an Alpine region

NASA Astrophysics Data System (ADS)

Schneeberger, Klaus; Huttenlau, Matthias; Steinberger, Thomas; Achleitner, Stefan; Stötter, Johann

2014-05-01

Flooding is among the natural hazards that regularly cause significant losses to property and human lives. The assessment of flood risk delivers crucial information for all participants involved in flood risk management and especially for local authorities and insurance companies in order to estimate the possible flood losses. Therefore a framework for assessing flood risk has been developed and is introduced with the presented contribution. Flood risk is thereby defined as combination of the probability of flood events and of potential flood damages. The probability of occurrence is described through the spatial and temporal characterisation of flood. The potential flood damages are determined in the course of vulnerability assessment, whereas, the exposure and the vulnerability of the elements at risks are considered. Direct costs caused by flooding with the focus on residential building are analysed. The innovative part of this contribution lies on the development of a framework which takes the probability of flood events and their spatio-temporal characteristic into account. Usually the probability of flooding will be determined by means of recurrence intervals for an entire catchment without any spatial variation. This may lead to a misinterpretation of the flood risk. Within the presented framework the probabilistic flood risk assessment is based on analysis of a large number of spatial correlated flood events. Since the number of historic flood events is relatively small additional events have to be generated synthetically. This temporal extrapolation is realised by means of the method proposed by Heffernan and Tawn (2004). It is used to generate a large number of possible spatial correlated flood events within a larger catchment. The approach is based on the modelling of multivariate extremes considering the spatial dependence structure of flood events. The input for this approach are time series derived from river gauging stations. In a next step the historic and synthetic flood events have to be spatially interpolated from point scale (i.e. river gauges) to the river network. Therefore, topological kriging (Top-kriging) proposed by Skøien et al. (2006) is applied. Top-kriging considers the nested structure of river networks and is therefore suitable to regionalise flood characteristics. Thus, the characteristics of a large number of possible flood events can be transferred to arbitrary locations (e.g. community level) at the river network within a study region. This framework has been used to generate a set of spatial correlated river flood events in the Austrian Federal Province of Vorarlberg. In addition, loss-probability-curves for each community has been calculated based on official inundation maps of public authorities, elements at risks and their vulnerability. One location along the river network within each community refers as interface between the set of flood events and the individual loss-probability relationships for the individual communities. Consequently, every flood event from the historic and synthetic generated dataset can be monetary evaluated. Thus, a time series comprising a large number of flood events and their corresponding monetary losses serves as basis for a probabilistic flood risk assessment. This includes expected annual losses and estimates of extreme event losses, which occur over the course of a certain time period. The gained results are essential decision-support for primary insurers, reinsurance companies and public authorities in order to setup a scale adequate risk management.

Model Verification and Validation Concepts for a Probabilistic Fracture Assessment Model to Predict Cracking of Knife Edge Seals in the Space Shuttle Main Engine High Pressure Oxidizer

NASA Technical Reports Server (NTRS)

Pai, Shantaram S.; Riha, David S.

2013-01-01

Physics-based models are routinely used to predict the performance of engineered systems to make decisions such as when to retire system components, how to extend the life of an aging system, or if a new design will be safe or available. Model verification and validation (V&V) is a process to establish credibility in model predictions. Ideally, carefully controlled validation experiments will be designed and performed to validate models or submodels. In reality, time and cost constraints limit experiments and even model development. This paper describes elements of model V&V during the development and application of a probabilistic fracture assessment model to predict cracking in space shuttle main engine high-pressure oxidizer turbopump knife-edge seals. The objective of this effort was to assess the probability of initiating and growing a crack to a specified failure length in specific flight units for different usage and inspection scenarios. The probabilistic fracture assessment model developed in this investigation combined a series of submodels describing the usage, temperature history, flutter tendencies, tooth stresses and numbers of cycles, fatigue cracking, nondestructive inspection, and finally the probability of failure. The analysis accounted for unit-to-unit variations in temperature, flutter limit state, flutter stress magnitude, and fatigue life properties. The investigation focused on the calculation of relative risk rather than absolute risk between the usage scenarios. Verification predictions were first performed for three units with known usage and cracking histories to establish credibility in the model predictions. Then, numerous predictions were performed for an assortment of operating units that had flown recently or that were projected for future flights. Calculations were performed using two NASA-developed software tools: NESSUS(Registered Trademark) for the probabilistic analysis, and NASGRO(Registered Trademark) for the fracture mechanics analysis. The goal of these predictions was to provide additional information to guide decisions on the potential of reusing existing and installed units prior to the new design certification.

Probabilistic Learning in Junior High School: Investigation of Student Probabilistic Thinking Levels

NASA Astrophysics Data System (ADS)

Kurniasih, R.; Sujadi, I.

2017-09-01

This paper was to investigate level on students’ probabilistic thinking. Probabilistic thinking level is level of probabilistic thinking. Probabilistic thinking is thinking about probabilistic or uncertainty matter in probability material. The research’s subject was students in grade 8th Junior High School students. The main instrument is a researcher and a supporting instrument is probabilistic thinking skills test and interview guidelines. Data was analyzed using triangulation method. The results showed that the level of students probabilistic thinking before obtaining a teaching opportunity at the level of subjective and transitional. After the students’ learning level probabilistic thinking is changing. Based on the results of research there are some students who have in 8th grade level probabilistic thinking numerically highest of levels. Level of students’ probabilistic thinking can be used as a reference to make a learning material and strategy.

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

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

Bozoki, G.E.; Fitzpatrick, R.G.; Bohn, M.P.

This report details the review of the Diablo Canyon Probabilistic Risk Assessment (DCPRA). The study was performed under contract from the Probabilistic Risk Analysis Branch, Office of Nuclear Reactor Research, USNRC by Brookhaven National Laboratory. The DCPRA is a full scope Level I effort and although the review touched on all aspects of the PRA, the internal events and seismic events received the vast majority of the review effort. The report includes a number of independent systems analyses sensitivity studies, importance analyses as well as conclusions on the adequacy of the DCPRA for use in the Diablo Canyon Long Termmore » Seismic Program.« less

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.

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.

Phenomenological constraints on the bulk viscosity of QCD

NASA Astrophysics Data System (ADS)

Paquet, Jean-François; Shen, Chun; Denicol, Gabriel; Jeon, Sangyong; Gale, Charles

2017-11-01

While small at very high temperature, the bulk viscosity of Quantum Chromodynamics is expected to grow in the confinement region. Although its precise magnitude and temperature-dependence in the cross-over region is not fully understood, recent theoretical and phenomenological studies provided evidence that the bulk viscosity can be sufficiently large to have measurable consequences on the evolution of the quark-gluon plasma. In this work, a Bayesian statistical analysis is used to establish probabilistic constraints on the temperature-dependence of bulk viscosity using hadronic measurements from RHIC and LHC.

The probabilistic origin of Bell's inequality

NASA Technical Reports Server (NTRS)

Krenn, Guenther

1994-01-01

The concept of local realism entails certain restrictions concerning the possible occurrence of correlated events. Although these restrictions are inherent in classical physics they have never been noticed until Bell showed in 1964 that general correlations in quantum mechanics can not be interpreted in a classical way. We demonstrate how a local realistic way of thinking about measurement results necessarily leads to limitations with regard to the possible appearance of correlated events. These limitations, which are equivalent to Bell's inequality can be easily formulated as an immediate consequence of our discussion.

Probabilistic dose-response modeling: case study using dichloromethane PBPK model results.

PubMed

Marino, Dale J; Starr, Thomas B

2007-12-01

A revised assessment of dichloromethane (DCM) has recently been reported that examines the influence of human genetic polymorphisms on cancer risks using deterministic PBPK and dose-response modeling in the mouse combined with probabilistic PBPK modeling in humans. This assessment utilized Bayesian techniques to optimize kinetic variables in mice and humans with mean values from posterior distributions used in the deterministic modeling in the mouse. To supplement this research, a case study was undertaken to examine the potential impact of probabilistic rather than deterministic PBPK and dose-response modeling in mice on subsequent unit risk factor (URF) determinations. Four separate PBPK cases were examined based on the exposure regimen of the NTP DCM bioassay. These were (a) Same Mouse (single draw of all PBPK inputs for both treatment groups); (b) Correlated BW-Same Inputs (single draw of all PBPK inputs for both treatment groups except for bodyweights (BWs), which were entered as correlated variables); (c) Correlated BW-Different Inputs (separate draws of all PBPK inputs for both treatment groups except that BWs were entered as correlated variables); and (d) Different Mouse (separate draws of all PBPK inputs for both treatment groups). Monte Carlo PBPK inputs reflect posterior distributions from Bayesian calibration in the mouse that had been previously reported. A minimum of 12,500 PBPK iterations were undertaken, in which dose metrics, i.e., mg DCM metabolized by the GST pathway/L tissue/day for lung and liver were determined. For dose-response modeling, these metrics were combined with NTP tumor incidence data that were randomly selected from binomial distributions. Resultant potency factors (0.1/ED(10)) were coupled with probabilistic PBPK modeling in humans that incorporated genetic polymorphisms to derive URFs. Results show that there was relatively little difference, i.e., <10% in central tendency and upper percentile URFs, regardless of the case evaluated. Independent draws of PBPK inputs resulted in the slightly higher URFs. Results were also comparable to corresponding values from the previously reported deterministic mouse PBPK and dose-response modeling approach that used LED(10)s to derive potency factors. This finding indicated that the adjustment from ED(10) to LED(10) in the deterministic approach for DCM compensated for variability resulting from probabilistic PBPK and dose-response modeling in the mouse. Finally, results show a similar degree of variability in DCM risk estimates from a number of different sources including the current effort even though these estimates were developed using very different techniques. Given the variety of different approaches involved, 95th percentile-to-mean risk estimate ratios of 2.1-4.1 represent reasonable bounds on variability estimates regarding probabilistic assessments of DCM.

Probabilistic Flood Maps to support decision-making: Mapping the Value of Information

NASA Astrophysics Data System (ADS)

Alfonso, L.; Mukolwe, M. M.; Di Baldassarre, G.

2016-02-01

Floods are one of the most frequent and disruptive natural hazards that affect man. Annually, significant flood damage is documented worldwide. Flood mapping is a common preimpact flood hazard mitigation measure, for which advanced methods and tools (such as flood inundation models) are used to estimate potential flood extent maps that are used in spatial planning. However, these tools are affected, largely to an unknown degree, by both epistemic and aleatory uncertainty. Over the past few years, advances in uncertainty analysis with respect to flood inundation modeling show that it is appropriate to adopt Probabilistic Flood Maps (PFM) to account for uncertainty. However, the following question arises; how can probabilistic flood hazard information be incorporated into spatial planning? Thus, a consistent framework to incorporate PFMs into the decision-making is required. In this paper, a novel methodology based on Decision-Making under Uncertainty theories, in particular Value of Information (VOI) is proposed. Specifically, the methodology entails the use of a PFM to generate a VOI map, which highlights floodplain locations where additional information is valuable with respect to available floodplain management actions and their potential consequences. The methodology is illustrated with a simplified example and also applied to a real case study in the South of France, where a VOI map is analyzed on the basis of historical land use change decisions over a period of 26 years. Results show that uncertain flood hazard information encapsulated in PFMs can aid decision-making in floodplain planning.

Modular neuron-based body estimation: maintaining consistency over different limbs, modalities, and frames of reference

PubMed Central

Ehrenfeld, Stephan; Herbort, Oliver; Butz, Martin V.

2013-01-01

This paper addresses the question of how the brain maintains a probabilistic body state estimate over time from a modeling perspective. The neural Modular Modality Frame (nMMF) model simulates such a body state estimation process by continuously integrating redundant, multimodal body state information sources. The body state estimate itself is distributed over separate, but bidirectionally interacting modules. nMMF compares the incoming sensory and present body state information across the interacting modules and fuses the information sources accordingly. At the same time, nMMF enforces body state estimation consistency across the modules. nMMF is able to detect conflicting sensory information and to consequently decrease the influence of implausible sensor sources on the fly. In contrast to the previously published Modular Modality Frame (MMF) model, nMMF offers a biologically plausible neural implementation based on distributed, probabilistic population codes. Besides its neural plausibility, the neural encoding has the advantage of enabling (a) additional probabilistic information flow across the separate body state estimation modules and (b) the representation of arbitrary probability distributions of a body state. The results show that the neural estimates can detect and decrease the impact of false sensory information, can propagate conflicting information across modules, and can improve overall estimation accuracy due to additional module interactions. Even bodily illusions, such as the rubber hand illusion, can be simulated with nMMF. We conclude with an outlook on the potential of modeling human data and of invoking goal-directed behavioral control. PMID:24191151

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.

Probabilistic assessment methodology for continuous-type petroleum accumulations

USGS Publications Warehouse

Crovelli, R.A.

2003-01-01

The analytic resource assessment method, called ACCESS (Analytic Cell-based Continuous Energy Spreadsheet System), was developed to calculate estimates of petroleum resources for the geologic assessment model, called FORSPAN, in continuous-type petroleum accumulations. The ACCESS method is based upon mathematical equations derived from probability theory in the form of a computer spreadsheet system. ?? 2003 Elsevier B.V. All rights reserved.

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.

Evaluation of the Plant-Craig stochastic convection scheme in an ensemble forecasting system

NASA Astrophysics Data System (ADS)

Keane, R. J.; Plant, R. S.; Tennant, W. J.

2015-12-01

The Plant-Craig stochastic convection parameterization (version 2.0) is implemented in the Met Office Regional Ensemble Prediction System (MOGREPS-R) and is assessed in comparison with the standard convection scheme with a simple stochastic element only, from random parameter variation. A set of 34 ensemble forecasts, each with 24 members, is considered, over the month of July 2009. Deterministic and probabilistic measures of the precipitation forecasts are assessed. The Plant-Craig parameterization is found to improve probabilistic forecast measures, particularly the results for lower precipitation thresholds. The impact on deterministic forecasts at the grid scale is neutral, although the Plant-Craig scheme does deliver improvements when forecasts are made over larger areas. The improvements found are greater in conditions of relatively weak synoptic forcing, for which convective precipitation is likely to be less predictable.

International Space Station End-of-Life Probabilistic Risk Assessment

NASA Technical Reports Server (NTRS)

Duncan, Gary W.

2014-01-01

The International Space Station (ISS) end-of-life (EOL) cycle is currently scheduled for 2020, although there are ongoing efforts to extend ISS life cycle through 2028. The EOL for the ISS will require deorbiting the ISS. This will be the largest manmade object ever to be de-orbited therefore safely deorbiting the station will be a very complex problem. This process is being planned by NASA and its international partners. Numerous factors will need to be considered to accomplish this such as target corridors, orbits, altitude, drag, maneuvering capabilities etc. The ISS EOL Probabilistic Risk Assessment (PRA) will play a part in this process by estimating the reliability of the hardware supplying the maneuvering capabilities. The PRA will model the probability of failure of the systems supplying and controlling the thrust needed to aid in the de-orbit maneuvering.

Probabilistic Volcanic Hazard and Risk Assessment

NASA Astrophysics Data System (ADS)

Marzocchi, W.; Neri, A.; Newhall, C. G.; Papale, P.

2007-08-01

Quantifying Long- and Short-Term Volcanic Hazard: Building Up a Common Strategy for Italian Volcanoes, Erice Italy, 8 November 2006 The term ``hazard'' can lead to some misunderstanding. In English, hazard has the generic meaning ``potential source of danger,'' but for more than 30 years [e.g., Fournier d'Albe, 1979], hazard has been also used in a more quantitative way, that reads, ``the probability of a certain hazardous event in a specific time-space window.'' However, many volcanologists still use ``hazard'' and ``volcanic hazard'' in purely descriptive and subjective ways. A recent meeting held in November 2006 at Erice, Italy, entitled ``Quantifying Long- and Short-Term Volcanic Hazard: Building up a Common Strategy for Italian Volcanoes'' (http://www.bo.ingv.it/erice2006) concluded that a more suitable term for the estimation of quantitative hazard is ``probabilistic volcanic hazard assessment'' (PVHA).

Probabilistic Assessment of Radiation Risk for Astronauts in Space Missions

NASA Technical Reports Server (NTRS)

Kim, Myung-Hee; DeAngelis, Giovanni; Cucinotta, Francis A.

2009-01-01

Accurate predictions of the health risks to astronauts from space radiation exposure are necessary for enabling future lunar and Mars missions. Space radiation consists of solar particle events (SPEs), comprised largely of medium energy protons, (less than 100 MeV); and galactic cosmic rays (GCR), which include protons and heavy ions of higher energies. While the expected frequency of SPEs is strongly influenced by the solar activity cycle, SPE occurrences themselves are random in nature. A solar modulation model has been developed for the temporal characterization of the GCR environment, which is represented by the deceleration potential, phi. The risk of radiation exposure from SPEs during extra-vehicular activities (EVAs) or in lightly shielded vehicles is a major concern for radiation protection, including determining the shielding and operational requirements for astronauts and hardware. To support the probabilistic risk assessment for EVAs, which would be up to 15% of crew time on lunar missions, we estimated the probability of SPE occurrence as a function of time within a solar cycle using a nonhomogeneous Poisson model to fit the historical database of measurements of protons with energy > 30 MeV, (phi)30. The resultant organ doses and dose equivalents, as well as effective whole body doses for acute and cancer risk estimations are analyzed for a conceptual habitat module and a lunar rover during defined space mission periods. This probabilistic approach to radiation risk assessment from SPE and GCR is in support of mission design and operational planning to manage radiation risks for space exploration.

Probabilistic modeling of the flows and environmental risks of nano-silica.

PubMed

Wang, Yan; Kalinina, Anna; Sun, Tianyin; Nowack, Bernd

2016-03-01

Nano-silica, the engineered nanomaterial with one of the largest production volumes, has a wide range of applications in consumer products and industry. This study aimed to quantify the exposure of nano-silica to the environment and to assess its risk to surface waters. Concentrations were calculated for four environmental (air, soil, surface water, sediments) and two technical compartments (wastewater, solid waste) for the EU and Switzerland using probabilistic material flow modeling. The corresponding median concentration in surface water is predicted to be 0.12 μg/l in the EU (0.053-3.3 μg/l, 15/85% quantiles). The concentrations in sediments in the complete sedimentation scenario were found to be the largest among all environmental compartments, with a median annual increase of 0.43 mg/kg · y in the EU (0.19-12 mg/kg · y, 15/85% quantiles). Moreover, probabilistic species sensitivity distributions (PSSD) were computed and the risk of nano-silica in surface waters was quantified by comparing the predicted environmental concentration (PEC) with the predicted no-effect concentration (PNEC) distribution, which was derived from the cumulative PSSD. This assessment suggests that nano-silica currently poses no risk to aquatic organisms in surface waters. Further investigations are needed to assess the risk of nano-silica in other environmental compartments, which is currently not possible due to a lack of ecotoxicological data. Copyright © 2015 Elsevier B.V. All rights reserved.

From Cyclone Tracks to the Costs of European Winter Storms: A Probabilistic Loss Assessment Model

NASA Astrophysics Data System (ADS)

Orwig, K.; Renggli, D.; Corti, T.; Reese, S.; Wueest, M.; Viktor, E.; Zimmerli, P.

2014-12-01

European winter storms cause billions of dollars of insured losses every year. Therefore, it is essential to understand potential impacts of future events, and the role reinsurance can play to mitigate the losses. The authors will present an overview on natural catastrophe risk assessment modeling in the reinsurance industry, and the development of a new innovative approach for modeling the risk associated with European winter storms.The new innovative approach includes the development of physically meaningful probabilistic (i.e. simulated) events for European winter storm loss assessment. The meteorological hazard component of the new model is based on cyclone and windstorm tracks identified in the 20thCentury Reanalysis data. The knowledge of the evolution of winter storms both in time and space allows the physically meaningful perturbation of historical event properties (e.g. track, intensity, etc.). The perturbation includes a random element but also takes the local climatology and the evolution of the historical event into account.The low-resolution wind footprints taken from the 20thCentury Reanalysis are processed by a statistical-dynamical downscaling to generate high-resolution footprints for both the simulated and historical events. Downscaling transfer functions are generated using ENSEMBLES regional climate model data. The result is a set of reliable probabilistic events representing thousands of years. The event set is then combined with country and site-specific vulnerability functions and detailed market- or client-specific information to compute annual expected losses.

Assessment of a Tsunami Hazard for Mediterranean Coast of Egypt

NASA Astrophysics Data System (ADS)

Zaytsev, Andrey; Babeyko, Andrey; Yalciner, Ahmet; Pelinovsky, Efim

2017-04-01

Analysis of tsunami hazard for Egypt based on historic data and numerical modelling of historic and prognostic events is given. There are 13 historic events for 4000 years, including one instrumental record (1956). Tsunami database includes 12 earthquake tsunamis and 1 event of volcanic origin (Santorini eruption). Tsunami intensity of events (365, 881, 1303, 1870) is estimated as I = 3 led to tsunami wave height more than 6 m. Numerical simulation of some possible scenario of tsunamis of seismic and landslide origin is done with use of NAMI-DANCE software solved the shallow-water equations. The PTHA method (Probabilistic Tsunami Hazard Assessment - Probabilistic assessment of a tsunami hazard) for the Mediterranean Sea developed in (Sorensen M.B., Spada M., Babeyko A., Wiemer S., Grunthal G. Probabilistic tsunami hazard in the Mediterranean Sea. J Geophysical Research, 2012, vol. 117, B01305) is used to evaluate the probability of tsunami occurrence on the Egyptian coast. The synthetic catalogue of prognostic tsunamis of seismic origin with magnitude more than 6.5 includes 84 920 events for 100000 years. For the wave heights more 1 m the curve: exceedance probability - tsunami height can be approximated by exponential Gumbel function with two parameters which are determined for each coastal location in Egypt (totally. 24 points). Prognostic extreme highest events with probability less 10-4 are not satisfied to the Gumbel function (approximately 10 events) and required the special analysis. Acknowledgements: This work was supported EU FP7 ASTARTE Project [603839], and for EP - NS6637.2016.5.

Exposure Estimation and Interpretation of Occupational Risk: Enhanced Information for the Occupational Risk Manager

PubMed Central

Waters, Martha; McKernan, Lauralynn; Maier, Andrew; Jayjock, Michael; Schaeffer, Val; Brosseau, Lisa

2015-01-01

The fundamental goal of this article is to describe, define, and analyze the components of the risk characterization process for occupational exposures. Current methods are described for the probabilistic characterization of exposure, including newer techniques that have increasing applications for assessing data from occupational exposure scenarios. In addition, since the probability of health effects reflects variability in the exposure estimate as well as the dose-response curve—the integrated considerations of variability surrounding both components of the risk characterization provide greater information to the occupational hygienist. Probabilistic tools provide a more informed view of exposure as compared to use of discrete point estimates for these inputs to the risk characterization process. Active use of such tools for exposure and risk assessment will lead to a scientifically supported worker health protection program. Understanding the bases for an occupational risk assessment, focusing on important sources of variability and uncertainty enables characterizing occupational risk in terms of a probability, rather than a binary decision of acceptable risk or unacceptable risk. A critical review of existing methods highlights several conclusions: (1) exposure estimates and the dose-response are impacted by both variability and uncertainty and a well-developed risk characterization reflects and communicates this consideration; (2) occupational risk is probabilistic in nature and most accurately considered as a distribution, not a point estimate; and (3) occupational hygienists have a variety of tools available to incorporate concepts of risk characterization into occupational health and practice. PMID:26302336

PROBABILISTIC RISK ANALYSIS OF RADIOACTIVE WASTE DISPOSALS - a case study

NASA Astrophysics Data System (ADS)

Trinchero, P.; Delos, A.; Tartakovsky, D. M.; Fernandez-Garcia, D.; Bolster, D.; Dentz, M.; Sanchez-Vila, X.; Molinero, J.

2009-12-01

The storage of contaminant material in superficial or sub-superficial repositories, such as tailing piles for mine waste or disposal sites for low and intermediate nuclear waste, poses a potential threat for the surrounding biosphere. The minimization of these risks can be achieved by supporting decision-makers with quantitative tools capable to incorporate all source of uncertainty within a rigorous probabilistic framework. A case study is presented where we assess the risks associated to the superficial storage of hazardous waste close to a populated area. The intrinsic complexity of the problem, involving many events with different spatial and time scales and many uncertainty parameters is overcome by using a formal PRA (probabilistic risk assessment) procedure that allows decomposing the system into a number of key events. Hence, the failure of the system is directly linked to the potential contamination of one of the three main receptors: the underlying karst aquifer, a superficial stream that flows near the storage piles and a protection area surrounding a number of wells used for water supply. The minimal cut sets leading to the failure of the system are obtained by defining a fault-tree that incorporates different events including the failure of the engineered system (e.g. cover of the piles) and the failure of the geological barrier (e.g. clay layer that separates the bottom of the pile from the karst formation). Finally the probability of failure is quantitatively assessed combining individual independent or conditional probabilities that are computed numerically or borrowed from reliability database.

Cost-consequence analysis of different active flowable hemostatic matrices in cardiac surgical procedures.

PubMed

Makhija, D; Rock, M; Xiong, Y; Epstein, J D; Arnold, M R; Lattouf, O M; Calcaterra, D

2017-06-01

A recent retrospective comparative effectiveness study found that use of the FLOSEAL Hemostatic Matrix in cardiac surgery was associated with significantly lower risks of complications, blood transfusions, surgical revisions, and shorter length of surgery than use of SURGIFLO Hemostatic Matrix. These outcome improvements in cardiac surgery procedures may translate to economic savings for hospitals and payers. The objective of this study was to estimate the cost-consequence of two flowable hemostatic matrices (FLOSEAL or SURGIFLO) in cardiac surgeries for US hospitals. A cost-consequence model was constructed using clinical outcomes from a previously published retrospective comparative effectiveness study of FLOSEAL vs SURGIFLO in adult cardiac surgeries. The model accounted for the reported differences between these products in length of surgery, rates of major and minor complications, surgical revisions, and blood product transfusions. Costs were derived from Healthcare Cost and Utilization Project's National Inpatient Sample (NIS) 2012 database and converted to 2015 US dollars. Savings were modeled for a hospital performing 245 cardiac surgeries annually, as identified as the average for hospitals in the NIS dataset. One-way sensitivity analysis and probabilistic sensitivity analysis were performed to test model robustness. The results suggest that if FLOSEAL is utilized in a hospital that performs 245 mixed cardiac surgery procedures annually, 11 major complications, 31 minor complications, nine surgical revisions, 79 blood product transfusions, and 260.3 h of cumulative operating time could be avoided. These improved outcomes correspond to a net annualized saving of $1,532,896. Cost savings remained consistent between $1.3m and $1.8m and between $911k and $2.4m, even after accounting for the uncertainty around clinical and cost inputs, in a one-way and probabilistic sensitivity analysis, respectively. Outcome differences associated with FLOSEAL vs SURGIFLO that were previously reported in a comparative effectiveness study may result in substantial cost savings for US hospitals.

BYMUR software: a free and open source tool for quantifying and visualizing multi-risk analyses

NASA Astrophysics Data System (ADS)

Tonini, Roberto; Selva, Jacopo

2013-04-01

The BYMUR software aims to provide an easy-to-use open source tool for both computing multi-risk and managing/visualizing/comparing all the inputs (e.g. hazard, fragilities and exposure) as well as the corresponding results (e.g. risk curves, risk indexes). For all inputs, a complete management of inter-model epistemic uncertainty is considered. The BYMUR software will be one of the final products provided by the homonymous ByMuR project (http://bymur.bo.ingv.it/) funded by Italian Ministry of Education, Universities and Research (MIUR), focused to (i) provide a quantitative and objective general method for a comprehensive long-term multi-risk analysis in a given area, accounting for inter-model epistemic uncertainty through Bayesian methodologies, and (ii) apply the methodology to seismic, volcanic and tsunami risks in Naples (Italy). More specifically, the BYMUR software will be able to separately account for the probabilistic hazard assessment of different kind of hazardous phenomena, the relative (time-dependent/independent) vulnerabilities and exposure data, and their possible (predefined) interactions: the software will analyze these inputs and will use them to estimate both single- and multi- risk associated to a specific target area. In addition, it will be possible to connect the software to further tools (e.g., a full hazard analysis), allowing a dynamic I/O of results. The use of Python programming language guarantees that the final software will be open source and platform independent. Moreover, thanks to the integration of some most popular and rich-featured Python scientific modules (Numpy, Matplotlib, Scipy) with the wxPython graphical user toolkit, the final tool will be equipped with a comprehensive Graphical User Interface (GUI) able to control and visualize (in the form of tables, maps and/or plots) any stage of the multi-risk analysis. The additional features of importing/exporting data in MySQL databases and/or standard XML formats (for instance, the global standards defined in the frame of GEM project for seismic hazard and risk) will grant the interoperability with other FOSS software and tools and, at the same time, to be on hand of the geo-scientific community. An already available example of connection is represented by the BET_VH(**) tool, which probabilistic volcanic hazard outputs will be used as input for BYMUR. Finally, the prototype version of BYMUR will be used for the case study of the municipality of Naples, by considering three different natural hazards (volcanic eruptions, earthquakes and tsunamis) and by assessing the consequent long-term risk evaluation. (**)BET_VH (Bayesian Event Tree for Volcanic Hazard) is probabilistic tool for long-term volcanic hazard assessment, recently re-designed and adjusted to be run on the Vhub cyber-infrastructure, a free web-based collaborative tool in volcanology research (see http://vhub.org/resources/betvh).

APOLLO_NG - a probabilistic interpretation of the APOLLO legacy for AVHRR heritage channels

NASA Astrophysics Data System (ADS)

Klüser, L.; Killius, N.; Gesell, G.

2015-10-01

The cloud processing scheme APOLLO (AVHRR Processing scheme Over cLouds, Land and Ocean) has been in use for cloud detection and cloud property retrieval since the late 1980s. The physics of the APOLLO scheme still build the backbone of a range of cloud detection algorithms for AVHRR (Advanced Very High Resolution Radiometer) heritage instruments. The APOLLO_NG (APOLLO_NextGeneration) cloud processing scheme is a probabilistic interpretation of the original APOLLO method. It builds upon the physical principles that have served well in the original APOLLO scheme. Nevertheless, a couple of additional variables have been introduced in APOLLO_NG. Cloud detection is no longer performed as a binary yes/no decision based on these physical principles. It is rather expressed as cloud probability for each satellite pixel. Consequently, the outcome of the algorithm can be tuned from being sure to reliably identify clear pixels to conditions of reliably identifying definitely cloudy pixels, depending on the purpose. The probabilistic approach allows retrieving not only the cloud properties (optical depth, effective radius, cloud top temperature and cloud water path) but also their uncertainties. APOLLO_NG is designed as a standalone cloud retrieval method robust enough for operational near-realtime use and for application to large amounts of historical satellite data. The radiative transfer solution is approximated by the same two-stream approach which also had been used for the original APOLLO. This allows the algorithm to be applied to a wide range of sensors without the necessity of sensor-specific tuning. Moreover it allows for online calculation of the radiative transfer (i.e., within the retrieval algorithm) giving rise to a detailed probabilistic treatment of cloud variables. This study presents the algorithm for cloud detection and cloud property retrieval together with the physical principles from the APOLLO legacy it is based on. Furthermore a couple of example results from NOAA-18 are presented.

APOLLO_NG - a probabilistic interpretation of the APOLLO legacy for AVHRR heritage channels

NASA Astrophysics Data System (ADS)

Klüser, L.; Killius, N.; Gesell, G.

2015-04-01

The cloud processing scheme APOLLO (Avhrr Processing scheme Over cLouds, Land and Ocean) has been in use for cloud detection and cloud property retrieval since the late 1980s. The physics of the APOLLO scheme still build the backbone of a range of cloud detection algorithms for AVHRR (Advanced Very High Resolution Radiometer) heritage instruments. The APOLLO_NG (APOLLO_NextGeneration) cloud processing scheme is a probabilistic interpretation of the original APOLLO method. While building upon the physical principles having served well in the original APOLLO a couple of additional variables have been introduced in APOLLO_NG. Cloud detection is not performed as a binary yes/no decision based on these physical principals but is expressed as cloud probability for each satellite pixel. Consequently the outcome of the algorithm can be tuned from clear confident to cloud confident depending on the purpose. The probabilistic approach allows to retrieving not only the cloud properties (optical depth, effective radius, cloud top temperature and cloud water path) but also their uncertainties. APOLLO_NG is designed as a standalone cloud retrieval method robust enough for operational near-realtime use and for the application with large amounts of historical satellite data. Thus the radiative transfer solution is approximated by the same two stream approach which also had been used for the original APOLLO. This allows the algorithm to be robust enough for being applied to a wide range of sensors without the necessity of sensor-specific tuning. Moreover it allows for online calculation of the radiative transfer (i.e. within the retrieval algorithm) giving rise to a detailed probabilistic treatment of cloud variables. This study presents the algorithm for cloud detection and cloud property retrieval together with the physical principles from the APOLLO legacy it is based on. Furthermore a couple of example results from on NOAA-18 are presented.

The exposure of Sydney (Australia) to earthquake-generated tsunamis, storms and sea level rise: a probabilistic multi-hazard approach

PubMed Central

Dall'Osso, F.; Dominey-Howes, D.; Moore, C.; Summerhayes, S.; Withycombe, G.

2014-01-01

Approximately 85% of Australia's population live along the coastal fringe, an area with high exposure to extreme inundations such as tsunamis. However, to date, no Probabilistic Tsunami Hazard Assessments (PTHA) that include inundation have been published for Australia. This limits the development of appropriate risk reduction measures by decision and policy makers. We describe our PTHA undertaken for the Sydney metropolitan area. Using the NOAA NCTR model MOST (Method for Splitting Tsunamis), we simulate 36 earthquake-generated tsunamis with annual probabilities of 1:100, 1:1,000 and 1:10,000, occurring under present and future predicted sea level conditions. For each tsunami scenario we generate a high-resolution inundation map of the maximum water level and flow velocity, and we calculate the exposure of buildings and critical infrastructure. Results indicate that exposure to earthquake-generated tsunamis is relatively low for present events, but increases significantly with higher sea level conditions. The probabilistic approach allowed us to undertake a comparison with an existing storm surge hazard assessment. Interestingly, the exposure to all the simulated tsunamis is significantly lower than that for the 1:100 storm surge scenarios, under the same initial sea level conditions. The results have significant implications for multi-risk and emergency management in Sydney. PMID:25492514

Improving medium-range ensemble streamflow forecasts through statistical post-processing

NASA Astrophysics Data System (ADS)

Mendoza, Pablo; Wood, Andy; Clark, Elizabeth; Nijssen, Bart; Clark, Martyn; Ramos, Maria-Helena; Nowak, Kenneth; Arnold, Jeffrey

2017-04-01

Probabilistic hydrologic forecasts are a powerful source of information for decision-making in water resources operations. A common approach is the hydrologic model-based generation of streamflow forecast ensembles, which can be implemented to account for different sources of uncertainties - e.g., from initial hydrologic conditions (IHCs), weather forecasts, and hydrologic model structure and parameters. In practice, hydrologic ensemble forecasts typically have biases and spread errors stemming from errors in the aforementioned elements, resulting in a degradation of probabilistic properties. In this work, we compare several statistical post-processing techniques applied to medium-range ensemble streamflow forecasts obtained with the System for Hydromet Applications, Research and Prediction (SHARP). SHARP is a fully automated prediction system for the assessment and demonstration of short-term to seasonal streamflow forecasting applications, developed by the National Center for Atmospheric Research, University of Washington, U.S. Army Corps of Engineers, and U.S. Bureau of Reclamation. The suite of post-processing techniques includes linear blending, quantile mapping, extended logistic regression, quantile regression, ensemble analogs, and the generalized linear model post-processor (GLMPP). We assess and compare these techniques using multi-year hindcasts in several river basins in the western US. This presentation discusses preliminary findings about the effectiveness of the techniques for improving probabilistic skill, reliability, discrimination, sharpness and resolution.

Probabilistic seismic hazard zonation for the Cuban building code update

NASA Astrophysics Data System (ADS)

Garcia, J.; Llanes-Buron, C.

2013-05-01

A probabilistic seismic hazard assessment has been performed in response to a revision and update of the Cuban building code (NC-46-99) for earthquake-resistant building construction. The hazard assessment have been done according to the standard probabilistic approach (Cornell, 1968) and importing the procedures adopted by other nations dealing with the problem of revising and updating theirs national building codes. Problems of earthquake catalogue treatment, attenuation of peak and spectral ground acceleration, as well as seismic source definition have been rigorously analyzed and a logic-tree approach was used to represent the inevitable uncertainties encountered through the whole seismic hazard estimation process. The seismic zonation proposed here, is formed by a map where it is reflected the behaviour of the spectral acceleration values for short (0.2 seconds) and large (1.0 seconds) periods on rock conditions with a 1642 -year return period, which being considered as maximum credible earthquake (ASCE 07-05). In addition, other three design levels are proposed (severe earthquake: with a 808 -year return period, ordinary earthquake: with a 475 -year return period and minimum earthquake: with a 225 -year return period). The seismic zonation proposed here fulfils the international standards (IBC-ICC) as well as the world tendencies in this thematic.

The exposure of Sydney (Australia) to earthquake-generated tsunamis, storms and sea level rise: a probabilistic multi-hazard approach.

PubMed

Dall'Osso, F; Dominey-Howes, D; Moore, C; Summerhayes, S; Withycombe, G

2014-12-10

Approximately 85% of Australia's population live along the coastal fringe, an area with high exposure to extreme inundations such as tsunamis. However, to date, no Probabilistic Tsunami Hazard Assessments (PTHA) that include inundation have been published for Australia. This limits the development of appropriate risk reduction measures by decision and policy makers. We describe our PTHA undertaken for the Sydney metropolitan area. Using the NOAA NCTR model MOST (Method for Splitting Tsunamis), we simulate 36 earthquake-generated tsunamis with annual probabilities of 1:100, 1:1,000 and 1:10,000, occurring under present and future predicted sea level conditions. For each tsunami scenario we generate a high-resolution inundation map of the maximum water level and flow velocity, and we calculate the exposure of buildings and critical infrastructure. Results indicate that exposure to earthquake-generated tsunamis is relatively low for present events, but increases significantly with higher sea level conditions. The probabilistic approach allowed us to undertake a comparison with an existing storm surge hazard assessment. Interestingly, the exposure to all the simulated tsunamis is significantly lower than that for the 1:100 storm surge scenarios, under the same initial sea level conditions. The results have significant implications for multi-risk and emergency management in Sydney.

Assessment of uncertainty in discrete fracture network modeling using probabilistic distribution method.

PubMed

Wei, Yaqiang; Dong, Yanhui; Yeh, Tian-Chyi J; Li, Xiao; Wang, Liheng; Zha, Yuanyuan

2017-11-01

There have been widespread concerns about solute transport problems in fractured media, e.g. the disposal of high-level radioactive waste in geological fractured rocks. Numerical simulation of particle tracking is gradually being employed to address these issues. Traditional predictions of radioactive waste transport using discrete fracture network (DFN) models often consider one particular realization of the fracture distribution based on fracture statistic features. This significantly underestimates the uncertainty of the risk of radioactive waste deposit evaluation. To adequately assess the uncertainty during the DFN modeling in a potential site for the disposal of high-level radioactive waste, this paper utilized the probabilistic distribution method (PDM). The method was applied to evaluate the risk of nuclear waste deposit in Beishan, China. Moreover, the impact of the number of realizations on the simulation results was analyzed. In particular, the differences between the modeling results of one realization and multiple realizations were demonstrated. Probabilistic distributions of 20 realizations at different times were also obtained. The results showed that the employed PDM can be used to describe the ranges of the contaminant particle transport. The high-possibility contaminated areas near the release point were more concentrated than the farther areas after 5E6 days, which was 25,400 m 2 .

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.

A Measure Approximation for Distributionally Robust PDE-Constrained Optimization Problems

DOE PAGES

Kouri, Drew Philip

2017-12-19

In numerous applications, scientists and engineers acquire varied forms of data that partially characterize the inputs to an underlying physical system. This data is then used to inform decisions such as controls and designs. Consequently, it is critical that the resulting control or design is robust to the inherent uncertainties associated with the unknown probabilistic characterization of the model inputs. Here in this work, we consider optimal control and design problems constrained by partial differential equations with uncertain inputs. We do not assume a known probabilistic model for the inputs, but rather we formulate the problem as a distributionally robustmore » optimization problem where the outer minimization problem determines the control or design, while the inner maximization problem determines the worst-case probability measure that matches desired characteristics of the data. We analyze the inner maximization problem in the space of measures and introduce a novel measure approximation technique, based on the approximation of continuous functions, to discretize the unknown probability measure. Finally, we prove consistency of our approximated min-max problem and conclude with numerical results.« less

Basal ganglia and Dopamine Contributions to Probabilistic Category Learning

PubMed Central

Shohamy, D.; Myers, C.E.; Kalanithi, J.; Gluck, M.A.

2009-01-01

Studies of the medial temporal lobe and basal ganglia memory systems have recently been extended towards understanding the neural systems contributing to category learning. The basal ganglia, in particular, have been linked to probabilistic category learning in humans. A separate parallel literature in systems neuroscience has emerged, indicating a role for the basal ganglia and related dopamine inputs in reward prediction and feedback processing. Here, we review behavioral, neuropsychological, functional neuroimaging, and computational studies of basal ganglia and dopamine contributions to learning in humans. Collectively, these studies implicate the basal ganglia in incremental, feedback-based learning that involves integrating information across multiple experiences. The medial temporal lobes, by contrast, contribute to rapid encoding of relations between stimuli and support flexible generalization of learning to novel contexts and stimuli. By breaking down our understanding of the cognitive and neural mechanisms contributing to different aspects of learning, recent studies are providing insight into how, and when, these different processes support learning, how they may interact with each other, and the consequence of different forms of learning for the representation of knowledge. PMID:18061261

Impaired risk evaluation in people with Internet gaming disorder: fMRI evidence from a probability discounting task.

PubMed

Lin, Xiao; Zhou, Hongli; Dong, Guangheng; Du, Xiaoxia

2015-01-02

This study examined how Internet gaming disorder (IGD) subjects modulating reward and risk at a neural level under a probability-discounting task with functional magnetic resonance imaging (fMRI). Behavioral and imaging data were collected from 19 IGD subjects (22.2 ± 3.08 years) and 21 healthy controls (HC, 22.8 ± 3.5 years). Behavior results showed that IGD subjects prefer the probabilistic options to fixed ones and were associated with shorter reaction time, when comparing to HC. The fMRI results revealed that IGD subjects show decreased activation in the inferior frontal gyrus and the precentral gyrus when choosing the probabilistic options than HC. Correlations were also calculated between behavioral performances and brain activities in relevant brain regions. Both of the behavioral performance and fMRI results indicate that people with IGD show impaired risk evaluation, which might be the reason why IGD subjects continue playing online games despite the risks of widely known negative consequence. Copyright © 2014 Elsevier Inc. All rights reserved.

Development of Testing Methodologies for the Mechanical Properties of MEMS

NASA Technical Reports Server (NTRS)

Ekwaro-Osire, Stephen

2003-01-01

This effort is to investigate and design testing strategies to determine the mechanical properties of MicroElectroMechanical Systems (MEMS) as well as investigate the development of a MEMS Probabilistic Design Methodology (PDM). One item of potential interest is the design of a test for the Weibull size effect in pressure membranes. 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. However, the primary area of investigation will most likely be analysis and modeling of material interfaces for strength as well as developing a strategy to handle stress singularities at sharp corners, filets, and material interfaces. This will be a continuation of the previous years work. The ultimate 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 probabilistic seismic risk assessment procedure for nuclear power plants: (I) Methodology

USGS Publications Warehouse

Huang, Y.-N.; Whittaker, A.S.; Luco, N.

2011-01-01

A new procedure for probabilistic seismic risk assessment of nuclear power plants (NPPs) is proposed. This procedure modifies the current procedures using tools developed recently for performance-based earthquake engineering of buildings. The proposed procedure uses (a) response-based fragility curves to represent the capacity of structural and nonstructural components of NPPs, (b) nonlinear response-history analysis to characterize the demands on those components, and (c) Monte Carlo simulations to determine the damage state of the components. The use of response-rather than ground-motion-based fragility curves enables the curves to be independent of seismic hazard and closely related to component capacity. The use of Monte Carlo procedure enables the correlation in the responses of components to be directly included in the risk assessment. An example of the methodology is presented in a companion paper to demonstrate its use and provide the technical basis for aspects of the methodology. ?? 2011 Published by Elsevier B.V.

Probabilistic Seismic Hazard Assessment for Iraq

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

Onur, Tuna; Gok, Rengin; Abdulnaby, Wathiq

Probabilistic Seismic Hazard Assessments (PSHA) form the basis for most contemporary seismic provisions in building codes around the world. The current building code of Iraq was published in 1997. An update to this edition is in the process of being released. However, there are no national PSHA studies in Iraq for the new building code to refer to for seismic loading in terms of spectral accelerations. As an interim solution, the new draft building code was considering to refer to PSHA results produced in the late 1990s as part of the Global Seismic Hazard Assessment Program (GSHAP; Giardini et al.,more » 1999). However these results are: a) more than 15 years outdated, b) PGA-based only, necessitating rough conversion factors to calculate spectral accelerations at 0.3s and 1.0s for seismic design, and c) at a probability level of 10% chance of exceedance in 50 years, not the 2% that the building code requires. Hence there is a pressing need for a new, updated PSHA for Iraq.« less

Augmenting Probabilistic Risk Assesment with Malevolent Initiators

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

Curtis Smith; David Schwieder

2011-11-01

As commonly practiced, the use of probabilistic risk assessment (PRA) in nuclear power plants only considers accident initiators such as natural hazards, equipment failures, and human error. Malevolent initiators are ignored in PRA, but are considered the domain of physical security, which uses vulnerability assessment based on an officially specified threat (design basis threat). This paper explores the implications of augmenting and extending existing PRA models by considering new and modified scenarios resulting from malevolent initiators. Teaming the augmented PRA models with conventional vulnerability assessments can cost-effectively enhance security of a nuclear power plant. This methodology is useful for operatingmore » plants, as well as in the design of new plants. For the methodology, we have proposed an approach that builds on and extends the practice of PRA for nuclear power plants for security-related issues. Rather than only considering 'random' failures, we demonstrated a framework that is able to represent and model malevolent initiating events and associated plant impacts.« less

Assessing Logo Programming among Jordanian Seventh Grade Students through Turtle Geometry

ERIC Educational Resources Information Center

Khasawneh, Amal A.

2009-01-01

The present study is concerned with assessing Logo programming experiences among seventh grade students. A formal multiple-choice test and five performance tasks were used to collect data. The results provided that students' performance was better than the expected score by the probabilistic laws, and a very low correlation between their Logo…