Probabilistic Risk Assessment Research Papers (original) (raw)

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- Chemical Engineering, Decision Making, Risk assessment, Sensitivity Analysis
- by Kuen Ting
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- Mechanical Engineering, Modeling, Risk assessment, Quantitative analysis

It is clear that probabilistic risk assessment or probabilistic safety assessment is embedded in the safety culture of the nuclear power industry, worldwide. Risk assessment applications are in transition in the sense that the regulatory apparatus is not yet in place, at least in the United States of America (USA), to fully support a risk-based licensing process. There is progress on the regulatory front, but it is tedious and not without its frustrations. Currently, the strategy in the USA is a “risk-informed” approach that tends to be “business as usual”, but while you're at it, “do a risk assessment”. The result is added burden (and costs) at a time of increased competition in the power field as a result of deregulation. There is hope in that some steps are finally being taken to modify the regulations to allow risk assessment to be more of a part of the licensing process. For example, the regulations having to do with maintenance, plant changes, and technical specifications have been modified to allow insights from risk assessment to be part of the basis for licensing amendments. On the matter of standards there is strong support that is scientifically based and addresses such issues as health effects and environmental impacts. There appears to be less support for standards on such matters as definition of terms, methodology, and data requirements.

- by Eko Susanto
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- Engineering, Risk assessment, Safety Culture, Nuclear power
- by Mustafa Aral
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- Engineering, Fuzzy set theory, Monte Carlo, Health Risk Assessment

The art and science of risk assessment as applied to foodborne pathogens is still in its infancy and limited to what can be measured and quantified.1 Many important process components are omitted from models, including this one, because of lack of data. Still the models may yield insights into process control and evaluation and/or into data collection priorities and need to be proposed for scientific evaluation and further refinement. This paper models four beef slaughterhouse events with two levels of process control of generic E. coli. Monte Carlo simulation is used to characterize the distribution of contamination of average raw burgers. For slaughter plants with each process at "level 1" control, <1.5% of raw hamburgers have >4 log10 colony forming units (CFU) of generic E. coli per quarter-pound hamburger. In contrast, plants with all "level 2" processes produced >93% of raw hamburgers with this level of generic E. coli. Sixteen scenarios are used t...

- by Scott Malcolm and +2
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- Monte Carlo Simulation, Process Control, Risk assessment, Probabilistic Risk Assessment
- by Kenneth Portier
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- Risk assessment, Adolescent, Multidisciplinary, Probability
- by Dale Dominey-howes
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- Geology, Natural Hazards, Risk Management, Community engagement

This study assesses the fire safety risks associated with compressed natural gas (CNG) vehicle systems, comprising primarily a typical school bus and supporting fuel infrastructure. The study determines the sensitivity of the results to... more

- by M. Modarres
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- Multidisciplinary, Risk Analysis, Natural Gas, Probabilistic Risk Assessment
- by E. Zampino and +1
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- Power System, Risk Management, Stress analysis, Accelerated Life Testing
- by Andrea Maioli
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- Information Design, Seismic Design, Probabilistic Risk Assessment, Pra
- by Fernando Carvalho
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- Ecology, Agriculture, Environmental Monitoring, Risk Management
- by Andrew S Whittaker
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- Time Series, Performance Assessment, Base Isolation, High Frequency
- by Wolfgang Nowak and +1
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- Environmental Engineering, Civil Engineering, Monte Carlo Simulation, Water resources
- by Vicki Bier
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- Engineering, Risk assessment, Mathematical Sciences, Probabilistic Risk Assessment
- by Thomas Kuhar
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- Zoology, Risk assessment, Biological Control, Probabilistic
- by Enrique Durán Medina
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- Engineering, Probability Theory, Risk Management, Nondestructive testing

According to the Institute of Medicine's (IOM's) 1999 report, To Err Is Human: Building a Safer Health System,1 the number of deaths due to iatrogenic errors of omission and commission in hospitals is estimated to be between... more

- by Brian Jack
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- Primary Care, Epidemiology, Methodology, Patient Safety
- by francis cucinotta
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- Radiation, Risk, Radiation Protection, Magnetic field
- by Peter Bos
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- Ecology, European Union, Risk Management, Risk assessment
- by John Komen
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- Decision Making, Risk assessment, Probabilistic Risk Assessment, United States

Probabilistic risk assessment (PRA) is an important methodology for assessing the risks of complex technologies. This paper discusses the strengths and weaknesses of PRA. Its application is explored in three different settings: adversarial policy processes, regulatory/licensing procedures, and plant safety audits. It is concluded that PRA is a valuable tool for auditing safety precautions of existing or planned technologies, especially when it is carried out as an interactive process involving designers and plant personnel who are familiar with actual, everyday operations. PRA has not proven to be as well-suited in providing absolute risk estimates in public-policy debates concerning the acceptability of a technology, or for the licensing and regulatory procedures. The reasons for this are discussed.

- by Joanne bayer
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- Multidisciplinary, Risk Analysis, Probabilistic Risk Assessment

Introduction: The transfer of patient care from the hospital team to primary care and other providers in the community at the time of discharge is a high-risk process characterized by fragmented, nonstandardized, and haphazard care that leads to errors and adverse events. The development of interventions to improve the discharge process requires a detailed evaluation of the process by a

- by Brian Jack
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- Primary Care, Patient Safety, Clinical Trial, Quality Control
- by Emanuele Borgonovo
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- Engineering, Mathematics, Computer Science, Modeling
- by Ivan Vrbanic
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- Operations Research, Probability, Probabilistic Logic, Failure Analysis

Triclosan, an antimicrobial compound used in personal care products, occurs in the aquatic environment due to residual concentrations in municipal wastewater treatment effluent. We evaluate triclosan-related risks to the aquatic environment, for aquatic and sediment-dwelling organisms and for aquatic-feeding wildlife, based on measured and modeled exposure concentrations. Triclosan concentrations in surface water, sediment, and biota tissue are predicted using a fugacity model parameterized to run probabilistically, to supplement the limited available measurements of triclosan in sediment and tissue. Aquatic toxicity is evaluated based on a species sensitivity distribution, which is extrapolated to sediment and tissues assuming equilibrium partitioning. A probabilistic wildlife exposure model is also used, and estimated doses are compared with wildlife toxicity benchmarks identified from a review of published and proprietary studies. The 95th percentiles of measured and modeled triclosan concentrations in surface water, sediment, and biota tissues are consistently below the 5th percentile of the respective species sensitivity distributions, indicating that, under most scenarios, adverse affects due to triclosan are unlikely.

- by Marie Capdevielle
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- Water, Ecotoxicology, Risk assessment, Benchmarking
- by Mark Cunningham
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- Engineering, Decision Making, Risk assessment, Reliability Engineering

Probabilistic risk assessment (PRA) methodologies are raising more and more interest in the context of the operation of high voltage transmission networks because they represent a new approach to the security assessment in power system operation. The classical deterministic methods, which compare the power system performance to a predefined set of requirements (e.g. no current and voltage violations, no stability problems), do not take into account the probability of occurrence of events. The fulfillment of the security requirements also for the most critical contingencies determines large security margins, thus higher operational and planning costs. This paper presents a new PRA methodology aimed at assessing the operational risk, measured through the probability of tripping of a set of lines within a 10-15 minute time window. Some simulation results on a large realistic power system are presented and discussed.

- by Emanuele Ciapessoni
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- Engineering, Power System, Risk Management, Electric Power Systems
- by Dennis Bley
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- Human Factors, Probabilistic Risk Assessment, HUMAN ERROR, Human Reliability Analysis
- by Song-Hua Shen
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- Cognitive Science, Taxonomy, Control system, Problem Solving
- by Song-Hua Shen
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- Engineering, Decision Making, Problem Solving, Mathematical Sciences
- by David DeForest
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- Risk assessment, Biological Sciences, Environmental Sciences, Copper
- by Theo Vermeire
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- Ecotoxicology, European Union, International Cooperation, Public Health

... discount rates were adjusted according to the preset decision rules as the ... Bridge Projects Computed Using Deterministic, Risk-Based, and Uncertainty-Based Analysis Approaches ... User benefit analysis for highways, American... more

- by Zongzhi Li
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- Engineering, Civil Engineering, Transportation Engineering, Methodology
- by Cristina Valhondo
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- Environmental Engineering, Civil Engineering, Geology, Decision Making
- by Ryan Davis
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- Biology, Ecology, Health, Risk assessment

Risk modeling techniques for probabilistic risk assessment are fairly well established, however, data to support risk assessment is still a major problem often leading to questionable risk assessment results. Selecting appropriate data sources and modeling uncertainty helps to improve risk assessment results and can help to make more informed decisions. Risk assessments need to be able to capture existing data

- by Bilal Ayub
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- Computer Science, Cystic Fibrosis, Risk Management, Risk assessment
- by Glenn Marion
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- Stochastic Process, Computer Science, Animal Behaviour, Parameter estimation

A methodological and computational platform called, "SoTeRiA-Fire," is developed to automate the "Fire Scenario Selection and Analysis (FSS)" step in the Fire Probabilistic Risk Assessment (PRA) of Nuclear Power Plants (NPPs). Although the SoTeRiA-Fire reflects the guidelines of NUREG/CR-6850 and ASME/ANS RA-Sa-2009, it can help NPP reduce resources required for Fire PRA implementation by (a) automating the pre-processing of input data, execution of a fire model, and post-processing of outputs for various tasks in the FSS and (b) providing a mechanism to gradually increase the realism of FSS while screening out insignificant scenarios. The fire hazard propagation event tree in SoTeRiA Fire includes multiple pivotal events: (1) initial fire ignition, (2) ignition of secondary combustibles and fire spread, (3) formation of damaging conditions for target equipment and cables, (4) failure of detection and suppression systems in the exposing compartment containing the initial fire source, (5) failure of fire barriers, and (6) failure of a suppression system in the exposed compartment. The SoTeRiA-Fire assembles the input parameters, conducts required input data processing, and constructs the input files for the Consolidated Model of Fire and Smoke Transport (CFAST) fire simulation program. It then analyzes various combinations or ranges of key input parameters based on the fire propagation event tree logic and prepares the outputs to be post-processed for FSS. SoTeRiA-Fire is applied in a plant and the results are reported; however, the code is applicable for various fire compartments in NPPs and can automate resource-efficient screening for single-or multi-compartment fire scenarios.

- by Sari Alkhatib
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- Screening, Fire risk modelling, Probabilistic Risk Assessment, Fire Risk Assessment
- by Glenn Thompson
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- Geology, Geochemistry, Geophysics, Volcanology
- by Tuula Tuhkanen
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- Housing, Environmental Monitoring, Public Health, Risk assessment
- by roberto santacroce
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- Geology, Geochemistry, Geophysics, Volcanology

Policies may help to keep the anthropogenic temperature change below some critical temperature thresholds. We apply MERGE in a probabilistic risk assessment framework to assess the risk of action versus inaction on climate change. The method applied gives a probabilistic assessment of the associated economic costs and levels of carbon-values and emissions reduction, as well as the needed technological change to restructure the energy system. The study suggests that a set of low-carbon and carbon-free technologies has to be developed and diffused around the world in order to reduce the risk of serious, adverse climate change. Eventually, a mass deployment of biomass farming technologies for bio-fuels and/or hydrogen production, in conjunction with carbon capture and sequestration options, are needed to satisfy the EU threshold of 2°C average atmospheric temperature rise above the pre-industrial temperature levels by the year 2100. However, because this temperature threshold represents a severe target, the global “willingness-to-pay” (WTP) must be significantly improved in relation with present attitudes.

- by Richel Montes
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- Applied Mathematics, Climate Change, Monte Carlo, Technological change