probabilistic risk-based management: Topics by Science.gov

Sample records for probabilistic risk-based management

Incorporating probabilistic seasonal climate forecasts into river management using a risk-based framework

USGS Publications Warehouse

Sojda, Richard S.; Towler, Erin; Roberts, Mike; Rajagopalan, Balaji

2013-01-01

[1] Despite the influence of hydroclimate on river ecosystems, most efforts to date have focused on using climate information to predict streamflow for water supply. However, as water demands intensify and river systems are increasingly stressed, research is needed to explicitly integrate climate into streamflow forecasts that are relevant to river ecosystem management. To this end, we present a five step risk-based framework: (1) define risk tolerance, (2) develop a streamflow forecast model, (3) generate climate forecast ensembles, (4) estimate streamflow ensembles and associated risk, and (5) manage for climate risk. The framework is successfully demonstrated for an unregulated watershed in southwest Montana, where the combination of recent drought and water withdrawals has made it challenging to maintain flows needed for healthy fisheries. We put forth a generalized linear modeling (GLM) approach to develop a suite of tools that skillfully model decision-relevant low flow characteristics in terms of climate predictors. Probabilistic precipitation forecasts are used in conjunction with the GLMs, resulting in season-ahead prediction ensembles that provide the full risk profile. These tools are embedded in an end-to-end risk management framework that directly supports proactive fish conservation efforts. Results show that the use of forecasts can be beneficial to planning, especially in wet years, but historical precipitation forecasts are quite conservative (i.e., not very “sharp”). Synthetic forecasts show that a modest “sharpening” can strongly impact risk and improve skill. We emphasize that use in management depends on defining relevant environmental flows and risk tolerance, requiring local stakeholder involvement.
Probabilistic framework for product design optimization and risk management

NASA Astrophysics Data System (ADS)

Keski-Rahkonen, J. K.

2018-05-01

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

2011-01-01

Probabilistic Risk Assessment (PRA) is a comprehensive, structured, and logical analysis method aimed at identifying and assessing risks in complex technological systems for the purpose of cost-effectively improving their safety and performance. NASA's objective is to better understand and effectively manage risk, and thus more effectively ensure mission and programmatic success, and to achieve and maintain high safety standards at NASA. NASA intends to use risk assessment in its programs and projects to support optimal management decision making for the improvement of safety and program performance. In addition to using quantitative/probabilistic risk assessment to improve safety and enhance the safety decision process, NASA has incorporated quantitative risk assessment into its system safety assessment process, which until now has relied primarily on a qualitative representation of risk. Also, NASA has recently adopted the Risk-Informed Decision Making (RIDM) process [1-1] as a valuable addition to supplement existing deterministic and experience-based engineering methods and tools. Over the years, NASA has been a leader in most of the technologies it has employed in its programs. One would think that PRA should be no exception. In fact, it would be natural for NASA to be a leader in PRA because, as a technology pioneer, NASA uses risk assessment and management implicitly or explicitly on a daily basis. NASA has probabilistic safety requirements (thresholds and goals) for crew transportation system missions to the International Space Station (ISS) [1-2]. NASA intends to have probabilistic requirements for any new human spaceflight transportation system acquisition. Methods to perform risk and reliability assessment in the early 1960s originated in U.S. aerospace and missile programs. Fault tree analysis (FTA) is an example. It would have been a reasonable extrapolation to expect that NASA would also become the world leader in the application of PRA. That was

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...
Improved water allocation utilizing probabilistic climate forecasts: Short-term water contracts in a risk management framework

NASA Astrophysics Data System (ADS)

Sankarasubramanian, A.; Lall, Upmanu; Souza Filho, Francisco Assis; Sharma, Ashish

2009-11-01

Probabilistic, seasonal to interannual streamflow forecasts are becoming increasingly available as the ability to model climate teleconnections is improving. However, water managers and practitioners have been slow to adopt such products, citing concerns with forecast skill. Essentially, a management risk is perceived in "gambling" with operations using a probabilistic forecast, while a system failure upon following existing operating policies is "protected" by the official rules or guidebook. In the presence of a prescribed system of prior allocation of releases under different storage or water availability conditions, the manager has little incentive to change. Innovation in allocation and operation is hence key to improved risk management using such forecasts. A participatory water allocation process that can effectively use probabilistic forecasts as part of an adaptive management strategy is introduced here. Users can express their demand for water through statements that cover the quantity needed at a particular reliability, the temporal distribution of the "allocation," the associated willingness to pay, and compensation in the event of contract nonperformance. The water manager then assesses feasible allocations using the probabilistic forecast that try to meet these criteria across all users. An iterative process between users and water manager could be used to formalize a set of short-term contracts that represent the resulting prioritized water allocation strategy over the operating period for which the forecast was issued. These contracts can be used to allocate water each year/season beyond long-term contracts that may have precedence. Thus, integrated supply and demand management can be achieved. In this paper, a single period multiuser optimization model that can support such an allocation process is presented. The application of this conceptual model is explored using data for the Jaguaribe Metropolitan Hydro System in Ceara, Brazil. The performance
Risk-based water resources planning: Incorporating probabilistic nonstationary climate uncertainties

NASA Astrophysics Data System (ADS)

Borgomeo, Edoardo; Hall, Jim W.; Fung, Fai; Watts, Glenn; Colquhoun, Keith; Lambert, Chris

2014-08-01

We present a risk-based approach for incorporating nonstationary probabilistic climate projections into long-term water resources planning. The proposed methodology uses nonstationary synthetic time series of future climates obtained via a stochastic weather generator based on the UK Climate Projections (UKCP09) to construct a probability distribution of the frequency of water shortages in the future. The UKCP09 projections extend well beyond the range of current hydrological variability, providing the basis for testing the robustness of water resources management plans to future climate-related uncertainties. The nonstationary nature of the projections combined with the stochastic simulation approach allows for extensive sampling of climatic variability conditioned on climate model outputs. The probability of exceeding planned frequencies of water shortages of varying severity (defined as Levels of Service for the water supply utility company) is used as a risk metric for water resources planning. Different sources of uncertainty, including demand-side uncertainties, are considered simultaneously and their impact on the risk metric is evaluated. Supply-side and demand-side management strategies can be compared based on how cost-effective they are at reducing risks to acceptable levels. A case study based on a water supply system in London (UK) is presented to illustrate the methodology. Results indicate an increase in the probability of exceeding the planned Levels of Service across the planning horizon. Under a 1% per annum population growth scenario, the probability of exceeding the planned Levels of Service is as high as 0.5 by 2040. The case study also illustrates how a combination of supply and demand management options may be required to reduce the risk of water shortages.
Incorporating linguistic, probabilistic, and possibilistic information in a risk-based approach for ranking contaminated sites.

PubMed

Zhang, Kejiang; Achari, Gopal; Pei, Yuansheng

2010-10-01

Different types of uncertain information-linguistic, probabilistic, and possibilistic-exist in site characterization. Their representation and propagation significantly influence the management of contaminated sites. In the absence of a framework with which to properly represent and integrate these quantitative and qualitative inputs together, decision makers cannot fully take advantage of the available and necessary information to identify all the plausible alternatives. A systematic methodology was developed in the present work to incorporate linguistic, probabilistic, and possibilistic information into the Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE), a subgroup of Multi-Criteria Decision Analysis (MCDA) methods for ranking contaminated sites. The identification of criteria based on the paradigm of comparative risk assessment provides a rationale for risk-based prioritization. Uncertain linguistic, probabilistic, and possibilistic information identified in characterizing contaminated sites can be properly represented as numerical values, intervals, probability distributions, and fuzzy sets or possibility distributions, and linguistic variables according to their nature. These different kinds of representation are first transformed into a 2-tuple linguistic representation domain. The propagation of hybrid uncertainties is then carried out in the same domain. This methodology can use the original site information directly as much as possible. The case study shows that this systematic methodology provides more reasonable results. © 2010 SETAC.
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
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 economic frameworks for disaster risk management

NASA Astrophysics Data System (ADS)

Dulac, Guillaume; Forni, Marc

2013-04-01

Starting from the general concept of risk, we set up an economic analysis framework for Disaster Risk Management (DRM) investment. It builds on uncertainty management techniques - notably Monte Carlo simulations - and includes both a risk and performance metrics adapted to recurring issues in disaster risk management as entertained by governments and international organisations. This type of framework proves to be enlightening in several regards, and is thought to ease the promotion of DRM projects as "investments" rather than "costs to be born" and allow for meaningful comparison between DRM and other sectors. We then look at the specificities of disaster risk investments of medium to large scales through this framework, where some "invariants" can be identified, notably: (i) it makes more sense to perform analysis over long-term horizons -space and time scales are somewhat linked; (ii) profiling of the fluctuations of the gains and losses of DRM investments over long periods requires the ability to handle possibly highly volatile variables; (iii) complexity increases with the scale which results in a higher sensitivity of the analytic framework on the results; (iv) as the perimeter of analysis (time, theme and space-wise) is widened, intrinsic parameters of the project tend to weight lighter. This puts DRM in a very different perspective from traditional modelling, which usually builds on more intrinsic features of the disaster as it relates to the scientific knowledge about hazard(s). As models hardly accommodate for such complexity or "data entropy" (they require highly structured inputs), there is a need for a complementary approach to understand risk at global scale. The proposed framework suggests opting for flexible ad hoc modelling of specific issues consistent with one's objective, risk and performance metrics. Such tailored solutions are strongly context-dependant (time and budget, sensitivity of the studied variable in the economic framework) and can
Willingness-to-pay for a probabilistic flood forecast: a risk-based decision-making game

NASA Astrophysics Data System (ADS)

Arnal, Louise; Ramos, Maria-Helena; Coughlan de Perez, Erin; Cloke, Hannah Louise; Stephens, Elisabeth; Wetterhall, Fredrik; van Andel, Schalk Jan; Pappenberger, Florian

2016-08-01

Probabilistic hydro-meteorological forecasts have over the last decades been used more frequently to communicate forecast uncertainty. This uncertainty is twofold, as it constitutes both an added value and a challenge for the forecaster and the user of the forecasts. Many authors have demonstrated the added (economic) value of probabilistic over deterministic forecasts across the water sector (e.g. flood protection, hydroelectric power management and navigation). However, the richness of the information is also a source of challenges for operational uses, due partially to the difficulty in transforming the probability of occurrence of an event into a binary decision. This paper presents the results of a risk-based decision-making game on the topic of flood protection mitigation, called "How much are you prepared to pay for a forecast?". The game was played at several workshops in 2015, which were attended by operational forecasters and academics working in the field of hydro-meteorology. The aim of this game was to better understand the role of probabilistic forecasts in decision-making processes and their perceived value by decision-makers. Based on the participants' willingness-to-pay for a forecast, the results of the game show that the value (or the usefulness) of a forecast depends on several factors, including the way users perceive the quality of their forecasts and link it to the perception of their own performances as decision-makers.
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.
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
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
Probabilistic thinking and death anxiety: a terror management based study.

PubMed

Hayslip, Bert; Schuler, Eric R; Page, Kyle S; Carver, Kellye S

2014-01-01

Terror Management Theory has been utilized to understand how death can change behavioral outcomes and social dynamics. One area that is not well researched is why individuals willingly engage in risky behavior that could accelerate their mortality. One method of distancing a potential life threatening outcome when engaging in risky behaviors is through stacking probability in favor of the event not occurring, termed probabilistic thinking. The present study examines the creation and psychometric properties of the Probabilistic Thinking scale in a sample of young, middle aged, and older adults (n = 472). The scale demonstrated adequate internal consistency reliability for each of the four subscales, excellent overall internal consistency, and good construct validity regarding relationships with measures of death anxiety. Reliable age and gender effects in probabilistic thinking were also observed. The relationship of probabilistic thinking as part of a cultural buffer against death anxiety is discussed, as well as its implications for Terror Management research.
Integration of Evidence Base into a Probabilistic Risk Assessment

NASA Technical Reports Server (NTRS)

Saile, Lyn; Lopez, Vilma; Bickham, Grandin; Kerstman, Eric; FreiredeCarvalho, Mary; Byrne, Vicky; Butler, Douglas; Myers, Jerry; Walton, Marlei

2011-01-01

INTRODUCTION: A probabilistic decision support model such as the Integrated Medical Model (IMM) utilizes an immense amount of input data that necessitates a systematic, integrated approach for data collection, and management. As a result of this approach, IMM is able to forecasts medical events, resource utilization and crew health during space flight. METHODS: Inflight data is the most desirable input for the Integrated Medical Model. Non-attributable inflight data is collected from the Lifetime Surveillance for Astronaut Health study as well as the engineers, flight surgeons, and astronauts themselves. When inflight data is unavailable cohort studies, other models and Bayesian analyses are used, in addition to subject matters experts input on occasion. To determine the quality of evidence of a medical condition, the data source is categorized and assigned a level of evidence from 1-5; the highest level is one. The collected data reside and are managed in a relational SQL database with a web-based interface for data entry and review. The database is also capable of interfacing with outside applications which expands capabilities within the database itself. Via the public interface, customers can access a formatted Clinical Findings Form (CLiFF) that outlines the model input and evidence base for each medical condition. Changes to the database are tracked using a documented Configuration Management process. DISSCUSSION: This strategic approach provides a comprehensive data management plan for IMM. The IMM Database s structure and architecture has proven to support additional usages. As seen by the resources utilization across medical conditions analysis. In addition, the IMM Database s web-based interface provides a user-friendly format for customers to browse and download the clinical information for medical conditions. It is this type of functionality that will provide Exploratory Medicine Capabilities the evidence base for their medical condition list
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.
Software for Probabilistic Risk Reduction

NASA Technical Reports Server (NTRS)

Hensley, Scott; Michel, Thierry; Madsen, Soren; Chapin, Elaine; Rodriguez, Ernesto

2004-01-01

A computer program implements a methodology, denoted probabilistic risk reduction, that is intended to aid in planning the development of complex software and/or hardware systems. This methodology integrates two complementary prior methodologies: (1) that of probabilistic risk assessment and (2) a risk-based planning methodology, implemented in a prior computer program known as Defect Detection and Prevention (DDP), in which multiple requirements and the beneficial effects of risk-mitigation actions are taken into account. The present methodology and the software are able to accommodate both process knowledge (notably of the efficacy of development practices) and product knowledge (notably of the logical structure of a system, the development of which one seeks to plan). Estimates of the costs and benefits of a planned development can be derived. Functional and non-functional aspects of software can be taken into account, and trades made among them. It becomes possible to optimize the planning process in the sense that it becomes possible to select the best suite of process steps and design choices to maximize the expectation of success while remaining within budget.
Probabilistic Scenario-based Seismic Risk Analysis for Critical Infrastructures Method and Application for a Nuclear Power Plant

NASA Astrophysics Data System (ADS)

Klügel, J.

2006-12-01

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

PubMed

Claycamp, H Gregg

2012-01-01

Essentially any concept of risk is built on fundamental concepts of chance, likelihood, or probability. Although risk is generally a probability of loss of something of value, given that a risk-generating event will occur or has occurred, it is ironic that the quality risk management literature and guidelines on quality risk management tools are relatively silent on the meaning and uses of "probability." The probability concept is typically applied by risk managers as a combination of frequency-based calculation and a "degree of belief" meaning of probability. Probability as a concept that is crucial for understanding and managing risk is discussed through examples from the most general, scenario-defining and ranking tools that use probability implicitly to more specific probabilistic tools in risk management. A rich history of probability in risk management applied to other fields suggests that high-quality risk management decisions benefit from the implementation of more thoughtful probability concepts in both risk modeling and risk management. Essentially any concept of risk is built on fundamental concepts of chance, likelihood, or probability. Although "risk" generally describes a probability of loss of something of value, given that a risk-generating event will occur or has occurred, it is ironic that the quality risk management literature and guidelines on quality risk management methodologies and respective tools focus on managing severity but are relatively silent on the in-depth meaning and uses of "probability." Pharmaceutical manufacturers are expanding their use of quality risk management to identify and manage risks to the patient that might occur in phases of the pharmaceutical life cycle from drug development to manufacture, marketing to product discontinuation. A probability concept is typically applied by risk managers as a combination of data-based measures of probability and a subjective "degree of belief" meaning of probability. Probability as

Asteroid Risk Assessment: A Probabilistic Approach.

PubMed

Reinhardt, Jason C; Chen, Xi; Liu, Wenhao; Manchev, Petar; Paté-Cornell, M Elisabeth

2016-02-01

Following the 2013 Chelyabinsk event, the risks posed by asteroids attracted renewed interest, from both the scientific and policy-making communities. It reminded the world that impacts from near-Earth objects (NEOs), while rare, have the potential to cause great damage to cities and populations. Point estimates of the risk (such as mean numbers of casualties) have been proposed, but because of the low-probability, high-consequence nature of asteroid impacts, these averages provide limited actionable information. While more work is needed to further refine its input distributions (e.g., NEO diameters), the probabilistic model presented in this article allows a more complete evaluation of the risk of NEO impacts because the results are distributions that cover the range of potential casualties. This model is based on a modularized simulation that uses probabilistic inputs to estimate probabilistic risk metrics, including those of rare asteroid impacts. Illustrative results of this analysis are presented for a period of 100 years. As part of this demonstration, we assess the effectiveness of civil defense measures in mitigating the risk of human casualties. We find that they are likely to be beneficial but not a panacea. We also compute the probability-but not the consequences-of an impact with global effects ("cataclysm"). We conclude that there is a continued need for NEO observation, and for analyses of the feasibility and risk-reduction effectiveness of space missions designed to deflect or destroy asteroids that threaten the Earth. © 2015 Society for Risk Analysis.
Probabilistic load simulation: Code development status

NASA Astrophysics Data System (ADS)

Newell, J. F.; Ho, H.

1991-05-01

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

PubMed

Liu, Jing; Li, Yongping; Huang, Guohe; Fu, Haiyan; Zhang, Junlong; Cheng, Guanhui

2017-06-01

In this study, a multi-level-factorial risk-inference-based possibilistic-probabilistic programming (MRPP) method is proposed for supporting water quality management under multiple uncertainties. The MRPP method can handle uncertainties expressed as fuzzy-random-boundary intervals, probability distributions, and interval numbers, and analyze the effects of uncertainties as well as their interactions on modeling outputs. It is applied to plan water quality management in the Xiangxihe watershed. Results reveal that a lower probability of satisfying the objective function (θ) as well as a higher probability of violating environmental constraints (q i ) would correspond to a higher system benefit with an increased risk of violating system feasibility. Chemical plants are the major contributors to biological oxygen demand (BOD) and total phosphorus (TP) discharges; total nitrogen (TN) would be mainly discharged by crop farming. It is also discovered that optimistic decision makers should pay more attention to the interactions between chemical plant and water supply, while decision makers who possess a risk-averse attitude would focus on the interactive effect of q i and benefit of water supply. The findings can help enhance the model's applicability and identify a suitable water quality management policy for environmental sustainability according to the practical situations.
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).
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
Predicting the onset of psychosis in patients at clinical high risk: practical guide to probabilistic prognostic reasoning.

PubMed

Fusar-Poli, P; Schultze-Lutter, F

2016-02-01

Prediction of psychosis in patients at clinical high risk (CHR) has become a mainstream focus of clinical and research interest worldwide. When using CHR instruments for clinical purposes, the predicted outcome is but only a probability; and, consequently, any therapeutic action following the assessment is based on probabilistic prognostic reasoning. Yet, probabilistic reasoning makes considerable demands on the clinicians. We provide here a scholarly practical guide summarising the key concepts to support clinicians with probabilistic prognostic reasoning in the CHR state. We review risk or cumulative incidence of psychosis in, person-time rate of psychosis, Kaplan-Meier estimates of psychosis risk, measures of prognostic accuracy, sensitivity and specificity in receiver operator characteristic curves, positive and negative predictive values, Bayes' theorem, likelihood ratios, potentials and limits of real-life applications of prognostic probabilistic reasoning in the CHR state. Understanding basic measures used for prognostic probabilistic reasoning is a prerequisite for successfully implementing the early detection and prevention of psychosis in clinical practice. Future refinement of these measures for CHR patients may actually influence risk management, especially as regards initiating or withholding treatment. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/
Probabilistic Methods for Structural Reliability and Risk

NASA Technical Reports Server (NTRS)

Chamis, Christos C.

2010-01-01

A probabilistic method is used to evaluate the structural reliability and risk of select metallic and composite structures. The method is a multiscale, multifunctional and it is based on the most elemental level. A multifactor interaction model is used to describe the material properties which are subsequently evaluated probabilistically. The metallic structure is a two rotor aircraft engine, while the composite structures consist of laminated plies (multiscale) and the properties of each ply are the multifunctional representation. The structural component is modeled by finite element. The solution method for structural responses is obtained by an updated simulation scheme. The results show that the risk for the two rotor engine is about 0.0001 and the composite built-up structure is also 0.0001.
Probabilistic Methods for Structural Reliability and Risk

NASA Technical Reports Server (NTRS)

Chamis, Christos C.

2008-01-01

A probabilistic method is used to evaluate the structural reliability and risk of select metallic and composite structures. The method is a multiscale, multifunctional and it is based on the most elemental level. A multi-factor interaction model is used to describe the material properties which are subsequently evaluated probabilistically. The metallic structure is a two rotor aircraft engine, while the composite structures consist of laminated plies (multiscale) and the properties of each ply are the multifunctional representation. The structural component is modeled by finite element. The solution method for structural responses is obtained by an updated simulation scheme. The results show that the risk for the two rotor engine is about 0.0001 and the composite built-up structure is also 0.0001.
Probabilistic risk analysis and terrorism risk.

PubMed

Ezell, Barry Charles; Bennett, Steven P; von Winterfeldt, Detlof; Sokolowski, John; Collins, Andrew J

2010-04-01

Since the terrorist attacks of September 11, 2001, and the subsequent establishment of the U.S. Department of Homeland Security (DHS), considerable efforts have been made to estimate the risks of terrorism and the cost effectiveness of security policies to reduce these risks. DHS, industry, and the academic risk analysis communities have all invested heavily in the development of tools and approaches that can assist decisionmakers in effectively allocating limited resources across the vast array of potential investments that could mitigate risks from terrorism and other threats to the homeland. Decisionmakers demand models, analyses, and decision support that are useful for this task and based on the state of the art. Since terrorism risk analysis is new, no single method is likely to meet this challenge. In this article we explore a number of existing and potential approaches for terrorism risk analysis, focusing particularly on recent discussions regarding the applicability of probabilistic and decision analytic approaches to bioterrorism risks and the Bioterrorism Risk Assessment methodology used by the DHS and criticized by the National Academies and others.
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.
Use of Probabilistic Risk Assessment in Shuttle Decision Making Process

NASA Technical Reports Server (NTRS)

Boyer, Roger L.; Hamlin, Teri, L.

2011-01-01

This slide presentation reviews the use of Probabilistic Risk Assessment (PRA) to assist in the decision making for the shuttle design and operation. Probabilistic Risk Assessment (PRA) is a comprehensive, structured, and disciplined approach to identifying and analyzing risk in complex systems and/or processes that seeks answers to three basic questions: (i.e., what can go wrong? what is the likelihood of these occurring? and what are the consequences that could result if these occur?) The purpose of the Shuttle PRA (SPRA) is to provide a useful risk management tool for the Space Shuttle Program (SSP) to identify strengths and possible weaknesses in the Shuttle design and operation. SPRA was initially developed to support upgrade decisions, but has evolved into a tool that supports Flight Readiness Reviews (FRR) and near real-time flight decisions. Examples of the use of PRA for the shuttle are reviewed.
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.
Applicability of risk-based management and the need for risk-based economic decision analysis at hazardous waste contaminated sites.

PubMed

Khadam, Ibrahim; Kaluarachchi, Jagath J

2003-07-01

Decision analysis in subsurface contamination management is generally carried out through a traditional engineering economic viewpoint. However, new advances in human health risk assessment, namely, the probabilistic risk assessment, and the growing awareness of the importance of soft data in the decision-making process, require decision analysis methodologies that are capable of accommodating non-technical and politically biased qualitative information. In this work, we discuss the major limitations of the currently practiced decision analysis framework, which evolves around the definition of risk and cost of risk, and its poor ability to communicate risk-related information. A demonstration using a numerical example was conducted to provide insight on these limitations of the current decision analysis framework. The results from this simple ground water contamination and remediation scenario were identical to those obtained from studies carried out on existing Superfund sites, which suggests serious flaws in the current risk management framework. In order to provide a perspective on how these limitations may be avoided in future formulation of the management framework, more matured and well-accepted approaches to decision analysis in dam safety and the utility industry, where public health and public investment are of great concern, are presented and their applicability in subsurface remediation management is discussed. Finally, in light of the success of the application of risk-based decision analysis in dam safety and the utility industry, potential options for decision analysis in subsurface contamination management are discussed.
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
2009 Space Shuttle Probabilistic Risk Assessment Overview

NASA Technical Reports Server (NTRS)

Hamlin, Teri L.; Canga, Michael A.; Boyer, Roger L.; Thigpen, Eric B.

2010-01-01

Loss of a Space Shuttle during flight has severe consequences, including loss of a significant national asset; loss of national confidence and pride; and, most importantly, loss of human life. The Shuttle Probabilistic Risk Assessment (SPRA) is used to identify risk contributors and their significance; thus, assisting management in determining how to reduce risk. In 2006, an overview of the SPRA Iteration 2.1 was presented at PSAM 8 [1]. Like all successful PRAs, the SPRA is a living PRA and has undergone revisions since PSAM 8. The latest revision to the SPRA is Iteration 3. 1, and it will not be the last as the Shuttle program progresses and more is learned. This paper discusses the SPRA scope, overall methodology, and results, as well as provides risk insights. The scope, assumptions, uncertainties, and limitations of this assessment provide risk-informed perspective to aid management s decision-making process. In addition, this paper compares the Iteration 3.1 analysis and results to the Iteration 2.1 analysis and results presented at PSAM 8.
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
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.
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.
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.
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.

An ontology-based nurse call management system (oNCS) with probabilistic priority assessment

PubMed Central

2011-01-01

Background The current, place-oriented nurse call systems are very static. A patient can only make calls with a button which is fixed to a wall of a room. Moreover, the system does not take into account various factors specific to a situation. In the future, there will be an evolution to a mobile button for each patient so that they can walk around freely and still make calls. The system would become person-oriented and the available context information should be taken into account to assign the correct nurse to a call. The aim of this research is (1) the design of a software platform that supports the transition to mobile and wireless nurse call buttons in hospitals and residential care and (2) the design of a sophisticated nurse call algorithm. This algorithm dynamically adapts to the situation at hand by taking the profile information of staff members and patients into account. Additionally, the priority of a call probabilistically depends on the risk factors, assigned to a patient. Methods The ontology-based Nurse Call System (oNCS) was developed as an extension of a Context-Aware Service Platform. An ontology is used to manage the profile information. Rules implement the novel nurse call algorithm that takes all this information into account. Probabilistic reasoning algorithms are designed to determine the priority of a call based on the risk factors of the patient. Results The oNCS system is evaluated through a prototype implementation and simulations, based on a detailed dataset obtained from Ghent University Hospital. The arrival times of nurses at the location of a call, the workload distribution of calls amongst nurses and the assignment of priorities to calls are compared for the oNCS system and the current, place-oriented nurse call system. Additionally, the performance of the system is discussed. Conclusions The execution time of the nurse call algorithm is on average 50.333 ms. Moreover, the oNCS system significantly improves the assignment of nurses
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.
Constellation Probabilistic Risk Assessment (PRA): Design Consideration for the Crew Exploration Vehicle

NASA Technical Reports Server (NTRS)

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

2010-01-01

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

NASA Astrophysics Data System (ADS)

Arnal, Louise; Ramos, Maria-Helena; Coughlan, Erin; Cloke, Hannah L.; Stephens, Elisabeth; Wetterhall, Fredrik; van Andel, Schalk-Jan; Pappenberger, Florian

2016-04-01

Forecast uncertainty is a twofold issue, as it constitutes both an added value and a challenge for the forecaster and the user of the forecasts. Many authors have demonstrated the added (economic) value of probabilistic forecasts over deterministic forecasts for a diversity of activities in the water sector (e.g. flood protection, hydroelectric power management and navigation). However, the richness of the information is also a source of challenges for operational uses, due partially to the difficulty to transform the probability of occurrence of an event into a binary decision. The setup and the results of a risk-based decision-making experiment, designed as a game on the topic of flood protection mitigation, called ``How much are you prepared to pay for a forecast?'', will be presented. The game was played at several workshops in 2015, including during this session at the EGU conference in 2015, and a total of 129 worksheets were collected and analysed. The aim of this experiment was to contribute to the understanding of the role of probabilistic forecasts in decision-making processes and their perceived value by decision-makers. Based on the participants' willingness-to-pay for a forecast, the results of the game showed that the value (or the usefulness) of a forecast depends on several factors, including the way users perceive the quality of their forecasts and link it to the perception of their own performances as decision-makers. Balancing avoided costs and the cost (or the benefit) of having forecasts available for making decisions is not straightforward, even in a simplified game situation, and is a topic that deserves more attention from the hydrological forecasting community in the future.
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
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.
Reliability and Probabilistic Risk Assessment - How They Play Together

NASA Technical Reports Server (NTRS)

Safie, Fayssal; Stutts, Richard; Huang, Zhaofeng

2015-01-01

Since the Space Shuttle Challenger accident in 1986, NASA has extensively used probabilistic analysis methods to assess, understand, and communicate the risk of space launch vehicles. Probabilistic Risk Assessment (PRA), used in the nuclear industry, is one of the probabilistic analysis methods NASA utilizes to assess Loss of Mission (LOM) and Loss of Crew (LOC) risk for launch vehicles. PRA is a system scenario based risk assessment that uses a combination of fault trees, event trees, event sequence diagrams, and probability distributions to analyze the risk of a system, a process, or an activity. It is a process designed to answer three basic questions: 1) what can go wrong that would lead to loss or degraded performance (i.e., scenarios involving undesired consequences of interest), 2) how likely is it (probabilities), and 3) what is the severity of the degradation (consequences). Since the Challenger accident, PRA has been used in supporting decisions regarding safety upgrades for launch vehicles. Another area that was given a lot of emphasis at NASA after the Challenger accident is reliability engineering. Reliability engineering has been a critical design function at NASA since the early Apollo days. However, after the Challenger accident, quantitative reliability analysis and reliability predictions were given more scrutiny because of their importance in understanding failure mechanism and quantifying the probability of failure, which are key elements in resolving technical issues, performing design trades, and implementing design improvements. Although PRA and reliability are both probabilistic in nature and, in some cases, use the same tools, they are two different activities. Specifically, reliability engineering is a broad design discipline that deals with loss of function and helps understand failure mechanism and improve component and system design. PRA is a system scenario based risk assessment process intended to assess the risk scenarios that could
A probabilistic topic model for clinical risk stratification from electronic health records.

PubMed

Huang, Zhengxing; Dong, Wei; Duan, Huilong

2015-12-01

Risk stratification aims to provide physicians with the accurate assessment of a patient's clinical risk such that an individualized prevention or management strategy can be developed and delivered. Existing risk stratification techniques mainly focus on predicting the overall risk of an individual patient in a supervised manner, and, at the cohort level, often offer little insight beyond a flat score-based segmentation from the labeled clinical dataset. To this end, in this paper, we propose a new approach for risk stratification by exploring a large volume of electronic health records (EHRs) in an unsupervised fashion. Along this line, this paper proposes a novel probabilistic topic modeling framework called probabilistic risk stratification model (PRSM) based on Latent Dirichlet Allocation (LDA). The proposed PRSM recognizes a patient clinical state as a probabilistic combination of latent sub-profiles, and generates sub-profile-specific risk tiers of patients from their EHRs in a fully unsupervised fashion. The achieved stratification results can be easily recognized as high-, medium- and low-risk, respectively. In addition, we present an extension of PRSM, called weakly supervised PRSM (WS-PRSM) by incorporating minimum prior information into the model, in order to improve the risk stratification accuracy, and to make our models highly portable to risk stratification tasks of various diseases. We verify the effectiveness of the proposed approach on a clinical dataset containing 3463 coronary heart disease (CHD) patient instances. Both PRSM and WS-PRSM were compared with two established supervised risk stratification algorithms, i.e., logistic regression and support vector machine, and showed the effectiveness of our models in risk stratification of CHD in terms of the Area Under the receiver operating characteristic Curve (AUC) analysis. As well, in comparison with PRSM, WS-PRSM has over 2% performance gain, on the experimental dataset, demonstrating that
Spatially based management of agricultural phosphorus pollution from diffuse sources: the SCIMAP risk based approach

NASA Astrophysics Data System (ADS)

Reaney, S. M.; Heathwaite, L.; Lane, S. N.; Buckley, C.

2007-12-01

Pollution of rivers from agricultural phosphorus is recognised as a significant global problem and is a major management challenge as it involves processes that are small in magnitude, distributed over large areas, operating at fine spatial scales and associated with certain land use types when they are well connected to the receiving waters. Whilst some of these processes have been addressed in terms of water quality forecasting models and field measurements, we lack effective tools to prioritise where action should be taken to remediate the diffuse pollution problem. From a management perspective, the required information is on 'what to do where' rather than absolute values. This change in focus opens up the problem to be considered in a probabilistic / relative framework rather than concentrating on absolute values. The SCIMAP risk management framework is based on the critical source area concept whereby a risk and a connection are required to generate a problem. Treatments of both surface and subsurface hydrological connectivity have been developed. The approach is based on the philosophy that for a point to be considered connected there needs to be a continuous flow path to the receiving water. This information is calculated by simulating the possible flow paths from the source cell to the receiving water and recording the required catchment wetness to allow flow along that route. This algorithm gives information on the ease at which each point in the landscape can export risk along surface and subsurface pathways to the receiving waters. To understand the annual dynamics of the locational diffuse P risk, a temporal risk framework has been developed. This risk framework accounts for land management activies within the agricultural calendar. These events include the application of fertiliser, the P additions from livestock and the offtake of P in crops. Changes to these risks can be made to investigate management options. The SCIMAP risk mapping framework has
Site-Based Management: Implications for Risk Management?

ERIC Educational Resources Information Center

Dunklee, Dennis R.

1990-01-01

Site-based school management opens the possibility of problems in districtwide risk management and liability prevention programs. Describes a program to transfer prevention law and risk management strategies to individual school sites. Cautions that only duly authorized agents of local school boards can commit boards to contractual obligations.…
Relative risk of probabilistic category learning deficits in patients with schizophrenia and their siblings

PubMed Central

Weickert, Thomas W.; Goldberg, Terry E.; Egan, Michael F.; Apud, Jose A.; Meeter, Martijn; Myers, Catherine E.; Gluck, Mark A; Weinberger, Daniel R.

2010-01-01

Background While patients with schizophrenia display an overall probabilistic category learning performance deficit, the extent to which this deficit occurs in unaffected siblings of patients with schizophrenia is unknown. There are also discrepant findings regarding probabilistic category learning acquisition rate and performance in patients with schizophrenia. Methods A probabilistic category learning test was administered to 108 patients with schizophrenia, 82 unaffected siblings, and 121 healthy participants. Results Patients with schizophrenia displayed significant differences from their unaffected siblings and healthy participants with respect to probabilistic category learning acquisition rates. Although siblings on the whole failed to differ from healthy participants on strategy and quantitative indices of overall performance and learning acquisition, application of a revised learning criterion enabling classification into good and poor learners based on individual learning curves revealed significant differences between percentages of sibling and healthy poor learners: healthy (13.2%), siblings (34.1%), patients (48.1%), yielding a moderate relative risk. Conclusions These results clarify previous discrepant findings pertaining to probabilistic category learning acquisition rate in schizophrenia and provide the first evidence for the relative risk of probabilistic category learning abnormalities in unaffected siblings of patients with schizophrenia, supporting genetic underpinnings of probabilistic category learning deficits in schizophrenia. These findings also raise questions regarding the contribution of antipsychotic medication to the probabilistic category learning deficit in schizophrenia. The distinction between good and poor learning may be used to inform genetic studies designed to detect schizophrenia risk alleles. PMID:20172502
Fuzzy-probabilistic model for risk assessment of radioactive material railway transportation.

PubMed

Avramenko, M; Bolyatko, V; Kosterev, V

2005-01-01

Transportation of radioactive materials is obviously accompanied by a certain risk. A model for risk assessment of emergency situations and terrorist attacks may be useful for choosing possible routes and for comparing the various defence strategies. In particular, risk assessment is crucial for safe transportation of excess weapons-grade plutonium arising from the removal of plutonium from military employment. A fuzzy-probabilistic model for risk assessment of railway transportation has been developed taking into account the different natures of risk-affecting parameters (probabilistic and not probabilistic but fuzzy). Fuzzy set theory methods as well as standard methods of probability theory have been used for quantitative risk assessment. Information-preserving transformations are applied to realise the correct aggregation of probabilistic and fuzzy parameters. Estimations have also been made of the inhalation doses resulting from possible accidents during plutonium transportation. The obtained data show the scale of possible consequences that may arise from plutonium transportation accidents.
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.
A Probabilistic Typhoon Risk Model for Vietnam

NASA Astrophysics Data System (ADS)

Haseemkunju, A.; Smith, D. F.; Brolley, J. M.

2017-12-01

Annually, the coastal Provinces of low-lying Mekong River delta region in the southwest to the Red River Delta region in Northern Vietnam is exposed to severe wind and flood risk from landfalling typhoons. On average, about two to three tropical cyclones with a maximum sustained wind speed of >=34 knots make landfall along the Vietnam coast. Recently, Typhoon Wutip (2013) crossed Central Vietnam as a category 2 typhoon causing significant damage to properties. As tropical cyclone risk is expected to increase with increase in exposure and population growth along the coastal Provinces of Vietnam, insurance/reinsurance, and capital markets need a comprehensive probabilistic model to assess typhoon risk in Vietnam. In 2017, CoreLogic has expanded the geographical coverage of its basin-wide Western North Pacific probabilistic typhoon risk model to estimate the economic and insured losses from landfalling and by-passing tropical cyclones in Vietnam. The updated model is based on 71 years (1945-2015) of typhoon best-track data and 10,000 years of a basin-wide simulated stochastic tracks covering eight countries including Vietnam. The model is capable of estimating damage from wind, storm surge and rainfall flooding using vulnerability models, which relate typhoon hazard to building damageability. The hazard and loss models are validated against past historical typhoons affecting Vietnam. Notable typhoons causing significant damage in Vietnam are Lola (1993), Frankie (1996), Xangsane (2006), and Ketsana (2009). The central and northern coastal provinces of Vietnam are more vulnerable to wind and flood hazard, while typhoon risk in the southern provinces are relatively low.
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.
Cost-Risk Trade-off of Solar Radiation Management and Mitigation under Probabilistic Information on Climate Sensitivity

NASA Astrophysics Data System (ADS)

Khabbazan, Mohammad Mohammadi; Roshan, Elnaz; Held, Hermann

2017-04-01

In principle solar radiation management (SRM) offers an option to ameliorate anthropogenic temperature rise. However we cannot expect it to simultaneously compensate for anthropogenic changes in further climate variables in a perfect manner. Here, we ask to what extent a proponent of the 2°C-temperature target would apply SRM in conjunction with mitigation in view of global or regional disparities in precipitation changes. We apply cost-risk analysis (CRA), which is a decision analytic framework that makes a trade-off between the expected welfare-loss from climate policy costs and the climate risks from transgressing a climate target. Here, in both global-scale and 'Giorgi'-regional-scale analyses, we evaluate the optimal mixture of SRM and mitigation under probabilistic information about climate sensitivity. To do so, we generalize CRA for the sake of including not only temperature risk, but also globally aggregated and regionally disaggregated precipitation risks. Social welfare is maximized for the following three valuation scenarios: temperature-risk-only, precipitation-risk-only, and equally weighted both-risks. For now, the Giorgi regions are treated by equal weight. We find that for regionally differentiated precipitation targets, the usage of SRM will be comparably more restricted. In the course of time, a cooling of up to 1.3°C can be attributed to SRM for the latter scenario and for a median climate sensitivity of 3°C (for a global target only, this number reduces by 0.5°C). Our results indicate that although SRM would almost completely substitute for mitigation in the globally aggregated analysis, it only saves 70% to 75% of the welfare-loss compared to a purely mitigation-based analysis (from economic costs and climate risks, approximately 4% in terms of BGE) when considering regional precipitation risks in precipitation-risk-only and both-risks scenarios. It remains to be shown how the inclusion of further risks or different regional weights would
A Probabilistic Risk Assessment of Groundwater-Related Risks at Excavation Sites

NASA Astrophysics Data System (ADS)

Jurado, A.; de Gaspari, F.; Vilarrasa, V.; Sanchez-Vila, X.; Fernandez-Garcia, D.; Tartakovsky, D. M.; Bolster, D.

2010-12-01

Excavation sites such as those associated with the construction of subway lines, railways and highway tunnels are hazardous places, posing risks to workers, machinery and surrounding buildings. Many of these risks can be groundwater related. In this work we develop a general framework based on a probabilistic risk assessment (PRA) to quantify such risks. This approach is compatible with standard PRA practices and it employs many well-developed risk analysis tools, such as fault trees. The novelty and computational challenges of the proposed approach stem from the reliance on stochastic differential equations, rather than reliability databases, to compute the probabilities of basic events. The general framework is applied to a specific case study in Spain. It is used to estimate and minimize risks for a potential construction site of an underground station for the new subway line in the Barcelona metropolitan area.
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
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
Probabilistic objective functions for sensor management

NASA Astrophysics Data System (ADS)

Mahler, Ronald P. S.; Zajic, Tim R.

2004-08-01

This paper continues the investigation of a foundational and yet potentially practical basis for control-theoretic sensor management, using a comprehensive, intuitive, system-level Bayesian paradigm based on finite-set statistics (FISST). In this paper we report our most recent progress, focusing on multistep look-ahead -- i.e., allocation of sensor resources throughout an entire future time-window. We determine future sensor states in the time-window using a "probabilistically natural" sensor management objective function, the posterior expected number of targets (PENT). This objective function is constructed using a new "maxi-PIMS" optimization strategy that hedges against unknowable future observation-collections. PENT is used in conjuction with approximate multitarget filters: the probability hypothesis density (PHD) filter or the multi-hypothesis correlator (MHC) filter.

Probabilistic risk analysis of building contamination.

PubMed

Bolster, D T; Tartakovsky, D M

2008-10-01

We present a general framework for probabilistic risk assessment (PRA) of building contamination. PRA provides a powerful tool for the rigorous quantification of risk in contamination of building spaces. A typical PRA starts by identifying relevant components of a system (e.g. ventilation system components, potential sources of contaminants, remediation methods) and proceeds by using available information and statistical inference to estimate the probabilities of their failure. These probabilities are then combined by means of fault-tree analyses to yield probabilistic estimates of the risk of system failure (e.g. building contamination). A sensitivity study of PRAs can identify features and potential problems that need to be addressed with the most urgency. Often PRAs are amenable to approximations, which can significantly simplify the approach. All these features of PRA are presented in this paper via a simple illustrative example, which can be built upon in further studies. The tool presented here can be used to design and maintain adequate ventilation systems to minimize exposure of occupants to contaminants.
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.
Risk analysis of analytical validations by probabilistic modification of FMEA.

PubMed

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

2012-05-01

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

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

Liming, James K.; Ravindra, Mayasandra K.

2006-07-01

Over the past several years, ABSG Consulting Inc. (ABS Consulting) and the South Texas Project Nuclear Operating Company (STPNOC) have developed a decision support process and associated software for risk-informed, performance-based asset management (RIPBAM) of nuclear power plant facilities. RIPBAM applies probabilistic risk assessment (PRA) tools and techniques in the realm of plant physical and financial asset management. The RIPBAM process applies a tiered set of models and supporting performance measures (or metrics) that can ultimately be applied to support decisions affecting the allocation and management of plant resources (e.g., funding, staffing, scheduling, etc.). In general, the ultimate goal ofmore » the RIPBAM process is to continually support decision-making to maximize a facility's net present value (NPV) and long-term profitability for its owners. While the initial applications of RIPBAM have been for nuclear power stations, the methodology can easily be adapted to other types of power station or complex facility decision-making support. RIPBAM can also be designed to focus on performance metrics other than NPV and profitability (e.g., mission reliability, operational availability, probability of mission success per dollar invested, etc.). Recent advancements in the RIPBAM process focus on expanding the scope of previous RIPBAM applications to include not only operations, maintenance, and safety issues, but also broader risk perception components affecting plant owner (stockholder), operator, and regulator biases. Conceptually, RIPBAM is a comprehensive risk-informed cash flow model for decision support. It originated as a tool to help manage plant refueling outage scheduling, and was later expanded to include the full spectrum of operations and maintenance decision support. However, it differs from conventional business modeling tools in that it employs a systems engineering approach with broadly based probabilistic analysis of organizational
Dream project: Applications of earth observations to disaster risk management

NASA Astrophysics Data System (ADS)

Dyke, G.; Gill, S.; Davies, R.; Betorz, F.; Andalsvik, Y.; Cackler, J.; Dos Santos, W.; Dunlop, K.; Ferreira, I.; Kebe, F.; Lamboglia, E.; Matsubara, Y.; Nikolaidis, V.; Ostoja-Starzewski, S.; Sakita, M.; Verstappen, N.

2011-01-01

The field of disaster risk management is relatively new and takes a structured approach to managing uncertainty related to the threat of natural and man-made disasters. Disaster risk management consists primarily of risk assessment and the development of strategies to mitigate disaster risk. This paper will discuss how increasing both Earth observation data and information technology capabilities can contribute to disaster risk management, particularly in Belize. The paper presents the results and recommendations of a project conducted by an international and interdisciplinary team of experts at the 2009 session of the International Space University in NASA Ames Research Center (California, USA). The aim is to explore the combination of current, planned and potential space-aided, airborne, and ground-based Earth observation tools, the emergence of powerful new web-based and mobile data management tools, and how this combination can support and improve the emerging field of disaster risk management. The starting point of the project was the World Bank's Comprehensive Approach to Probabilistic Risk Assessment (CAPRA) program, focused in Central America. This program was used as a test bed to analyze current space technologies used in risk management and develop new strategies and tools to be applied in other regions around the world.
Staged decision making based on probabilistic forecasting

NASA Astrophysics Data System (ADS)

Booister, Nikéh; Verkade, Jan; Werner, Micha; Cranston, Michael; Cumiskey, Lydia; Zevenbergen, Chris

2016-04-01

Flood forecasting systems reduce, but cannot eliminate uncertainty about the future. Probabilistic forecasts explicitly show that uncertainty remains. However, as - compared to deterministic forecasts - a dimension is added ('probability' or 'likelihood'), with this added dimension decision making is made slightly more complicated. A technique of decision support is the cost-loss approach, which defines whether or not to issue a warning or implement mitigation measures (risk-based method). With the cost-loss method a warning will be issued when the ratio of the response costs to the damage reduction is less than or equal to the probability of the possible flood event. This cost-loss method is not widely used, because it motivates based on only economic values and is a technique that is relatively static (no reasoning, yes/no decision). Nevertheless it has high potential to improve risk-based decision making based on probabilistic flood forecasting because there are no other methods known that deal with probabilities in decision making. The main aim of this research was to explore the ways of making decision making based on probabilities with the cost-loss method better applicable in practice. The exploration began by identifying other situations in which decisions were taken based on uncertain forecasts or predictions. These cases spanned a range of degrees of uncertainty: from known uncertainty to deep uncertainty. Based on the types of uncertainties, concepts of dealing with situations and responses were analysed and possible applicable concepts where chosen. Out of this analysis the concepts of flexibility and robustness appeared to be fitting to the existing method. Instead of taking big decisions with bigger consequences at once, the idea is that actions and decisions are cut-up into smaller pieces and finally the decision to implement is made based on economic costs of decisions and measures and the reduced effect of flooding. The more lead-time there is in
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.
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.
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
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
Anesthesia patient risk: a quantitative approach to organizational factors and risk management options.

PubMed

Paté-Cornell, M E; Lakats, L M; Murphy, D M; Gaba, D M

1997-08-01

The risk of death or brain damage to anesthesia patients is relatively low, particularly for healthy patients in modern hospitals. When an accident does occur, its cause is usually an error made by the anesthesiologist, either in triggering the accident sequence, or failing to take timely corrective measures. This paper presents a pilot study which explores the feasibility of extending probabilistic risk analysis (PRA) of anesthesia accidents to assess the effects of human and management components on the patient risk. We develop first a classic PRA model for the patient risk per operation. We then link the probabilities of the different accident types to their root causes using a probabilistic analysis of the performance shaping factors. These factors are described here as the "state of the anesthesiologist" characterized both in terms of alertness and competence. We then analyze the effects of different management factors that affect the state of the anesthesiologist and we compute the risk reduction benefits of several risk management policies. Our data sources include the published version of the Australian Incident Monitoring Study as well as expert opinions. We conclude that patient risk could be reduced substantially by closer supervision of residents, the use of anesthesia simulators both in training and for periodic recertification, and regular medical examinations for all anesthesiologists.
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.
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
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
A probabilistic method for computing quantitative risk indexes from medical injuries compensation claims.

PubMed

Dalle Carbonare, S; Folli, F; Patrini, E; Giudici, P; Bellazzi, R

2013-01-01

The increasing demand of health care services and the complexity of health care delivery require Health Care Organizations (HCOs) to approach clinical risk management through proper methods and tools. An important aspect of risk management is to exploit the analysis of medical injuries compensation claims in order to reduce adverse events and, at the same time, to optimize the costs of health insurance policies. This work provides a probabilistic method to estimate the risk level of a HCO by computing quantitative risk indexes from medical injury compensation claims. Our method is based on the estimate of a loss probability distribution from compensation claims data through parametric and non-parametric modeling and Monte Carlo simulations. The loss distribution can be estimated both on the whole dataset and, thanks to the application of a Bayesian hierarchical model, on stratified data. The approach allows to quantitatively assessing the risk structure of the HCO by analyzing the loss distribution and deriving its expected value and percentiles. We applied the proposed method to 206 cases of injuries with compensation requests collected from 1999 to the first semester of 2007 by the HCO of Lodi, in the Northern part of Italy. We computed the risk indexes taking into account the different clinical departments and the different hospitals involved. The approach proved to be useful to understand the HCO risk structure in terms of frequency, severity, expected and unexpected loss related to adverse events.

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.
A Practical Probabilistic Graphical Modeling Tool for Weighing Ecological Risk-Based Evidence

EPA Science Inventory

Past weight-of-evidence frameworks for adverse ecological effects have provided soft-scoring procedures for judgments based on the quality and measured attributes of evidence. Here, we provide a flexible probabilistic structure for weighing and integrating lines of evidence for e...
Rational risk-based decision support for drinking water well managers by optimized monitoring designs

NASA Astrophysics Data System (ADS)

Enzenhöfer, R.; Geiges, A.; Nowak, W.

2011-12-01

Advection-based well-head protection zones are commonly used to manage the contamination risk of drinking water wells. Considering the insufficient knowledge about hazards and transport properties within the catchment, current Water Safety Plans recommend that catchment managers and stakeholders know, control and monitor all possible hazards within the catchments and perform rational risk-based decisions. Our goal is to supply catchment managers with the required probabilistic risk information, and to generate tools that allow for optimal and rational allocation of resources between improved monitoring versus extended safety margins and risk mitigation measures. To support risk managers with the indispensable information, we address the epistemic uncertainty of advective-dispersive solute transport and well vulnerability (Enzenhoefer et al., 2011) within a stochastic simulation framework. Our framework can separate between uncertainty of contaminant location and actual dilution of peak concentrations by resolving heterogeneity with high-resolution Monte-Carlo simulation. To keep computational costs low, we solve the reverse temporal moment transport equation. Only in post-processing, we recover the time-dependent solute breakthrough curves and the deduced well vulnerability criteria from temporal moments by non-linear optimization. Our first step towards optimal risk management is optimal positioning of sampling locations and optimal choice of data types to reduce best the epistemic prediction uncertainty for well-head delineation, using the cross-bred Likelihood Uncertainty Estimator (CLUE, Leube et al., 2011) for optimal sampling design. Better monitoring leads to more reliable and realistic protection zones and thus helps catchment managers to better justify smaller, yet conservative safety margins. In order to allow an optimal choice in sampling strategies, we compare the trade-off in monitoring versus the delineation costs by accounting for ill
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.
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.
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.
Risk Management of NASA Projects

NASA Technical Reports Server (NTRS)

Sarper, Hueseyin

1997-01-01

Various NASA Langley Research Center and other center projects were attempted for analysis to obtain historical data comparing pre-phase A study and the final outcome for each project. This attempt, however, was abandoned once it became clear that very little documentation was available. Next, extensive literature search was conducted on the role of risk and reliability concepts in project management. Probabilistic risk assessment (PRA) techniques are being used with increasing regularity both in and outside of NASA. The value and the usage of PRA techniques were reviewed for large projects. It was found that both civilian and military branches of the space industry have traditionally refrained from using PRA, which was developed and expanded by nuclear industry. Although much has changed with the end of the cold war and the Challenger disaster, it was found that ingrained anti-PRA culture is hard to stop. Examples of skepticism against the use of risk management and assessment techniques were found both in the literature and in conversations with some technical staff. Program and project managers need to be convinced that the applicability and use of risk management and risk assessment techniques is much broader than just in the traditional safety-related areas of application. The time has come to begin to uniformly apply these techniques. The whole idea of risk-based system can maximize the 'return on investment' that the public demands. Also, it would be very useful if all project documents of NASA Langley Research Center, pre-phase A through final report, are carefully stored in a central repository preferably in electronic format.
WIPCast: Probabilistic Forecasting for Aviation Decision Aid Applications

DTIC Science & Technology

2011-06-01

traders, or families planning an outing – manage weather-related risk. By quantifying risk , probabilistic forecasting enables optimization of actions via...confidence interval to the user’s risk tolerance helps drive highly effective and innovative decision support mechanisms for visually quantifying risk for
Using probabilistic terrorism risk modeling for regulatory benefit-cost analysis: application to the Western hemisphere travel initiative in the land environment.

PubMed

Willis, Henry H; LaTourrette, Tom

2008-04-01

This article presents a framework for using probabilistic terrorism risk modeling in regulatory analysis. We demonstrate the framework with an example application involving a regulation under consideration, the Western Hemisphere Travel Initiative for the Land Environment, (WHTI-L). First, we estimate annualized loss from terrorist attacks with the Risk Management Solutions (RMS) Probabilistic Terrorism Model. We then estimate the critical risk reduction, which is the risk-reducing effectiveness of WHTI-L needed for its benefit, in terms of reduced terrorism loss in the United States, to exceed its cost. Our analysis indicates that the critical risk reduction depends strongly not only on uncertainties in the terrorism risk level, but also on uncertainty in the cost of regulation and how casualties are monetized. For a terrorism risk level based on the RMS standard risk estimate, the baseline regulatory cost estimate for WHTI-L, and a range of casualty cost estimates based on the willingness-to-pay approach, our estimate for the expected annualized loss from terrorism ranges from $2.7 billion to $5.2 billion. For this range in annualized loss, the critical risk reduction for WHTI-L ranges from 7% to 13%. Basing results on a lower risk level that results in halving the annualized terrorism loss would double the critical risk reduction (14-26%), and basing the results on a higher risk level that results in a doubling of the annualized terrorism loss would cut the critical risk reduction in half (3.5-6.6%). Ideally, decisions about terrorism security regulations and policies would be informed by true benefit-cost analyses in which the estimated benefits are compared to costs. Such analyses for terrorism security efforts face substantial impediments stemming from the great uncertainty in the terrorist threat and the very low recurrence interval for large attacks. Several approaches can be used to estimate how a terrorism security program or regulation reduces the
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.
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.
Transient flow conditions in probabilistic wellhead protection: importance and ways to manage spatial and temporal uncertainty in capture zone delineation

NASA Astrophysics Data System (ADS)

Enzenhoefer, R.; Rodriguez-Pretelin, A.; Nowak, W.

2012-12-01

"From an engineering standpoint, the quantification of uncertainty is extremely important not only because it allows estimating risk but mostly because it allows taking optimal decisions in an uncertain framework" (Renard, 2007). The most common way to account for uncertainty in the field of subsurface hydrology and wellhead protection is to randomize spatial parameters, e.g. the log-hydraulic conductivity or porosity. This enables water managers to take robust decisions in delineating wellhead protection zones with rationally chosen safety margins in the spirit of probabilistic risk management. Probabilistic wellhead protection zones are commonly based on steady-state flow fields. However, several past studies showed that transient flow conditions may substantially influence the shape and extent of catchments. Therefore, we believe they should be accounted for in the probabilistic assessment and in the delineation process. The aim of our work is to show the significance of flow transients and to investigate the interplay between spatial uncertainty and flow transients in wellhead protection zone delineation. To this end, we advance our concept of probabilistic capture zone delineation (Enzenhoefer et al., 2012) that works with capture probabilities and other probabilistic criteria for delineation. The extended framework is able to evaluate the time fraction that any point on a map falls within a capture zone. In short, we separate capture probabilities into spatial/statistical and time-related frequencies. This will provide water managers additional information on how to manage a well catchment in the light of possible hazard conditions close to the capture boundary under uncertain and time-variable flow conditions. In order to save computational costs, we take advantage of super-positioned flow components with time-variable coefficients. We assume an instantaneous development of steady-state flow conditions after each temporal change in driving forces, following
Risk Assessment: Evidence Base

NASA Technical Reports Server (NTRS)

Johnson-Throop, Kathy A.

2007-01-01

Human systems PRA (Probabilistic Risk Assessment: a) Provides quantitative measures of probability, consequence, and uncertainty; and b) Communicates risk and informs decision-making. Human health risks rated highest in ISS PRA are based on 1997 assessment of clinical events in analog operational settings. Much work remains to analyze remaining human health risks identified in Bioastronautics Roadmap.
Robust Decision Making Approach to Managing Water Resource Risks (Invited)

NASA Astrophysics Data System (ADS)

Lempert, R.

2010-12-01

The IPCC and US National Academies of Science have recommended iterative risk management as the best approach for water management and many other types of climate-related decisions. Such an approach does not rely on a single set of judgments at any one time but rather actively updates and refines strategies as new information emerges. In addition, the approach emphasizes that a portfolio of different types of responses, rather than any single action, often provides the best means to manage uncertainty. Implementing an iterative risk management approach can however prove difficult in actual decision support applications. This talk will suggest that robust decision making (RDM) provides a particularly useful set of quantitative methods for implementing iterative risk management. This RDM approach is currently being used in a wide variety of water management applications. RDM employs three key concepts that differentiate it from most types of probabilistic risk analysis: 1) characterizing uncertainty with multiple views of the future (which can include sets of probability distributions) rather than a single probabilistic best-estimate, 2) employing a robustness rather than an optimality criterion to assess alternative policies, and 3) organizing the analysis with a vulnerability and response option framework, rather than a predict-then-act framework. This talk will summarize the RDM approach, describe its use in several different types of water management applications, and compare the results to those obtained with other methods.
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.
Flood risk and adaptation strategies under climate change and urban expansion: A probabilistic analysis using global data.

PubMed

Muis, Sanne; Güneralp, Burak; Jongman, Brenden; Aerts, Jeroen C J H; Ward, Philip J

2015-12-15

An accurate understanding of flood risk and its drivers is crucial for effective risk management. Detailed risk projections, including uncertainties, are however rarely available, particularly in developing countries. This paper presents a method that integrates recent advances in global-scale modeling of flood hazard and land change, which enables the probabilistic analysis of future trends in national-scale flood risk. We demonstrate its application to Indonesia. We develop 1000 spatially-explicit projections of urban expansion from 2000 to 2030 that account for uncertainty associated with population and economic growth projections, as well as uncertainty in where urban land change may occur. The projections show that the urban extent increases by 215%-357% (5th and 95th percentiles). Urban expansion is particularly rapid on Java, which accounts for 79% of the national increase. From 2000 to 2030, increases in exposure will elevate flood risk by, on average, 76% and 120% for river and coastal floods. While sea level rise will further increase the exposure-induced trend by 19%-37%, the response of river floods to climate change is highly uncertain. However, as urban expansion is the main driver of future risk, the implementation of adaptation measures is increasingly urgent, regardless of the wide uncertainty in climate projections. Using probabilistic urban projections, we show that spatial planning can be a very effective adaptation strategy. Our study emphasizes that global data can be used successfully for probabilistic risk assessment in data-scarce countries. Copyright © 2015 Elsevier B.V. All rights reserved.
Software risk estimation and management techniques at JPL

NASA Technical Reports Server (NTRS)

Hihn, J.; Lum, K.

2002-01-01

In this talk we will discuss how uncertainty has been incorporated into the JPL software model, probabilistic-based estimates, and how risk is addressed, how cost risk is currently being explored via a variety of approaches, from traditional risk lists, to detailed WBS-based risk estimates to the Defect Detection and Prevention (DDP) tool.
Uncertainty characterization approaches for risk assessment of DBPs in drinking water: a review.

PubMed

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

2009-04-01

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

NASA Astrophysics Data System (ADS)

Wahl, Thomas; Plant, Nathaniel G.; Long, Joseph W.

2016-05-01

We assess erosion and flooding risk in the northern Gulf of Mexico by identifying interdependencies among oceanographic drivers and probabilistically modeling the resulting potential for coastal change. Wave and water level observations are used to determine relationships between six hydrodynamic parameters that influence total water level and therefore erosion and flooding, through consideration of a wide range of univariate distribution functions and multivariate elliptical copulas. Using these relationships, we explore how different our interpretation of the present-day erosion/flooding risk could be if we had seen more or fewer extreme realizations of individual and combinations of parameters in the past by simulating 10,000 physically and statistically consistent sea-storm time series. We find that seasonal total water levels associated with the 100 year return period could be up to 3 m higher in summer and 0.6 m higher in winter relative to our best estimate based on the observational records. Impact hours of collision and overwash—where total water levels exceed the dune toe or dune crest elevations—could be on average 70% (collision) and 100% (overwash) larger than inferred from the observations. Our model accounts for non-stationarity in a straightforward, non-parametric way that can be applied (with little adjustments) to many other coastlines. The probabilistic model presented here, which accounts for observational uncertainty, can be applied to other coastlines where short record lengths limit the ability to identify the full range of possible wave and water level conditions that coastal mangers and planners must consider to develop sustainable management strategies.
Probabilistic assessment of erosion and flooding risk in the northern Gulf of Mexico

USGS Publications Warehouse

Plant, Nathaniel G.; Wahl, Thomas; Long, Joseph W.

2016-01-01

We assess erosion and flooding risk in the northern Gulf of Mexico by identifying interdependencies among oceanographic drivers and probabilistically modeling the resulting potential for coastal change. Wave and water level observations are used to determine relationships between six hydrodynamic parameters that influence total water level and therefore erosion and flooding, through consideration of a wide range of univariate distribution functions and multivariate elliptical copulas. Using these relationships, we explore how different our interpretation of the present-day erosion/flooding risk could be if we had seen more or fewer extreme realizations of individual and combinations of parameters in the past by simulating 10,000 physically and statistically consistent sea-storm time series. We find that seasonal total water levels associated with the 100 year return period could be up to 3 m higher in summer and 0.6 m higher in winter relative to our best estimate based on the observational records. Impact hours of collision and overwash—where total water levels exceed the dune toe or dune crest elevations—could be on average 70% (collision) and 100% (overwash) larger than inferred from the observations. Our model accounts for non-stationarity in a straightforward, non-parametric way that can be applied (with little adjustments) to many other coastlines. The probabilistic model presented here, which accounts for observational uncertainty, can be applied to other coastlines where short record lengths limit the ability to identify the full range of possible wave and water level conditions that coastal mangers and planners must consider to develop sustainable management strategies.

Comparison of a Traditional Probabilistic Risk Assessment Approach with Advanced Safety Analysis

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

Smith, Curtis L; Mandelli, Diego; Zhegang Ma

2014-11-01

As part of the Light Water Sustainability Program (LWRS) [1], the purpose of the Risk Informed Safety Margin Characterization (RISMC) [2] Pathway research and development (R&D) is to support plant decisions for risk-informed margin management with the aim to improve economics, reliability, and sustain safety of current NPPs. In this paper, we describe the RISMC analysis process illustrating how mechanistic and probabilistic approaches are combined in order to estimate a safety margin. We use the scenario of a “station blackout” (SBO) wherein offsite power and onsite power is lost, thereby causing a challenge to plant safety systems. We describe themore » RISMC approach, illustrate the station blackout modeling, and contrast this with traditional risk analysis modeling for this type of accident scenario. We also describe our approach we are using to represent advanced flooding analysis.« less
Propagating Water Quality Analysis Uncertainty Into Resource Management Decisions Through Probabilistic Modeling

NASA Astrophysics Data System (ADS)

Gronewold, A. D.; Wolpert, R. L.; Reckhow, K. H.

2007-12-01

Most probable number (MPN) and colony-forming-unit (CFU) are two estimates of fecal coliform bacteria concentration commonly used as measures of water quality in United States shellfish harvesting waters. The MPN is the maximum likelihood estimate (or MLE) of the true fecal coliform concentration based on counts of non-sterile tubes in serial dilution of a sample aliquot, indicating bacterial metabolic activity. The CFU is the MLE of the true fecal coliform concentration based on the number of bacteria colonies emerging on a growth plate after inoculation from a sample aliquot. Each estimating procedure has intrinsic variability and is subject to additional uncertainty arising from minor variations in experimental protocol. Several versions of each procedure (using different sized aliquots or different numbers of tubes, for example) are in common use, each with its own levels of probabilistic and experimental error and uncertainty. It has been observed empirically that the MPN procedure is more variable than the CFU procedure, and that MPN estimates are somewhat higher on average than CFU estimates, on split samples from the same water bodies. We construct a probabilistic model that provides a clear theoretical explanation for the observed variability in, and discrepancy between, MPN and CFU measurements. We then explore how this variability and uncertainty might propagate into shellfish harvesting area management decisions through a two-phased modeling strategy. First, we apply our probabilistic model in a simulation-based analysis of future water quality standard violation frequencies under alternative land use scenarios, such as those evaluated under guidelines of the total maximum daily load (TMDL) program. Second, we apply our model to water quality data from shellfish harvesting areas which at present are closed (either conditionally or permanently) to shellfishing, to determine if alternative laboratory analysis procedures might have led to different
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.
Equipment management risk rating system based on engineering endpoints.

PubMed

James, P J

1999-01-01

The equipment management risk ratings system outlined here offers two significant departures from current practice: risk classifications are based on intrinsic device risks, and the risk rating system is based on engineering endpoints. Intrinsic device risks are categorized as physical, clinical and technical, and these flow from the incoming equipment assessment process. Engineering risk management is based on verification of engineering endpoints such as clinical measurements or energy delivery. This practice eliminates the ambiguity associated with ranking risk in terms of physiologic and higher-level outcome endpoints such as no significant hazards, low significance, injury, or mortality.
A Two-Stage Probabilistic Approach to Manage Personal Worklist in Workflow Management Systems

NASA Astrophysics Data System (ADS)

Han, Rui; Liu, Yingbo; Wen, Lijie; Wang, Jianmin

The application of workflow scheduling in managing individual actor's personal worklist is one area that can bring great improvement to business process. However, current deterministic work cannot adapt to the dynamics and uncertainties in the management of personal worklist. For such an issue, this paper proposes a two-stage probabilistic approach which aims at assisting actors to flexibly manage their personal worklists. To be specific, the approach analyzes every activity instance's continuous probability of satisfying deadline at the first stage. Based on this stochastic analysis result, at the second stage, an innovative scheduling strategy is proposed to minimize the overall deadline violation cost for an actor's personal worklist. Simultaneously, the strategy recommends the actor a feasible worklist of activity instances which meet the required bottom line of successful execution. The effectiveness of our approach is evaluated in a real-world workflow management system and with large scale simulation experiments.
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.
Future trends in flood risk in Indonesia - A probabilistic approach

NASA Astrophysics Data System (ADS)

Muis, Sanne; Guneralp, Burak; Jongman, Brenden; Ward, Philip

2014-05-01

Indonesia is one of the 10 most populous countries in the world and is highly vulnerable to (river) flooding. Catastrophic floods occur on a regular basis; total estimated damages were US 0.8 bn in 2010 and US 3 bn in 2013. Large parts of Greater Jakarta, the capital city, are annually subject to flooding. Flood risks (i.e. the product of hazard, exposure and vulnerability) are increasing due to rapid increases in exposure, such as strong population growth and ongoing economic development. The increase in risk may also be amplified by increasing flood hazards, such as increasing flood frequency and intensity due to climate change and land subsidence. The implementation of adaptation measures, such as the construction of dykes and strategic urban planning, may counteract these increasing trends. However, despite its importance for adaptation planning, a comprehensive assessment of current and future flood risk in Indonesia is lacking. This contribution addresses this issue and aims to provide insight into how socio-economic trends and climate change projections may shape future flood risks in Indonesia. Flood risk were calculated using an adapted version of the GLOFRIS global flood risk assessment model. Using this approach, we produced probabilistic maps of flood risks (i.e. annual expected damage) at a resolution of 30"x30" (ca. 1km x 1km at the equator). To represent flood exposure, we produced probabilistic projections of urban growth in a Monte-Carlo fashion based on probability density functions of projected population and GDP values for 2030. To represent flood hazard, inundation maps were computed using the hydrological-hydraulic component of GLOFRIS. These maps show flood inundation extent and depth for several return periods and were produced for several combinations of GCMs and future socioeconomic scenarios. Finally, the implementation of different adaptation strategies was incorporated into the model to explore to what extent adaptation may be able to
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.
Behavior-Based Safety and Occupational Risk Management

ERIC Educational Resources Information Center

Geller, E. Scott

2005-01-01

The behavior-based approach to managing occupational risk and preventing workplace injuries is reviewed. Unlike the typical top-down control approach to industrial safety, behavior-based safety (BBS) provides tools and procedures workers can use to take personal control of occupational risks. Strategies the author and his colleagues have been…
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.
Probabilistic Wind Power Ramp Forecasting Based on a Scenario Generation Method

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

Wang, Qin; Florita, Anthony R; Krishnan, Venkat K

Wind power ramps (WPRs) are particularly important in the management and dispatch of wind power and currently drawing the attention of balancing authorities. With the aim to reduce the impact of WPRs for power system operations, this paper develops a probabilistic ramp forecasting method based on a large number of simulated scenarios. An ensemble machine learning technique is first adopted to forecast the basic wind power forecasting scenario and calculate the historical forecasting errors. A continuous Gaussian mixture model (GMM) is used to fit the probability distribution function (PDF) of forecasting errors. The cumulative distribution function (CDF) is analytically deduced.more » The inverse transform method based on Monte Carlo sampling and the CDF is used to generate a massive number of forecasting error scenarios. An optimized swinging door algorithm is adopted to extract all the WPRs from the complete set of wind power forecasting scenarios. The probabilistic forecasting results of ramp duration and start-time are generated based on all scenarios. Numerical simulations on publicly available wind power data show that within a predefined tolerance level, the developed probabilistic wind power ramp forecasting method is able to predict WPRs with a high level of sharpness and accuracy.« less
Probabilistic flood damage modelling at the meso-scale

NASA Astrophysics Data System (ADS)

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

2014-05-01

Decisions on flood risk management and adaptation are usually based on risk analyses. 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. Most damage models have in common that complex damaging processes are described by simple, deterministic approaches like stage-damage functions. Novel probabilistic, multi-variate flood damage 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 show how the model BT-FLEMO (Bagging decision Tree based Flood Loss Estimation MOdel) can be applied on the meso-scale, namely on the basis of ATKIS land-use units. The model is applied in 19 municipalities which were affected during the 2002 flood by the River Mulde in Saxony, Germany. The application of BT-FLEMO provides a probability distribution of estimated damage to residential buildings per municipality. Validation is undertaken on the one hand via a comparison with eight other damage models including stage-damage functions as well as multi-variate models. On the other hand the results are compared with official damage data provided by the Saxon Relief Bank (SAB). The results show, that uncertainties of damage estimation remain high. Thus, the significant advantage of this probabilistic flood loss estimation model BT-FLEMO is that it inherently provides quantitative information about the uncertainty of the prediction. Reference: Merz, B.; Kreibich, H.; Lall, U. (2013): Multi-variate flood damage assessment: a tree-based data-mining approach. NHESS, 13(1), 53-64.
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.
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.
Risk management for the Space Exploration Initiative

NASA Technical Reports Server (NTRS)

Buchbinder, Ben

1993-01-01

Probabilistic Risk Assessment (PRA) is a quantitative engineering process that provides the analytic structure and decision-making framework for total programmatic risk management. Ideally, it is initiated in the conceptual design phase and used throughout the program life cycle. Although PRA was developed for assessment of safety, reliability, and availability risk, it has far greater application. Throughout the design phase, PRA can guide trade-off studies among system performance, safety, reliability, cost, and schedule. These studies are based on the assessment of the risk of meeting each parameter goal, with full consideration of the uncertainties. Quantitative trade-off studies are essential, but without full identification, propagation, and display of uncertainties, poor decisions may result. PRA also can focus attention on risk drivers in situations where risk is too high. For example, if safety risk is unacceptable, the PRA prioritizes the risk contributors to guide the use of resources for risk mitigation. PRA is used in the Space Exploration Initiative (SEI) Program. To meet the stringent requirements of the SEI mission, within strict budgetary constraints, the PRA structure supports informed and traceable decision-making. This paper briefly describes the SEI PRA process.
Comparing probabilistic microbial risk assessments for drinking water against daily rather than annualised infection probability targets.

PubMed

Signor, R S; Ashbolt, N J

2009-12-01

Some national drinking water guidelines provide guidance on how to define 'safe' drinking water. Regarding microbial water quality, a common position is that the chance of an individual becoming infected by some reference waterborne pathogen (e.g. Cryptsporidium) present in the drinking water should < 10(-4) in any year. However the instantaneous levels of risk to a water consumer vary over the course of a year, and waterborne disease outbreaks have been associated with shorter-duration periods of heightened risk. Performing probabilistic microbial risk assessments is becoming commonplace to capture the impacts of temporal variability on overall infection risk levels. A case is presented here for adoption of a shorter-duration reference period (i.e. daily) infection probability target over which to assess, report and benchmark such risks. A daily infection probability benchmark may provide added incentive and guidance for exercising control over short-term adverse risk fluctuation events and their causes. Management planning could involve outlining measures so that the daily target is met under a variety of pre-identified event scenarios. Other benefits of a daily target could include providing a platform for managers to design and assess management initiatives, as well as simplifying the technical components of the risk assessment process.
Use of documentary sources on past flood events for flood risk management and land planning

NASA Astrophysics Data System (ADS)

Cœur, Denis; Lang, Michel

2008-09-01

The knowledge of past catastrophic events can improve flood risk mitigation policy, with a better awareness against risk. As such historical information is usually available in Europe for the past five centuries, historians are able to understand how past society dealt with flood risk, and hydrologists can include information on past floods into an adapted probabilistic framework. In France, Flood Risk Mitigation Maps are based either on the largest historical known flood event or on the 100-year flood event if it is greater. Two actions can be suggested in terms of promoting the use of historical information for flood risk management: (1) the development of a regional flood data base, with both historical and current data, in order to get a good feedback on recent events and to improve the flood risk education and awareness; (2) the commitment to keep a persistent/perennial management of a reference network of hydrometeorological observations for climate change studies.
Adolescents' Heightened Risk-Seeking in a Probabilistic Gambling Task

ERIC Educational Resources Information Center

Burnett, Stephanie; Bault, Nadege; Coricelli, Giorgio; Blakemore, Sarah-Jayne

2010-01-01

This study investigated adolescent males' decision-making under risk, and the emotional response to decision outcomes, using a probabilistic gambling task designed to evoke counterfactually mediated emotions (relief and regret). Participants were 20 adolescents (aged 9-11), 26 young adolescents (aged 12-15), 20 mid-adolescents (aged 15-18) and 17…
How well does the Post-fire Erosion Risk Management Tool (ERMiT) really work?

NASA Astrophysics Data System (ADS)

Robichaud, Peter; Elliot, William; Lewis, Sarah; Miller, Mary Ellen

2016-04-01

The decision of where, when, and how to apply the most effective postfire erosion mitigation treatments requires land managers to assess the risk of damaging runoff and erosion events occurring after a fire. The Erosion Risk Management Tool (ERMiT) was developed to assist post fire assessment teams identify high erosion risk areas and effectiveness of various mitigation treatments to reduce that risk. ERMiT is a web-based application that uses the Water Erosion Prediction Project (WEPP) technology to estimate erosion, in probabilistic terms, on burned and recovering forest, range, and chaparral lands with and without the application of mitigation treatments. User inputs are processed by ERMiT to combine rain event variability with spatial and temporal variabilities of hillslope burn severity and soil properties which are then used as WEPP inputs. Since 2007, the model has been used in making hundreds of land management decisions in the US and elsewhere. We use eight published field study sites in the Western US to compare ERMiT predictions to observed hillslope erosion rates. Most sites experience only a few rainfall events that produced runoff and sediment except for a California site with a Mediterranean climate. When hillslope erosion occurred, significant correlations occurred between the observed hillslope erosion and those predicted by ERMiT. Significant correlation occurred for most mitigation treatments as well as the five recovery years. These model validation results suggest reasonable estimates of probabilistic post-fire hillslope sediment delivery when compared to observation.
Integrating legal liabilities in nanomanufacturing risk management.

PubMed

Mohan, Mayank; Trump, Benjamin D; Bates, Matthew E; Monica, John C; Linkov, Igor

2012-08-07

Among other things, the wide-scale development and use of nanomaterials is expected to produce costly regulatory and civil liabilities for nanomanufacturers due to lingering uncertainties, unanticipated effects, and potential toxicity. The life-cycle environmental, health, and safety (EHS) risks of nanomaterials are currently being studied, but the corresponding legal risks have not been systematically addressed. With the aid of a systematic approach that holistically evaluates and accounts for uncertainties about the inherent properties of nanomaterials, it is possible to provide an order of magnitude estimate of liability risks from regulatory and litigious sources based on current knowledge. In this work, we present a conceptual framework for integrating estimated legal liabilities with EHS risks across nanomaterial life-cycle stages using empirical knowledge in the field, scientific and legal judgment, probabilistic risk assessment, and multicriteria decision analysis. Such estimates will provide investors and operators with a basis to compare different technologies and practices and will also inform regulatory and legislative bodies in determining standards that balance risks with technical advancement. We illustrate the framework through the hypothetical case of a manufacturer of nanoscale titanium dioxide and use the resulting expected legal costs to evaluate alternative risk-management actions.

Probabilistic Wind Power Ramp Forecasting Based on a Scenario Generation Method: Preprint

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

Wang, Qin; Florita, Anthony R; Krishnan, Venkat K

2017-08-31

Wind power ramps (WPRs) are particularly important in the management and dispatch of wind power, and they are currently drawing the attention of balancing authorities. With the aim to reduce the impact of WPRs for power system operations, this paper develops a probabilistic ramp forecasting method based on a large number of simulated scenarios. An ensemble machine learning technique is first adopted to forecast the basic wind power forecasting scenario and calculate the historical forecasting errors. A continuous Gaussian mixture model (GMM) is used to fit the probability distribution function (PDF) of forecasting errors. The cumulative distribution function (CDF) ismore » analytically deduced. The inverse transform method based on Monte Carlo sampling and the CDF is used to generate a massive number of forecasting error scenarios. An optimized swinging door algorithm is adopted to extract all the WPRs from the complete set of wind power forecasting scenarios. The probabilistic forecasting results of ramp duration and start time are generated based on all scenarios. Numerical simulations on publicly available wind power data show that within a predefined tolerance level, the developed probabilistic wind power ramp forecasting method is able to predict WPRs with a high level of sharpness and accuracy.« less
A Probabilistic Asteroid Impact Risk Model

NASA Technical Reports Server (NTRS)

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

2016-01-01

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 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. 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 has little effect on the metrics of interest.
The Research on Safety Management Information System of Railway Passenger Based on Risk Management Theory

NASA Astrophysics Data System (ADS)

Zhu, Wenmin; Jia, Yuanhua

2018-01-01

Based on the risk management theory and the PDCA cycle model, requirements of the railway passenger transport safety production is analyzed, and the establishment of the security risk assessment team is proposed to manage risk by FTA with Delphi from both qualitative and quantitative aspects. The safety production committee is also established to accomplish performance appraisal, which is for further ensuring the correctness of risk management results, optimizing the safety management business processes and improving risk management capabilities. The basic framework and risk information database of risk management information system of railway passenger transport safety are designed by Ajax, Web Services and SQL technologies. The system realizes functions about risk management, performance appraisal and data management, and provides an efficient and convenient information management platform for railway passenger safety manager.
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.
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
The case for probabilistic forecasting in hydrology

NASA Astrophysics Data System (ADS)

Krzysztofowicz, Roman

2001-08-01

That forecasts should be stated in probabilistic, rather than deterministic, terms has been argued from common sense and decision-theoretic perspectives for almost a century. Yet most operational hydrological forecasting systems produce deterministic forecasts and most research in operational hydrology has been devoted to finding the 'best' estimates rather than quantifying the predictive uncertainty. This essay presents a compendium of reasons for probabilistic forecasting of hydrological variates. Probabilistic forecasts are scientifically more honest, enable risk-based warnings of floods, enable rational decision making, and offer additional economic benefits. The growing demand for information about risk and the rising capability to quantify predictive uncertainties create an unparalleled opportunity for the hydrological profession to dramatically enhance the forecasting paradigm.
Progress report on the Worldwide Earthquake Risk Management (WWERM) Program

USGS Publications Warehouse

Algermissen, S.T.; Hays, Walter W.; Krumpe, Paul R.

1992-01-01

Considerable progress has been made in the Worldwide Earthquake Risk Management (WWERM) Program since its initiation in late 1989 as a cooperative program of the Agency for International Development (AID), Office of U.S. Foreign Disaster Assistance (OFDA), and the U.S. Geological Survey. Probabilistic peak acceleration and peak Modified Mercalli intensity (MMI) maps have been prepared for Chile and for Sulawesi province in Indonesia. Earthquake risk (loss) studies for dwellings in Gorontalo, North Sulawesi, have been completed and risk studies for dwellings in selected areas of central Chile are underway. A special study of the effect of site response on earthquake ground motion estimation in central Chile has also been completed and indicates that site response may modify the ground shaking by as much as plus or minus two units of MMI. A program for the development of national probabilistic ground motion maps for the Philippines is now underway and pilot studies of earthquake ground motion and risk are being planned for Morocco.
The Effect of Forest Management Strategy on Carbon Storage and Revenue in Western Washington: A Probabilistic Simulation of Tradeoffs.

PubMed

Fischer, Paul W; Cullen, Alison C; Ettl, Gregory J

2017-01-01

The objectives of this study are to understand tradeoffs between forest carbon and timber values, and evaluate the impact of uncertainty in improved forest management (IFM) carbon offset projects to improve forest management decisions. The study uses probabilistic simulation of uncertainty in financial risk for three management scenarios (clearcutting in 45- and 65-year rotations and no harvest) under three carbon price schemes (historic voluntary market prices, cap and trade, and carbon prices set to equal net present value (NPV) from timber-oriented management). Uncertainty is modeled for value and amount of carbon credits and wood products, the accuracy of forest growth model forecasts, and four other variables relevant to American Carbon Registry methodology. Calculations use forest inventory data from a 1,740 ha forest in western Washington State, using the Forest Vegetation Simulator (FVS) growth model. Sensitivity analysis shows that FVS model uncertainty contributes more than 70% to overall NPV variance, followed in importance by variability in inventory sample (3-14%), and short-term prices for timber products (8%), while variability in carbon credit price has little influence (1.1%). At regional average land-holding costs, a no-harvest management scenario would become revenue-positive at a carbon credit break-point price of $14.17/Mg carbon dioxide equivalent (CO 2 e). IFM carbon projects are associated with a greater chance of both large payouts and large losses to landowners. These results inform policymakers and forest owners of the carbon credit price necessary for IFM approaches to equal or better the business-as-usual strategy, while highlighting the magnitude of financial risk and reward through probabilistic simulation. © 2016 Society for Risk Analysis.
A risk assessment methodology to evaluate the risk failure of managed aquifer recharge in the Mediterranean Basin

NASA Astrophysics Data System (ADS)

Rodríguez-Escales, Paula; Canelles, Arnau; Sanchez-Vila, Xavier; Folch, Albert; Kurtzman, Daniel; Rossetto, Rudy; Fernández-Escalante, Enrique; Lobo-Ferreira, João-Paulo; Sapiano, Manuel; San-Sebastián, Jon; Schüth, Christoph

2018-06-01

Managed aquifer recharge (MAR) can be affected by many risks. Those risks are related to different technical and non-technical aspects of recharge, like water availability, water quality, legislation, social issues, etc. Many other works have acknowledged risks of this nature theoretically; however, their quantification and definition has not been developed. In this study, the risk definition and quantification has been performed by means of fault trees and probabilistic risk assessment (PRA). We defined a fault tree with 65 basic events applicable to the operation phase. After that, we have applied this methodology to six different managed aquifer recharge sites located in the Mediterranean Basin (Portugal, Spain, Italy, Malta, and Israel). The probabilities of the basic events were defined by expert criteria, based on the knowledge of the different managers of the facilities. From that, we conclude that in all sites, the perception of the expert criteria of the non-technical aspects were as much or even more important than the technical aspects. Regarding the risk results, we observe that the total risk in three of the six sites was equal to or above 0.90. That would mean that the MAR facilities have a risk of failure equal to or higher than 90 % in the period of 2-6 years. The other three sites presented lower risks (75, 29, and 18 % for Malta, Menashe, and Serchio, respectively).
The probabilistic nature of preferential choice.

PubMed

Rieskamp, Jörg

2008-11-01

Previous research has developed a variety of theories explaining when and why people's decisions under risk deviate from the standard economic view of expected utility maximization. These theories are limited in their predictive accuracy in that they do not explain the probabilistic nature of preferential choice, that is, why an individual makes different choices in nearly identical situations, or why the magnitude of these inconsistencies varies in different situations. To illustrate the advantage of probabilistic theories, three probabilistic theories of decision making under risk are compared with their deterministic counterparts. The probabilistic theories are (a) a probabilistic version of a simple choice heuristic, (b) a probabilistic version of cumulative prospect theory, and (c) decision field theory. By testing the theories with the data from three experimental studies, the superiority of the probabilistic models over their deterministic counterparts in predicting people's decisions under risk become evident. When testing the probabilistic theories against each other, decision field theory provides the best account of the observed behavior.
Application of Risk Assessment Tools in the Continuous Risk Management (CRM) Process

NASA Technical Reports Server (NTRS)

Ray, Paul S.

2002-01-01

Marshall Space Flight Center (MSFC) of the National Aeronautics and Space Administration (NASA) is currently implementing the Continuous Risk Management (CRM) Program developed by the Carnegie Mellon University and recommended by NASA as the Risk Management (RM) implementation approach. The four most frequently used risk assessment tools in the center are: (a) Failure Modes and Effects Analysis (FMEA), Hazard Analysis (HA), Fault Tree Analysis (FTA), and Probabilistic Risk Analysis (PRA). There are some guidelines for selecting the type of risk assessment tools during the project formulation phase of a project, but there is not enough guidance as to how to apply these tools in the Continuous Risk Management process (CRM). But the ways the safety and risk assessment tools are used make a significant difference in the effectiveness in the risk management function. Decisions regarding, what events are to be included in the analysis, to what level of details should the analysis be continued, make significant difference in the effectiveness of risk management program. Tools of risk analysis also depends on the phase of a project e.g. at the initial phase of a project, when not much data are available on hardware, standard FMEA cannot be applied; instead a functional FMEA may be appropriate. This study attempted to provide some directives to alleviate the difficulty in applying FTA, PRA, and FMEA in the CRM process. Hazard Analysis was not included in the scope of the study due to the short duration of the summer research project.
An integrated GIS-based interval-probabilistic programming model for land-use planning management under uncertainty--a case study at Suzhou, China.

PubMed

Lu, Shasha; Zhou, Min; Guan, Xingliang; Tao, Lizao

2015-03-01

A large number of mathematical models have been developed for supporting optimization of land-use allocation; however, few of them simultaneously consider land suitability (e.g., physical features and spatial information) and various uncertainties existing in many factors (e.g., land availabilities, land demands, land-use patterns, and ecological requirements). This paper incorporates geographic information system (GIS) technology into interval-probabilistic programming (IPP) for land-use planning management (IPP-LUPM). GIS is utilized to assemble data for the aggregated land-use alternatives, and IPP is developed for tackling uncertainties presented as discrete intervals and probability distribution. Based on GIS, the suitability maps of different land users are provided by the outcomes of land suitability assessment and spatial analysis. The maximum area of every type of land use obtained from the suitability maps, as well as various objectives/constraints (i.e., land supply, land demand of socioeconomic development, future development strategies, and environmental capacity), is used as input data for the optimization of land-use areas with IPP-LUPM model. The proposed model not only considers the outcomes of land suitability evaluation (i.e., topography, ground conditions, hydrology, and spatial location) but also involves economic factors, food security, and eco-environmental constraints, which can effectively reflect various interrelations among different aspects in a land-use planning management system. The case study results at Suzhou, China, demonstrate that the model can help to examine the reliability of satisfying (or risk of violating) system constraints under uncertainty. Moreover, it may identify the quantitative relationship between land suitability and system benefits. Willingness to arrange the land areas based on the condition of highly suitable land will not only reduce the potential conflicts on the environmental system but also lead to a lower
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
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
Developing EHR-driven heart failure risk prediction models using CPXR(Log) with the probabilistic loss function.

PubMed

Taslimitehrani, Vahid; Dong, Guozhu; Pereira, Naveen L; Panahiazar, Maryam; Pathak, Jyotishman

2016-04-01

Computerized survival prediction in healthcare identifying the risk of disease mortality, helps healthcare providers to effectively manage their patients by providing appropriate treatment options. In this study, we propose to apply a classification algorithm, Contrast Pattern Aided Logistic Regression (CPXR(Log)) with the probabilistic loss function, to develop and validate prognostic risk models to predict 1, 2, and 5year survival in heart failure (HF) using data from electronic health records (EHRs) at Mayo Clinic. The CPXR(Log) constructs a pattern aided logistic regression model defined by several patterns and corresponding local logistic regression models. One of the models generated by CPXR(Log) achieved an AUC and accuracy of 0.94 and 0.91, respectively, and significantly outperformed prognostic models reported in prior studies. Data extracted from EHRs allowed incorporation of patient co-morbidities into our models which helped improve the performance of the CPXR(Log) models (15.9% AUC improvement), although did not improve the accuracy of the models built by other classifiers. We also propose a probabilistic loss function to determine the large error and small error instances. The new loss function used in the algorithm outperforms other functions used in the previous studies by 1% improvement in the AUC. This study revealed that using EHR data to build prediction models can be very challenging using existing classification methods due to the high dimensionality and complexity of EHR data. The risk models developed by CPXR(Log) also reveal that HF is a highly heterogeneous disease, i.e., different subgroups of HF patients require different types of considerations with their diagnosis and treatment. Our risk models provided two valuable insights for application of predictive modeling techniques in biomedicine: Logistic risk models often make systematic prediction errors, and it is prudent to use subgroup based prediction models such as those given by CPXR
Practice management based on risk assessment.

PubMed

Sandberg, Hans

2004-01-01

The management of a dental practice is most often focused on what clinicians do (production of items), and not so much on what is achieved in terms of oral health. The main reason for this is probably that it is easier to measure production and more difficult to measure health outcome. This paper presents a model based on individual risk assessment that aims to achieve a financially sound economy and good oral health. The close-to-the-clinic management tool, the HIDEP Model (Health Improvement in a DEntal Practice) was pioneered initially in Sweden at the end of 1980s. The experience over a 15-year period with different elements of the model is presented, including: the basis of examination and risk assessment; motivation; task delegation and leadership issues; health-finance evaluations; and quality development within a dental clinic. DentiGroupXL, a software program designed to support the work based on the model, is also described.
Forecasting risk along a river basin using a probabilistic and deterministic model for environmental risk assessment of effluents through ecotoxicological evaluation and GIS.

PubMed

Gutiérrez, Simón; Fernandez, Carlos; Barata, Carlos; Tarazona, José Vicente

2009-12-20

This work presents a computer model for Risk Assessment of Basins by Ecotoxicological Evaluation (RABETOX). The model is based on whole effluent toxicity testing and water flows along a specific river basin. It is capable of estimating the risk along a river segment using deterministic and probabilistic approaches. The Henares River Basin was selected as a case study to demonstrate the importance of seasonal hydrological variations in Mediterranean regions. As model inputs, two different ecotoxicity tests (the miniaturized Daphnia magna acute test and the D.magna feeding test) were performed on grab samples from 5 waste water treatment plant effluents. Also used as model inputs were flow data from the past 25 years, water velocity measurements and precise distance measurements using Geographical Information Systems (GIS). The model was implemented into a spreadsheet and the results were interpreted and represented using GIS in order to facilitate risk communication. To better understand the bioassays results, the effluents were screened through SPME-GC/MS analysis. The deterministic model, performed each month during one calendar year, showed a significant seasonal variation of risk while revealing that September represents the worst-case scenario with values up to 950 Risk Units. This classifies the entire area of study for the month of September as "sublethal significant risk for standard species". The probabilistic approach using Monte Carlo analysis was performed on 7 different forecast points distributed along the Henares River. A 0% probability of finding "low risk" was found at all forecast points with a more than 50% probability of finding "potential risk for sensitive species". The values obtained through both the deterministic and probabilistic approximations reveal the presence of certain substances, which might be causing sublethal effects in the aquatic species present in the Henares River.
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
Risk-based management of invading plant disease.

PubMed

Hyatt-Twynam, Samuel R; Parnell, Stephen; Stutt, Richard O J H; Gottwald, Tim R; Gilligan, Christopher A; Cunniffe, Nik J

2017-05-01

Effective control of plant disease remains a key challenge. Eradication attempts often involve removal of host plants within a certain radius of detection, targeting asymptomatic infection. Here we develop and test potentially more effective, epidemiologically motivated, control strategies, using a mathematical model previously fitted to the spread of citrus canker in Florida. We test risk-based control, which preferentially removes hosts expected to cause a high number of infections in the remaining host population. Removals then depend on past patterns of pathogen spread and host removal, which might be nontransparent to affected stakeholders. This motivates a variable radius strategy, which approximates risk-based control via removal radii that vary by location, but which are fixed in advance of any epidemic. Risk-based control outperforms variable radius control, which in turn outperforms constant radius removal. This result is robust to changes in disease spread parameters and initial patterns of susceptible host plants. However, efficiency degrades if epidemiological parameters are incorrectly characterised. Risk-based control including additional epidemiology can be used to improve disease management, but it requires good prior knowledge for optimal performance. This focuses attention on gaining maximal information from past epidemics, on understanding model transferability between locations and on adaptive management strategies that change over time. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.
Probabilistic soil erosion modeling using the Erosion Risk Management Tool (ERMIT) after wildfires

Treesearch

P. R. Robichaud; W. J. Elliot; J. W. Wagenbrenner

2011-01-01

The decision of whether or not to apply post-fire hillslope erosion mitigation treatments, and if so, where these treatments are most needed, is a multi-step process. Land managers must assess the risk of damaging runoff and sediment delivery events occurring on the unrecovered burned hillslope. We developed the Erosion Risk Management Tool (ERMiT) to address this need...

Probabilistic dual heuristic programming-based adaptive critic

NASA Astrophysics Data System (ADS)

Herzallah, Randa

2010-02-01

Adaptive critic (AC) methods have common roots as generalisations of dynamic programming for neural reinforcement learning approaches. Since they approximate the dynamic programming solutions, they are potentially suitable for learning in noisy, non-linear and non-stationary environments. In this study, a novel probabilistic dual heuristic programming (DHP)-based AC controller is proposed. Distinct to current approaches, the proposed probabilistic (DHP) AC method takes uncertainties of forward model and inverse controller into consideration. Therefore, it is suitable for deterministic and stochastic control problems characterised by functional uncertainty. Theoretical development of the proposed method is validated by analytically evaluating the correct value of the cost function which satisfies the Bellman equation in a linear quadratic control problem. The target value of the probabilistic critic network is then calculated and shown to be equal to the analytically derived correct value. Full derivation of the Riccati solution for this non-standard stochastic linear quadratic control problem is also provided. Moreover, the performance of the proposed probabilistic controller is demonstrated on linear and non-linear control examples.
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 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.
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.
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 liquefaction triggering based on the cone penetration test

USGS Publications Warehouse

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

2005-01-01

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

PubMed

Jenkins, Katie; Hall, Jim; Glenis, Vassilis; Kilsby, Chris

2018-06-01

Flooding in urban areas during heavy rainfall, often characterized by short duration and high-intensity events, is known as "surface water flooding." Analyzing surface water flood risk is complex as it requires understanding of biophysical and human factors, such as the localized scale and nature of heavy precipitation events, characteristics of the urban area affected (including detailed topography and drainage networks), and the spatial distribution of economic and social vulnerability. Climate change is recognized as having the potential to enhance the intensity and frequency of heavy rainfall events. This study develops a methodology to link high spatial resolution probabilistic projections of hourly precipitation with detailed surface water flood depth maps and characterization of urban vulnerability to estimate surface water flood risk. It incorporates probabilistic information on the range of uncertainties in future precipitation in a changing climate. The method is applied to a case study of Greater London and highlights that both the frequency and spatial extent of surface water flood events are set to increase under future climate change. The expected annual damage from surface water flooding is estimated to be to be £171 million, £343 million, and £390 million/year under the baseline, 2030 high, and 2050 high climate change scenarios, respectively. © 2017 Society for Risk Analysis.
A novel probabilistic framework for event-based speech recognition

NASA Astrophysics Data System (ADS)

Juneja, Amit; Espy-Wilson, Carol

2003-10-01

One of the reasons for unsatisfactory performance of the state-of-the-art automatic speech recognition (ASR) systems is the inferior acoustic modeling of low-level acoustic-phonetic information in the speech signal. An acoustic-phonetic approach to ASR, on the other hand, explicitly targets linguistic information in the speech signal, but such a system for continuous speech recognition (CSR) is not known to exist. A probabilistic and statistical framework for CSR based on the idea of the representation of speech sounds by bundles of binary valued articulatory phonetic features is proposed. Multiple probabilistic sequences of linguistically motivated landmarks are obtained using binary classifiers of manner phonetic features-syllabic, sonorant and continuant-and the knowledge-based acoustic parameters (APs) that are acoustic correlates of those features. The landmarks are then used for the extraction of knowledge-based APs for source and place phonetic features and their binary classification. Probabilistic landmark sequences are constrained using manner class language models for isolated or connected word recognition. The proposed method could overcome the disadvantages encountered by the early acoustic-phonetic knowledge-based systems that led the ASR community to switch to systems highly dependent on statistical pattern analysis methods and probabilistic language or grammar models.
Fews-Risk: A step towards risk-based flood forecasting

NASA Astrophysics Data System (ADS)

Bachmann, Daniel; Eilander, Dirk; de Leeuw, Annemargreet; Diermanse, Ferdinand; Weerts, Albrecht; de Bruijn, Karin; Beckers, Joost; Boelee, Leonore; Brown, Emma; Hazlewood, Caroline

2015-04-01

Operational flood prediction and the assessment of flood risk are important components of flood management. Currently, the model-based prediction of discharge and/or water level in a river is common practice for operational flood forecasting. Based on the prediction of these values decisions about specific emergency measures are made within operational flood management. However, the information provided for decision support is restricted to pure hydrological or hydraulic aspects of a flood. Information about weak sections within the flood defences, flood prone areas and assets at risk in the protected areas are rarely used in a model-based flood forecasting system. This information is often available for strategic planning, but is not in an appropriate format for operational purposes. The idea of FEWS-Risk is the extension of existing flood forecasting systems with elements of strategic flood risk analysis, such as probabilistic failure analysis, two dimensional flood spreading simulation and the analysis of flood impacts and consequences. Thus, additional information is provided to the decision makers, such as: • Location, timing and probability of failure of defined sections of the flood defence line; • Flood spreading, extent and hydraulic values in the hinterland caused by an overflow or a breach flow • Impacts and consequences in case of flooding in the protected areas, such as injuries or casualties and/or damages to critical infrastructure or economy. In contrast with purely hydraulic-based operational information, these additional data focus upon decision support for answering crucial questions within an operational flood forecasting framework, such as: • Where should I reinforce my flood defence system? • What type of action can I take to mend a weak spot in my flood defences? • What are the consequences of a breach? • Which areas should I evacuate first? This presentation outlines the additional required workflows towards risk-based flood
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
Worksite-based cardiovascular risk screening and management: a feasibility study.

PubMed

Padwal, Raj; Rashead, Mohammad; Snider, Jonathan; Morrin, Louise; Lehman, Agnes; Campbell, Norm Rc

2017-01-01

Established cardiovascular risk factors are highly prevalent and contribute substantially to cardiovascular morbidity and mortality because they remain uncontrolled in many Canadians. Worksite-based cardiovascular risk factor screening and management represent a largely untapped strategy for optimizing risk factor control. In a 2-phase collaborative demonstration project between Alberta Health Services (AHS) and the Alberta Newsprint Company (ANC), ANC employees were offered cardiovascular risk factor screening and management. Screening was performed at the worksite by AHS nurses, who collected baseline history, performed automated blood pressure measurement and point-of-care testing for lipids and A1c, and calculated 10-year Framingham risk. Employees with a Framingham risk score of ≥10% and uncontrolled blood pressure, dyslipidemia, or smoking were offered 6 months of pharmacist case management to optimize their risk factor control. In total, 87 of 190 (46%) employees volunteered to undergo cardiovascular risk factor screening. Mean age was 44.5±11.9 years, 73 (83.9%) were male, 14 (16.1%) had hypertension, 4 (4.6%) had diabetes, 12 (13.8%) were current smokers, and 9 (10%) had dyslipidemia. Of 36 employees with an estimated Framingham risk score of ≥10%, 21 (58%) agreed to receive case management and 15 (42%) attended baseline and 6-month follow-up case management visits. Statistically significant reductions in left arm systolic blood pressure (-8.0±12.4 mmHg; p =0.03) and triglyceride levels (-0.8±1.4 mmol/L; p =0.04) occurred following case management. These findings demonstrate the feasibility and usefulness of collaborative, worksite-based cardiovascular risk factor screening and management. Expansion of this type of partnership in a cost-effective manner is warranted.
Time-based collision risk modeling for air traffic management

NASA Astrophysics Data System (ADS)

Bell, Alan E.

Since the emergence of commercial aviation in the early part of last century, economic forces have driven a steadily increasing demand for air transportation. Increasing density of aircraft operating in a finite volume of airspace is accompanied by a corresponding increase in the risk of collision, and in response to a growing number of incidents and accidents involving collisions between aircraft, governments worldwide have developed air traffic control systems and procedures to mitigate this risk. The objective of any collision risk management system is to project conflicts and provide operators with sufficient opportunity to recognize potential collisions and take necessary actions to avoid them. It is therefore the assertion of this research that the currency of collision risk management is time. Future Air Traffic Management Systems are being designed around the foundational principle of four dimensional trajectory based operations, a method that replaces legacy first-come, first-served sequencing priorities with time-based reservations throughout the airspace system. This research will demonstrate that if aircraft are to be sequenced in four dimensions, they must also be separated in four dimensions. In order to separate aircraft in four dimensions, time must emerge as the primary tool by which air traffic is managed. A functional relationship exists between the time-based performance of aircraft, the interval between aircraft scheduled to cross some three dimensional point in space, and the risk of collision. This research models that relationship and presents two key findings. First, a method is developed by which the ability of an aircraft to meet a required time of arrival may be expressed as a robust standard for both industry and operations. Second, a method by which airspace system capacity may be increased while maintaining an acceptable level of collision risk is presented and demonstrated for the purpose of formulating recommendations for procedures
Superposition-Based Analysis of First-Order Probabilistic Timed Automata

NASA Astrophysics Data System (ADS)

Fietzke, Arnaud; Hermanns, Holger; Weidenbach, Christoph

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

NASA Astrophysics Data System (ADS)

Henri, Christopher V.; Fernàndez-Garcia, Daniel; de Barros, Felipe P. J.

2015-06-01

The increasing presence of toxic chemicals released in the subsurface has led to a rapid growth of social concerns and the need to develop and employ models that can predict the impact of groundwater contamination on human health risk under uncertainty. Monitored natural attenuation is a common remediation action in many contamination cases. However, natural attenuation can lead to the production of daughter species of distinct toxicity that may pose challenges in pollution management strategies. The actual threat that these contaminants pose to human health depends on the interplay between the complex structure of the geological media and the toxicity of each pollutant byproduct. This work addresses human health risk for chemical mixtures resulting from the sequential degradation of a contaminant (such as a chlorinated solvent) under uncertainty through high-resolution three-dimensional numerical simulations. We systematically investigate the interaction between aquifer heterogeneity, flow connectivity, contaminant injection model, and chemical toxicity in the probabilistic characterization of health risk. We illustrate how chemical-specific travel times control the regime of the expected risk and its corresponding uncertainties. Results indicate conditions where preferential flow paths can favor the reduction of the overall risk of the chemical mixture. The overall human risk response to aquifer connectivity is shown to be nontrivial for multispecies transport. This nontriviality is a result of the interaction between aquifer heterogeneity and chemical toxicity. To quantify the joint effect of connectivity and toxicity in health risk, we propose a toxicity-based Damköhler number. Furthermore, we provide a statistical characterization in terms of low-order moments and the probability density function of the individual and total risks.
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.
Systems Reliability Framework for Surface Water Sustainability and Risk Management

NASA Astrophysics Data System (ADS)

Myers, J. R.; Yeghiazarian, L.

2016-12-01

With microbial contamination posing a serious threat to the availability of clean water across the world, it is necessary to develop a framework that evaluates the safety and sustainability of water systems in respect to non-point source fecal microbial contamination. The concept of water safety is closely related to the concept of failure in reliability theory. In water quality problems, the event of failure can be defined as the concentration of microbial contamination exceeding a certain standard for usability of water. It is pertinent in watershed management to know the likelihood of such an event of failure occurring at a particular point in space and time. Microbial fate and transport are driven by environmental processes taking place in complex, multi-component, interdependent environmental systems that are dynamic and spatially heterogeneous, which means these processes and therefore their influences upon microbial transport must be considered stochastic and variable through space and time. A physics-based stochastic model of microbial dynamics is presented that propagates uncertainty using a unique sampling method based on artificial neural networks to produce a correlation between watershed characteristics and spatial-temporal probabilistic patterns of microbial contamination. These results are used to address the question of water safety through several sustainability metrics: reliability, vulnerability, resilience and a composite sustainability index. System reliability is described uniquely though the temporal evolution of risk along watershed points or pathways. Probabilistic resilience describes how long the system is above a certain probability of failure, and the vulnerability metric describes how the temporal evolution of risk changes throughout a hierarchy of failure levels. Additionally our approach allows for the identification of contributions in microbial contamination and uncertainty from specific pathways and sources. We expect that this
Probabilistic approaches to accounting for data variability in the practical application of bioavailability in predicting aquatic risks from metals.

PubMed

Ciffroy, Philippe; Charlatchka, Rayna; Ferreira, Daniel; Marang, Laura

2013-07-01

The biotic ligand model (BLM) theoretically enables the derivation of environmental quality standards that are based on true bioavailable fractions of metals. Several physicochemical variables (especially pH, major cations, dissolved organic carbon, and dissolved metal concentrations) must, however, be assigned to run the BLM, but they are highly variable in time and space in natural systems. This article describes probabilistic approaches for integrating such variability during the derivation of risk indexes. To describe each variable using a probability density function (PDF), several methods were combined to 1) treat censored data (i.e., data below the limit of detection), 2) incorporate the uncertainty of the solid-to-liquid partitioning of metals, and 3) detect outliers. From a probabilistic perspective, 2 alternative approaches that are based on log-normal and Γ distributions were tested to estimate the probability of the predicted environmental concentration (PEC) exceeding the predicted non-effect concentration (PNEC), i.e., p(PEC/PNEC>1). The probabilistic approach was tested on 4 real-case studies based on Cu-related data collected from stations on the Loire and Moselle rivers. The approach described in this article is based on BLM tools that are freely available for end-users (i.e., the Bio-Met software) and on accessible statistical data treatments. This approach could be used by stakeholders who are involved in risk assessments of metals for improving site-specific studies. Copyright © 2013 SETAC.
Probabilistic Fatigue Life Updating for Railway Bridges Based on Local Inspection and Repair.

PubMed

Lee, Young-Joo; Kim, Robin E; Suh, Wonho; Park, Kiwon

2017-04-24

Railway bridges are exposed to repeated train loads, which may cause fatigue failure. As critical links in a transportation network, railway bridges are expected to survive for a target period of time, but sometimes they fail earlier than expected. To guarantee the target bridge life, bridge maintenance activities such as local inspection and repair should be undertaken properly. However, this is a challenging task because there are various sources of uncertainty associated with aging bridges, train loads, environmental conditions, and maintenance work. Therefore, to perform optimal risk-based maintenance of railway bridges, it is essential to estimate the probabilistic fatigue life of a railway bridge and update the life information based on the results of local inspections and repair. Recently, a system reliability approach was proposed to evaluate the fatigue failure risk of structural systems and update the prior risk information in various inspection scenarios. However, this approach can handle only a constant-amplitude load and has limitations in considering a cyclic load with varying amplitude levels, which is the major loading pattern generated by train traffic. In addition, it is not feasible to update the prior risk information after bridges are repaired. In this research, the system reliability approach is further developed so that it can handle a varying-amplitude load and update the system-level risk of fatigue failure for railway bridges after inspection and repair. The proposed method is applied to a numerical example of an in-service railway bridge, and the effects of inspection and repair on the probabilistic fatigue life are discussed.

Probabilistic Fatigue Life Updating for Railway Bridges Based on Local Inspection and Repair

PubMed Central

Lee, Young-Joo; Kim, Robin E.; Suh, Wonho; Park, Kiwon

2017-01-01

Railway bridges are exposed to repeated train loads, which may cause fatigue failure. As critical links in a transportation network, railway bridges are expected to survive for a target period of time, but sometimes they fail earlier than expected. To guarantee the target bridge life, bridge maintenance activities such as local inspection and repair should be undertaken properly. However, this is a challenging task because there are various sources of uncertainty associated with aging bridges, train loads, environmental conditions, and maintenance work. Therefore, to perform optimal risk-based maintenance of railway bridges, it is essential to estimate the probabilistic fatigue life of a railway bridge and update the life information based on the results of local inspections and repair. Recently, a system reliability approach was proposed to evaluate the fatigue failure risk of structural systems and update the prior risk information in various inspection scenarios. However, this approach can handle only a constant-amplitude load and has limitations in considering a cyclic load with varying amplitude levels, which is the major loading pattern generated by train traffic. In addition, it is not feasible to update the prior risk information after bridges are repaired. In this research, the system reliability approach is further developed so that it can handle a varying-amplitude load and update the system-level risk of fatigue failure for railway bridges after inspection and repair. The proposed method is applied to a numerical example of an in-service railway bridge, and the effects of inspection and repair on the probabilistic fatigue life are discussed. PMID:28441768
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
Towards risk-based drought management in the Netherlands: quantifying the welfare effects of water shortage

NASA Astrophysics Data System (ADS)

van der Vat, Marnix; Femke, Schasfoort; Rhee Gigi, Van; Manfred, Wienhoven; Nico, Polman; Joost, Delsman; den Hoek Paul, Van; Maat Judith, Ter; Marjolein, Mens

2016-04-01

It is widely acknowledged that drought management should move from a crisis to a risk-based approach. A risk-based approach to managing water resources requires a sound drought risk analysis, quantifying the probability and impacts of water shortage due to droughts. Impacts of droughts are for example crop yield losses, hydropower production losses, and water shortage for municipal and industrial use. Many studies analyse the balance between supply and demand, but there is little experience in translating this into economic metrics that can be used in a decision-making process on investments to reduce drought risk. We will present a drought risk analysis method for the Netherlands, with a focus on the underlying economic method to quantify the welfare effects of water shortage for different water users. Both the risk-based approach as well as the economic valuation of water shortage for various water users was explored in a study for the Dutch Government. First, an historic analysis of the effects of droughts on revenues and prices in agriculture as well as on shipping and nature was carried out. Second, a drought risk analysis method was developed that combines drought hazard and drought impact analysis in a probabilistic way for various sectors. This consists of a stepwise approach, from water availability through water shortage to economic impact, for a range of drought events with a certain return period. Finally, a local case study was conducted to test the applicability of the drought risk analysis method. Through the study, experience was gained into integrating hydrological and economic analyses, which is a prerequisite for drought risk analysis. Results indicate that the risk analysis method is promising and applicable for various sectors. However, it was also found that quantification of economic impacts from droughts is time-consuming, because location- and sector-specific data is needed, which is not always readily available. Furthermore, for some
A Probabilistic Model for Hydrokinetic Turbine Collision Risks: Exploring Impacts on Fish

PubMed Central

Hammar, Linus; Eggertsen, Linda; Andersson, Sandra; Ehnberg, Jimmy; Arvidsson, Rickard; Gullström, Martin; Molander, Sverker

2015-01-01

A variety of hydrokinetic turbines are currently under development for power generation in rivers, tidal straits and ocean currents. Because some of these turbines are large, with rapidly moving rotor blades, the risk of collision with aquatic animals has been brought to attention. The behavior and fate of animals that approach such large hydrokinetic turbines have not yet been monitored at any detail. In this paper, we conduct a synthesis of the current knowledge and understanding of hydrokinetic turbine collision risks. The outcome is a generic fault tree based probabilistic model suitable for estimating population-level ecological risks. New video-based data on fish behavior in strong currents are provided and models describing fish avoidance behaviors are presented. The findings indicate low risk for small-sized fish. However, at large turbines (≥5 m), bigger fish seem to have high probability of collision, mostly because rotor detection and avoidance is difficult in low visibility. Risks can therefore be substantial for vulnerable populations of large-sized fish, which thrive in strong currents. The suggested collision risk model can be applied to different turbine designs and at a variety of locations as basis for case-specific risk assessments. The structure of the model facilitates successive model validation, refinement and application to other organism groups such as marine mammals. PMID:25730314
A probabilistic model for hydrokinetic turbine collision risks: exploring impacts on fish.

PubMed

Hammar, Linus; Eggertsen, Linda; Andersson, Sandra; Ehnberg, Jimmy; Arvidsson, Rickard; Gullström, Martin; Molander, Sverker

2015-01-01

A variety of hydrokinetic turbines are currently under development for power generation in rivers, tidal straits and ocean currents. Because some of these turbines are large, with rapidly moving rotor blades, the risk of collision with aquatic animals has been brought to attention. The behavior and fate of animals that approach such large hydrokinetic turbines have not yet been monitored at any detail. In this paper, we conduct a synthesis of the current knowledge and understanding of hydrokinetic turbine collision risks. The outcome is a generic fault tree based probabilistic model suitable for estimating population-level ecological risks. New video-based data on fish behavior in strong currents are provided and models describing fish avoidance behaviors are presented. The findings indicate low risk for small-sized fish. However, at large turbines (≥5 m), bigger fish seem to have high probability of collision, mostly because rotor detection and avoidance is difficult in low visibility. Risks can therefore be substantial for vulnerable populations of large-sized fish, which thrive in strong currents. The suggested collision risk model can be applied to different turbine designs and at a variety of locations as basis for case-specific risk assessments. The structure of the model facilitates successive model validation, refinement and application to other organism groups such as marine mammals.
Economic assessment of home-based COPD management programs.

PubMed

Liu, Sheena Xin; Lee, Michael C; Atakhorrami, Maryam; Tatousek, Jan; McCormack, Meredith; Yung, Rex; Hart, Nicholas; White, David P

2013-12-01

Home-based exacerbation management programs have been proposed as an approach to reducing the clinical and financial burden of COPD. We demonstrate a framework to evaluate such programs in order to guide program design and performance decisions towards optimizing cost and clinical outcomes. This study models the impact of hypothetical exacerbation management programs through probabilistic Markov simulations. Patients were stratified by risk using exacerbation rates from the ECLIPSE study and expert opinion. Three scenarios were modeled, using base, worst and best case parameters to suggest potential telehealth program performance. In these scenarios, acute exacerbations could be detected early, with sensitivity and specificity ranging from 60-90%. Detected acute exacerbations could be diverted to either a sub-acute pathway (12.5-50% probability), thus entirely avoiding hospitalization, or a lower cost pathway through length-of-stay reduction (14-28% reduction). For a cohort of patients without prior hospitalization, the base case telehealth scenario results in a cumulative per-patient lifetime savings of $2.9 K over ≈ 12 years. For a higher risk cohort of patients with a prior admission and 1 to 2 acute exacerbations per year, a cumulative $16K per patient was saved during the remaining ≈ 3 life-years. Acceptable prices for home-based exacerbation detection testing were highly dependent on patient risk and scenario, but ranged from $290-$1263 per month for the highest risk groups. These results suggest the economic viability of exacerbation management programs and highlight the importance of risk stratification in such programs. The presented model can further be adapted to model specific programs as trial data becomes available.
Probabilistic Tsunami Hazard Analysis

NASA Astrophysics Data System (ADS)

Thio, H. K.; Ichinose, G. A.; Somerville, P. G.; Polet, J.

2006-12-01

The recent tsunami disaster caused by the 2004 Sumatra-Andaman earthquake has focused our attention to the hazard posed by large earthquakes that occur under water, in particular subduction zone earthquakes, and the tsunamis that they generate. Even though these kinds of events are rare, the very large loss of life and material destruction caused by this earthquake warrant a significant effort towards the mitigation of the tsunami hazard. For ground motion hazard, Probabilistic Seismic Hazard Analysis (PSHA) has become a standard practice in the evaluation and mitigation of seismic hazard to populations in particular with respect to structures, infrastructure and lifelines. Its ability to condense the complexities and variability of seismic activity into a manageable set of parameters greatly facilitates the design of effective seismic resistant buildings but also the planning of infrastructure projects. Probabilistic Tsunami Hazard Analysis (PTHA) achieves the same goal for hazards posed by tsunami. There are great advantages of implementing such a method to evaluate the total risk (seismic and tsunami) to coastal communities. The method that we have developed is based on the traditional PSHA and therefore completely consistent with standard seismic practice. Because of the strong dependence of tsunami wave heights on bathymetry, we use a full waveform tsunami waveform computation in lieu of attenuation relations that are common in PSHA. By pre-computing and storing the tsunami waveforms at points along the coast generated for sets of subfaults that comprise larger earthquake faults, we can efficiently synthesize tsunami waveforms for any slip distribution on those faults by summing the individual subfault tsunami waveforms (weighted by their slip). This efficiency make it feasible to use Green's function summation in lieu of attenuation relations to provide very accurate estimates of tsunami height for probabilistic calculations, where one typically computes
A Risk-based Assessment And Management Framework For Multipollutant Air Quality

PubMed Central

Frey, H. Christopher; Hubbell, Bryan

2010-01-01

The National Research Council recommended both a risk- and performance-based multipollutant approach to air quality management. Specifically, management decisions should be based on minimizing the exposure to, and risk of adverse effects from, multiple sources of air pollution and that the success of these decisions should be measured by how well they achieved this objective. We briefly describe risk analysis and its application within the current approach to air quality management. Recommendations are made as to how current practice could evolve to support a fully risk- and performance-based multipollutant air quality management system. The ability to implement a risk assessment framework in a credible and policy-relevant manner depends on the availability of component models and data which are scientifically sound and developed with an understanding of their application in integrated assessments. The same can be said about accountability assessments used to evaluate the outcomes of decisions made using such frameworks. The existing risk analysis framework, although typically applied to individual pollutants, is conceptually well suited for analyzing multipollutant management actions. Many elements of this framework, such as emissions and air quality modeling, already exist with multipollutant characteristics. However, the framework needs to be supported with information on exposure and concentration response relationships that result from multipollutant health studies. Because the causal chain that links management actions to emission reductions, air quality improvements, exposure reductions and health outcomes is parallel between prospective risk analyses and retrospective accountability assessments, both types of assessment should be placed within a single framework with common metrics and indicators where possible. Improvements in risk reductions can be obtained by adopting a multipollutant risk analysis framework within the current air quality management
Predicting Rib Fracture Risk With Whole-Body Finite Element Models: Development and Preliminary Evaluation of a Probabilistic Analytical Framework

PubMed Central

Forman, Jason L.; Kent, Richard W.; Mroz, Krystoffer; Pipkorn, Bengt; Bostrom, Ola; Segui-Gomez, Maria

2012-01-01

This study sought to develop a strain-based probabilistic method to predict rib fracture risk with whole-body finite element (FE) models, and to describe a method to combine the results with collision exposure information to predict injury risk and potential intervention effectiveness in the field. An age-adjusted ultimate strain distribution was used to estimate local rib fracture probabilities within an FE model. These local probabilities were combined to predict injury risk and severity within the whole ribcage. The ultimate strain distribution was developed from a literature dataset of 133 tests. Frontal collision simulations were performed with the THUMS (Total HUman Model for Safety) model with four levels of delta-V and two restraints: a standard 3-point belt and a progressive 3.5–7 kN force-limited, pretensioned (FL+PT) belt. The results of three simulations (29 km/h standard, 48 km/h standard, and 48 km/h FL+PT) were compared to matched cadaver sled tests. The numbers of fractures predicted for the comparison cases were consistent with those observed experimentally. Combining these results with field exposure informantion (ΔV, NASS-CDS 1992–2002) suggests a 8.9% probability of incurring AIS3+ rib fractures for a 60 year-old restrained by a standard belt in a tow-away frontal collision with this restraint, vehicle, and occupant configuration, compared to 4.6% for the FL+PT belt. This is the first study to describe a probabilistic framework to predict rib fracture risk based on strains observed in human-body FE models. Using this analytical framework, future efforts may incorporate additional subject or collision factors for multi-variable probabilistic injury prediction. PMID:23169122
Satellite Based Probabilistic Snow Cover Extent Mapping (SCE) at Hydro-Québec

NASA Astrophysics Data System (ADS)

Teasdale, Mylène; De Sève, Danielle; Angers, Jean-François; Perreault, Luc

2016-04-01

Over 40% of Canada's water resources are in Quebec and Hydro-Quebec has developed potential to become one of the largest producers of hydroelectricity in the world, with a total installed capacity of 36,643 MW. The Hydro-Québec fleet park includes 27 large reservoirs with a combined storage capacity of 176 TWh, and 668 dams and 98 controls. Thus, over 98% of all electricity used to supply the domestic market comes from water resources and the excess output is sold on the wholesale markets. In this perspective the efficient management of water resources is needed and it is based primarily on a good river flow estimation including appropriate hydrological data. Snow on ground is one of the significant variables representing 30% to 40% of its annual energy reserve. More specifically, information on snow cover extent (SCE) and snow water equivalent (SWE) is crucial for hydrological forecasting, particularly in northern regions since the snowmelt provides the water that fills the reservoirs and is subsequently used for hydropower generation. For several years Hydro Quebec's research institute ( IREQ) developed several algorithms to map SCE and SWE. So far all the methods were deterministic. However, given the need to maximize the efficient use of all resources while ensuring reliability, the electrical systems must now be managed taking into account all risks. Since snow cover estimation is based on limited spatial information, it is important to quantify and handle its uncertainty in the hydrological forecasting system. This paper presents the first results of a probabilistic algorithm for mapping SCE by combining Bayesian mixture of probability distributions and multiple logistic regression models applied to passive microwave data. This approach allows assigning for each grid point, probabilities to the set of the mutually exclusive discrete outcomes: "snow" and "no snow". Its performance was evaluated using the Brier score since it is particularly appropriate to
Probabilistic seismic vulnerability and risk assessment of stone masonry structures

NASA Astrophysics Data System (ADS)

Abo El Ezz, Ahmad

Earthquakes represent major natural hazards that regularly impact the built environment in seismic prone areas worldwide and cause considerable social and economic losses. The high losses incurred following the past destructive earthquakes promoted the need for assessment of the seismic vulnerability and risk of the existing buildings. Many historic buildings in the old urban centers in Eastern Canada such as Old Quebec City are built of stone masonry and represent un-measurable architectural and cultural heritage. These buildings were built to resist gravity loads only and generally offer poor resistance to lateral seismic loads. Seismic vulnerability assessment of stone masonry buildings is therefore the first necessary step in developing seismic retrofitting and pre-disaster mitigation plans. The objective of this study is to develop a set of probability-based analytical tools for efficient seismic vulnerability and uncertainty analysis of stone masonry buildings. A simplified probabilistic analytical methodology for vulnerability modelling of stone masonry building with systematic treatment of uncertainties throughout the modelling process is developed in the first part of this study. Building capacity curves are developed using a simplified mechanical model. A displacement based procedure is used to develop damage state fragility functions in terms of spectral displacement response based on drift thresholds of stone masonry walls. A simplified probabilistic seismic demand analysis is proposed to capture the combined uncertainty in capacity and demand on fragility functions. In the second part, a robust analytical procedure for the development of seismic hazard compatible fragility and vulnerability functions is proposed. The results are given by sets of seismic hazard compatible vulnerability functions in terms of structure-independent intensity measure (e.g. spectral acceleration) that can be used for seismic risk analysis. The procedure is very efficient for
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.
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
Assessing Probabilistic Risk Assessment Approaches for Insect Biological Control Introductions.

PubMed

Kaufman, Leyla V; Wright, Mark G

2017-07-07

The introduction of biological control agents to new environments requires host specificity tests to estimate potential non-target impacts of a prospective agent. Currently, the approach is conservative, and is based on physiological host ranges determined under captive rearing conditions, without consideration for ecological factors that may influence realized host range. We use historical data and current field data from introduced parasitoids that attack an endemic Lepidoptera species in Hawaii to validate a probabilistic risk assessment (PRA) procedure for non-target impacts. We use data on known host range and habitat use in the place of origin of the parasitoids to determine whether contemporary levels of non-target parasitism could have been predicted using PRA. Our results show that reasonable predictions of potential non-target impacts may be made if comprehensive data are available from places of origin of biological control agents, but scant data produce poor predictions. Using apparent mortality data rather than marginal attack rate estimates in PRA resulted in over-estimates of predicted non-target impact. Incorporating ecological data into PRA models improved the predictive power of the risk assessments.
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...
Regional crop yield forecasting: a probabilistic approach

NASA Astrophysics Data System (ADS)

de Wit, A.; van Diepen, K.; Boogaard, H.

2009-04-01

Information on the outlook on yield and production of crops over large regions is essential for government services dealing with import and export of food crops, for agencies with a role in food relief, for international organizations with a mandate in monitoring the world food production and trade, and for commodity traders. Process-based mechanistic crop models are an important tool for providing such information, because they can integrate the effect of crop management, weather and soil on crop growth. When properly integrated in a yield forecasting system, the aggregated model output can be used to predict crop yield and production at regional, national and continental scales. Nevertheless, given the scales at which these models operate, the results are subject to large uncertainties due to poorly known weather conditions and crop management. Current yield forecasting systems are generally deterministic in nature and provide no information about the uncertainty bounds on their output. To improve on this situation we present an ensemble-based approach where uncertainty bounds can be derived from the dispersion of results in the ensemble. The probabilistic information provided by this ensemble-based system can be used to quantify uncertainties (risk) on regional crop yield forecasts and can therefore be an important support to quantitative risk analysis in a decision making process.
Probabilistic graphs as a conceptual and computational tool in hydrology and water management

NASA Astrophysics Data System (ADS)

Schoups, Gerrit

2014-05-01

Originally developed in the fields of machine learning and artificial intelligence, probabilistic graphs constitute a general framework for modeling complex systems in the presence of uncertainty. The framework consists of three components: 1. Representation of the model as a graph (or network), with nodes depicting random variables in the model (e.g. parameters, states, etc), which are joined together by factors. Factors are local probabilistic or deterministic relations between subsets of variables, which, when multiplied together, yield the joint distribution over all variables. 2. Consistent use of probability theory for quantifying uncertainty, relying on basic rules of probability for assimilating data into the model and expressing unknown variables as a function of observations (via the posterior distribution). 3. Efficient, distributed approximation of the posterior distribution using general-purpose algorithms that exploit model structure encoded in the graph. These attributes make probabilistic graphs potentially useful as a conceptual and computational tool in hydrology and water management (and beyond). Conceptually, they can provide a common framework for existing and new probabilistic modeling approaches (e.g. by drawing inspiration from other fields of application), while computationally they can make probabilistic inference feasible in larger hydrological models. The presentation explores, via examples, some of these benefits.
Efficient probabilistic inference in generic neural networks trained with non-probabilistic feedback.

PubMed

Orhan, A Emin; Ma, Wei Ji

2017-07-26

Animals perform near-optimal probabilistic inference in a wide range of psychophysical tasks. Probabilistic inference requires trial-to-trial representation of the uncertainties associated with task variables and subsequent use of this representation. Previous work has implemented such computations using neural networks with hand-crafted and task-dependent operations. We show that generic neural networks trained with a simple error-based learning rule perform near-optimal probabilistic inference in nine common psychophysical tasks. In a probabilistic categorization task, error-based learning in a generic network simultaneously explains a monkey's learning curve and the evolution of qualitative aspects of its choice behavior. In all tasks, the number of neurons required for a given level of performance grows sublinearly with the input population size, a substantial improvement on previous implementations of probabilistic inference. The trained networks develop a novel sparsity-based probabilistic population code. Our results suggest that probabilistic inference emerges naturally in generic neural networks trained with error-based learning rules.Behavioural tasks often require probability distributions to be inferred about task specific variables. Here, the authors demonstrate that generic neural networks can be trained using a simple error-based learning rule to perform such probabilistic computations efficiently without any need for task specific operations.
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.
Probabilistic risk assessment of exposure to leucomalachite green residues from fish products.

PubMed

Chu, Yung-Lin; Chimeddulam, Dalaijamts; Sheen, Lee-Yan; Wu, Kuen-Yuh

2013-12-01

To assess the potential risk of human exposure to carcinogenic leucomalachite green (LMG) due to fish consumption, the probabilistic risk assessment was conducted for adolescent, adult and senior adult consumers in Taiwan. The residues of LMG with the mean concentration of 13.378±20.56 μg kg(-1) (BFDA, 2009) in fish was converted into dose, considering fish intake reported for three consumer groups by NAHSIT (1993-1996) and body weight of an average individual of the group. The lifetime average and high 95th percentile dietary intakes of LMG from fish consumption for Taiwanese consumers were estimated at up to 0.0135 and 0.0451 μg kg-bw(-1) day(-1), respectively. Human equivalent dose (HED) of 2.875 mg kg-bw(-1) day(-1) obtained from a lower-bound benchmark dose (BMDL10) in mice by interspecies extrapolation was linearly extrapolated to oral cancer slope factor (CSF) of 0.035 (mgkg-bw(-1)day(-1))(-1) for humans. Although, the assumptions and methods are different, the results of lifetime cancer risk varying from 3×10(-7) to 1.6×10(-6) were comparable to those of margin of exposures (MOEs) varying from 410,000 to 4,800,000. In conclusions, Taiwanese fish consumers with the 95th percentile LADD of LMG have greater risk of liver cancer and need to an action of risk management in Taiwan. Copyright © 2013 Elsevier Ltd. All rights reserved.

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.
Probabilistic Risk Assessment (PRA): A Practical and Cost Effective Approach

NASA Technical Reports Server (NTRS)

Lee, Lydia L.; Ingegneri, Antonino J.; Djam, Melody

2006-01-01

The Lunar Reconnaissance Orbiter (LRO) is the first mission of the Robotic Lunar Exploration Program (RLEP), a space exploration venture to the Moon, Mars and beyond. The LRO mission includes spacecraft developed by NASA Goddard Space Flight Center (GSFC) and seven instruments built by GSFC, Russia, and contractors across the nation. LRO is defined as a measurement mission, not a science mission. It emphasizes the overall objectives of obtaining data to facilitate returning mankind safely to the Moon in preparation for an eventual manned mission to Mars. As the first mission in response to the President's commitment of the journey of exploring the solar system and beyond: returning to the Moon in the next decade, then venturing further into the solar system, ultimately sending humans to Mars and beyond, LRO has high-visibility to the public but limited resources and a tight schedule. This paper demonstrates how NASA's Lunar Reconnaissance Orbiter Mission project office incorporated reliability analyses in assessing risks and performing design tradeoffs to ensure mission success. Risk assessment is performed using NASA Procedural Requirements (NPR) 8705.5 - Probabilistic Risk Assessment (PRA) Procedures for NASA Programs and Projects to formulate probabilistic risk assessment (PRA). As required, a limited scope PRA is being performed for the LRO project. The PRA is used to optimize the mission design within mandated budget, manpower, and schedule constraints. The technique that LRO project office uses to perform PRA relies on the application of a component failure database to quantify the potential mission success risks. To ensure mission success in an efficient manner, low cost and tight schedule, the traditional reliability analyses, such as reliability predictions, Failure Modes and Effects Analysis (FMEA), and Fault Tree Analysis (FTA), are used to perform PRA for the large system of LRO with more than 14,000 piece parts and over 120 purchased or contractor
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.
Early childhood caries: risk-based disease prevention and management.

PubMed

Ng, Man Wai; Chase, Isabelle

2013-01-01

Early childhood caries (ECC), common in preschoolers, can lead to pain and infection if left untreated. Yet, ECC is largely preventable, and if it is identified early and the responsible risk factors are addressed, its progression can be halted or slowed. This article reviews the rationale for a first dental visit by age 1 year, caries risk assessment, and risk-based prevention and management of ECC and discusses strategies for providers to implement these contemporary evidence-based concepts into clinical practice. Copyright © 2013 Elsevier Inc. All rights reserved.
Managing wildfire events: risk-based decision making among a group of federal fire managers

Treesearch

Robyn S. Wilson; Patricia L. Winter; Lynn A. Maguire; Timothy Ascher

2011-01-01

Managing wildfire events to achieve multiple management objectives involves a high degree of decision complexity and uncertainty, increasing the likelihood that decisions will be informed by experience-based heuristics triggered by available cues at the time of the decision. The research reported here tests the prevalence of three risk-based biases among 206...
A Probabilistic Feature Map-Based Localization System Using a Monocular Camera.

PubMed

Kim, Hyungjin; Lee, Donghwa; Oh, Taekjun; Choi, Hyun-Taek; Myung, Hyun

2015-08-31

Image-based localization is one of the most widely researched localization techniques in the robotics and computer vision communities. As enormous image data sets are provided through the Internet, many studies on estimating a location with a pre-built image-based 3D map have been conducted. Most research groups use numerous image data sets that contain sufficient features. In contrast, this paper focuses on image-based localization in the case of insufficient images and features. A more accurate localization method is proposed based on a probabilistic map using 3D-to-2D matching correspondences between a map and a query image. The probabilistic feature map is generated in advance by probabilistic modeling of the sensor system as well as the uncertainties of camera poses. Using the conventional PnP algorithm, an initial camera pose is estimated on the probabilistic feature map. The proposed algorithm is optimized from the initial pose by minimizing Mahalanobis distance errors between features from the query image and the map to improve accuracy. To verify that the localization accuracy is improved, the proposed algorithm is compared with the conventional algorithm in a simulation and realenvironments.
A Probabilistic Feature Map-Based Localization System Using a Monocular Camera

PubMed Central

Kim, Hyungjin; Lee, Donghwa; Oh, Taekjun; Choi, Hyun-Taek; Myung, Hyun

2015-01-01

Image-based localization is one of the most widely researched localization techniques in the robotics and computer vision communities. As enormous image data sets are provided through the Internet, many studies on estimating a location with a pre-built image-based 3D map have been conducted. Most research groups use numerous image data sets that contain sufficient features. In contrast, this paper focuses on image-based localization in the case of insufficient images and features. A more accurate localization method is proposed based on a probabilistic map using 3D-to-2D matching correspondences between a map and a query image. The probabilistic feature map is generated in advance by probabilistic modeling of the sensor system as well as the uncertainties of camera poses. Using the conventional PnP algorithm, an initial camera pose is estimated on the probabilistic feature map. The proposed algorithm is optimized from the initial pose by minimizing Mahalanobis distance errors between features from the query image and the map to improve accuracy. To verify that the localization accuracy is improved, the proposed algorithm is compared with the conventional algorithm in a simulation and realenvironments. PMID:26404284
A probabilistic risk assessment for deployed military personnel after the implementation of the "Leishmaniasis Control Program" at Tallil Air Base, Iraq.

PubMed

Schleier, Jerome J; Davis, Ryan S; Barber, Loren M; Macedo, Paula A; Peterson, Robert K D

2009-05-01

Leishmaniasis has been of concern to the U.S. military and has re-emerged in importance because of recent deployments to the Middle East. We conducted a retrospective probabilistic risk assessment for military personnel potentially exposed to insecticides during the "Leishmaniasis Control Plan" (LCP) undertaken in 2003 at Tallil Air Base, Iraq. We estimated acute and subchronic risks from resmethrin, malathion, piperonyl butoxide (PBO), and pyrethrins applied using a truck-mounted ultra-low-volume (ULV) sprayer and lambda-cyhalothrin, cyfluthrin, bifenthrin, chlorpyrifos, and cypermethrin used for residual sprays. We used the risk quotient (RQ) method for our risk assessment (estimated environmental exposure/toxic endpoint) and set the RQ level of concern (LOC) at 1.0. Acute RQs for truck-mounted ULV and residual sprays ranged from 0.00007 to 33.3 at the 95th percentile. Acute exposure to lambda-cyhalothrin, bifenthrin, and chlorpyrifos exceeded the RQ LOC. Subchronic RQs for truck-mounted ULV and residual sprays ranged from 0.00008 to 32.8 at the 95th percentile. Subchronic exposures to lambda-cyhalothrin and chlorpyrifos exceeded the LOC. However, estimated exposures to lambda-cyhalothrin, bifenthrin, and chlorpyrifos did not exceed their respective no observed adverse effect levels.
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
Risk assessments of regional climate change over Europe: generation of probabilistic ensemble and uncertainty assessment for EURO-CODEX

NASA Astrophysics Data System (ADS)

Yuan, J.; Kopp, R. E.

2017-12-01

Quantitative risk analysis of regional climate change is crucial for risk management and impact assessment of climate change. Two major challenges to assessing the risks of climate change are: CMIP5 model runs, which drive EURO-CODEX downscaling runs, do not cover the full range of uncertainty of future projections; Climate models may underestimate the probability of tail risks (i.e. extreme events). To overcome the difficulties, this study offers a viable avenue, where a set of probabilistic climate ensemble is generated using the Surrogate/Model Mixed Ensemble (SMME) method. The probabilistic ensembles for temperature and precipitation are used to assess the range of uncertainty covered by five bias-corrected simulations from the high-resolution (0.11º) EURO-CODEX database, which are selected by the PESETA (The Projection of Economic impacts of climate change in Sectors of the European Union based on bottom-up Analysis) III project. Results show that the distribution of SMME ensemble is notably wider than both distribution of raw ensemble of GCMs and the spread of the five EURO-CORDEX in RCP8.5. Tail risks are well presented by the SMME ensemble. Both SMME ensemble and EURO-CORDEX projections are aggregated to administrative level, and are integrated into impact functions of PESETA III to assess climate risks in Europe. To further evaluate the uncertainties introduced by the downscaling process, we compare the 5 runs from EURO-CORDEX with runs from the corresponding GCMs. Time series of regional mean, spatial patterns, and climate indices are examined for the future climate (2080-2099) deviating from the present climate (1981-2010). The downscaling processes do not appear to be trend-preserving, e.g. the increase in regional mean temperature from EURO-CORDEX is slower than that from the corresponding GCM. The spatial pattern comparison reveals that the differences between each pair of GCM and EURO-CORDEX are small in winter. In summer, the temperatures of EURO
Probabilistic Human Health Risk Assessment of Chemical Mixtures: Hydro-Toxicological Interactions and Controlling Factors

NASA Astrophysics Data System (ADS)

Henri, C.; Fernandez-Garcia, D.; de Barros, F.

2014-12-01

Improper disposals of hazardous wastes in most industrial countries give rise to severe groundwater contamination problems that can lead to adverse health effects in humans. Therefore risk assessment methods play an important role in population protection by (1) quantifying the impact on human health of an aquifer contamination and (2) aiding the decision making process of to better manage our groundwater resources. Many reactive components such as chlorinated solvent or nitrate potentially experience attenuation processes under common geochemical conditions. Based on this, monitored natural attenuation has become nowadays an attractive remediation solution. However, in some cases, intermediate degradation products can constitute noxious chemical compounds before reaching a harmless chemical form. In these cases, the joint effect of advection-dispersion transport and the species-dependent kinetic reactions and toxicity will dictate the relative importance of the degradation byproducts to the total risk. This renders the interpretation of risk a non-trivial task. In this presentation, we quantify, through a probabilistic framework, the human health risk posed by a chemical mixture in a heterogeneous aquifer. This work focuses on a Perchloroethylene contamination problem followed by the first-order production/biodegradation of its daughter species Trichloroethylene, Dichloroethylene and Vinyl Chlorine that is known to be highly toxic. Uncertainty on the hydraulic conductivity field is considered through a Monte Carlo scheme. A comparative description of human health risk metrics as a function of aquifer heterogeneity and contaminant injection mode is provided by means of a spatial characterization of the lower-order statistical moments and empirical probability density functions of both individual and total risks. Interestingly, we show that the human health risk of a chemical mixture is mainly controlled by a modified Damköhler number that express the joint effect
Risk-based requirements management framework with applications to assurance cases

NASA Astrophysics Data System (ADS)

Feng, D.; Eyster, C.

The current regulatory approach for assuring device safety primarily focuses on compliance with prescriptive safety regulations and relevant safety standards. This approach, however, does not always lead to a safe system design even though safety regulations and standards have been met. In the medical device industry, several high profile recalls involving infusion pumps have prompted the regulatory agency to reconsider how device safety should be managed, reviewed and approved. An assurance case has been cited as a promising tool to address this growing concern. Assurance cases have been used in safety-critical systems for some time. Most assurance cases, if not all, in literature today are developed in an ad hoc fashion, independent from risk management and requirement development. An assurance case is a resource-intensive endeavor that requires additional effort and documentation from equipment manufacturers. Without a well-organized requirements infrastructure in place, such “ additional effort” can be substantial, to the point where the cost of adoption outweighs the benefit of adoption. In this paper, the authors present a Risk-Based Requirements and Assurance Management (RBRAM) methodology. The RBRAM is an elaborate framework that combines Risk-Based Requirements Management (RBRM) with assurance case methods. Such an integrated framework can help manufacturers leverage an existing risk management to present a comprehensive assurance case with minimal additional effort while providing a supplementary means to reexamine the integrity of the system design in terms of the mission objective. Although the example used is from the medical industry, the authors believe that the RBRAM methodology underlines the fundamental principle of risk management, and offers a simple, yet effective framework applicable to aerospace industry, perhaps, to any industry.
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.
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.
Fault tree analysis for integrated and probabilistic risk analysis of drinking water systems.

PubMed

Lindhe, Andreas; Rosén, Lars; Norberg, Tommy; Bergstedt, Olof

2009-04-01

Drinking water systems are vulnerable and subject to a wide range of risks. To avoid sub-optimisation of risk-reduction options, risk analyses need to include the entire drinking water system, from source to tap. Such an integrated approach demands tools that are able to model interactions between different events. Fault tree analysis is a risk estimation tool with the ability to model interactions between events. Using fault tree analysis on an integrated level, a probabilistic risk analysis of a large drinking water system in Sweden was carried out. The primary aims of the study were: (1) to develop a method for integrated and probabilistic risk analysis of entire drinking water systems; and (2) to evaluate the applicability of Customer Minutes Lost (CML) as a measure of risk. The analysis included situations where no water is delivered to the consumer (quantity failure) and situations where water is delivered but does not comply with water quality standards (quality failure). Hard data as well as expert judgements were used to estimate probabilities of events and uncertainties in the estimates. The calculations were performed using Monte Carlo simulations. CML is shown to be a useful measure of risks associated with drinking water systems. The method presented provides information on risk levels, probabilities of failure, failure rates and downtimes of the system. This information is available for the entire system as well as its different sub-systems. Furthermore, the method enables comparison of the results with performance targets and acceptable levels of risk. The method thus facilitates integrated risk analysis and consequently helps decision-makers to minimise sub-optimisation of risk-reduction options.
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
Do probabilistic forecasts lead to better decisions?

NASA Astrophysics Data System (ADS)

Ramos, M. H.; van Andel, S. J.; Pappenberger, F.

2012-12-01

The last decade has seen growing research in producing probabilistic hydro-meteorological forecasts and increasing their reliability. This followed the promise that, supplied with information about uncertainty, people would take better risk-based decisions. In recent years, therefore, research and operational developments have also start putting attention to ways of communicating the probabilistic forecasts to decision makers. Communicating probabilistic forecasts includes preparing tools and products for visualization, but also requires understanding how decision makers perceive and use uncertainty information in real-time. At the EGU General Assembly 2012, we conducted a laboratory-style experiment in which several cases of flood forecasts and a choice of actions to take were presented as part of a game to participants, who acted as decision makers. Answers were collected and analyzed. In this paper, we present the results of this exercise and discuss if indeed we make better decisions on the basis of probabilistic forecasts.
Do probabilistic forecasts lead to better decisions?

NASA Astrophysics Data System (ADS)

Ramos, M. H.; van Andel, S. J.; Pappenberger, F.

2013-06-01

The last decade has seen growing research in producing probabilistic hydro-meteorological forecasts and increasing their reliability. This followed the promise that, supplied with information about uncertainty, people would take better risk-based decisions. In recent years, therefore, research and operational developments have also started focusing attention on ways of communicating the probabilistic forecasts to decision-makers. Communicating probabilistic forecasts includes preparing tools and products for visualisation, but also requires understanding how decision-makers perceive and use uncertainty information in real time. At the EGU General Assembly 2012, we conducted a laboratory-style experiment in which several cases of flood forecasts and a choice of actions to take were presented as part of a game to participants, who acted as decision-makers. Answers were collected and analysed. In this paper, we present the results of this exercise and discuss if we indeed make better decisions on the basis of probabilistic forecasts.
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.
Assessing Probabilistic Risk Assessment Approaches for Insect Biological Control Introductions

PubMed Central

Kaufman, Leyla V.; Wright, Mark G.

2017-01-01

The introduction of biological control agents to new environments requires host specificity tests to estimate potential non-target impacts of a prospective agent. Currently, the approach is conservative, and is based on physiological host ranges determined under captive rearing conditions, without consideration for ecological factors that may influence realized host range. We use historical data and current field data from introduced parasitoids that attack an endemic Lepidoptera species in Hawaii to validate a probabilistic risk assessment (PRA) procedure for non-target impacts. We use data on known host range and habitat use in the place of origin of the parasitoids to determine whether contemporary levels of non-target parasitism could have been predicted using PRA. Our results show that reasonable predictions of potential non-target impacts may be made if comprehensive data are available from places of origin of biological control agents, but scant data produce poor predictions. Using apparent mortality data rather than marginal attack rate estimates in PRA resulted in over-estimates of predicted non-target impact. Incorporating ecological data into PRA models improved the predictive power of the risk assessments. PMID:28686180

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.
Development of risk-based air quality management strategies under impacts of climate change.

PubMed

Liao, Kuo-Jen; Amar, Praveen; Tagaris, Efthimios; Russell, Armistead G

2012-05-01

Climate change is forecast to adversely affect air quality through perturbations in meteorological conditions, photochemical reactions, and precursor emissions. To protect the environment and human health from air pollution, there is an increasing recognition of the necessity of developing effective air quality management strategies under the impacts of climate change. This paper presents a framework for developing risk-based air quality management strategies that can help policy makers improve their decision-making processes in response to current and future climate change about 30-50 years from now. Development of air quality management strategies under the impacts of climate change is fundamentally a risk assessment and risk management process involving four steps: (1) assessment of the impacts of climate change and associated uncertainties; (2) determination of air quality targets; (3) selections of potential air quality management options; and (4) identification of preferred air quality management strategies that minimize control costs, maximize benefits, or limit the adverse effects of climate change on air quality when considering the scarcity of resources. The main challenge relates to the level of uncertainties associated with climate change forecasts and advancements in future control measures, since they will significantly affect the risk assessment results and development of effective air quality management plans. The concept presented in this paper can help decision makers make appropriate responses to climate change, since it provides an integrated approach for climate risk assessment and management when developing air quality management strategies. Development of climate-responsive air quality management strategies is fundamentally a risk assessment and risk management process. The risk assessment process includes quantification of climate change impacts on air quality and associated uncertainties. Risk management for air quality under the impacts of
Probabilistic fatigue life prediction of metallic and composite materials

NASA Astrophysics Data System (ADS)

Xiang, Yibing

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

PubMed Central

Hall, Jim; Borgomeo, Edoardo

2013-01-01

The concept of water security implies concern about potentially harmful states of coupled human and natural water systems. Those harmful states may be associated with water scarcity (for humans and/or the environment), floods or harmful water quality. The theories and practices of risk analysis and risk management have been developed and elaborated to deal with the uncertain occurrence of harmful events. Yet despite their widespread application in public policy, theories and practices of risk management have well-known limitations, particularly in the context of severe uncertainties and contested values. Here, we seek to explore the boundaries of applicability of risk-based principles as a means of formalizing discussion of water security. Not only do risk concepts have normative appeal, but they also provide an explicit means of addressing the variability that is intrinsic to hydrological, ecological and socio-economic systems. We illustrate the nature of these interconnections with a simulation study, which demonstrates how water resources planning could take more explicit account of epistemic uncertainties, tolerability of risk and the trade-offs in risk among different actors. PMID:24080616
Stochastic Simulation and Forecast of Hydrologic Time Series Based on Probabilistic Chaos Expansion

NASA Astrophysics Data System (ADS)

Li, Z.; Ghaith, M.

2017-12-01

Hydrological processes are characterized by many complex features, such as nonlinearity, dynamics and uncertainty. How to quantify and address such complexities and uncertainties has been a challenging task for water engineers and managers for decades. To support robust uncertainty analysis, an innovative approach for the stochastic simulation and forecast of hydrologic time series is developed is this study. Probabilistic Chaos Expansions (PCEs) are established through probabilistic collocation to tackle uncertainties associated with the parameters of traditional hydrological models. The uncertainties are quantified in model outputs as Hermite polynomials with regard to standard normal random variables. Sequentially, multivariate analysis techniques are used to analyze the complex nonlinear relationships between meteorological inputs (e.g., temperature, precipitation, evapotranspiration, etc.) and the coefficients of the Hermite polynomials. With the established relationships between model inputs and PCE coefficients, forecasts of hydrologic time series can be generated and the uncertainties in the future time series can be further tackled. The proposed approach is demonstrated using a case study in China and is compared to a traditional stochastic simulation technique, the Markov-Chain Monte-Carlo (MCMC) method. Results show that the proposed approach can serve as a reliable proxy to complicated hydrological models. It can provide probabilistic forecasting in a more computationally efficient manner, compared to the traditional MCMC method. This work provides technical support for addressing uncertainties associated with hydrological modeling and for enhancing the reliability of hydrological modeling results. Applications of the developed approach can be extended to many other complicated geophysical and environmental modeling systems to support the associated uncertainty quantification and risk analysis.
A Risk-Based Approach to Evaluating Wildlife Demographics for Management in a Changing Climate: A Case Study of the Lewis's Woodpecker

NASA Astrophysics Data System (ADS)

Towler, Erin; Saab, Victoria A.; Sojda, Richard S.; Dickinson, Katherine; Bruyère, Cindy L.; Newlon, Karen R.

2012-12-01

Given the projected threat that climate change poses to biodiversity, the need for proactive response efforts is clear. However, integrating uncertain climate change information into conservation planning is challenging, and more explicit guidance is needed. To this end, this article provides a specific example of how a risk-based approach can be used to incorporate a species' response to climate into conservation decisions. This is shown by taking advantage of species' response (i.e., impact) models that have been developed for a well-studied bird species of conservation concern. Specifically, we examine the current and potential impact of climate on nest survival of the Lewis's Woodpecker ( Melanerpes lewis) in two different habitats. To address climate uncertainty, climate scenarios are developed by manipulating historical weather observations to create ensembles (i.e., multiple sequences of daily weather) that reflect historical variability and potential climate change. These ensembles allow for a probabilistic evaluation of the risk posed to Lewis's Woodpecker nest survival and are used in two demographic analyses. First, the relative value of each habitat is compared in terms of nest survival, and second, the likelihood of exceeding a critical population threshold is examined. By embedding the analyses in a risk framework, we show how management choices can be made to be commensurate with a defined level of acceptable risk. The results can be used to inform habitat prioritization and are discussed in the context of an economic framework for evaluating trade-offs between management alternatives.
A risk-based approach to evaluating wildlife demographics for management in a changing climate: A case study of the Lewis's Woodpecker

USGS Publications Warehouse

Towler, Erin; Saab, Victoria A.; Sojda, Richard S.; Dickinson, Katherine; Bruyere, Cindy L.; Newlon, Karen R.

2012-01-01

Given the projected threat that climate change poses to biodiversity, the need for proactive response efforts is clear. However, integrating uncertain climate change information into conservation planning is challenging, and more explicit guidance is needed. To this end, this article provides a specific example of how a risk-based approach can be used to incorporate a species' response to climate into conservation decisions. This is shown by taking advantage of species' response (i.e., impact) models that have been developed for a well-studied bird species of conservation concern. Specifically, we examine the current and potential impact of climate on nest survival of the Lewis's Woodpecker (Melanerpes lewis) in two different habitats. To address climate uncertainty, climate scenarios are developed by manipulating historical weather observations to create ensembles (i.e., multiple sequences of daily weather) that reflect historical variability and potential climate change. These ensembles allow for a probabilistic evaluation of the risk posed to Lewis's Woodpecker nest survival and are used in two demographic analyses. First, the relative value of each habitat is compared in terms of nest survival, and second, the likelihood of exceeding a critical population threshold is examined. By embedding the analyses in a risk framework, we show how management choices can be made to be commensurate with a defined level of acceptable risk. The results can be used to inform habitat prioritization and are discussed in the context of an economic framework for evaluating trade-offs between management alternatives.
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.
Application of receptor-specific risk distribution in the arsenic contaminated land management.

PubMed

Chen, I-chun; Ng, Shane; Wang, Gen-shuh; Ma, Hwong-wen

2013-11-15

Concerns over health risks and financial costs have caused difficulties in the management of arsenic contaminated land in Taiwan. Inflexible risk criteria and lack of economic support often result in failure of a brownfields regeneration project. To address the issue of flexible risk criteria, this study is aimed to develop maps with receptor-specific risk distribution to facilitate scenario analysis of contaminated land management. A contaminated site risk map model (ArcGIS for risk assessment and management, abbreviated as Arc-RAM) was constructed by combining the four major steps of risk assessment with Geographic Information Systems. Sampling of contaminated media, survey of exposure attributes, and modeling of multimedia transport were integrated to produce receptor group-specific maps that depicted the probabilistic spatial distribution of risks of various receptor groups. Flexible risk management schemes can then be developed and assessed. In this study, a risk management program that took into account the ratios of various land use types at specified risk levels was explored. A case study of arsenic contaminated land of 6.387 km(2) has found that for a risk value between 1.00E-05 and 1.00E-06, the proposed flexible risk management of agricultural land achieves improved utilization of land. Using this method, the investigated case can reduce costs related to compensation for farmland totaling approximately NTD 5.94 million annually. Copyright © 2012 Elsevier B.V. All rights reserved.
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
Probabilistic Approaches for Multi-Hazard Risk Assessment of Structures and Systems

NASA Astrophysics Data System (ADS)

Kwag, Shinyoung

Performance assessment of structures, systems, and components for multi-hazard scenarios has received significant attention in recent years. However, the concept of multi-hazard analysis is quite broad in nature and the focus of existing literature varies across a wide range of problems. In some cases, such studies focus on hazards that either occur simultaneously or are closely correlated with each other. For example, seismically induced flooding or seismically induced fires. In other cases, multi-hazard studies relate to hazards that are not dependent or correlated but have strong likelihood of occurrence at different times during the lifetime of a structure. The current approaches for risk assessment need enhancement to account for multi-hazard risks. It must be able to account for uncertainty propagation in a systems-level analysis, consider correlation among events or failure modes, and allow integration of newly available information from continually evolving simulation models, experimental observations, and field measurements. This dissertation presents a detailed study that proposes enhancements by incorporating Bayesian networks and Bayesian updating within a performance-based probabilistic framework. The performance-based framework allows propagation of risk as well as uncertainties in the risk estimates within a systems analysis. Unlike conventional risk assessment techniques such as a fault-tree analysis, a Bayesian network can account for statistical dependencies and correlations among events/hazards. The proposed approach is extended to develop a risk-informed framework for quantitative validation and verification of high fidelity system-level simulation tools. Validation of such simulations can be quite formidable within the context of a multi-hazard risk assessment in nuclear power plants. The efficiency of this approach lies in identification of critical events, components, and systems that contribute to the overall risk. Validation of any event or
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.
Are engineered nano iron oxide particles safe? an environmental risk assessment by probabilistic exposure, effects and risk modeling.

PubMed

Wang, Yan; Deng, Lei; Caballero-Guzman, Alejandro; Nowack, Bernd

2016-12-01

Nano iron oxide particles are beneficial to our daily lives through their use in paints, construction materials, biomedical imaging and other industrial fields. However, little is known about the possible risks associated with the current exposure level of engineered nano iron oxides (nano-FeOX) to organisms in the environment. The goal of this study was to predict the release of nano-FeOX to the environment and assess their risks for surface waters in the EU and Switzerland. The material flows of nano-FeOX to technical compartments (waste incineration and waste water treatment plants) and to the environment were calculated with a probabilistic modeling approach. The mean value of the predicted environmental concentrations (PECs) of nano-FeOX in surface waters in the EU for a worst-case scenario (no particle sedimentation) was estimated to be 28 ng/l. Using a probabilistic species sensitivity distribution, the predicted no-effect concentration (PNEC) was determined from ecotoxicological data. The risk characterization ratio, calculated by dividing the PEC by PNEC values, was used to characterize the risks. The mean risk characterization ratio was predicted to be several orders of magnitude smaller than 1 (1.4 × 10 - 4 ). Therefore, this modeling effort indicates that only a very limited risk is posed by the current release level of nano-FeOX to organisms in surface waters. However, a better understanding of the hazards of nano-FeOX to the organisms in other ecosystems (such as sediment) needs to be assessed to determine the overall risk of these particles to the environment.
A Bayesian-based two-stage inexact optimization method for supporting stream water quality management in the Three Gorges Reservoir region.

PubMed

Hu, X H; Li, Y P; Huang, G H; Zhuang, X W; Ding, X W

2016-05-01

In this study, a Bayesian-based two-stage inexact optimization (BTIO) method is developed for supporting water quality management through coupling Bayesian analysis with interval two-stage stochastic programming (ITSP). The BTIO method is capable of addressing uncertainties caused by insufficient inputs in water quality model as well as uncertainties expressed as probabilistic distributions and interval numbers. The BTIO method is applied to a real case of water quality management for the Xiangxi River basin in the Three Gorges Reservoir region to seek optimal water quality management schemes under various uncertainties. Interval solutions for production patterns under a range of probabilistic water quality constraints have been generated. Results obtained demonstrate compromises between the system benefit and the system failure risk due to inherent uncertainties that exist in various system components. Moreover, information about pollutant emission is accomplished, which would help managers to adjust production patterns of regional industry and local policies considering interactions of water quality requirement, economic benefit, and industry structure.
Levels, sources and probabilistic health risks of polycyclic aromatic hydrocarbons in the agricultural soils from sites neighboring suburban industries in Shanghai.

PubMed

Tong, Ruipeng; Yang, Xiaoyi; Su, Hanrui; Pan, Yue; Zhang, Qiuzhuo; Wang, Juan; Long, Mingce

2018-03-01

The levels, sources and quantitative probabilistic health risks for polycyclic aromatic hydrocarbons (PAHs) in agricultural soils in the vicinity of power, steel and petrochemical plants in the suburbs of Shanghai are discussed. The total concentration of 16 PAHs in the soils ranges from 223 to 8214ng g -1 . The sources of PAHs were analyzed by both isomeric ratios and a principal component analysis-multiple linear regression method. The results indicate that PAHs mainly originated from the incomplete combustion of coal and oil. The probabilistic risk assessments for both carcinogenic and non-carcinogenic risks posed by PAHs in soils with adult farmers as concerned receptors were quantitatively calculated by Monte Carlo simulation. The estimated total carcinogenic risks (TCR) for the agricultural soils has a 45% possibility of exceeding the acceptable threshold value (10 -6 ), indicating potential adverse health effects. However, all non-carcinogenic risks are below the threshold value. Oral intake is the dominant exposure pathway, accounting for 77.7% of TCR, while inhalation intake is negligible. The three PAHs with the highest contribution for TCR are BaP (64.35%), DBA (17.56%) and InP (9.06%). Sensitivity analyses indicate that exposure frequency has the greatest impact on the total risk uncertainty, followed by the exposure dose through oral intake and exposure duration. These results indicate that it is essential to manage the health risks of PAH-contaminated agricultural soils in the vicinity of typical industries in megacities. Copyright © 2017 Elsevier B.V. All rights reserved.
Reliability and Probabilistic Risk Assessment - How They Play Together

NASA Technical Reports Server (NTRS)

Safie, Fayssal M.; Stutts, Richard G.; Zhaofeng, Huang

2015-01-01

PRA methodology is one of the probabilistic analysis methods that NASA brought from the nuclear industry to assess the risk of LOM, LOV and LOC for launch vehicles. PRA is a system scenario based risk assessment that uses a combination of fault trees, event trees, event sequence diagrams, and probability and statistical data to analyze the risk of a system, a process, or an activity. It is a process designed to answer three basic questions: What can go wrong? How likely is it? What is the severity of the degradation? Since 1986, NASA, along with industry partners, has conducted a number of PRA studies to predict the overall launch vehicles risks. Planning Research Corporation conducted the first of these studies in 1988. In 1995, Science Applications International Corporation (SAIC) conducted a comprehensive PRA study. In July 1996, NASA conducted a two-year study (October 1996 - September 1998) to develop a model that provided the overall Space Shuttle risk and estimates of risk changes due to proposed Space Shuttle upgrades. After the Columbia accident, NASA conducted a PRA on the Shuttle External Tank (ET) foam. This study was the most focused and extensive risk assessment that NASA has conducted in recent years. It used a dynamic, physics-based, integrated system analysis approach to understand the integrated system risk due to ET foam loss in flight. Most recently, a PRA for Ares I launch vehicle has been performed in support of the Constellation program. Reliability, on the other hand, addresses the loss of functions. In a broader sense, reliability engineering is a discipline that involves the application of engineering principles to the design and processing of products, both hardware and software, for meeting product reliability requirements or goals. It is a very broad design-support discipline. It has important interfaces with many other engineering disciplines. Reliability as a figure of merit (i.e. the metric) is the probability that an item will
Learning Probabilistic Logic Models from Probabilistic Examples

PubMed Central

Chen, Jianzhong; Muggleton, Stephen; Santos, José

2009-01-01

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

PubMed

Chen, Jianzhong; Muggleton, Stephen; Santos, José

2008-10-01

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

NASA Astrophysics Data System (ADS)

Port, Daniel; Boehm, Barry

2002-03-01

In 1996, USC switched its core two-semester software engineering course from a hypothetical-project, homework-and-exam course based on the Bloom taxonomy of educational objectives (knowledge, comprehension, application, analysis, synthesis, and evaluation). The revised course is a real-client team-project course based on the CRESST model of learning objectives (content understanding, problem solving, collaboration, communication, and self-regulation). We used the CRESST cognitive demands analysis to determine the necessary student skills required for software risk management and the other major project activities, and have been refining the approach over the last 5 years of experience, including revised versions for one-semester undergraduate and graduate project course at Columbia. This paper summarizes our experiences in evolving the risk management aspects of the project course. These have helped us mature more general techniques such as risk-driven specifications, domain-specific simplifier and complicator lists, and the schedule as an independent variable (SAIV) process model. The largely positive results in terms of review of pass / fail rates, client evaluations, product adoption rates, and hiring manager feedback are summarized as well.
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....

Evaluating probabilistic dengue risk forecasts from a prototype early warning system for Brazil.

PubMed

Lowe, Rachel; Coelho, Caio As; Barcellos, Christovam; Carvalho, Marilia Sá; Catão, Rafael De Castro; Coelho, Giovanini E; Ramalho, Walter Massa; Bailey, Trevor C; Stephenson, David B; Rodó, Xavier

2016-02-24

Recently, a prototype dengue early warning system was developed to produce probabilistic forecasts of dengue risk three months ahead of the 2014 World Cup in Brazil. Here, we evaluate the categorical dengue forecasts across all microregions in Brazil, using dengue cases reported in June 2014 to validate the model. We also compare the forecast model framework to a null model, based on seasonal averages of previously observed dengue incidence. When considering the ability of the two models to predict high dengue risk across Brazil, the forecast model produced more hits and fewer missed events than the null model, with a hit rate of 57% for the forecast model compared to 33% for the null model. This early warning model framework may be useful to public health services, not only ahead of mass gatherings, but also before the peak dengue season each year, to control potentially explosive dengue epidemics.
Designing and operating infrastructure for nonstationary flood risk management

NASA Astrophysics Data System (ADS)

Doss-Gollin, J.; Farnham, D. J.; Lall, U.

2017-12-01

Climate exhibits organized low-frequency and regime-like variability at multiple time scales, causing the risk associated with climate extremes such as floods and droughts to vary in time. Despite broad recognition of this nonstationarity, there has been little theoretical development of ideas for the design and operation of infrastructure considering the regime structure of such changes and their potential predictability. We use paleo streamflow reconstructions to illustrate an approach to the design and operation of infrastructure to address nonstationary flood and drought risk. Specifically, we consider the tradeoff between flood control and conservation storage, and develop design and operation principles for allocating these storage volumes considering both a m-year project planning period and a n-year historical sampling record. As n increases, the potential uncertainty in probabilistic estimates of the return periods associated with the T-year extreme event decreases. As the duration m of the future operation period decreases, the uncertainty associated with the occurrence of the T-year event also increases. Finally, given the quasi-periodic nature of the system it may be possible to offer probabilistic predictions of the conditions in the m-year future period, especially if m is small. In the context of such predictions, one can consider that a m-year prediction may have lower bias, but higher variance, than would be associated with using a stationary estimate from the preceding n years. This bias-variance trade-off, and the potential for considering risk management for multiple values of m, provides an interesting system design challenge. We use wavelet-based simulation models in a Bayesian framework to estimate these biases and uncertainty distributions and devise a risk-optimized decision rule for the allocation of flood and conservation storage. The associated theoretical development also provides a methodology for the sizing of storage for new
Web based collaborative decision making in flood risk management

NASA Astrophysics Data System (ADS)

Evers, Mariele; Almoradie, Adrian; Jonoski, Andreja

2014-05-01

Stakeholder participation in the development of flood risk management (FRM) plans is essential since stakeholders often have a better understanding or knowledge of the potentials and limitation of their local area. Moreover, a participatory approach also creates trust amongst stakeholders, leading to a successful implementation of measures. Stakeholder participation however has its challenges and potential pitfalls that could lead to its premature termination. Such challenges and pitfalls are the limitation of financial resources, stakeholders' spatial distribution and their interest to participate. Different type of participation in FRM may encounter diverse challenges. These types of participation in FRM can be classified into (1) Information and knowledge sharing (IKS), (2) Consultative participation (CP) or (3) Collaborative decision making (CDM)- the most challenging type of participation. An innovative approach to address these challenges and potential pitfalls is a web-based mobile or computer-aided environment for stakeholder participation. This enhances the remote interaction between participating entities such as stakeholders. This paper presents a developed framework and an implementation of CDM web based environment for the Alster catchment (Hamburg, Germany) and Cranbrook catchment (London, UK). The CDM framework consists of two main stages: (1) Collaborative modelling and (2) Participatory decision making. This paper also highlights the stakeholder analyses, modelling approach and application of General Public License (GPL) technologies in developing the web-based environments. Actual test and evaluation of the environments was through series of stakeholders workshops. The overall results based from stakeholders' evaluation shows that web-based environments can address the challenges and potential pitfalls in stakeholder participation and it enhances participation in flood risk management. The web-based environment was developed within the DIANE
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.
Probabilistic Modeling of Settlement Risk at Land Disposal Facilities - 12304

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

Foye, Kevin C.; Soong, Te-Yang

2012-07-01

specific example, relative density, which can be determined through field measurements, was selected as the field quality control parameter for waste placement. This technique can be extended to include a rigorous performance-based methodology using other parameters (void space criteria, debris-soil mix ratio, pre-loading, etc.). As shown in this example, each parameter range, or sets of parameter ranges can be selected such that they can result in an acceptable, long-term differential settlement according to the probabilistic model. The methodology can also be used to re-evaluate the long-term differential settlement behavior at closed land disposal facilities to identify, if any, problematic facilities so that remedial action (e.g., reinforcement of upper and intermediate waste layers) can be implemented. Considering the inherent spatial variability in waste and earth materials and the need for engineers to apply sound quantitative practices to engineering analysis, it is important to apply the available probabilistic techniques to problems of differential settlement. One such method to implement probability-based differential settlement analyses for the design of landfill final covers has been presented. The design evaluation technique presented is one tool to bridge the gap from deterministic practice to probabilistic practice. (authors)« less
A Risk Management Method for the Operation of a Supply-Chain without Storage:

NASA Astrophysics Data System (ADS)

Kobayashi, Yasuhiro; Manabe, Yuuji; Nakata, Norimasa; Kusaka, Satoshi

A business risk management method has been developed for a supply-chain without a storage function under demand uncertainty. Power supply players in the deregulated power market face the need to develop the best policies for power supply from self-production and reserved purchases to balance demand, which is predictable with error. The proposed method maximizes profit from the operation of the supply-chain under probabilistic demand uncertainty on the basis of a probabilistic programming approach. Piece-wise linear functions are employed to formulate the impact of under-booked or over-booked purchases on the supply cost, and constraints on over-demand probability are introduced to limit over-demand frequency on the basis of the demand probability distribution. The developed method has been experimentally applied to the supply policy of a power-supply-chain, the operation of which is based on a 3-stage pricing purchase contract and on 28 time zones. The characteristics of the obtained optimal supply policy are successfully captured in the numerical results, which suggest the applicability of the proposed method.
Probabilistic-numerical assessment of pyroclastic current hazard at Campi Flegrei and Naples city: Multi-VEI scenarios as a tool for "full-scale" risk management.

PubMed

Mastrolorenzo, Giuseppe; Palladino, Danilo M; Pappalardo, Lucia; Rossano, Sergio

2017-01-01

The Campi Flegrei volcanic field (Italy) poses very high risk to the highly urbanized Neapolitan area. Eruptive history was dominated by explosive activity producing pyroclastic currents (hereon PCs; acronym for Pyroclastic Currents) ranging in scale from localized base surges to regional flows. Here we apply probabilistic numerical simulation approaches to produce PC hazard maps, based on a comprehensive spectrum of flow properties and vent locations. These maps are incorporated in a Geographic Information System (GIS) and provide all probable Volcanic Explosivity Index (VEI) scenarios from different source vents in the caldera, relevant for risk management planning. For each VEI scenario, we report the conditional probability for PCs (i.e., the probability for a given area to be affected by the passage of PCs in case of a PC-forming explosive event) and related dynamic pressure. Model results indicate that PCs from VEI<4 events would be confined within the Campi Flegrei caldera, PC propagation being impeded by the northern and eastern caldera walls. Conversely, PCs from VEI 4-5 events could invade a wide area beyond the northern caldera rim, as well as part of the Naples metropolitan area to the east. A major controlling factor of PC dispersal is represented by the location of the vent area. PCs from the potentially largest eruption scenarios (analogous to the ~15 ka, VEI 6 Neapolitan Yellow Tuff or even the ~39 ka, VEI 7 Campanian Ignimbrite extreme event) would affect a large part of the Campanian Plain to the north and the city of Naples to the east. Thus, in case of renewal of eruptive activity at Campi Flegrei, up to 3 million people will be potentially exposed to volcanic hazard, pointing out the urgency of an emergency plan. Considering the present level of uncertainty in forecasting the future eruption type, size and location (essentially based on statistical analysis of previous activity), we suggest that appropriate planning measures should face at
A Probabilistic Risk Analysis (PRA) of Human Space Missions for the Advanced Integration Matrix (AIM)

NASA Technical Reports Server (NTRS)

Jones, Harry W.; Dillon-Merrill, Robin L.; Thomas, Gretchen A.

2003-01-01

The Advanced Integration Matrix (AIM) Project u7ill study and solve systems-level integration issues for exploration missions beyond Low Earth Orbit (LEO), through the design and development of a ground-based facility for developing revolutionary integrated systems for joint human-robotic missions. This paper describes a Probabilistic Risk Analysis (PRA) of human space missions that was developed to help define the direction and priorities for AIM. Risk analysis is required for all major NASA programs and has been used for shuttle, station, and Mars lander programs. It is a prescribed part of early planning and is necessary during concept definition, even before mission scenarios and system designs exist. PRA cm begin when little failure data are available, and be continually updated and refined as detail becomes available. PRA provides a basis for examining tradeoffs among safety, reliability, performance, and cost. The objective of AIM's PRA is to indicate how risk can be managed and future human space missions enabled by the AIM Project. Many critical events can cause injuries and fatalities to the crew without causing loss of vehicle or mission. Some critical systems are beyond AIM's scope, such as propulsion and guidance. Many failure-causing events can be mitigated by conducting operational tests in AIM, such as testing equipment and evaluating operational procedures, especially in the areas of communications and computers, autonomous operations, life support, thermal design, EVA and rover activities, physiological factors including habitation, medical equipment, and food, and multifunctional tools and repairable systems. AIM is well suited to test and demonstrate the habitat, life support, crew operations, and human interface. Because these account for significant crew, systems performance, and science risks, AIM will help reduce mission risk, and missions beyond LEO are far enough in the future that AIM can have significant impact.
Precursor Analysis for Flight- and Ground-Based Anomaly Risk Significance Determination

NASA Technical Reports Server (NTRS)

Groen, Frank

2010-01-01

This slide presentation reviews the precursor analysis for flight and ground based anomaly risk significance. It includes information on accident precursor analysis, real models vs. models, and probabilistic analysis.
Bayesian Monte Carlo and Maximum Likelihood Approach for Uncertainty Estimation and Risk Management: Application to Lake Oxygen Recovery Model

EPA Science Inventory

Model uncertainty estimation and risk assessment is essential to environmental management and informed decision making on pollution mitigation strategies. In this study, we apply a probabilistic methodology, which combines Bayesian Monte Carlo simulation and Maximum Likelihood e...
An obesity/cardiometabolic risk reduction disease management program: a population-based approach.

PubMed

Villagra, Victor G

2009-04-01

Obesity is a critical health concern that has captured the attention of public and private healthcare payers who are interested in controlling costs and mitigating the long-term economic consequences of the obesity epidemic. Population-based approaches to obesity management have been proposed that take advantage of a chronic care model (CCM), including patient self-care, the use of community-based resources, and the realization of care continuity through ongoing communications with patients, information technology, and public policy changes. Payer-sponsored disease management programs represent an important conduit to delivering population-based care founded on similar CCM concepts. Disease management is founded on population-based disease identification, evidence-based care protocols, and collaborative practices between clinicians. While substantial clinician training, technology infrastructure commitments, and financial support at the payer level will be needed for the success of disease management programs in obesity and cardiometabolic risk reduction, these barriers can be overcome with the proper commitment. Disease management programs represent an important tool to combat the growing societal risks of overweight and obesity.
Application of a web-based Decision Support System in risk management

NASA Astrophysics Data System (ADS)

Aye, Zar Chi; Jaboyedoff, Michel; Derron, Marc-Henri

2013-04-01

Increasingly, risk information is widely available with the help of advanced technologies such as earth observation satellites, global positioning technologies, coupled with hazard modeling and analysis, and geographical information systems (GIS). Even though it exists, no effort will be put into action if it is not properly presented to the decision makers. These information need to be communicated clearly and show its usefulness so that people can make better informed decision. Therefore, communicating available risk information has become an important challenge and decision support systems have been one of the significant approaches which can help not only in presenting risk information to the decision makers but also in making efficient decisions while reducing human resources and time needed. In this study, the conceptual framework of an internet-based decision support system is presented to highlight its importance role in risk management framework and how it can be applied in case study areas chosen. The main purpose of the proposed system is to facilitate the available risk information in risk reduction by taking into account of the changes in climate, land use and socio-economic along with the risk scenarios. It allows the users to formulate, compare and select risk reduction scenarios (mainly for floods and landslides) through an enhanced participatory platform with diverse stakeholders' involvement in the decision making process. It is based on the three-tier (client-server) architecture which integrates web-GIS plus DSS functionalities together with cost benefit analysis and other supporting tools. Embedding web-GIS provides its end users to make better planning and informed decisions referenced to a geographical location, which is the one of the essential factors in disaster risk reduction programs. Different risk reduction measures of a specific area (local scale) will be evaluated using this web-GIS tool, available risk scenarios obtained from
Probabilistic and deterministic evaluation of uncertainty in a local scale multi-risk analysis

NASA Astrophysics Data System (ADS)

Lari, S.; Frattini, P.; Crosta, G. B.

2009-04-01

We performed a probabilistic multi-risk analysis (QPRA) at the local scale for a 420 km2 area surrounding the town of Brescia (Northern Italy). We calculated the expected annual loss in terms of economical damage and life loss, for a set of risk scenarios of flood, earthquake and industrial accident with different occurrence probabilities and different intensities. The territorial unit used for the study was the census parcel, of variable area, for which a large amount of data was available. Due to the lack of information related to the evaluation of the hazards, to the value of the exposed elements (e.g., residential and industrial area, population, lifelines, sensitive elements as schools, hospitals) and to the process-specific vulnerability, and to a lack of knowledge of the processes (floods, industrial accidents, earthquakes), we assigned an uncertainty to the input variables of the analysis. For some variables an homogeneous uncertainty was assigned on the whole study area, as for instance for the number of buildings of various typologies, and for the event occurrence probability. In other cases, as for phenomena intensity (e.g.,depth of water during flood) and probability of impact, the uncertainty was defined in relation to the census parcel area. In fact assuming some variables homogeneously diffused or averaged on the census parcels, we introduce a larger error for larger parcels. We propagated the uncertainty in the analysis using three different models, describing the reliability of the output (risk) as a function of the uncertainty of the inputs (scenarios and vulnerability functions). We developed a probabilistic approach based on Monte Carlo simulation, and two deterministic models, namely First Order Second Moment (FOSM) and Point Estimate (PE). In general, similar values of expected losses are obtained with the three models. The uncertainty of the final risk value is in the three cases around the 30% of the expected value. Each of the models
Prototype development of a web-based participative decision support platform in risk management

NASA Astrophysics Data System (ADS)

Aye, Zar Chi; Olyazadeh, Roya; Jaboyedoff, Michel; Derron, Marc-Henri

2014-05-01

This paper discusses the proposed background architecture and prototype development of an internet-based decision support system (DSS) in the field of natural hazards and risk management using open-source geospatial software and web technologies. It is based on a three-tier, client-server architecture with the support of boundless (opengeo) framework and its client side SDK application environment using customized gxp components and data utility classes. The main purpose of the system is to integrate the workflow of risk management systematically with the diverse involvement of stakeholders from different organizations dealing with natural hazards and risk for evaluation of management measures through the active online participation approach. It aims to develop an adaptive user friendly, web-based environment that allows the users to set up risk management strategies based on actual context and data by integrating web-GIS and DSS functionality associated with process flow and other visualization tools. Web-GIS interface has been integrated within the DSS to deliver maps and provide certain geo-processing capabilities on the web, which can be easily accessible and shared by different organizations located in case study sites of the project. This platform could be envisaged not only as a common web-based platform for the centralized sharing of data such as hazard maps, elements at risk maps and additional information but also to ensure an integrated platform of risk management where the users could upload data, analyze risk and identify possible alternative scenarios for risk reduction especially for floods and landslides, either quantitatively or qualitatively depending on the risk information provided by the stakeholders in case study regions. The level of involvement, access to and interaction with the provided functionality of the system varies depending on the roles and responsibilities of the stakeholders, for example, only the experts (planners, geological
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.
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.
Flood Risk and Asset Management

DTIC Science & Technology

2012-09-01

use by third parties of results or methods presented in this report. The Company also stresses that various sections of this report rely on data...inundation probability  Levee contribution to risk The methods used in FRE have been applied to establish the National Flood Risk in England and...be noted that when undertaking high level probabilistic risk assessments in the UK, if a defence’s condition is unknown, grade 3 is applied with
ERMiT: Estimating Post-Fire Erosion in Probabilistic Terms

NASA Astrophysics Data System (ADS)

Pierson, F. B.; Robichaud, P. R.; Elliot, W. J.; Hall, D. E.; Moffet, C. A.

2006-12-01

Mitigating the impact of post-wildfire runoff and erosion on life, property, and natural resources have cost the United States government tens of millions of dollars over the past decade. The decision of where, when, and how to apply the most effective mitigation treatments requires land managers to assess the risk of damaging runoff and erosion events occurring after a fire. The Erosion Risk Management Tool (ERMiT) is a web-based application that estimates erosion in probabilistic terms on burned and recovering forest, range, and chaparral lands. Unlike most erosion prediction models, ERMiT does not provide `average annual erosion rates;' rather, it provides a distribution of erosion rates with the likelihood of their occurrence. ERMiT combines rain event variability with spatial and temporal variabilities of hillslope burn severity, soil properties, and ground cover to estimate Water Erosion Prediction Project (WEPP) model input parameter values. Based on 20 to 40 individual WEPP runs, ERMiT produces a distribution of rain event erosion rates with a probability of occurrence for each of five post-fire years. Over the 5 years of modeled recovery, the occurrence probability of the less erodible soil parameters is increased and the occurrence probability of the more erodible soil parameters is decreased. In addition, the occurrence probabilities and the four spatial arrangements of burn severity (arrangements of overland flow elements (OFE's)), are shifted toward lower burn severity with each year of recovery. These yearly adjustments are based on field measurements made through post-fire recovery periods. ERMiT also provides rain event erosion rate distributions for hillslopes that have been treated with seeding, straw mulch, straw wattles and contour-felled log erosion barriers. Such output can help managers make erosion mitigation treatment decisions based on the probability of high sediment yields occurring, the value of resources at risk for damage, cost, and
Probabilistic risk models for multiple disturbances: an example of forest insects and wildfires

Treesearch

Haiganoush K. Preisler; Alan A. Ager; Jane L. Hayes

2010-01-01

Building probabilistic risk models for highly random forest disturbances like wildfire and forest insect outbreaks is a challenging. Modeling the interactions among natural disturbances is even more difficult. In the case of wildfire and forest insects, we looked at the probability of a large fire given an insect outbreak and also the incidence of insect outbreaks...
Evaluating probabilistic dengue risk forecasts from a prototype early warning system for Brazil

PubMed Central

Lowe, Rachel; Coelho, Caio AS; Barcellos, Christovam; Carvalho, Marilia Sá; Catão, Rafael De Castro; Coelho, Giovanini E; Ramalho, Walter Massa; Bailey, Trevor C; Stephenson, David B; Rodó, Xavier

2016-01-01

Recently, a prototype dengue early warning system was developed to produce probabilistic forecasts of dengue risk three months ahead of the 2014 World Cup in Brazil. Here, we evaluate the categorical dengue forecasts across all microregions in Brazil, using dengue cases reported in June 2014 to validate the model. We also compare the forecast model framework to a null model, based on seasonal averages of previously observed dengue incidence. When considering the ability of the two models to predict high dengue risk across Brazil, the forecast model produced more hits and fewer missed events than the null model, with a hit rate of 57% for the forecast model compared to 33% for the null model. This early warning model framework may be useful to public health services, not only ahead of mass gatherings, but also before the peak dengue season each year, to control potentially explosive dengue epidemics. DOI: http://dx.doi.org/10.7554/eLife.11285.001 PMID:26910315

Probabilistic cost-benefit analysis of disaster risk management in a development context.

PubMed

Kull, Daniel; Mechler, Reinhard; Hochrainer-Stigler, Stefan

2013-07-01

Limited studies have shown that disaster risk management (DRM) can be cost-efficient in a development context. Cost-benefit analysis (CBA) is an evaluation tool to analyse economic efficiency. This research introduces quantitative, stochastic CBA frameworks and applies them in case studies of flood and drought risk reduction in India and Pakistan, while also incorporating projected climate change impacts. DRM interventions are shown to be economically efficient, with integrated approaches more cost-effective and robust than singular interventions. The paper highlights that CBA can be a useful tool if certain issues are considered properly, including: complexities in estimating risk; data dependency of results; negative effects of interventions; and distributional aspects. The design and process of CBA must take into account specific objectives, available information, resources, and the perceptions and needs of stakeholders as transparently as possible. Intervention design and uncertainties should be qualified through dialogue, indicating that process is as important as numerical results. © 2013 The Author(s). Journal compilation © Overseas Development Institute, 2013.
Affective and cognitive factors influencing sensitivity to probabilistic information.

PubMed

Tyszka, Tadeusz; Sawicki, Przemyslaw

2011-11-01

In study 1 different groups of female students were randomly assigned to one of four probabilistic information formats. Five different levels of probability of a genetic disease in an unborn child were presented to participants (within-subject factor). After the presentation of the probability level, participants were requested to indicate the acceptable level of pain they would tolerate to avoid the disease (in their unborn child), their subjective evaluation of the disease risk, and their subjective evaluation of being worried by this risk. The results of study 1 confirmed the hypothesis that an experience-based probability format decreases the subjective sense of worry about the disease, thus, presumably, weakening the tendency to overrate the probability of rare events. Study 2 showed that for the emotionally laden stimuli, the experience-based probability format resulted in higher sensitivity to probability variations than other formats of probabilistic information. These advantages of the experience-based probability format are interpreted in terms of two systems of information processing: the rational deliberative versus the affective experiential and the principle of stimulus-response compatibility. © 2011 Society for Risk Analysis.
Application of probabilistic risk assessment: Evaluating remedial alternatives at the Portland Harbor Superfund Site, Portland, Oregon, USA.

PubMed

Ruffle, Betsy; Henderson, James; Murphy-Hagan, Clare; Kirkwood, Gemma; Wolf, Frederick; Edwards, Deborah A

2018-01-01

A probabilistic risk assessment (PRA) was performed to evaluate the range of potential baseline and postremedy health risks to fish consumers at the Portland Harbor Superfund Site (the "Site"). The analysis focused on risks of consuming fish resident to the Site containing polychlorinated biphenyls (PCBs), given that this exposure scenario and contaminant are the primary basis for US Environmental Protection Agency's (USEPA's) selected remedy per the January 2017 Record of Decision (ROD). The PRA used probability distributions fit to the same data sets used in the deterministic baseline human health risk assessment (BHHRA) as well as recent sediment and fish tissue data to evaluate the range and likelihood of current baseline cancer risks and noncancer hazards for anglers. Areas of elevated PCBs in sediment were identified on the basis of a geospatial evaluation of the surface sediment data, and the ranges of risks and hazards associated with pre- and postremedy conditions were calculated. The analysis showed that less active remediation (targeted to areas with the highest concentrations) compared to the remedial alternative selected by USEPA in the ROD can achieve USEPA's interim risk management benchmarks (cancer risk of 10 -4 and noncancer hazard index [HI] of 10) immediately postremediation for the vast majority of subsistence anglers that consume smallmouth bass (SMB) fillet tissue. In addition, the same targeted remedy achieves USEPA's long-term benchmarks (10 -5 and HI of 1) for the majority of recreational anglers. Additional sediment remediation would result in negligible additional risk reduction due to the influence of background. The PRA approach applied here provides a simple but adaptive framework for analysis of risks and remedial options focused on variability in exposures. It can be updated and refined with new data to evaluate and reduce uncertainty, improve understanding of the Site and target populations, and foster informed remedial decision
Risk-Based Treatment Targets for Onsite Non-Potable Water Reuse

EPA Science Inventory

This presentation presents risk-based enteric pathogen log reduction targets for non-potable and potable uses of a variety of alternative source waters (i.e., municipal wastewater, locally-collected greywater, rainwater, and stormwater). A probabilistic, forward Quantitative Micr...
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.
Communicating uncertainty: managing the inherent probabilistic character of hazard estimates

NASA Astrophysics Data System (ADS)

Albarello, Dario

2013-04-01

Science is much more fixing the limits of our knowledge about possible occurrences than the identification of any "truth". This is particularly true when scientific statements concern prediction of natural phenomena largely exceeding the laboratory scale as in the case of seismogenesis. In these cases, many scenarios about future occurrences result possible (plausible) and the contribution of scientific knowledge (based on the available knowledge about underlying processes or the phenomenological studies) mainly consists in attributing to each scenario a different level of likelihood (probability). In other terms, scientific predictions in the field of geosciences (hazard assessment) are inherently probabilistic. However, despite of this, many scientist (seismologists, etc.) in communicating their position in public debates tend to stress the " truth" of their statements against the fancy character of pseudo-scientific assertions: stronger is the opposition of science and pseudo-science, more hidden becomes the probabilistic character of scientific statements. The problem arises when this kind of "probabilistic" knowledge becomes the basis of any political action (e.g., to impose expensive form of risk reducing activities): in these cases the lack of any definitive "truth" requires a direct assumption of responsibility by the relevant decider (being the single citizen or the legitimate expression of a larger community) to choose among several possibilities (however characterized by different levels of likelihood). In many cases, this can be uncomfortable and strong is the attitude to delegate to the scientific counterpart the responsibility of these decisions. This "transfer" from the genuine political field to an improper scientific context is also facilitated by the lack of a diffuse culture of "probability" outside the scientific community (and in many cases inside also). This is partially the effect of the generalized adoption (by media and scientific
Probabilistic-numerical assessment of pyroclastic current hazard at Campi Flegrei and Naples city: Multi-VEI scenarios as a tool for “full-scale” risk management

PubMed Central

Mastrolorenzo, Giuseppe; Palladino, Danilo M.; Pappalardo, Lucia; Rossano, Sergio

2017-01-01

The Campi Flegrei volcanic field (Italy) poses very high risk to the highly urbanized Neapolitan area. Eruptive history was dominated by explosive activity producing pyroclastic currents (hereon PCs; acronym for Pyroclastic Currents) ranging in scale from localized base surges to regional flows. Here we apply probabilistic numerical simulation approaches to produce PC hazard maps, based on a comprehensive spectrum of flow properties and vent locations. These maps are incorporated in a Geographic Information System (GIS) and provide all probable Volcanic Explosivity Index (VEI) scenarios from different source vents in the caldera, relevant for risk management planning. For each VEI scenario, we report the conditional probability for PCs (i.e., the probability for a given area to be affected by the passage of PCs in case of a PC-forming explosive event) and related dynamic pressure. Model results indicate that PCs from VEI<4 events would be confined within the Campi Flegrei caldera, PC propagation being impeded by the northern and eastern caldera walls. Conversely, PCs from VEI 4–5 events could invade a wide area beyond the northern caldera rim, as well as part of the Naples metropolitan area to the east. A major controlling factor of PC dispersal is represented by the location of the vent area. PCs from the potentially largest eruption scenarios (analogous to the ~15 ka, VEI 6 Neapolitan Yellow Tuff or even the ~39 ka, VEI 7 Campanian Ignimbrite extreme event) would affect a large part of the Campanian Plain to the north and the city of Naples to the east. Thus, in case of renewal of eruptive activity at Campi Flegrei, up to 3 million people will be potentially exposed to volcanic hazard, pointing out the urgency of an emergency plan. Considering the present level of uncertainty in forecasting the future eruption type, size and location (essentially based on statistical analysis of previous activity), we suggest that appropriate planning measures should face at
Derivation of Failure Rates and Probability of Failures for the International Space Station Probabilistic Risk Assessment Study

NASA Technical Reports Server (NTRS)

Vitali, Roberto; Lutomski, Michael G.

2004-01-01

National Aeronautics and Space Administration s (NASA) International Space Station (ISS) Program uses Probabilistic Risk Assessment (PRA) as part of its Continuous Risk Management Process. It is used as a decision and management support tool to not only quantify risk for specific conditions, but more importantly comparing different operational and management options to determine the lowest risk option and provide rationale for management decisions. This paper presents the derivation of the probability distributions used to quantify the failure rates and the probability of failures of the basic events employed in the PRA model of the ISS. The paper will show how a Bayesian approach was used with different sources of data including the actual ISS on orbit failures to enhance the confidence in results of the PRA. As time progresses and more meaningful data is gathered from on orbit failures, an increasingly accurate failure rate probability distribution for the basic events of the ISS PRA model can be obtained. The ISS PRA has been developed by mapping the ISS critical systems such as propulsion, thermal control, or power generation into event sequences diagrams and fault trees. The lowest level of indenture of the fault trees was the orbital replacement units (ORU). The ORU level was chosen consistently with the level of statistically meaningful data that could be obtained from the aerospace industry and from the experts in the field. For example, data was gathered for the solenoid valves present in the propulsion system of the ISS. However valves themselves are composed of parts and the individual failure of these parts was not accounted for in the PRA model. In other words the failure of a spring within a valve was considered a failure of the valve itself.
Review of ecological-based risk management approaches used at five Army Superfund sites.

PubMed

Poucher, Sherri L; Tracey, Gregory A; Johnson, Mark S; Haines, Laurie B

2012-04-01

Factors used in environmental remedial decision making concerning ecological risk are not well understood or necessarily consistent. Recent Records of Decision (RODs) for Army CERCLA sites were reviewed to select case studies where remedial management occurred in response to ecological risks. Thirty-four Army RODs were evaluated representing decisions promulgated between 1996 and 2004. Five were selected based on assessments that remedial actions were clearly linked to concern for ecological receptors. The Ecological Risk Assessment (ERA) approach and the subsequent risk management process were reviewed for each site. The case studies demonstrated that the ERA findings, as well as critical management decisions regarding interpretation of identified ecological risks, were determinants of remedial action objectives. Decisions regarding the selection of remedial alternatives were based on a set of criteria prescribed by Superfund requirements and guidance. Remedial alternative evaluations require protection of human health and the environment, but protective conditions were determined using different methods at each site. Examining the remedial management process for the 5 case study sites revealed that uncertainty in the risk assessment and decisions regarding appropriate spatial scales for both risk assessment and remediation were important factors influencing remedial action decisions. The case reviews also revealed that levels of documentation were variable from site to site. In the future, more detailed documentation of decision criteria and the development of criteria that consider the resilience of the site will result in more technically defensible ecological risk management. Copyright © 2011 SETAC.
Evidence-based disease management: its role in cardiovascular risk reduction.

PubMed

Fanning, Etta L

2004-01-01

Cardiovascular disease remains the most pressing healthcare problem in the United States. Traditional risk factors--hypertension, obesity, and diabetes-are still unresolved issues; and new risk factors--pre-diabetes, insulin resistance, and pediatric and adolescent diabetes-have emerged. There is an urgent need to identify the risk factors for cardiovascular disease, and address risk reduction with disease management and treatment for each factor, based on qualitative and quantitative approaches for developing the evidence base for public health action. The objectives of this paper are to review (i) the burden of cardiovascular illness-morbidity, mortality, and cost; (ii) risk factors and the emerging epidemic of adolescent obesity; (iii) the challenges of attaining target endpoints; and (iv) the attributes of a successful programmatic healthcare initiative for potential impact on cardiovascular care and, eventually, public health.
Nine steps to risk-informed wellhead protection and management: Methods and application to the Burgberg Catchment

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

ERIC Educational Resources Information Center

Shah, Akhtar H.

2014-01-01

Many projects fail despite the use of evidence-based project management practices such as Performance Measurement Baseline (PMB), Earned Value Management (EVM) and Risk Management (RM). Although previous researchers have found that integrated project management techniques could be more valuable than the same techniques used by themselves, these…
Evidence-based risk communication: a systematic review.

PubMed

Zipkin, Daniella A; Umscheid, Craig A; Keating, Nancy L; Allen, Elizabeth; Aung, KoKo; Beyth, Rebecca; Kaatz, Scott; Mann, Devin M; Sussman, Jeremy B; Korenstein, Deborah; Schardt, Connie; Nagi, Avishek; Sloane, Richard; Feldstein, David A

2014-08-19

Effective communication of risks and benefits to patients is critical for shared decision making. To review the comparative effectiveness of methods of communicating probabilistic information to patients that maximize their cognitive and behavioral outcomes. PubMed (1966 to March 2014) and CINAHL, EMBASE, and the Cochrane Central Register of Controlled Trials (1966 to December 2011) using several keywords and structured terms. Prospective or cross-sectional studies that recruited patients or healthy volunteers and compared any method of communicating probabilistic information with another method. Two independent reviewers extracted study characteristics and assessed risk of bias. Eighty-four articles, representing 91 unique studies, evaluated various methods of numerical and visual risk display across several risk scenarios and with diverse outcome measures. Studies showed that visual aids (icon arrays and bar graphs) improved patients' understanding and satisfaction. Presentations including absolute risk reductions were better than those including relative risk reductions for maximizing accuracy and seemed less likely than presentations with relative risk reductions to influence decisions to accept therapy. The presentation of numbers needed to treat reduced understanding. Comparative effects of presentations of frequencies (such as 1 in 5) versus event rates (percentages, such as 20%) were inconclusive. Most studies were small and highly variable in terms of setting, context, and methods of administering interventions. Visual aids and absolute risk formats can improve patients' understanding of probabilistic information, whereas numbers needed to treat can lessen their understanding. Due to study heterogeneity, the superiority of any single method for conveying probabilistic information is not established, but there are several good options to help clinicians communicate with patients. None.
Dynamic Positioning System (DPS) Risk Analysis Using Probabilistic Risk Assessment (PRA)

NASA Technical Reports Server (NTRS)

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

2017-01-01

The National Aeronautics and Space Administration (NASA) Safety & Mission Assurance (S&MA) directorate at the Johnson Space Center (JSC) has applied its knowledge and experience with Probabilistic Risk Assessment (PRA) to projects in industries ranging from spacecraft to nuclear power plants. PRA is a comprehensive and structured process for analyzing risk in complex engineered systems and/or processes. The PRA process enables the user to identify potential risk contributors such as, hardware and software failure, human error, and external events. Recent developments in the oil and gas industry have presented opportunities for NASA to lend their PRA expertise to both ongoing and developmental projects within the industry. This paper provides an overview of the PRA process and demonstrates how this process was applied in estimating the probability that a Mobile Offshore Drilling Unit (MODU) operating in the Gulf of Mexico and equipped with a generically configured Dynamic Positioning System (DPS) loses location and needs to initiate an emergency disconnect. The PRA described in this paper is intended to be generic such that the vessel meets the general requirements of an International Maritime Organization (IMO) Maritime Safety Committee (MSC)/Circ. 645 Class 3 dynamically positioned vessel. The results of this analysis are not intended to be applied to any specific drilling vessel, although provisions were made to allow the analysis to be configured to a specific vessel if required.
Uncertainty and probability in wildfire management decision support: An example from the United States [Chapter 4

Treesearch

Matthew Thompson; David Calkin; Joe H. Scott; Michael Hand

2017-01-01

Wildfire risk assessment is increasingly being adopted to support federal wildfire management decisions in the United States. Existing decision support systems, specifically the Wildland Fire Decision Support System (WFDSS), provide a rich set of probabilistic and riskâbased information to support the management of active wildfire incidents. WFDSS offers a wide range...
Base-Rate Neglect as a Function of Base Rates in Probabilistic Contingency Learning

ERIC Educational Resources Information Center

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

2008-01-01

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

NASA Astrophysics Data System (ADS)

Peeters, L. J.; Mallants, D.; Turnadge, C.

2017-12-01

Groundwater impact assessments are increasingly being undertaken in a probabilistic framework whereby various sources of uncertainty (model parameters, model structure, boundary conditions, and calibration data) are taken into account. This has resulted in groundwater impact metrics being presented as probability density functions and/or cumulative distribution functions, spatial maps displaying isolines of percentile values for specific metrics, etc. Groundwater management on the other hand typically uses single values (i.e., in a deterministic framework) to evaluate what decisions are required to protect groundwater resources. For instance, in New South Wales, Australia, a nominal drawdown value of two metres is specified by the NSW Aquifer Interference Policy as trigger-level threshold. In many cases, when drawdowns induced by groundwater extraction exceed two metres, "make-good" provisions are enacted (such as the surrendering of extraction licenses). The information obtained from a quantitative uncertainty analysis can be used to guide decision making in several ways. Two examples are discussed here: the first of which would not require modification of existing "deterministic" trigger or guideline values, whereas the second example assumes that the regulatory criteria are also expressed in probabilistic terms. The first example is a straightforward interpretation of calculated percentile values for specific impact metrics. The second examples goes a step further, as the previous deterministic thresholds do not currently allow for a probabilistic interpretation; e.g., there is no statement that "the probability of exceeding the threshold shall not be larger than 50%". It would indeed be sensible to have a set of thresholds with an associated acceptable probability of exceedance (or probability of not exceeding a threshold) that decreases as the impact increases. We here illustrate how both the prediction uncertainty and management rules can be expressed in a
Probabilistic Structural Analysis Program

NASA Technical Reports Server (NTRS)

Pai, Shantaram S.; Chamis, Christos C.; Murthy, Pappu L. N.; Stefko, George L.; Riha, David S.; Thacker, Ben H.; Nagpal, Vinod K.; Mital, Subodh K.

2010-01-01

NASA/NESSUS 6.2c is a general-purpose, probabilistic analysis program that computes probability of failure and probabilistic sensitivity measures of engineered systems. Because NASA/NESSUS uses highly computationally efficient and accurate analysis techniques, probabilistic solutions can be obtained even for extremely large and complex models. Once the probabilistic response is quantified, the results can be used to support risk-informed decisions regarding reliability for safety-critical and one-of-a-kind systems, as well as for maintaining a level of quality while reducing manufacturing costs for larger-quantity products. NASA/NESSUS has been successfully applied to a diverse range of problems in aerospace, gas turbine engines, biomechanics, pipelines, defense, weaponry, and infrastructure. This program combines state-of-the-art probabilistic algorithms with general-purpose structural analysis and lifting methods to compute the probabilistic response and reliability of engineered structures. Uncertainties in load, material properties, geometry, boundary conditions, and initial conditions can be simulated. The structural analysis methods include non-linear finite-element methods, heat-transfer analysis, polymer/ceramic matrix composite analysis, monolithic (conventional metallic) materials life-prediction methodologies, boundary element methods, and user-written subroutines. Several probabilistic algorithms are available such as the advanced mean value method and the adaptive importance sampling method. NASA/NESSUS 6.2c is structured in a modular format with 15 elements.
The role of risk-based prioritization in total quality management

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

Bennett, C.T.

1994-10-01

The climate in which government managers must make decisions grows more complex and uncertain. All stakeholders - the public, industry, and Congress - are demanding greater consciousness, responsibility, and accountability of programs and their budgets. Yet, managerial decisions have become multifaceted, involve greater risk, and operate over much longer time periods. Over the last four or five decades, as policy analysis and decisions became more complex, scientists from psychology, operations research, systems science, and economics have developed a more or less coherent process called decision analysis to aid program management. The process of decision analysis - a systems theoretic approachmore » - provides the backdrop for this paper. The Laboratory Integrated Prioritization System (LIPS) has been developed as a systems analytic and risk-based prioritization tool to aid the management of the Tri-Labs` (Lawrence Livermore, Los Alamos, and Sandia) operating resources. Preliminary analyses of the effects of LIPS has confirmed the practical benefits of decision and systems sciences - the systematic, quantitative reduction in uncertainty. To date, the use of LIPS - and, hence, its value - has been restricted to resource allocation within the Tri-Labs` operations budgets. This report extends the role of risk-based prioritization to the support of DOE Total Quality Management (TQM) programs. Furthermore, this paper will argue for the requirement to institutionalize an evolutionary, decision theoretic approach to the policy analysis of the Department of Energy`s Program Budget.« less
Risk-based zoning for urbanizing floodplains.

PubMed

Porse, Erik

2014-01-01

Urban floodplain development brings economic benefits and enhanced flood risks. Rapidly growing cities must often balance the economic benefits and increased risks of floodplain settlement. Planning can provide multiple flood mitigation and environmental benefits by combining traditional structural measures such as levees, increasingly popular landscape and design features (green infrastructure), and non-structural measures such as zoning. Flexibility in both structural and non-structural options, including zoning procedures, can reduce flood risks. This paper presents a linear programming formulation to assess cost-effective urban floodplain development decisions that consider benefits and costs of development along with expected flood damages. It uses a probabilistic approach to identify combinations of land-use allocations (residential and commercial development, flood channels, distributed runoff management) and zoning regulations (development zones in channel) to maximize benefits. The model is applied to a floodplain planning analysis for an urbanizing region in the Baja Sur peninsula of Mexico. The analysis demonstrates how (1) economic benefits drive floodplain development, (2) flexible zoning can improve economic returns, and (3) cities can use landscapes, enhanced by technology and design, to manage floods. The framework can incorporate additional green infrastructure benefits, and bridges typical disciplinary gaps for planning and engineering.

Modeling and Quantification of Team Performance in Human Reliability Analysis for Probabilistic Risk Assessment

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

Jeffrey C. JOe; Ronald L. Boring

Probabilistic Risk Assessment (PRA) and Human Reliability Assessment (HRA) are important technical contributors to the United States (U.S.) Nuclear Regulatory Commission’s (NRC) risk-informed and performance based approach to regulating U.S. commercial nuclear activities. Furthermore, all currently operating commercial NPPs in the U.S. are required by federal regulation to be staffed with crews of operators. Yet, aspects of team performance are underspecified in most HRA methods that are widely used in the nuclear industry. There are a variety of "emergent" team cognition and teamwork errors (e.g., communication errors) that are 1) distinct from individual human errors, and 2) important to understandmore » from a PRA perspective. The lack of robust models or quantification of team performance is an issue that affects the accuracy and validity of HRA methods and models, leading to significant uncertainty in estimating HEPs. This paper describes research that has the objective to model and quantify team dynamics and teamwork within NPP control room crews for risk informed applications, thereby improving the technical basis of HRA, which improves the risk-informed approach the NRC uses to regulate the U.S. commercial nuclear industry.« less
Managing Space Radiation Risks on Lunar and Mars Missions: Risk Assessment and Mitigation

NASA Technical Reports Server (NTRS)

Cucinotta, F. A.; George, K.; Hu, X.; Kim, M. H.; Nikjoo, H.

2006-01-01

Radiation-induced health risks are a primary concern for human exploration outside the Earth's magnetosphere, and require improved approaches to risk estimation and tools for mitigation including shielding and biological countermeasures. Solar proton events are the major concern for short-term lunar missions (<60 d), and for long-term missions (>60 d) such as Mars exploration, the exposures to the high energy and charge (HZE) ions that make-up the galactic cosmic rays are the major concern. Health risks from radiation exposure are chronic risks including carcinogenesis and degenerative tissue risks, central nervous system effects, and acute risk such as radiation sickness or early lethality. The current estimate is that a more than four-fold uncertainty exists in the projection of lifetime mortality risk from cosmic rays, which severely limits analysis of possible benefits of shielding or biological countermeasure designs. Uncertainties in risk projections are largely due to insufficient knowledge of HZE ion radiobiology, which has led NASA to develop a unique probabilistic approach to radiation protection. We review NASA's approach to radiation risk assessment including its impact on astronaut dose limits and application of the ALARA (As Low as Reasonably Achievable) principle. The recently opened NASA Space Radiation Laboratory (NSRL) provides the capability to simulate the cosmic rays in controlled ground-based experiments with biological and shielding models. We discuss how research at NSRL will lead to reductions in the uncertainties in risk projection models. In developing mission designs, the reduction of health risks and mission constraints including costs are competing concerns that need to be addressed through optimization procedures. Mitigating the risks from space radiation is a multi-factorial problem involving individual factors (age, gender, genetic makeup, and exposure history), operational factors (planetary destination, mission length, and period
Managing Space Radiation Risks On Lunar and Mars Missions: Risk Assessment and Mitigation

NASA Technical Reports Server (NTRS)

Cucinotta, F. A.; George, K.; Hu, X.; Kim, M. H.; Nikjoo, H.

2005-01-01

Radiation-induced health risks are a primary concern for human exploration outside the Earth's magnetosphere, and require improved approaches to risk estimation and tools for mitigation including shielding and biological countermeasures. Solar proton events are the major concern for short-term lunar missions (<60 d), and for long-term missions (>60 d) such as Mars exploration, the exposures to the high energy and charge (HZE) ions that make-up the galactic cosmic rays are the major concern. Health risks from radiation exposure are chronic risks including carcinogenesis and degenerative tissue risks, central nervous system effects, and acute risk such as radiation sickness or early lethality. The current estimate is that a more than four-fold uncertainty exists in the projection of lifetime mortality risk from cosmic rays, which severely limits analysis of possible benefits of shielding or biological countermeasure designs. Uncertainties in risk projections are largely due to insufficient knowledge of HZE ion radiobiology, which has led NASA to develop a unique probabilistic approach to radiation protection. We review NASA's approach to radiation risk assessment including its impact on astronaut dose limits and application of the ALARA (As Low as Reasonably Achievable) principle. The recently opened NASA Space Radiation Laboratory (NSRL) provides the capability to simulate the cosmic rays in controlled ground-based experiments with biological and shielding models. We discuss how research at NSRL will lead to reductions in the uncertainties in risk projection models. In developing mission designs, the reduction of health risks and mission constraints including costs are competing concerns that need to be addressed through optimization procedures. Mitigating the risks from space radiation is a multi-factorial problem involving individual factors (age, gender, genetic makeup, and exposure history), operational factors (planetary destination, mission length, and period
Managing Space Radiation Risks on Lunar and Mars Missions: Risk Assessment and Mitigation

NASA Technical Reports Server (NTRS)

Cucinotta, F. A.; George, K.; Hu, X.; Kim, M. H.; Nikjoo, H.; Ponomarev, A.; Ren, L.; Shavers, M. R.; Wu, H.

2005-01-01

Radiation-induced health risks are a primary concern for human exploration outside the Earth's magnetosphere, and require improved approaches to risk estimation and tools for mitigation including shielding and biological countermeasures. Solar proton events are the major concern for short-term lunar missions (<60 d), and for long-term missions (>60 d) such as Mars exploration, the exposures to the high energy and charge (HZE) ions that make-up the galactic cosmic rays are the major concern. Health risks from radiation exposure are chronic risks including carcinogenesis and degenerative tissue risks, central nervous system effects, and acute risk such as radiation sickness or early lethality. The current estimate is that a more than four-fold uncertainty exists in the projection of lifetime mortality risk from cosmic rays, which severely limits analysis of possible benefits of shielding or biological countermeasure designs. Uncertainties in risk projections are largely due to insufficient knowledge of HZE ion radiobiology, which has led NASA to develop a unique probabilistic approach to radiation protection. We review NASA's approach to radiation risk assessment including its impact on astronaut dose limits and application of the ALARA (As Low as Reasonably Achievable) principle. The recently opened NASA Space Radiation Laboratory (NSRL) provides the capability to simulate the cosmic rays in controlled ground-based experiments with biological and shielding models. We discuss how research at NSRL will lead to reductions in the uncertainties in risk projection models. In developing mission designs, the reduction of health risks and mission constraints including costs are competing concerns that need to be addressed through optimization procedures. Mitigating the risks from space radiation is a multi-factorial problem involving individual factors (age, gender, genetic makeup, and exposure history), operational factors (planetary destination, mission length, and period
Probabilistic framework for assessing the arsenic exposure risk from cooked fish consumption.

PubMed

Ling, Min-Pei; Wu, Chiu-Hua; Chen, Szu-Chieh; Chen, Wei-Yu; Chio, Chia-Pin; Cheng, Yi-Hsien; Liao, Chung-Min

2014-12-01

Geogenic arsenic (As) contamination of groundwater is a major ecological and human health problem in southwestern and northeastern coastal areas of Taiwan. Here, we present a probabilistic framework for assessing the human health risks from consuming raw and cooked fish that were cultured in groundwater As-contaminated ponds in Taiwan by linking a physiologically based pharmacokinetics model and a Weibull dose-response model. Results indicate that As levels in baked, fried, and grilled fish were higher than those of raw fish. Frying resulted in the greatest increase in As concentration, followed by grilling, with baking affecting the As concentration the least. Simulation results show that, following consumption of baked As-contaminated fish, the health risk to humans is <10(-6) excess bladder cancer risk level for lifetime exposure; as the incidence ratios of liver and lung cancers are generally acceptable at risk ranging from 10(-6) to 10(-4), the consumption of baked As-contaminated fish is unlikely to pose a significant risk to human health. However, contaminated fish cooked by frying resulted in significant health risks, showing the highest cumulative incidence ratios of liver cancer. We also show that males have higher cumulative incidence ratio of liver cancer than females. We found that although cooking resulted in an increase for As levels in As-contaminated fish, the risk to human health of consuming baked fish is nevertheless acceptable. We suggest the adoption of baking as a cooking method and warn against frying As-contaminated fish. We conclude that the concentration of contaminants after cooking should be taken into consideration when assessing the risk to human health.
Probabilistic, Seismically-Induced Landslide Hazard Mapping of Western Oregon

NASA Astrophysics Data System (ADS)

Olsen, M. J.; Sharifi Mood, M.; Gillins, D. T.; Mahalingam, R.

2015-12-01

Earthquake-induced landslides can generate significant damage within urban communities by damaging structures, obstructing lifeline connection routes and utilities, generating various environmental impacts, and possibly resulting in loss of life. Reliable hazard and risk maps are important to assist agencies in efficiently allocating and managing limited resources to prepare for such events. This research presents a new methodology in order to communicate site-specific landslide hazard assessments in a large-scale, regional map. Implementation of the proposed methodology results in seismic-induced landslide hazard maps that depict the probabilities of exceeding landslide displacement thresholds (e.g. 0.1, 0.3, 1.0 and 10 meters). These maps integrate a variety of data sources including: recent landslide inventories, LIDAR and photogrammetric topographic data, geology map, mapped NEHRP site classifications based on available shear wave velocity data in each geologic unit, and USGS probabilistic seismic hazard curves. Soil strength estimates were obtained by evaluating slopes present along landslide scarps and deposits for major geologic units. Code was then developed to integrate these layers to perform a rigid, sliding block analysis to determine the amount and associated probabilities of displacement based on each bin of peak ground acceleration in the seismic hazard curve at each pixel. The methodology was applied to western Oregon, which contains weak, weathered, and often wet soils at steep slopes. Such conditions have a high landslide hazard even without seismic events. A series of landslide hazard maps highlighting the probabilities of exceeding the aforementioned thresholds were generated for the study area. These output maps were then utilized in a performance based design framework enabling them to be analyzed in conjunction with other hazards for fully probabilistic-based hazard evaluation and risk assessment. a) School of Civil and Construction
An Integrated Web-based Decision Support System in Disaster Risk Management

NASA Astrophysics Data System (ADS)

Aye, Z. C.; Jaboyedoff, M.; Derron, M. H.

2012-04-01

Nowadays, web based decision support systems (DSS) play an essential role in disaster risk management because of their supporting abilities which help the decision makers to improve their performances and make better decisions without needing to solve complex problems while reducing human resources and time. Since the decision making process is one of the main factors which highly influence the damages and losses of society, it is extremely important to make right decisions at right time by combining available risk information with advanced web technology of Geographic Information System (GIS) and Decision Support System (DSS). This paper presents an integrated web-based decision support system (DSS) of how to use risk information in risk management efficiently and effectively while highlighting the importance of a decision support system in the field of risk reduction. Beyond the conventional systems, it provides the users to define their own strategies starting from risk identification to the risk reduction, which leads to an integrated approach in risk management. In addition, it also considers the complexity of changing environment from different perspectives and sectors with diverse stakeholders' involvement in the development process. The aim of this platform is to contribute a part towards the natural hazards and geosciences society by developing an open-source web platform where the users can analyze risk profiles and make decisions by performing cost benefit analysis, Environmental Impact Assessment (EIA) and Strategic Environmental Assessment (SEA) with the support of others tools and resources provided. There are different access rights to the system depending on the user profiles and their responsibilities. The system is still under development and the current version provides maps viewing, basic GIS functionality, assessment of important infrastructures (e.g. bridge, hospital, etc.) affected by landslides and visualization of the impact
Combining exposure and effect modeling into an integrated probabilistic environmental risk assessment for nanoparticles.

PubMed

Jacobs, Rianne; Meesters, Johannes A J; Ter Braak, Cajo J F; van de Meent, Dik; van der Voet, Hilko

2016-12-01

There is a growing need for good environmental risk assessment of engineered nanoparticles (ENPs). Environmental risk assessment of ENPs has been hampered by lack of data and knowledge about ENPs, their environmental fate, and their toxicity. This leads to uncertainty in the risk assessment. To deal with uncertainty in the risk assessment effectively, probabilistic methods are advantageous. In the present study, the authors developed a method to model both the variability and the uncertainty in environmental risk assessment of ENPs. This method is based on the concentration ratio and the ratio of the exposure concentration to the critical effect concentration, both considered to be random. In this method, variability and uncertainty are modeled separately so as to allow the user to see which part of the total variation in the concentration ratio is attributable to uncertainty and which part is attributable to variability. The authors illustrate the use of the method with a simplified aquatic risk assessment of nano-titanium dioxide. The authors' method allows a more transparent risk assessment and can also direct further environmental and toxicological research to the areas in which it is most needed. Environ Toxicol Chem 2016;35:2958-2967. © 2016 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC. © 2016 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.
Continuous Risk Management: An Overview

NASA Technical Reports Server (NTRS)

Rosenberg, Linda; Hammer, Theodore F.

1999-01-01

Software risk management is important because it helps avoid disasters, rework, and overkill, but more importantly because it stimulates win-win situations. The objectives of software risk management are to identify, address, and eliminate software risk items before they become threats to success or major sources of rework. In general, good project managers are also good managers of risk. It makes good business sense for all software development projects to incorporate risk management as part of project management. The Software Assurance Technology Center (SATC) at NASA GSFC has been tasked with the responsibility for developing and teaching a systems level course for risk management that provides information on how to implement risk management. The course was developed in conjunction with the Software Engineering Institute at Carnegie Mellon University, then tailored to the NASA systems community. This is an introductory tutorial to continuous risk management based on this course. The rational for continuous risk management and how it is incorporated into project management are discussed. The risk management structure of six functions is discussed in sufficient depth for managers to understand what is involved in risk management and how it is implemented. These functions include: (1) Identify the risks in a specific format; (2) Analyze the risk probability, impact/severity, and timeframe; (3) Plan the approach; (4) Track the risk through data compilation and analysis; (5) Control and monitor the risk; (6) Communicate and document the process and decisions.
Probabilistic Risk Assessment for Decision Making During Spacecraft Operations

NASA Technical Reports Server (NTRS)

Meshkat, Leila

2009-01-01

Decisions made during the operational phase of a space mission often have significant and immediate consequences. Without the explicit consideration of the risks involved and their representation in a solid model, it is very likely that these risks are not considered systematically in trade studies. Wrong decisions during the operational phase of a space mission can lead to immediate system failure whereas correct decisions can help recover the system even from faulty conditions. A problem of special interest is the determination of the system fault protection strategies upon the occurrence of faults within the system. Decisions regarding the fault protection strategy also heavily rely on a correct understanding of the state of the system and an integrated risk model that represents the various possible scenarios and their respective likelihoods. Probabilistic Risk Assessment (PRA) modeling is applicable to the full lifecycle of a space mission project, from concept development to preliminary design, detailed design, development and operations. The benefits and utilities of the model, however, depend on the phase of the mission for which it is used. This is because of the difference in the key strategic decisions that support each mission phase. The focus of this paper is on describing the particular methods used for PRA modeling during the operational phase of a spacecraft by gleaning insight from recently conducted case studies on two operational Mars orbiters. During operations, the key decisions relate to the commands sent to the spacecraft for any kind of diagnostics, anomaly resolution, trajectory changes, or planning. Often, faults and failures occur in the parts of the spacecraft but are contained or mitigated before they can cause serious damage. The failure behavior of the system during operations provides valuable data for updating and adjusting the related PRA models that are built primarily based on historical failure data. The PRA models, in turn
Gender, Race, and Risk: Intersectional Risk Management in the Sale of Sex Online.

PubMed

Moorman, Jessica D; Harrison, Kristen

2016-09-01

Sex worker experience of risk (e.g., physical violence or rape) is shaped by race, gender, and context. For web-based sex workers, experience of risk is comparatively minimal; what is unclear is how web-based sex workers manage risk and if online advertising plays a role in risk management. Building on intersectionality theory and research exploring risk management in sex work, we content-analyzed 600 escort advertisements from Backpage.com ( http://www.backpage.com ) to explore risk management in web-based sex work. To guide our research we asked: Do advertisements contain risk management messages? Does the use of risk management messaging differ by sex worker race or gender? Which groups have the highest overall use of risk management messages? Through a multivariate analysis of covariance (MANCOVA) we found that advertisements contained risk management messages and that uses of these phrases varied by race and gender. Blacks, women, and transgender women drove the use of risk management messages. Black and White transgender women had the highest overall use of these phrases. We conclude that risk management is an intersectional practice and that the use of risk management messages is a venue-specific manifestation of broader risk management priorities found in all venues where sex is sold.
A mediation model to explain decision making under conditions of risk among adolescents: the role of fluid intelligence and probabilistic reasoning.

PubMed

Donati, Maria Anna; Panno, Angelo; Chiesi, Francesca; Primi, Caterina

2014-01-01

This study tested the mediating role of probabilistic reasoning ability in the relationship between fluid intelligence and advantageous decision making among adolescents in explicit situations of risk--that is, in contexts in which information on the choice options (gains, losses, and probabilities) were explicitly presented at the beginning of the task. Participants were 282 adolescents attending high school (77% males, mean age = 17.3 years). We first measured fluid intelligence and probabilistic reasoning ability. Then, to measure decision making under explicit conditions of risk, participants performed the Game of Dice Task, in which they have to decide among different alternatives that are explicitly linked to a specific amount of gain or loss and have obvious winning probabilities that are stable over time. Analyses showed a significant positive indirect effect of fluid intelligence on advantageous decision making through probabilistic reasoning ability that acted as a mediator. Specifically, fluid intelligence may enhance ability to reason in probabilistic terms, which in turn increases the likelihood of advantageous choices when adolescents are confronted with an explicit decisional context. Findings show that in experimental paradigm settings, adolescents are able to make advantageous decisions using cognitive abilities when faced with decisions under explicit risky conditions. This study suggests that interventions designed to promote probabilistic reasoning, for example by incrementing the mathematical prerequisites necessary to reason in probabilistic terms, may have a positive effect on adolescents' decision-making abilities.
A Novel TRM Calculation Method by Probabilistic Concept

NASA Astrophysics Data System (ADS)

Audomvongseree, Kulyos; Yokoyama, Akihiko; Verma, Suresh Chand; Nakachi, Yoshiki

In a new competitive environment, it becomes possible for the third party to access a transmission facility. From this structure, to efficiently manage the utilization of the transmission network, a new definition about Available Transfer Capability (ATC) has been proposed. According to the North American ElectricReliability Council (NERC)’s definition, ATC depends on several parameters, i. e. Total Transfer Capability (TTC), Transmission Reliability Margin (TRM), and Capacity Benefit Margin (CBM). This paper is focused on the calculation of TRM which is one of the security margin reserved for any uncertainty of system conditions. The TRM calculation by probabilistic method is proposed in this paper. Based on the modeling of load forecast error and error in transmission line limitation, various cases of transmission transfer capability and its related probabilistic nature can be calculated. By consideration of the proposed concept of risk analysis, the appropriate required amount of TRM can be obtained. The objective of this research is to provide realistic information on the actual ability of the network which may be an alternative choice for system operators to make an appropriate decision in the competitive market. The advantages of the proposed method are illustrated by application to the IEEJ-WEST10 model system.
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.
Simulation-Based Probabilistic Tsunami Hazard Analysis: Empirical and Robust Hazard Predictions

NASA Astrophysics Data System (ADS)

De Risi, Raffaele; Goda, Katsuichiro

2017-08-01

Probabilistic tsunami hazard analysis (PTHA) is the prerequisite for rigorous risk assessment and thus for decision-making regarding risk mitigation strategies. This paper proposes a new simulation-based methodology for tsunami hazard assessment for a specific site of an engineering project along the coast, or, more broadly, for a wider tsunami-prone region. The methodology incorporates numerous uncertain parameters that are related to geophysical processes by adopting new scaling relationships for tsunamigenic seismic regions. Through the proposed methodology it is possible to obtain either a tsunami hazard curve for a single location, that is the representation of a tsunami intensity measure (such as inundation depth) versus its mean annual rate of occurrence, or tsunami hazard maps, representing the expected tsunami intensity measures within a geographical area, for a specific probability of occurrence in a given time window. In addition to the conventional tsunami hazard curve that is based on an empirical statistical representation of the simulation-based PTHA results, this study presents a robust tsunami hazard curve, which is based on a Bayesian fitting methodology. The robust approach allows a significant reduction of the number of simulations and, therefore, a reduction of the computational effort. Both methods produce a central estimate of the hazard as well as a confidence interval, facilitating the rigorous quantification of the hazard uncertainties.
Risk Based Framework for Geotechnical Asset Management

DOT National Transportation Integrated Search

2017-12-28

This report presents the outcome from a multi-year research study to incorporate a risk management framework for the Alaska Department of Transportation & Public Facilities Geotechnical Asset Management (GAM) Plan. The GAM Plan was developed by Paul ...
Probabilistic evaluation of uncertainties and risks in aerospace components

NASA Technical Reports Server (NTRS)

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

1992-01-01

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

PubMed

Thyvalikakath, Thankam P; Padman, Rema; Gupta, Sugandh

2013-01-01

Mounting evidence suggests a potential association of periodontal disease with systemic diseases such as diabetes, cardiovascular disease, cancer and stroke. The objective of this study is to develop an integrated risk assessment tool that displays a patients' risk for periodontal disease in the context of their systemic disease, social habits and oral health. Such a tool will be used by not just dental professionals but also by care providers who participate in the team-based care for chronic disease management. Displaying relationships between risk factors and its influence on the patient's general health could be a powerful educational and disease management tool for patients and clinicians. It may also improve the coordination of care provided by the provider-members of a chronic care team.
Addressing the Hard Factors for Command File Errors by Probabilistic Reasoning

NASA Technical Reports Server (NTRS)

Meshkat, Leila; Bryant, Larry

2014-01-01

Command File Errors (CFE) are managed using standard risk management approaches at the Jet Propulsion Laboratory. Over the last few years, more emphasis has been made on the collection, organization, and analysis of these errors for the purpose of reducing the CFE rates. More recently, probabilistic modeling techniques have been used for more in depth analysis of the perceived error rates of the DAWN mission and for managing the soft factors in the upcoming phases of the mission. We broadly classify the factors that can lead to CFE's as soft factors, which relate to the cognition of the operators and hard factors which relate to the Mission System which is composed of the hardware, software and procedures used for the generation, verification & validation and execution of commands. The focus of this paper is to use probabilistic models that represent multiple missions at JPL to determine the root cause and sensitivities of the various components of the mission system and develop recommendations and techniques for addressing them. The customization of these multi-mission models to a sample interplanetary spacecraft is done for this purpose.
RISK MANAGEMENT USING PROJECT RECON

DTIC Science & Technology

2016-11-28

Risk Management Using Project Recon UNCLASSIFIED: Distribution Statement A. Approved for public release; distribution is unlimited. Bonnie Leece... Project Recon Lead What is Project Recon? • A web-based GOTS tool designed to capture, manage, and link Risks, Issues, and Opportunities in a...centralized database. • Project Recon (formerly Risk Recon) is designed to be used by all Program Management Offices, Integrated Project Teams and any

[Risk management for medical devices].

PubMed

Xie, Ying-jie; Xu, Xing-gang

2007-07-01

Based on the practices of the risk management activities by Chinese medical device manufacturers and theoretical study of the latest international standard ISO 14971:2007, this article analyses the risk management in medical device manufacturing industry by introducing the status quo of applications, four requirements at operational stages, and future trends of development. Methods and suggestions are therefore given to medical device manufacturers for risk management.
Integrating statistical and process-based models to produce probabilistic landslide hazard at regional scale

NASA Astrophysics Data System (ADS)

Strauch, R. L.; Istanbulluoglu, E.

2017-12-01

We develop a landslide hazard modeling approach that integrates a data-driven statistical model and a probabilistic process-based shallow landslide model for mapping probability of landslide initiation, transport, and deposition at regional scales. The empirical model integrates the influence of seven site attribute (SA) classes: elevation, slope, curvature, aspect, land use-land cover, lithology, and topographic wetness index, on over 1,600 observed landslides using a frequency ratio (FR) approach. A susceptibility index is calculated by adding FRs for each SA on a grid-cell basis. Using landslide observations we relate susceptibility index to an empirically-derived probability of landslide impact. This probability is combined with results from a physically-based model to produce an integrated probabilistic map. Slope was key in landslide initiation while deposition was linked to lithology and elevation. Vegetation transition from forest to alpine vegetation and barren land cover with lower root cohesion leads to higher frequency of initiation. Aspect effects are likely linked to differences in root cohesion and moisture controlled by solar insulation and snow. We demonstrate the model in the North Cascades of Washington, USA and identify locations of high and low probability of landslide impacts that can be used by land managers in their design, planning, and maintenance.
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.
Chronic kidney disease risk reduction in a Hispanic population through pharmacist-based disease-state management.

PubMed

Leal, Sandra; Soto, Marisa

2008-04-01

The purpose of this study was to evaluate the ability of a pharmacist-based disease-state management service to improve the care of indigent, predominately Spanish-speaking patients with diabetes mellitus and common comorbid conditions at high risk for the development of chronic kidney disease (CKD). Patients at high risk for developing CKD who have diabetes at a community health center were placed in a pharmacist-based disease state management service for CKD risk reduction. A residency-trained, bilingual, certified diabetes educator, with a PharmD served as the patient's provider using diagnostic, educational, and therapeutic management services under a medical staff approved collaborative practice agreement. Outcomes were assessed by using national standards of care for disease control and prevention screening. The impact on CKD was shown with a mean A1C decrease of 2% and improvement in the proportion of patients at target goals for blood pressure, A1C, and cholesterol levels and receiving aspirin and angiotensin-converting enzyme inhibitor/angiotensin receptor blocker. A pharmacist-based disease-state management service for CKD risk reduction, care of diabetes, and frequently associated comorbid conditions improved compliance with national standards for diabetes care in a high-risk population.
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...
A comprehensive probabilistic analysis model of oil pipelines network based on Bayesian network

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

NASA Astrophysics Data System (ADS)

Pelorosso, Leandro; Diehl, Alexandra; Matković, Krešimir; Delrieux, Claudio; Ruiz, Juan; Gröeller, M. Eduard; Bruckner, Stefan

2016-04-01

Numerical weather forecasts are prone to uncertainty coming from inaccuracies in the initial and boundary conditions and lack of precision in numerical models. Ensemble of forecasts partially addresses these problems by considering several runs of the numerical model. Each forecast is generated with different initial and boundary conditions and different model configurations [GR05]. The ensembles can be expressed as probabilistic forecasts, which have proven to be very effective in the decision-making processes [DE06]. The ensemble of forecasts represents only some of the possible future atmospheric states, usually underestimating the degree of uncertainty in the predictions [KAL03, PH06]. Hamill and Whitaker [HW06] introduced the "Reforecast Analog Regression" (RAR) technique to overcome the limitations of ensemble forecasting. This technique produces probabilistic predictions based on the analysis of historical forecasts and observations. Visual analytics provides tools for processing, visualizing, and exploring data to get new insights and discover hidden information patterns in an interactive exchange between the user and the application [KMS08]. In this work, we introduce Albero, a visual analytics solution for probabilistic weather forecasting based on the RAR technique. Albero targets at least two different type of users: "forecasters", who are meteorologists working in operational weather forecasting and "researchers", who work in the construction of numerical prediction models. Albero is an efficient tool for analyzing precipitation forecasts, allowing forecasters to make and communicate quick decisions. Our solution facilitates the analysis of a set of probabilistic forecasts, associated statistical data, observations and uncertainty. A dashboard with small-multiples of probabilistic forecasts allows the forecasters to analyze at a glance the distribution of probabilities as a function of time, space, and magnitude. It provides the user with a more
The Climate-Agriculture-Modeling and Decision Tool (CAMDT) for Climate Risk Management in Agriculture

NASA Astrophysics Data System (ADS)

Ines, A. V. M.; Han, E.; Baethgen, W.

2017-12-01

Advances in seasonal climate forecasts (SCFs) during the past decades have brought great potential to improve agricultural climate risk managements associated with inter-annual climate variability. In spite of popular uses of crop simulation models in addressing climate risk problems, the models cannot readily take seasonal climate predictions issued in the format of tercile probabilities of most likely rainfall categories (i.e, below-, near- and above-normal). When a skillful SCF is linked with the crop simulation models, the informative climate information can be further translated into actionable agronomic terms and thus better support strategic and tactical decisions. In other words, crop modeling connected with a given SCF allows to simulate "what-if" scenarios with different crop choices or management practices and better inform the decision makers. In this paper, we present a decision support tool, called CAMDT (Climate Agriculture Modeling and Decision Tool), which seamlessly integrates probabilistic SCFs to DSSAT-CSM-Rice model to guide decision-makers in adopting appropriate crop and agricultural water management practices for given climatic conditions. The CAMDT has a functionality to disaggregate a probabilistic SCF into daily weather realizations (either a parametric or non-parametric disaggregation method) and to run DSSAT-CSM-Rice with the disaggregated weather realizations. The convenient graphical user-interface allows easy implementation of several "what-if" scenarios for non-technical users and visualize the results of the scenario runs. In addition, the CAMDT also translates crop model outputs to economic terms once the user provides expected crop price and cost. The CAMDT is a practical tool for real-world applications, specifically for agricultural climate risk management in the Bicol region, Philippines, having a great flexibility for being adapted to other crops or regions in the world. CAMDT GitHub: https://github.com/Agro-Climate/CAMDT
Risk Management.

ERIC Educational Resources Information Center

Randal, L. Nathan

This chapter of "Principles of School Business Management" presents an overview of risk management for school districts. The chapter first discusses four fundamental elements of risk management: (1) identifying and measuring risks; (2) reducing or eliminating risks; (3) transferring unassumable risks; and (4) assuming remaining risks.…
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.
Weighing costs and losses: A decision making game using probabilistic forecasts

NASA Astrophysics Data System (ADS)

Werner, Micha; Ramos, Maria-Helena; Wetterhall, Frederik; Cranston, Michael; van Andel, Schalk-Jan; Pappenberger, Florian; Verkade, Jan

2017-04-01

Probabilistic forecasts are increasingly recognised as an effective and reliable tool to communicate uncertainties. The economic value of probabilistic forecasts has been demonstrated by several authors, showing the benefit to using probabilistic forecasts over deterministic forecasts in several sectors, including flood and drought warning, hydropower, and agriculture. Probabilistic forecasting is also central to the emerging concept of risk-based decision making, and underlies emerging paradigms such as impact-based forecasting. Although the economic value of probabilistic forecasts is easily demonstrated in academic works, its evaluation in practice is more complex. The practical use of probabilistic forecasts requires decision makers to weigh the cost of an appropriate response to a probabilistic warning against the projected loss that would occur if the event forecast becomes reality. In this paper, we present the results of a simple game that aims to explore how decision makers are influenced by the costs required for taking a response and the potential losses they face in case the forecast flood event occurs. Participants play the role of one of three possible different shop owners. Each type of shop has losses of quite different magnitude, should a flood event occur. The shop owners are presented with several forecasts, each with a probability of a flood event occurring, which would inundate their shop and lead to those losses. In response, they have to decide if they want to do nothing, raise temporary defences, or relocate their inventory. Each action comes at a cost; and the different shop owners therefore have quite different cost/loss ratios. The game was played on four occasions. Players were attendees of the ensemble hydro-meteorological forecasting session of the 2016 EGU Assembly, professionals participating at two other conferences related to hydrometeorology, and a group of students. All audiences were familiar with the principles of forecasting
Risk management.

PubMed

Chambers, David W

2010-01-01

Every plan contains risk. To proceed without planning some means of managing that risk is to court failure. The basic logic of risk is explained. It consists in identifying a threshold where some corrective action is necessary, the probability of exceeding that threshold, and the attendant cost should the undesired outcome occur. This is the probable cost of failure. Various risk categories in dentistry are identified, including lack of liquidity; poor quality; equipment or procedure failures; employee slips; competitive environments; new regulations; unreliable suppliers, partners, and patients; and threats to one's reputation. It is prudent to make investments in risk management to the extent that the cost of managing the risk is less than the probable loss due to risk failure and when risk management strategies can be matched to type of risk. Four risk management strategies are discussed: insurance, reducing the probability of failure, reducing the costs of failure, and learning. A risk management accounting of the financial meltdown of October 2008 is provided.
A Copula-Based Conditional Probabilistic Forecast Model for Wind Power Ramps

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

Hodge, Brian S; Krishnan, Venkat K; Zhang, Jie

Efficient management of wind ramping characteristics can significantly reduce wind integration costs for balancing authorities. By considering the stochastic dependence of wind power ramp (WPR) features, this paper develops a conditional probabilistic wind power ramp forecast (cp-WPRF) model based on Copula theory. The WPRs dataset is constructed by extracting ramps from a large dataset of historical wind power. Each WPR feature (e.g., rate, magnitude, duration, and start-time) is separately forecasted by considering the coupling effects among different ramp features. To accurately model the marginal distributions with a copula, a Gaussian mixture model (GMM) is adopted to characterize the WPR uncertaintymore » and features. The Canonical Maximum Likelihood (CML) method is used to estimate parameters of the multivariable copula. The optimal copula model is chosen based on the Bayesian information criterion (BIC) from each copula family. Finally, the best conditions based cp-WPRF model is determined by predictive interval (PI) based evaluation metrics. Numerical simulations on publicly available wind power data show that the developed copula-based cp-WPRF model can predict WPRs with a high level of reliability and sharpness.« less
Nature-based flood risk management -challenges in implementing catchment-wide management concepts

NASA Astrophysics Data System (ADS)

Thaler, Thomas; Fuchs, Sven

2017-04-01

Traditionally, flood risk management focused on coping with the flow at a given point by, for example, building dikes or straightening the watercourse. Increasingly the emphasis has shifted to measures within the flood plain to delay the flow through storage. As such the fluent boundaries imposed by the behaviour of the catchment at a certain point are relocated upstream by the human intervention. Therefore, the implementation of flood storages and the use of natural retention areas are promoted as mitigation measures to support sustainable flood risk management. They aimed at reducing the effluent boundaries on the floodplain by increasing the effluent boundaries upstream. However, beyond the simple change of practices it is indeed often a question of land use change which is at stake in water management. As such, it poses the questions on how to govern both water and land to satisfy the different stakeholders. Nature-based strategies often follow with voluntary agreements, which are promoted as an alternative instrument to the traditional top-down command and control regulation. Voluntary agreements aim at bringing more efficiency, participatory and transparency in solving problems between different social groups. In natural hazard risk management voluntary agreements are now receiving high interests to complement the existing policy instruments in order to achieve the objectives the EU WFD and of the Floods Directive. This paper investigates the use of voluntary agreements as an alternative instrument to the traditional top-down command and control regulation in the implementation of flood storages in Austria. The paper provides a framework of analysis to reveal barriers and opportunities associated with such approach. The paper concludes that institution and power are the central elements to tackle for allowing the success of voluntary agreement.
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.
Risk Management

DTIC Science & Technology

2011-06-02

actively attack the risks, they will actively attack you.” -Tom Gib Why do Risk Management? 8 “The first step in the risk management process is to...opportunities to manage and improve our chances of success. - Roger Vanscoy “If you do not actively attack the risks, they will actively attack ...our risks provides opportunities to manage and improve our chances of success. - Roger Vanscoy “If you do not actively attack the risks, they will
Problem-Based Teaching in International Management: A Political/Economic Risk Assessment Exercise

ERIC Educational Resources Information Center

Daly, Paula S.; White, Marion M.; Zisk, Daniel S.; Cavazos, David E.

2013-01-01

This article draws from the current literature to examine problem-based learning (PBL) as a management education tool, and provides an example of how to incorporate PBL into an undergraduate international management course. Also included are an explanation of, and specific guidelines for, a PBL exercise focused on the analysis of "country risk"…
Use of raster-based data layers to model spatial variation of seismotectonic data in probabilistic seismic hazard assessment

NASA Astrophysics Data System (ADS)

Zolfaghari, Mohammad R.

2009-07-01

Recent achievements in computer and information technology have provided the necessary tools to extend the application of probabilistic seismic hazard mapping from its traditional engineering use to many other applications. Examples for such applications are risk mitigation, disaster management, post disaster recovery planning and catastrophe loss estimation and risk management. Due to the lack of proper knowledge with regard to factors controlling seismic hazards, there are always uncertainties associated with all steps involved in developing and using seismic hazard models. While some of these uncertainties can be controlled by more accurate and reliable input data, the majority of the data and assumptions used in seismic hazard studies remain with high uncertainties that contribute to the uncertainty of the final results. In this paper a new methodology for the assessment of seismic hazard is described. The proposed approach provides practical facility for better capture of spatial variations of seismological and tectonic characteristics, which allows better treatment of their uncertainties. In the proposed approach, GIS raster-based data models are used in order to model geographical features in a cell-based system. The cell-based source model proposed in this paper provides a framework for implementing many geographically referenced seismotectonic factors into seismic hazard modelling. Examples for such components are seismic source boundaries, rupture geometry, seismic activity rate, focal depth and the choice of attenuation functions. The proposed methodology provides improvements in several aspects of the standard analytical tools currently being used for assessment and mapping of regional seismic hazard. The proposed methodology makes the best use of the recent advancements in computer technology in both software and hardware. The proposed approach is well structured to be implemented using conventional GIS tools.
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.
PubMed related articles: a probabilistic topic-based model for content similarity

PubMed Central

Lin, Jimmy; Wilbur, W John

2007-01-01

Background We present a probabilistic topic-based model for content similarity called pmra that underlies the related article search feature in PubMed. Whether or not a document is about a particular topic is computed from term frequencies, modeled as Poisson distributions. Unlike previous probabilistic retrieval models, we do not attempt to estimate relevance–but rather our focus is "relatedness", the probability that a user would want to examine a particular document given known interest in another. We also describe a novel technique for estimating parameters that does not require human relevance judgments; instead, the process is based on the existence of MeSH ® in MEDLINE ®. Results The pmra retrieval model was compared against bm25, a competitive probabilistic model that shares theoretical similarities. Experiments using the test collection from the TREC 2005 genomics track shows a small but statistically significant improvement of pmra over bm25 in terms of precision. Conclusion Our experiments suggest that the pmra model provides an effective ranking algorithm for related article search. PMID:17971238

Application of a generic bow-tie based risk analysis framework on risk management of sea ports and offshore terminals.

PubMed

Mokhtari, Kambiz; Ren, Jun; Roberts, Charles; Wang, Jin

2011-08-30

Ports and offshore terminals are critical infrastructure resources and play key roles in the transportation of goods and people. With more than 80 percent of international trade by volume being carried out by sea, ports and offshore terminals are vital for seaborne trade and international commerce. Furthermore in today's uncertain and complex environment there is a need to analyse the participated risk factors in order to prioritise protective measures in these critically logistics infrastructures. As a result of this study is carried out to support the risk assessment phase of the proposed Risk Management (RM) framework used for the purpose of sea ports and offshore terminals operations and management (PTOM). This has been fulfilled by integration of a generic bow-tie based risk analysis framework into the risk assessment phase as a backbone of the phase. For this reason Fault Tree Analysis (FTA) and Event Tree Analysis (ETA) are used to analyse the risk factors associated within the PTOM. This process will eventually help the port professionals and port risk managers to investigate the identified risk factors more in detail. In order to deal with vagueness of the data Fuzzy Set Theory (FST) and possibility approach are used to overcome the disadvantages of the conventional probability based approaches. Copyright © 2011 Elsevier B.V. All rights reserved.
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
[Reliability theory based on quality risk network analysis for Chinese medicine injection].

PubMed

Li, Zheng; Kang, Li-Yuan; Fan, Xiao-Hui

2014-08-01

A new risk analysis method based upon reliability theory was introduced in this paper for the quality risk management of Chinese medicine injection manufacturing plants. The risk events including both cause and effect ones were derived in the framework as nodes with a Bayesian network analysis approach. It thus transforms the risk analysis results from failure mode and effect analysis (FMEA) into a Bayesian network platform. With its structure and parameters determined, the network can be used to evaluate the system reliability quantitatively with probabilistic analytical appraoches. Using network analysis tools such as GeNie and AgenaRisk, we are able to find the nodes that are most critical to influence the system reliability. The importance of each node to the system can be quantitatively evaluated by calculating the effect of the node on the overall risk, and minimization plan can be determined accordingly to reduce their influences and improve the system reliability. Using the Shengmai injection manufacturing plant of SZYY Ltd as a user case, we analyzed the quality risk with both static FMEA analysis and dynamic Bayesian Network analysis. The potential risk factors for the quality of Shengmai injection manufacturing were identified with the network analysis platform. Quality assurance actions were further defined to reduce the risk and improve the product quality.
A Framework for Integrating Knowledge Management with Risk Management for Information Technology Projects (RiskManiT)

ERIC Educational Resources Information Center

Karadsheh, Louay A.

2010-01-01

This research focused on the challenges experienced when executing risk management activities for information technology projects. The lack of adequate knowledge management support of risk management activities has caused many project failures in the past. The research objective was to propose a conceptual framework of the Knowledge-Based Risk…
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.
Risk Assessment and Hierarchical Risk Management of Enterprises in Chemical Industrial Parks Based on Catastrophe Theory

PubMed Central

Chen, Yu; Song, Guobao; Yang, Fenglin; Zhang, Shushen; Zhang, Yun; Liu, Zhenyu

2012-01-01

According to risk systems theory and the characteristics of the chemical industry, an index system was established for risk assessment of enterprises in chemical industrial parks (CIPs) based on the inherent risk of the source, effectiveness of the prevention and control mechanism, and vulnerability of the receptor. A comprehensive risk assessment method based on catastrophe theory was then proposed and used to analyze the risk levels of ten major chemical enterprises in the Songmu Island CIP, China. According to the principle of equal distribution function, the chemical enterprise risk level was divided into the following five levels: 1.0 (very safe), 0.8 (safe), 0.6 (generally recognized as safe, GRAS), 0.4 (unsafe), 0.2 (very unsafe). The results revealed five enterprises (50%) with an unsafe risk level, and another five enterprises (50%) at the generally recognized as safe risk level. This method solves the multi-objective evaluation and decision-making problem. Additionally, this method involves simple calculations and provides an effective technique for risk assessment and hierarchical risk management of enterprises in CIPs. PMID:23208298
A red-flag-based approach to risk management of EHR-related safety concerns.

PubMed

Sittig, Dean F; Singh, Hardeep

2013-01-01

Although electronic health records (EHRs) have a significant potential to improve patient safety, EHR-related safety concerns have begun to emerge. Based on 369 responses to a survey sent to the memberships of the American Society for Healthcare Risk Management and the American Health Lawyers Association and supplemented by our previous work in EHR-related patient safety, we identified the following common EHR-related safety concerns: (1) incorrect patient identification; (2) extended EHR unavailability (either planned or unplanned); (3) failure to heed a computer-generated warning or alert; (4) system-to-system interface errors; (5) failure to identify, find, or use the most recent patient data; (6) misunderstandings about time; (7) incorrect item selected from a list of items; and (8) open or incomplete orders. In this article, we present a "red-flag"-based approach that can be used by risk managers to identify potential EHR safety concerns in their institutions. An organization that routinely conducts EHR-related surveillance activities, such as the ones proposed here, can significantly reduce risks associated with EHR implementation and use. © 2013 American Society for Healthcare Risk Management of the American Hospital Association.
Promoting evidence-based practice: managing change in the assessment of pressure damage risk.

PubMed

Gerrish, K; Clayton, J; Nolan, M; Parker, K; Morgan, L

1999-11-01

This study set out to facilitate the development of evidence-based practice in the assessment of pressure damage risk to patients within a large acute hospital. The importance of nursing practice being based on the best available evidence is emphasized in recent health policy. Meeting this objective is not easy as both individual and organizational factors create barriers to the implementation of research findings and the achievement of change. The study was based on an action research model. It comprised three stages: a review of the research evidence; a survey of qualified nurses' knowledge of risk assessment of pressure damage and an audit of record keeping, and a multifaceted approach to achieving change in which researchers, managers, practitioners and clinical nurse specialists worked together collaboratively. The findings from the survey and audit indicated a shortfall in nurses' knowledge of risk assessment of pressure damage and in their record keeping. The researchers, with the help of the clinical nurse specialist, built upon these findings by assisting practitioners and managers to take ownership of the need to base practice on the appropriate evidence. Achieving evidence-based practice is a complex undertaking that requires the development of an evaluative culture and a commitment by practitioners and managers to change practice. Researchers can play a valuable role in facilitating this process.
Leaching characteristics, ecotoxicity, and risk assessment based management of mine wastes

NASA Astrophysics Data System (ADS)

Kim, J.; Ju, W. J.; Jho, E. H.; Nam, K.; Hong, J. K.

2016-12-01

Mine wastes generated during mining activities in metal mines generally contain high concentrations of metals that may impose toxic effects to surrounding environment. Thus, it is necessary to properly assess the mining-impacted landscapes for management. The study investigated leaching characteristics, potential environmental effects, and human health risk of mine wastes from three different metal mines in South Korea (molybdenum mine, lead-zinc mine, and magnetite mine). The heavy metal concentrations in the leachates obtained by using the Korean Standard Test Method for Solid Wastes (STM), Toxicity Characteristics Leaching Procedure (TCLP), and Synthetic Precipitation Leaching Procedure (SPLP) met the Korea Waste Control Act and the USEPA region 3 regulatory levels accordingly, even though the mine wastes contained high concentrations of metals. Assuming that the leachates may get into nearby water sources, the leachate toxicity was tested using Daphnia Magna. The toxic unit (TU) values after 24 h and 48 h exposure of all the mine wastes tested met the Korea Allowable Effluent Water Quality Standards (TU<1). The column leaching test showed that the lead-zinc mine waste may have long-term toxic effects (TU>1 for the eluent at L/S of 30) implying that the long-term effect of mine wastes left in mining areas need to be assessed. Considering reuse of mine wastes as a way of managing mine wastes, the human health risk assessment of reusing the lead-zinc mine waste in industrial areas was carried out using the bioavailable fraction of the heavy metals contained in the mine wastes, which was determined by using the Solubility/Bioavailability Research Consortium method. There may be potential carcinogenic risk (9.7E-05) and non-carcinogenic risk (HI, Hazard Index of 1.0E+00) as CR≧1.0E-05 has carcinogenic risk and HI≧1.0E+00 has non-carcinogenic risk. Overall, this study shows that not only the concentration-based assessment but ecological toxic effect and human
Assessment of possible airborne impact from nuclear risk sites - Part II: probabilistic analysis of atmospheric transport patterns in Euro-Arctic region

NASA Astrophysics Data System (ADS)

Mahura, A. G.; Baklanov, A. A.

2003-10-01

The probabilistic analysis of atmospheric transport patterns from most important nuclear risk sites in the Euro-Arctic region is performed employing the methodology developed within the "Arctic Risk" Project of the NARP Programme (Baklanov and Mahura, 2003). The risk sites are the nuclear power plants in the Northwest Russia, Finland, Sweden, Lithuania, United Kingdom, and Germany as well as the Novaya Zemlya test site of Russia. The geographical regions of interest are the Northern and Central European countries and Northwest Russia. In this study, the employed research tools are the trajectory model to calculate a multiyear dataset of forward trajectories that originated over the risk site locations, and a set of statistical methods (including exploratory, cluster, and probability fields analyses) for analysis of trajectory modelling results. The probabilistic analyses of trajectory modelling results for eleven sites are presented as a set of various indicators of the risk sites possible impact on geographical regions and countries of interest. The nuclear risk site possible impact (on a particular geographical region, territory, country, site, etc.) due to atmospheric transport from the site after hypothetical accidental release of radioactivity can be properly estimated based on a combined interpretation of the indicators (simple characteristics, atmospheric transport pathways, airflow and fast transport probability fields, maximum reaching distance and maximum possible impact zone, typical transport time and precipitation factor fields) for different time periods (annual, seasonal, and monthly) for any selected site (both separately for each site or grouped for several sites) in the Euro-Arctic region. Such estimation could be the useful input information for the decision-making process, risk assessment, and planning of emergency response systems for sites of nuclear, chemical, and biological danger.
Developing a synthetic national population to investigate the impact of different cardiovascular disease risk management strategies: A derivation and validation study

PubMed Central

Jackson, Rod

2017-01-01

Background Many national cardiovascular disease (CVD) risk factor management guidelines now recommend that drug treatment decisions should be informed primarily by patients’ multi-variable predicted risk of CVD, rather than on the basis of single risk factor thresholds. To investigate the potential impact of treatment guidelines based on CVD risk thresholds at a national level requires individual level data representing the multi-variable CVD risk factor profiles for a country’s total adult population. As these data are seldom, if ever, available, we aimed to create a synthetic population, representing the joint CVD risk factor distributions of the adult New Zealand population. Methods and results A synthetic population of 2,451,278 individuals, representing the actual age, gender, ethnicity and social deprivation composition of people aged 30–84 years who completed the 2013 New Zealand census was generated using Monte Carlo sampling. Each ‘synthetic’ person was then probabilistically assigned values of the remaining cardiovascular disease (CVD) risk factors required for predicting their CVD risk, based on data from the national census national hospitalisation and drug dispensing databases and a large regional cohort study, using Monte Carlo sampling and multiple imputation. Where possible, the synthetic population CVD risk distributions for each non-demographic risk factor were validated against independent New Zealand data sources. Conclusions We were able to develop a synthetic national population with realistic multi-variable CVD risk characteristics. The construction of this population is the first step in the development of a micro-simulation model intended to investigate the likely impact of a range of national CVD risk management strategies that will inform CVD risk management guideline updates in New Zealand and elsewhere. PMID:28384217
Developing a synthetic national population to investigate the impact of different cardiovascular disease risk management strategies: A derivation and validation study.

PubMed

Knight, Josh; Wells, Susan; Marshall, Roger; Exeter, Daniel; Jackson, Rod

2017-01-01

Many national cardiovascular disease (CVD) risk factor management guidelines now recommend that drug treatment decisions should be informed primarily by patients' multi-variable predicted risk of CVD, rather than on the basis of single risk factor thresholds. To investigate the potential impact of treatment guidelines based on CVD risk thresholds at a national level requires individual level data representing the multi-variable CVD risk factor profiles for a country's total adult population. As these data are seldom, if ever, available, we aimed to create a synthetic population, representing the joint CVD risk factor distributions of the adult New Zealand population. A synthetic population of 2,451,278 individuals, representing the actual age, gender, ethnicity and social deprivation composition of people aged 30-84 years who completed the 2013 New Zealand census was generated using Monte Carlo sampling. Each 'synthetic' person was then probabilistically assigned values of the remaining cardiovascular disease (CVD) risk factors required for predicting their CVD risk, based on data from the national census national hospitalisation and drug dispensing databases and a large regional cohort study, using Monte Carlo sampling and multiple imputation. Where possible, the synthetic population CVD risk distributions for each non-demographic risk factor were validated against independent New Zealand data sources. We were able to develop a synthetic national population with realistic multi-variable CVD risk characteristics. The construction of this population is the first step in the development of a micro-simulation model intended to investigate the likely impact of a range of national CVD risk management strategies that will inform CVD risk management guideline updates in New Zealand and elsewhere.
Enhancing Cost Realism through Risk-Driven Contracting: Designing Incentive Fees Based on Probabilistic Cost Estimates

DTIC Science & Technology

2012-04-01

Comparison of Management Practices in the Army, Navy, and Air Force 142Defense ARJ, April 2012, Vol. 19 No. 2 : 133–160 It appears the pendulum may be...the cost risk for requiring greater innovation. However, this natural flattening trend also leads to a potential drawback of the risk-driven
Probabilistic mapping of urban flood risk: Application to extreme events in Surat, India

NASA Astrophysics Data System (ADS)

Ramirez, Jorge; Rajasekar, Umamaheshwaran; Coulthard, Tom; Keiler, Margreth

2016-04-01

Surat, India is a coastal city that lies on the banks of the river Tapti and is located downstream from the Ukai dam. Given Surat's geographic location, the population of five million people are repeatedly exposed to flooding caused by high tide combined with large emergency dam releases into the Tapti river. In 2006 such a flood event occurred when intense rainfall in the Tapti catchment caused a dam release near 25,000 m3 s-1 and flooded 90% of the city. A first step towards strengthening resilience in Surat requires a robust method for mapping potential flood risk that considers the uncertainty in future dam releases. Here, in this study we develop many combinations of dam release magnitude and duration for the Ukai dam. Afterwards we use these dam releases to drive a two dimensional flood model (CAESAR-Lisflood) of Surat that also considers tidal effects. Our flood model of Surat utilizes fine spatial resolution (30m) topography produced from an extensive differential global positioning system survey and measurements of river cross-sections. Within the city we have modelled scenarios that include extreme conditions with near maximum dam release levels (e.g. 1:250 year flood) and high tides. Results from all scenarios have been summarized into probabilistic flood risk maps for Surat. These maps are currently being integrated within the city disaster management plan for taking both mitigation and adaptation measures for different scenarios of flooding.
Prioritization Risk Integration Simulation Model (PRISM) For Environmental Remediation and Waste Management - 12097

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

Pentz, David L.; Stoll, Ralph H.; Greeves, John T.

2012-07-01

The PRISM (Prioritization Risk Integration Simulation Model), a computer model was developed to support the Department of Energy's Office of Environmental Management (DOE-EM) in its mission to clean up the environmental legacy from the Nation's nuclear weapons materials production complex. PRISM provides a comprehensive, fully integrated planning tool that can tie together DOE-EM's projects. It is designed to help DOE managers develop sound, risk-informed business practices and defend program decisions. It provides a better ability to understand and manage programmatic risks. The underlying concept for PRISM is that DOE-EM 'owns' a portfolio of environmental legacy obligations (ELOs), and that itsmore » mission is to transform the ELOs from their current conditions to acceptable conditions, in the most effective way possible. There are many types of ELOs - - contaminated soils and groundwater plumes, disused facilities awaiting D and D, and various types of wastes waiting for processing or disposal. For a given suite of planned activities, PRISM simulates the outcomes as they play out over time, allowing for all key identified uncertainties and risk factors. Each contaminated building, land area and waste stream is tracked from cradle to grave, and all of the linkages affecting different waste streams are captured. The progression of the activities is fully dynamic, reflecting DOE-EM's prioritization approaches, precedence requirements, available funding, and the consequences of risks and uncertainties. The top level of PRISM is the end-user interface that allows rapid evaluation of alternative scenarios and viewing the results in a variety of useful ways. PRISM is a fully probabilistic model, allowing the user to specify uncertainties in input data (such as the magnitude of an existing groundwater plume, or the total cost to complete a planned activity) as well as specific risk events that might occur. PRISM is based on the GoldSim software that is widely used
Segmentation of risk structures for otologic surgery using the Probabilistic Active Shape Model (PASM)

NASA Astrophysics Data System (ADS)

Becker, Meike; Kirschner, Matthias; Sakas, Georgios

2014-03-01

Our research project investigates a multi-port approach for minimally-invasive otologic surgery. For planning such a surgery, an accurate segmentation of the risk structures is crucial. However, the segmentation of these risk structures is a challenging task: The anatomical structures are very small and some have a complex shape, low contrast and vary both in shape and appearance. Therefore, prior knowledge is needed which is why we apply model-based approaches. In the present work, we use the Probabilistic Active Shape Model (PASM), which is a more flexible and specific variant of the Active Shape Model (ASM), to segment the following risk structures: cochlea, semicircular canals, facial nerve, chorda tympani, ossicles, internal auditory canal, external auditory canal and internal carotid artery. For the evaluation we trained and tested the algorithm on 42 computed tomography data sets using leave-one-out tests. Visual assessment of the results shows in general a good agreement of manual and algorithmic segmentations. Further, we achieve a good Average Symmetric Surface Distance while the maximum error is comparatively large due to low contrast at start and end points. Last, we compare the PASM to the standard ASM and show that the PASM leads to a higher accuracy.
Probabilistic Physics-Based Risk Tools Used to Analyze the International Space Station Electrical Power System Output

NASA Technical Reports Server (NTRS)

Patel, Bhogila M.; Hoge, Peter A.; Nagpal, Vinod K.; Hojnicki, Jeffrey S.; Rusick, Jeffrey J.

2004-01-01

This paper describes the methods employed to apply probabilistic modeling techniques to the International Space Station (ISS) power system. These techniques were used to quantify the probabilistic variation in the power output, also called the response variable, due to variations (uncertainties) associated with knowledge of the influencing factors called the random variables. These uncertainties can be due to unknown environmental conditions, variation in the performance of electrical power system components or sensor tolerances. Uncertainties in these variables, cause corresponding variations in the power output, but the magnitude of that effect varies with the ISS operating conditions, e.g. whether or not the solar panels are actively tracking the sun. Therefore, it is important to quantify the influence of these uncertainties on the power output for optimizing the power available for experiments.
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
SHM-Based Probabilistic Fatigue Life Prediction for Bridges Based on FE Model Updating

PubMed Central

Lee, Young-Joo; Cho, Soojin

2016-01-01

Fatigue life prediction for a bridge should be based on the current condition of the bridge, and various sources of uncertainty, such as material properties, anticipated vehicle loads and environmental conditions, make the prediction very challenging. This paper presents a new approach for probabilistic fatigue life prediction for bridges using finite element (FE) model updating based on structural health monitoring (SHM) data. Recently, various types of SHM systems have been used to monitor and evaluate the long-term structural performance of bridges. For example, SHM data can be used to estimate the degradation of an in-service bridge, which makes it possible to update the initial FE model. The proposed method consists of three steps: (1) identifying the modal properties of a bridge, such as mode shapes and natural frequencies, based on the ambient vibration under passing vehicles; (2) updating the structural parameters of an initial FE model using the identified modal properties; and (3) predicting the probabilistic fatigue life using the updated FE model. The proposed method is demonstrated by application to a numerical model of a bridge, and the impact of FE model updating on the bridge fatigue life is discussed. PMID:26950125
Probabilistic Sizing and Verification of Space Ceramic Structures

NASA Astrophysics Data System (ADS)

Denaux, David; Ballhause, Dirk; Logut, Daniel; Lucarelli, Stefano; Coe, Graham; Laine, Benoit

2012-07-01

Sizing of ceramic parts is best optimised using a probabilistic approach which takes into account the preexisting flaw distribution in the ceramic part to compute a probability of failure of the part depending on the applied load, instead of a maximum allowable load as for a metallic part. This requires extensive knowledge of the material itself but also an accurate control of the manufacturing process. In the end, risk reduction approaches such as proof testing may be used to lower the final probability of failure of the part. Sizing and verification of ceramic space structures have been performed by Astrium for more than 15 years, both with Zerodur and SiC: Silex telescope structure, Seviri primary mirror, Herschel telescope, Formosat-2 instrument, and other ceramic structures flying today. Throughout this period of time, Astrium has investigated and developed experimental ceramic analysis tools based on the Weibull probabilistic approach. In the scope of the ESA/ESTEC study: “Mechanical Design and Verification Methodologies for Ceramic Structures”, which is to be concluded in the beginning of 2012, existing theories, technical state-of-the-art from international experts, and Astrium experience with probabilistic analysis tools have been synthesized into a comprehensive sizing and verification method for ceramics. Both classical deterministic and more optimised probabilistic methods are available, depending on the criticality of the item and on optimisation needs. The methodology, based on proven theory, has been successfully applied to demonstration cases and has shown its practical feasibility.

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.
Project Risk Management

NASA Technical Reports Server (NTRS)

Jr., R. F. Miles

1995-01-01

Project risk management is primarily concerned with performance, reliability, cost, and schedule. Environmental risk management is primarily concerned with human health and ecological hazards and likelihoods. This paper discusses project risk management and compares it to environmental risk management, both with respect to goals and implementation. The approach of the Jet Propulsion Laboratory to risk management is presented as an example of a project risk management approach that is an extension to NASA NHB 7120.5: Management of Major System Programs and Projects.
Geothermal probabilistic cost study

NASA Technical Reports Server (NTRS)

Orren, L. H.; Ziman, G. M.; Jones, S. C.; Lee, T. K.; Noll, R.; Wilde, L.; Sadanand, V.

1981-01-01

A tool is presented to quantify the risks of geothermal projects, the Geothermal Probabilistic Cost Model (GPCM). The GPCM model was used to evaluate a geothermal reservoir for a binary-cycle electric plant at Heber, California. Three institutional aspects of the geothermal risk which can shift the risk among different agents was analyzed. The leasing of geothermal land, contracting between the producer and the user of the geothermal heat, and insurance against faulty performance were examined.
Scalable DB+IR Technology: Processing Probabilistic Datalog with HySpirit.

PubMed

Frommholz, Ingo; Roelleke, Thomas

2016-01-01

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

NASA Technical Reports Server (NTRS)

Duncan, Gary

2014-01-01

Although there are ongoing efforts to extend the ISS life cycle through 2028, the International Space Station (ISS) end-of-life (EOL) cycle is currently scheduled for 2020. The EOL for the ISS will require de-orbiting the ISS. This will be the largest manmade object ever to be de-orbited, therefore safely de-orbiting 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, debris mapping 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.
Research on Risk Manage of Power Construction Project Based on Bayesian Network

NASA Astrophysics Data System (ADS)

Jia, Zhengyuan; Fan, Zhou; Li, Yong

With China's changing economic structure and increasingly fierce competition in the market, the uncertainty and risk factors in the projects of electric power construction are increasingly complex, the projects will face huge risks or even fail if we don't consider or ignore these risk factors. Therefore, risk management in the projects of electric power construction plays an important role. The paper emphatically elaborated the influence of cost risk in electric power projects through study overall risk management and the behavior of individual in risk management, and introduced the Bayesian network to the project risk management. The paper obtained the order of key factors according to both scene analysis and causal analysis for effective risk management.
Calysto: Risk Management for Commercial Manned Spaceflight

NASA Technical Reports Server (NTRS)

Dillaman, Gary

2012-01-01

The Calysto: Risk Management for Commercial Manned Spaceflight study analyzes risk management in large enterprises and how to effectively communicate risks across organizations. The Calysto Risk Management tool developed by NASA's Kennedy Space Center's SharePoint team is used and referenced throughout the study. Calysto is a web-base tool built on Microsoft's SharePoint platform. The risk management process at NASA is examined and incorporated in the study. Using risk management standards from industry and specific organizations at the Kennedy Space Center, three methods of communicating and elevating risk are examined. Each method describes details of the effectiveness and plausibility of using the method in the Calysto Risk Management Tool. At the end of the study suggestions are made for future renditions of Calysto.
A ligand predication tool based on modeling and reasoning with imprecise probabilistic knowledge.

PubMed

Liu, Weiru; Yue, Anbu; Timson, David J

2010-04-01

Ligand prediction has been driven by a fundamental desire to understand more about how biomolecules recognize their ligands and by the commercial imperative to develop new drugs. Most of the current available software systems are very complex and time-consuming to use. Therefore, developing simple and efficient tools to perform initial screening of interesting compounds is an appealing idea. In this paper, we introduce our tool for very rapid screening for likely ligands (either substrates or inhibitors) based on reasoning with imprecise probabilistic knowledge elicited from past experiments. Probabilistic knowledge is input to the system via a user-friendly interface showing a base compound structure. A prediction of whether a particular compound is a substrate is queried against the acquired probabilistic knowledge base and a probability is returned as an indication of the prediction. This tool will be particularly useful in situations where a number of similar compounds have been screened experimentally, but information is not available for all possible members of that group of compounds. We use two case studies to demonstrate how to use the tool. 2009 Elsevier Ireland Ltd. All rights reserved.
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.
A Probabilistic Collocation Based Iterative Kalman Filter for Landfill Data Assimilation

NASA Astrophysics Data System (ADS)

Qiang, Z.; Zeng, L.; Wu, L.

2016-12-01

Due to the strong spatial heterogeneity of landfill, uncertainty is ubiquitous in gas transport process in landfill. To accurately characterize the landfill properties, the ensemble Kalman filter (EnKF) has been employed to assimilate the measurements, e.g., the gas pressure. As a Monte Carlo (MC) based method, the EnKF usually requires a large ensemble size, which poses a high computational cost for large scale problems. In this work, we propose a probabilistic collocation based iterative Kalman filter (PCIKF) to estimate permeability in a liquid-gas coupling model. This method employs polynomial chaos expansion (PCE) to represent and propagate the uncertainties of model parameters and states, and an iterative form of Kalman filter to assimilate the current gas pressure data. To further reduce the computation cost, the functional ANOVA (analysis of variance) decomposition is conducted, and only the first order ANOVA components are remained for PCE. Illustrated with numerical case studies, this proposed method shows significant superiority in computation efficiency compared with the traditional MC based iterative EnKF. The developed method has promising potential in reliable prediction and management of landfill gas production.
A new Volcanic managEment Risk Database desIgn (VERDI): Application to El Hierro Island (Canary Islands)

NASA Astrophysics Data System (ADS)

Bartolini, S.; Becerril, L.; Martí, J.

2014-11-01

One of the most important issues in modern volcanology is the assessment of volcanic risk, which will depend - among other factors - on both the quantity and quality of the available data and an optimum storage mechanism. This will require the design of purpose-built databases that take into account data format and availability and afford easy data storage and sharing, and will provide for a more complete risk assessment that combines different analyses but avoids any duplication of information. Data contained in any such database should facilitate spatial and temporal analysis that will (1) produce probabilistic hazard models for future vent opening, (2) simulate volcanic hazards and (3) assess their socio-economic impact. We describe the design of a new spatial database structure, VERDI (Volcanic managEment Risk Database desIgn), which allows different types of data, including geological, volcanological, meteorological, monitoring and socio-economic information, to be manipulated, organized and managed. The root of the question is to ensure that VERDI will serve as a tool for connecting different kinds of data sources, GIS platforms and modeling applications. We present an overview of the database design, its components and the attributes that play an important role in the database model. The potential of the VERDI structure and the possibilities it offers in regard to data organization are here shown through its application on El Hierro (Canary Islands). The VERDI database will provide scientists and decision makers with a useful tool that will assist to conduct volcanic risk assessment and management.
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.
How might Model-based Probabilities Extracted from Imperfect Models Guide Rational Decisions: The Case for non-probabilistic odds

NASA Astrophysics Data System (ADS)

Smith, Leonard A.

2010-05-01

This contribution concerns "deep" or "second-order" uncertainty, such as the uncertainty in our probability forecasts themselves. It asks the question: "Is it rational to take (or offer) bets using model-based probabilities as if they were objective probabilities?" If not, what alternative approaches for determining odds, perhaps non-probabilistic odds, might prove useful in practice, given the fact we know our models are imperfect? We consider the case where the aim is to provide sustainable odds: not to produce a profit but merely to rationally expect to break even in the long run. In other words, to run a quantified risk of ruin that is relatively small. Thus the cooperative insurance schemes of coastal villages provide a more appropriate parallel than a casino. A "better" probability forecast would lead to lower premiums charged and less volatile fluctuations in the cash reserves of the village. Note that the Bayesian paradigm does not constrain one to interpret model distributions as subjective probabilities, unless one believes the model to be empirically adequate for the task at hand. In geophysics, this is rarely the case. When a probability forecast is interpreted as the objective probability of an event, the odds on that event can be easily computed as one divided by the probability of the event, and one need not favour taking either side of the wager. (Here we are using "odds-for" not "odds-to", the difference being whether of not the stake is returned; odds of one to one are equivalent to odds of two for one.) The critical question is how to compute sustainable odds based on information from imperfect models. We suggest that this breaks the symmetry between the odds-on an event and the odds-against it. While a probability distribution can always be translated into odds, interpreting the odds on a set of events might result in "implied-probabilities" that sum to more than one. And/or the set of odds may be incomplete, not covering all events. We ask
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.
Earthquake parametrics based protection for microfinance disaster management in Indonesia

NASA Astrophysics Data System (ADS)

Sedayo, M. H.; Damanik, R.

2017-07-01

Financial institutions included microfinance institutions those lend money to people also face the risk when catastrophe event hit their operation area. Liquidity risk when withdrawal amount and Non Performance Loan (NPL) hiking fast in the same time could hit their cash flow. There are products in market that provide backup fund for this kind of situation. Microfinance institution needs a guideline too make contingency plan in their disaster management program. We develop a probabilistic seismic hazard, index and zonation map as a tool to help in making financial disaster impact reduction program for microfinance in Indonesia. GMPE was used to estimate PGA for each Kabupaten points. PGA to MMI conversion was done by applied empirical relationship. We used loan distribution data from Financial Service Authority and Bank Indonesia as exposure in indexing. Index level from this study could be use as rank of urgency. Probabilistic hazard map was used to pricing two backup scenarios and to make a zonation. We proposed three zones with annual average cost 0.0684‰, 0.4236‰ and 1.4064 for first scenario and 0.3588‰, 2.6112‰, and 6.0816‰ for second scenario.
Application of probabilistic analysis/design methods in space programs - The approaches, the status, and the needs

NASA Technical Reports Server (NTRS)

Ryan, Robert S.; Townsend, John S.

1993-01-01

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

PubMed Central

Karisani, Payam; Qin, Zhaohui S; Agichtein, Eugene

2018-01-01

Abstract The bioCADDIE dataset retrieval challenge brought together different approaches to retrieval of biomedical datasets relevant to a user’s query, expressed as a text description of a needed dataset. We describe experiments in applying a data-driven, machine learning-based approach to biomedical dataset retrieval as part of this challenge. We report on a series of experiments carried out to evaluate the performance of both probabilistic and machine learning-driven techniques from information retrieval, as applied to this challenge. Our experiments with probabilistic information retrieval methods, such as query term weight optimization, automatic query expansion and simulated user relevance feedback, demonstrate that automatically boosting the weights of important keywords in a verbose query is more effective than other methods. We also show that although there is a rich space of potential representations and features available in this domain, machine learning-based re-ranking models are not able to improve on probabilistic information retrieval techniques with the currently available training data. The models and algorithms presented in this paper can serve as a viable implementation of a search engine to provide access to biomedical datasets. The retrieval performance is expected to be further improved by using additional training data that is created by expert annotation, or gathered through usage logs, clicks and other processes during natural operation of the system. Database URL: https://github.com/emory-irlab/biocaddie PMID:29688379
Adaptive probabilistic collocation based Kalman filter for unsaturated flow problem

NASA Astrophysics Data System (ADS)

Man, J.; Li, W.; Zeng, L.; Wu, L.

2015-12-01

The ensemble Kalman filter (EnKF) has gained popularity in hydrological data assimilation problems. As a Monte Carlo based method, a relatively large ensemble size is usually required to guarantee the accuracy. As an alternative approach, the probabilistic collocation based Kalman filter (PCKF) employs the Polynomial Chaos to approximate the original system. In this way, the sampling error can be reduced. However, PCKF suffers from the so called "cure of dimensionality". When the system nonlinearity is strong and number of parameters is large, PCKF is even more computationally expensive than EnKF. Motivated by recent developments in uncertainty quantification, we propose a restart adaptive probabilistic collocation based Kalman filter (RAPCKF) for data assimilation in unsaturated flow problem. During the implementation of RAPCKF, the important parameters are identified and active PCE basis functions are adaptively selected. The "restart" technology is used to alleviate the inconsistency between model parameters and states. The performance of RAPCKF is tested by unsaturated flow numerical cases. It is shown that RAPCKF is more efficient than EnKF with the same computational cost. Compared with the traditional PCKF, the RAPCKF is more applicable in strongly nonlinear and high dimensional problems.
Risk perception as a driver for risk management policies

NASA Astrophysics Data System (ADS)

Carmona, María; Mañez, María

2016-04-01

Risk is generally defined as the "combination of the probability of the occurrence of an event and its negative consequences" ( UNISDR, 2009). However, the perception of a risk differs among cultures regarding different features such as the context,causes, benefits or damage. Risk perception is the subjective valuation of the probability of an event happening and how concerned individuals or groups are with the consequences (Sjöberg, 2004). Our study is based on an existing framework for risk perception (Rehn and Rohrmann, 2000). We analyse the characteristics of the risk perception regarding extreme events (e.g.droughts) and how the perception of the group drives the action to manage the risk. We do this to achieve an overview of the conditions that let stakeholders join each other to improve risk management especially when governments are not reacting properly. For our research, attention is paid on risk perception of Multi-Sector Partnerships not taking into account the individual level of risk perception. We focus on those factors that make risk management effective and increase resilience. Multi-Sector Partnerships, considered as significant governance structures for risk management, might contribute to reduce vulnerability in prone areas to natural hazards and disasters. The Multi-Sector Partnerships used for our research are existing partnerships identified in the cases studies of the European project ENHANCE. We implement a survey to analyse the perception of risk in the case studies. That survey is based on the Cultural Theory (Douglas and Wildavsky, 1982)and the Protection Motivation Theory (Rogers, 1975). We analyse the results using the Qualitative-Comparative Analysis proposed by Ragin in 1987. The results show the main characteristics of a risk culture that are beneficial to manage a risk. Those characteristics are shaped by the perception of risk of the people involved in the partnership, which in turn shapes their risk management. Nevertheless, we
Introduction to Decision Support Systems for Risk Based Management of Contaminated Sites

EPA Science Inventory

A book on Decision Support Systems for Risk-based Management of contaminated sites is appealing for two reasons. First, it addresses the problem of contaminated sites, which has worldwide importance. Second, it presents Decision Support Systems (DSSs), which are powerful comput...

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 Risk Assessment for Astronaut Post Flight Bone Fracture

NASA Technical Reports Server (NTRS)

Lewandowski, Beth; Myers, Jerry; Licata, Angelo

2015-01-01

Introduction: Space flight potentially reduces the loading that bone can resist before fracture. This reduction in bone integrity may result from a combination of factors, the most common reported as reduction in astronaut BMD. Although evaluating the condition of bones continues to be a critical aspect of understanding space flight fracture risk, defining the loading regime, whether on earth, in microgravity, or in reduced gravity on a planetary surface, remains a significant component of estimating the fracture risks to astronauts. This presentation summarizes the concepts, development, and application of NASA's Bone Fracture Risk Module (BFxRM) to understanding pre-, post, and in mission astronaut bone fracture risk. The overview includes an assessment of contributing factors utilized in the BFxRM and illustrates how new information, such as biomechanics of space suit design or better understanding of post flight activities may influence astronaut fracture risk. Opportunities for the bone mineral research community to contribute to future model development are also discussed. Methods: To investigate the conditions in which spaceflight induced changes to bone plays a critical role in post-flight fracture probability, we implement a modified version of the NASA Bone Fracture Risk Model (BFxRM). Modifications included incorporation of variations in physiological characteristics, post-flight recovery rate, and variations in lateral fall conditions within the probabilistic simulation parameter space. The modeled fracture probability estimates for different loading scenarios at preflight and at 0 and 365 days post-flight time periods are compared. Results: For simple lateral side falls, mean post-flight fracture probability is elevated over mean preflight fracture probability due to spaceflight induced BMD loss and is not fully recovered at 365 days post-flight. In the case of more energetic falls, such as from elevated heights or with the addition of lateral movement
An evaluation of a risk-based environmental regulation in Brazil: Limitations to risk management of hazardous installations

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

Naime, Andre, E-mail: andre.naime.ibama@gmail.com

The environmental regulation of hazardous projects with risk-based decision-making processes can lead to a deficient management of human exposure to technological hazards. Such an approach for regulation is criticized for simplifying the complexity of decisions involving the economic, social, and environmental aspects of the installation and operation of hazardous facilities in urban areas. Results of a Brazilian case study indicate that oil and gas transmission pipelines may represent a threat to diverse communities if the relationship between such linear projects and human populations is overlooked by regulatory bodies. Results also corroborate known challenges to the implementation of EIA processes andmore » outline limitations to an effective environmental and risk management. Two preliminary topics are discussed to strengthen similar regulatory practices. Firstly, an effective integration between social impact assessment and risk assessment in EIA processes to have a more comprehensive understanding of the social fabric. Secondly, the advancement of traditional management practices for hazardous installations to pursue a strong transition from assessment and evaluation to management and control and to promote an effective interaction between land-use planning and environmental regulation.« less
Sensor Based Engine Life Calculation: A Probabilistic Perspective

NASA Technical Reports Server (NTRS)

Guo, Ten-Huei; Chen, Philip

2003-01-01

It is generally known that an engine component will accumulate damage (life usage) during its lifetime of use in a harsh operating environment. The commonly used cycle count for engine component usage monitoring has an inherent range of uncertainty which can be overly costly or potentially less safe from an operational standpoint. With the advance of computer technology, engine operation modeling, and the understanding of damage accumulation physics, it is possible (and desirable) to use the available sensor information to make a more accurate assessment of engine component usage. This paper describes a probabilistic approach to quantify the effects of engine operating parameter uncertainties on the thermomechanical fatigue (TMF) life of a selected engine part. A closed-loop engine simulation with a TMF life model is used to calculate the life consumption of different mission cycles. A Monte Carlo simulation approach is used to generate the statistical life usage profile for different operating assumptions. The probabilities of failure of different operating conditions are compared to illustrate the importance of the engine component life calculation using sensor information. The results of this study clearly show that a sensor-based life cycle calculation can greatly reduce the risk of component failure as well as extend on-wing component life by avoiding unnecessary maintenance actions.
Adoption of Building Information Modelling in project planning risk management

NASA Astrophysics Data System (ADS)

Mering, M. M.; Aminudin, E.; Chai, C. S.; Zakaria, R.; Tan, C. S.; Lee, Y. Y.; Redzuan, A. A.

2017-11-01

An efficient and effective risk management required a systematic and proper methodology besides knowledge and experience. However, if the risk management is not discussed from the starting of the project, this duty is notably complicated and no longer efficient. This paper presents the adoption of Building Information Modelling (BIM) in project planning risk management. The objectives is to identify the traditional risk management practices and its function, besides, determine the best function of BIM in risk management and investigating the efficiency of adopting BIM-based risk management during the project planning phase. In order to obtain data, a quantitative approach is adopted in this research. Based on data analysis, the lack of compliance with project requirements and failure to recognise risk and develop responses to opportunity are the risks occurred when traditional risk management is implemented. When using BIM in project planning, it works as the tracking of cost control and cash flow give impact on the project cycle to be completed on time. 5D cost estimation or cash flow modeling benefit risk management in planning, controlling and managing budget and cost reasonably. There were two factors that mostly benefit a BIM-based technology which were formwork plan with integrated fall plan and design for safety model check. By adopting risk management, potential risks linked with a project and acknowledging to those risks can be identified to reduce them to an acceptable extent. This means recognizing potential risks and avoiding threat by reducing their negative effects. The BIM-based risk management can enhance the planning process of construction projects. It benefits the construction players in various aspects. It is important to know the application of BIM-based risk management as it can be a lesson learnt to others to implement BIM and increase the quality of the project.
A cost-effectiveness analysis of a proactive management strategy for the Sprint Fidelis recall: a probabilistic decision analysis model.

PubMed

Bashir, Jamil; Cowan, Simone; Raymakers, Adam; Yamashita, Michael; Danter, Matthew; Krahn, Andrew; Lynd, Larry D

2013-12-01

The management of the recall is complicated by the competing risks of lead failure and complications that can occur with lead revision. Many of these patients are currently undergoing an elective generator change--an ideal time to consider lead revision. To determine the cost-effectiveness of a proactive management strategy for the Sprint Fidelis recall. We obtained detailed clinical outcomes and costing data from a retrospective analysis of 341 patients who received the Sprint Fidelis lead in British Columbia, where patients younger than 60 years were offered lead extraction when undergoing generator replacement. These population-based data were used to construct and populate a probabilistic Markov model in which a proactive management strategy was compared to a conservative strategy to determine the incremental cost per lead failure avoided. In our population, elective lead revisions were half the cost of emergent revisions and had a lower complication rate. In the model, the incremental cost-effectiveness ratio of proactive lead revision versus a recommended monitoring strategy was $12,779 per lead failure avoided. The proactive strategy resulted in 21 fewer failures per 100 patients treated and reduced the chance of an additional complication from an unexpected surgery. Cost-effectiveness analysis suggests that prospective lead revision should be considered when patients with a Sprint Fidelis lead present for pulse generator change. Elective revision of the lead is justified even when 25% of the population is operated on per year, and in some scenarios, it is both less costly and provides a better outcome. © 2013 Heart Rhythm Society Published by Heart Rhythm Society All rights reserved.
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.
Comparison of acrylamide intake from Western and guideline based diets using probabilistic techniques and linear programming.

PubMed

Katz, Josh M; Winter, Carl K; Buttrey, Samuel E; Fadel, James G

2012-03-01

Western and guideline based diets were compared to determine if dietary improvements resulting from following dietary guidelines reduce acrylamide intake. Acrylamide forms in heat treated foods and is a human neurotoxin and animal carcinogen. Acrylamide intake from the Western diet was estimated with probabilistic techniques using teenage (13-19 years) National Health and Nutrition Examination Survey (NHANES) food consumption estimates combined with FDA data on the levels of acrylamide in a large number of foods. Guideline based diets were derived from NHANES data using linear programming techniques to comport to recommendations from the Dietary Guidelines for Americans, 2005. Whereas the guideline based diets were more properly balanced and rich in consumption of fruits, vegetables, and other dietary components than the Western diets, acrylamide intake (mean±SE) was significantly greater (P<0.001) from consumption of the guideline based diets (0.508±0.003 μg/kg/day) than from consumption of the Western diets (0.441±0.003 μg/kg/day). Guideline based diets contained less acrylamide contributed by French fries and potato chips than Western diets. Overall acrylamide intake, however, was higher in guideline based diets as a result of more frequent breakfast cereal intake. This is believed to be the first example of a risk assessment that combines probabilistic techniques with linear programming and results demonstrate that linear programming techniques can be used to model specific diets for the assessment of toxicological and nutritional dietary components. Copyright Â© 2011 Elsevier Ltd. All rights reserved.
Evaluation of the risk of perchlorate exposure in a population of late-gestation pregnant women in the United States: Application of probabilistic biologically-based dose response modeling

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

Lumen, A, E-mail: Annie.Lumen@fda.hhs.gov

The risk of ubiquitous perchlorate exposure and the dose-response on thyroid hormone levels in pregnant women in the United States (U.S.) have yet to be characterized. In the current work, we integrated a previously developed perchlorate submodel into a recently developed population-based pregnancy model to predict reductions in maternal serum free thyroxine (fT4) levels for late-gestation pregnant women in the U.S. Our findings indicated no significant difference in geometric mean estimates of fT4 when perchlorate exposure from food only was compared to no perchlorate exposure. The reduction in maternal fT4 levels reached statistical significance when an added contribution from drinkingmore » water (i.e., 15 μg/L, 20 μg/L, or 24.5 μg/L) was assumed in addition to the 90th percentile of food intake for pregnant women (0.198 μg/kg/day). We determined that a daily intake of 0.45 to 0.50 μg/kg/day of perchlorate was necessary to produce results that were significantly different than those obtained from no perchlorate exposure. Adjusting for this food intake dose, the relative source contribution of perchlorate from drinking water (or other non-dietary sources) was estimated to range from 0.25–0.3 μg/kg/day. Assuming a drinking water intake rate of 0.033 L/kg/day, the drinking water concentration allowance for perchlorate equates to 7.6–9.2 μg/L. In summary, we have demonstrated the utility of a probabilistic biologically-based dose-response model for perchlorate risk assessment in a sensitive life-stage at a population level; however, there is a need for continued monitoring in regions of the U.S. where perchlorate exposure may be higher. - Highlights: • Probabilistic risk assessment for perchlorate in U.S. pregnant women was conducted. • No significant change in maternal fT4 predicted due to perchlorate from food alone. • Drinking water concentration allowance for perchlorate estimated as 7.6–9.2 μg/L.« less
Managing health and safety risks: Implications for tailoring health and safety management system practices.

PubMed

Willmer, D R; Haas, E J

2016-01-01

As national and international health and safety management system (HSMS) standards are voluntarily accepted or regulated into practice, organizations are making an effort to modify and integrate strategic elements of a connected management system into their daily risk management practices. In high-risk industries such as mining, that effort takes on added importance. The mining industry has long recognized the importance of a more integrated approach to recognizing and responding to site-specific risks, encouraging the adoption of a risk-based management framework. Recently, the U.S. National Mining Association led the development of an industry-specific HSMS built on the strategic frameworks of ANSI: Z10, OHSAS 18001, The American Chemistry Council's Responsible Care, and ILO-OSH 2001. All of these standards provide strategic guidance and focus on how to incorporate a plan-do-check-act cycle into the identification, management and evaluation of worksite risks. This paper details an exploratory study into whether practices associated with executing a risk-based management framework are visible through the actions of an organization's site-level management of health and safety risks. The results of this study show ways that site-level leaders manage day-to-day risk at their operations that can be characterized according to practices associated with a risk-based management framework. Having tangible operational examples of day-to-day risk management can serve as a starting point for evaluating field-level risk assessment efforts and their alignment to overall company efforts at effective risk mitigation through a HSMS or other processes.
MO-E-9A-01: Risk Based Quality Management: TG100 In Action

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

Huq, M; Palta, J; Dunscombe, P

2014-06-15

One of the goals of quality management in radiation therapy is to gain high confidence that patients will receive the prescribed treatment correctly. To accomplish these goals professional societies such as the American Association of Physicists in Medicine (AAPM) has published many quality assurance (QA), quality control (QC), and quality management (QM) guidance documents. In general, the recommendations provided in these documents have emphasized on performing device-specific QA at the expense of process flow and protection of the patient against catastrophic errors. Analyses of radiation therapy incidents find that they are most often caused by flaws in the overall therapymore » process, from initial consult through final treatment, than by isolated hardware or computer failures detectable by traditional physics QA. This challenge is shared by many intrinsically hazardous industries. Risk assessment tools and analysis techniques have been developed to define, identify, and eliminate known and/or potential failures, problems, or errors, from a system, process and/or service before they reach the customer. These include, but are not limited to, process mapping, failure modes and effects analysis (FMEA), fault tree analysis (FTA), and establishment of a quality management program that best avoids the faults and risks that have been identified in the overall process. These tools can be easily adapted to radiation therapy practices because of their simplicity and effectiveness to provide efficient ways to enhance the safety and quality of treatment processes. Task group 100 (TG100) of AAPM has developed a risk-based quality management program that uses these tools. This session will be devoted to a discussion of these tools and how these tools can be used in a given radiotherapy clinic to develop a risk based QM program. Learning Objectives: Learn how to design a process map for a radiotherapy process. Learn how to perform a FMEA analysis for a given process
NASA's Risk Management System

NASA Technical Reports Server (NTRS)

Perera, Jeevan S.

2011-01-01

Leadership is key to success. Phased-approach for implementation of risk management is necessary. Risk management system will be simple, accessible and promote communication of information to all relevant stakeholders for optimal resource allocation and risk mitigation. Risk management should be used by all team members to manage risks -- risk office personnel. Each group is assigned Risk Integrators who are facilitators for effective risk management. Risks will be managed at the lowest-level feasible, elevate only those risks that require coordination or management from above. Risk reporting and communication is an essential element of risk management and will combine both qualitative and quantitative elements. Risk informed decision making should be introduced to all levels of management. Provide necessary checks and balances to insure that risks are caught/identified and dealt with in a timely manner. Many supporting tools, processes & training must be deployed for effective risk management implementation. Process improvement must be included in the risk processes.
[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.
Applications of the International Space Station Probabilistic Risk Assessment Model

NASA Technical Reports Server (NTRS)

Grant, Warren; Lutomski, Michael G.

2011-01-01

Recently the International Space Station (ISS) has incorporated more Probabilistic Risk Assessments (PRAs) in the decision making process for significant issues. Future PRAs will have major impact to ISS and future spacecraft development and operations. These PRAs will have their foundation in the current complete ISS PRA model and the current PRA trade studies that are being analyzed as requested by ISS Program stakeholders. ISS PRAs have recently helped in the decision making process for determining reliability requirements for future NASA spacecraft and commercial spacecraft, making crew rescue decisions, as well as making operational requirements for ISS orbital orientation, planning Extravehicular activities (EVAs) and robotic operations. This paper will describe some applications of the ISS PRA model and how they impacted the final decision. This paper will discuss future analysis topics such as life extension, requirements of new commercial vehicles visiting ISS.
Toward a Responsibility-Catering Prioritarian Ethical Theory of Risk.

PubMed

Wikman-Svahn, Per; Lindblom, Lars

2018-03-05

Standard tools used in societal risk management such as probabilistic risk analysis or cost-benefit analysis typically define risks in terms of only probabilities and consequences and assume a utilitarian approach to ethics that aims to maximize expected utility. The philosopher Carl F. Cranor has argued against this view by devising a list of plausible aspects of the acceptability of risks that points towards a non-consequentialist ethical theory of societal risk management. This paper revisits Cranor's list to argue that the alternative ethical theory responsibility-catering prioritarianism can accommodate the aspects identified by Cranor and that the elements in the list can be used to inform the details of how to view risks within this theory. An approach towards operationalizing the theory is proposed based on a prioritarian social welfare function that operates on responsibility-adjusted utilities. A responsibility-catering prioritarian ethical approach towards managing risks is a promising alternative to standard tools such as cost-benefit analysis.
NASA's Risk Management System

NASA Technical Reports Server (NTRS)

Perera, Jeevan S.

2013-01-01

Phased-approach for implementation of risk management is necessary. Risk management system will be simple, accessible and promote communication of information to all relevant stakeholders for optimal resource allocation and risk mitigation. Risk management should be used by all team members to manage risks - not just risk office personnel. Each group/department is assigned Risk Integrators who are facilitators for effective risk management. Risks will be managed at the lowest-level feasible, elevate only those risks that require coordination or management from above. Risk informed decision making should be introduced to all levels of management. ? Provide necessary checks and balances to insure that risks are caught/identified and dealt with in a timely manner. Many supporting tools, processes & training must be deployed for effective risk management implementation. Process improvement must be included in the risk processes.
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
A simulation-based probabilistic design method for arctic sea transport systems

NASA Astrophysics Data System (ADS)

Martin, Bergström; Ove, Erikstad Stein; Sören, Ehlers

2016-12-01

When designing an arctic cargo ship, it is necessary to consider multiple stochastic factors. This paper evaluates the merits of a simulation-based probabilistic design method specifically developed to deal with this challenge. The outcome of the paper indicates that the incorporation of simulations and probabilistic design parameters into the design process enables more informed design decisions. For instance, it enables the assessment of the stochastic transport capacity of an arctic ship, as well as of its long-term ice exposure that can be used to determine an appropriate level of ice-strengthening. The outcome of the paper also indicates that significant gains in transport system cost-efficiency can be obtained by extending the boundaries of the design task beyond the individual vessel. In the case of industrial shipping, this allows for instance the consideration of port-based cargo storage facilities allowing for temporary shortages in transport capacity and thus a reduction in the required fleet size / ship capacity.
Hybrid Packet-Pheromone-Based Probabilistic Routing for Mobile Ad Hoc Networks

NASA Astrophysics Data System (ADS)

Kashkouli Nejad, Keyvan; Shawish, Ahmed; Jiang, Xiaohong; Horiguchi, Susumu

Ad-Hoc networks are collections of mobile nodes communicating using wireless media without any fixed infrastructure. Minimal configuration and quick deployment make Ad-Hoc networks suitable for emergency situations like natural disasters or military conflicts. The current Ad-Hoc networks can only support either high mobility or high transmission rate at a time because they employ static approaches in their routing schemes. However, due to the continuous expansion of the Ad-Hoc network size, node-mobility and transmission rate, the development of new adaptive and dynamic routing schemes has become crucial. In this paper we propose a new routing scheme to support high transmission rates and high node-mobility simultaneously in a big Ad-Hoc network, by combining a new proposed packet-pheromone-based approach with the Hint Based Probabilistic Protocol (HBPP) for congestion avoidance with dynamic path selection in packet forwarding process. Because of using the available feedback information, the proposed algorithm does not introduce any additional overhead. The extensive simulation-based analysis conducted in this paper indicates that the proposed algorithm offers small packet-latency and achieves a significantly higher delivery probability in comparison with the available Hint-Based Probabilistic Protocol (HBPP).
Risk management frameworks for human health and environmental risks.

PubMed

Jardine, Cindy; Hrudey, Steve; Shortreed, John; Craig, Lorraine; Krewski, Daniel; Furgal, Chris; McColl, Stephen

2003-01-01

-Making Framework for Identifying, Assessing and Managing Health Risks (Health Canada, 2000). 4. Canadian Environmental Protection Act: Human Health Risk Assessment of Priority Substances(Health Canada, 1994). 5. CSA-Q8550 Risk Management: Guidelines for Decision-Makers (Canada Standards Association, 1997). 6. Risk Assessment in the Federal Government: Managing the Process (US National Research Council, 1983). 7. Understanding Risk: Informing Decisions in a Democratic Society (US National Research Council, 1996). 8. Environmental Health Risk Assessment (enHealth Council of Australia, 2002). 9. A Framework for Ecological Risk Assessment (CCME, 1996). 10. Ecological Risk Assessments of Priority Substances Under the Canadian Environmental Protection Act (Environment Canada, 1996).11. Guidelines for Ecological Risk Assessment (US EPA, 1998b). 12. Proposed Model for Occupational Health Risk Assessment and Management (Rampal & Sadhra, 1999). Based on the extensive review of these frameworks, seven key elements that should be included in a comprehensive framework for human health, ecological, and occupational risk assessment and management were identified: 1. Problem formulation stage. 2. Stakeholder involvement. 3. Communication. 4. Quantitative risk assessment components. 5. Iteration and evaluation. 6. Informed decision making. 7. Flexibility. On the basis of this overarching approach to risk management, the following "checklist" to ensure a good risk management decision is proposed: - Make sure you're solving the right problem. - Consider the problem and the risk within the full context of the situation, using a broad perspective. - Acknowledge, incorporate, and balance the multiple dimensions of risk. - Ensure the highest degree of reliability for all components of the risk management process. - Involve interested and effected parties from the outset of the process. - Commit to honest and open communication between all parties. - Employ continuous evaluation throughout the process

Cognitive mapping tools: review and risk management needs.

PubMed

Wood, Matthew D; Bostrom, Ann; Bridges, Todd; Linkov, Igor

2012-08-01

Risk managers are increasingly interested in incorporating stakeholder beliefs and other human factors into the planning process. Effective risk assessment and management requires understanding perceptions and beliefs of involved stakeholders, and how these beliefs give rise to actions that influence risk management decisions. Formal analyses of risk manager and stakeholder cognitions represent an important first step. Techniques for diagramming stakeholder mental models provide one tool for risk managers to better understand stakeholder beliefs and perceptions concerning risk, and to leverage this new understanding in developing risk management strategies. This article reviews three methodologies for assessing and diagramming stakeholder mental models--decision-analysis-based mental modeling, concept mapping, and semantic web analysis--and assesses them with regard to their ability to address risk manager needs. © 2012 Society for Risk Analysis.
How Confident can we be in Flood Risk Assessments?

NASA Astrophysics Data System (ADS)

Merz, B.

2017-12-01

Flood risk management should be based on risk analyses quantifying the risk and its reduction for different risk reduction strategies. However, validating risk estimates by comparing model simulations with past observations is hardly possible, since the assessment typically encompasses extreme events and their impacts that have not been observed before. Hence, risk analyses are strongly based on assumptions and expert judgement. This situation opens the door for cognitive biases, such as `illusion of certainty', `overconfidence' or `recency bias'. Such biases operate specifically in complex situations with many factors involved, when uncertainty is high and events are probabilistic, or when close learning feedback loops are missing - aspects that all apply to risk analyses. This contribution discusses how confident we can be in flood risk assessments, and reflects about more rigorous approaches towards their validation.
A risk-based approach to sanitary sewer pipe asset management.

PubMed

Baah, Kelly; Dubey, Brajesh; Harvey, Richard; McBean, Edward

2015-02-01

Wastewater collection systems are an important component of proper management of wastewater to prevent environmental and human health implications from mismanagement of anthropogenic waste. Due to aging and inadequate asset management practices, the wastewater collection assets of many cities around the globe are in a state of rapid decline and in need of urgent attention. Risk management is a tool which can help prioritize resources to better manage and rehabilitate wastewater collection systems. In this study, a risk matrix and a weighted sum multi-criteria decision-matrix are used to assess the consequence and risk of sewer pipe failure for a mid-sized city, using ArcGIS. The methodology shows that six percent of the uninspected sewer pipe assets of the case study have a high consequence of failure while four percent of the assets have a high risk of failure and hence provide priorities for inspection. A map incorporating risk of sewer pipe failure and consequence is developed to facilitate future planning, rehabilitation and maintenance programs. The consequence of failure assessment also includes a novel failure impact factor which captures the effect of structurally defective stormwater pipes on the failure assessment. The methodology recommended in this study can serve as a basis for future planning and decision making and has the potential to be universally applied by municipal sewer pipe asset managers globally to effectively manage the sanitary sewer pipe infrastructure within their jurisdiction. Copyright © 2014 Elsevier B.V. All rights reserved.
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.
Risk-based enteric pathogen reduction targets for non-potable and direct potable use of roof runoff, stormwater, and greywater

EPA Science Inventory

This paper presents risk-based enteric pathogen log reduction targets for non-potable and potable uses of a variety of alternative source waters (i.e., locally-collected greywater, roof runoff, and stormwater). A probabilistic Quantitative Microbial Risk Assessment (QMRA) was use...
[Global risk management].

PubMed

Sghaier, W; Hergon, E; Desroches, A

2015-08-01

Risk management is a fundamental component of any successful company, whether it is in economic, societal or environmental aspect. Risk management is an especially important activity for companies that optimal security challenge of products and services is great. This is the case especially for the health sector institutions. Risk management is therefore a decision support tool and a means to ensure the sustainability of an organization. In this context, what methods and approaches implemented to manage the risks? Through this state of the art, we are interested in the concept of risk and risk management processes. Then we focus on the different methods of risk management and the criteria for choosing among these methods. Finally we highlight the need to supplement these methods by a systemic and global approach including through risk assessment by the audits. Copyright © 2015 Elsevier Masson SAS. All rights reserved.
Robust Observation Detection for Single Object Tracking: Deterministic and Probabilistic Patch-Based Approaches

PubMed Central

Zulkifley, Mohd Asyraf; Rawlinson, David; Moran, Bill

2012-01-01

In video analytics, robust observation detection is very important as the content of the videos varies a lot, especially for tracking implementation. Contrary to the image processing field, the problems of blurring, moderate deformation, low illumination surroundings, illumination change and homogenous texture are normally encountered in video analytics. Patch-Based Observation Detection (PBOD) is developed to improve detection robustness to complex scenes by fusing both feature- and template-based recognition methods. While we believe that feature-based detectors are more distinctive, however, for finding the matching between the frames are best achieved by a collection of points as in template-based detectors. Two methods of PBOD—the deterministic and probabilistic approaches—have been tested to find the best mode of detection. Both algorithms start by building comparison vectors at each detected points of interest. The vectors are matched to build candidate patches based on their respective coordination. For the deterministic method, patch matching is done in 2-level test where threshold-based position and size smoothing are applied to the patch with the highest correlation value. For the second approach, patch matching is done probabilistically by modelling the histograms of the patches by Poisson distributions for both RGB and HSV colour models. Then, maximum likelihood is applied for position smoothing while a Bayesian approach is applied for size smoothing. The result showed that probabilistic PBOD outperforms the deterministic approach with average distance error of 10.03% compared with 21.03%. This algorithm is best implemented as a complement to other simpler detection methods due to heavy processing requirement. PMID:23202226
Managing Research in a Risk World

NASA Technical Reports Server (NTRS)

Anton, W.; Havenhill, M.

2014-01-01

The Office of Chief Medical Officer (OCHMO) owns all human health and performance risks managed by the Human System Risk Board (HSRB). While the HSRB manages the risks, the Human Research Program (HRP) manages the research portion of the overall risk mitigation strategy for these risks. The HSRB manages risks according to a process that identifies and analyzes risks, plans risk mitigation and tracks and reviews the implementation of these strategies according to its decisions pertaining to the OCHMO risk posture. HRP manages risk research work using an architecture that describes evidence-based risks, gaps in our knowledge about characterizing or mitigating the risk, and the tasks needed to produce deliverables to fill the gaps and reduce the risk. A planning schedule reflecting expected research milestones is developed, and as deliverables and new evidence are generated, research progress is tracked via the Path to Risk Reduction (PRR) that reflects a risk's research plan for a design reference mission. HRP's risk research process closely interfaces with the HSRB risk management process. As research progresses, new deliverables and evidence are used by the HSRB in conjunction with other operational and non-research evidence to inform decisions pertaining to the likelihood and consequence of the risk and risk posture. Those decisions in turn guide forward work for research as it contributes to overall risk mitigation strategies. As HRP tracks its research work, it aligns its priorities by assessing the effectiveness of its contributions and maintaining specific core competencies that would be invaluable for future work for exploration missions.
A Framework for Probabilistic Evaluation of Interval Management Tolerance in the Terminal Radar Control Area

NASA Technical Reports Server (NTRS)

Hercencia-Zapana, Heber; Herencia-Zapana, Heber; Hagen, George E.; Neogi, Natasha

2012-01-01

Projections of future traffic in the national airspace show that most of the hub airports and their attendant airspace will need to undergo significant redevelopment and redesign in order to accommodate any significant increase in traffic volume. Even though closely spaced parallel approaches increase throughput into a given airport, controller workload in oversubscribed metroplexes is further taxed by these approaches that require stringent monitoring in a saturated environment. The interval management (IM) concept in the TRACON area is designed to shift some of the operational burden from the control tower to the flight deck, placing the flight crew in charge of implementing the required speed changes to maintain a relative spacing interval. The interval management tolerance is a measure of the allowable deviation from the desired spacing interval for the IM aircraft (and its target aircraft). For this complex task, Formal Methods can help to ensure better design and system implementation. In this paper, we propose a probabilistic framework to quantify the uncertainty and performance associated with the major components of the IM tolerance. The analytical basis for this framework may be used to formalize both correctness and probabilistic system safety claims in a modular fashion at the algorithmic level in a way compatible with several Formal Methods tools.
Students’ difficulties in probabilistic problem-solving

NASA Astrophysics Data System (ADS)

Arum, D. P.; Kusmayadi, T. A.; Pramudya, I.

2018-03-01

There are many errors can be identified when students solving mathematics problems, particularly in solving the probabilistic problem. This present study aims to investigate students’ difficulties in solving the probabilistic problem. It focuses on analyzing and describing students errors during solving the problem. This research used the qualitative method with case study strategy. The subjects in this research involve ten students of 9th grade that were selected by purposive sampling. Data in this research involve students’ probabilistic problem-solving result and recorded interview regarding students’ difficulties in solving the problem. Those data were analyzed descriptively using Miles and Huberman steps. The results show that students have difficulties in solving the probabilistic problem and can be divided into three categories. First difficulties relate to students’ difficulties in understanding the probabilistic problem. Second, students’ difficulties in choosing and using appropriate strategies for solving the problem. Third, students’ difficulties with the computational process in solving the problem. Based on the result seems that students still have difficulties in solving the probabilistic problem. It means that students have not able to use their knowledge and ability for responding probabilistic problem yet. Therefore, it is important for mathematics teachers to plan probabilistic learning which could optimize students probabilistic thinking ability.
Probabilistic stability analysis: the way forward for stability analysis of sustainable power systems.

PubMed

Milanović, Jovica V

2017-08-13

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

EPA Pesticide Factsheets

Past weight-of-evidence frameworks for adverse ecological effects have provided soft-scoring procedures for judgments based on the quality and measured attributes of evidence. Here, we provide a flexible probabilistic structure for weighing and integrating lines of evidence for ecological risk determinations. Probabilistic approaches can provide both a quantitative weighing of lines of evidence and methods for evaluating risk and uncertainty. The current modeling structure wasdeveloped for propagating uncertainties in measured endpoints and their influence on the plausibility of adverse effects. To illustrate the approach, we apply the model framework to the sediment quality triad using example lines of evidence for sediment chemistry measurements, bioassay results, and in situ infauna diversity of benthic communities using a simplified hypothetical case study. We then combine the three lines evidence and evaluate sensitivity to the input parameters, and show how uncertainties are propagated and how additional information can be incorporated to rapidly update the probability of impacts. The developed network model can be expanded to accommodate additional lines of evidence, variables and states of importance, and different types of uncertainties in the lines of evidence including spatial and temporal as well as measurement errors. We provide a flexible Bayesian network structure for weighing and integrating lines of evidence for ecological risk determinations
Assessing and managing the health risk due to ingestion of inorganic arsenic from fish and shellfish farmed in blackfoot disease areas for general Taiwanese.

PubMed

Liang, Ching-Ping; Liu, Chen-Wuing; Jang, Cheng-Shin; Wang, Sheng-Wei; Lee, Jin-Jing

2011-02-15

This paper assesses health risks due to the ingestion of inorganic arsenic from fish and shellfish farmed in blackfoot disease areas by general public in Taiwan. The provisional tolerable weekly intake of arsenic set by FAO/WHO and the target cancer risk assessment model proposed by USEPA were integrated to evaluate the acceptable consumption rate. Five aquacultural species, tilapia (Oreochromis mossambicus), milkfish (Chanos chanos), mullet (Mugil cephalus), clam (Meretrix lusoria) and oyster (Crassostrea gigas) were included. Monte Carlo analysis was used to propagate the parameter uncertainty and to probabilistically assess the health risk associated with the daily intake of inorganic As from farmed fish and shellfish. The integrated risk-based analysis indicates that the associated 50th and 95th percentile health risk are 2.06×10(-5) and 8.77×10(-5), respectively. Moreover, the acceptable intakes of inorganic As are defined and illustrated by a two dimensional graphical model. According to the relationship between C(inorg) and IR(f) derived from this study, two risk-based curves are constructed. An acceptable risk zone is determined (risk ranging from 1×10(-5) to 6.07×10(-5)) which is recommended for acceptable consumption rates of fish and shellfish. To manage the health risk due to the ingestion of inorganic As from fish and shellfish in BFD areas, a risk-based management scheme is derived which provide a convenient way for general public to self-determine the acceptable seafood consumption rate. Copyright © 2010 Elsevier B.V. All rights reserved.
Is Probabilistic Evidence a Source of Knowledge?

ERIC Educational Resources Information Center

Friedman, Ori; Turri, John

2015-01-01

We report a series of experiments examining whether people ascribe knowledge for true beliefs based on probabilistic evidence. Participants were less likely to ascribe knowledge for beliefs based on probabilistic evidence than for beliefs based on perceptual evidence (Experiments 1 and 2A) or testimony providing causal information (Experiment 2B).…
Managing Liability. Employment Discrimination: A Risk Management Strategy.

ERIC Educational Resources Information Center

McMullan, Sandra H.

This booklet discusses the risks that educational institutions face in regard to employment discrimination litigation and outlines a program to effectively manage such risks. Institutions need to address three main types of employment discrimination issues: sexual harassment, disability-based discrimination, and age discrimination. To deal with…
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
A Comparison of Probabilistic and Deterministic Campaign Analysis for Human Space Exploration

NASA Technical Reports Server (NTRS)

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

2008-01-01

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

PubMed

Dimitrova, Dimitrina S; Kaishev, Vladimir K; Zhao, Shouqi

2015-10-01

In this article, we introduce a framework for analyzing the risk of systems failure based on estimating the failure probability. The latter is defined as the probability that a certain risk process, characterizing the operations of a system, reaches a possibly time-dependent critical risk level within a finite-time interval. Under general assumptions, we define two dually connected models for the risk process and derive explicit expressions for the failure probability and also the joint probability of the time of the occurrence of failure and the excess of the risk process over the risk level. We illustrate how these probabilistic models and results can be successfully applied in several important areas of risk analysis, among which are systems reliability, inventory management, flood control via dam management, infectious disease spread, and financial insolvency. Numerical illustrations are also presented. © 2015 Society for Risk Analysis.
A global probabilistic tsunami hazard assessment from earthquake sources

USGS Publications Warehouse

Davies, Gareth; Griffin, Jonathan; Lovholt, Finn; Glimsdal, Sylfest; Harbitz, Carl; Thio, Hong Kie; Lorito, Stefano; Basili, Roberto; Selva, Jacopo; Geist, Eric L.; Baptista, Maria Ana

2017-01-01

Large tsunamis occur infrequently but have the capacity to cause enormous numbers of casualties, damage to the built environment and critical infrastructure, and economic losses. A sound understanding of tsunami hazard is required to underpin management of these risks, and while tsunami hazard assessments are typically conducted at regional or local scales, globally consistent assessments are required to support international disaster risk reduction efforts, and can serve as a reference for local and regional studies. This study presents a global-scale probabilistic tsunami hazard assessment (PTHA), extending previous global-scale assessments based largely on scenario analysis. Only earthquake sources are considered, as they represent about 80% of the recorded damaging tsunami events. Globally extensive estimates of tsunami run-up height are derived at various exceedance rates, and the associated uncertainties are quantified. Epistemic uncertainties in the exceedance rates of large earthquakes often lead to large uncertainties in tsunami run-up. Deviations between modelled tsunami run-up and event observations are quantified, and found to be larger than suggested in previous studies. Accounting for these deviations in PTHA is important, as it leads to a pronounced increase in predicted tsunami run-up for a given exceedance rate.
Probabilistic numerics and uncertainty in computations

PubMed Central

Hennig, Philipp; Osborne, Michael A.; Girolami, Mark

2015-01-01

We deliver a call to arms for probabilistic numerical methods: algorithms for numerical tasks, including linear algebra, integration, optimization and solving differential equations, that return uncertainties in their calculations. Such uncertainties, arising from the loss of precision induced by numerical calculation with limited time or hardware, are important for much contemporary science and industry. Within applications such as climate science and astrophysics, the need to make decisions on the basis of computations with large and complex data have led to a renewed focus on the management of numerical uncertainty. We describe how several seminal classic numerical methods can be interpreted naturally as probabilistic inference. We then show that the probabilistic view suggests new algorithms that can flexibly be adapted to suit application specifics, while delivering improved empirical performance. We provide concrete illustrations of the benefits of probabilistic numeric algorithms on real scientific problems from astrometry and astronomical imaging, while highlighting open problems with these new algorithms. Finally, we describe how probabilistic numerical methods provide a coherent framework for identifying the uncertainty in calculations performed with a combination of numerical algorithms (e.g. both numerical optimizers and differential equation solvers), potentially allowing the diagnosis (and control) of error sources in computations. PMID:26346321

Probabilistic numerics and uncertainty in computations.

PubMed

Hennig, Philipp; Osborne, Michael A; Girolami, Mark

2015-07-08

We deliver a call to arms for probabilistic numerical methods : algorithms for numerical tasks, including linear algebra, integration, optimization and solving differential equations, that return uncertainties in their calculations. Such uncertainties, arising from the loss of precision induced by numerical calculation with limited time or hardware, are important for much contemporary science and industry. Within applications such as climate science and astrophysics, the need to make decisions on the basis of computations with large and complex data have led to a renewed focus on the management of numerical uncertainty. We describe how several seminal classic numerical methods can be interpreted naturally as probabilistic inference. We then show that the probabilistic view suggests new algorithms that can flexibly be adapted to suit application specifics, while delivering improved empirical performance. We provide concrete illustrations of the benefits of probabilistic numeric algorithms on real scientific problems from astrometry and astronomical imaging, while highlighting open problems with these new algorithms. Finally, we describe how probabilistic numerical methods provide a coherent framework for identifying the uncertainty in calculations performed with a combination of numerical algorithms (e.g. both numerical optimizers and differential equation solvers), potentially allowing the diagnosis (and control) of error sources in computations.
Is probabilistic bias analysis approximately Bayesian?

PubMed Central

MacLehose, Richard F.; Gustafson, Paul

2011-01-01

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

PubMed

Strametz, R; Tannheimer, M; Rall, M

2017-02-01

Background: The fact that medical treatment is associated with errors has long been recognized. Based on the principle of "first do no harm", numerous efforts have since been made to prevent such errors or limit their impact. However, recent statistics show that these measures do not sufficiently prevent grave mistakes with serious consequences. Preventable mistakes such as wrong patient or wrong site surgery still frequently occur in error statistics. Methods: Based on insight from research on human error, in due consideration of recent legislative regulations in Germany, the authors give an overview of the clinical risk management tools needed to identify risks in surgery, analyse their causes, and determine adequate measures to manage those risks depending on their relevance. The use and limitations of critical incident reporting systems (CIRS), safety checklists and crisis resource management (CRM) are highlighted. Also the rationale for IT systems to support the risk management process is addressed. Results/Conclusion: No single tool of risk management can be effective as a standalone instrument, but unfolds its effect only when embedded in a superordinate risk management system, which integrates tailor-made elements to increase patient safety into the workflows of each organisation. Competence in choosing adequate tools, effective IT systems to support the risk management process as well as leadership and commitment to constructive handling of human error are crucial components to establish a safety culture in surgery. Georg Thieme Verlag KG Stuttgart · New York.
Probabilistic Weather Information Tailored to the Needs of Transmission System Operators

NASA Astrophysics Data System (ADS)

Alberts, I.; Stauch, V.; Lee, D.; Hagedorn, R.

2014-12-01

Reliable and accurate forecasts for wind and photovoltaic (PV) power production are essential for stable transmission systems. A high potential for improving the wind and PV power forecasts lies in optimizing the weather forecasts, since these energy sources are highly weather dependent. For this reason the main objective of the German research project EWeLiNE is to improve the quality the underlying numerical weather predictions towards energy operations. In this project, the German Meteorological Service (DWD), the Fraunhofer Institute for Wind Energy and Energy System Technology, and three of the German transmission system operators (TSOs) are working together to improve the weather and power forecasts. Probabilistic predictions are of particular interest, as the quantification of uncertainties provides an important tool for risk management. Theoretical considerations suggest that it can be advantageous to use probabilistic information to represent and respond to the remaining uncertainties in the forecasts. However, it remains a challenge to integrate this information into the decision making processes related to market participation and power systems operations. The project is planned and carried out in close cooperation with the involved TSOs in order to ensure the usability of the products developed. It will conclude with a demonstration phase, in which the improved models and newly developed products are combined into a process chain and used to provide information to TSOs in a real-time decision support tool. The use of a web-based development platform enables short development cycles and agile adaptation to evolving user needs. This contribution will present the EWeLiNE project and discuss ideas on how to incorporate probabilistic information into the users' current decision making processes.
Probabilistic health risk assessment for ingestion of seafood farmed in arsenic contaminated groundwater in Taiwan.

PubMed

Liang, Ching-Ping; Jang, Cheng-Shin; Chen, Jui-Sheng; Wang, Sheng-Wei; Lee, Jin-Jing; Liu, Chen-Wuing

2013-08-01

Seafood farmed in arsenic (As)-contaminated areas is a major exposure pathway for the ingestion of inorganic As by individuals in the southwestern part of Taiwan. This study presents a probabilistic risk assessment using limited data for inorganic As intake through the consumption of the seafood by local residents in these areas. The As content and the consumption rate are both treated as probability distributions, taking into account the variability of the amount in the seafood and individual consumption habits. The Monte Carlo simulation technique is utilized to conduct an assessment of exposure due to the daily intake of inorganic As from As-contaminated seafood. Exposure is evaluated according to the provisional tolerable weekly intake (PTWI) established by the FAO/WHO and the target risk based on the US Environmental Protection Agency guidelines. The assessment results show that inorganic As intake from five types of fish (excluding mullet) and shellfish fall below the PTWI threshold values for the 95th percentiles, but exceed the target cancer risk of 10(-6). The predicted 95th percentile for inorganic As intake and lifetime cancer risks obtained in the study are both markedly higher than those obtained in previous studies in which the consumption rate of seafood considered is a deterministic value. This study demonstrates the importance of the individual variability of seafood consumption when evaluating a high exposure sub-group of the population who eat higher amounts of fish and shellfish than the average Taiwanese.
Surveying perceptions of landslide risk management in Norway

NASA Astrophysics Data System (ADS)

Chiu, Jessica Ka Yi; Eidsvig, Unni

2016-04-01

Enhanced precipitation due to climate change leads to increase in both frequency and intensity of landslides in Norway. A proactive approach to risk management is therefore required to significantly reduce the losses associated with landslides. Opinions and perceptions from practitioners on the performance of landslide risk management can provide insights on areas for improvement in the landslide risk management strategies in Norway. The Risk Management Index (RMI), proposed by Cardona et al. (2004), is a well-established method to measure perceptions of disaster management of selected actors holistically. The RMI is measured based on opinion questionnaires to technical staff, decision-makers, and stakeholders involved in all stages of risk reduction strategies. It is a composite index that considers a wide variety of strategies to manage risks, including structural and non-structural measures, acceptance strategies, disaster management, and risk transfer. The RMI method was modified to be implemented in landslide hazards and to fit with Norwegian conditions. An opinion survey was conducted in autumn 2015 to measure perceptions of landslide risk management in Norway. Perceptions were surveyed for two time periods: 2015 and 2050, and are based on national, county, and municipality levels. Based on the survey results, performance of landslide risk management at any administrative levels in Norway is perceived to improve from `significant' in 2015 to `significant' to `outstanding' in 2050. Knowledge and technology, climate, risk perceptions, and anthropogenic activities are mostly considered by respondents for their 2050 perceptions. Several aspects of landslide risk management in Norway can be improved. For example, landslide hazard evaluation and mapping should be prioritised in Norway. Upgrading, retrofitting, and reconstruction of assets may also be included in the landslide risk reduction strategies. In addition, there should be more focus on inter
Surrogate modeling of joint flood risk across coastal watersheds

NASA Astrophysics Data System (ADS)

Bass, Benjamin; Bedient, Philip

2018-03-01

This study discusses the development and performance of a rapid prediction system capable of representing the joint rainfall-runoff and storm surge flood response of tropical cyclones (TCs) for probabilistic risk analysis. Due to the computational demand required for accurately representing storm surge with the high-fidelity ADvanced CIRCulation (ADCIRC) hydrodynamic model and its coupling with additional numerical models to represent rainfall-runoff, a surrogate or statistical model was trained to represent the relationship between hurricane wind- and pressure-field characteristics and their peak joint flood response typically determined from physics based numerical models. This builds upon past studies that have only evaluated surrogate models for predicting peak surge, and provides the first system capable of probabilistically representing joint flood levels from TCs. The utility of this joint flood prediction system is then demonstrated by improving upon probabilistic TC flood risk products, which currently account for storm surge but do not take into account TC associated rainfall-runoff. Results demonstrate the source apportionment of rainfall-runoff versus storm surge and highlight that slight increases in flood risk levels may occur due to the interaction between rainfall-runoff and storm surge as compared to the Federal Emergency Management Association's (FEMAs) current practices.
Management of groundwater in farmed pond area using risk-based regulation.

PubMed

Huang, Jun-Ying; Liao, Chiao-Miao; Lin, Kao-Hung; Lee, Cheng-Haw

2014-09-01

Blackfoot disease (BFD) had occurred seriously in the Yichu, Hsuehchia, Putai, and Peimen townships of Chia-Nan District of Taiwan in the early days. These four townships are the districts of fishpond cultivation domestically in Taiwan. Groundwater becomes the main water supply because of short income in surface water. The problems of over pumping in groundwater may not only result in land subsidence and seawater intrusion but also be harmful to the health of human giving rise to the bioaccumulation via food chain in groundwater with arsenic (As). This research uses sequential indicator simulation (SIS) to characterize the spatial arsenic distribution in groundwater in the four townships. Risk assessment is applied to explore the dilution ratio (DR) of groundwater utilization, which is defined as the ratio showing the volume of groundwater utilization compared to pond water, for fish farming in the range of target cancer risk (TR) especially on the magnitude of 10(-4)~10(-6). Our study results reveal that the 50th percentile of groundwater DRs served as a regulation standard can be used to perform fish farm groundwater management for a TR of 10(-6). For a TR of 5 × 10(-6), we suggest using the 75th percentile of DR for groundwater management. For a TR of 10(-5), we suggest using the 95th percentile of the DR standard for performing groundwater management in fish farm areas. For the TR of exceeding 5 × 10(-5), we do not suggest establishing groundwater management standards under these risk standards. Based on the research results, we suggest that establishing a TR at 10(-5) and using the 95th percentile of DR are best for groundwater management in fish farm areas.
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.
A Framework for Drought Risk Management

NASA Astrophysics Data System (ADS)

Apurv, T.; Cai, X.

2016-12-01

Drought is one of the most expensive natural disasters as it affects many sectors of the economy. The threat posed by droughts is expected to further increase due to increasing water demands fuelled by increasing population and also due to climate change in many regions. Management of the increasing drought risk requires shift from traditional crisis management approaches to long term strategic planning for reduction of drought risk. This study proposes a framework for management of long term drought risk. The framework uses the system based approach proposed by Tsakiris et al. (2013), in which a watershed is considered as a system and different water sources in the watershed (like groundwater, reservoirs, streams etc.) are considered as subsystems associated with certain water requirements of different sectors. Droughts are defined separately for each subsystem considering water availability and requirement. The percentile based drought indicator framework proposed by Steinemann et al. (2015) is used for defining drought for each subsystem, allowing the selection of thresholds, variables of interest, and time scale which are most relevant for stakeholders dependent on a particular subsystem. Future drought risk under different drought management strategies are assessed using hydrologic models that model both hydrologic and human components of a watershed. The robustness of a management strategy is assessed by simulating system response across a wide range of stochastically generated future climate scenarios. The framework is useful for operational drought management as it allows direct management of drought risks with consideration of different water sources and water users. Steinemann, A., Iacobellis, S.F., Cayan, D.R., (2015) "Developing and evaluating drought indicators for decision-making" J. Hydrometeor. 16 (4), 1793-1803 Tsakiris, G, Nalbantis, I, Vangelis, H, Verbeiren, B, Huysmans, M, Tychon, B, Jacquemin, I, Canters, F, Vanderhaegen, S, Engelen, G
The Diagnostic Challenge Competition: Probabilistic Techniques for Fault Diagnosis in Electrical Power Systems

NASA Technical Reports Server (NTRS)

Ricks, Brian W.; Mengshoel, Ole J.

2009-01-01

Reliable systems health management is an important research area of NASA. A health management system that can accurately and quickly diagnose faults in various on-board systems of a vehicle will play a key role in the success of current and future NASA missions. We introduce in this paper the ProDiagnose algorithm, a diagnostic algorithm that uses a probabilistic approach, accomplished with Bayesian Network models compiled to Arithmetic Circuits, to diagnose these systems. We describe the ProDiagnose algorithm, how it works, and the probabilistic models involved. We show by experimentation on two Electrical Power Systems based on the ADAPT testbed, used in the Diagnostic Challenge Competition (DX 09), that ProDiagnose can produce results with over 96% accuracy and less than 1 second mean diagnostic time.
Probabilistic Risk Analysis of Groundwater Related Problems in Subterranean Excavation Sites

NASA Astrophysics Data System (ADS)

Sanchez-Vila, X.; Jurado, A.; de Gaspari, F.; Vilarrasa, V.; Bolster, D.; Fernandez-Garcia, D.; Tartakovsky, D. M.

2009-12-01

Construction of subterranean excavations in densely populated areas is inherently hazardous. The number of construction sites (e.g., subway lines, railways and highway tunnels) has increased in recent years. These sites can pose risks to workers at the site as well as cause damage to surrounding buildings. The presence of groundwater makes the excavation even more complicated. We develop a probabilistic risk assessment (PRA) model o estimate the likelihood of occurrence of certain risks during a subway station construction. While PRA is widely used in many engineering fields, its applications to the underground constructions in general and to an underground station construction in particular are scarce if not nonexistent. This method enables us not only to evaluate the probability of failure, but also to quantify the uncertainty of the different events considered. The risk analysis was carried out using a fault tree analysis that made it possible to study a complex system in a structured and straightforward manner. As an example we consider an underground station for the new subway line in the Barcelona metropolitan area (Línia 9) through the town of Prat de Llobregat in the Llobregat River Delta, which is currently under development. A typical station on the L9 line lies partially between the shallow and the main aquifer. Specifically, it is located in the middle layer which is made up of silts and clays. By presenting this example we aim to illustrate PRA as an effective methodology for estimating and minimising risks and to demonstrate its utility as a potential tool for decision making.
Analysis and probabilistic risk assessment of bioaccessible arsenic in polished and husked jasmine rice sold in Bangkok.

PubMed

Hensawang, Supanad; Chanpiwat, Penradee

2018-09-01

Food is one of the major sources of arsenic (As) exposure in humans. The objectives of this study were to determine the bioaccessible concentration of As in rice grain sold in Bangkok and to evaluate the potential health risks associated with rice consumption. Polished (n = 32) and husked (n = 17) jasmine rice were collected from local markets. In vitro digestion was performed to determine the bioaccessible As concentrations, which were used for probabilistic health risk assessments in different age groups of the population. Approximately 43.0% and 44.4% of the total As in the grain of polished and husked rice, respectively, was in the form of bioaccessible As. Significantly higher bioaccessible As concentrations were found in husked rice than in polished rice (1.5-3.8 times greater). The concentrations of bioaccessible As in polished and husked rice were lower than the Codex standard for As in rice. The average daily dose of As via rice consumption is equivalent to the daily ingestion of 2 L of water containing approximately 3.2-7.2 μg L -1 of As. Approximately 0.2%-13.7% and 10.7%-55.3% of the population may experience non-carcinogenic effects from polished and husked rice consumption, respectively. Approximately 1%-11.6% of children and 74.1%-99.8% of adults were at risk of cancer. The maximum cancer probabilities were 3 children and 6 adults in 10,000 individuals. The probabilistic risk results indicated that children and adults were at risk of both non-carcinogenic and carcinogenic effects from both types of rice consumption. Copyright © 2018 Elsevier Ltd. All rights reserved.
Recent developments of the NESSUS probabilistic structural analysis computer program

NASA Technical Reports Server (NTRS)

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

1992-01-01

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

PubMed

Moreno-Ortega, Alicia; Moreno-Rojas, Rafael; Martínez-Álvarez, Jesús Román; González Estecha, Montserrat; Castro González, Numa Pompilio; Amaro López, Manuel Ángel

2017-09-01

In Spain, recently, the public institutions have given information to the population in relation to fish consumption and the risk that it poses to health from the ingestion of mercury supposedly contained in the fish. At the same time, several scientific societies have published various works in this direction. All this without there being, up to now, any study on the evaluation of a probabilistic risk from mercury due to fish and seafood intake in Spain, which is the objective of this present work. For that purpose, we took individual data from a survey of the total diet of 3000 people, whose consumption of the principal fish and seafood species (49) was estimated. We compiled individualized data (2000) on the total mercury content of those species, which were completed and validated with bibliographic statistical data. After estimating the distributions of each fish and seafood species, both of their consumption and their mercury content, a simulation was made of the distribution of mercury ingestion from fish and seafood offered by 2.6% of the Spanish population at risk of exceeding total mercury recommendations, and between 12.2% and 21.2% of those exceeding methylmercury ones. The main species responsible were tuna fish, swordfish and hake, and significant differences were identified in fish consumption between sexes and ages, although, in the risk percentage, what stands out is an increase in the latter with an increase in age. Copyright © 2017 Elsevier GmbH. All rights reserved.
Seizure risk with AVM treatment or conservative management: prospective, population-based study.

PubMed

Josephson, Colin B; Bhattacharya, Jo J; Counsell, Carl E; Papanastassiou, Vakis; Ritchie, Vaughn; Roberts, Richard; Sellar, Robin; Warlow, Charles P; Al-Shahi Salman, Rustam

2012-08-07

To compare the risk of epileptic seizures in adults during conservative management or following invasive treatment for a brain arteriovenous malformation (AVM). We used annual general practitioner follow-up, patient questionnaires, and medical records surveillance to quantify the 5-year risk of seizures and the chances of achieving 2-year seizure freedom for adults undergoing AVM treatment compared to adults managed conservatively in a prospective, population-based observational study of adults in Scotland, newly diagnosed with an AVM in 1999-2003. We identified 229 adults with a new diagnosis of an AVM, of whom two-thirds received AVM treatment (154/229; 67%) during 1,862 person-years of follow-up (median completeness of follow-up 97%). There was no significant difference in the proportions with a first or recurrent seizure over 5 years following AVM treatment, compared to the first 5 years following clinical presentation in conservatively managed adults, in analyses stratified by mode of presentation (intracerebral hemorrhage, 35% vs 26%, p = 0.5; seizure, 67% vs 72%, p = 0.6; incidental, 21% vs 10%, p = 0.4). For patients with epilepsy, the chances of achieving 2-year seizure freedom during 5-year follow-up were similar following AVM treatment (n = 39; 52%, 95% confidence interval [CI] 36% to 68%) or conservative management (n = 21; 57%, 95% CI 35% to 79%; p = 0.7). In this observational study, there was no difference in the 5-year risk of seizures with AVM treatment or conservative management, irrespective of whether the AVM had presented with hemorrhage or epileptic seizures.
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.
Error Discounting in Probabilistic Category Learning

PubMed Central

Craig, Stewart; Lewandowsky, Stephan; Little, Daniel R.

2011-01-01

Some current theories of probabilistic categorization assume that people gradually attenuate their learning in response to unavoidable error. However, existing evidence for this error discounting is sparse and open to alternative interpretations. We report two probabilistic-categorization experiments that investigated error discounting by shifting feedback probabilities to new values after different amounts of training. In both experiments, responding gradually became less responsive to errors, and learning was slowed for some time after the feedback shift. Both results are indicative of error discounting. Quantitative modeling of the data revealed that adding a mechanism for error discounting significantly improved the fits of an exemplar-based and a rule-based associative learning model, as well as of a recency-based model of categorization. We conclude that error discounting is an important component of probabilistic learning. PMID:21355666
Probabilistic modelling of drought events in China via 2-dimensional joint copula

NASA Astrophysics Data System (ADS)

Ayantobo, Olusola O.; Li, Yi; Song, Songbai; Javed, Tehseen; Yao, Ning

2018-04-01

Probabilistic modelling of drought events is a significant aspect of water resources management and planning. In this study, popularly applied and several relatively new bivariate Archimedean copulas were employed to derive regional and spatial based copula models to appraise drought risk in mainland China over 1961-2013. Drought duration (Dd), severity (Ds), and peak (Dp), as indicated by Standardized Precipitation Evapotranspiration Index (SPEI), were extracted according to the run theory and fitted with suitable marginal distributions. The maximum likelihood estimation (MLE) and curve fitting method (CFM) were used to estimate the copula parameters of nineteen bivariate Archimedean copulas. Drought probabilities and return periods were analysed based on appropriate bivariate copula in sub-region I-VII and entire mainland China. The goodness-of-fit tests as indicated by the CFM showed that copula NN19 in sub-regions III, IV, V, VI and mainland China, NN20 in sub-region I and NN13 in sub-region VII are the best for modeling drought variables. Bivariate drought probability across mainland China is relatively high, and the highest drought probabilities are found mainly in the Northwestern and Southwestern China. Besides, the result also showed that different sub-regions might suffer varying drought risks. The drought risks as observed in Sub-region III, VI and VII, are significantly greater than other sub-regions. Higher probability of droughts of longer durations in the sub-regions also corresponds to shorter return periods with greater drought severity. These results may imply tremendous challenges for the water resources management in different sub-regions, particularly the Northwestern and Southwestern China.
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.

Probabilistic drug connectivity mapping

PubMed Central

2014-01-01

Background The aim of connectivity mapping is to match drugs using drug-treatment gene expression profiles from multiple cell lines. This can be viewed as an information retrieval task, with the goal of finding the most relevant profiles for a given query drug. We infer the relevance for retrieval by data-driven probabilistic modeling of the drug responses, resulting in probabilistic connectivity mapping, and further consider the available cell lines as different data sources. We use a special type of probabilistic model to separate what is shared and specific between the sources, in contrast to earlier connectivity mapping methods that have intentionally aggregated all available data, neglecting information about the differences between the cell lines. Results We show that the probabilistic multi-source connectivity mapping method is superior to alternatives in finding functionally and chemically similar drugs from the Connectivity Map data set. We also demonstrate that an extension of the method is capable of retrieving combinations of drugs that match different relevant parts of the query drug response profile. Conclusions The probabilistic modeling-based connectivity mapping method provides a promising alternative to earlier methods. Principled integration of data from different cell lines helps to identify relevant responses for specific drug repositioning applications. PMID:24742351
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.
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.
An agent based architecture for high-risk neonate management at neonatal intensive care unit.

PubMed

Malak, Jaleh Shoshtarian; Safdari, Reza; Zeraati, Hojjat; Nayeri, Fatemeh Sadat; Mohammadzadeh, Niloofar; Farajollah, Seide Sedighe Seied

2018-01-01

In recent years, the use of new tools and technologies has decreased the neonatal mortality rate. Despite the positive effect of using these technologies, the decisions are complex and uncertain in critical conditions when the neonate is preterm or has a low birth weight or malformations. There is a need to automate the high-risk neonate management process by creating real-time and more precise decision support tools. To create a collaborative and real-time environment to manage neonates with critical conditions at the NICU (Neonatal Intensive Care Unit) and to overcome high-risk neonate management weaknesses by applying a multi agent based analysis and design methodology as a new solution for NICU management. This study was a basic research for medical informatics method development that was carried out in 2017. The requirement analysis was done by reviewing articles on NICU Decision Support Systems. PubMed, Science Direct, and IEEE databases were searched. Only English articles published after 1990 were included; also, a needs assessment was done by reviewing the extracted features and current processes at the NICU environment where the research was conducted. We analyzed the requirements and identified the main system roles (agents) and interactions by a comparative study of existing NICU decision support systems. The Universal Multi Agent Platform (UMAP) was applied to implement a prototype of our multi agent based high-risk neonate management architecture. Local environment agents interacted inside a container and each container interacted with external resources, including other NICU systems and consultation centers. In the NICU container, the main identified agents were reception, monitoring, NICU registry, and outcome prediction, which interacted with human agents including nurses and physicians. Managing patients at the NICU units requires online data collection, real-time collaboration, and management of many components. Multi agent systems are applied as
FlySec: a risk-based airport security management system based on security as a service concept

NASA Astrophysics Data System (ADS)

Kyriazanos, Dimitris M.; Segou, Olga E.; Zalonis, Andreas; Thomopoulos, Stelios C. A.

2016-05-01

Complementing the ACI/IATA efforts, the FLYSEC European H2020 Research and Innovation project (http://www.fly-sec.eu/) aims to develop and demonstrate an innovative, integrated and end-to-end airport security process for passengers, enabling a guided and streamlined procedure from the landside to airside and into the boarding gates, and offering for an operationally validated innovative concept for end-to-end aviation security. FLYSEC ambition turns through a well-structured work plan into: (i) innovative processes facilitating risk-based screening; (ii) deployment and integration of new technologies and repurposing existing solutions towards a risk-based Security paradigm shift; (iii) improvement of passenger facilitation and customer service, bringing security as a real service in the airport of tomorrow;(iv) achievement of measurable throughput improvement and a whole new level of Quality of Service; and (v) validation of the results through advanced "in-vitro" simulation and "in-vivo" pilots. On the technical side, FLYSEC achieves its ambitious goals by integrating new technologies on video surveillance, intelligent remote image processing and biometrics combined with big data analysis, open-source intelligence and crowdsourcing. Repurposing existing technologies is also in the FLYSEC objectives, such as mobile application technologies for improved passenger experience and positive boarding applications (i.e. services to facilitate boarding and landside/airside way finding) as well as RFID for carry-on luggage tracking and quick unattended luggage handling. In this paper, the authors will describe the risk based airport security management system which powers FLYSEC intelligence and serves as the backend on top of which FLYSEC's front end technologies reside for security services management, behaviour and risk analysis.
Risk Management Implementation Tool

NASA Technical Reports Server (NTRS)

Wright, Shayla L.

2004-01-01

Continuous Risk Management (CM) is a software engineering practice with processes, methods, and tools for managing risk in a project. It provides a controlled environment for practical decision making, in order to assess continually what could go wrong, determine which risk are important to deal with, implement strategies to deal with those risk and assure the measure effectiveness of the implemented strategies. Continuous Risk Management provides many training workshops and courses to teach the staff how to implement risk management to their various experiments and projects. The steps of the CRM process are identification, analysis, planning, tracking, and control. These steps and the various methods and tools that go along with them, identification, and dealing with risk is clear-cut. The office that I worked in was the Risk Management Office (RMO). The RMO at NASA works hard to uphold NASA s mission of exploration and advancement of scientific knowledge and technology by defining and reducing program risk. The RMO is one of the divisions that fall under the Safety and Assurance Directorate (SAAD). I worked under Cynthia Calhoun, Flight Software Systems Engineer. My task was to develop a help screen for the Continuous Risk Management Implementation Tool (RMIT). The Risk Management Implementation Tool will be used by many NASA managers to identify, analyze, track, control, and communicate risks in their programs and projects. The RMIT will provide a means for NASA to continuously assess risks. The goals and purposes for this tool is to provide a simple means to manage risks, be used by program and project managers throughout NASA for managing risk, and to take an aggressive approach to advertise and advocate the use of RMIT at each NASA center.
Research on Risk Management and Power Supplying Enterprise Control

NASA Astrophysics Data System (ADS)

Shen, Jianfei; Wang, Yige

2017-09-01

This paper derived from the background that electric power enterprises strengthen their risk management under requirements of the government. For the power industry, we explained the risk management theory, analysed current macro environment as well as basic situation, then classified and interpreted the main risks. In a case study on a power bureau, we established a risk management system based on deep understanding about the characteristics of its organization system and risk management function. Then, we focused on risks in operation as well as incorrupt government construction to give a more effective framework of the risk management system. Finally, we came up with the problems and specific countermeasures in risk management, which provided a reference for other electric power enterprises.
Probabilistic Risk Assessment of Hydraulic Fracturing in Unconventional Reservoirs by Means of Fault Tree Analysis: An Initial Discussion

NASA Astrophysics Data System (ADS)

Rodak, C. M.; McHugh, R.; Wei, X.

2016-12-01

The development and combination of horizontal drilling and hydraulic fracturing has unlocked unconventional hydrocarbon reserves around the globe. These advances have triggered a number of concerns regarding aquifer contamination and over-exploitation, leading to scientific studies investigating potential risks posed by directional hydraulic fracturing activities. These studies, balanced with potential economic benefits of energy production, are a crucial source of information for communities considering the development of unconventional reservoirs. However, probabilistic quantification of the overall risk posed by hydraulic fracturing at the system level are rare. Here we present the concept of fault tree analysis to determine the overall probability of groundwater contamination or over-exploitation, broadly referred to as the probability of failure. The potential utility of fault tree analysis for the quantification and communication of risks is approached with a general application. However, the fault tree design is robust and can handle various combinations of regional-specific data pertaining to relevant spatial scales, geological conditions, and industry practices where available. All available data are grouped into quantity and quality-based impacts and sub-divided based on the stage of the hydraulic fracturing process in which the data is relevant as described by the USEPA. Each stage is broken down into the unique basic events required for failure; for example, to quantify the risk of an on-site spill we must consider the likelihood, magnitude, composition, and subsurface transport of the spill. The structure of the fault tree described above can be used to render a highly complex system of variables into a straightforward equation for risk calculation based on Boolean logic. This project shows the utility of fault tree analysis for the visual communication of the potential risks of hydraulic fracturing activities on groundwater resources.
Probabilistic estimation of residential air exchange rates for population-based human exposure modeling

EPA Science Inventory

Residential air exchange rates (AERs) are a key determinant in the infiltration of ambient air pollution indoors. Population-based human exposure models using probabilistic approaches to estimate personal exposure to air pollutants have relied on input distributions from AER meas...
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.
Risk assessment for enterprise resource planning (ERP) system implementations: a fault tree analysis approach

NASA Astrophysics Data System (ADS)

Zeng, Yajun; Skibniewski, Miroslaw J.

2013-08-01

Enterprise resource planning (ERP) system implementations are often characterised with large capital outlay, long implementation duration, and high risk of failure. In order to avoid ERP implementation failure and realise the benefits of the system, sound risk management is the key. This paper proposes a probabilistic risk assessment approach for ERP system implementation projects based on fault tree analysis, which models the relationship between ERP system components and specific risk factors. Unlike traditional risk management approaches that have been mostly focused on meeting project budget and schedule objectives, the proposed approach intends to address the risks that may cause ERP system usage failure. The approach can be used to identify the root causes of ERP system implementation usage failure and quantify the impact of critical component failures or critical risk events in the implementation process.
Managing the risks of disease transmission through trade: a commodities-based approach?

PubMed

Brückner, G K

2011-04-01

Since its founding in 1924, the World Organisation for Animal Health (OIE) has facilitated safe trade in animals and animal products by developing effective standards to prevent the spread of animal diseases across the globe. A protocol for recognising the disease-free status of countries is an integral part of this process and has been adopted and advanced through the years to assist OIE Member Countries in placing disease-free animals and their products on the international market. Options such as trade from disease-free zones and disease-free compartments are now available to Members and have proven to be a positive mechanism for facilitating trade. A further option is trading in safe commodities, i.e. animals and animal products that have been identified as safe to trade even in the presence of disease, either with or without applying risk mitigation measures before export. Although most Members have incorporated the acceptance of disease-free countries or zones into their animal health policies and sanitary measures, there still appears to be a reluctance to trade in commodities from infected countries, despite clear, scientifically based risk management standards that can be applied if needed. This paper offers some examples reflecting the apparent reluctance to trade in commodities and discusses how the standards in the OIE's Terrestrial Animal Health Code could be used to apply scientifically based risk management practices to review outdated policies.
Selecting Statistical Procedures for Quality Control Planning Based on Risk Management.

PubMed

Yago, Martín; Alcover, Silvia

2016-07-01

According to the traditional approach to statistical QC planning, the performance of QC procedures is assessed in terms of its probability of rejecting an analytical run that contains critical size errors (PEDC). Recently, the maximum expected increase in the number of unacceptable patient results reported during the presence of an undetected out-of-control error condition [Max E(NUF)], has been proposed as an alternative QC performance measure because it is more related to the current introduction of risk management concepts for QC planning in the clinical laboratory. We used a statistical model to investigate the relationship between PEDC and Max E(NUF) for simple QC procedures widely used in clinical laboratories and to construct charts relating Max E(NUF) with the capability of the analytical process that allow for QC planning based on the risk of harm to a patient due to the report of erroneous results. A QC procedure shows nearly the same Max E(NUF) value when used for controlling analytical processes with the same capability, and there is a close relationship between PEDC and Max E(NUF) for simple QC procedures; therefore, the value of PEDC can be estimated from the value of Max E(NUF) and vice versa. QC procedures selected by their high PEDC value are also characterized by a low value for Max E(NUF). The PEDC value can be used for estimating the probability of patient harm, allowing for the selection of appropriate QC procedures in QC planning based on risk management. © 2016 American Association for Clinical Chemistry.
Biosimilars: pharmacovigilance and risk management.

PubMed

Zuñiga, Leyre; Calvo, Begoña

2010-07-01

Biosimilars cannot be authorized based on the same requirements that apply to generic medicines. Despite the fact that the biosimilar and reference drug can show similar efficacy, the biosimilar may exhibit different safety profile in terms of nature, seriousness or incidence of adverse reactions. However, the data from pre-authorization clinical studies normally are insufficient to identify all potential differences. Therefore, clinical safety of similar biological medicinal products must be monitored closely on an ongoing basis during the post-approval phase including continued risk-benefit assessment. The biosimilar applicant must provide the European Medicines Agency (EMEA) with a risk management plan (EU-RMP) and pharmacovigilance programme with its application, including a description of the potential safety issues associated with the similar biological medicinal product that may be a result of differences in the manufacturing process from the reference biologic. The most critical safety concern relating to biopharmaceuticals (including biosimilars) is immunogenicity. Risk management applies scientifically based methodologies to identify, assess, communicate and minimise risk throughout a drug's life cycle so as to establish and maintain a favourable benefit-risk profile in patients. The risk management plan for biosimilars should focus on heightens the pharmacovigilance measures, identify immunogenicity risk and implement special post-marketing surveillance. Although International Nonproprietary Names (INNs) served as a useful tool in worldwide pharmacovigilance, for biologicals they should not be relied upon as the only means of product identification. Biologicals should always be commercialized with a brand name or the INN plus the manufacturer's name. (c) 2010 John Wiley & Sons, Ltd.
Mental Health Professionals' Suicide Risk Assessment and Management Practices.

PubMed

Roush, Jared F; Brown, Sarah L; Jahn, Danielle R; Mitchell, Sean M; Taylor, Nathanael J; Quinnett, Paul; Ries, Richard

2018-01-01

Approximately 20% of suicide decedents have had contact with a mental health professional within 1 month prior to their death, and the majority of mental health professionals have treated suicidal individuals. Despite limited evidence-based training, mental health professionals make important clinical decisions related to suicide risk assessment and management. The current study aimed to determine the frequency of suicide risk assessment and management practices and the association between fear of suicide-related outcomes or comfort working with suicidal individuals and adequacy of suicide risk management decisions among mental health professionals. Mental health professionals completed self-report assessments of fear, comfort, and suicide risk assessment and management practices. Approximately one third of mental health professionals did not ask every patient about current or previous suicidal thoughts or behaviors. Further, comfort, but not fear, was positively associated with greater odds of conducting evidence-based suicide risk assessments at first appointments and adequacy of suicide risk management practices with patients reporting suicide ideation and a recent suicide attempt. The study utilized a cross-sectional design and self-report questionnaires. Although the majority of mental health professionals report using evidenced-based practices, there appears to be variability in utilization of evidence-based practices.
Heart failure disease management programs: a cost-effectiveness analysis.

PubMed

Chan, David C; Heidenreich, Paul A; Weinstein, Milton C; Fonarow, Gregg C

2008-02-01

Heart failure (HF) disease management programs have shown impressive reductions in hospitalizations and mortality, but in studies limited to short time frames and high-risk patient populations. Current guidelines thus only recommend disease management targeted to high-risk patients with HF. This study applied a new technique to infer the degree to which clinical trials have targeted patients by risk based on observed rates of hospitalization and death. A Markov model was used to assess the incremental life expectancy and cost of providing disease management for high-risk to low-risk patients. Sensitivity analyses of various long-term scenarios and of reduced effectiveness in low-risk patients were also considered. The incremental cost-effectiveness ratio of extending coverage to all patients was $9700 per life-year gained in the base case. In aggregate, universal coverage almost quadrupled life-years saved as compared to coverage of only the highest quintile of risk. A worst case analysis with simultaneous conservative assumptions yielded an incremental cost-effectiveness ratio of $110,000 per life-year gained. In a probabilistic sensitivity analysis, 99.74% of possible incremental cost-effectiveness ratios were <$50,000 per life-year gained. Heart failure disease management programs are likely cost-effective in the long-term along the whole spectrum of patient risk. Health gains could be extended by enrolling a broader group of patients with HF in disease management.
Risk Management in EVA

NASA Technical Reports Server (NTRS)

Hall, Jonathan; Lutomski, M.

2006-01-01

This viewgraph presentation reviews the use of risk management in Extravehicular Activities (EVA). The contents include: 1) EVA Office at NASA - JSC; 2) EVA Project Risk Management: Why and When; 3) EVA Office Risk Management: How; 4) Criteria for Closing a Risk; 5) Criteria for Accepting a Risk; 6) ISS IRMA Reference Card Data Entry Requirement s; 7) XA/ EVA Office Risk Activity Summary; 8) EVA Significant Change Summary; 9) Integrated Risk Management Application (XA) Matrix, March 31, 2004; 10) ISS Watch Item: 50XX Summary Report; and 11) EVA Project RM Usefulness
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.
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.
Building a high-resolution T2-weighted MR-based probabilistic model of tumor occurrence in the prostate.

PubMed

Nagarajan, Mahesh B; Raman, Steven S; Lo, Pechin; Lin, Wei-Chan; Khoshnoodi, Pooria; Sayre, James W; Ramakrishna, Bharath; Ahuja, Preeti; Huang, Jiaoti; Margolis, Daniel J A; Lu, David S K; Reiter, Robert E; Goldin, Jonathan G; Brown, Matthew S; Enzmann, Dieter R

2018-02-19

We present a method for generating a T2 MR-based probabilistic model of tumor occurrence in the prostate to guide the selection of anatomical sites for targeted biopsies and serve as a diagnostic tool to aid radiological evaluation of prostate cancer. In our study, the prostate and any radiological findings within were segmented retrospectively on 3D T2-weighted MR images of 266 subjects who underwent radical prostatectomy. Subsequent histopathological analysis determined both the ground truth and the Gleason grade of the tumors. A randomly chosen subset of 19 subjects was used to generate a multi-subject-derived prostate template. Subsequently, a cascading registration algorithm involving both affine and non-rigid B-spline transforms was used to register the prostate of every subject to the template. Corresponding transformation of radiological findings yielded a population-based probabilistic model of tumor occurrence. The quality of our probabilistic model building approach was statistically evaluated by measuring the proportion of correct placements of tumors in the prostate template, i.e., the number of tumors that maintained their anatomical location within the prostate after their transformation into the prostate template space. Probabilistic model built with tumors deemed clinically significant demonstrated a heterogeneous distribution of tumors, with higher likelihood of tumor occurrence at the mid-gland anterior transition zone and the base-to-mid-gland posterior peripheral zones. Of 250 MR lesions analyzed, 248 maintained their original anatomical location with respect to the prostate zones after transformation to the prostate. We present a robust method for generating a probabilistic model of tumor occurrence in the prostate that could aid clinical decision making, such as selection of anatomical sites for MR-guided prostate biopsies.

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.
Risk preferences, probability weighting, and strategy tradeoffs in wildfire management

Treesearch

Michael S. Hand; Matthew J. Wibbenmeyer; Dave Calkin; Matthew P. Thompson

2015-01-01

Wildfires present a complex applied risk management environment, but relatively little attention has been paid to behavioral and cognitive responses to risk among public agency wildfire managers. This study investigates responses to risk, including probability weighting and risk aversion, in a wildfire management context using a survey-based experiment administered to...
Why is Probabilistic Seismic Hazard Analysis (PSHA) still used?

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

Probabilistic Hazard Assessment (PHA) is becoming an essential tool for risk mitigation policies, since it allows to quantify the hazard due to hazardous phenomena and, differently from the deterministic approach, it accounts for both aleatory and epistemic uncertainties. On the other hand, one of the main disadvantages of PHA methods is that their results are not easy to understand and interpret by people who are not specialist in probabilistic tools. For scientists, this leads to the issue of providing tools that can be easily used and understood by decision makers (i.e., risk managers or local authorities). The work here presented fits into the problem of simplifying the transfer between scientific knowledge and land protection policies, by providing an interface between scientists, who produce PHA's results, and decision makers, who use PHA's results for risk analyses. In this framework we present pyPHaz, an open tool developed and designed to visualize and analyze PHA results due to one or more phenomena affecting a specific area of interest. The software implementation has been fully developed with the free and open-source Python programming language and some featured Python-based libraries and modules. The pyPHaz tool allows to visualize the Hazard Curves (HC) calculated in a selected target area together with different levels of uncertainty (mean and percentiles) on maps that can be interactively created and modified by the user, thanks to a dedicated Graphical User Interface (GUI). Moreover, the tool can be used to compare the results of different PHA models and to merge them, by creating ensemble models. The pyPHaz software has been designed with the features of storing and accessing all the data through a MySQL database and of being able to read as input the XML-based standard file formats defined in the frame of GEM (Global Earthquake Model). This format model is easy to extend also to any other kind of hazard, as it will be shown in the applications
Some Advances in Downscaling Probabilistic Climate Forecasts for Agricultural Decision Support

NASA Astrophysics Data System (ADS)

Han, E.; Ines, A.

2015-12-01

Seasonal climate forecasts, commonly provided in tercile-probabilities format (below-, near- and above-normal), need to be translated into more meaningful information for decision support of practitioners in agriculture. In this paper, we will present two new novel approaches to temporally downscale probabilistic seasonal climate forecasts: one non-parametric and another parametric method. First, the non-parametric downscaling approach called FResampler1 uses the concept of 'conditional block sampling' of weather data to create daily weather realizations of a tercile-based seasonal climate forecasts. FResampler1 randomly draws time series of daily weather parameters (e.g., rainfall, maximum and minimum temperature and solar radiation) from historical records, for the season of interest from years that belong to a certain rainfall tercile category (e.g., being below-, near- and above-normal). In this way, FResampler1 preserves the covariance between rainfall and other weather parameters as if conditionally sampling maximum and minimum temperature and solar radiation if that day is wet or dry. The second approach called predictWTD is a parametric method based on a conditional stochastic weather generator. The tercile-based seasonal climate forecast is converted into a theoretical forecast cumulative probability curve. Then the deviates for each percentile is converted into rainfall amount or frequency or intensity to downscale the 'full' distribution of probabilistic seasonal climate forecasts. Those seasonal deviates are then disaggregated on a monthly basis and used to constrain the downscaling of forecast realizations at different percentile values of the theoretical forecast curve. As well as the theoretical basis of the approaches we will discuss sensitivity analysis (length of data and size of samples) of them. In addition their potential applications for managing climate-related risks in agriculture will be shown through a couple of case studies based on
Risk-based cost-benefit analysis for evaluating microbial risk mitigation in a drinking water system.

PubMed

Bergion, Viktor; Lindhe, Andreas; Sokolova, Ekaterina; Rosén, Lars

2018-04-01

Waterborne outbreaks of gastrointestinal diseases can cause large costs to society. Risk management needs to be holistic and transparent in order to reduce these risks in an effective manner. Microbial risk mitigation measures in a drinking water system were investigated using a novel approach combining probabilistic risk assessment and cost-benefit analysis. Lake Vomb in Sweden was used to exemplify and illustrate the risk-based decision model. Four mitigation alternatives were compared, where the first three alternatives, A1-A3, represented connecting 25, 50 and 75%, respectively, of on-site wastewater treatment systems in the catchment to the municipal wastewater treatment plant. The fourth alternative, A4, represented installing a UV-disinfection unit in the drinking water treatment plant. Quantitative microbial risk assessment was used to estimate the positive health effects in terms of quality adjusted life years (QALYs), resulting from the four mitigation alternatives. The health benefits were monetised using a unit cost per QALY. For each mitigation alternative, the net present value of health and environmental benefits and investment, maintenance and running costs was calculated. The results showed that only A4 can reduce the risk (probability of infection) below the World Health Organization guidelines of 10 -4 infections per person per year (looking at the 95th percentile). Furthermore, all alternatives resulted in a negative net present value. However, the net present value would be positive (looking at the 50 th percentile using a 1% discount rate) if non-monetised benefits (e.g. increased property value divided evenly over the studied time horizon and reduced microbial risks posed to animals), estimated at 800-1200 SEK (€100-150) per connected on-site wastewater treatment system per year, were included. This risk-based decision model creates a robust and transparent decision support tool. It is flexible enough to be tailored and applied to local
An optimization-based approach for facility energy management with uncertainties, and, Power portfolio optimization in deregulated electricity markets with risk management

NASA Astrophysics Data System (ADS)

Xu, Jun

Topic 1. An Optimization-Based Approach for Facility Energy Management with Uncertainties. Effective energy management for facilities is becoming increasingly important in view of the rising energy costs, the government mandate on the reduction of energy consumption, and the human comfort requirements. This part of dissertation presents a daily energy management formulation and the corresponding solution methodology for HVAC systems. The problem is to minimize the energy and demand costs through the control of HVAC units while satisfying human comfort, system dynamics, load limit constraints, and other requirements. The problem is difficult in view of the fact that the system is nonlinear, time-varying, building-dependent, and uncertain; and that the direct control of a large number of HVAC components is difficult. In this work, HVAC setpoints are the control variables developed on top of a Direct Digital Control (DDC) system. A method that combines Lagrangian relaxation, neural networks, stochastic dynamic programming, and heuristics is developed to predict the system dynamics and uncontrollable load, and to optimize the setpoints. Numerical testing and prototype implementation results show that our method can effectively reduce total costs, manage uncertainties, and shed the load, is computationally efficient. Furthermore, it is significantly better than existing methods. Topic 2. Power Portfolio Optimization in Deregulated Electricity Markets with Risk Management. In a deregulated electric power system, multiple markets of different time scales exist with various power supply instruments. A load serving entity (LSE) has multiple choices from these instruments to meet its load obligations. In view of the large amount of power involved, the complex market structure, risks in such volatile markets, stringent constraints to be satisfied, and the long time horizon, a power portfolio optimization problem is of critical importance but difficulty for an LSE to serve the
Environmental risk assessment of white phosphorus from the use of munitions - a probabilistic approach.

PubMed

Voie, Øyvind Albert; Johnsen, Arnt; Strømseng, Arnljot; Longva, Kjetil Sager

2010-03-15

White phosphorus (P(4)) is a highly toxic compound used in various pyrotechnic products. Ammunitions containing P(4) are widely used in military training areas where the unburned products of P(4) contaminate soil and local ponds. Traditional risk assessment methods presuppose a homogeneous spatial distribution of pollutants. The distribution of P(4) in military training areas is heterogeneous, which reduces the probability of potential receptors being exposed to the P(4) by ingestion, for example. The current approach to assess the environmental risk from the use of P(4) suggests a Bayesian network (Bn) as a risk assessment tool. The probabilistic reasoning supported by a Bn allows us to take into account the heterogeneous distribution of P(4). Furthermore, one can combine empirical data and expert knowledge, which allows the inclusion of all kinds of data that are relevant to the problem. The current work includes an example of the use of the Bn as a risk assessment tool where the risk for P(4) poisoning in humans and grazing animals at a military shooting range in Northern Norway was calculated. P(4) was detected in several craters on the range at concentrations up to 5.7g/kg. The risk to human health was considered acceptable under the current land use. The risk for grazing animals such as sheep, however, was higher, suggesting that precautionary measures may be advisable.
Algebraic and Probabilistic Bases for Fuzzy Sets and the Development of Fuzzy Conditioning

DTIC Science & Technology

1991-08-01

results; and also recently, among others, Bruno & Gilio (1985) bringing forth the basic is- e of combining implicatives compatible with conditional...probabilistic bases for fuzzy sets 67 7. Bruno, G. & Gilio , A. (1985), Confronto fra eventi condizionati di probabililiti nulla nell’ inferenza statistica
ePORT, NASA's Computer Database Program for System Safety Risk Management Oversight (Electronic Project Online Risk Tool)

NASA Technical Reports Server (NTRS)

Johnson, Paul W.

2008-01-01

ePORT (electronic Project Online Risk Tool) provides a systematic approach to using an electronic database program to manage a program/project risk management processes. This presentation will briefly cover the standard risk management procedures, then thoroughly cover NASA's Risk Management tool called ePORT. This electronic Project Online Risk Tool (ePORT) is a web-based risk management program that provides a common framework to capture and manage risks, independent of a programs/projects size and budget. It is used to thoroughly cover the risk management paradigm providing standardized evaluation criterion for common management reporting, ePORT improves Product Line, Center and Corporate Management insight, simplifies program/project manager reporting, and maintains an archive of data for historical reference.
Application of Probabilistic Methods to Assess Risk Due to Resonance in the Design of J-2X Rocket Engine Turbine Blades

NASA Technical Reports Server (NTRS)

Brown, Andrew M.; DeHaye, Michael; DeLessio, Steven

2011-01-01

The LOX-Hydrogen J-2X Rocket Engine, which is proposed for use as an upper-stage engine for numerous earth-to-orbit and heavy lift launch vehicle architectures, is presently in the design phase and will move shortly to the initial development test phase. Analysis of the design has revealed numerous potential resonance issues with hardware in the turbomachinery turbine-side flow-path. The analysis of the fuel pump turbine blades requires particular care because resonant failure of the blades, which are rotating in excess of 30,000 revolutions/minutes (RPM), could be catastrophic for the engine and the entire launch vehicle. This paper describes a series of probabilistic analyses performed to assess the risk of failure of the turbine blades due to resonant vibration during past and present test series. Some significant results are that the probability of failure during a single complete engine hot-fire test is low (1%) because of the small likelihood of resonance, but that the probability increases to around 30% for a more focused turbomachinery-only test because all speeds will be ramped through and there is a greater likelihood of dwelling at more speeds. These risk calculations have been invaluable for use by program management in deciding if risk-reduction methods such as dampers are necessary immediately or if the test can be performed before the risk-reduction hardware is ready.
Probabilistic flood inundation mapping at ungauged streams due to roughness coefficient uncertainty in hydraulic modelling

NASA Astrophysics Data System (ADS)

Papaioannou, George; Vasiliades, Lampros; Loukas, Athanasios; Aronica, Giuseppe T.

2017-04-01

Probabilistic flood inundation mapping is performed and analysed at the ungauged Xerias stream reach, Volos, Greece. The study evaluates the uncertainty introduced by the roughness coefficient values on hydraulic models in flood inundation modelling and mapping. The well-established one-dimensional (1-D) hydraulic model, HEC-RAS is selected and linked to Monte-Carlo simulations of hydraulic roughness. Terrestrial Laser Scanner data have been used to produce a high quality DEM for input data uncertainty minimisation and to improve determination accuracy on stream channel topography required by the hydraulic model. Initial Manning's n roughness coefficient values are based on pebble count field surveys and empirical formulas. Various theoretical probability distributions are fitted and evaluated on their accuracy to represent the estimated roughness values. Finally, Latin Hypercube Sampling has been used for generation of different sets of Manning roughness values and flood inundation probability maps have been created with the use of Monte Carlo simulations. Historical flood extent data, from an extreme historical flash flood event, are used for validation of the method. The calibration process is based on a binary wet-dry reasoning with the use of Median Absolute Percentage Error evaluation metric. The results show that the proposed procedure supports probabilistic flood hazard mapping at ungauged rivers and provides water resources managers with valuable information for planning and implementing flood risk mitigation strategies.
Probabilistic objective functions for margin-less IMRT planning

NASA Astrophysics Data System (ADS)

Bohoslavsky, Román; Witte, Marnix G.; Janssen, Tomas M.; van Herk, Marcel

2013-06-01

We present a method to implement probabilistic treatment planning of intensity-modulated radiation therapy using custom software plugins in a commercial treatment planning system. Our method avoids the definition of safety-margins by directly including the effect of geometrical uncertainties during optimization when objective functions are evaluated. Because the shape of the resulting dose distribution implicitly defines the robustness of the plan, the optimizer has much more flexibility than with a margin-based approach. We expect that this added flexibility helps to automatically strike a better balance between target coverage and dose reduction for surrounding healthy tissue, especially for cases where the planning target volume overlaps organs at risk. Prostate cancer treatment planning was chosen to develop our method, including a novel technique to include rotational uncertainties. Based on population statistics, translations and rotations are simulated independently following a marker-based IGRT correction strategy. The effects of random and systematic errors are incorporated by first blurring and then shifting the dose distribution with respect to the clinical target volume. For simplicity and efficiency, dose-shift invariance and a rigid-body approximation are assumed. Three prostate cases were replanned using our probabilistic objective functions. To compare clinical and probabilistic plans, an evaluation tool was used that explicitly incorporates geometric uncertainties using Monte-Carlo methods. The new plans achieved similar or better dose distributions than the original clinical plans in terms of expected target coverage and rectum wall sparing. Plan optimization times were only about a factor of two higher than in the original clinical system. In conclusion, we have developed a practical planning tool that enables margin-less probability-based treatment planning with acceptable planning times, achieving the first system that is feasible for clinical
A screening level probabilistic ecological risk assessment of PAHs in sediments of San Francisco Bay

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

Febbo, E.J.; Arnold, W.R.; Biddinger, G.R.

1995-12-31

As part of the Regional Monitoring Program administered by the San Francisco Estuary Institute (SFEI), sediment samples were collected at 20 stations in San Francisco Bay and analyzed to determine concentrations of 43 PAHs. These data were obtained from SFEI and used to calculate the potential risk to aquatic organisms using probabilistic modeling and Monte Carlo statistical procedures. Sediment chemistry data were used in conjunction with a sediment equilibrium model, a bioconcentration model, biota-sediment accumulation factors, and critical body burden effects concentrations to assess potential risk to bivalves. Bivalves were the chosen receptors because they lack a well-developed enzymatic systemmore » for metabolizing PAHs. Thus, they more readily accumulate PAHs and represent a species at greater risk than other taxa, such as fish and crustaceans. PAHs considered in this study span a broad range of octanol-water partition coefficients. Results indicate that risk of non-polar narcotic effects from PAHs was low in the Northern Bay Area, but higher in the South Bay near the more urbanized sections of the drainage basin.« less
17 CFR 23.609 - Clearing member risk management.

Code of Federal Regulations, 2014 CFR

2014-04-01

... management. 23.609 Section 23.609 Commodity and Securities Exchanges COMMODITY FUTURES TRADING COMMISSION... Clearing member risk management. (a) With respect to clearing activities in futures, security futures...) Monitor for adherence to the risk-based limits intra-day and overnight; (4) Conduct stress tests under...
17 CFR 23.609 - Clearing member risk management.

Code of Federal Regulations, 2013 CFR

2013-04-01

... management. 23.609 Section 23.609 Commodity and Securities Exchanges COMMODITY FUTURES TRADING COMMISSION... Clearing member risk management. (a) With respect to clearing activities in futures, security futures...) Monitor for adherence to the risk-based limits intra-day and overnight; (4) Conduct stress tests under...
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
Cardiovascular risk management after reproductive and pregnancy-related disorders: A Dutch multidisciplinary evidence-based guideline.

PubMed

Heida, Karst Y; Bots, Michiel L; de Groot, Christianne Jm; van Dunné, Frederique M; Hammoud, Nurah M; Hoek, Annemiek; Laven, Joop Se; Maas, Angela Hem; Roeters van Lennep, Jeanine E; Velthuis, Birgitta K; Franx, Arie

2016-11-01

In the past decades evidence has accumulated that women with reproductive and pregnancy-related disorders are at increased risk of developing cardiovascular disease (CVD) in the future. Up to now there is no standardised follow-up of these women becausee guidelines on cardiovascular risk management for this group are lacking. However, early identification of high-risk populations followed by prevention and treatment of CVD risk factors has the potential to reduce CVD incidence. Therefore, the Dutch Society of Obstetrics and Gynaecology initiated a multidisciplinary working group to develop a guideline for cardiovascular risk management after reproductive and pregnancy-related disorders. The guideline addresses the cardiovascular risk consequences of gestational hypertension, preeclampsia, preterm delivery, small-for-gestational-age infant, recurrent miscarriage, polycystic ovary syndrome and premature ovarian insufficiency. The best available evidence on these topics was captured by systematic review. Recommendations for clinical practice were formulated based on the evidence and consensus of expert opinion. The Dutch societies of gynaecologists, cardiologists, vascular internists, radiologists and general practitioners reviewed the guideline to ensure support for implementation in clinical practice. For all reproductive and pregnancy-related disorders a moderate increased relative risk was found for overall CVD, except for preeclampsia (relative risk 2.15, 95% confidence interval 1.76-2.61). Based on the current available evidence, follow-up is only recommended for women with a history of preeclampsia. For all reproductive and pregnancy-related disorders optimisation of modifiable cardiovascular risk factors is recommended to reduce the risk of future CVD. © The European Society of Cardiology 2016.
PBPK-Based Probabilistic Risk Assessment for Total Chlorotriazines in Drinking Water

PubMed Central

Breckenridge, Charles B.; Campbell, Jerry L.; Clewell, Harvey J.; Andersen, Melvin E.; Valdez-Flores, Ciriaco; Sielken, Robert L.

2016-01-01

The risk of human exposure to total chlorotriazines (TCT) in drinking water was evaluated using a physiologically based pharmacokinetic (PBPK) model. Daily TCT (atrazine, deethylatrazine, deisopropylatrazine, and diaminochlorotriazine) chemographs were constructed for 17 frequently monitored community water systems (CWSs) using linear interpolation and Krieg estimates between observed TCT values. Synthetic chemographs were created using a conservative bias factor of 3 to generate intervening peaks between measured values. Drinking water consumption records from 24-h diaries were used to calculate daily exposure. Plasma TCT concentrations were updated every 30 minutes using the PBPK model output for each simulated calendar year from 2006 to 2010. Margins of exposure (MOEs) were calculated (MOE = [Human Plasma TCTPOD] ÷ [Human Plasma TCTEXP]) based on the toxicological point of departure (POD) and the drinking water-derived exposure to TCT. MOEs were determined based on 1, 2, 3, 4, 7, 14, 28, or 90 days of rolling average exposures and plasma TCT Cmax, or the area under the curve (AUC). Distributions of MOE were determined and the 99.9th percentile was used for risk assessment. MOEs for all 17 CWSs were >1000 at the 99.9th percentile. The 99.9th percentile of the MOE distribution was 2.8-fold less when the 3-fold synthetic chemograph bias factor was used. MOEs were insensitive to interpolation method, the consumer’s age, the water consumption database used and the duration of time over which the rolling average plasma TCT was calculated, for up to 90 days. MOEs were sensitive to factors that modified the toxicological, or hyphenated appropriately no-observed-effects level (NOEL), including rat strain, endpoint used, method of calculating the NOEL, and the pharmacokinetics of elimination, as well as the magnitude of exposure (CWS, calendar year, and use of bias factors). PMID:26794141
Reconstruction of metabolic pathways by combining probabilistic graphical model-based and knowledge-based methods

PubMed Central

2014-01-01

Automatic reconstruction of metabolic pathways for an organism from genomics and transcriptomics data has been a challenging and important problem in bioinformatics. Traditionally, known reference pathways can be mapped into an organism-specific ones based on its genome annotation and protein homology. However, this simple knowledge-based mapping method might produce incomplete pathways and generally cannot predict unknown new relations and reactions. In contrast, ab initio metabolic network construction methods can predict novel reactions and interactions, but its accuracy tends to be low leading to a lot of false positives. Here we combine existing pathway knowledge and a new ab initio Bayesian probabilistic graphical model together in a novel fashion to improve automatic reconstruction of metabolic networks. Specifically, we built a knowledge database containing known, individual gene / protein interactions and metabolic reactions extracted from existing reference pathways. Known reactions and interactions were then used as constraints for Bayesian network learning methods to predict metabolic pathways. Using individual reactions and interactions extracted from different pathways of many organisms to guide pathway construction is new and improves both the coverage and accuracy of metabolic pathway construction. We applied this probabilistic knowledge-based approach to construct the metabolic networks from yeast gene expression data and compared its results with 62 known metabolic networks in the KEGG database. The experiment showed that the method improved the coverage of metabolic network construction over the traditional reference pathway mapping method and was more accurate than pure ab initio methods. PMID:25374614

Methodology for Developing a Probabilistic Risk Assessment Model of Spacecraft Rendezvous and Dockings

NASA Technical Reports Server (NTRS)

Farnham, Steven J., II; Garza, Joel, Jr.; Castillo, Theresa M.; Lutomski, Michael

2011-01-01

In 2007 NASA was preparing to send two new visiting vehicles carrying logistics and propellant to the International Space Station (ISS). These new vehicles were the European Space Agency s (ESA) Automated Transfer Vehicle (ATV), the Jules Verne, and the Japanese Aerospace and Explorations Agency s (JAXA) H-II Transfer Vehicle (HTV). The ISS Program wanted to quantify the increased risk to the ISS from these visiting vehicles. At the time, only the Shuttle, the Soyuz, and the Progress vehicles rendezvoused and docked to the ISS. The increased risk to the ISS was from an increase in vehicle traffic, thereby, increasing the potential catastrophic collision during the rendezvous and the docking or berthing of the spacecraft to the ISS. A universal method of evaluating the risk of rendezvous and docking or berthing was created by the ISS s Risk Team to accommodate the increasing number of rendezvous and docking or berthing operations due to the increasing number of different spacecraft, as well as the future arrival of commercial spacecraft. Before the first docking attempt of ESA's ATV and JAXA's HTV to the ISS, a probabilistic risk model was developed to quantitatively calculate the risk of collision of each spacecraft with the ISS. The 5 rendezvous and docking risk models (Soyuz, Progress, Shuttle, ATV, and HTV) have been used to build and refine the modeling methodology for rendezvous and docking of spacecrafts. This risk modeling methodology will be NASA s basis for evaluating the addition of future ISS visiting spacecrafts hazards, including SpaceX s Dragon, Orbital Science s Cygnus, and NASA s own Orion spacecraft. This paper will describe the methodology used for developing a visiting vehicle risk model.
Evaluation of wholesale electric power market rules and financial risk management by agent-based simulations

NASA Astrophysics Data System (ADS)

Yu, Nanpeng

As U.S. regional electricity markets continue to refine their market structures, designs and rules of operation in various ways, two critical issues are emerging. First, although much experience has been gained and costly and valuable lessons have been learned, there is still a lack of a systematic platform for evaluation of the impact of a new market design from both engineering and economic points of view. Second, the transition from a monopoly paradigm characterized by a guaranteed rate of return to a competitive market created various unfamiliar financial risks for various market participants, especially for the Investor Owned Utilities (IOUs) and Independent Power Producers (IPPs). This dissertation uses agent-based simulation methods to tackle the market rules evaluation and financial risk management problems. The California energy crisis in 2000-01 showed what could happen to an electricity market if it did not go through a comprehensive and rigorous testing before its implementation. Due to the complexity of the market structure, strategic interaction between the participants, and the underlying physics, it is difficult to fully evaluate the implications of potential changes to market rules. This dissertation presents a flexible and integrative method to assess market designs through agent-based simulations. Realistic simulation scenarios on a 225-bus system are constructed for evaluation of the proposed PJM-like market power mitigation rules of the California electricity market. Simulation results show that in the absence of market power mitigation, generation company (GenCo) agents facilitated by Q-learning are able to exploit the market flaws and make significantly higher profits relative to the competitive benchmark. The incorporation of PJM-like local market power mitigation rules is shown to be effective in suppressing the exercise of market power. The importance of financial risk management is exemplified by the recent financial crisis. In this
Integrated Risk and Knowledge Management Program -- IRKM-P

NASA Technical Reports Server (NTRS)

Lengyel, David M.

2009-01-01

The NASA Exploration Systems Mission Directorate (ESMD) IRKM-P tightly couples risk management and knowledge management processes and tools to produce an effective "modern" work environment. IRKM-P objectives include: (1) to learn lessons from past and current programs (Apollo, Space Shuttle, and the International Space Station); (2) to generate and share new engineering design, operations, and management best practices through preexisting Continuous Risk Management (CRM) procedures and knowledge-management practices; and (3) to infuse those lessons and best practices into current activities. The conceptual framework of the IRKM-P is based on the assumption that risks highlight potential knowledge gaps that might be mitigated through one or more knowledge management practices or artifacts. These same risks also serve as cues for collection of knowledge particularly, knowledge of technical or programmatic challenges that might recur.
A probabilistic approach of the Flash Flood Early Warning System (FF-EWS) in Catalonia based on radar ensemble generation

NASA Astrophysics Data System (ADS)

Velasco, David; Sempere-Torres, Daniel; Corral, Carles; Llort, Xavier; Velasco, Enrique

2010-05-01

Early Warning Systems (EWS) are commonly identified as the most efficient tools in order to improve the preparedness and risk management against heavy rains and Flash Floods (FF) with the objective of reducing economical losses and human casualties. In particular, flash floods affecting torrential Mediterranean catchments are a key element to be incorporated within operational EWSs. The characteristic high spatial and temporal variability of the storms requires high-resolution data and methods to monitor/forecast the evolution of rainfall and its hydrological impact in small and medium torrential basins. A first version of an operational FF-EWS has been implemented in Catalonia (NE Spain) under the name of EHIMI system (Integrated Tool for Hydrometeorological Forecasting) with the support of the Catalan Water Agency (ACA) and the Meteorological Service of Catalonia (SMC). Flash flood warnings are issued based on radar-rainfall estimates. Rainfall estimation is performed on radar observations with high spatial and temporal resolution (1km2 and 10 minutes) in order to adapt the warning scale to the 1-km grid of the EWS. The method is based on comparing observed accumulated rainfall against rainfall thresholds provided by the regional Intensity-Duration-Frequency (IDF) curves. The so-called "aggregated rainfall warning" at every river cell is obtained as the spatially averaged rainfall over its associated upstream draining area. Regarding the time aggregation of rainfall, the critical duration is thought to be an accumulation period similar to the concentration time of each cachtment. The warning is issued once the forecasted rainfall accumulation exceeds the rainfall thresholds mentioned above, which are associated to certain probability of occurrence. Finally, the hazard warning is provided and shown to the decision-maker in terms of exceeded return periods at every river cell covering the whole area of Catalonia. The objective of the present work includes the
Evaluating the impacts of agricultural land management practices on water resources: A probabilistic hydrologic modeling approach.

PubMed

Prada, A F; Chu, M L; Guzman, J A; Moriasi, D N

2017-05-15

Evaluating the effectiveness of agricultural land management practices in minimizing environmental impacts using models is challenged by the presence of inherent uncertainties during the model development stage. One issue faced during the model development stage is the uncertainty involved in model parameterization. Using a single optimized set of parameters (one snapshot) to represent baseline conditions of the system limits the applicability and robustness of the model to properly represent future or alternative scenarios. The objective of this study was to develop a framework that facilitates model parameter selection while evaluating uncertainty to assess the impacts of land management practices at the watershed scale. The model framework was applied to the Lake Creek watershed located in southwestern Oklahoma, USA. A two-step probabilistic approach was implemented to parameterize the Agricultural Policy/Environmental eXtender (APEX) model using global uncertainty and sensitivity analysis to estimate the full spectrum of total monthly water yield (WYLD) and total monthly Nitrogen loads (N) in the watershed under different land management practices. Twenty-seven models were found to represent the baseline scenario in which uncertainty of up to 29% and 400% in WYLD and N, respectively, is plausible. Changing the land cover to pasture manifested the highest decrease in N to up to 30% for a full pasture coverage while changing to full winter wheat cover can increase the N up to 11%. The methodology developed in this study was able to quantify the full spectrum of system responses, the uncertainty associated with them, and the most important parameters that drive their variability. Results from this study can be used to develop strategic decisions on the risks and tradeoffs associated with different management alternatives that aim to increase productivity while also minimizing their environmental impacts. Copyright © 2017 Elsevier Ltd. All rights reserved.
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.
Analysis of interactions among barriers in project risk management

NASA Astrophysics Data System (ADS)

Dandage, Rahul V.; Mantha, Shankar S.; Rane, Santosh B.; Bhoola, Vanita

2018-03-01

In the context of the scope, time, cost, and quality constraints, failure is not uncommon in project management. While small projects have 70% chances of success, large projects virtually have no chance of meeting the quadruple constraints. While there is no dearth of research on project risk management, the manifestation of barriers to project risk management is a less dwelt topic. The success of project management is oftentimes based on the understanding of barriers to effective risk management, application of appropriate risk management methodology, proactive leadership to avoid barriers, workers' attitude, adequate resources, organizational culture, and involvement of top management. This paper represents various risk categories and barriers to risk management in domestic and international projects through literature survey and feedback from project professionals. After analysing the various modelling methods used in project risk management literature, interpretive structural modelling (ISM) and MICMAC analysis have been used to analyse interactions among the barriers and prioritize them. The analysis indicates that lack of top management support, lack of formal training, and lack of addressing cultural differences are the high priority barriers, among many others.
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
Communicating Risk to Program Managers

NASA Technical Reports Server (NTRS)

Shivers, C. Herbert

2005-01-01

Program Managers (PM) can protect program resources and improve chances of success by anticipating, understanding and managing risks. Understanding the range of potential risks helps one to avoid or manage the risks. A PM must choose which risks to accept to reduce fire fighting, must meet the expectations of stakeholders consistently, and avoid falling into costly "black holes" that may open. A good risk management process provides the PM more confidence to seize opportunities save money, meet schedule, even improve relationships with people important to the program. Evidence of managing risk and sound internal controls can mean better support from superiors for the program by building a trust and reputation from being on top of issues. Risk managers have an obligation to provide the PM with the best information possible to allow the benefits to be realized (Small Business Consortium, 2004). The Institute for Chartered Accountants in England and Wales sees very important benefits for companies in providing better information about what they do to assess and manage key business risks. Such information will: a) provide practical forward-looking information; b) reduce the cost of capital; c) encourage better risk management; and d) improve accountability for stewardship, investor protection and the usefulness of financial reporting. We are particularly convinced that enhanced risk reporting will help listed companies obtain capital at the lowest possible cost (The Institute of Chartered Accountants in England &Wales, June 2002). Risk managers can take a significant role in quantifying the success of their department and communicating those figures to executive (program) management levels while pushing for a broader risk management role. Overall, risk managers must show that risk management work matters in the most crucial place-the bottom line- as they prove risk management can be a profit center (Sullivan, 2004).
Probabilistic Neighborhood-Based Data Collection Algorithms for 3D Underwater Acoustic Sensor Networks

PubMed Central

Han, Guangjie; Li, Shanshan; Zhu, Chunsheng; Jiang, Jinfang; Zhang, Wenbo

2017-01-01

Marine environmental monitoring provides crucial information and support for the exploitation, utilization, and protection of marine resources. With the rapid development of information technology, the development of three-dimensional underwater acoustic sensor networks (3D UASNs) provides a novel strategy to acquire marine environment information conveniently, efficiently and accurately. However, the specific propagation effects of acoustic communication channel lead to decreased successful information delivery probability with increased distance. Therefore, we investigate two probabilistic neighborhood-based data collection algorithms for 3D UASNs which are based on a probabilistic acoustic communication model instead of the traditional deterministic acoustic communication model. An autonomous underwater vehicle (AUV) is employed to traverse along the designed path to collect data from neighborhoods. For 3D UASNs without prior deployment knowledge, partitioning the network into grids can allow the AUV to visit the central location of each grid for data collection. For 3D UASNs in which the deployment knowledge is known in advance, the AUV only needs to visit several selected locations by constructing a minimum probabilistic neighborhood covering set to reduce data latency. Otherwise, by increasing the transmission rounds, our proposed algorithms can provide a tradeoff between data collection latency and information gain. These algorithms are compared with basic Nearest-neighbor Heuristic algorithm via simulations. Simulation analyses show that our proposed algorithms can efficiently reduce the average data collection completion time, corresponding to a decrease of data latency. PMID:28208735
Probabilistic Neighborhood-Based Data Collection Algorithms for 3D Underwater Acoustic Sensor Networks.

PubMed

Han, Guangjie; Li, Shanshan; Zhu, Chunsheng; Jiang, Jinfang; Zhang, Wenbo

2017-02-08

Marine environmental monitoring provides crucial information and support for the exploitation, utilization, and protection of marine resources. With the rapid development of information technology, the development of three-dimensional underwater acoustic sensor networks (3D UASNs) provides a novel strategy to acquire marine environment information conveniently, efficiently and accurately. However, the specific propagation effects of acoustic communication channel lead to decreased successful information delivery probability with increased distance. Therefore, we investigate two probabilistic neighborhood-based data collection algorithms for 3D UASNs which are based on a probabilistic acoustic communication model instead of the traditional deterministic acoustic communication model. An autonomous underwater vehicle (AUV) is employed to traverse along the designed path to collect data from neighborhoods. For 3D UASNs without prior deployment knowledge, partitioning the network into grids can allow the AUV to visit the central location of each grid for data collection. For 3D UASNs in which the deployment knowledge is known in advance, the AUV only needs to visit several selected locations by constructing a minimum probabilistic neighborhood covering set to reduce data latency. Otherwise, by increasing the transmission rounds, our proposed algorithms can provide a tradeoff between data collection latency and information gain. These algorithms are compared with basic Nearest-neighbor Heuristic algorithm via simulations. Simulation analyses show that our proposed algorithms can efficiently reduce the average data collection completion time, corresponding to a decrease of data latency.
Adaptive predictors based on probabilistic SVM for real time disruption mitigation on JET

NASA Astrophysics Data System (ADS)

Murari, A.; Lungaroni, M.; Peluso, E.; Gaudio, P.; Vega, J.; Dormido-Canto, S.; Baruzzo, M.; Gelfusa, M.; Contributors, JET

2018-05-01

Detecting disruptions with sufficient anticipation time is essential to undertake any form of remedial strategy, mitigation or avoidance. Traditional predictors based on machine learning techniques can be very performing, if properly optimised, but do not provide a natural estimate of the quality of their outputs and they typically age very quickly. In this paper a new set of tools, based on probabilistic extensions of support vector machines (SVM), are introduced and applied for the first time to JET data. The probabilistic output constitutes a natural qualification of the prediction quality and provides additional flexibility. An adaptive training strategy ‘from scratch’ has also been devised, which allows preserving the performance even when the experimental conditions change significantly. Large JET databases of disruptions, covering entire campaigns and thousands of discharges, have been analysed, both for the case of the graphite and the ITER Like Wall. Performance significantly better than any previous predictor using adaptive training has been achieved, satisfying even the requirements of the next generation of devices. The adaptive approach to the training has also provided unique information about the evolution of the operational space. The fact that the developed tools give the probability of disruption improves the interpretability of the results, provides an estimate of the predictor quality and gives new insights into the physics. Moreover, the probabilistic treatment permits to insert more easily these classifiers into general decision support and control systems.
Managing the risks of risk management on large fires

Treesearch

Donald G. MacGregor; Armando González-Cabán

2013-01-01

Large fires pose risks to a number of important values, including the ecology, property and the lives of incident responders. A relatively unstudied aspect of fire management is the risks to which incident managers are exposed due to organizational and sociopolitical factors that put them in a position of, for example, potential liability or degradation of their image...
The SAM framework: modeling the effects of management factors on human behavior in risk analysis.

PubMed

Murphy, D M; Paté-Cornell, M E

1996-08-01

Complex engineered systems, such as nuclear reactors and chemical plants, have the potential for catastrophic failure with disastrous consequences. In recent years, human and management factors have been recognized as frequent root causes of major failures in such systems. However, classical probabilistic risk analysis (PRA) techniques do not account for the underlying causes of these errors because they focus on the physical system and do not explicitly address the link between components' performance and organizational factors. This paper describes a general approach for addressing the human and management causes of system failure, called the SAM (System-Action-Management) framework. Beginning with a quantitative risk model of the physical system, SAM expands the scope of analysis to incorporate first the decisions and actions of individuals that affect the physical system. SAM then links management factors (incentives, training, policies and procedures, selection criteria, etc.) to those decisions and actions. The focus of this paper is on four quantitative models of action that describe this last relationship. These models address the formation of intentions for action and their execution as a function of the organizational environment. Intention formation is described by three alternative models: a rational model, a bounded rationality model, and a rule-based model. The execution of intentions is then modeled separately. These four models are designed to assess the probabilities of individual actions from the perspective of management, thus reflecting the uncertainties inherent to human behavior. The SAM framework is illustrated for a hypothetical case of hazardous materials transportation. This framework can be used as a tool to increase the safety and reliability of complex technical systems by modifying the organization, rather than, or in addition to, re-designing the physical system.
Potential advantages associated with implementing a risk-based inspection program by a nuclear facility

NASA Astrophysics Data System (ADS)

McNeill, Alexander, III; Balkey, Kenneth R.

1995-05-01

The current inservice inspection activities at a U.S. nuclear facility are based upon the American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel Code, Section XI. The Code selects examination locations based upon a sampling criteria which includes component geometry, stress, and usage among other criteria. This can result in a significant number of required examinations. As a result of regulatory action each nuclear facility has conducted probabilistic risk assessments (PRA) or individual plant examinations (IPE), producing plant specific risk-based information. Several initiatives have been introduced to apply this new plant risk information. Among these initiatives is risk-based inservice inspection. A code case has been introduced for piping inspections based upon this new risk- based technology. This effort brought forward to the ASME Section XI Code committee, has been initiated and championed by the ASME Research Task Force on Risk-Based Inspection Guidelines -- LWR Nuclear Power Plant Application. Preliminary assessments associated with the code case have revealed that potential advantages exist in a risk-based inservice inspection program with regard to a number of exams, risk, personnel exposure, and cost.
Periodontal Management by Risk Assessment: A Pragmatic Approach.

PubMed

Mullins, Joanna M; Even, Joshua B; White, Joel M

2016-06-01

An evidence-based periodontal disease risk assessment and diagnosis system has been developed and combined with a clinical decision support and management program to improve treatment and measure patient outcomes. There is little agreement on a universally accepted periodontal risk assessment, periodontal diagnosis, and treatment management tool and their incorporation into dental practice to improve patient care. This article highlights the development and use of a practical periodontal management and risk assessment program that can be implemented in dental settings. The approach taken by Willamette Dental Group to develop a periodontal disease risk assessment, periodontal diagnosis, and treatment management tool is described using evidence-based best practices. With goals of standardized treatment interventions while maintaining personalized care and improved communication, this process is described to facilitate its incorporation into other dental settings. Current electronic health records can be leveraged to enhance patient-centered care through the use of risk assessments and standardized guidelines to more effectively assess, diagnose, and treat patients to improve outcomes. Dental hygienists, and other committed providers, with their emphasis on prevention of periodontal disease can be principal drivers in creation and implementation of periodontal risk assessments and personalized treatment planning. Willamette Dental Group believes that such evidence-based tools can advance dentistry to new diagnostic and treatment standards. Copyright © 2016 Elsevier Inc. All rights reserved.
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.
Clinical risk management.

PubMed

Knowles, D

Managing clinical risk involves all staff with clinical and managerial responsibilities. This article draws attention to some key steps in risk management and ways to deal with the problems when things do go wrong.
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.
The HTA Risk Analysis Chart: Visualising the Need for and Potential Value of Managed Entry Agreements in Health Technology Assessment.

PubMed

Grimm, Sabine Elisabeth; Strong, Mark; Brennan, Alan; Wailoo, Allan J

2017-12-01

Recent changes to the regulatory landscape of pharmaceuticals may sometimes require reimbursement authorities to issue guidance on technologies that have a less mature evidence base. Decision makers need to be aware of risks associated with such health technology assessment (HTA) decisions and the potential to manage this risk through managed entry agreements (MEAs). This work develops methods for quantifying risk associated with specific MEAs and for clearly communicating this to decision makers. We develop the 'HTA risk analysis chart', in which we present the payer strategy and uncertainty burden (P-SUB) as a measure of overall risk. The P-SUB consists of the payer uncertainty burden (PUB), the risk stemming from decision uncertainty as to which is the truly optimal technology from the relevant set of technologies, and the payer strategy burden (PSB), the additional risk of approving a technology that is not expected to be optimal. We demonstrate the approach using three recent technology appraisals from the UK National Institute for Health and Clinical Excellence (NICE), each of which considered a price-based MEA. The HTA risk analysis chart was calculated using results from standard probabilistic sensitivity analyses. In all three HTAs, the new interventions were associated with substantial risk as measured by the P-SUB. For one of these technologies, the P-SUB was reduced to zero with the proposed price reduction, making this intervention cost effective with near complete certainty. For the other two, the risk reduced substantially with a much reduced PSB and a slightly increased PUB. The HTA risk analysis chart shows the risk that the healthcare payer incurs under unresolved decision uncertainty and when considering recommending a technology that is not expected to be optimal given current evidence. This allows the simultaneous consideration of financial and data-collection MEA schemes in an easily understood format. The use of HTA risk analysis charts will

Functional mechanisms of probabilistic inference in feature- and space-based attentional systems.

PubMed

Dombert, Pascasie L; Kuhns, Anna; Mengotti, Paola; Fink, Gereon R; Vossel, Simone

2016-11-15

Humans flexibly attend to features or locations and these processes are influenced by the probability of sensory events. We combined computational modeling of response times with fMRI to compare the functional correlates of (re-)orienting, and the modulation by probabilistic inference in spatial and feature-based attention systems. Twenty-four volunteers performed two task versions with spatial or color cues. Percentage of cue validity changed unpredictably. A hierarchical Bayesian model was used to derive trial-wise estimates of probability-dependent attention, entering the fMRI analysis as parametric regressors. Attentional orienting activated a dorsal frontoparietal network in both tasks, without significant parametric modulation. Spatially invalid trials activated a bilateral frontoparietal network and the precuneus, while invalid feature trials activated the left intraparietal sulcus (IPS). Probability-dependent attention modulated activity in the precuneus, left posterior IPS, middle occipital gyrus, and right temporoparietal junction for spatial attention, and in the left anterior IPS for feature-based and spatial attention. These findings provide novel insights into the generality and specificity of the functional basis of attentional control. They suggest that probabilistic inference can distinctively affect each attentional subsystem, but that there is an overlap in the left IPS, which responds to both spatial and feature-based expectancy violations. Copyright © 2016 Elsevier Inc. All rights reserved.
Probabilistic population projections with migration uncertainty

PubMed Central

Azose, Jonathan J.; Ševčíková, Hana; Raftery, Adrian E.

2016-01-01

We produce probabilistic projections of population for all countries based on probabilistic projections of fertility, mortality, and migration. We compare our projections to those from the United Nations’ Probabilistic Population Projections, which uses similar methods for fertility and mortality but deterministic migration projections. We find that uncertainty in migration projection is a substantial contributor to uncertainty in population projections for many countries. Prediction intervals for the populations of Northern America and Europe are over 70% wider, whereas prediction intervals for the populations of Africa, Asia, and the world as a whole are nearly unchanged. Out-of-sample validation shows that the model is reasonably well calibrated. PMID:27217571
Risk Management Issues - An Aerospace Perspective

NASA Technical Reports Server (NTRS)

Perera, Jeevan S.

2011-01-01

Phased-approach for implementation of risk management is necessary. Risk management system will be simple, accessible and promote communication of information to all relevant stakeholders for optimal resource allocation and risk mitigation. Risk management should be used by all team members to manage risks--risk office personnel. Each group is assigned Risk Integrators who are facilitators for effective risk management. Risks will be managed at the lowest-level feasible, elevate only those risks that require coordination or management from above. Risk reporting and communication is an essential element of risk management and will combine both qualitative and quantitative elements.. Risk informed decision making should be introduced to all levels of management. Provide necessary checks and balances to insure that risks are caught/identified and dealt with in a timely manner, Many supporting tools, processes & training must be deployed for effective risk management implementation. Process improvement must be included in the risk processes.
Estimating and controlling workplace risk: an approach for occupational hygiene and safety professionals.

PubMed

Toffel, Michael W; Birkner, Lawrence R

2002-07-01

The protection of people and physical assets is the objective of health and safety professionals and is accomplished through the paradigm of anticipation, recognition, evaluation, and control of risks in the occupational environment. Risk assessment concepts are not only used by health and safety professionals, but also by business and financial planners. Since meeting health and safety objectives requires financial resources provided by business and governmental managers, the hypothesis addressed here is that health and safety risk decisions should be made with probabilistic processes used in financial decision-making and which are familiar and recognizable to business and government planners and managers. This article develops the processes and demonstrates the use of incident probabilities, historic outcome information, and incremental impact analysis to estimate risk of multiple alternatives in the chemical process industry. It also analyzes how the ethical aspects of decision-making can be addressed in formulating health and safety risk management plans. It is concluded that certain, easily understood, and applied probabilistic risk assessment methods used by business and government to assess financial and outcome risk have applicability to improving workplace health and safety in three ways: 1) by linking the business and health and safety risk assessment processes to securing resources, 2) by providing an additional set of tools for health and safety risk assessment, and 3) by requiring the risk assessor to consider multiple risk management alternatives.
Space Shuttle Probabilistic Risk Assessment (SPRA) Iteration 3.2

NASA Technical Reports Server (NTRS)

Boyer, Roger L.

2010-01-01

The Shuttle is a very reliable vehicle in comparison with other launch systems. Much of the risk posed by Shuttle operations is related to fundamental aspects of the spacecraft design and the environments in which it operates. It is unlikely that significant design improvements can be implemented to address these risks prior to the end of the Shuttle program. The model will continue to be used to identify possible emerging risk drivers and allow management to make risk-informed decisions on future missions. Potential uses of the SPRA in the future include: - Calculate risk impact of various mission contingencies (e.g. late inspection, crew rescue, etc.). - Assessing the risk impact of various trade studies (e.g. flow control valves). - Support risk analysis on mission specific events, such as in flight anomalies. - Serve as a guiding star and data source for future NASA programs.
Probabilistic evaluation of uncertainties and risks in aerospace components

NASA Technical Reports Server (NTRS)

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

1992-01-01

This paper summarizes a methodology developed at NASA Lewis Research Center which computationally simulates the structural, material, and load uncertainties associated with Space Shuttle Main Engine (SSME) components. The methodology was applied to evaluate the scatter in static, buckling, dynamic, fatigue, and damage behavior of the SSME turbo pump blade. Also calculated are the probability densities of typical critical blade responses, such as effective stress, natural frequency, damage initiation, most probable damage path, etc. Risk assessments were performed for different failure modes, and the effect of material degradation on the fatigue and damage behaviors of a blade were calculated using a multi-factor interaction equation. Failure probabilities for different fatigue cycles were computed and the uncertainties associated with damage initiation and damage propagation due to different load cycle were quantified. Evaluations on the effects of mistuned blades on a rotor were made; uncertainties in the excitation frequency were found to significantly amplify the blade responses of a mistuned rotor. The effects of the number of blades on a rotor were studied. The autocorrelation function of displacements and the probability density function of the first passage time for deterministic and random barriers for structures subjected to random processes also were computed. A brief discussion was included on the future direction of probabilistic structural analysis.
Trade Studies of Space Launch Architectures using Modular Probabilistic Risk Analysis

NASA Technical Reports Server (NTRS)

Mathias, Donovan L.; Go, Susie

2006-01-01

A top-down risk assessment in the early phases of space exploration architecture development can provide understanding and intuition of the potential risks associated with new designs and technologies. In this approach, risk analysts draw from their past experience and the heritage of similar existing systems as a source for reliability data. This top-down approach captures the complex interactions of the risk driving parts of the integrated system without requiring detailed knowledge of the parts themselves, which is often unavailable in the early design stages. Traditional probabilistic risk analysis (PRA) technologies, however, suffer several drawbacks that limit their timely application to complex technology development programs. The most restrictive of these is a dependence on static planning scenarios, expressed through fault and event trees. Fault trees incorporating comprehensive mission scenarios are routinely constructed for complex space systems, and several commercial software products are available for evaluating fault statistics. These static representations cannot capture the dynamic behavior of system failures without substantial modification of the initial tree. Consequently, the development of dynamic models using fault tree analysis has been an active area of research in recent years. This paper discusses the implementation and demonstration of dynamic, modular scenario modeling for integration of subsystem fault evaluation modules using the Space Architecture Failure Evaluation (SAFE) tool. SAFE is a C++ code that was originally developed to support NASA s Space Launch Initiative. It provides a flexible framework for system architecture definition and trade studies. SAFE supports extensible modeling of dynamic, time-dependent risk drivers of the system and functions at the level of fidelity for which design and failure data exists. The approach is scalable, allowing inclusion of additional information as detailed data becomes available. The tool
Improving organisational resilience through enterprise security risk management.

PubMed

Petruzzi, John; Loyear, Rachelle

Enterprise Security Risk Management (ESRM) is a new philosophy and method of managing security programmes through the use of traditional risk principles. As a philosophy and life cycle, ESRM is focused on creating a business partnership between security practitioners and business leaders to more effectively provide protection against security risks in line with acceptable risk tolerances as defined by business asset owners and stakeholders. This paper explores the basics of the ESRM philosophy and life cycle and also shows how embracing the ESRM philosophy and implementing a risk-based security management model in the business organisation can lead to higher levels of organisational resilience as desired by organisation leaders, executives and the board of directors.
Decisionmaking under risk in invasive species management: risk management theory and applications

Treesearch

Shefali V. Mehta; Robert G. Haight; Frances R. Homans

2010-01-01

Invasive species management is closely entwined with the assessment and management of risk that arises from the inherently random nature of the invasion process. The theory and application of risk management for invasive species with an economic perspective is reviewed in this synthesis. Invasive species management can be delineated into three general categories:...
Risk management in waste water treatment.

PubMed

Wagner, M; Strube, I

2005-01-01

With the continuous restructuring of the water market due to liberalisation, privatisation and internationalisation processes, the requirements on waste water disposal companies have grown. Increasing competition requires a target-oriented and clearly structured procedure. At the same time it is necessary to meet the environment-relevant legal requirements and to design the processes to be environment-oriented. The implementation of risk management and the integration of such a management instrument in an existing system in addition to the use of modern technologies and procedures can help to make the operation of the waste water treatment safer and consequently strengthen market position. The risk management process consists of three phases, risk identification, risk analysis/risk assessment and risk handling, which are based on each other, as well as of the risk managing. To achieve an identification of the risks as complete as possible, a subdivision of the kind of risks (e.g. legal, financial, market, operational) is suggested. One possibility to assess risks is the portfolio method which offers clear representation. It allows a division of the risks into classes showing which areas need handling. The determination of the appropriate measures to handle a risk (e.g. avoidance, reduction, shift) is included in the concluding third phase. Different strategies can be applied here. On the one hand, the cause-oriented strategy, aiming at preventive measures which aim to reduce the probability of occurrence of a risk (e.g. creation of redundancy, systems with low susceptibility to malfunction). On the other hand, the effect-oriented strategy, aiming to minimise the level of damage in case of an undesired occurrence (e.g. use of alarm systems, insurance cover).
Probabilistic Analysis of Radiation Doses for Shore-Based Individuals in Operation Tomodachi

DTIC Science & Technology

2013-05-01

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

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

Henneke, Dennis W.; Robinson, James

In 2015, GE Hitachi Nuclear Energy (GEH) teamed with Argonne National Laboratory (Argonne) to perform Research and Development (R&D) of next-generation Probabilistic Risk Assessment (PRA) methodologies for the modernization of an advanced non-Light Water Reactor (non-LWR) PRA. This effort built upon a PRA developed in the early 1990s for GEH’s Power Reactor Inherently Safe Module (PRISM) Sodium Fast Reactor (SFR). The work had four main tasks: internal events development modeling the risk from the reactor for hazards occurring at-power internal to the plant; an all hazards scoping review to analyze the risk at a high level from external hazards suchmore » as earthquakes and high winds; an all modes scoping review to understand the risk at a high level from operating modes other than at-power; and risk insights to integrate the results from each of the three phases above. To achieve these objectives, GEH and Argonne used and adapted proven PRA methodologies and techniques to build a modern non-LWR all hazards/all modes PRA. The teams also advanced non-LWR PRA methodologies, which is an important outcome from this work. This report summarizes the project outcomes in two major phases. The first phase presents the methodologies developed for non-LWR PRAs. The methodologies are grouped by scope, from Internal Events At-Power (IEAP) to hazards analysis to modes analysis. The second phase presents details of the PRISM PRA model which was developed as a validation of the non-LWR methodologies. The PRISM PRA was performed in detail for IEAP, and at a broader level for hazards and modes. In addition to contributing methodologies, this project developed risk insights applicable to non-LWR PRA, including focus-areas for future R&D, and conclusions about the PRISM design.« less
GAR Global Risk Assessment

NASA Astrophysics Data System (ADS)

Maskrey, Andrew; Safaie, Sahar

2015-04-01

Disaster risk management strategies, policies and actions need to be based on evidence of current disaster loss and risk patterns, past trends and future projections, and underlying risk factors. Faced with competing demands for resources, at any level it is only possible to priorities a range of disaster risk management strategies and investments with adequate understanding of realised losses, current and future risk levels and impacts on economic growth and social wellbeing as well as cost and impact of the strategy. The mapping and understanding of the global risk landscape has been greatly enhanced by the latest iteration of the GAR Global Risk Assessment and the objective of this submission is to present the GAR global risk assessment which contributed to Global Assessment Report (GAR) 2015. This initiative which has been led by UNISDR, was conducted by a consortium of technical institutions from around the world and has covered earthquake, cyclone, riverine flood, and tsunami probabilistic risk for all countries of the world. In addition, the risks associated with volcanic ash in the Asia-Pacific region, drought in various countries in sub-Saharan Africa and climate change in a number of countries have been calculated. The presentation will share thee results as well as the experience including the challenges faced in technical elements as well as the process and recommendations for the future of such endeavour.
Global Infrasound Association Based on Probabilistic Clutter Categorization

NASA Astrophysics Data System (ADS)

Arora, Nimar; Mialle, Pierrick

2016-04-01

The IDC advances its methods and continuously improves its automatic system for the infrasound technology. The IDC focuses on enhancing the automatic system for the identification of valid signals and the optimization of the network detection threshold by identifying ways to refine signal characterization methodology and association criteria. An objective of this study is to reduce the number of associated infrasound arrivals that are rejected from the automatic bulletins when generating the reviewed event bulletins. Indeed, a considerable number of signal detections are due to local clutter sources such as microbaroms, waterfalls, dams, gas flares, surf (ocean breaking waves) etc. These sources are either too diffuse or too local to form events. Worse still, the repetitive nature of this clutter leads to a large number of false event hypotheses due to the random matching of clutter at multiple stations. Previous studies, for example [1], have worked on categorization of clutter using long term trends on detection azimuth, frequency, and amplitude at each station. In this work we continue the same line of reasoning to build a probabilistic model of clutter that is used as part of NETVISA [2], a Bayesian approach to network processing. The resulting model is a fusion of seismic, hydroacoustic and infrasound processing built on a unified probabilistic framework. References: [1] Infrasound categorization Towards a statistics based approach. J. Vergoz, P. Gaillard, A. Le Pichon, N. Brachet, and L. Ceranna. ITW 2011 [2] NETVISA: Network Processing Vertically Integrated Seismic Analysis. N. S. Arora, S. Russell, and E. Sudderth. BSSA 2013
PBPK-Based Probabilistic Risk Assessment for Total Chlorotriazines in Drinking Water.

PubMed

Breckenridge, Charles B; Campbell, Jerry L; Clewell, Harvey J; Andersen, Melvin E; Valdez-Flores, Ciriaco; Sielken, Robert L

2016-04-01

The risk of human exposure to total chlorotriazines (TCT) in drinking water was evaluated using a physiologically based pharmacokinetic (PBPK) model. Daily TCT (atrazine, deethylatrazine, deisopropylatrazine, and diaminochlorotriazine) chemographs were constructed for 17 frequently monitored community water systems (CWSs) using linear interpolation and Krieg estimates between observed TCT values. Synthetic chemographs were created using a conservative bias factor of 3 to generate intervening peaks between measured values. Drinking water consumption records from 24-h diaries were used to calculate daily exposure. Plasma TCT concentrations were updated every 30 minutes using the PBPK model output for each simulated calendar year from 2006 to 2010. Margins of exposure (MOEs) were calculated (MOE = [Human Plasma TCTPOD] ÷ [Human Plasma TCTEXP]) based on the toxicological point of departure (POD) and the drinking water-derived exposure to TCT. MOEs were determined based on 1, 2, 3, 4, 7, 14, 28, or 90 days of rolling average exposures and plasma TCT Cmax, or the area under the curve (AUC). Distributions of MOE were determined and the 99.9th percentile was used for risk assessment. MOEs for all 17 CWSs were >1000 at the 99.9(th)percentile. The 99.9(th)percentile of the MOE distribution was 2.8-fold less when the 3-fold synthetic chemograph bias factor was used. MOEs were insensitive to interpolation method, the consumer's age, the water consumption database used and the duration of time over which the rolling average plasma TCT was calculated, for up to 90 days. MOEs were sensitive to factors that modified the toxicological, or hyphenated appropriately no-observed-effects level (NOEL), including rat strain, endpoint used, method of calculating the NOEL, and the pharmacokinetics of elimination, as well as the magnitude of exposure (CWS, calendar year, and use of bias factors). © The Author 2016. Published by Oxford University Press on behalf of the Society of
Probabilistic risk assessment of the effect of acidified seawater on development stages of sea urchin (Strongylocentrotus droebachiensis).

PubMed

Chen, Wei-Yu; Lin, Hsing-Chieh

2018-05-01

Growing evidence indicates that ocean acidification has a significant impact on calcifying marine organisms. However, there is a lack of exposure risk assessments for aquatic organisms under future environmentally relevant ocean acidification scenarios. The objective of this study was to investigate the probabilistic effects of acidified seawater on the life-stage response dynamics of fertilization, larvae growth, and larvae mortality of the green sea urchin (Strongylocentrotus droebachiensis). We incorporated the regulation of primary body cavity (PBC) pH in response to seawater pH into the assessment by constructing an explicit model to assess effective life-stage response dynamics to seawater or PBC pH levels. The likelihood of exposure to ocean acidification was also evaluated by addressing the uncertainties of the risk characterization. For unsuccessful fertilization, the estimated 50% effect level of seawater acidification (EC50 SW ) was 0.55 ± 0.014 (mean ± SE) pH units. This life stage was more sensitive than growth inhibition and mortality, for which the EC50 values were 1.13 and 1.03 pH units, respectively. The estimated 50% effect levels of PBC pH (EC50 PBC ) were 0.99 ± 0.05 and 0.88 ± 0.006 pH units for growth inhibition and mortality, respectively. We also predicted the probability distributions for seawater and PBC pH levels in 2100. The level of unsuccessful fertilization had 50 and 90% probability risks of 5.07-24.51 (95% CI) and 0-6.95%, respectively. We conclude that this probabilistic risk analysis model is parsimonious enough to quantify the multiple vulnerabilities of the green sea urchin while addressing the systemic effects of ocean acidification. This study found a high potential risk of acidification affecting the fertilization of the green sea urchin, whereas there was no evidence for adverse effects on growth and mortality resulting from exposure to the predicted acidified environment.
A Computationally-Efficient Inverse Approach to Probabilistic Strain-Based Damage Diagnosis

NASA Technical Reports Server (NTRS)

Warner, James E.; Hochhalter, Jacob D.; Leser, William P.; Leser, Patrick E.; Newman, John A

2016-01-01

This work presents a computationally-efficient inverse approach to probabilistic damage diagnosis. Given strain data at a limited number of measurement locations, Bayesian inference and Markov Chain Monte Carlo (MCMC) sampling are used to estimate probability distributions of the unknown location, size, and orientation of damage. Substantial computational speedup is obtained by replacing a three-dimensional finite element (FE) model with an efficient surrogate model. The approach is experimentally validated on cracked test specimens where full field strains are determined using digital image correlation (DIC). Access to full field DIC data allows for testing of different hypothetical sensor arrangements, facilitating the study of strain-based diagnosis effectiveness as the distance between damage and measurement locations increases. The ability of the framework to effectively perform both probabilistic damage localization and characterization in cracked plates is demonstrated and the impact of measurement location on uncertainty in the predictions is shown. Furthermore, the analysis time to produce these predictions is orders of magnitude less than a baseline Bayesian approach with the FE method by utilizing surrogate modeling and effective numerical sampling approaches.
The Probabilistic Nature of Preferential Choice

ERIC Educational Resources Information Center

Rieskamp, Jorg

2008-01-01

Previous research has developed a variety of theories explaining when and why people's decisions under risk deviate from the standard economic view of expected utility maximization. These theories are limited in their predictive accuracy in that they do not explain the probabilistic nature of preferential choice, that is, why an individual makes…
Probabilistic risk assessment of Chinese residents' exposure to fluoride in improved drinking water in endemic fluorosis areas.

PubMed

Zhang, Li E; Huang, Daizheng; Yang, Jie; Wei, Xiao; Qin, Jian; Ou, Songfeng; Zhang, Zhiyong; Zou, Yunfeng

2017-03-01

Studies have yet to evaluate the effects of water improvement on fluoride concentrations in drinking water and the corresponding health risks to Chinese residents in endemic fluorosis areas (EFAs) at a national level. This paper summarized available data in the published literature (2008-2016) on water fluoride from the EFAs in China before and after water quality was improved. Based on these obtained data, health risk assessment of Chinese residents' exposure to fluoride in improved drinking water was performed by means of a probabilistic approach. The uncertainties in the risk estimates were quantified using Monte Carlo simulation and sensitivity analysis. Our results showed that in general, the average fluoride levels (0.10-2.24 mg/L) in the improved drinking water in the EFAs of China were lower than the pre-intervention levels (0.30-15.24 mg/L). The highest fluoride levels were detected in North and Southwest China. The mean non-carcinogenic risks associated with consumption of the improved drinking water for Chinese residents were mostly accepted (hazard quotient < 1), but the non-carcinogenic risk of children in most of the EFAs at the 95th percentile exceeded the safe level of 1, indicating the potential non-cancer-causing health effects on this fluoride-exposed population. Sensitivity analyses indicated that fluoride concentration in drinking water, ingestion rate of water, and the exposure time in the shower were the most relevant variables in the model, therefore, efforts should focus mainly on the definition of their probability distributions for a more accurate risk assessment. Copyright © 2016 Elsevier Ltd. All rights reserved.

Risk-Based Contaminated Land Investigation and Assessment

NASA Astrophysics Data System (ADS)

Davis, Donald R.

With increasing frequency, problems of environmental contamination are being analyzed from a risk perspective. Risk-Based Contaminated Land Investigation and Assessment is written for those who wish to present the results of their examination of contaminated land in terms of risk.The opening chapters introduce the concepts of risk analysis for contaminated land. Risk management and the risk assessment process are based on a source-pathway-target framework. Readers are warned against an “over-reliance on the identification of contaminants rather than the potential pathways by which targets may be exposed to these hazards.” In the risk management framework presented in this book, risk evaluation and resultant decision making are seen as part of both the risk assessment and risk reduction process. The sharp separation of risk assessment from risk management as seen in the National Academy of Sciences' (NAS) risk assessment paradigm is not advocatedsemi; perhaps this is because the NAS' concern was regulatory decision while the book's concern is the assessment of a specific site.
Best practice vendor risk management in today's interconnected world.

PubMed

Beale, Ian

2017-01-01

This paper explains why vendor/third-party risk is so important to all organisations, as well as the principal risks that organisations must consider. It describes the responsibility of management to manage these risks with support from risk experts at the selection phase and through the ongoing relationship. Different sources of information about the management of the key risks and alternative ways of collecting the data are evaluated. The paper concludes by discussing how both customer and supplier organisations benefit from a balanced approach to risk management. The approach described in the paper applies to organisations of all types and sizes and can be applied to varied supply chains. The data and insights are based on research conducted by CEB.
Issuance of Final Guidance: Ecological Risk Assessment and Risk Management Principles for Superfund Sites, October 7, 1999

EPA Pesticide Factsheets

This guidance is intended to help Superfund risk managers make ecological risk management decisions that are based on sound science, consistent across Regions, and present a characterization of site risks that is transparent to the public.
Probabilistic Structural Analysis of SSME Turbopump Blades: Probabilistic Geometry Effects

NASA Technical Reports Server (NTRS)

Nagpal, V. K.

1985-01-01

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

NASA Technical Reports Server (NTRS)

Ramakrishnan, Salesh; Pollack, Martha E.; Smith, David E.

2004-01-01

In this paper, we introduce plan-graph based heuristics to solve a variation of the conformant probabilistic planning (CPP) problem. In many real-world problems, it is the case that the sensors are unreliable or take too many resources to provide knowledge about the environment. These domains are better modeled as conformant planning problems. POMDP based techniques are currently the most successful approach for solving CPP but have the limitation of state- space explosion. Recent advances in deterministic and conformant planning have shown that plan-graphs can be used to enhance the performance significantly. We show that this enhancement can also be translated to CPP. We describe our process for developing the plan-graph heuristics and estimating the probability of a partial plan. We compare the performance of our planner PVHPOP when used with different heuristics. We also perform a comparison with a POMDP solver to show over a order of magnitude improvement in performance.
Information Risk Management and Resilience

NASA Astrophysics Data System (ADS)

Dynes, Scott

Are the levels of information risk management efforts within and between firms correlated with the resilience of the firms to information disruptions? This paper examines the question by considering the results of field studies of information risk management practices at organizations and in supply chains. The organizations investigated differ greatly in the degree of coupling from a general and information risk management standpoint, as well as in the levels of internal awareness and activity regarding information risk management. The comparison of the levels of information risk management in the firms and their actual or inferred resilience indicates that a formal information risk management approach is not necessary for resilience in certain sectors.
Conceptualization and Pilot Testing of a Core Competency-Based Training Workshop in Suicide Risk Assessment and Management: Notes From the Field.

PubMed

Cramer, Robert J; Bryson, Claire N; Eichorst, Morgam K; Keyes, Lee N; Ridge, Brittany E

2017-03-01

As professional psychology training programs and continuing education have moved toward competency based approaches, it has become equally important to develop uniform, evidence-based approaches for suicide risk assessment and management. The present article presents a workshop curriculum based on established core competencies in suicide risk assessment and management. Drawing on theories suicide risk formation, the workshop features an integration of didactic, process, and experiential components. We present pilot data from 2 small group workshops (n = 17): 1 from a clinical psychology doctoral program and 1 from a university counseling center. Workshop participation yielded increases in (a) the ability to recognize appropriate clinician responses to suicidal client statements, (b) self-perceptions of general capacity to interface with suicidal patients and mastery of the 10 core competencies, (c) factual knowledge concerning suicide risk assessment and management, and (d) the self-rated ability to assess and manage a suicidal patient. We discuss statistical and generalizability limitations as well as implications for future modification, implementation, and provision of this training method. © 2016 Wiley Periodicals, Inc.
Process for computing geometric perturbations for probabilistic analysis

DOEpatents

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

2012-04-10

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

NASA Technical Reports Server (NTRS)

Hammer, Theodore F.; Rosenberg, Linda

1999-01-01

NPG 7120.5A, "NASA Program and Project Management Processes and Requirements" enacted in April, 1998, requires that "The program or project manager shall apply risk management principles..." The Software Assurance Technology Center (SATC) at NASA GSFC has been tasked with the responsibility for developing and teaching a systems level course for risk management that provides information on how to comply with this edict. The course was developed in conjunction with the Software Engineering Institute at Carnegie Mellon University, then tailored to the NASA systems community. This presentation will briefly discuss the six functions for risk management: (1) Identify the risks in a specific format; (2) Analyze the risk probability, impact/severity, and timeframe; (3) Plan the approach; (4) Track the risk through data compilation and analysis; (5) Control and monitor the risk; (6) Communicate and document the process and decisions. This risk management structure of functions has been taught to projects at all NASA Centers and is being successfully implemented on many projects. This presentation will give project managers the information they need to understand if risk management is to be effectively implemented on their projects at a cost they can afford.
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).
An empirical system for probabilistic seasonal climate prediction

NASA Astrophysics Data System (ADS)

Eden, Jonathan; van Oldenborgh, Geert Jan; Hawkins, Ed; Suckling, Emma

2016-04-01

Preparing for episodes with risks of anomalous weather a month to a year ahead is an important challenge for governments, non-governmental organisations, and private companies and is dependent on the availability of reliable forecasts. The majority of operational seasonal forecasts are made using process-based dynamical models, which are complex, computationally challenging and prone to biases. Empirical forecast approaches built on statistical models to represent physical processes offer an alternative to dynamical systems and can provide either a benchmark for comparison or independent supplementary forecasts. Here, we present a simple empirical system based on multiple linear regression for producing probabilistic forecasts of seasonal surface air temperature and precipitation across the globe. The global CO2-equivalent concentration is taken as the primary predictor; subsequent predictors, including large-scale modes of variability in the climate system and local-scale information, are selected on the basis of their physical relationship with the predictand. The focus given to the climate change signal as a source of skill and the probabilistic nature of the forecasts produced constitute a novel approach to global empirical prediction. Hindcasts for the period 1961-2013 are validated against observations using deterministic (correlation of seasonal means) and probabilistic (continuous rank probability skill scores) metrics. Good skill is found in many regions, particularly for surface air temperature and most notably in much of Europe during the spring and summer seasons. For precipitation, skill is generally limited to regions with known El Niño-Southern Oscillation (ENSO) teleconnections. The system is used in a quasi-operational framework to generate empirical seasonal forecasts on a monthly basis.
Case Study on Project Risk Management Planning Based on Soft System Methodology

NASA Astrophysics Data System (ADS)

Lifang, Xie; Jun, Li

This paper analyzed the soft system characters of construction projects and the applicability on using Soft System Methodology (SSM) for risk analysis after a brief review of SSM. Taking a hydropower project as an example, it constructed the general frame of project risk management planning (PRMP) and established the Risk Management Planning (RMP) system from the perspective of the interests of co-ordination. This paper provided the ideas and methods for construction RMP under the win-win situation through the practice of SSM.
Applying risk management strategies to strengthen an IDS's investment policy.

PubMed

Fine, R P

1998-11-01

The increased financial risk that not-for-profit integrated delivery systems have assumed to function under managed care has required them to become increasingly reliant on income and gains from their investment portfolios. This reliance underscores the need for these organizations to take steps to effectively manage their investment risk. Not-for-profit IDSs should establish a systematic approach to investment risk management that is based on maintaining a sound fiduciary infrastructure and having a clear understanding of risk exposures, the most important of which are policy and market risk. Applying reasonable and common-sense risk management strategies to investment policy will enhance an IDS's overall financial and competitive strength.
Use of the LUS in sequence allele designations to facilitate probabilistic genotyping of NGS-based STR typing results.

PubMed

Just, Rebecca S; Irwin, Jodi A

2018-05-01

Some of the expected advantages of next generation sequencing (NGS) for short tandem repeat (STR) typing include enhanced mixture detection and genotype resolution via sequence variation among non-homologous alleles of the same length. However, at the same time that NGS methods for forensic DNA typing have advanced in recent years, many caseworking laboratories have implemented or are transitioning to probabilistic genotyping to assist the interpretation of complex autosomal STR typing results. Current probabilistic software programs are designed for length-based data, and were not intended to accommodate sequence strings as the product input. Yet to leverage the benefits of NGS for enhanced genotyping and mixture deconvolution, the sequence variation among same-length products must be utilized in some form. Here, we propose use of the longest uninterrupted stretch (LUS) in allele designations as a simple method to represent sequence variation within the STR repeat regions and facilitate - in the nearterm - probabilistic interpretation of NGS-based typing results. An examination of published population data indicated that a reference LUS region is straightforward to define for most autosomal STR loci, and that using repeat unit plus LUS length as the allele designator can represent greater than 80% of the alleles detected by sequencing. A proof of concept study performed using a freely available probabilistic software demonstrated that the LUS length can be used in allele designations when a program does not require alleles to be integers, and that utilizing sequence information improves interpretation of both single-source and mixed contributor STR typing results as compared to using repeat unit information alone. The LUS concept for allele designation maintains the repeat-based allele nomenclature that will permit backward compatibility to extant STR databases, and the LUS lengths themselves will be concordant regardless of the NGS assay or analysis tools
Barriers to implementation of risk management for federal wildland fire management agencies in the United States

Treesearch

Dave Calkin; Matthew P. Thompson; Alan A. Ager; Mark Finney

2010-01-01

In this presentation we review progress towards the implementation of a risk-based management framework for U.S. Federal wildland fire policy and operations. We first describe new developments in wildfire simulation technology that catalyzed the development of risk-based decision support systems for strategic wildfire management. These systems include new analytical...
Probabilistic forecasting of extreme weather events based on extreme value theory

NASA Astrophysics Data System (ADS)

Van De Vyver, Hans; Van Schaeybroeck, Bert

2016-04-01

Extreme events in weather and climate such as high wind gusts, heavy precipitation or extreme temperatures are commonly associated with high impacts on both environment and society. Forecasting extreme weather events is difficult, and very high-resolution models are needed to describe explicitly extreme weather phenomena. A prediction system for such events should therefore preferably be probabilistic in nature. Probabilistic forecasts and state estimations are nowadays common in the numerical weather prediction community. In this work, we develop a new probabilistic framework based on extreme value theory that aims to provide early warnings up to several days in advance. We consider the combined events when an observation variable Y (for instance wind speed) exceeds a high threshold y and its corresponding deterministic forecasts X also exceeds a high forecast threshold y. More specifically two problems are addressed:} We consider pairs (X,Y) of extreme events where X represents a deterministic forecast, and Y the observation variable (for instance wind speed). More specifically two problems are addressed: Given a high forecast X=x_0, what is the probability that Y>y? In other words: provide inference on the conditional probability: [ Pr{Y>y|X=x_0}. ] Given a probabilistic model for Problem 1, what is the impact on the verification analysis of extreme events. These problems can be solved with bivariate extremes (Coles, 2001), and the verification analysis in (Ferro, 2007). We apply the Ramos and Ledford (2009) parametric model for bivariate tail estimation of the pair (X,Y). The model accommodates different types of extremal dependence and asymmetry within a parsimonious representation. Results are presented using the ensemble reforecast system of the European Centre of Weather Forecasts (Hagedorn, 2008). Coles, S. (2001) An Introduction to Statistical modelling of Extreme Values. Springer-Verlag.Ferro, C.A.T. (2007) A probability model for verifying deterministic
Probabilistic characterization of wind turbine blades via aeroelasticity and spinning finite element formulation

NASA Astrophysics Data System (ADS)

Velazquez, Antonio; Swartz, R. Andrew

2012-04-01

Wind energy is an increasingly important component of this nation's renewable energy portfolio, however safe and economical wind turbine operation is a critical need to ensure continued adoption. Safe operation of wind turbine structures requires not only information regarding their condition, but their operational environment. Given the difficulty inherent in SHM processes for wind turbines (damage detection, location, and characterization), some uncertainty in conditional assessment is expected. Furthermore, given the stochastic nature of the loading on turbine structures, a probabilistic framework is appropriate to characterize their risk of failure at a given time. Such information will be invaluable to turbine controllers, allowing them to operate the structures within acceptable risk profiles. This study explores the characterization of the turbine loading and response envelopes for critical failure modes of the turbine blade structures. A framework is presented to develop an analytical estimation of the loading environment (including loading effects) based on the dynamic behavior of the blades. This is influenced by behaviors including along and across-wind aero-elastic effects, wind shear gradient, tower shadow effects, and centrifugal stiffening effects. The proposed solution includes methods that are based on modal decomposition of the blades and require frequent updates to the estimated modal properties to account for the time-varying nature of the turbine and its environment. The estimated demand statistics are compared to a code-based resistance curve to determine a probabilistic estimate of the risk of blade failure given the loading environment.
Evaluation of feature-based 3-d registration of probabilistic volumetric scenes

NASA Astrophysics Data System (ADS)

Restrepo, Maria I.; Ulusoy, Ali O.; Mundy, Joseph L.

2014-12-01

Automatic estimation of the world surfaces from aerial images has seen much attention and progress in recent years. Among current modeling technologies, probabilistic volumetric models (PVMs) have evolved as an alternative representation that can learn geometry and appearance in a dense and probabilistic manner. Recent progress, in terms of storage and speed, achieved in the area of volumetric modeling, opens the opportunity to develop new frameworks that make use of the PVM to pursue the ultimate goal of creating an entire map of the earth, where one can reason about the semantics and dynamics of the 3-d world. Aligning 3-d models collected at different time-instances constitutes an important step for successful fusion of large spatio-temporal information. This paper evaluates how effectively probabilistic volumetric models can be aligned using robust feature-matching techniques, while considering different scenarios that reflect the kind of variability observed across aerial video collections from different time instances. More precisely, this work investigates variability in terms of discretization, resolution and sampling density, errors in the camera orientation, and changes in illumination and geographic characteristics. All results are given for large-scale, outdoor sites. In order to facilitate the comparison of the registration performance of PVMs to that of other 3-d reconstruction techniques, the registration pipeline is also carried out using Patch-based Multi-View Stereo (PMVS) algorithm. Registration performance is similar for scenes that have favorable geometry and the appearance characteristics necessary for high quality reconstruction. In scenes containing trees, such as a park, or many buildings, such as a city center, registration performance is significantly more accurate when using the PVM.
The Experimental Breeder Reactor II seismic probabilistic risk assessment

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

Roglans, J; Hill, D J

1994-02-01

The Experimental Breeder Reactor II (EBR-II) is a US Department of Energy (DOE) Category A research reactor located at Argonne National Laboratory (ANL)-West in Idaho. EBR-II is a 62.5 MW-thermal Liquid Metal Reactor (LMR) that started operation in 1964 and it is currently being used as a testbed in the Integral Fast Reactor (IFR) Program. ANL has completed a Level 1 Probabilistic Risk Assessment (PRA) for EBR-II. The Level 1 PRA for internal events and most external events was completed in June 1991. The seismic PRA for EBR-H has recently been completed. The EBR-II reactor building contains the reactor, themore » primary system, and the decay heat removal systems. The reactor vessel, which contains the core, and the primary system, consisting of two primary pumps and an intermediate heat exchanger, are immersed in the sodium-filled primary tank, which is suspended by six hangers from a beam support structure. Three systems or functions in EBR-II were identified as the most significant from the standpoint of risk of seismic-induced fuel damage: (1) the reactor shutdown system, (2) the structural integrity of the passive decay heat removal systems, and (3) the integrity of major structures, like the primary tank containing the reactor that could threaten both the reactivity control and decay heat removal functions. As part of the seismic PRA, efforts were concentrated in studying these three functions or systems. The passive safety response of EBR-II reactor -- both passive reactivity shutdown and passive decay heat removal, demonstrated in a series of tests in 1986 -- was explicitly accounted for in the seismic PRA as it had been included in the internal events assessment.« less
Probabilistic performance-based design for high performance control systems

NASA Astrophysics Data System (ADS)

Micheli, Laura; Cao, Liang; Gong, Yongqiang; Cancelli, Alessandro; Laflamme, Simon; Alipour, Alice

2017-04-01

High performance control systems (HPCS) are advanced damping systems capable of high damping performance over a wide frequency bandwidth, ideal for mitigation of multi-hazards. They include active, semi-active, and hybrid damping systems. However, HPCS are more expensive than typical passive mitigation systems, rely on power and hardware (e.g., sensors, actuators) to operate, and require maintenance. In this paper, a life cycle cost analysis (LCA) approach is proposed to estimate the economic benefit these systems over the entire life of the structure. The novelty resides in the life cycle cost analysis in the performance based design (PBD) tailored to multi-level wind hazards. This yields a probabilistic performance-based design approach for HPCS. Numerical simulations are conducted on a building located in Boston, MA. LCA are conducted for passive control systems and HPCS, and the concept of controller robustness is demonstrated. Results highlight the promise of the proposed performance-based design procedure.

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