WorldWideScience

Sample records for integrated risk uncertainty

  1. Integration of expert knowledge and uncertainty in natural risk assessment

    Science.gov (United States)

    Baruffini, Mirko; Jaboyedoff, Michel

    2010-05-01

    Natural hazards occurring in alpine regions during the last decades have clearly shown that interruptions of the Swiss railway power supply and closures of the Gotthard highway due to those events have increased the awareness of infrastructure vulnerability also in Switzerland and illustrate the potential impacts of failures on the performance of infrastructure systems. This asks for a high level of surveillance and preservation along the transalpine lines. Traditional simulation models are only partially capable to predict complex systems behaviours and the subsequently designed and implemented protection strategies are not able to mitigate the full spectrum of risk consequences. They are costly, and maximal protection is most probably not economically feasible. In addition, the quantitative risk assessment approaches such as fault tree analysis, event tree analysis and equivalent annual fatality analysis rely heavily on statistical information. Collecting sufficient data to base a statistical probability of risk is costly and, in many situations, such data does not exist; thus, expert knowledge and experience or engineering judgment can be exploited to estimate risk qualitatively. In order to overcome the statistics lack we used models based on expert's knowledge in order to qualitatively predict based on linguistic appreciation that are more expressive and natural in risk assessment. Fuzzy reasoning (FR) can be used providing a mechanism of computing with words (Zadeh, 1965) for modelling qualitative human thought processes in analyzing complex systems and decisions. Uncertainty in predicting the risk levels arises from such situations because no fully-formalized knowledge are available. Another possibility is to use probability based on triangular probability density function (T-PDF) that can be used to follow the same flow-chart as FR. We implemented the Swiss natural hazard recommendations FR and probability using T-PDF in order to obtain hazard zoning and

  2. Integration of renewable generation uncertainties into stochastic unit commitment considering reserve and risk: A comparative study

    International Nuclear Information System (INIS)

    Quan, Hao; Srinivasan, Dipti; Khosravi, Abbas

    2016-01-01

    The uncertainties of renewable energy have brought great challenges to power system commitment, dispatches and reserve requirement. This paper presents a comparative study on integration of renewable generation uncertainties into SCUC (stochastic security-constrained unit commitment) considering reserve and risk. Renewable forecast uncertainties are captured by a list of PIs (prediction intervals). A new scenario generation method is proposed to generate scenarios from these PIs. Different system uncertainties are considered as scenarios in the stochastic SCUC problem formulation. Two comparative simulations with single (E1: wind only) and multiple sources of uncertainty (E2: load, wind, solar and generation outages) are investigated. Five deterministic and four stochastic case studies are performed. Different generation costs, reserve strategies and associated risks are compared under various scenarios. Demonstrated results indicate the overall costs of E2 is lower than E1 due to penetration of solar power and the associated risk in deterministic cases of E2 is higher than E1. It implies the superimposed effect of uncertainties during uncertainty integration. The results also demonstrate that power systems run a higher level of risk during peak load hours, and that stochastic models are more robust than deterministic ones. - Highlights: • An extensive comparative study for renewable integration is presented. • A novel scenario generation method is proposed. • Wind and solar uncertainties are represented by a list of prediction intervals. • Unit commitment and dispatch costs are discussed considering reserve and risk.

  3. Integrated Risk-Capability Analysis under Deep Uncertainty : An ESDMA Approach

    NARCIS (Netherlands)

    Pruyt, E.; Kwakkel, J.H.

    2012-01-01

    Integrated risk-capability analysis methodologies for dealing with increasing degrees of complexity and deep uncertainty are urgently needed in an ever more complex and uncertain world. Although scenario approaches, risk assessment methods, and capability analysis methods are used, few organizations

  4. Exploring the uncertainties in cancer risk assessment using the integrated probabilistic risk assessment (IPRA) approach.

    Science.gov (United States)

    Slob, Wout; Bakker, Martine I; Biesebeek, Jan Dirk Te; Bokkers, Bas G H

    2014-08-01

    Current methods for cancer risk assessment result in single values, without any quantitative information on the uncertainties in these values. Therefore, single risk values could easily be overinterpreted. In this study, we discuss a full probabilistic cancer risk assessment approach in which all the generally recognized uncertainties in both exposure and hazard assessment are quantitatively characterized and probabilistically evaluated, resulting in a confidence interval for the final risk estimate. The methodology is applied to three example chemicals (aflatoxin, N-nitrosodimethylamine, and methyleugenol). These examples illustrate that the uncertainty in a cancer risk estimate may be huge, making single value estimates of cancer risk meaningless. Further, a risk based on linear extrapolation tends to be lower than the upper 95% confidence limit of a probabilistic risk estimate, and in that sense it is not conservative. Our conceptual analysis showed that there are two possible basic approaches for cancer risk assessment, depending on the interpretation of the dose-incidence data measured in animals. However, it remains unclear which of the two interpretations is the more adequate one, adding an additional uncertainty to the already huge confidence intervals for cancer risk estimates. © 2014 Society for Risk Analysis.

  5. Financial risk management for new technology integration in energy planning under uncertainty

    International Nuclear Information System (INIS)

    Ahmed, Sajjad; Elsholkami, Mohamed; Elkamel, Ali; Du, Juan; Ydstie, Erik B.; Douglas, Peter L.

    2014-01-01

    Highlights: • Financial risk associated with over or underproduction of electricity is studied. • A two-stage stochastic model that considers parameter uncertainties is developed. • The model was applied to a real case to meet projected electricity demand of a fleet of generating stations. • Incorporation of financial risk resulted in an increase in electricity cost. • The selection of technologies was the same as that obtained from a deterministic model. - Abstract: This paper proposes a new methodology to include financial risk management in the framework of two-stage stochastic programming for energy planning under uncertainties in demand and fuel price. A deterministic mixed integer linear programming formulation is extended to a two-stage stochastic programming model in order to take into account random parameters that have discrete and finite probabilistic distributions. This was applied to a case study focusing on planning the capacity supply to meet the projected electricity demand for the fleet of electricity generation stations owned and operated by Ontario Power Generation (OPG). The objective of the proposed mathematical model is to minimize cost subject to environmental constraints. The case study is investigated by considering only existing technologies and also by considering the integration of new technologies that help achieve stricter carbon reduction requirements

  6. Model Uncertainty via the Integration of Hormesis and LNT as the Default in Cancer Risk Assessment.

    Science.gov (United States)

    Calabrese, Edward J

    2015-01-01

    On June 23, 2015, the US Nuclear Regulatory Commission (NRC) issued a formal notice in the Federal Register that it would consider whether "it should amend its 'Standards for Protection Against Radiation' regulations from the linear non-threshold (LNT) model of radiation protection to the hormesis model." The present commentary supports this recommendation based on the (1) flawed and deceptive history of the adoption of LNT by the US National Academy of Sciences (NAS) in 1956; (2) the documented capacity of hormesis to make more accurate predictions of biological responses for diverse biological end points in the low-dose zone; (3) the occurrence of extensive hormetic data from the peer-reviewed biomedical literature that revealed hormetic responses are highly generalizable, being independent of biological model, end point measured, inducing agent, level of biological organization, and mechanism; and (4) the integration of hormesis and LNT models via a model uncertainty methodology that optimizes public health responses at 10(-4). Thus, both LNT and hormesis can be integratively used for risk assessment purposes, and this integration defines the so-called "regulatory sweet spot."

  7. Risk and Uncertainties, Analysis and Evaluation: Lessons for Adaptation and Integration

    International Nuclear Information System (INIS)

    Yohe, G.; Dowlatabadi, H.

    1999-01-01

    This paper draws ten lessons from analyses of adaptation to climate change under conditions of risk and uncertainty: (1) Socio-economic systems will likely respond most to extreme realizations of climate change. (2) Systems have been responding to variations in climate for centuries. (3) Future change will effect future citizens and their institutions. (4) Human systems can be the sources of surprise. (5) Perceptions of risk depend upon welfare valuations that depend upon expectations. (6) Adaptive decisions will be made in response to climate change and climate change policy. (7) Analysis of adaptive decisions should recognize the second-best context of those decisions. (8) Climate change offers opportunity as well as risk. (9) All plausible futures should be explored. (10) Multiple methodological approaches should be accommodated. These lessons support two pieces of advice for the Third Assessment Report: (1) Work toward consensus, but not at the expense of thorough examination and reporting of the 'tails' of the distributions of the future. (2) Integrated assessment is only one unifying methodology; others that can better accommodate those tails should be encouraged and embraced. 12 refs

  8. Analysis of algal bloom risk with uncertainties in lakes by integrating self-organizing map and fuzzy information theory

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Qiuwen, E-mail: qchen@rcees.ac.cn [RCEES, Chinese Academy of Sciences, Shuangqinglu 18, Beijing 10085 (China); China Three Gorges University, Daxuelu 8, Yichang 443002 (China); CEER, Nanjing Hydraulics Research Institute, Guangzhoulu 223, Nanjing 210029 (China); Rui, Han; Li, Weifeng; Zhang, Yanhui [RCEES, Chinese Academy of Sciences, Shuangqinglu 18, Beijing 10085 (China)

    2014-06-01

    Algal blooms are a serious problem in waters, which damage aquatic ecosystems and threaten drinking water safety. However, the outbreak mechanism of algal blooms is very complex with great uncertainty, especially for large water bodies where environmental conditions have obvious variation in both space and time. This study developed an innovative method which integrated a self-organizing map (SOM) and fuzzy information diffusion theory to comprehensively analyze algal bloom risks with uncertainties. The Lake Taihu was taken as study case and the long-term (2004–2010) on-site monitoring data were used. The results showed that algal blooms in Taihu Lake were classified into four categories and exhibited obvious spatial–temporal patterns. The lake was mainly characterized by moderate bloom but had high uncertainty, whereas severe blooms with low uncertainty were observed in the northwest part of the lake. The study gives insight on the spatial–temporal dynamics of algal blooms, and should help government and decision-makers outline policies and practices on bloom monitoring and prevention. The developed method provides a promising approach to estimate algal bloom risks under uncertainties. - Highlights: • An innovative method is developed to analyze algal bloom risks with uncertainties. • The algal blooms in Taihu Lake showed obvious spatial and temporal patterns. • The lake is mainly characterized as moderate bloom but with high uncertainty. • Severe bloom with low uncertainty appeared occasionally in the northwest part. • The results provide important information to bloom monitoring and management.

  9. Uncertainty: lotteries and risk

    OpenAIRE

    Ávalos, Eloy

    2011-01-01

    In this paper we develop the theory of uncertainty in a context where the risks assumed by the individual are measurable and manageable. We primarily use the definition of lottery to formulate the axioms of the individual's preferences, and its representation through the utility function von Neumann - Morgenstern. We study the expected utility theorem and its properties, the paradoxes of choice under uncertainty and finally the measures of risk aversion with monetary lotteries.

  10. Integrating risk analysis and multi-criteria decision support under uncertainty in electricity distribution system asset management

    International Nuclear Information System (INIS)

    Catrinu, M.D.; Nordgard, D.E.

    2011-01-01

    Asset managers in electricity distribution companies generally recognize the need and the challenge of adding structure and a higher degree of formal analysis into the increasingly complex asset management decisions. This implies improving the present asset management practice by making the best use of the available data and expert knowledge and by adopting new methods for risk analysis and decision support and nevertheless better ways to document the decisions made. This paper discusses methods for integrating risk analysis and multi-criteria decision support under uncertainty in electricity distribution system asset management. The focus is on how to include the different company objectives and risk analyses into a structured decision framework when deciding how to handle the physical assets of the electricity distribution network. This paper presents an illustrative example of decision support for maintenance and reinvestment strategies based, using expert knowledge, simplified risk analyses and multi-criteria decision analysis under uncertainty.

  11. Handling Uncertainty in Social Lending Credit Risk Prediction with a Choquet Fuzzy Integral Model

    OpenAIRE

    Namvar, Anahita; Naderpour, Mohsen

    2018-01-01

    As one of the main business models in the financial technology field, peer-to-peer (P2P) lending has disrupted traditional financial services by providing an online platform for lending money that has remarkably reduced financial costs. However, the inherent uncertainty in P2P loans can result in huge financial losses for P2P platforms. Therefore, accurate risk prediction is critical to the success of P2P lending platforms. Indeed, even a small improvement in credit risk prediction would be o...

  12. Analysis of algal bloom risk with uncertainties in lakes by integrating self-organizing map and fuzzy information theory.

    Science.gov (United States)

    Chen, Qiuwen; Rui, Han; Li, Weifeng; Zhang, Yanhui

    2014-06-01

    Algal blooms are a serious problem in waters, which damage aquatic ecosystems and threaten drinking water safety. However, the outbreak mechanism of algal blooms is very complex with great uncertainty, especially for large water bodies where environmental conditions have obvious variation in both space and time. This study developed an innovative method which integrated a self-organizing map (SOM) and fuzzy information diffusion theory to comprehensively analyze algal bloom risks with uncertainties. The Lake Taihu was taken as study case and the long-term (2004-2010) on-site monitoring data were used. The results showed that algal blooms in Taihu Lake were classified into four categories and exhibited obvious spatial-temporal patterns. The lake was mainly characterized by moderate bloom but had high uncertainty, whereas severe blooms with low uncertainty were observed in the northwest part of the lake. The study gives insight on the spatial-temporal dynamics of algal blooms, and should help government and decision-makers outline policies and practices on bloom monitoring and prevention. The developed method provides a promising approach to estimate algal bloom risks under uncertainties. Copyright © 2014 Elsevier B.V. All rights reserved.

  13. Risks, uncertainty, vagueness

    International Nuclear Information System (INIS)

    Haefele, W.; Renn, O.; Erdmann, G.

    1990-01-01

    The notion of 'risk' is discussed in its social and technological contexts, leading to an investigation of the terms factuality, hypotheticality, uncertainty, and vagueness, and to the problems of acceptance and acceptability especially in the context of political decision finding. (DG) [de

  14. Addressing uncertainties in the ERICA Integrated Approach

    International Nuclear Information System (INIS)

    Oughton, D.H.; Agueero, A.; Avila, R.; Brown, J.E.; Copplestone, D.; Gilek, M.

    2008-01-01

    Like any complex environmental problem, ecological risk assessment of the impacts of ionising radiation is confounded by uncertainty. At all stages, from problem formulation through to risk characterisation, the assessment is dependent on models, scenarios, assumptions and extrapolations. These include technical uncertainties related to the data used, conceptual uncertainties associated with models and scenarios, as well as social uncertainties such as economic impacts, the interpretation of legislation, and the acceptability of the assessment results to stakeholders. The ERICA Integrated Approach has been developed to allow an assessment of the risks of ionising radiation, and includes a number of methods that are intended to make the uncertainties and assumptions inherent in the assessment more transparent to users and stakeholders. Throughout its development, ERICA has recommended that assessors deal openly with the deeper dimensions of uncertainty and acknowledge that uncertainty is intrinsic to complex systems. Since the tool is based on a tiered approach, the approaches to dealing with uncertainty vary between the tiers, ranging from a simple, but highly conservative screening to a full probabilistic risk assessment including sensitivity analysis. This paper gives on overview of types of uncertainty that are manifest in ecological risk assessment and the ERICA Integrated Approach to dealing with some of these uncertainties

  15. Assessing risks for integrated water resource management: coping with uncertainty and the human factor

    Directory of Open Access Journals (Sweden)

    M. J. Polo

    2014-09-01

    Full Text Available Risk assessment for water resource planning must deal with the uncertainty associated with excess/scarcity situations and their costs. The projected actions for increasing water security usually involve an indirect "call-effect": the territory occupation/water use is increased following the achieved protection. In this work, flood and water demand in a mountainous semi-arid watershed in southern Spain are assessed by means of the stochastic simulation of extremes, when this human factor is/is not considered. The results show how not including this call-effect induced an underestimation of flood risk after protecting the floodplain of between 35 and 78 % in a 35-year planning horizon. Similarly, the pursued water availability of a new reservoir resulted in a 10-year scarcity risk increase up to 38 % when the trend of expanding the irrigated area was included in the simulations. These results highlight the need for including this interaction in the decision-making assessment.

  16. Managing project risks and uncertainties

    Directory of Open Access Journals (Sweden)

    Mike Mentis

    2015-01-01

    Full Text Available This article considers threats to a project slipping on budget, schedule and fit-for-purpose. Threat is used here as the collective for risks (quantifiable bad things that can happen and uncertainties (poorly or not quantifiable bad possible events. Based on experience with projects in developing countries this review considers that (a project slippage is due to uncertainties rather than risks, (b while eventuation of some bad things is beyond control, managed execution and oversight are still the primary means to keeping within budget, on time and fit-for-purpose, (c improving project delivery is less about bigger and more complex and more about coordinated focus, effectiveness and developing thought-out heuristics, and (d projects take longer and cost more partly because threat identification is inaccurate, the scope of identified threats is too narrow, and the threat assessment product is not integrated into overall project decision-making and execution. Almost by definition, what is poorly known is likely to cause problems. Yet it is not just the unquantifiability and intangibility of uncertainties causing project slippage, but that they are insufficiently taken into account in project planning and execution that cause budget and time overruns. Improving project performance requires purpose-driven and managed deployment of scarce seasoned professionals. This can be aided with independent oversight by deeply experienced panelists who contribute technical insights and can potentially show that diligence is seen to be done.

  17. RECOVERY ACT - Methods for Decision under Technological Change Uncertainty and Risk Assessment for Integrated Assessment of Climate Change

    Energy Technology Data Exchange (ETDEWEB)

    Webster, Mort D. [Pennsylvania State Univ., University Park, PA (United States). Dept. of Energy and Mineral Engineering

    2015-11-30

    This report presents the final outcomes and products of the project as performed both at the Massachusetts Institute of Technology and subsequently at Pennsylvania State University. The research project can be divided into three main components: methodology development for decision-making under uncertainty, improving the resolution of the electricity sector to improve integrated assessment, and application of these methods to integrated assessment.

  18. RECOVERY ACT - Methods for Decision under Technological Change Uncertainty and Risk Assessment for Integrated Assessment of Climate Change

    Energy Technology Data Exchange (ETDEWEB)

    Webster, Mort David [MIT

    2015-03-10

    This report presents the final outcomes and products of the project as performed at the Massachusetts Institute of Technology. The research project consists of three main components: methodology development for decision-making under uncertainty, improving the resolution of the electricity sector to improve integrated assessment, and application of these methods to integrated assessment. Results in each area is described in the report.

  19. Uncertainties in risk assessment at USDOE facilities

    Energy Technology Data Exchange (ETDEWEB)

    Hamilton, L.D.; Holtzman, S.; Meinhold, A.F.; Morris, S.C.; Rowe, M.D.

    1994-01-01

    The United States Department of Energy (USDOE) has embarked on an ambitious program to remediate environmental contamination at its facilities. Decisions concerning cleanup goals, choices among cleanup technologies, and funding prioritization should be largely risk-based. Risk assessments will be used more extensively by the USDOE in the future. USDOE needs to develop and refine risk assessment methods and fund research to reduce major sources of uncertainty in risk assessments at USDOE facilities. The terms{open_quote} risk assessment{close_quote} and{open_quote} risk management{close_quote} are frequently confused. The National Research Council (1983) and the United States Environmental Protection Agency (USEPA, 1991a) described risk assessment as a scientific process that contributes to risk management. Risk assessment is the process of collecting, analyzing and integrating data and information to identify hazards, assess exposures and dose responses, and characterize risks. Risk characterization must include a clear presentation of {open_quotes}... the most significant data and uncertainties...{close_quotes} in an assessment. Significant data and uncertainties are {open_quotes}...those that define and explain the main risk conclusions{close_quotes}. Risk management integrates risk assessment information with other considerations, such as risk perceptions, socioeconomic and political factors, and statutes, to make and justify decisions. Risk assessments, as scientific processes, should be made independently of the other aspects of risk management (USEPA, 1991a), but current methods for assessing health risks are based on conservative regulatory principles, causing unnecessary public concern and misallocation of funds for remediation.

  20. Uncertainties in risk assessment at USDOE facilities

    International Nuclear Information System (INIS)

    Hamilton, L.D.; Holtzman, S.; Meinhold, A.F.; Morris, S.C.; Rowe, M.D.

    1994-01-01

    The United States Department of Energy (USDOE) has embarked on an ambitious program to remediate environmental contamination at its facilities. Decisions concerning cleanup goals, choices among cleanup technologies, and funding prioritization should be largely risk-based. Risk assessments will be used more extensively by the USDOE in the future. USDOE needs to develop and refine risk assessment methods and fund research to reduce major sources of uncertainty in risk assessments at USDOE facilities. The terms open-quote risk assessment close-quote and open-quote risk management close-quote are frequently confused. The National Research Council (1983) and the United States Environmental Protection Agency (USEPA, 1991a) described risk assessment as a scientific process that contributes to risk management. Risk assessment is the process of collecting, analyzing and integrating data and information to identify hazards, assess exposures and dose responses, and characterize risks. Risk characterization must include a clear presentation of open-quotes... the most significant data and uncertainties...close quotes in an assessment. Significant data and uncertainties are open-quotes...those that define and explain the main risk conclusionsclose quotes. Risk management integrates risk assessment information with other considerations, such as risk perceptions, socioeconomic and political factors, and statutes, to make and justify decisions. Risk assessments, as scientific processes, should be made independently of the other aspects of risk management (USEPA, 1991a), but current methods for assessing health risks are based on conservative regulatory principles, causing unnecessary public concern and misallocation of funds for remediation

  1. The Uncertainties of Risk Management

    DEFF Research Database (Denmark)

    Vinnari, Eija; Skærbæk, Peter

    2014-01-01

    for expanding risk management. More generally, such uncertainties relate to the professional identities and responsibilities of operational managers as defined by the framing devices. Originality/value – The paper offers three contributions to the extant literature: first, it shows how risk management itself......Purpose – The purpose of this paper is to analyse the implementation of risk management as a tool for internal audit activities, focusing on unexpected effects or uncertainties generated during its application. Design/methodology/approach – Public and confidential documents as well as semi......-structured interviews are analysed through the lens of actor-network theory to identify the effects of risk management devices in a Finnish municipality. Findings – The authors found that risk management, rather than reducing uncertainty, itself created unexpected uncertainties that would otherwise not have emerged...

  2. Risk-Informed Safety Margin Characterization (RISMC): Integrated Treatment of Aleatory and Epistemic Uncertainty in Safety Analysis

    International Nuclear Information System (INIS)

    Youngblood, R.W.

    2010-01-01

    The concept of 'margin' has a long history in nuclear licensing and in the codification of good engineering practices. However, some traditional applications of 'margin' have been carried out for surrogate scenarios (such as design basis scenarios), without regard to the actual frequencies of those scenarios, and have been carried out with in a systematically conservative fashion. This means that the effectiveness of the application of the margin concept is determined in part by the original choice of surrogates, and is limited in any case by the degree of conservatism imposed on the evaluation. In the RISMC project, which is part of the Department of Energy's 'Light Water Reactor Sustainability Program' (LWRSP), we are developing a risk-informed characterization of safety margin. Beginning with the traditional discussion of 'margin' in terms of a 'load' (a physical challenge to system or component function) and a 'capacity' (the capability of that system or component to accommodate the challenge), we are developing the capability to characterize probabilistic load and capacity spectra, reflecting both aleatory and epistemic uncertainty in system response. For example, the probabilistic load spectrum will reflect the frequency of challenges of a particular severity. Such a characterization is required if decision-making is to be informed optimally. However, in order to enable the quantification of probabilistic load spectra, existing analysis capability needs to be extended. Accordingly, the INL is working on a next-generation safety analysis capability whose design will allow for much more efficient parameter uncertainty analysis, and will enable a much better integration of reliability-related and phenomenology-related aspects of margin.

  3. Risk, Uncertainty, and Entrepreneurship

    DEFF Research Database (Denmark)

    Koudstaal, Martin; Sloof, Randolph; Van Praag, Mirjam

    2016-01-01

    21288). The results indicate that entrepreneurs perceive themselves as less risk averse than managers and employees, in line with common wisdom. However, when using experimental incentivized measures, the differences are subtler. Entrepreneurs are only found to be unique in their lower degree of loss...... aversion, and not in their risk or ambiguity aversion. This combination of results might be explained by our finding that perceived risk attitude is not only correlated to risk aversion but also to loss aversion. Overall, we therefore suggest using a broader definition of risk that captures this unique...... feature of entrepreneurs: their willingness to risk losses....

  4. Risk, Uncertainty and Entrepreneurship

    DEFF Research Database (Denmark)

    Koudstaal, Martin; Sloof, Randolph; Van Praag, Mirjam

    . Entrepreneurs are only found to be unique in their lower degree of loss aversion, and not in their risk or ambiguity aversion. This combination of results might be explained by our finding that perceived risk attitude is not only correlated to risk aversion but also to loss aversion. Overall, we therefore...... entrepreneurs to managers – a suitable comparison group – and employees (n = 2288). The results indicate that entrepreneurs perceive themselves as less risk averse than managers and employees, in line with common wisdom. However, when using experimental incentivized measures, the differences are subtler...... suggest using a broader definition of risk that captures this unique feature of entrepreneurs; their willingness to risk losses....

  5. Integrating uncertainties for climate change mitigation

    Science.gov (United States)

    Rogelj, Joeri; McCollum, David; Reisinger, Andy; Meinshausen, Malte; Riahi, Keywan

    2013-04-01

    The target of keeping global average temperature increase to below 2°C has emerged in the international climate debate more than a decade ago. In response, the scientific community has tried to estimate the costs of reaching such a target through modelling and scenario analysis. Producing such estimates remains a challenge, particularly because of relatively well-known, but ill-quantified uncertainties, and owing to limited integration of scientific knowledge across disciplines. The integrated assessment community, on one side, has extensively assessed the influence of technological and socio-economic uncertainties on low-carbon scenarios and associated costs. The climate modelling community, on the other side, has worked on achieving an increasingly better understanding of the geophysical response of the Earth system to emissions of greenhouse gases (GHG). This geophysical response remains a key uncertainty for the cost of mitigation scenarios but has only been integrated with assessments of other uncertainties in a rudimentary manner, i.e., for equilibrium conditions. To bridge this gap between the two research communities, we generate distributions of the costs associated with limiting transient global temperature increase to below specific temperature limits, taking into account uncertainties in multiple dimensions: geophysical, technological, social and political. In other words, uncertainties resulting from our incomplete knowledge about how the climate system precisely reacts to GHG emissions (geophysical uncertainties), about how society will develop (social uncertainties and choices), which technologies will be available (technological uncertainty and choices), when we choose to start acting globally on climate change (political choices), and how much money we are or are not willing to spend to achieve climate change mitigation. We find that political choices that delay mitigation have the largest effect on the cost-risk distribution, followed by

  6. Uncertainty quantification in flood risk assessment

    Science.gov (United States)

    Blöschl, Günter; Hall, Julia; Kiss, Andrea; Parajka, Juraj; Perdigão, Rui A. P.; Rogger, Magdalena; Salinas, José Luis; Viglione, Alberto

    2017-04-01

    Uncertainty is inherent to flood risk assessments because of the complexity of the human-water system, which is characterised by nonlinearities and interdependencies, because of limited knowledge about system properties and because of cognitive biases in human perception and decision-making. On top of the uncertainty associated with the assessment of the existing risk to extreme events, additional uncertainty arises because of temporal changes in the system due to climate change, modifications of the environment, population growth and the associated increase in assets. Novel risk assessment concepts are needed that take into account all these sources of uncertainty. They should be based on the understanding of how flood extremes are generated and how they change over time. They should also account for the dynamics of risk perception of decision makers and population in the floodplains. In this talk we discuss these novel risk assessment concepts through examples from Flood Frequency Hydrology, Socio-Hydrology and Predictions Under Change. We believe that uncertainty quantification in flood risk assessment should lead to a robust approach of integrated flood risk management aiming at enhancing resilience rather than searching for optimal defense strategies.

  7. Approach to uncertainty in risk analysis

    Energy Technology Data Exchange (ETDEWEB)

    Rish, W.R.

    1988-08-01

    In the Fall of 1985 EPA's Office of Radiation Programs (ORP) initiated a project to develop a formal approach to dealing with uncertainties encountered when estimating and evaluating risks to human health and the environment. Based on a literature review of modeling uncertainty, interviews with ORP technical and management staff, and input from experts on uncertainty analysis, a comprehensive approach was developed. This approach recognizes by design the constraints on budget, time, manpower, expertise, and availability of information often encountered in ''real world'' modeling. It is based on the observation that in practice risk modeling is usually done to support a decision process. As such, the approach focuses on how to frame a given risk modeling problem, how to use that framing to select an appropriate mixture of uncertainty analyses techniques, and how to integrate the techniques into an uncertainty assessment that effectively communicates important information and insight to decision-makers. The approach is presented in this report. Practical guidance on characterizing and analyzing uncertainties about model form and quantities and on effectively communicating uncertainty analysis results is included. Examples from actual applications are presented.

  8. Approach to uncertainty in risk analysis

    International Nuclear Information System (INIS)

    Rish, W.R.

    1988-08-01

    In the Fall of 1985 EPA's Office of Radiation Programs (ORP) initiated a project to develop a formal approach to dealing with uncertainties encountered when estimating and evaluating risks to human health and the environment. Based on a literature review of modeling uncertainty, interviews with ORP technical and management staff, and input from experts on uncertainty analysis, a comprehensive approach was developed. This approach recognizes by design the constraints on budget, time, manpower, expertise, and availability of information often encountered in ''real world'' modeling. It is based on the observation that in practice risk modeling is usually done to support a decision process. As such, the approach focuses on how to frame a given risk modeling problem, how to use that framing to select an appropriate mixture of uncertainty analyses techniques, and how to integrate the techniques into an uncertainty assessment that effectively communicates important information and insight to decision-makers. The approach is presented in this report. Practical guidance on characterizing and analyzing uncertainties about model form and quantities and on effectively communicating uncertainty analysis results is included. Examples from actual applications are presented

  9. Risk uncertainty analysis methods for NUREG-1150

    International Nuclear Information System (INIS)

    Benjamin, A.S.; Boyd, G.J.

    1987-01-01

    Evaluation and display of risk uncertainties for NUREG-1150 constitute a principal focus of the Severe Accident Risk Rebaselining/Risk Reduction Program (SARRP). Some of the principal objectives of the uncertainty evaluation are: (1) to provide a quantitative estimate that reflects, for those areas considered, a credible and realistic range of uncertainty in risk; (2) to rank the various sources of uncertainty with respect to their importance for various measures of risk; and (3) to characterize the state of understanding of each aspect of the risk assessment for which major uncertainties exist. This paper describes the methods developed to fulfill these objectives

  10. Correlated uncertainties in integral data

    International Nuclear Information System (INIS)

    McCracken, A.K.

    1978-01-01

    The use of correlated uncertainties in calculational data is shown in cases investigated to lead to a reduction in the uncertainty of calculated quantities of importance to reactor design. It is stressed however that such reductions are likely to be important in a minority of cases of practical interest. The effect of uncertainties in detector cross-sections is considered and is seen to be, in some cases, of equal importance to that in the data used in calculations. Numerical investigations have been limited by the sparse information available on data correlations; some comparisons made of these data reveal quite large inconsistencies for both detector cross-sections and cross-section of interest for reactor calculations

  11. Risk Characterization uncertainties associated description, sensitivity analysis

    International Nuclear Information System (INIS)

    Carrillo, M.; Tovar, M.; Alvarez, J.; Arraez, M.; Hordziejewicz, I.; Loreto, I.

    2013-01-01

    The power point presentation is about risks to the estimated levels of exposure, uncertainty and variability in the analysis, sensitivity analysis, risks from exposure to multiple substances, formulation of guidelines for carcinogenic and genotoxic compounds and risk subpopulations

  12. The Stock Market: Risk vs. Uncertainty.

    Science.gov (United States)

    Griffitts, Dawn

    2002-01-01

    This economics education publication focuses on the U.S. stock market and the risk and uncertainty that an individual faces when investing in the market. The material explains that risk and uncertainty relate to the same underlying concept randomness. It defines and discusses both concepts and notes that although risk is quantifiable, uncertainty…

  13. Scientific uncertainties and climate risks

    International Nuclear Information System (INIS)

    Petit, M.

    2005-01-01

    Human activities have induced a significant change in the Earth's atmospheric composition and, most likely, this trend will increase throughout the coming decades. During the last decades, the mean temperature has actually increased by the expected amount. Moreover, the geographical distribution of the warming, and day-to-night temperature variation have evolved as predicted. The magnitude of those changes is relatively small for the time being, but is expected to increase alarmingly during the coming decades. Greenhouse warming is a representative example of the problems of sustainable development: long-term risks can be estimated on a rational basis from scientific laws alone, but the non-specialist is generally not prepared to understand the steps required. However, even the non-specialist has obviously the right to decide about his way of life and the inheritance that he would like to leave for his children, but it is preferable that he is fully informed before making his decisions. Dialog, mutual understanding and confidence must prevail between Science and Society to avoid irrational actions. Controversy among experts is quite frequent. In the case of greenhouse warming, a commendable collective expertise has drastically reduced possible confusion. The Intergovernmental Panel on Climate Change was created jointly by the World Meteorology Organization (WMO) and the UN Program for the Environment (UNEP). Its reports evaluate the state of knowledge on past and future global climate changes, their impact, and the possibility of controlling anthropogenic emissions. The main targeted readers are, nevertheless, non-specialists, who should be made aware of results deduced from approaches that they may not be able to follow step by step. Moreover, these results, in particular, future projections, are, and will remain, subject to some uncertainty, which a fair description of the state of knowledge must include. Many misunderstandings between writers and readers can

  14. Uncertainty governance: an integrated framework for managing and communicating uncertainties

    International Nuclear Information System (INIS)

    Umeki, H.; Naito, M.; Takase, H.

    2004-01-01

    Treatment of uncertainty, or in other words, reasoning with imperfect information is widely recognised as being of great importance within performance assessment (PA) of the geological disposal mainly because of the time scale of interest and spatial heterogeneity that geological environment exhibits. A wide range of formal methods have been proposed for the optimal processing of incomplete information. Many of these methods rely on the use of numerical information, the frequency based concept of probability in particular, to handle the imperfections. However, taking quantitative information as a base for models that solve the problem of handling imperfect information merely creates another problem, i.e., how to provide the quantitative information. In many situations this second problem proves more resistant to solution, and in recent years several authors have looked at a particularly ingenious way in accordance with the rules of well-founded methods such as Bayesian probability theory, possibility theory, and the Dempster-Shafer theory of evidence. Those methods, while drawing inspiration from quantitative methods, do not require the kind of complete numerical information required by quantitative methods. Instead they provide information that, though less precise than that provided by quantitative techniques, is often, if not sufficient, the best that could be achieved. Rather than searching for the best method for handling all imperfect information, our strategy for uncertainty management, that is recognition and evaluation of uncertainties associated with PA followed by planning and implementation of measures to reduce them, is to use whichever method best fits the problem at hand. Such an eclectic position leads naturally to integration of the different formalisms. While uncertainty management based on the combination of semi-quantitative methods forms an important part of our framework for uncertainty governance, it only solves half of the problem

  15. Analysis of uncertainty in modeling perceived risks

    International Nuclear Information System (INIS)

    Melnyk, R.; Sandquist, G.M.

    2005-01-01

    Expanding on a mathematical model developed for quantifying and assessing perceived risks, the distribution functions, variances, and uncertainties associated with estimating the model parameters are quantified. The analytical model permits the identification and assignment of any number of quantifiable risk perception factors that can be incorporated within standard risk methodology. Those risk perception factors associated with major technical issues are modeled using lognormal probability density functions to span the potentially large uncertainty variations associated with these risk perceptions. The model quantifies the logic of public risk perception and provides an effective means for measuring and responding to perceived risks. (authors)

  16. Review of studies related to uncertainty in risk analsis

    International Nuclear Information System (INIS)

    Rish, W.R.; Marnicio, R.J.

    1988-08-01

    The Environmental Protection Agency's Office of Radiation Programs (ORP) is responsible for regulating on a national level the risks associated with technological sources of ionizing radiation in the environment. A critical activity of the ORP is analyzing and evaluating risk. The ORP believes that the analysis of uncertainty should be an integral part of any risk assessment; therefore, the ORP has initiated a project to develop framework for the treatment of uncertainty in risk analysis. Summaries of recent studies done in five areas of study are presented

  17. Review of studies related to uncertainty in risk analsis

    Energy Technology Data Exchange (ETDEWEB)

    Rish, W.R.; Marnicio, R.J.

    1988-08-01

    The Environmental Protection Agency's Office of Radiation Programs (ORP) is responsible for regulating on a national level the risks associated with technological sources of ionizing radiation in the environment. A critical activity of the ORP is analyzing and evaluating risk. The ORP believes that the analysis of uncertainty should be an integral part of any risk assessment; therefore, the ORP has initiated a project to develop framework for the treatment of uncertainty in risk analysis. Summaries of recent studies done in five areas of study are presented.

  18. Risk Aversion, Price Uncertainty and Irreversible Investments

    NARCIS (Netherlands)

    van den Goorbergh, R.W.J.; Huisman, K.J.M.; Kort, P.M.

    2003-01-01

    This paper generalizes the theory of irreversible investment under uncertainty by allowing for risk averse investors in the absence of com-plete markets.Until now this theory has only been developed in the cases of risk neutrality, or risk aversion in combination with complete markets.Within a

  19. Farm decision making under risk and uncertainty.

    NARCIS (Netherlands)

    Backus, G.B.C.; Eidman, V.R.; Dijkhuizen, A.A.

    1997-01-01

    Relevant portions of the risk literature are reviewed, relating them to observed behaviour in farm decision-making. Relevant topics for applied agricultural risk research are proposed. The concept of decision making under risk and uncertainty is discussed by reviewing the theory of Subjective

  20. Attitudes, beliefs, uncertainty and risk

    Energy Technology Data Exchange (ETDEWEB)

    Greenhalgh, Geoffrey [Down Park Place, Crawley Down (United Kingdom)

    2001-07-01

    There is now unmistakable evidence of a widening split within the Western industrial nations arising from conflicting views of society; for and against change. The argument is over the benefits of 'progress' and growth. On one side are those who seek more jobs, more production and consumption, higher standards of living, an ever-increasing GNP with an increasing globalisation of production and welcome the advances of science and technology confident that any temporary problems that arise can be solved by further technological development - possible energy shortages as a growing population increases energy usage can be met by nuclear power development; food shortages by the increased yields of GM crops. In opposition are those who put the quality of life before GNP, advocate a more frugal life-style, reducing needs and energy consumption, and, pointing to the harm caused by increasing pollution, press for cleaner air and water standards. They seek to reduce the pressure of an ever-increasing population and above all to preserve the natural environment. This view is associated with a growing uncertainty as the established order is challenged with the rise in status of 'alternative' science and medicine. This paper argues that these conflicting views reflect instinctive attitudes. These in turn draw support from beliefs selected from those which uncertainty offers. Where there is scope for argument over the truth or validity of a 'fact', the choice of which of the disputed views to believe will be determined by a value judgement. This applies to all controversial social and political issues. Nuclear waste disposal and biotechnology are but two particular examples in the technological field; joining the EMU is a current political controversy where value judgements based on attitudes determine beliefs. When, or if, a controversy is finally resolved the judgement arrived at will be justified by the belief that the consequences of the course chosen will be more favourable

  1. Attitudes, beliefs, uncertainty and risk

    Energy Technology Data Exchange (ETDEWEB)

    Greenhalgh, Geoffrey [Down Park Place, Crawley Down (United Kingdom)

    2001-07-01

    There is now unmistakable evidence of a widening split within the Western industrial nations arising from conflicting views of society; for and against change. The argument is over the benefits of 'progress' and growth. On one side are those who seek more jobs, more production and consumption, higher standards of living, an ever-increasing GNP with an increasing globalisation of production and welcome the advances of science and technology confident that any temporary problems that arise can be solved by further technological development - possible energy shortages as a growing population increases energy usage can be met by nuclear power development; food shortages by the increased yields of GM crops. In opposition are those who put the quality of life before GNP, advocate a more frugal life-style, reducing needs and energy consumption, and, pointing to the harm caused by increasing pollution, press for cleaner air and water standards. They seek to reduce the pressure of an ever-increasing population and above all to preserve the natural environment. This view is associated with a growing uncertainty as the established order is challenged with the rise in status of 'alternative' science and medicine. This paper argues that these conflicting views reflect instinctive attitudes. These in turn draw support from beliefs selected from those which uncertainty offers. Where there is scope for argument over the truth or validity of a 'fact', the choice of which of the disputed views to believe will be determined by a value judgement. This applies to all controversial social and political issues. Nuclear waste disposal and biotechnology are but two particular examples in the technological field; joining the EMU is a current political controversy where value judgements based on attitudes determine beliefs. When, or if, a controversy is finally resolved the judgement arrived at will be justified by the belief that the consequences of the course

  2. Attitudes, beliefs, uncertainty and risk

    International Nuclear Information System (INIS)

    Greenhalgh, Geoffrey

    2001-01-01

    There is now unmistakable evidence of a widening split within the Western industrial nations arising from conflicting views of society; for and against change. The argument is over the benefits of 'progress' and growth. On one side are those who seek more jobs, more production and consumption, higher standards of living, an ever-increasing GNP with an increasing globalisation of production and welcome the advances of science and technology confident that any temporary problems that arise can be solved by further technological development - possible energy shortages as a growing population increases energy usage can be met by nuclear power development; food shortages by the increased yields of GM crops. In opposition are those who put the quality of life before GNP, advocate a more frugal life-style, reducing needs and energy consumption, and, pointing to the harm caused by increasing pollution, press for cleaner air and water standards. They seek to reduce the pressure of an ever-increasing population and above all to preserve the natural environment. This view is associated with a growing uncertainty as the established order is challenged with the rise in status of 'alternative' science and medicine. This paper argues that these conflicting views reflect instinctive attitudes. These in turn draw support from beliefs selected from those which uncertainty offers. Where there is scope for argument over the truth or validity of a 'fact', the choice of which of the disputed views to believe will be determined by a value judgement. This applies to all controversial social and political issues. Nuclear waste disposal and biotechnology are but two particular examples in the technological field; joining the EMU is a current political controversy where value judgements based on attitudes determine beliefs. When, or if, a controversy is finally resolved the judgement arrived at will be justified by the belief that the consequences of the course chosen will be more favourable

  3. Uncertainties in risk assessment and decision making

    International Nuclear Information System (INIS)

    Starzec, Peter; Purucker, Tom; Stewart, Robert

    2008-02-01

    The general concept for risk assessment in accordance with the Swedish model for contaminated soil implies that the toxicological reference value for a given receptor is first back-calculated to a corresponding concentration of a compound in soil and (if applicable) then modified with respect to e.g. background levels, acute toxicity, and factor of safety. This result in a guideline value that is subsequently compared to the observed concentration levels. Many sources of uncertainty exist when assessing whether the risk for a receptor is significant or not. In this study, the uncertainty aspects have been addressed from three standpoints: 1. Uncertainty in the comparison between the level of contamination (source) and a given risk criterion (e.g. a guideline value) and possible implications on subsequent decisions. This type of uncertainty is considered to be most important in situations where a contaminant is expected to be spatially heterogeneous without any tendency to form isolated clusters (hotspots) that can be easily delineated, i.e. where mean values are appropriate to compare to the risk criterion. 2. Uncertainty in spatial distribution of a contaminant. Spatial uncertainty should be accounted for when hotspots are to be delineated and the volume of soil contaminated with levels above a stated decision criterion has to be assessed (quantified). 3. Uncertainty in an ecological exposure model with regard to the moving pattern of a receptor in relation to spatial distribution of contaminant in question. The study points out that the choice of methodology to characterize the relation between contaminant concentration and a pre-defined risk criterion is governed by a conceptual perception of the contaminant's spatial distribution and also depends on the structure of collected data (observations). How uncertainty in transition from contaminant concentration into risk criterion can be quantified was demonstrated by applying hypothesis tests and the concept of

  4. Political uncertainty and firm risk in China

    Directory of Open Access Journals (Sweden)

    Danglun Luo

    2017-12-01

    Full Text Available The political uncertainty surrounded by the turnover of government officials has a major impact on local economies and local firms. This paper investigates the relationship between the turnover of prefecture-city officials and the inherent risk faced by local firms in China. Using data from 1999 to 2012, we find that prefecture-city official turnovers significantly increased firm risk. Our results show that the political risk was mitigated when new prefecture-city officials were well connected with their provincial leaders. In addition, the impact of political uncertainty was more pronounced for regulated firms and firms residing in provinces with low market openness.

  5. Risk Assessment Uncertainties in Cybersecurity Investments

    Directory of Open Access Journals (Sweden)

    Andrew Fielder

    2018-06-01

    Full Text Available When undertaking cybersecurity risk assessments, it is important to be able to assign numeric values to metrics to compute the final expected loss that represents the risk that an organization is exposed to due to cyber threats. Even if risk assessment is motivated by real-world observations and data, there is always a high chance of assigning inaccurate values due to different uncertainties involved (e.g., evolving threat landscape, human errors and the natural difficulty of quantifying risk. Existing models empower organizations to compute optimal cybersecurity strategies given their financial constraints, i.e., available cybersecurity budget. Further, a general game-theoretic model with uncertain payoffs (probability-distribution-valued payoffs shows that such uncertainty can be incorporated in the game-theoretic model by allowing payoffs to be random. This paper extends previous work in the field to tackle uncertainties in risk assessment that affect cybersecurity investments. The findings from simulated examples indicate that although uncertainties in cybersecurity risk assessment lead, on average, to different cybersecurity strategies, they do not play a significant role in the final expected loss of the organization when utilising a game-theoretic model and methodology to derive these strategies. The model determines robust defending strategies even when knowledge regarding risk assessment values is not accurate. As a result, it is possible to show that the cybersecurity investments’ tool is capable of providing effective decision support.

  6. Methods for Addressing Uncertainty and Variability to Characterize Potential Health Risk From Trichloroethylene-Contaminated Ground Water Beale Air Force Base in California: Integration of Uncertainty and Variability in Pharmacokinetics and Dose-Response; TOPICAL

    International Nuclear Information System (INIS)

    Bogen, K.T.

    1999-01-01

    Traditional estimates of health risk are typically inflated, particularly if cancer is the dominant endpoint and there is fundamental uncertainty as to mechanism(s) of action. Risk is more realistically characterized if it accounts for joint uncertainty and interindividual variability after applying a unified probabilistic approach to the distributed parameters of all (linear as well as nonlinear) risk-extrapolation models involved. Such an approach was applied to characterize risks to potential future residents posed by trichloroethylene (TCE) in ground water at an inactive landfill site on Beale Air Force Base in California. Variability and uncertainty were addressed in exposure-route-specific estimates of applied dose, in pharmacokinetically based estimates of route-specific metabolized fractions of absorbed TCE, and in corresponding biologically effective doses estimated under a genotoxic/linear (MA(sub g)) vs. a cytotoxic/nonlinear (MA(sub c)) mechanistic assumption for TCE-induced cancer. Increased risk conditional on effective dose was estimated under MA(sub G) based on seven rodent-bioassay data sets, and under MA, based on mouse hepatotoxicity data. Mean and upper-bound estimates of combined risk calculated by the unified approach were and lt;10(sup -6) and and lt;10(sup -4), respectively, while corresponding estimates based on traditional deterministic methods were and gt;10(sup -5) and and gt;10(sup -4), respectively. It was estimated that no TCE-related harm is likely occur due any plausible residential exposure scenario involving the site. The unified approach illustrated is particularly suited to characterizing risks that involve uncertain and/or diverse mechanisms of action

  7. Climate policy uncertainty and investment risk

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2007-06-21

    Our climate is changing. This is certain. Less certain, however, is the timing and magnitude of climate change, and the cost of transition to a low-carbon world. Therefore, many policies and programmes are still at a formative stage, and policy uncertainty is very high. This book identifies how climate change policy uncertainty may affect investment behaviour in the power sector. For power companies, where capital stock is intensive and long-lived, those risks rank among the biggest and can create an incentive to delay investment. Our analysis results show that the risk premiums of climate change uncertainty can add 40% of construction costs of the plant for power investors, and 10% of price surcharges for the electricity end-users. This publication tells what can be done in policy design to reduce these costs. Incorporating the results of quantitative analysis, this publication also shows the sensitivity of different power sector investment decisions to different risks. It compares the effects of climate policy uncertainty with energy market uncertainty, showing the relative importance of these sources of risk for different technologies in different market types. Drawing on extensive consultation with power companies and financial investors, it also assesses the implications for policy makers, allowing the key messages to be transferred into policy designs. This book is a useful tool for governments to improve climate policy mechanisms and create more certainty for power investors.

  8. Managing Uncertainty for an Integrated Fishery

    Directory of Open Access Journals (Sweden)

    MB Hasan

    2012-06-01

    Full Text Available This paper investigates ways to deal with the uncertainties in fishing trawler scheduling and production planning in a quota-based integrated commercial fishery. A commercial fishery faces uncertainty mainly from variation in catch rate, which may be due to weather, and other environmental factors. The firm tries to manage this uncertainty through planning co-ordination of fishing trawler scheduling, catch quota, processing and labour allocation, and inventory control. Scheduling must necessarily be done over some finite planning horizon, and the trawler schedule itself introduces man-made variability, which in turn induces inventory in the processing plant. This induced inventory must be managed, complicated by the inability to plan easily beyond the current planning horizon. We develop a surprisingly simple innovation in inventory, which we have not seen in other papers on production management, which of requiring beginning inventory to equal ending inventory. This tool gives management a way to calculate a profit-maximizing safety stock that counter-acts the man-made variability due to the trawler scheduling. We found that the variability of catch rate had virtually no effects on the profitability with inventory. We report numerical results for several planning horizon models, based on data for a major New Zealand fishery.

  9. Risk Management and Uncertainty in Infrastructure Projects

    DEFF Research Database (Denmark)

    Harty, Chris; Neerup Themsen, Tim; Tryggestad, Kjell

    2014-01-01

    The assumption that large complex projects should be managed in order to reduce uncertainty and increase predictability is not new. What is relatively new, however, is that uncertainty reduction can and should be obtained through formal risk management approaches. We question both assumptions...... by addressing a more fundamental question about the role of knowledge in current risk management practices. Inquiries into the predominant approaches to risk management in large infrastructure and construction projects reveal their assumptions about knowledge and we discuss the ramifications these have...... for project and construction management. Our argument and claim is that predominant risk management approaches tends to reinforce conventional ideas of project control whilst undermining other notions of value and relevance of built assets and project management process. These approaches fail to consider...

  10. GENERAL RISKS AND UNCERTAINTIES OF REPORTING AND MANAGEMENT REPORTING RISKS

    Directory of Open Access Journals (Sweden)

    CAMELIA I. LUNGU

    2011-04-01

    Full Text Available Purpose: Highlighting risks and uncertainties reporting based on a literature review research. Objectives: The delimitation of risk management models and uncertainties in fundamental research. Research method: Fundamental research study directed to identify the relevant risks’ models presented in entities’ financial statements. Uncertainty is one of the fundamental coordinates of our world. As showed J.K. Galbraith (1978, the world now lives under the age of uncertainty. Moreover, we can say that contemporary society development could be achieved by taking decisions under uncertainty, though, risks. Growing concern for the study of uncertainty, its effects and precautions led to the rather recent emergence of a new science, science of hazards (les cindyniques - l.fr. (Kenvern, 1991. Current analysis of risk are dominated by Beck’s (1992 notion that a risk society now exists whereby we have become more concerned about our impact upon nature than the impact of nature upon us. Clearly, risk permeates most aspects of corporate but also of regular life decision-making and few can predict with any precision the future. The risk is almost always a major variable in real-world corporate decision-making, and managers that ignore it are in a real peril. In these circumstances, a possible answer is assuming financial discipline with an appropriate system of incentives.

  11. Assessment and uncertainty analysis of groundwater risk.

    Science.gov (United States)

    Li, Fawen; Zhu, Jingzhao; Deng, Xiyuan; Zhao, Yong; Li, Shaofei

    2018-01-01

    Groundwater with relatively stable quantity and quality is commonly used by human being. However, as the over-mining of groundwater, problems such as groundwater funnel, land subsidence and salt water intrusion have emerged. In order to avoid further deterioration of hydrogeological problems in over-mining regions, it is necessary to conduct the assessment of groundwater risk. In this paper, risks of shallow and deep groundwater in the water intake area of the South-to-North Water Transfer Project in Tianjin, China, were evaluated. Firstly, two sets of four-level evaluation index system were constructed based on the different characteristics of shallow and deep groundwater. Secondly, based on the normalized factor values and the synthetic weights, the risk values of shallow and deep groundwater were calculated. Lastly, the uncertainty of groundwater risk assessment was analyzed by indicator kriging method. The results meet the decision maker's demand for risk information, and overcome previous risk assessment results expressed in the form of deterministic point estimations, which ignore the uncertainty of risk assessment. Copyright © 2017 Elsevier Inc. All rights reserved.

  12. Developing methodology and tools for integrated assessment of the risks of global environmental change: Analyzing uncertainty, risk assessment, risk perception, expert judgment, and a case study on sea level rise. Report of collaborative research, July 1991--June 1993: Final report

    International Nuclear Information System (INIS)

    Lancaster, J.; Shlyakhter, A.; Wilson, R.

    1993-01-01

    Members of Congress, federal administrators, state regulators, city planners, corporate strategists and private citizens face decisions that may or may not warrant considering the potential impacts of climate change. The extent to which the global warming issue will weigh in these many decisions will be determined by (a) expert scientific judgement about global warming and its potential impacts, (b) public perception of the global warming problem, (c) uncertainties, and (d) other legal and political factors controlling the entry of a large-scale environmental issue into many avenues of decision making. The complexity and uncertainty surrounding the problem of climate change present new challenges to our ability to formulate rational decisions. The authors provide a methodical approach to characterizing the risks of global warming in a way that will be useful to decision makers

  13. Integrated risk analysis of global climate change

    International Nuclear Information System (INIS)

    Shlyakhter, Alexander; Wilson, Richard; Valverde A, L.J. Jr.

    1995-01-01

    This paper discusses several factors that should be considered in integrated risk analyses of global climate change. We begin by describing how the problem of global climate change can be subdivided into largely independent parts that can be linked together in an analytically tractable fashion. Uncertainty plays a central role in integrated risk analyses of global climate change. Accordingly, we consider various aspects of uncertainty as they relate to the climate change problem. We also consider the impacts of these uncertainties on various risk management issues, such as sequential decision strategies, value of information, and problems of interregional and intergenerational equity. (author)

  14. Assessment of Risks and Uncertainties in Poultry Farming in Kwara ...

    African Journals Online (AJOL)

    , identify the risks and uncertainties encountered by the farmers, determines the level of severity of the risks and uncertainties, and identifies the coping strategies employed by the farmers. Primary data obtained from 99 registered poultry ...

  15. Where do uncertainties reside within environmental risk assessments? Expert opinion on uncertainty distributions for pesticide risks to surface water organisms.

    Science.gov (United States)

    Skinner, Daniel J C; Rocks, Sophie A; Pollard, Simon J T

    2016-12-01

    A reliable characterisation of uncertainties can aid uncertainty identification during environmental risk assessments (ERAs). However, typologies can be implemented inconsistently, causing uncertainties to go unidentified. We present an approach based on nine structured elicitations, in which subject-matter experts, for pesticide risks to surface water organisms, validate and assess three dimensions of uncertainty: its level (the severity of uncertainty, ranging from determinism to ignorance); nature (whether the uncertainty is epistemic or aleatory); and location (the data source or area in which the uncertainty arises). Risk characterisation contains the highest median levels of uncertainty, associated with estimating, aggregating and evaluating the magnitude of risks. Regarding the locations in which uncertainty is manifest, data uncertainty is dominant in problem formulation, exposure assessment and effects assessment. The comprehensive description of uncertainty described will enable risk analysts to prioritise the required phases, groups of tasks, or individual tasks within a risk analysis according to the highest levels of uncertainty, the potential for uncertainty to be reduced or quantified, or the types of location-based uncertainty, thus aiding uncertainty prioritisation during environmental risk assessments. In turn, it is expected to inform investment in uncertainty reduction or targeted risk management action. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

  16. Information-integration category learning and the human uncertainty response.

    Science.gov (United States)

    Paul, Erick J; Boomer, Joseph; Smith, J David; Ashby, F Gregory

    2011-04-01

    The human response to uncertainty has been well studied in tasks requiring attention and declarative memory systems. However, uncertainty monitoring and control have not been studied in multi-dimensional, information-integration categorization tasks that rely on non-declarative procedural memory. Three experiments are described that investigated the human uncertainty response in such tasks. Experiment 1 showed that following standard categorization training, uncertainty responding was similar in information-integration tasks and rule-based tasks requiring declarative memory. In Experiment 2, however, uncertainty responding in untrained information-integration tasks impaired the ability of many participants to master those tasks. Finally, Experiment 3 showed that the deficit observed in Experiment 2 was not because of the uncertainty response option per se, but rather because the uncertainty response provided participants a mechanism via which to eliminate stimuli that were inconsistent with a simple declarative response strategy. These results are considered in the light of recent models of category learning and metacognition.

  17. Risk and Uncertainty in Production Economics | Otaha | African ...

    African Journals Online (AJOL)

    One of the most celebrated and feared concepts in the World today are risk which is the product of uncertainty. Risk and uncertainty are often used interchangeably by many economists as if they are the same thing, but it is not true. While risk can be measured and estimated, and even ensured, uncertainty can not.

  18. Forecasting Investment Risks in Conditions of Uncertainty

    Directory of Open Access Journals (Sweden)

    Andrenko Elena A.

    2017-04-01

    Full Text Available The article is aimed at studying the topical problem of evaluation and forecasting risks of investment activity of enterprises in conditions of uncertainty. Generalizing the researches on qualitative and quantitative methods for evaluating investment risks has helped to reveal certain shortcomings of the proposed approaches, to note in most of the publications there are no results as to any practical application, and to allocate promising directions. On the basis of the theory of fuzzy sets, a model of forecasting the expected risk has been proposed, making use of the Gauss membership function, which has certain advantages over the multi-angular membership functions. Dependences of investment risk from the parameters characterizing the investment project have been obtained. Using the formulas obtained, the total risk of investing in innovation project depending on the boundary conditions has been defined. As the researched target, index of profitability has been selected. The model provides the potential investors and developers with forecasting possible scenarios of investment process to make informed managerial decisions about the appropriateness of introduction and implementation of a project.

  19. Quantile uncertainty and value-at-risk model risk.

    Science.gov (United States)

    Alexander, Carol; Sarabia, José María

    2012-08-01

    This article develops a methodology for quantifying model risk in quantile risk estimates. The application of quantile estimates to risk assessment has become common practice in many disciplines, including hydrology, climate change, statistical process control, insurance and actuarial science, and the uncertainty surrounding these estimates has long been recognized. Our work is particularly important in finance, where quantile estimates (called Value-at-Risk) have been the cornerstone of banking risk management since the mid 1980s. A recent amendment to the Basel II Accord recommends additional market risk capital to cover all sources of "model risk" in the estimation of these quantiles. We provide a novel and elegant framework whereby quantile estimates are adjusted for model risk, relative to a benchmark which represents the state of knowledge of the authority that is responsible for model risk. A simulation experiment in which the degree of model risk is controlled illustrates how to quantify Value-at-Risk model risk and compute the required regulatory capital add-on for banks. An empirical example based on real data shows how the methodology can be put into practice, using only two time series (daily Value-at-Risk and daily profit and loss) from a large bank. We conclude with a discussion of potential applications to nonfinancial risks. © 2012 Society for Risk Analysis.

  20. Uncertainties of nanotechnology: environmental and health risks

    International Nuclear Information System (INIS)

    Delgado Ramos, Giancarlo

    2007-01-01

    The nanotechnology, as any leading edge technology, develops in the border of the unknown thing and, as such, it provokes a degree of uncertainty. On having manipulated the matter to a nanometric scale (thousand millionth of a meter), the potential risks suggest to be not only relatively unpredictable, but also imperceptible to our senses. In such a tenor, evaluating the eventual implications of the nanotechnological progress is a very complex task. And even more if we take into consideration all ethic, legal, socioeconomic, environmental and health issues. The present article evaluates studies and discourses related to promises about the use of nanostructures and their environmental impact. It also treats health impact by evaluating nanotechnology to medicine application, nano make-up and new cancer treatment.

  1. Characterizing spatial uncertainty when integrating social data in conservation planning.

    Science.gov (United States)

    Lechner, A M; Raymond, C M; Adams, V M; Polyakov, M; Gordon, A; Rhodes, J R; Mills, M; Stein, A; Ives, C D; Lefroy, E C

    2014-12-01

    Recent conservation planning studies have presented approaches for integrating spatially referenced social (SRS) data with a view to improving the feasibility of conservation action. We reviewed the growing conservation literature on SRS data, focusing on elicited or stated preferences derived through social survey methods such as choice experiments and public participation geographic information systems. Elicited SRS data includes the spatial distribution of willingness to sell, willingness to pay, willingness to act, and assessments of social and cultural values. We developed a typology for assessing elicited SRS data uncertainty which describes how social survey uncertainty propagates when projected spatially and the importance of accounting for spatial uncertainty such as scale effects and data quality. These uncertainties will propagate when elicited SRS data is integrated with biophysical data for conservation planning and may have important consequences for assessing the feasibility of conservation actions. To explore this issue further, we conducted a systematic review of the elicited SRS data literature. We found that social survey uncertainty was commonly tested for, but that these uncertainties were ignored when projected spatially. Based on these results we developed a framework which will help researchers and practitioners estimate social survey uncertainty and use these quantitative estimates to systematically address uncertainty within an analysis. This is important when using SRS data in conservation applications because decisions need to be made irrespective of data quality and well characterized uncertainty can be incorporated into decision theoretic approaches. © 2014 Society for Conservation Biology.

  2. Accounting for Households' Perceived Income Uncertainty in Consumption Risk Sharing

    NARCIS (Netherlands)

    Singh, S.; Stoltenberg, C.A.

    2017-01-01

    We develop a consumption risk-sharing model that distinguishes households' perceived income uncertainty from income uncertainty as measured by an econometrician. Households receive signals on their future disposable income that can drive a gap between the two uncertainties. Accounting for the

  3. Sensitivity to Uncertainty in Asteroid Impact Risk Assessment

    Science.gov (United States)

    Mathias, D.; Wheeler, L.; Prabhu, D. K.; Aftosmis, M.; Dotson, J.; Robertson, D. K.

    2015-12-01

    The Engineering Risk Assessment (ERA) team at NASA Ames Research Center is developing a physics-based impact risk model for probabilistically assessing threats from potential asteroid impacts on Earth. The model integrates probabilistic sampling of asteroid parameter ranges with physics-based analyses of entry, breakup, and impact to estimate damage areas and casualties from various impact scenarios. Assessing these threats is a highly coupled, dynamic problem involving significant uncertainties in the range of expected asteroid characteristics, how those characteristics may affect the level of damage, and the fidelity of various modeling approaches and assumptions. The presented model is used to explore the sensitivity of impact risk estimates to these uncertainties in order to gain insight into what additional data or modeling refinements are most important for producing effective, meaningful risk assessments. In the extreme cases of very small or very large impacts, the results are generally insensitive to many of the characterization and modeling assumptions. However, the nature of the sensitivity can change across moderate-sized impacts. Results will focus on the value of additional information in this critical, mid-size range, and how this additional data can support more robust mitigation decisions.

  4. Uncertainty propagation in probabilistic risk assessment: A comparative study

    International Nuclear Information System (INIS)

    Ahmed, S.; Metcalf, D.R.; Pegram, J.W.

    1982-01-01

    Three uncertainty propagation techniques, namely method of moments, discrete probability distribution (DPD), and Monte Carlo simulation, generally used in probabilistic risk assessment, are compared and conclusions drawn in terms of the accuracy of the results. For small uncertainty in the basic event unavailabilities, the three methods give similar results. For large uncertainty, the method of moments is in error, and the appropriate method is to propagate uncertainty in the discrete form either by DPD method without sampling or by Monte Carlo. (orig.)

  5. Assessing scenario and parametric uncertainties in risk analysis: a model uncertainty audit

    International Nuclear Information System (INIS)

    Tarantola, S.; Saltelli, A.; Draper, D.

    1999-01-01

    In the present study a process of model audit is addressed on a computational model used for predicting maximum radiological doses to humans in the field of nuclear waste disposal. Global uncertainty and sensitivity analyses are employed to assess output uncertainty and to quantify the contribution of parametric and scenario uncertainties to the model output. These tools are of fundamental importance for risk analysis and decision making purposes

  6. Risk-sensitivity in Bayesian sensorimotor integration.

    Directory of Open Access Journals (Sweden)

    Jordi Grau-Moya

    Full Text Available Information processing in the nervous system during sensorimotor tasks with inherent uncertainty has been shown to be consistent with Bayesian integration. Bayes optimal decision-makers are, however, risk-neutral in the sense that they weigh all possibilities based on prior expectation and sensory evidence when they choose the action with highest expected value. In contrast, risk-sensitive decision-makers are sensitive to model uncertainty and bias their decision-making processes when they do inference over unobserved variables. In particular, they allow deviations from their probabilistic model in cases where this model makes imprecise predictions. Here we test for risk-sensitivity in a sensorimotor integration task where subjects exhibit Bayesian information integration when they infer the position of a target from noisy sensory feedback. When introducing a cost associated with subjects' response, we found that subjects exhibited a characteristic bias towards low cost responses when their uncertainty was high. This result is in accordance with risk-sensitive decision-making processes that allow for deviations from Bayes optimal decision-making in the face of uncertainty. Our results suggest that both Bayesian integration and risk-sensitivity are important factors to understand sensorimotor integration in a quantitative fashion.

  7. Bayesian uncertainty analyses of probabilistic risk models

    International Nuclear Information System (INIS)

    Pulkkinen, U.

    1989-01-01

    Applications of Bayesian principles to the uncertainty analyses are discussed in the paper. A short review of the most important uncertainties and their causes is provided. An application of the principle of maximum entropy to the determination of Bayesian prior distributions is described. An approach based on so called probabilistic structures is presented in order to develop a method of quantitative evaluation of modelling uncertainties. The method is applied to a small example case. Ideas for application areas for the proposed method are discussed

  8. Gambling in Latin: incorporating uncertainty in risk management

    Energy Technology Data Exchange (ETDEWEB)

    Gratt, L.B.; Levin, L. (IWG Corporation, San Diego, CA (United States))

    1994-08-01

    Risk assessment uses assumptions based on differing degrees of conservatism. This complicates the understanding of the uncertainty in the final risk estimate. Uncertainties arise from each component of the risk assessment process: source terms, atmospheric transport, exposure, and dose response. Probabilistic modeling using Monte Carlo and Latin Square sampling techniques (reference to Gambling in Latin) allows for an improved approach to risk assessment and management. 16 refs., 1 fig., 1 tab.

  9. Risk, unexpected uncertainty, and estimation uncertainty: Bayesian learning in unstable settings.

    Directory of Open Access Journals (Sweden)

    Elise Payzan-LeNestour

    Full Text Available Recently, evidence has emerged that humans approach learning using Bayesian updating rather than (model-free reinforcement algorithms in a six-arm restless bandit problem. Here, we investigate what this implies for human appreciation of uncertainty. In our task, a Bayesian learner distinguishes three equally salient levels of uncertainty. First, the Bayesian perceives irreducible uncertainty or risk: even knowing the payoff probabilities of a given arm, the outcome remains uncertain. Second, there is (parameter estimation uncertainty or ambiguity: payoff probabilities are unknown and need to be estimated. Third, the outcome probabilities of the arms change: the sudden jumps are referred to as unexpected uncertainty. We document how the three levels of uncertainty evolved during the course of our experiment and how it affected the learning rate. We then zoom in on estimation uncertainty, which has been suggested to be a driving force in exploration, in spite of evidence of widespread aversion to ambiguity. Our data corroborate the latter. We discuss neural evidence that foreshadowed the ability of humans to distinguish between the three levels of uncertainty. Finally, we investigate the boundaries of human capacity to implement Bayesian learning. We repeat the experiment with different instructions, reflecting varying levels of structural uncertainty. Under this fourth notion of uncertainty, choices were no better explained by Bayesian updating than by (model-free reinforcement learning. Exit questionnaires revealed that participants remained unaware of the presence of unexpected uncertainty and failed to acquire the right model with which to implement Bayesian updating.

  10. Uncertainty in ecological risk assessment: A statistician's view

    International Nuclear Information System (INIS)

    Smith, E.P.

    1995-01-01

    Uncertainty is a topic that has different meanings to researchers, modelers, managers and policy makers. The perspective of this presentation will be on the modeling view of uncertainty and its quantitative assessment. The goal is to provide some insight into how a statistician visualizes and addresses the issue of uncertainty in ecological risk assessment problems. In ecological risk assessment, uncertainty arises from many sources and is of different type depending on what is studies, where it is studied and how it is studied. Some major sources and their impact are described. A variety of quantitative approaches to modeling uncertainty are characterized and a general taxonomy given. Examples of risk assessments of lake acidification, power plant impact assessment and the setting of standards for chemicals will be used discuss approaches to quantitative assessment of uncertainty and some of the potential difficulties

  11. Uncertainty analysis in the applications of nuclear probabilistic risk assessment

    International Nuclear Information System (INIS)

    Le Duy, T.D.

    2011-01-01

    The aim of this thesis is to propose an approach to model parameter and model uncertainties affecting the results of risk indicators used in the applications of nuclear Probabilistic Risk assessment (PRA). After studying the limitations of the traditional probabilistic approach to represent uncertainty in PRA model, a new approach based on the Dempster-Shafer theory has been proposed. The uncertainty analysis process of the proposed approach consists in five main steps. The first step aims to model input parameter uncertainties by belief and plausibility functions according to the data PRA model. The second step involves the propagation of parameter uncertainties through the risk model to lay out the uncertainties associated with output risk indicators. The model uncertainty is then taken into account in the third step by considering possible alternative risk models. The fourth step is intended firstly to provide decision makers with information needed for decision making under uncertainty (parametric and model) and secondly to identify the input parameters that have significant uncertainty contributions on the result. The final step allows the process to be continued in loop by studying the updating of beliefs functions given new data. The proposed methodology was implemented on a real but simplified application of PRA model. (author)

  12. Uncertainty management in integrated modelling, the IMAGE case

    International Nuclear Information System (INIS)

    Van der Sluijs, J.P.

    1995-01-01

    Integrated assessment models of global environmental problems play an increasingly important role in decision making. This use demands a good insight regarding the reliability of these models. In this paper we analyze uncertainty management in the IMAGE-project (Integrated Model to Assess the Greenhouse Effect). We use a classification scheme comprising type and source of uncertainty. Our analysis shows reliability analysis as main area for improvement. We briefly review a recently developed methodology, NUSAP (Numerical, Unit, Spread, Assessment and Pedigree), that systematically addresses the strength of data in terms of spread, reliability and scientific status (pedigree) of information. This approach is being tested through interviews with model builders. 3 tabs., 20 refs

  13. An introductory guide to uncertainty analysis in environmental and health risk assessment

    International Nuclear Information System (INIS)

    Hoffman, F.O.; Hammonds, J.S.

    1992-10-01

    To compensate for the potential for overly conservative estimates of risk using standard US Environmental Protection Agency methods, an uncertainty analysis should be performed as an integral part of each risk assessment. Uncertainty analyses allow one to obtain quantitative results in the form of confidence intervals that will aid in decision making and will provide guidance for the acquisition of additional data. To perform an uncertainty analysis, one must frequently rely on subjective judgment in the absence of data to estimate the range and a probability distribution describing the extent of uncertainty about a true but unknown value for each parameter of interest. This information is formulated from professional judgment based on an extensive review of literature, analysis of the data, and interviews with experts. Various analytical and numerical techniques are available to allow statistical propagation of the uncertainty in the model parameters to a statement of uncertainty in the risk to a potentially exposed individual. Although analytical methods may be straightforward for relatively simple models, they rapidly become complicated for more involved risk assessments. Because of the tedious efforts required to mathematically derive analytical approaches to propagate uncertainty in complicated risk assessments, numerical methods such as Monte Carlo simulation should be employed. The primary objective of this report is to provide an introductory guide for performing uncertainty analysis in risk assessments being performed for Superfund sites

  14. Use of quantitative uncertainty analysis for human health risk assessment

    International Nuclear Information System (INIS)

    Duncan, F.L.W.; Gordon, J.W.; Kelly, M.

    1994-01-01

    Current human health risk assessment method for environmental risks typically use point estimates of risk accompanied by qualitative discussions of uncertainty. Alternatively, Monte Carlo simulations may be used with distributions for input parameters to estimate the resulting risk distribution and descriptive risk percentiles. These two techniques are applied for the ingestion of 1,1=dichloroethene in ground water. The results indicate that Monte Carlo simulations provide significantly more information for risk assessment and risk management than do point estimates

  15. UNCERTAINTY IN THE PROCESS INTEGRATION FOR THE BIOREFINERIES DEVELOPMENT

    Directory of Open Access Journals (Sweden)

    Meilyn González Cortés

    2015-07-01

    Full Text Available This paper presents how the design approaches with high level of flexibility can reduce the additional costs of the strategies that apply overdesign factors to consider parameters with uncertainty that impact on the economic feasibility of a project. The elements with associate uncertainties and that are important in the configurations of the process integration under a biorefinery scheme are: raw material, raw material technologies of conversion, and variety of products that can be obtained. From the analysis it is obtained that in the raw materials and products with potentialities in a biorefinery scheme, there are external uncertainties such as availability, demands and prices in the market. Those external uncertainties can determine their impact on the biorefinery and also in the product prices we can find minimum and maximum limits that can be identified in intervals which should be considered for the project economic evaluation and the sensibility analysis due to varied conditions.

  16. The characterisation and evaluation of uncertainty in probabilistic risk analysis

    International Nuclear Information System (INIS)

    Parry, G.W.; Winter, P.W.

    1980-10-01

    The sources of uncertainty in probabilistic risk analysis are discussed using the event/fault tree methodology as an example. The role of statistics in quantifying these uncertainties is investigated. A class of uncertainties is identified which is, at present, unquantifiable, using either classical or Bayesian statistics. It is argued that Bayesian statistics is the more appropriate vehicle for the probabilistic analysis of rare events and a short review is given with some discussion on the representation of ignorance. (author)

  17. Decision-making under risk and uncertainty

    International Nuclear Information System (INIS)

    Gatev, G.I.

    2006-01-01

    Fuzzy sets and interval analysis tools to make computations and solve optimisation problems are presented. Fuzzy and interval extensions of Decision Theory criteria for decision-making under parametric uncertainty of prior information (probabilities, payoffs) are developed. An interval probability approach to the mean-value criterion is proposed. (author)

  18. Risk in technical and scientific studies: general introduction to uncertainty management and the concept of risk

    International Nuclear Information System (INIS)

    Apostolakis, G.E.

    2004-01-01

    George Apostolakis (MIT) presented an introduction to the concept of risk and uncertainty management and their use in technical and scientific studies. He noted that Quantitative Risk Assessment (QRA) provides support to the overall treatment of a system as an integrated socio-technical system. Specifically, QRA aims to answer the questions: - What can go wrong (e.g., accident sequences or scenarios)? - How likely are these sequences or scenarios? - What are the consequences of these sequences or scenarios? The Quantitative Risk Assessment deals with two major types of uncertainty. An assessment requires a 'model of the world', and this preferably would be a deterministic model based on underlying processes. In practice, there are uncertainties in this model of the world relating to variability or randomness that cannot be accounted for directly in a deterministic model and that may require a probabilistic or aleatory model. Both deterministic and aleatory models of the world have assumptions and parameters, and there are 'state-of-knowledge' or epistemic uncertainties associated with these. Sensitivity studies or eliciting expert opinion can be used to address the uncertainties in assumptions, and the level of confidence in parameter values can be characterised using probability distributions (pdfs). Overall, the distinction between aleatory and epistemic uncertainties is not always clear, and both can be treated mathematically in the same way. Lessons on safety assessments that can be learnt from experience at nuclear power plants are that beliefs about what is important can be wrong if a risk assessment is not performed. Also, precautionary approaches are not always conservative if failure modes are not identified. Nevertheless, it is important to recognize that uncertainties will remain despite a quantitative risk assessment: e.g., is the scenario list complete, are the models accepted as reasonable, and are parameter probability distributions representative of

  19. Uncertainty and risk in wildland fire management: A review

    Science.gov (United States)

    Matthew P. Thompson; Dave E. Calkin

    2011-01-01

    Wildland fire management is subject to manifold sources of uncertainty. Beyond the unpredictability of wildfire behavior, uncertainty stems from inaccurate/missing data, limited resource value measures to guide prioritization across fires and resources at risk, and an incomplete scientific understanding of ecological response to fire, of fire behavior response to...

  20. Risk assessment under deep uncertainty: A methodological comparison

    International Nuclear Information System (INIS)

    Shortridge, Julie; Aven, Terje; Guikema, Seth

    2017-01-01

    Probabilistic Risk Assessment (PRA) has proven to be an invaluable tool for evaluating risks in complex engineered systems. However, there is increasing concern that PRA may not be adequate in situations with little underlying knowledge to support probabilistic representation of uncertainties. As analysts and policy makers turn their attention to deeply uncertain hazards such as climate change, a number of alternatives to traditional PRA have been proposed. This paper systematically compares three diverse approaches for risk analysis under deep uncertainty (qualitative uncertainty factors, probability bounds, and robust decision making) in terms of their representation of uncertain quantities, analytical output, and implications for risk management. A simple example problem is used to highlight differences in the way that each method relates to the traditional risk assessment process and fundamental issues associated with risk assessment and description. We find that the implications for decision making are not necessarily consistent between approaches, and that differences in the representation of uncertain quantities and analytical output suggest contexts in which each method may be most appropriate. Finally, each methodology demonstrates how risk assessment can inform decision making in deeply uncertain contexts, informing more effective responses to risk problems characterized by deep uncertainty. - Highlights: • We compare three diverse approaches to risk assessment under deep uncertainty. • A simple example problem highlights differences in analytical process and results. • Results demonstrate how methodological choices can impact risk assessment results.

  1. Sensitivity and uncertainty analyses in aging risk-based prioritizations

    International Nuclear Information System (INIS)

    Hassan, M.; Uryas'ev, S.; Vesely, W.E.

    1993-01-01

    Aging risk evaluations of nuclear power plants using Probabilistic Risk Analyses (PRAs) involve assessments of the impact of aging structures, systems, and components (SSCs) on plant core damage frequency (CDF). These assessments can be used to prioritize the contributors to aging risk reflecting the relative risk potential of the SSCs. Aging prioritizations are important for identifying the SSCs contributing most to plant risk and can provide a systematic basis on which aging risk control and management strategies for a plant can be developed. However, these prioritizations are subject to variabilities arising from uncertainties in data, and/or from various modeling assumptions. The objective of this paper is to present an evaluation of the sensitivity of aging prioritizations of active components to uncertainties in aging risk quantifications. Approaches for robust prioritization of SSCs also are presented which are less susceptible to the uncertainties

  2. A Framework for Understanding Uncertainty in Seismic Risk Assessment.

    Science.gov (United States)

    Foulser-Piggott, Roxane; Bowman, Gary; Hughes, Martin

    2017-10-11

    A better understanding of the uncertainty that exists in models used for seismic risk assessment is critical to improving risk-based decisions pertaining to earthquake safety. Current models estimating the probability of collapse of a building do not consider comprehensively the nature and impact of uncertainty. This article presents a model framework to enhance seismic risk assessment and thus gives decisionmakers a fuller understanding of the nature and limitations of the estimates. This can help ensure that risks are not over- or underestimated and the value of acquiring accurate data is appreciated fully. The methodology presented provides a novel treatment of uncertainties in input variables, their propagation through the model, and their effect on the results. The study presents ranges of possible annual collapse probabilities for different case studies on buildings in different parts of the world, exposed to different levels of seismicity, and with different vulnerabilities. A global sensitivity analysis was conducted to determine the significance of uncertain variables. Two key outcomes are (1) that the uncertainty in ground-motion conversion equations has the largest effect on the uncertainty in the calculation of annual collapse probability; and (2) the vulnerability of a building appears to have an effect on the range of annual collapse probabilities produced, i.e., the level of uncertainty in the estimate of annual collapse probability, with less vulnerable buildings having a smaller uncertainty. © 2017 Society for Risk Analysis.

  3. Model uncertainty in financial markets : Long run risk and parameter uncertainty

    NARCIS (Netherlands)

    de Roode, F.A.

    2014-01-01

    Uncertainty surrounding key parameters of financial markets, such as the in- flation and equity risk premium, constitute a major risk for institutional investors with long investment horizons. Hedging the investors’ inflation exposure can be challenging due to the lack of domestic inflation-linked

  4. Modelling and propagation of uncertainties in the German Risk Study

    International Nuclear Information System (INIS)

    Hofer, E.; Krzykacz, B.

    1982-01-01

    Risk assessments are generally subject to uncertainty considerations. This is because of the various estimates that are involved. The paper points out those estimates in the so-called phase A of the German Risk Study, for which uncertainties were quantified. It explains the probabilistic models applied in the assessment to their impact on the findings of the study. Finally the resulting subjective confidence intervals of the study results are presented and their sensitivity to these probabilistic models is investigated

  5. The treatment of uncertainties in risk for regulatory decision making

    International Nuclear Information System (INIS)

    Baybutt, P.; Cox, D.C.; Denning, R.S.; Kurth, R.E.; Fraley, D.W.; Heaberlin, S.W.

    1982-01-01

    This paper describes research conducted in an ongoing program at Battelle to develop and adapt decision analysis methods for regulatory decision making. A general approach to risk-based decision making is discussed. The nature of uncertainties in risk assessment is described and methods for their inclusion in decision making are proposed. The use of decision analysis methods in regulatory decision making and the consideration of uncertainties is illustrated in a realistic case study

  6. Introduction to risk and uncertainty in hydrosystem engineering

    CERN Document Server

    Goodarzi, Ehsan; Teang Shui, Lee

    2013-01-01

    Water engineers require knowledge of stochastic, frequency concepts, uncertainty analysis, risk assessment, and the processes that predict unexpected events. This book presents the basics of stochastic, risk and uncertainty analysis, and random sampling techniques in conjunction with straightforward examples which are solved step by step. In addition, appropriate Excel functions are included as an alternative to solve the examples, and two real case studies is presented in the last chapters of book.

  7. Uncertainties and demonstration of compliance with numerical risk standards

    International Nuclear Information System (INIS)

    Preyssl, C.; Cullingford, M.C.

    1987-01-01

    When dealing with numerical results of a probabilistic risk analysis performed for a complex system, such as a nuclear power plant, one major objective may be to deal with the problem of compliance or non-compliance with a prefixed risk standard. The uncertainties in the risk results associated with the consequences and their probabilities of occurrence may be considered by representing the risk as a risk band. Studying the area and distance between the upper and lower bound of the risk band provides consistent information on the uncertainties in terms of risk, not by means of scalars only but also by real functions. Criteria can be defined for determining compliance with a numerical risk standard, and the 'weighting functional' method, representing a possible tool for testing compliance of risk results, is introduced. By shifting the upper confidence bound due to redefinition, part of the risk band may exceed the standard without changing the underlying results. Using the concept described it is possible to determine the amount of risk, i.e. uncertainty, exceeding the standard. The mathematical treatment of uncertainties therefore allows probabilistic risk assessment results to be compared. A realistic example illustrates the method. (author)

  8. Integration of inaccurate data into model building and uncertainty assessment

    Energy Technology Data Exchange (ETDEWEB)

    Coleou, Thierry

    1998-12-31

    Model building can be seen as integrating numerous measurements and mapping through data points considered as exact. As the exact data set is usually sparse, using additional non-exact data improves the modelling and reduces the uncertainties. Several examples of non-exact data are discussed and a methodology to honor them in a single pass, along with the exact data is presented. This automatic procedure is valid for both ``base case`` model building and stochastic simulations for uncertainty analysis. 5 refs., 3 figs.

  9. New challenges on uncertainty propagation assessment of flood risk analysis

    Science.gov (United States)

    Martins, Luciano; Aroca-Jiménez, Estefanía; Bodoque, José M.; Díez-Herrero, Andrés

    2016-04-01

    Natural hazards, such as floods, cause considerable damage to the human life, material and functional assets every year and around the World. Risk assessment procedures has associated a set of uncertainties, mainly of two types: natural, derived from stochastic character inherent in the flood process dynamics; and epistemic, that are associated with lack of knowledge or the bad procedures employed in the study of these processes. There are abundant scientific and technical literature on uncertainties estimation in each step of flood risk analysis (e.g. rainfall estimates, hydraulic modelling variables); but very few experience on the propagation of the uncertainties along the flood risk assessment. Therefore, epistemic uncertainties are the main goal of this work, in particular,understand the extension of the propagation of uncertainties throughout the process, starting with inundability studies until risk analysis, and how far does vary a proper analysis of the risk of flooding. These methodologies, such as Polynomial Chaos Theory (PCT), Method of Moments or Monte Carlo, are used to evaluate different sources of error, such as data records (precipitation gauges, flow gauges...), hydrologic and hydraulic modelling (inundation estimation), socio-demographic data (damage estimation) to evaluate the uncertainties propagation (UP) considered in design flood risk estimation both, in numerical and cartographic expression. In order to consider the total uncertainty and understand what factors are contributed most to the final uncertainty, we used the method of Polynomial Chaos Theory (PCT). It represents an interesting way to handle to inclusion of uncertainty in the modelling and simulation process. PCT allows for the development of a probabilistic model of the system in a deterministic setting. This is done by using random variables and polynomials to handle the effects of uncertainty. Method application results have a better robustness than traditional analysis

  10. Simplified quantitative treatment of uncertainty and interindividual variability in health risk assessment

    International Nuclear Information System (INIS)

    Bogen, K.T.

    1993-01-01

    A distinction between uncertainty (or the extent of lack of knowledge) and interindividual variability (or the extent of person-to-person heterogeneity) regarding the values of input variates must be maintained if a quantitative characterization of uncertainty in population risk or in individual risk is sought. Here, some practical methods are presented that should facilitate implementation of the analytic framework for uncertainty and variability proposed by Bogen and Spear. (1,2) Two types of methodology are discussed: one that facilitates the distinction between uncertainty and variability per se, and another that may be used to simplify quantitative analysis of distributed inputs representing either uncertainty or variability. A simple and a complex form for modeled increased risk are presented and then used to illustrate methods facilitating the distinction between uncertainty and variability in reference to characterization of both population and individual risk. Finally, a simple form of discrete probability calculus is proposed as an easily implemented, practical altemative to Monte-Carlo based procedures to quantitative integration of uncertainty and variability in risk assessment

  11. Integral risk assessment

    International Nuclear Information System (INIS)

    Chakraborty, S.; Yadigaroglu, G.

    1991-01-01

    The series of lectures which forms the basis of this book and took place in the winter of 1989/90 at the ETH in Zuerich were held for the purpose of discussing the stage of development of our system of ethics in view of the extremely fast pace of technological progress and the risks which accompany it. Legal, psychological and political aspects of the problem were examined, but the emphasis was placed on ethical aspects. The effects which are examined in conventional risk analyses can be considered as a part of the ethical and social aspects involved, and in turn, the consideration of ethical and social aspects can be viewed as an extension of the conventional form of risk analysis. In any case, among risk experts, the significance of ethical and social factors is uncontested, especially as regards activities which can have far-reaching repurcussions. Some objective difficulties interfere with this goal, however: - No generally acknowledged set of ethical values exists. - Cultural influences and personal motives can interfere. - Normally a risk assessment is carried out in reference to individual facilities and within a small, clearly defined framework. Under certain circumstances, generalizations which are made for complete technological systems can lead to completely different conclusions. One contribution deals with integral views of the risks of atomic energy from an ethical and social perspective. (orig.) [de

  12. Dealing with phenomenological uncertainty in risk analysis

    International Nuclear Information System (INIS)

    Theofanous, T.G.

    1994-01-01

    The Risk-Oriented Accident Analysis Methodology (ROAAM) is summarized and developed further towards a formal definition. The key ideas behind the methodology and these more formal aspects are also presented and discussed

  13. Climate change, uncertainty and investment in flood risk reduction

    OpenAIRE

    Pol, van der, T.D.

    2015-01-01

    Economic analysis of flood risk management strategies has become more complex due to climate change. This thesis investigates the impact of climate change on investment in flood risk reduction, and applies optimisation methods to support identification of optimal flood risk management strategies. Chapter 2 provides an overview of cost-benefit analysis (CBA) of flood risk management strategies under climate change uncertainty and new information. CBA is applied to determine optimal dike height...

  14. Uncertainties in fatal cancer risk estimates used in radiation protection

    International Nuclear Information System (INIS)

    Kai, Michiaki

    1999-01-01

    Although ICRP and NCRP had not described the details of uncertainties in cancer risk estimates in radiation protection, NCRP, in 1997, firstly reported the results of uncertainty analysis (NCRP No.126) and which is summarized in this paper. The NCRP report pointed out that there are following five factors which uncertainty possessing: uncertainty in epidemiological studies, in dose assessment, in transforming the estimates to risk assessment, in risk prediction and in extrapolation to the low dose/dose rate. These individual factors were analyzed statistically to obtain the relationship between the probability of cancer death in the US population and life time risk coefficient (% per Sv), which showed that, for the latter, the mean value was 3.99 x 10 -2 /Sv, median, 3.38 x 10 -2 /Sv, GSD (geometrical standard deviation), 1.83 x 10 -2 /Sv and 95% confidential limit, 1.2-8.84 x 10 -2 /Sv. The mean value was smaller than that of ICRP recommendation (5 x 10 -2 /Sv), indicating that the value has the uncertainty factor of 2.5-3. Moreover, the most important factor was shown to be the uncertainty in DDREF (dose/dose rate reduction factor). (K.H.)

  15. Assessing uncertainty and risk in exploited marine populations

    International Nuclear Information System (INIS)

    Fogarty, M.J.; Mayo, R.K.; O'Brien, L.; Serchuk, F.M.; Rosenberg, A.A.

    1996-01-01

    The assessment and management of exploited fish and invertebrate populations is subject to several types of uncertainty. This uncertainty translates into risk to the population in the development and implementation of fishery management advice. Here, we define risk as the probability that exploitation rates will exceed a threshold level where long term sustainability of the stock is threatened. We distinguish among several sources of error or uncertainty due to (a) stochasticity in demographic rates and processes, particularly in survival rates during the early fife stages; (b) measurement error resulting from sampling variation in the determination of population parameters or in model estimation; and (c) the lack of complete information on population and ecosystem dynamics. The first represents a form of aleatory uncertainty while the latter two factors represent forms of epistemic uncertainty. To illustrate these points, we evaluate the recent status of the Georges Bank cod stock in a risk assessment framework. Short term stochastic projections are made accounting for uncertainty in population size and for random variability in the number of young surviving to enter the fishery. We show that recent declines in this cod stock can be attributed to exploitation rates that have substantially exceeded sustainable levels

  16. Business corruption, uncertainty and risk aversion

    OpenAIRE

    Tina Søreide

    2006-01-01

    The presence of business-corruption in a market provokes firms to make choices between legal business approaches and illegal bribery. The outcome of a chosen strategy will usually be uncertain at the time the decision is made, and a firm's decision will depend partly on its attitude towards risk. Drawing on the empirical data provided by a survey of 82 Norwegian exporting businesses, the paper proposes a theory about firm's choices between legal and illegal business practices. It begins by de...

  17. Uncertainty, Risk Taking and Marital Happiness

    OpenAIRE

    Anderson-Jones, William

    2009-01-01

    Abstract: By analysing the effect of internal and external risks on marital happiness this paper concludes that social welfare is maximised by employment status and limiting the negative effect of children. Muslim, Christian and Sikh marriages were predominantly found to be unhappier as a parent in the household specialised in domestic labour and didn’t enter the workforce. ‘Non-religious’ groups have higher levels of female employment and consequently happier marriages. The discussion sugges...

  18. Perceived risk: rationality, uncertainty and scepticism

    International Nuclear Information System (INIS)

    Green, C.H.

    1981-01-01

    The subject is discussed under the headings: introduction; measuring what (deciding which outcomes are to be considered; personal safety, threat to health and safety (threat to society, threat to health)); accuracy of beliefs (distinction between immediate-in-effect hazards and delayed-in-effect hazards); the context of beliefs about risk (evolution of beliefs, changes in beliefs). Some references are made to nuclear power. (U.K.)

  19. Sources of uncertainty in characterizing health risks from flare emissions

    International Nuclear Information System (INIS)

    Hrudey, S.E.

    2000-01-01

    The assessment of health risks associated with gas flaring was the focus of this paper. Health risk assessments for environmental decision-making includes the evaluation of scientific data to identify hazards and to determine dose-response assessments, exposure assessments and risk characterization. Gas flaring has been the cause for public health concerns in recent years, most notably since 1996 after a published report by the Alberta Research Council. Some of the major sources of uncertainty associated with identifying hazardous contaminants in flare emissions were discussed. Methods to predict human exposures to emitted contaminants were examined along with risk characterization of predicted exposures to several identified contaminants. One of the problems is that elemental uncertainties exist regarding flare emissions which places limitations of the degree of reassurance that risk assessment can provide, but risk assessment can nevertheless offer some guidance to those responsible for flare emissions

  20. Integrating uncertainty into public energy research and development decisions

    Science.gov (United States)

    Anadón, Laura Díaz; Baker, Erin; Bosetti, Valentina

    2017-05-01

    Public energy research and development (R&D) is recognized as a key policy tool for transforming the world's energy system in a cost-effective way. However, managing the uncertainty surrounding technological change is a critical challenge for designing robust and cost-effective energy policies. The design of such policies is particularly important if countries are going to both meet the ambitious greenhouse-gas emissions reductions goals set by the Paris Agreement and achieve the required harmonization with the broader set of objectives dictated by the Sustainable Development Goals. The complexity of informing energy technology policy requires, and is producing, a growing collaboration between different academic disciplines and practitioners. Three analytical components have emerged to support the integration of technological uncertainty into energy policy: expert elicitations, integrated assessment models, and decision frameworks. Here we review efforts to incorporate all three approaches to facilitate public energy R&D decision-making under uncertainty. We highlight emerging insights that are robust across elicitations, models, and frameworks, relating to the allocation of public R&D investments, and identify gaps and challenges that remain.

  1. Uncertainties in human health risk assessment of environmental contaminants: A review and perspective.

    Science.gov (United States)

    Dong, Zhaomin; Liu, Yanju; Duan, Luchun; Bekele, Dawit; Naidu, Ravi

    2015-12-01

    Addressing uncertainties in human health risk assessment is a critical issue when evaluating the effects of contaminants on public health. A range of uncertainties exist through the source-to-outcome continuum, including exposure assessment, hazard and risk characterisation. While various strategies have been applied to characterising uncertainty, classical approaches largely rely on how to maximise the available resources. Expert judgement, defaults and tools for characterising quantitative uncertainty attempt to fill the gap between data and regulation requirements. The experiences of researching 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) illustrated uncertainty sources and how to maximise available information to determine uncertainties, and thereby provide an 'adequate' protection to contaminant exposure. As regulatory requirements and recurring issues increase, the assessment of complex scenarios involving a large number of chemicals requires more sophisticated tools. Recent advances in exposure and toxicology science provide a large data set for environmental contaminants and public health. In particular, biomonitoring information, in vitro data streams and computational toxicology are the crucial factors in the NexGen risk assessment, as well as uncertainties minimisation. Although in this review we cannot yet predict how the exposure science and modern toxicology will develop in the long-term, current techniques from emerging science can be integrated to improve decision-making. Copyright © 2015 Elsevier Ltd. All rights reserved.

  2. Optimizing integrated airport surface and terminal airspace operations under uncertainty

    Science.gov (United States)

    Bosson, Christabelle S.

    In airports and surrounding terminal airspaces, the integration of surface, arrival and departure scheduling and routing have the potential to improve the operations efficiency. Moreover, because both the airport surface and the terminal airspace are often altered by random perturbations, the consideration of uncertainty in flight schedules is crucial to improve the design of robust flight schedules. Previous research mainly focused on independently solving arrival scheduling problems, departure scheduling problems and surface management scheduling problems and most of the developed models are deterministic. This dissertation presents an alternate method to model the integrated operations by using a machine job-shop scheduling formulation. A multistage stochastic programming approach is chosen to formulate the problem in the presence of uncertainty and candidate solutions are obtained by solving sample average approximation problems with finite sample size. The developed mixed-integer-linear-programming algorithm-based scheduler is capable of computing optimal aircraft schedules and routings that reflect the integration of air and ground operations. The assembled methodology is applied to a Los Angeles case study. To show the benefits of integrated operations over First-Come-First-Served, a preliminary proof-of-concept is conducted for a set of fourteen aircraft evolving under deterministic conditions in a model of the Los Angeles International Airport surface and surrounding terminal areas. Using historical data, a representative 30-minute traffic schedule and aircraft mix scenario is constructed. The results of the Los Angeles application show that the integration of air and ground operations and the use of a time-based separation strategy enable both significant surface and air time savings. The solution computed by the optimization provides a more efficient routing and scheduling than the First-Come-First-Served solution. Additionally, a data driven analysis is

  3. Dealing with uncertainty arising out of probabilistic risk assessment

    International Nuclear Information System (INIS)

    Solomon, K.A.; Kastenberg, W.E.; Nelson, P.F.

    1984-03-01

    In addressing the area of safety goal implementation, the question of uncertainty arises. This report suggests that the Nuclear Regulatory Commission (NRC) should examine how other regulatory organizations have addressed the issue. Several examples are given from the chemical industry, and comparisons are made to nuclear power risks. Recommendations are made as to various considerations that the NRC should require in probabilistic risk assessments in order to properly treat uncertainties in the implementation of the safety goal policy. 40 references, 7 figures, 5 tables

  4. Uncertainty Instability Risk Analysis of High Concrete Arch Dam Abutments

    Directory of Open Access Journals (Sweden)

    Xin Cao

    2017-01-01

    Full Text Available The uncertainties associated with concrete arch dams rise with the increased height of dams. Given the uncertainties associated with influencing factors, the stability of high arch dam abutments as a fuzzy random event was studied. In addition, given the randomness and fuzziness of calculation parameters as well as the failure criterion, hazard point and hazard surface uncertainty instability risk ratio models were proposed for high arch dam abutments on the basis of credibility theory. The uncertainty instability failure criterion was derived through the analysis of the progressive instability failure process on the basis of Shannon’s entropy theory. The uncertainties associated with influencing factors were quantized by probability or possibility distribution assignments. Gaussian random theory was used to generate random realizations for influence factors with spatial variability. The uncertainty stability analysis method was proposed by combining the finite element analysis and the limit equilibrium method. The instability risk ratio was calculated using the Monte Carlo simulation method and fuzzy random postprocessing. Results corroborate that the modeling approach is sound and that the calculation method is feasible.

  5. Statistically based uncertainty assessments in nuclear risk analysis

    International Nuclear Information System (INIS)

    Spencer, F.W.; Diegert, K.V.; Easterling, R.G.

    1987-01-01

    Over the last decade, the problems of estimation and uncertainty assessment in probabilistics risk assessment (PRAs) have been addressed in a variety of NRC and industry-sponsored projects. These problems have received attention because of a recognition that major uncertainties in risk estimation exist, which can be reduced by collecting more and better data and other information, and because of a recognition that better methods for assessing these uncertainties are needed. In particular, a clear understanding of the nature and magnitude of various sources of uncertainty is needed to facilitate descision-making on possible plant changes and research options. Recent PRAs have employed methods of probability propagation, sometimes involving the use of Bayes Theorem, and intended to formalize the use of ''engineering judgment'' or ''expert opinion.'' All sources, or feelings, of uncertainty are expressed probabilistically, so that uncertainty analysis becomes simply a matter of probability propagation. Alternatives to forcing a probabilistic framework at all stages of a PRA are a major concern in this paper, however

  6. Including model uncertainty in risk-informed decision making

    International Nuclear Information System (INIS)

    Reinert, Joshua M.; Apostolakis, George E.

    2006-01-01

    Model uncertainties can have a significant impact on decisions regarding licensing basis changes. We present a methodology to identify basic events in the risk assessment that have the potential to change the decision and are known to have significant model uncertainties. Because we work with basic event probabilities, this methodology is not appropriate for analyzing uncertainties that cause a structural change to the model, such as success criteria. We use the risk achievement worth (RAW) importance measure with respect to both the core damage frequency (CDF) and the change in core damage frequency (ΔCDF) to identify potentially important basic events. We cross-check these with generically important model uncertainties. Then, sensitivity analysis is performed on the basic event probabilities, which are used as a proxy for the model parameters, to determine how much error in these probabilities would need to be present in order to impact the decision. A previously submitted licensing basis change is used as a case study. Analysis using the SAPHIRE program identifies 20 basic events as important, four of which have model uncertainties that have been identified in the literature as generally important. The decision is fairly insensitive to uncertainties in these basic events. In three of these cases, one would need to show that model uncertainties would lead to basic event probabilities that would be between two and four orders of magnitude larger than modeled in the risk assessment before they would become important to the decision. More detailed analysis would be required to determine whether these higher probabilities are reasonable. Methods to perform this analysis from the literature are reviewed and an example is demonstrated using the case study

  7. Evaluation of risk impact of changes to Completion Times addressing model and parameter uncertainties

    International Nuclear Information System (INIS)

    Martorell, S.; Martón, I.; Villamizar, M.; Sánchez, A.I.; Carlos, S.

    2014-01-01

    This paper presents an approach and an example of application for the evaluation of risk impact of changes to Completion Times within the License Basis of a Nuclear Power Plant based on the use of the Probabilistic Risk Assessment addressing identification, treatment and analysis of uncertainties in an integrated manner. It allows full development of a three tired approach (Tier 1–3) following the principles of the risk-informed decision-making accounting for uncertainties as proposed by many regulators. Completion Time is the maximum outage time a safety related equipment is allowed to be down, e.g. for corrective maintenance, which is established within the Limiting Conditions for Operation included into Technical Specifications for operation of a Nuclear Power Plant. The case study focuses on a Completion Time change of the Accumulators System of a Nuclear Power Plant using a level 1 PRA. It focuses on several sources of model and parameter uncertainties. The results obtained show the risk impact of the proposed CT change including both types of epistemic uncertainties is small as compared with current safety goals of concern to Tier 1. However, what concerns to Tier 2 and 3, the results obtained show how the use of some traditional and uncertainty importance measures helps in identifying high risky configurations that should be avoided in NPP technical specifications no matter the duration of CT (Tier 2), and other configurations that could take part of a configuration risk management program (Tier 3). - Highlights: • New approach for evaluation of risk impact of changes to Completion Times. • Integrated treatment and analysis of model and parameter uncertainties. • PSA based application to support risk-informed decision-making. • Measures of importance for identification of risky configurations. • Management of important safety issues to accomplish safety goals

  8. How risk and uncertainty is used in Supply Chain Management: a literature study

    DEFF Research Database (Denmark)

    Bøge Sørensen, Lars

    2004-01-01

    Keywords Supply Chain Management, Risk Management, Supply Chain Risk ManagementAbstract To comply with Supply Chain Management dogma companies have cut their inventoriesto a minimum, lead times have been shortened, new suppliers have been chosen and the customerportfolio has been reduced. All...... of these activities impose a great deal of risk on the firms,jeopardizing the survival of entire supply chains. In this article the author intends to investigateand document the use and meaning of Risk and Uncertainty within journals publishing material onSupply Chain Management and Logistics. Subsequently...... suggestions for further research areproposed - the integration of Risk Management into the discipline of Supply Chain Design....

  9. Risk Management and Uncertainty in Large Complex Public Projects

    DEFF Research Database (Denmark)

    Neerup Themsen, Tim; Harty, Chris; Tryggestad, Kjell

    Governmental actors worldwide are promoting risk management as a rational approach to man-age uncertainty and improve the abilities to deliver large complex projects according to budget, time plans, and pre-set project specifications: But what do we know about the effects of risk management...... on the abilities to meet such objectives? Using Callon’s (1998) twin notions of framing and overflowing we examine the implementation of risk management within the Dan-ish public sector and the effects this generated for the management of two large complex pro-jects. We show how the rational framing of risk...... management have generated unexpected costly outcomes such as: the undermining of the longer-term value and societal relevance of the built asset, the negligence of the wider range of uncertainties emerging during project processes, and constraining forms of knowledge. We also show how expert accountants play...

  10. Uncertainty estimation and risk prediction in air quality

    International Nuclear Information System (INIS)

    Garaud, Damien

    2011-01-01

    This work is about uncertainty estimation and risk prediction in air quality. Firstly, we build a multi-model ensemble of air quality simulations which can take into account all uncertainty sources related to air quality modeling. Ensembles of photochemical simulations at continental and regional scales are automatically generated. Then, these ensemble are calibrated with a combinatorial optimization method. It selects a sub-ensemble which is representative of uncertainty or shows good resolution and reliability for probabilistic forecasting. This work shows that it is possible to estimate and forecast uncertainty fields related to ozone and nitrogen dioxide concentrations or to improve the reliability of threshold exceedance predictions. The approach is compared with Monte Carlo simulations, calibrated or not. The Monte Carlo approach appears to be less representative of the uncertainties than the multi-model approach. Finally, we quantify the observational error, the representativeness error and the modeling errors. The work is applied to the impact of thermal power plants, in order to quantify the uncertainty on the impact estimates. (author) [fr

  11. A method for minimum risk portfolio optimization under hybrid uncertainty

    Science.gov (United States)

    Egorova, Yu E.; Yazenin, A. V.

    2018-03-01

    In this paper, we investigate a minimum risk portfolio model under hybrid uncertainty when the profitability of financial assets is described by fuzzy random variables. According to Feng, the variance of a portfolio is defined as a crisp value. To aggregate fuzzy information the weakest (drastic) t-norm is used. We construct an equivalent stochastic problem of the minimum risk portfolio model and specify the stochastic penalty method for solving it.

  12. The explicit treatment of model uncertainties in the presence of aleatory and epistemic parameter uncertainties in risk and reliability analysis

    International Nuclear Information System (INIS)

    Ahn, Kwang Il; Yang, Joon Eon

    2003-01-01

    In the risk and reliability analysis of complex technological systems, the primary concern of formal uncertainty analysis is to understand why uncertainties arise, and to evaluate how they impact the results of the analysis. In recent times, many of the uncertainty analyses have focused on parameters of the risk and reliability analysis models, whose values are uncertain in an aleatory or an epistemic way. As the field of parametric uncertainty analysis matures, however, more attention is being paid to the explicit treatment of uncertainties that are addressed in the predictive model itself as well as the accuracy of the predictive model. The essential steps for evaluating impacts of these model uncertainties in the presence of parameter uncertainties are to determine rigorously various sources of uncertainties to be addressed in an underlying model itself and in turn model parameters, based on our state-of-knowledge and relevant evidence. Answering clearly the question of how to characterize and treat explicitly the forgoing different sources of uncertainty is particularly important for practical aspects such as risk and reliability optimization of systems as well as more transparent risk information and decision-making under various uncertainties. The main purpose of this paper is to provide practical guidance for quantitatively treating various model uncertainties that would often be encountered in the risk and reliability modeling process of complex technological systems

  13. Hydroclimatic risks and uncertainty in the global power sector

    Science.gov (United States)

    Gidden, Matthew; Byers, Edward; Greve, Peter; Kahil, Taher; Parkinson, Simon; Raptis, Catherine; Rogelj, Joeri; Satoh, Yusuke; van Vliet, Michelle; Wada, Yoshide; Krey, Volker; Langan, Simon; Riahi, Keywan

    2017-04-01

    Approximately 80% of the world's electricity supply depends on reliable water resources. Thermoelectric and hydropower plants have been impacted by low flows and floods in recent years, notably in the US, Brazil, France, and China, amongst other countries. The dependence on reliable flows imputes a large vulnerability to the electricity supply system due to hydrological variability and the impacts of climate change. Using an updated dataset of global electricity capacity with global climate and hydrological data from the ISI-MIP project, we present an overview analysis of power sector vulnerability to hydroclimatic risks, including low river flows and peak flows. We show how electricity generation in individual countries and transboundary river basins can be impacted, helping decision-makers identify key at-risk geographical regions. Furthermore, our use of a multi-model ensemble of climate and hydrological models allows us to quantify the uncertainty of projected impacts, such that basin-level risks and uncertainty can be compared.

  14. Exploiting risk-reward structures in decision making under uncertainty.

    Science.gov (United States)

    Leuker, Christina; Pachur, Thorsten; Hertwig, Ralph; Pleskac, Timothy J

    2018-06-01

    People often have to make decisions under uncertainty-that is, in situations where the probabilities of obtaining a payoff are unknown or at least difficult to ascertain. One solution to this problem is to infer the probability from the magnitude of the potential payoff and thus exploit the inverse relationship between payoffs and probabilities that occurs in many domains in the environment. Here, we investigated how the mind may implement such a solution: (1) Do people learn about risk-reward relationships from the environment-and if so, how? (2) How do learned risk-reward relationships impact preferences in decision-making under uncertainty? Across three experiments (N = 352), we found that participants can learn risk-reward relationships from being exposed to choice environments with a negative, positive, or uncorrelated risk-reward relationship. They were able to learn the associations both from gambles with explicitly stated payoffs and probabilities (Experiments 1 & 2) and from gambles about epistemic events (Experiment 3). In subsequent decisions under uncertainty, participants often exploited the learned association by inferring probabilities from the magnitudes of the payoffs. This inference systematically influenced their preferences under uncertainty: Participants who had been exposed to a negative risk-reward relationship tended to prefer the uncertain option over a smaller sure option for low payoffs, but not for high payoffs. This pattern reversed in the positive condition and disappeared in the uncorrelated condition. This adaptive change in preferences is consistent with the use of the risk-reward heuristic. Copyright © 2018 Elsevier B.V. All rights reserved.

  15. Stochastic goal programming based groundwater remediation management under human-health-risk uncertainty

    International Nuclear Information System (INIS)

    Li, Jing; He, Li; Lu, Hongwei; Fan, Xing

    2014-01-01

    Highlights: • We propose an integrated optimal groundwater remediation design approach. • The approach can address stochasticity in carcinogenic risks. • Goal programming is used to make the system approaching to ideal operation and remediation effects. • The uncertainty in slope factor is evaluated under different confidence levels. • Optimal strategies are obtained to support remediation design under uncertainty. - Abstract: An optimal design approach for groundwater remediation is developed through incorporating numerical simulation, health risk assessment, uncertainty analysis and nonlinear optimization within a general framework. Stochastic analysis and goal programming are introduced into the framework to handle uncertainties in real-world groundwater remediation systems. Carcinogenic risks associated with remediation actions are further evaluated at four confidence levels. The differences between ideal and predicted constraints are minimized by goal programming. The approach is then applied to a contaminated site in western Canada for creating a set of optimal remediation strategies. Results from the case study indicate that factors including environmental standards, health risks and technical requirements mutually affected and restricted themselves. Stochastic uncertainty existed in the entire process of remediation optimization, which should to be taken into consideration in groundwater remediation design

  16. Integrated climate change risk assessment:

    DEFF Research Database (Denmark)

    Kaspersen, Per Skougaard; Halsnæs, Kirsten

    2017-01-01

    Risk assessments of flooding in urban areas during extreme precipitation for use in, for example, decision-making regarding climate adaptation, are surrounded by great uncertainties stemming from climate model projections, methods of downscaling and the assumptions of socioeconomic impact models...... to address the complex linkages between the different kinds of data required in assessing climate adaptation. It emphasizes that the availability of spatially explicit data can reduce the overall uncertainty of the risk assessment and assist in identifying key vulnerable assets. The usefulness...... of such a framework is demonstrated by means of a risk assessment of flooding from extreme precipitation for the city of Odense, Denmark. A sensitivity analysis shows how the presence of particularly important assets, such as cultural and historical heritage, may be addressed in assessing such risks. The output...

  17. The spectre of uncertainty in communicating technological risk

    Energy Technology Data Exchange (ETDEWEB)

    Broesius, Michael T. [Univ. of California, Livermore, CA (United States)

    1993-12-01

    The literature does not clearly describe the potential moral and ethical conflicts that can exist between technology sponsors and the technical communicators whose job it is to present potentially risky technology to the non-technical people most likely to be imperiled by such risk. Equally important, the literature does not address the issue of uncertainty -- not the uncertainty likely to be experienced by the community at risk, but the unreliable processes and methodologies used by technology sponsors to define, quantify, and develop strategies to mitigate technological risks. In this paper, the author goes beyond a description of risk communication, the nature of the generally predictable interaction between technology advocates and non-technically trained individuals, and current trends in the field. Although that kind of information is critical to the success of any risk communication activity, and he has included it when necessary to provide background and perspective, without knowing how and why risk assessment is done, it has limited practical applicability outside the sterile, value-free vacuum in which it is usually framed. Technical communicators, particularly those responsible for communicating potential technological risk, must also understand the social, political, economic, statistical, and ethical issues they will invariably encounter.

  18. Improving default risk prediction using Bayesian model uncertainty techniques.

    Science.gov (United States)

    Kazemi, Reza; Mosleh, Ali

    2012-11-01

    Credit risk is the potential exposure of a creditor to an obligor's failure or refusal to repay the debt in principal or interest. The potential of exposure is measured in terms of probability of default. Many models have been developed to estimate credit risk, with rating agencies dating back to the 19th century. They provide their assessment of probability of default and transition probabilities of various firms in their annual reports. Regulatory capital requirements for credit risk outlined by the Basel Committee on Banking Supervision have made it essential for banks and financial institutions to develop sophisticated models in an attempt to measure credit risk with higher accuracy. The Bayesian framework proposed in this article uses the techniques developed in physical sciences and engineering for dealing with model uncertainty and expert accuracy to obtain improved estimates of credit risk and associated uncertainties. The approach uses estimates from one or more rating agencies and incorporates their historical accuracy (past performance data) in estimating future default risk and transition probabilities. Several examples demonstrate that the proposed methodology can assess default probability with accuracy exceeding the estimations of all the individual models. Moreover, the methodology accounts for potentially significant departures from "nominal predictions" due to "upsetting events" such as the 2008 global banking crisis. © 2012 Society for Risk Analysis.

  19. Advanced Approach to Consider Aleatory and Epistemic Uncertainties for Integral Accident Simulations

    International Nuclear Information System (INIS)

    Peschke, Joerg; Kloos, Martina

    2013-01-01

    The use of best-estimate codes together with realistic input data generally requires that all potentially important epistemic uncertainties which may affect the code prediction are considered in order to get an adequate quantification of the epistemic uncertainty of the prediction as an expression of the existing imprecise knowledge. To facilitate the performance of the required epistemic uncertainty analyses, methods and corresponding software tools are available like, for instance, the GRS-tool SUSA (Software for Uncertainty and Sensitivity Analysis). However, for risk-informed decision-making, the restriction on epistemic uncertainties alone is not enough. Transients and accident scenarios are also affected by aleatory uncertainties which are due to the unpredictable nature of phenomena. It is essential that aleatory uncertainties are taken into account as well, not only in a simplified and supposedly conservative way but as realistic as possible. The additional consideration of aleatory uncertainties, for instance, on the behavior of the technical system, the performance of plant operators, or on the behavior of the physical process provides a quantification of probabilistically significant accident sequences. Only if a safety analysis is able to account for both epistemic and aleatory uncertainties in a realistic manner, it can provide a well-founded risk-informed answer for decision-making. At GRS, an advanced probabilistic dynamics method was developed to address this problem and to provide a more realistic modeling and assessment of transients and accident scenarios. This method allows for an integral simulation of complex dynamic processes particularly taking into account interactions between the plant dynamics as simulated by a best-estimate code, the dynamics of operator actions and the influence of epistemic and aleatory uncertainties. In this paper, the GRS method MCDET (Monte Carlo Dynamic Event Tree) for probabilistic dynamics analysis is explained

  20. A model for optimization of process integration investments under uncertainty

    International Nuclear Information System (INIS)

    Svensson, Elin; Stroemberg, Ann-Brith; Patriksson, Michael

    2011-01-01

    The long-term economic outcome of energy-related industrial investment projects is difficult to evaluate because of uncertain energy market conditions. In this article, a general, multistage, stochastic programming model for the optimization of investments in process integration and industrial energy technologies is proposed. The problem is formulated as a mixed-binary linear programming model where uncertainties are modelled using a scenario-based approach. The objective is to maximize the expected net present value of the investments which enables heat savings and decreased energy imports or increased energy exports at an industrial plant. The proposed modelling approach enables a long-term planning of industrial, energy-related investments through the simultaneous optimization of immediate and later decisions. The stochastic programming approach is also suitable for modelling what is possibly complex process integration constraints. The general model formulation presented here is a suitable basis for more specialized case studies dealing with optimization of investments in energy efficiency. -- Highlights: → Stochastic programming approach to long-term planning of process integration investments. → Extensive mathematical model formulation. → Multi-stage investment decisions and scenario-based modelling of uncertain energy prices. → Results illustrate how investments made now affect later investment and operation opportunities. → Approach for evaluation of robustness with respect to variations in probability distribution.

  1. County-Level Climate Uncertainty for Risk Assessments: Volume 1.

    Energy Technology Data Exchange (ETDEWEB)

    Backus, George A.; Lowry, Thomas Stephen; Jones, Shannon M; Walker, La Tonya Nicole; Roberts, Barry L; Malczynski, Leonard A.

    2017-06-01

    This report uses the CMIP5 series of climate model simulations to produce country- level uncertainty distributions for use in socioeconomic risk assessments of climate change impacts. It provides appropriate probability distributions, by month, for 169 countries and autonomous-areas on temperature, precipitation, maximum temperature, maximum wind speed, humidity, runoff, soil moisture and evaporation for the historical period (1976-2005), and for decadal time periods to 2100. It also provides historical and future distributions for the Arctic region on ice concentration, ice thickness, age of ice, and ice ridging in 15-degree longitude arc segments from the Arctic Circle to 80 degrees latitude, plus two polar semicircular regions from 80 to 90 degrees latitude. The uncertainty is meant to describe the lack of knowledge rather than imprecision in the physical simulation because the emphasis is on unfalsified risk and its use to determine potential socioeconomic impacts. The full report is contained in 27 volumes.

  2. Development of Risk Uncertainty Factors from Historical NASA Projects

    Science.gov (United States)

    Amer, Tahani R.

    2011-01-01

    NASA is a good investment of federal funds and strives to provide the best value to the nation. NASA has consistently budgeted to unrealistic cost estimates, which are evident in the cost growth in many of its programs. In this investigation, NASA has been using available uncertainty factors from the Aerospace Corporation, Air Force, and Booz Allen Hamilton to develop projects risk posture. NASA has no insight into the developmental of these factors and, as demonstrated here, this can lead to unrealistic risks in many NASA Programs and projects (P/p). The primary contribution of this project is the development of NASA missions uncertainty factors, from actual historical NASA projects, to aid cost-estimating as well as for independent reviews which provide NASA senior management with information and analysis to determine the appropriate decision regarding P/p. In general terms, this research project advances programmatic analysis for NASA projects.

  3. Epistemic and aleatory uncertainties in integrated deterministic and probabilistic safety assessment: Tradeoff between accuracy and accident simulations

    International Nuclear Information System (INIS)

    Karanki, D.R.; Rahman, S.; Dang, V.N.; Zerkak, O.

    2017-01-01

    The coupling of plant simulation models and stochastic models representing failure events in Dynamic Event Trees (DET) is a framework used to model the dynamic interactions among physical processes, equipment failures, and operator responses. The integration of physical and stochastic models may additionally enhance the treatment of uncertainties. Probabilistic Safety Assessments as currently implemented propagate the (epistemic) uncertainties in failure probabilities, rates, and frequencies; while the uncertainties in the physical model (parameters) are not propagated. The coupling of deterministic (physical) and probabilistic models in integrated simulations such as DET allows both types of uncertainties to be considered. However, integrated accident simulations with epistemic uncertainties will challenge even today's high performance computing infrastructure, especially for simulations of inherently complex nuclear or chemical plants. Conversely, intentionally limiting computations for practical reasons would compromise accuracy of results. This work investigates how to tradeoff accuracy and computations to quantify risk in light of both uncertainties and accident dynamics. A simple depleting tank problem that can be solved analytically is considered to examine the adequacy of a discrete DET approach. The results show that optimal allocation of computational resources between epistemic and aleatory calculations by means of convergence studies ensures accuracy within a limited budget. - Highlights: • Accident simulations considering uncertainties require intensive computations. • Tradeoff between accuracy and accident simulations is a challenge. • Optimal allocation between epistemic & aleatory computations ensures the tradeoff. • Online convergence gives an early indication of computational requirements. • Uncertainty propagation in DDET is examined on a tank problem solved analytically.

  4. Accounting for data uncertainties in comparing risks from energy systems

    International Nuclear Information System (INIS)

    Hauptmanns, Ulrich

    1998-01-01

    Data and models for risk comparisons are uncertain and this is true all the more the larger the time horizon contemplated. Statistical methods are presented for dealing with data uncertainties thus providing a broader foundation for decisions. Nevertheless, it has to be borne in mind that no method exists to account for the 'unforeseeable' which is always present in decision making with respect to the far future. (author)

  5. Information Uncertainty to Compare Qualitative Reasoning Security Risk Assessment Results

    Energy Technology Data Exchange (ETDEWEB)

    Chavez, Gregory M [Los Alamos National Laboratory; Key, Brian P [Los Alamos National Laboratory; Zerkle, David K [Los Alamos National Laboratory; Shevitz, Daniel W [Los Alamos National Laboratory

    2009-01-01

    The security risk associated with malevolent acts such as those of terrorism are often void of the historical data required for a traditional PRA. Most information available to conduct security risk assessments for these malevolent acts is obtained from subject matter experts as subjective judgements. Qualitative reasoning approaches such as approximate reasoning and evidential reasoning are useful for modeling the predicted risk from information provided by subject matter experts. Absent from these approaches is a consistent means to compare the security risk assessment results. Associated with each predicted risk reasoning result is a quantifiable amount of information uncertainty which can be measured and used to compare the results. This paper explores using entropy measures to quantify the information uncertainty associated with conflict and non-specificity in the predicted reasoning results. The measured quantities of conflict and non-specificity can ultimately be used to compare qualitative reasoning results which are important in triage studies and ultimately resource allocation. Straight forward extensions of previous entropy measures are presented here to quantify the non-specificity and conflict associated with security risk assessment results obtained from qualitative reasoning models.

  6. Operational Implementation of a Pc Uncertainty Construct for Conjunction Assessment Risk Analysis

    Science.gov (United States)

    Newman, Lauri K.; Hejduk, Matthew D.; Johnson, Lauren C.

    2016-01-01

    Earlier this year the NASA Conjunction Assessment and Risk Analysis (CARA) project presented the theoretical and algorithmic aspects of a method to include the uncertainties in the calculation inputs when computing the probability of collision (Pc) between two space objects, principally uncertainties in the covariances and the hard-body radius. The output of this calculation approach is to produce rather than a single Pc value an entire probability density function that will represent the range of possible Pc values given the uncertainties in the inputs and bring CA risk analysis methodologies more in line with modern risk management theory. The present study provides results from the exercise of this method against an extended dataset of satellite conjunctions in order to determine the effect of its use on the evaluation of conjunction assessment (CA) event risk posture. The effects are found to be considerable: a good number of events are downgraded from or upgraded to a serious risk designation on the basis of consideration of the Pc uncertainty. The findings counsel the integration of the developed methods into NASA CA operations.

  7. A risk assessment methodology for incorporating uncertainties using fuzzy concepts

    International Nuclear Information System (INIS)

    Cho, Hyo-Nam; Choi, Hyun-Ho; Kim, Yoon-Bae

    2002-01-01

    This paper proposes a new methodology for incorporating uncertainties using fuzzy concepts into conventional risk assessment frameworks. This paper also introduces new forms of fuzzy membership curves, designed to consider the uncertainty range that represents the degree of uncertainties involved in both probabilistic parameter estimates and subjective judgments, since it is often difficult or even impossible to precisely estimate the occurrence rate of an event in terms of one single crisp probability. It is to be noted that simple linguistic variables such as 'High/Low' and 'Good/Bad' have the limitations in quantifying the various risks inherent in construction projects, but only represent subjective mental cognition adequately. Therefore, in this paper, the statements that include some quantification with giving specific value or scale, such as 'Close to any value' or 'Higher/Lower than analyzed value', are used in order to get over the limitations. It may be stated that the proposed methodology will be very useful for the systematic and rational risk assessment of construction projects

  8. Regulatory uncertainty and the associated business risk for emerging technologies

    International Nuclear Information System (INIS)

    Hoerr, Robert A.

    2011-01-01

    An oversight system specifically concerned with nanomaterials should be flexible enough to take into account the unique aspects of individual novel materials and the settings in which they might be used, while recognizing that heretofore unrecognized safety issues may require future modifications. This article considers a question not explicitly considered by the project team: what is the risk that uncertainty over how regulatory oversight will be applied to nanomaterials will delay or block the development of this emerging technology, thereby depriving human health of potential and substantial benefits? An ambiguous regulatory environment could delay the availability of valuable new technology and therapeutics for human health by reducing access to investment capital. Venture capitalists list regulatory uncertainty as a major reason not to invest at all in certain areas. Uncertainty is far more difficult to evaluate than risk, which lends itself to quantitative models and can be factored into projections of return on possible investments. Loss of time has a large impact on investment return. An examination of regulatory case histories suggests that an increase in regulatory resting requirement, where the path is well-defined, is far less costly than a delay of a year or more in achieving product approval and market launch.

  9. Regulatory uncertainty and the associated business risk for emerging technologies

    Science.gov (United States)

    Hoerr, Robert A.

    2011-04-01

    An oversight system specifically concerned with nanomaterials should be flexible enough to take into account the unique aspects of individual novel materials and the settings in which they might be used, while recognizing that heretofore unrecognized safety issues may require future modifications. This article considers a question not explicitly considered by the project team: what is the risk that uncertainty over how regulatory oversight will be applied to nanomaterials will delay or block the development of this emerging technology, thereby depriving human health of potential and substantial benefits? An ambiguous regulatory environment could delay the availability of valuable new technology and therapeutics for human health by reducing access to investment capital. Venture capitalists list regulatory uncertainty as a major reason not to invest at all in certain areas. Uncertainty is far more difficult to evaluate than risk, which lends itself to quantitative models and can be factored into projections of return on possible investments. Loss of time has a large impact on investment return. An examination of regulatory case histories suggests that an increase in regulatory resting requirement, where the path is well-defined, is far less costly than a delay of a year or more in achieving product approval and market launch.

  10. A Bayesian Framework of Uncertainties Integration in 3D Geological Model

    Science.gov (United States)

    Liang, D.; Liu, X.

    2017-12-01

    3D geological model can describe complicated geological phenomena in an intuitive way while its application may be limited by uncertain factors. Great progress has been made over the years, lots of studies decompose the uncertainties of geological model to analyze separately, while ignored the comprehensive impacts of multi-source uncertainties. Great progress has been made over the years, while lots of studies ignored the comprehensive impacts of multi-source uncertainties when analyzed them item by item from each source. To evaluate the synthetical uncertainty, we choose probability distribution to quantify uncertainty, and propose a bayesian framework of uncertainties integration. With this framework, we integrated data errors, spatial randomness, and cognitive information into posterior distribution to evaluate synthetical uncertainty of geological model. Uncertainties propagate and cumulate in modeling process, the gradual integration of multi-source uncertainty is a kind of simulation of the uncertainty propagation. Bayesian inference accomplishes uncertainty updating in modeling process. Maximum entropy principle makes a good effect on estimating prior probability distribution, which ensures the prior probability distribution subjecting to constraints supplied by the given information with minimum prejudice. In the end, we obtained a posterior distribution to evaluate synthetical uncertainty of geological model. This posterior distribution represents the synthetical impact of all the uncertain factors on the spatial structure of geological model. The framework provides a solution to evaluate synthetical impact on geological model of multi-source uncertainties and a thought to study uncertainty propagation mechanism in geological modeling.

  11. Media reporting of risk information: Uncertainties and the future

    International Nuclear Information System (INIS)

    Peltu, M.

    1988-01-01

    This paper argues that very little is known with a reasonable degree of certainty about how the media influence their audiences. Media effects are mediated through diverse, subtle social interactions and processes. Future changes in the regulatory and technological media environment will create even more uncertainty by changing basic parameters of media/audience interaction. More research is needed to help shed light on these uncertainties and future changes. If this research is to be of relevance to real communicators of real risk, it must fully address the issues of how the media are influenced, not just media impacts. In this context, the role of experts, PR, advertising, and media professionals' motivations are key priorities. (orig.)

  12. What do experts stakeholders think about chemical risks and uncertainties. An Internet survey

    Energy Technology Data Exchange (ETDEWEB)

    Assmuth, T.; Lyytimaeki, J.; Hilden, M.; Lindholm, M.; Munier, B.

    2007-07-01

    This report presents results from a web-based explorative survey on integrated risk assessment. The survey was conducted in the EU-funded project NoMiracle (Novel Methods for Risk Assessment of Cumulative Stressors in Europe) which develops methods for assessing cumulative risks from combined exposures to multiple stressors. The objectives of the survey were to give a general picture of perceptions and views among experts and stakeholders concerning risks, risk assessment and risk management. The survey focused on chemicals with an emphasis on information related to complex risks and uncertainties in a management context. The methodology of the survey combined traditional multiple choice questions and a novel approach that charted the importance of different types of information in two-dimensional graphs describing simultaneously use in regulatory procedures and public discussion. Another part was linked to new methods of presenting risks and explored the ranking of separate and cumulative risks in map grids. The survey was e-mailed to 952 recipients representing researchers, national and EU level administrators, enterprises, NGOs and international organizations, and most EU member states and some other countries. The response rate (26 %) can be considered acceptable but limits the possibilities to make quantitative claims concerning the views held by different groups although it gives an overview of the types of views one encounter among experts. A key finding was the pronounced variability of concepts and views regarding risks and uncertainties, and regarding information and knowledge about these. Opinions on risks and risk assessment, particularly on integrated risk assessment, on related principles, and on the role of experts are genuinely variable. They cannot be reduced to any simple model, and cannot (and need not) be dispelled in a forced manner. The observations should be taken into account in the development and application of novel methods for risk

  13. Integrated Risk Information System (IRIS)

    Data.gov (United States)

    U.S. Environmental Protection Agency — EPA?s Integrated Risk Information System (IRIS) is a compilation of electronic reports on specific substances found in the environment and their potential to cause...

  14. Uncertainty studies and risk assessment for CO{sub 2} storage in geological formations

    Energy Technology Data Exchange (ETDEWEB)

    Walter, Lena Sophie

    2013-07-01

    drinking water aquifers. The uncertainties on all three levels are investigated in three approaches with different focus. The concept can also be applied to CO{sub 2} leakage or hazards related to other technologies in the subsurface such as methane storage or atomic waste disposal. In the second part of this thesis, uncertainty studies for two realistic storage formations (the pilot site Ketzin (Germany) and a realistic storage formation in the North German Basin) are performed to investigate the related uncertainties and to reduce them as much as possible. For the Ketzin site, history matching of the measurement data, is an important task for dynamic modeling and essential for future risk assessment. A systematic approach to fit the data set using inverse modeling is presented in this work. For future risk assessment for realistic sites, e.g. for the Ketzin site, the uncertainty studies and the history matching approach provide important information. Finally, CCS is discussed in the context of risk perception and the possible input of the risk assessment concept presented in this work is discussed. This work is a first attempt to connect the technical risk assessment for CO{sub 2} storage to the social science approach for risk assessment. It is bridging the gap between engineering and social sciences by integrating the technical quantification of risk into the wider context of a comprehensive risk governance model.

  15. Uncertainty studies and risk assessment for CO2 storage in geological formations

    International Nuclear Information System (INIS)

    Walter, Lena Sophie

    2013-01-01

    aquifers. The uncertainties on all three levels are investigated in three approaches with different focus. The concept can also be applied to CO 2 leakage or hazards related to other technologies in the subsurface such as methane storage or atomic waste disposal. In the second part of this thesis, uncertainty studies for two realistic storage formations (the pilot site Ketzin (Germany) and a realistic storage formation in the North German Basin) are performed to investigate the related uncertainties and to reduce them as much as possible. For the Ketzin site, history matching of the measurement data, is an important task for dynamic modeling and essential for future risk assessment. A systematic approach to fit the data set using inverse modeling is presented in this work. For future risk assessment for realistic sites, e.g. for the Ketzin site, the uncertainty studies and the history matching approach provide important information. Finally, CCS is discussed in the context of risk perception and the possible input of the risk assessment concept presented in this work is discussed. This work is a first attempt to connect the technical risk assessment for CO 2 storage to the social science approach for risk assessment. It is bridging the gap between engineering and social sciences by integrating the technical quantification of risk into the wider context of a comprehensive risk governance model.

  16. Integrated supply chain risk management

    OpenAIRE

    Riaan Bredell; Jackie Walters

    2007-01-01

    Integrated supply chain risk management (ISCRM) has become indispensable to the theory and practice of supply chain management. The economic and political realities of the modern world require not only a different approach to supply chain management, but also bold steps to secure supply chain performance and sustainable wealth creation. Integrated supply chain risk management provides supply chain organisations with a level of insight into their supply chains yet to be achieved. If correctly ...

  17. Uncertainty analysis in vulnerability estimations for elements at risk- a review of concepts and some examples on landslides

    Science.gov (United States)

    Ciurean, R. L.; Glade, T.

    2012-04-01

    Decision under uncertainty is a constant of everyday life and an important component of risk management and governance. Recently, experts have emphasized the importance of quantifying uncertainty in all phases of landslide risk analysis. Due to its multi-dimensional and dynamic nature, (physical) vulnerability is inherently complex and the "degree of loss" estimates imprecise and to some extent even subjective. Uncertainty analysis introduces quantitative modeling approaches that allow for a more explicitly objective output, improving the risk management process as well as enhancing communication between various stakeholders for better risk governance. This study presents a review of concepts for uncertainty analysis in vulnerability of elements at risk to landslides. Different semi-quantitative and quantitative methods are compared based on their feasibility in real-world situations, hazard dependency, process stage in vulnerability assessment (i.e. input data, model, output), and applicability within an integrated landslide hazard and risk framework. The resulted observations will help to identify current gaps and future needs in vulnerability assessment, including estimation of uncertainty propagation, transferability of the methods, development of visualization tools, but also address basic questions like what is uncertainty and how uncertainty can be quantified or treated in a reliable and reproducible way.

  18. Incorporating the Technology Roadmap Uncertainties into the Project Risk Assessment

    International Nuclear Information System (INIS)

    Bonnema, B.E.

    2002-01-01

    This paper describes two methods, Technology Roadmapping and Project Risk Assessment, which were used to identify and manage the technical risks relating to the treatment of sodium bearing waste at the Idaho National Engineering and Environmental Laboratory. The waste treatment technology under consideration was Direct Vitrification. The primary objective of the Technology Roadmap is to identify technical data uncertainties for the technologies involved and to prioritize the testing or development studies to fill the data gaps. Similarly, project management's objective for a multi-million dollar construction project includes managing all the key risks in accordance to DOE O 413.3 - ''Program and Project Management for the Acquisition of Capital Assets.'' In the early stages, the Project Risk Assessment is based upon a qualitative analysis for each risk's probability and consequence. In order to clearly prioritize the work to resolve the technical issues identified in the Technology Roadmap, the issues must be cross- referenced to the project's Risk Assessment. This will enable the project to get the best value for the cost to mitigate the risks

  19. Risk-sensitive optimal feedback control accounts for sensorimotor behavior under uncertainty.

    Directory of Open Access Journals (Sweden)

    Arne J Nagengast

    2010-07-01

    Full Text Available Many aspects of human motor behavior can be understood using optimality principles such as optimal feedback control. However, these proposed optimal control models are risk-neutral; that is, they are indifferent to the variability of the movement cost. Here, we propose the use of a risk-sensitive optimal controller that incorporates movement cost variance either as an added cost (risk-averse controller or as an added value (risk-seeking controller to model human motor behavior in the face of uncertainty. We use a sensorimotor task to test the hypothesis that subjects are risk-sensitive. Subjects controlled a virtual ball undergoing Brownian motion towards a target. Subjects were required to minimize an explicit cost, in points, that was a combination of the final positional error of the ball and the integrated control cost. By testing subjects on different levels of Brownian motion noise and relative weighting of the position and control cost, we could distinguish between risk-sensitive and risk-neutral control. We show that subjects change their movement strategy pessimistically in the face of increased uncertainty in accord with the predictions of a risk-averse optimal controller. Our results suggest that risk-sensitivity is a fundamental attribute that needs to be incorporated into optimal feedback control models.

  20. Optimal natural resources management under uncertainty with catastrophic risk

    Energy Technology Data Exchange (ETDEWEB)

    Motoh, Tsujimura [Graduate School of Economics, Kyoto University, Yoshida-honmochi, Sakyo-ku, Kyoto 606-8501 (Japan)

    2004-05-01

    We examine an optimal natural resources management problem under uncertainty with catastrophic risk and investigate the optimal rate of use of a natural resource. For this purpose, we use stochastic control theory. We assume that, until a catastrophic event occurs, the stock of the natural resource is governed by a stochastic differential equation. We describe the catastrophic phenomenon as a Poisson process. From this analysis, we show the optimal rate of use of the natural resource in explicit form. Furthermore, we present comparative static results for the optimal rate of use of the natural resource.

  1. Optimal natural resources management under uncertainty with catastrophic risk

    International Nuclear Information System (INIS)

    Motoh, Tsujimura

    2004-01-01

    We examine an optimal natural resources management problem under uncertainty with catastrophic risk and investigate the optimal rate of use of a natural resource. For this purpose, we use stochastic control theory. We assume that, until a catastrophic event occurs, the stock of the natural resource is governed by a stochastic differential equation. We describe the catastrophic phenomenon as a Poisson process. From this analysis, we show the optimal rate of use of the natural resource in explicit form. Furthermore, we present comparative static results for the optimal rate of use of the natural resource

  2. Probabilistic evaluation of uncertainties and risks in aerospace components

    Science.gov (United States)

    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.

  3. Risk classification and uncertainty propagation for virtual water distribution systems

    International Nuclear Information System (INIS)

    Torres, Jacob M.; Brumbelow, Kelly; Guikema, Seth D.

    2009-01-01

    While the secrecy of real water distribution system data is crucial, it poses difficulty for research as results cannot be publicized. This data includes topological layouts of pipe networks, pump operation schedules, and water demands. Therefore, a library of virtual water distribution systems can be an important research tool for comparative development of analytical methods. A virtual city, 'Micropolis', has been developed, including a comprehensive water distribution system, as a first entry into such a library. This virtual city of 5000 residents is fully described in both geographic information systems (GIS) and EPANet hydraulic model frameworks. A risk classification scheme and Monte Carlo analysis are employed for an attempted water supply contamination attack. Model inputs to be considered include uncertainties in: daily water demand, seasonal demand, initial storage tank levels, the time of day a contamination event is initiated, duration of contamination event, and contaminant quantity. Findings show that reasonable uncertainties in model inputs produce high variability in exposure levels. It is also shown that exposure level distributions experience noticeable sensitivities to population clusters within the contaminant spread area. High uncertainties in exposure patterns lead to greater resources needed for more effective mitigation strategies.

  4. Assessment of volcanic hazards, vulnerability, risk and uncertainty (Invited)

    Science.gov (United States)

    Sparks, R. S.

    2009-12-01

    many sources of uncertainty in forecasting the areas that volcanic activity will effect and the severity of the effects. Uncertainties arise from: natural variability, inadequate data, biased data, incomplete data, lack of understanding of the processes, limitations to predictive models, ambiguity, and unknown unknowns. The description of volcanic hazards is thus necessarily probabilistic and requires assessment of the attendant uncertainties. Several issues arise from the probabilistic nature of volcanic hazards and the intrinsic uncertainties. Although zonation maps require well-defined boundaries for administrative pragmatism, such boundaries cannot divide areas that are completely safe from those that are unsafe. Levels of danger or safety need to be defined to decide on and justify boundaries through the concepts of vulnerability and risk. More data, better observations, improved models may reduce uncertainties, but can increase uncertainties and may lead to re-appraisal of zone boundaries. Probabilities inferred by statistical techniques are hard to communicate. Expert elicitation is an emerging methodology for risk assessment and uncertainty evaluation. The method has been applied at one major volcanic crisis (Soufrière Hills Volcano, Montserrat), and is being applied in planning for volcanic crises at Vesuvius.

  5. Integrating risks at contaminated sites

    International Nuclear Information System (INIS)

    MacDonell, M.; Habegger, L.; Nieves, L.; Schreiber, Z.; Travis, C.

    2000-01-01

    The U.S. Department of Energy (DOE) is responsible for a number of large sites across the country that were radioactively and chemically contaminated by past nuclear research, development, and production activities. Multiple risk assessments are being conducted for these sites to evaluate current conditions and determine what measures are needed to protect human health and the environment from today through the long term. Integrating the risks associated with multiple contaminants in different environmental media across extensive areas, over time periods that extend beyond 1,000 years, and for a number of different impact categories--from human health and ecological to social and economic--represents a considerable challenge. A central element of these integrated analyses is the ability to reflect key interrelationships among environmental resources and human communities that may be adversely affected by the actions or inactions being considered for a given site. Complicating the already difficult task of integrating many kinds of risk is the importance of reflecting the diverse values and preferences brought to bear by the multiple parties interested in the risk analysis process and outcome. An initial conceptual framework has been developed to provide an organized structure to this risk integration, with the aim of supporting effective environmental management decisions. This paper highlights key issues associated with comprehensive risk integration and offers suggestions developed from preliminary work at a complex DOE site

  6. Estimation of Uncertainty in Risk Assessment of Hydrogen Applications

    DEFF Research Database (Denmark)

    Markert, Frank; Krymsky, V.; Kozine, Igor

    2011-01-01

    Hydrogen technologies such as hydrogen fuelled vehicles and refuelling stations are being tested in practice in a number of projects (e.g. HyFleet-Cute and Whistler project) giving valuable information on the reliability and maintenance requirements. In order to establish refuelling stations the ...... probability and the NUSAP concept to quantify uncertainties of new not fully qualified hydrogen technologies and implications to risk management.......Hydrogen technologies such as hydrogen fuelled vehicles and refuelling stations are being tested in practice in a number of projects (e.g. HyFleet-Cute and Whistler project) giving valuable information on the reliability and maintenance requirements. In order to establish refuelling stations...... the permitting authorities request qualitative and quantitative risk assessments (QRA) to show the safety and acceptability in terms of failure frequencies and respective consequences. For new technologies not all statistical data might be established or are available in good quality causing assumptions...

  7. Methodology evaluation of innovative projects under risk and uncertainty

    Directory of Open Access Journals (Sweden)

    2012-09-01

    Full Text Available This article deals with problems connected with the assessment of innovative projects in the context of risk and uncertainty, topical issues of evaluation of innovative projects at the present stage of development of the Russian economy. By the example of the solution of the "crossing the river" is considering the possibility of using hierarchical models to address it. In what follows, and compares the priorities of different groups of factors are given by calculating the overall costs and benefits. The paper provides a rationale for combined use of four aspects: the beneficial aspects of the decision (the benefits and opportunities and negative (costs and risks that may lead to the decision in question.

  8. Uncertainty and Risk Management in Cyber Situational Awareness

    Science.gov (United States)

    Li, Jason; Ou, Xinming; Rajagopalan, Raj

    Handling cyber threats unavoidably needs to deal with both uncertain and imprecise information. What we can observe as potential malicious activities can seldom give us 100% confidence on important questions we care about, e.g. what machines are compromised and what damage has been incurred. In security planning, we need information on how likely a vulnerability can lead to a successful compromise to better balance security and functionality, performance, and ease of use. These information are at best qualitative and are often vague and imprecise. In cyber situational awareness, we have to rely on such imperfect information to detect real attacks and to prevent an attack from happening through appropriate risk management. This chapter surveys existing technologies in handling uncertainty and risk management in cyber situational awareness.

  9. Uncertainties

    Indian Academy of Sciences (India)

    To reflect this uncertainty in the climate scenarios, the use of AOGCMs that explicitly simulate the carbon cycle and chemistry of all the substances are needed. The Hadley Centre has developed a version of the climate model that allows the effect of climate change on the carbon cycle and its feedback into climate, to be ...

  10. Uncertainty

    International Nuclear Information System (INIS)

    Silva, T.A. da

    1988-01-01

    The comparison between the uncertainty method recommended by International Atomic Energy Agency (IAEA) and the and the International Weight and Measure Commitee (CIPM) are showed, for the calibration of clinical dosimeters in the secondary standard Dosimetry Laboratory (SSDL). (C.G.C.) [pt

  11. Scientific uncertainties associated with risk assessment of radiation

    International Nuclear Information System (INIS)

    Hubert, P.; Fagnani, F.

    1989-05-01

    The proper use and interpretation of data pertaining to biological effects of ionizing radiations is based on a continuous effort to discuss the various assumptions and uncertainties in the process of risk assessment. In this perspective, it has been considered useful by the Committee to review critically the general scientific foundations that constitute the basic framework of data for the evaluation of health effects of radiation. This review is an attempt to identify the main sources of uncertainties, to give, when possible, an order of magnitude for their relative importance, and to clarify the principal interactions between the different steps of the process of risk quantification. The discussion has been restricted to stochastic effects and especially to cancer induction in man: observations at the cellular levels and animal and in vitro experiments have not been considered. The consequences which might result from abandoning the hypothesis of linearity have not been directly examined in this draft, especially in respect to the concept of collective dose. Since another document dealing with 'Dose-response relationships for radiation-induced cancer' is in preparation, an effort has been made to avoid any overlap by making reference to that document whenever necessary

  12. Scientific uncertainties associated with risk assessment of radiation

    Energy Technology Data Exchange (ETDEWEB)

    Hubert, P; Fagnani, F

    1989-05-01

    The proper use and interpretation of data pertaining to biological effects of ionizing radiations is based on a continuous effort to discuss the various assumptions and uncertainties in the process of risk assessment. In this perspective, it has been considered useful by the Committee to review critically the general scientific foundations that constitute the basic framework of data for the evaluation of health effects of radiation. This review is an attempt to identify the main sources of uncertainties, to give, when possible, an order of magnitude for their relative importance, and to clarify the principal interactions between the different steps of the process of risk quantification. The discussion has been restricted to stochastic effects and especially to cancer induction in man: observations at the cellular levels and animal and in vitro experiments have not been considered. The consequences which might result from abandoning the hypothesis of linearity have not been directly examined in this draft, especially in respect to the concept of collective dose. Since another document dealing with 'Dose-response relationships for radiation-induced cancer' is in preparation, an effort has been made to avoid any overlap by making reference to that document whenever necessary.

  13. Bayesian models for comparative analysis integrating phylogenetic uncertainty

    Directory of Open Access Journals (Sweden)

    Villemereuil Pierre de

    2012-06-01

    Full Text Available Abstract Background Uncertainty in comparative analyses can come from at least two sources: a phylogenetic uncertainty in the tree topology or branch lengths, and b uncertainty due to intraspecific variation in trait values, either due to measurement error or natural individual variation. Most phylogenetic comparative methods do not account for such uncertainties. Not accounting for these sources of uncertainty leads to false perceptions of precision (confidence intervals will be too narrow and inflated significance in hypothesis testing (e.g. p-values will be too small. Although there is some application-specific software for fitting Bayesian models accounting for phylogenetic error, more general and flexible software is desirable. Methods We developed models to directly incorporate phylogenetic uncertainty into a range of analyses that biologists commonly perform, using a Bayesian framework and Markov Chain Monte Carlo analyses. Results We demonstrate applications in linear regression, quantification of phylogenetic signal, and measurement error models. Phylogenetic uncertainty was incorporated by applying a prior distribution for the phylogeny, where this distribution consisted of the posterior tree sets from Bayesian phylogenetic tree estimation programs. The models were analysed using simulated data sets, and applied to a real data set on plant traits, from rainforest plant species in Northern Australia. Analyses were performed using the free and open source software OpenBUGS and JAGS. Conclusions Incorporating phylogenetic uncertainty through an empirical prior distribution of trees leads to more precise estimation of regression model parameters than using a single consensus tree and enables a more realistic estimation of confidence intervals. In addition, models incorporating measurement errors and/or individual variation, in one or both variables, are easily formulated in the Bayesian framework. We show that BUGS is a useful, flexible

  14. Bayesian models for comparative analysis integrating phylogenetic uncertainty

    Science.gov (United States)

    2012-01-01

    Background Uncertainty in comparative analyses can come from at least two sources: a) phylogenetic uncertainty in the tree topology or branch lengths, and b) uncertainty due to intraspecific variation in trait values, either due to measurement error or natural individual variation. Most phylogenetic comparative methods do not account for such uncertainties. Not accounting for these sources of uncertainty leads to false perceptions of precision (confidence intervals will be too narrow) and inflated significance in hypothesis testing (e.g. p-values will be too small). Although there is some application-specific software for fitting Bayesian models accounting for phylogenetic error, more general and flexible software is desirable. Methods We developed models to directly incorporate phylogenetic uncertainty into a range of analyses that biologists commonly perform, using a Bayesian framework and Markov Chain Monte Carlo analyses. Results We demonstrate applications in linear regression, quantification of phylogenetic signal, and measurement error models. Phylogenetic uncertainty was incorporated by applying a prior distribution for the phylogeny, where this distribution consisted of the posterior tree sets from Bayesian phylogenetic tree estimation programs. The models were analysed using simulated data sets, and applied to a real data set on plant traits, from rainforest plant species in Northern Australia. Analyses were performed using the free and open source software OpenBUGS and JAGS. Conclusions Incorporating phylogenetic uncertainty through an empirical prior distribution of trees leads to more precise estimation of regression model parameters than using a single consensus tree and enables a more realistic estimation of confidence intervals. In addition, models incorporating measurement errors and/or individual variation, in one or both variables, are easily formulated in the Bayesian framework. We show that BUGS is a useful, flexible general purpose tool for

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

    OpenAIRE

    Jacobs, R.; Voet, van der, H.; Braak, ter, C.J.F.

    2015-01-01

    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 integrate...

  16. Visualizing the uncertainty in the relationship between seasonal average climate and malaria risk.

    Science.gov (United States)

    MacLeod, D A; Morse, A P

    2014-12-02

    Around $1.6 billion per year is spent financing anti-malaria initiatives, and though malaria morbidity is falling, the impact of annual epidemics remains significant. Whilst malaria risk may increase with climate change, projections are highly uncertain and to sidestep this intractable uncertainty, adaptation efforts should improve societal ability to anticipate and mitigate individual events. Anticipation of climate-related events is made possible by seasonal climate forecasting, from which warnings of anomalous seasonal average temperature and rainfall, months in advance are possible. Seasonal climate hindcasts have been used to drive climate-based models for malaria, showing significant skill for observed malaria incidence. However, the relationship between seasonal average climate and malaria risk remains unquantified. Here we explore this relationship, using a dynamic weather-driven malaria model. We also quantify key uncertainty in the malaria model, by introducing variability in one of the first order uncertainties in model formulation. Results are visualized as location-specific impact surfaces: easily integrated with ensemble seasonal climate forecasts, and intuitively communicating quantified uncertainty. Methods are demonstrated for two epidemic regions, and are not limited to malaria modeling; the visualization method could be applied to any climate impact.

  17. Sensing risk, fearing uncertainty: Systems science approach to change.

    Directory of Open Access Journals (Sweden)

    Ivo P Janecka

    2014-03-01

    Full Text Available BackgroundMedicine devotes its primary focus to understanding change, from cells to network relationships; observations of non-linearity are inescapable. Recent events provide extraordinary examples of major non-linear surprises within the societal system: human genome-from anticipated 100,000+ genes to only 20,000+; junk DNA-initially ignored but now proven to control genetic processes; economic reversals-bursting of bubbles in technology, housing, finance; foreign wars; relentless rise in obesity, neurodegenerative diseases.There are two attributes of systems science that are especially relevant to this research: One- it offers a method for creating a structural context with a guiding path to pragmatic knowledge; and, two- it gives pre-eminence to sensory input capable to register, evaluate, and react to change. Material / MethodPublic domain records of change, during the last fifty years, have been studied in the context of systems science, the dynamic systems model, and various cycles. Results / Conclusions Change is dynamic, ever-present, never isolated, and of variable impact; it reflects innumerable relationships among contextual systems; change can be perceived as risk or uncertainty depending upon how the assessment is made; risk is quantifiable by sensory input and generates a degree of rational optimism; uncertainty is not quantifiable and evokes fear; trust is key to sharing risk; the measurable financial credit can be a proxy for societal trust; expanding credit dilutes trust; when a credit bubble bursts, so will trust; absence of trust paralyzes systems’ relationships leading to disorganized complexity which prevents value creation and heightens the probability of random events; disappearance of value, accompanied by chaos, threatens all systems.From personal health to economic sustainability and collective rationality, most examined components of the societal system were found not to be optimized and trust was not in evidence.

  18. Quantification of Uncertainties in Integrated Spacecraft System Models, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — The proposed effort is to investigate a novel uncertainty quantification (UQ) approach based on non-intrusive polynomial chaos (NIPC) for computationally efficient...

  19. Uncertainties in Cancer Risk Coefficients for Environmental Exposure to Radionuclides. An Uncertainty Analysis for Risk Coefficients Reported in Federal Guidance Report No. 13

    Energy Technology Data Exchange (ETDEWEB)

    Pawel, David [U.S. Environmental Protection Agency; Leggett, Richard Wayne [ORNL; Eckerman, Keith F [ORNL; Nelson, Christopher [U.S. Environmental Protection Agency

    2007-01-01

    Federal Guidance Report No. 13 (FGR 13) provides risk coefficients for estimation of the risk of cancer due to low-level exposure to each of more than 800 radionuclides. Uncertainties in risk coefficients were quantified in FGR 13 for 33 cases (exposure to each of 11 radionuclides by each of three exposure pathways) on the basis of sensitivity analyses in which various combinations of plausible biokinetic, dosimetric, and radiation risk models were used to generate alternative risk coefficients. The present report updates the uncertainty analysis in FGR 13 for the cases of inhalation and ingestion of radionuclides and expands the analysis to all radionuclides addressed in that report. The analysis indicates that most risk coefficients for inhalation or ingestion of radionuclides are determined within a factor of 5 or less by current information. That is, application of alternate plausible biokinetic and dosimetric models and radiation risk models (based on the linear, no-threshold hypothesis with an adjustment for the dose and dose rate effectiveness factor) is unlikely to change these coefficients by more than a factor of 5. In this analysis the assessed uncertainty in the radiation risk model was found to be the main determinant of the uncertainty category for most risk coefficients, but conclusions concerning the relative contributions of risk and dose models to the total uncertainty in a risk coefficient may depend strongly on the method of assessing uncertainties in the risk model.

  20. Integrated supply chain risk management

    Directory of Open Access Journals (Sweden)

    Riaan Bredell

    2007-11-01

    Full Text Available Integrated supply chain risk management (ISCRM has become indispensable to the theory and practice of supply chain management. The economic and political realities of the modern world require not only a different approach to supply chain management, but also bold steps to secure supply chain performance and sustainable wealth creation. Integrated supply chain risk management provides supply chain organisations with a level of insight into their supply chains yet to be achieved. If correctly applied, this process may optimise management decision-making and assist in the protection and enhancement of shareholder value.

  1. Margins for geometric uncertainty around organs at risk in radiotherapy

    International Nuclear Information System (INIS)

    McKenzie, Alan; Herk, Marcel van; Mijnheer, Ben

    2002-01-01

    Background and purpose: ICRU Report 62 suggests drawing margins around organs at risk (ORs) to produce planning organ at risk volumes (PRVs) to account for geometric uncertainty in the radiotherapy treatment process. This paper proposes an algorithm for drawing such margins, and compares the recommended margin widths with examples from clinical practice and discusses the limitations of the approach. Method: The use of the PRV defined in this way is that, despite the geometric uncertainties, the dose calculated within the PRV by the treatment planning system can be used to represent the dose in the OR with a certain confidence level. A suitable level is where, in the majority of cases (90%), the dose-volume histogram of the PRV will not under-represent the high-dose components in the OR. In order to provide guidelines on how to do this in clinical practice, this paper distinguishes types of OR in terms of the tolerance doses relative to the prescription dose and suggests appropriate margins for serial-structure and parallel-structure ORs. Results: In some instances of large and parallel ORs, the clinician may judge that the complication risk in omitting a margin is acceptable. Otherwise, for all types of OR, systematic, treatment preparation uncertainties may be accommodated by an OR→PRV margin width of 1.3Σ. Here, Σ is the standard deviation of the combined systematic (treatment preparation) uncertainties. In the case of serial ORs or small, parallel ORs, the effects of blurring caused by daily treatment execution errors (set-up and organ motion) should be taken into account. Near a region of high dose, blurring tends to shift the isodoses away from the unblurred edge as shown on the treatment planning system by an amount that may be represented by 0.5σ. This margin may be used either to increase or to decrease the margin already calculated for systematic uncertainties, depending upon the size of the tolerance dose relative to the detailed planned dose

  2. Guidance for treatment of variability and uncertainty in ecological risk assessments of contaminated sites

    International Nuclear Information System (INIS)

    1998-06-01

    Uncertainty is a seemingly simple concept that has caused great confusion and conflict in the field of risk assessment. This report offers guidance for the analysis and presentation of variability and uncertainty in ecological risk assessments, an important issue in the remedial investigation and feasibility study processes. This report discusses concepts of probability in terms of variance and uncertainty, describes how these concepts differ in ecological risk assessment from human health risk assessment, and describes probabilistic aspects of specific ecological risk assessment techniques. The report ends with 17 points to consider in performing an uncertainty analysis for an ecological risk assessment of a contaminated site

  3. Managing risks of market price uncertainty for a microgrid operation

    Science.gov (United States)

    Raghavan, Sriram

    After deregulation of electricity in the United States, the day-ahead and real-time markets allow load serving entities and generation companies to bid and purchase/sell energy under the supervision of the independent system operator (ISO). The electricity market prices are inherently uncertain, and can be highly volatile. The main objective of this thesis is to hedge against the risk from the uncertainty of the market prices when purchasing/selling energy from/to the market. The energy manager can also schedule distributed generators (DGs) and storage of the microgrid to meet the demand, in addition to energy transactions from the market. The risk measure used in this work is the variance of the uncertain market purchase/sale cost/revenue, assuming the price following a Gaussian distribution. Using Markowitz optimization, the risk is minimized to find the optimal mix of purchase from the markets. The problem is formulated as a mixed integer quadratic program. The microgrid at Illinois Institute of Technology (IIT) in Chicago, IL was used as a case study. The result of this work reveals the tradeoff faced by the microgrid energy manager between minimizing the risk and minimizing the mean of the total operating cost (TOC) of the microgrid. With this information, the microgrid energy manager can make decisions in the day-ahead and real-time markets according to their risk aversion preference. The assumption of market prices following Gaussian distribution is also verified to be reasonable for the purpose of hedging against their risks. This is done by comparing the result of the proposed formulation with that obtained from the sample market prices randomly generated using the distribution of actual historic market price data.

  4. Integrated Foreign Exchange Risk Management

    DEFF Research Database (Denmark)

    Aabo, Tom; Høg, Esben; Kuhn, Jochen

    Empirical research has focused on export as a proxy for the exchange rate exposure and the use of foreign exchange derivatives as the instrument to deal with this exposure. This empirical study applies an integrated foreign exchange risk management approach with a particular focus on the role...

  5. Managing IT Integration Risk in Acquisitions

    DEFF Research Database (Denmark)

    Henningsson, Stefan; Kettinger, William J.

    2016-01-01

    The article discusses a framework for evaluating risk of information technology (IT) integration in acquisitions. Topics include the use of the experience of serial acquirer Trelleborg AB to show the merits of the framework for managing the risk and to determine low-risk acquisitions......, the importance of managing IT integration risk, and various risk areas for acquisition IT integration....

  6. Uncertainties in smart grids behavior and modeling: What are the risks and vulnerabilities? How to analyze them?

    Energy Technology Data Exchange (ETDEWEB)

    Zio, Enrico, E-mail: enrico.zio@ecp.fr [Ecole Centrale Paris - Supelec, Paris (France); Politecnico di Milano, Milano (Italy); Aven, Terje, E-mail: terje.aven@uis.no [University of Stavanger, Stavanger (Norway)

    2011-10-15

    This paper looks into the future world of smart grids from a rather different perspective than usual: that of uncertainties and the related risks and vulnerabilities. An analysis of the foreseen constituents of smart grids and of the technological, operational, economical and policy-driven challenges is carried out to identify and characterize the related uncertainties and associated risks and vulnerabilities. The focus is on the challenges posed to the representation and treatment of uncertainties in the performance assessment of such systems, given their complexity and high-level of integration of novel technologies. A general framework of analysis is proposed. - Highlights: > We have looked into the development and operation of smart grids for power distribution. > We have identified a number of uncertainties, which are expected to play an influential role. > We have provided some guidelines to address these issues, based on probability intervals.

  7. Securitization of residential solar photovoltaic assets: Costs, risks and uncertainty

    International Nuclear Information System (INIS)

    Alafita, T.; Pearce, J.M.

    2014-01-01

    Limited access to low-cost financing is an impediment to high-velocity technological diffusion and high grid penetration of solar photovoltaic (PV) technology. Securitization of solar assets provides a potential solution to this problem. This paper assesses the viability of solar asset-backed securities (ABS) as a lower cost financing mechanism and identifies policies that could facilitate implementation of securitization. First, traditional solar financing is examined to provide a baseline for cost comparisons. Next, the securitization process is modeled. The model enables identification of several junctures at which risk and uncertainty influence costs. Next, parameter values are assigned and used to generate cost estimates. Results show that, under reasonable assumptions, securitization of solar power purchase agreements (PPA) can significantly reduce project financing costs, suggesting that securitization is a viable mechanism for improving the financing of PV projects. The clear impediment to the successful launch of a solar ABS is measuring and understanding the riskiness of underlying assets. This study identifies three classes of policy intervention that lower the cost of ABS by reducing risk or by improving the measurement of risk: (i) standardization of contracts and the contracting process, (ii) improved access to contract and equipment performance data, and (iii) geographic diversification. - Highlights: • Limited access to low-cost financing is hampering penetration of solar PV. • Solar asset-backed securities (ABS) provide a low cost financing mechanism. • Results for securitization of solar leases and power purchase agreements (PPA). • Securitization can significantly reduce project financing costs. • Identifies policy intervention that lower cost of ABS by reducing risk

  8. Evaluating the Impact of Contaminant Dilution and Biodegradation in Uncertainty Quantification of Human Health Risk

    Science.gov (United States)

    Zarlenga, Antonio; de Barros, Felipe; Fiori, Aldo

    2016-04-01

    We present a probabilistic framework for assessing human health risk due to groundwater contamination. Our goal is to quantify how physical hydrogeological and biochemical parameters control the magnitude and uncertainty of human health risk. Our methodology captures the whole risk chain from the aquifer contamination to the tap water assumption by human population. The contaminant concentration, the key parameter for the risk estimation, is governed by the interplay between the large-scale advection, caused by heterogeneity and the degradation processes strictly related to the local scale dispersion processes. The core of the hazard identification and of the methodology is the reactive transport model: erratic displacement of contaminant in groundwater, due to the spatial variability of hydraulic conductivity (K), is characterized by a first-order Lagrangian stochastic model; different dynamics are considered as possible ways of biodegradation in aerobic and anaerobic conditions. With the goal of quantifying uncertainty, the Beta distribution is assumed for the concentration probability density function (pdf) model, while different levels of approximation are explored for the estimation of the one-point concentration moments. The information pertaining the flow and transport is connected with a proper dose response assessment which generally involves the estimation of physiological parameters of the exposed population. Human health response depends on the exposed individual metabolism (e.g. variability) and is subject to uncertainty. Therefore, the health parameters are intrinsically a stochastic. As a consequence, we provide an integrated in a global probabilistic human health risk framework which allows the propagation of the uncertainty from multiple sources. The final result, the health risk pdf, is expressed as function of a few relevant, physically-based parameters such as the size of the injection area, the Péclet number, the K structure metrics and

  9. Managing uncertainty in fi shing and processing of an integrated ...

    African Journals Online (AJOL)

    The firm attempts to manage this uncertainty through planning co-ordination of fishing trawler scheduling, catch quota, processing and labour allocation, and inventory control. Schedules must necessarily be determined over some finite planning time horizon, and the trawler schedule itself introduces man-made variability, ...

  10. Risk Formulations versus Comprehensive Uncertainty Characterizations for Climate Extremes and their Impacts

    Science.gov (United States)

    Parish, E. S.; Ganguly, A. R.

    2009-12-01

    Climate extremes—defined inclusively as extreme hydro-metrological events and regional changes in climate patterns at decadal scales—and their impacts on natural, engineered or human systems, represent among the most significant knowledge-gaps in climate prediction and integrated assessments in a post-AR4 world. Risks and uncertainties are related but distinct concepts. However, their relevance to decision-support tools in the context of climate change is indisputable. The opportunities and challenges are presented with case studies developed for stakeholders and policy makers.

  11. From risk management to uncertainty management: a significant change in project management

    Institute of Scientific and Technical Information of China (English)

    LI Gui-jun; ZHANG Yue-song

    2006-01-01

    Starting with the meanings of the terms "risk" and "uncertainty,"" he paper compares uncertainty management with risk management in project management. We bring some doubt to the use of "risk" and "uncertainty" interchangeably in project management and deem their scope, methods, responses, monitoring and controlling should be different too. Illustrations are given covering terminology, description, and treatment from different perspectives of uncertainty management and risk management. Furthermore, the paper retains that project risk management (PRM) processes might be modified to facilitate an uncertainty management perspective,and we support that project uncertainty management (PUM) can enlarge its contribution to improving project management performance, which will result in a significant change in emphasis compared with most risk management.

  12. Safety Goal, Multi-unit Risk and PSA Uncertainty

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Joon-Eon [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2015-10-15

    The safety goal is an answer of each country to the question 'How safe is safe enough?'. Table 1 shows some examples of the safety goal. However, many countries including Korea do not have the official safety goal for NPPs up to now since the establishment of safety goal is not just a technical issue but a very complex socio-technical issue. In establishing the safety goal for nuclear facilities, we have to consider various factors including not only technical aspects but also social, cultural ones. Recently, Korea is trying to establish the official safety goal. In this paper, we will review the relationship between the safety goal and Probabilistic Safety Assessment (PSA). We will also address some important technical issues to be considered in establishing the safety goal for NPPs from PSA point of view, i.e. a multi-unit risk issue and the uncertainty of PSA. In this paper, we reviewed some issues related to the safety goal and PSA. We believe that the safety goal is to be established in Korea considering the multi-unit risk. In addition, the relationship between the safety goal and PSA should be also defined clearly since PSA is the only way to answer to the question 'How safe is safe enough?'.

  13. A review of different perspectives on uncertainty and risk and an alternative modeling paradigm

    International Nuclear Information System (INIS)

    Samson, Sundeep; Reneke, James A.; Wiecek, Margaret M.

    2009-01-01

    The literature in economics, finance, operations research, engineering and in general mathematics is first reviewed on the subject of defining uncertainty and risk. The review goes back to 1901. Different perspectives on uncertainty and risk are examined and a new paradigm to model uncertainty and risk is proposed using relevant ideas from this study. This new paradigm is used to represent, aggregate and propagate uncertainty and interpret the resulting variability in a challenge problem developed by Oberkampf et al. [2004, Challenge problems: uncertainty in system response given uncertain parameters. Reliab Eng Syst Safety 2004; 85(1): 11-9]. The challenge problem is further extended into a decision problem that is treated within a multicriteria decision making framework to illustrate how the new paradigm yields optimal decisions under uncertainty. The accompanying risk is defined as the probability of an unsatisfactory system response quantified by a random function of the uncertainty

  14. Integrated fatigue damage diagnosis and prognosis under uncertainties

    Data.gov (United States)

    National Aeronautics and Space Administration — An integrated fatigue damage diagnosis and prognosis framework is proposed in this paper. The proposed methodology integrates a Lamb wave-based damage detection...

  15. Integrated risk information system (IRIS)

    Energy Technology Data Exchange (ETDEWEB)

    Tuxen, L. [Environmental Protection Agency, Washington, DC (United States)

    1990-12-31

    The Integrated Risk Information System (IRIS) is an electronic information system developed by the US Environmental Protection Agency (EPA) containing information related to health risk assessment. IRIS is the Agency`s primary vehicle for communication of chronic health hazard information that represents Agency consensus following comprehensive review by intra-Agency work groups. The original purpose for developing IRIS was to provide guidance to EPA personnel in making risk management decisions. This original purpose for developing IRIS was to guidance to EPA personnel in making risk management decisions. This role has expanded and evolved with wider access and use of the system. IRIS contains chemical-specific information in summary format for approximately 500 chemicals. IRIS is available to the general public on the National Library of Medicine`s Toxicology Data Network (TOXNET) and on diskettes through the National Technical Information Service (NTIS).

  16. Too Risk Averse to Stay Honest? Business Corruption, Uncertainty and Attitudes Toward Risk

    OpenAIRE

    Soreide, T.

    2009-01-01

    The presence of business-corruption provokes firms to make choices between legal business approaches and illegal bribery. The outcome of a chosen strategy will usually be uncertain at the time the decision is made, and a firm's decision will depend partly on its attitude towards risk. Drawing on empirical results about business corruption, this paper describes the risks, uncertainties and benefits attached to bribery, and specifies their impact on firms' propensity to offer bribes. it then de...

  17. Risk Worth Taking - Entrepreneurial Behaviour When Faced with Risk and Uncertainty

    DEFF Research Database (Denmark)

    Zichella, Giulio

    theory suggests differences in risk taking due to individual characteristics. However, entrepreneurship theory did not provide empirical support for such differences. Using data from a laboratory experiment with simple money games, we observe how individuals from two different groups (entrepreneurial......-oriented, non-entrepreneurial-oriented) react to different degrees of risk and uncertainty when real monetary incentives are involved in each decision. The analysis reveals significant differences between entrepreneurial and non-entrepreneurial-oriented individuals in their decision making. In particular...

  18. Key drivers and economic consequences of high-end climate scenarios: uncertainties and risks

    DEFF Research Database (Denmark)

    Halsnæs, Kirsten; Kaspersen, Per Skougaard; Drews, Martin

    2015-01-01

    The consequences of high-end climate scenarios and the risks of extreme events involve a number of critical assumptions and methodological challenges related to key uncertainties in climate scenarios and modelling, impact analysis, and economics. A methodological framework for integrated analysis...... of extreme events increase beyond scaling, and in combination with economic assumptions we find a very wide range of risk estimates for urban precipitation events. A sensitivity analysis addresses 32 combinations of climate scenarios, damage cost curve approaches, and economic assumptions, including risk...... aversion and equity represented by discount rates. Major impacts of alternative assumptions are investigated. As a result, this study demonstrates that in terms of decision making the actual expectations concerning future climate scenarios and the economic assumptions applied are very important...

  19. INTEGRATION OF SYSTEM COMPONENTS AND UNCERTAINTY ANALYSIS - HANFORD EXAMPLES

    International Nuclear Information System (INIS)

    Wood, M.I.

    2009-01-01

    (sm b ullet) Deterministic 'One Off' analyses as basis for evaluating sensitivity and uncertainty relative to reference case (sm b ullet) Spatial coverage identical to reference case (sm b ullet) Two types of analysis assumptions - Minimax parameter values around reference case conditions - 'What If' cases that change reference case condition and associated parameter values (sm b ullet) No conclusions about likelihood of estimated result other than' qualitative expectation that actual outcome should tend toward reference case estimate

  20. Uncertainty Estimation Cheat Sheet for Probabilistic Risk Assessment

    Science.gov (United States)

    Britton, Paul T.; Al Hassan, Mohammad; Ring, Robert W.

    2017-01-01

    "Uncertainty analysis itself is uncertain, therefore, you cannot evaluate it exactly," Source Uncertain Quantitative results for aerospace engineering problems are influenced by many sources of uncertainty. Uncertainty analysis aims to make a technical contribution to decision-making through the quantification of uncertainties in the relevant variables as well as through the propagation of these uncertainties up to the result. Uncertainty can be thought of as a measure of the 'goodness' of a result and is typically represented as statistical dispersion. This paper will explain common measures of centrality and dispersion; and-with examples-will provide guidelines for how they may be estimated to ensure effective technical contributions to decision-making.

  1. Implications of model uncertainty for the practice of risk assessment

    International Nuclear Information System (INIS)

    Laskey, K.B.

    1994-01-01

    A model is a representation of a system that can be used to answer questions about the system's behavior. The term model uncertainty refers to problems in which there is no generally agreed upon, validated model that can be used as a surrogate for the system itself. Model uncertainty affects both the methodology appropriate for building models and how models should be used. This paper discusses representations of model uncertainty, methodologies for exercising and interpreting models in the presence of model uncertainty, and the appropriate use of fallible models for policy making

  2. Evaluating Sources of Risks in Large Engineering Projects: The Roles of Equivocality and Uncertainty

    Directory of Open Access Journals (Sweden)

    Leena Pekkinen

    2015-11-01

    Full Text Available Contemporary project risk management literature introduces uncertainty, i.e., the lack of information, as a fundamental basis of project risks. In this study the authors assert that equivocality, i.e., the existence of multiple and conflicting interpretations, can also serve as a basis of risks. With an in-depth empirical investigation of a large complex engineering project the authors identified risk sources having their bases in the situations where uncertainty or equivocality was the predominant attribute. The information processing theory proposes different managerial practices for risk management based on the sources of risks in uncertainty or equivocality.

  3. A Quantitative Measure For Evaluating Project Uncertainty Under Variation And Risk Effects

    Directory of Open Access Journals (Sweden)

    A. Chenarani

    2017-10-01

    Full Text Available The effects of uncertainty on a project and the risk event as the consequence of uncertainty are analyzed. The uncertainty index is proposed as a quantitative measure for evaluating the uncertainty of a project. This is done by employing entropy as the indicator of system disorder and lack of information. By employing this index, the uncertainty of each activity and its increase due to risk effects as well as project uncertainty changes as a function of time can be assessed. The results are implemented and analyzed for a small turbojet engine development project as the case study. The results of this study can be useful for project managers and other stakeholders for selecting the most effective risk management and uncertainty controlling method.

  4. An introductory guide to uncertainty analysis in environmental and health risk assessment. Environmental Restoration Program

    International Nuclear Information System (INIS)

    Hammonds, J.S.; Hoffman, F.O.; Bartell, S.M.

    1994-12-01

    This report presents guidelines for evaluating uncertainty in mathematical equations and computer models applied to assess human health and environmental risk. Uncertainty analyses involve the propagation of uncertainty in model parameters and model structure to obtain confidence statements for the estimate of risk and identify the model components of dominant importance. Uncertainty analyses are required when there is no a priori knowledge about uncertainty in the risk estimate and when there is a chance that the failure to assess uncertainty may affect the selection of wrong options for risk reduction. Uncertainty analyses are effective when they are conducted in an iterative mode. When the uncertainty in the risk estimate is intolerable for decision-making, additional data are acquired for the dominant model components that contribute most to uncertainty. This process is repeated until the level of residual uncertainty can be tolerated. A analytical and numerical methods for error propagation are presented along with methods for identifying the most important contributors to uncertainty. Monte Carlo simulation with either Simple Random Sampling (SRS) or Latin Hypercube Sampling (LHS) is proposed as the most robust method for propagating uncertainty through either simple or complex models. A distinction is made between simulating a stochastically varying assessment endpoint (i.e., the distribution of individual risks in an exposed population) and quantifying uncertainty due to lack of knowledge about a fixed but unknown quantity (e.g., a specific individual, the maximally exposed individual, or the mean, median, or 95%-tile of the distribution of exposed individuals). Emphasis is placed on the need for subjective judgement to quantify uncertainty when relevant data are absent or incomplete

  5. Uncertainty assessment of urban pluvial flood risk in a context of climate change adaptation decision making

    DEFF Research Database (Denmark)

    Arnbjerg-Nielsen, Karsten; Zhou, Qianqian

    2014-01-01

    uncertainty analysis, which can assess and quantify the overall uncertainty in relation to climate change adaptation to urban flash floods. The analysis is based on an uncertainty cascade that by means of Monte Carlo simulations of flood risk assessments incorporates climate change impacts as a key driver......There has been a significant increase in climatic extremes in many regions. In Central and Northern Europe, this has led to more frequent and more severe floods. Along with improved flood modelling technologies this has enabled development of economic assessment of climate change adaptation...... to increasing urban flood risk. Assessment of adaptation strategies often requires a comprehensive risk-based economic analysis of current risk, drivers of change of risk over time, and measures to reduce the risk. However, such studies are often associated with large uncertainties. The uncertainties arise from...

  6. Methodology for optimization of process integration schemes in a biorefinery under uncertainty

    International Nuclear Information System (INIS)

    Marta Abreu de las Villas (Cuba))" data-affiliation=" (Departamento de Ingeniería Química. Facultad de Química y Farmacia. Universidad Central Marta Abreu de las Villas (Cuba))" >González-Cortés, Meilyn; Marta Abreu de las Villas (Cuba))" data-affiliation=" (Departamento de Ingeniería Química. Facultad de Química y Farmacia. Universidad Central Marta Abreu de las Villas (Cuba))" >Martínez-Martínez, Yenisleidys; Marta Abreu de las Villas (Cuba))" data-affiliation=" (Departamento de Ingeniería Química. Facultad de Química y Farmacia. Universidad Central Marta Abreu de las Villas (Cuba))" >Albernas-Carvajal, Yailet; Marta Abreu de las Villas (Cuba))" data-affiliation=" (Departamento de Ingeniería Química. Facultad de Química y Farmacia. Universidad Central Marta Abreu de las Villas (Cuba))" >Pedraza-Garciga, Julio; Marta Abreu de las Villas (Cuba))" data-affiliation=" (Departamento de Ingeniería Química. Facultad de Química y Farmacia. Universidad Central Marta Abreu de las Villas (Cuba))" >Morales-Zamora, Marlen

    2017-01-01

    The uncertainty has a great impact in the investment decisions, operability of the plants and in the feasibility of integration opportunities in the chemical processes. This paper, presents the steps to consider the optimization of process investment in the processes integration under conditions of uncertainty. It is shown the potentialities of the biomass cane of sugar for the integration with several plants in a biorefinery scheme for the obtaining chemical products, thermal and electric energy. Among the factories with potentialities for this integration are the pulp and paper and sugar factories and other derivative processes. Theses factories have common resources and also have a variety of products that can be exchange between them so certain products generated in a one of them can be raw matter in another plant. The methodology developed guide to obtaining of feasible investment projects under uncertainty. As objective function was considered the maximization of net profitable value in different scenarios that are generated from the integration scheme. (author)

  7. Nonlinear Uncertainty Propagation of Satellite State Error for Tracking and Conjunction Risk Assessment

    Science.gov (United States)

    2017-12-18

    AFRL-RV-PS- AFRL-RV-PS- TR-2017-0177 TR-2017-0177 NONLINEAR UNCERTAINTY PROPAGATION OF SATELLITE STATE ERROR FOR TRACKING AND CONJUNCTION RISK...Uncertainty Propagation of Satellite State Error for Tracking and Conjunction Risk Assessment 5a. CONTRACT NUMBER FA9453-16-1-0084 5b. GRANT NUMBER...prediction and satellite conjunction analysis. Statistical approach utilizes novel methods to build better uncertainty state characterization in the context

  8. Integrating Dynamic Pricing and Replenishment Decisions Under Supply Capacity Uncertainty

    OpenAIRE

    Qi Feng

    2010-01-01

    This paper examines an integrated decision-making process regarding pricing for uncertain demand and sourcing from uncertain supply, which are often studied separately in the literature. Our analysis of the integrated system suggests that the base stock list price policy fails to achieve optimality even under deterministic demand. Instead, the optimal policy is characterized by two critical values: a reorder point and a target safety stock. Under this policy, a positive order is issued if and...

  9. Integrating geological uncertainty in long-term open pit mine production planning by ant colony optimization

    Science.gov (United States)

    Gilani, Seyed-Omid; Sattarvand, Javad

    2016-02-01

    Meeting production targets in terms of ore quantity and quality is critical for a successful mining operation. In-situ grade uncertainty causes both deviations from production targets and general financial deficits. A new stochastic optimization algorithm based on ant colony optimization (ACO) approach is developed herein to integrate geological uncertainty described through a series of the simulated ore bodies. Two different strategies were developed based on a single predefined probability value (Prob) and multiple probability values (Pro bnt) , respectively in order to improve the initial solutions that created by deterministic ACO procedure. Application at the Sungun copper mine in the northwest of Iran demonstrate the abilities of the stochastic approach to create a single schedule and control the risk of deviating from production targets over time and also increase the project value. A comparison between two strategies and traditional approach illustrates that the multiple probability strategy is able to produce better schedules, however, the single predefined probability is more practical in projects requiring of high flexibility degree.

  10. Learning Risk-Taking and Coping with Uncertainty through Experiential, Team-Based Entrepreneurship Education

    Science.gov (United States)

    Arpiainen, Riitta-Liisa; Kurczewska, Agnieszka

    2017-01-01

    This empirical study investigates how students' perceptions of risk-taking and coping with uncertainty change while they are exposed to experience-based entrepreneurship education. The aim of the study is twofold. First, the authors set out to identify the dynamics of entrepreneurial thinking among students experiencing risk and uncertainty while…

  11. Risk analysis under uncertainty, the precautionary principle, and the new EU chemicals strategy.

    Science.gov (United States)

    Rogers, Michael D

    2003-06-01

    Three categories of uncertainty in relation to risk assessment are defined; uncertainty in effect, uncertainty in cause, and uncertainty in the relationship between a hypothesised cause and effect. The Precautionary Principle (PP) relates to the third type of uncertainty. Three broad descriptions of the PP are set out, uncertainty justifies action, uncertainty requires action, and uncertainty requires a reversal of the burden of proof for risk assessments. The application of the PP is controversial but what matters in practise is the precautionary action (PA) that follows. The criteria by which the PAs should be judged are detailed. This framework for risk assessment and management under uncertainty is then applied to the envisaged European system for the regulation of chemicals. A new EU regulatory system has been proposed which shifts the burden of proof concerning risk assessments from the regulator to the producer, and embodies the PP in all three of its main regulatory stages. The proposals are critically discussed in relation to three chemicals, namely, atrazine (an endocrine disrupter), cadmium (toxic and possibly carcinogenic), and hydrogen fluoride (a toxic, high-production-volume chemical). Reversing the burden of proof will speed up the regulatory process but the examples demonstrate that applying the PP appropriately, and balancing the countervailing risks and the socio-economic benefits, will continue to be a difficult task for the regulator. The paper concludes with a discussion of the role of precaution in the management of change and of the importance of trust in the effective regulation of uncertain risks.

  12. Optimisation of internal contamination monitoring programme by integration of uncertainties

    International Nuclear Information System (INIS)

    Davesne, E.; Casanova, P.; Chojnacki, E.; Paquet, F.; Blanchardon, E.

    2011-01-01

    Potential internal contamination of workers is monitored by periodic bioassay measurements interpreted in terms of intake and committed effective dose by the use of biokinetic and dosimetric models. After a prospective evaluation of exposure at a workplace, a suitable monitoring programme can be defined by choosing adequate measurement techniques and frequency. In this study, the sensitivity of a programme is evaluated by the minimum intake and dose, which may be detected with a given level of confidence by taking into account uncertainties on exposure conditions and measurements. This is made for programme optimisation, which is performed by comparing the sensitivities of different alternative programmes. These methods were applied at the AREVA NC reprocessing plant and support the current monitoring programme as the best compromise between the cost of the measurements and the sensitivity of the programme. (authors)

  13. An Integrated Approach for Characterization of Uncertainty in Complex Best Estimate Safety Assessment

    International Nuclear Information System (INIS)

    Pourgol-Mohamad, Mohammad; Modarres, Mohammad; Mosleh, Ali

    2013-01-01

    This paper discusses an approach called Integrated Methodology for Thermal-Hydraulics Uncertainty Analysis (IMTHUA) to characterize and integrate a wide range of uncertainties associated with the best estimate models and complex system codes used for nuclear power plant safety analyses. Examples of applications include complex thermal hydraulic and fire analysis codes. In identifying and assessing uncertainties, the proposed methodology treats the complex code as a 'white box', thus explicitly treating internal sub-model uncertainties in addition to the uncertainties related to the inputs to the code. The methodology accounts for uncertainties related to experimental data used to develop such sub-models, and efficiently propagates all uncertainties during best estimate calculations. Uncertainties are formally analyzed and probabilistically treated using a Bayesian inference framework. This comprehensive approach presents the results in a form usable in most other safety analyses such as the probabilistic safety assessment. The code output results are further updated through additional Bayesian inference using any available experimental data, for example from thermal hydraulic integral test facilities. The approach includes provisions to account for uncertainties associated with user-specified options, for example for choices among alternative sub-models, or among several different correlations. Complex time-dependent best-estimate calculations are computationally intense. The paper presents approaches to minimize computational intensity during the uncertainty propagation. Finally, the paper will report effectiveness and practicality of the methodology with two applications to a complex thermal-hydraulics system code as well as a complex fire simulation code. In case of multiple alternative models, several techniques, including dynamic model switching, user-controlled model selection, and model mixing, are discussed. (authors)

  14. Environment and Human Health: The Challenge of Uncertainty in Risk Assessment

    Directory of Open Access Journals (Sweden)

    Alex G. Stewart

    2018-01-01

    Full Text Available High quality and accurate environmental investigations and analysis are essential to any assessment of contamination and to the decision-making process thereafter. Remediation decisions may be focused by health outcomes, whether already present or a predicted risk. The variability inherent in environmental media and analysis can be quantified statistically; uncertainty in models can be reduced by additional research; deep uncertainty exists when environmental or biomedical processes are not understood, or agreed upon, or remain uncharacterized. Deep uncertainty is common where health and environment interact. Determinants of health operate from the individual’s genes to the international level; often several levels act synergistically. We show this in detail for lead (Pb. Pathways, exposure, dose and response also vary, modifying certainty. Multi-disciplinary approaches, built on high-quality environmental investigations, enable the management of complex and uncertain situations. High quality, accurate environmental investigations into pollution issues remain the cornerstone of understanding attributable health outcomes and developing appropriate responses and remediation. However, they are not sufficient on their own, needing careful integration with the wider contexts and stakeholder agendas, without which any response to the environmental assessment may very well founder. Such approaches may benefit more people than any other strategy.

  15. Conditional Density Models Integrating Fuzzy and Probabilistic Representations of Uncertainty

    NARCIS (Netherlands)

    R.J. Almeida e Santos Nogueira (Rui Jorge)

    2014-01-01

    markdownabstract__Abstract__ Conditional density estimation is an important problem in a variety of areas such as system identification, machine learning, artificial intelligence, empirical economics, macroeconomic analysis, quantitative finance and risk management. This work considers the

  16. Uncertainty and sensitivity assessments of GPS and GIS integrated applications for transportation.

    Science.gov (United States)

    Hong, Sungchul; Vonderohe, Alan P

    2014-02-10

    Uncertainty and sensitivity analysis methods are introduced, concerning the quality of spatial data as well as that of output information from Global Positioning System (GPS) and Geographic Information System (GIS) integrated applications for transportation. In the methods, an error model and an error propagation method form a basis for formulating characterization and propagation of uncertainties. They are developed in two distinct approaches: analytical and simulation. Thus, an initial evaluation is performed to compare and examine uncertainty estimations from the analytical and simulation approaches. The evaluation results show that estimated ranges of output information from the analytical and simulation approaches are compatible, but the simulation approach rather than the analytical approach is preferred for uncertainty and sensitivity analyses, due to its flexibility and capability to realize positional errors in both input data. Therefore, in a case study, uncertainty and sensitivity analyses based upon the simulation approach is conducted on a winter maintenance application. The sensitivity analysis is used to determine optimum input data qualities, and the uncertainty analysis is then applied to estimate overall qualities of output information from the application. The analysis results show that output information from the non-distance-based computation model is not sensitive to positional uncertainties in input data. However, for the distance-based computational model, output information has a different magnitude of uncertainties, depending on position uncertainties in input data.

  17. Train integrity detection risk analysis based on PRISM

    Science.gov (United States)

    Wen, Yuan

    2018-04-01

    GNSS based Train Integrity Monitoring System (TIMS) is an effective and low-cost detection scheme for train integrity detection. However, as an external auxiliary system of CTCS, GNSS may be influenced by external environments, such as uncertainty of wireless communication channels, which may lead to the failure of communication and positioning. In order to guarantee the reliability and safety of train operation, a risk analysis method of train integrity detection based on PRISM is proposed in this article. First, we analyze the risk factors (in GNSS communication process and the on-board communication process) and model them. Then, we evaluate the performance of the model in PRISM based on the field data. Finally, we discuss how these risk factors influence the train integrity detection process.

  18. Uncertainty, causality and decision: The case of social risks and nuclear risk in particular

    International Nuclear Information System (INIS)

    Lahidji, R.

    2012-01-01

    Probability and causality are two indispensable tools for addressing situations of social risk. Causal relations are the foundation for building risk assessment models and identifying risk prevention, mitigation and compensation measures. Probability enables us to quantify risk assessments and to calibrate intervention measures. It therefore seems not only natural, but also necessary to make the role of causality and probability explicit in the definition of decision problems in situations of social risk. Such is the aim of this thesis.By reviewing the terminology of risk and the logic of public interventions in various fields of social risk, we gain a better understanding of the notion and of the issues that one faces when trying to model it. We further elaborate our analysis in the case of nuclear safety, examining in detail how methods and policies have been developed in this field and how they have evolved through time. This leads to a number of observations concerning risk and safety assessments.Generalising the concept of intervention in a Bayesian network allows us to develop a variety of causal Bayesian networks adapted to our needs. In this framework, we propose a definition of risk which seems to be relevant for a broad range of issues. We then offer simple applications of our model to specific aspects of the Fukushima accident and other nuclear safety problems. In addition to specific lessons, the analysis leads to the conclusion that a systematic approach for identifying uncertainties is needed in this area. When applied to decision theory, our tool evolves into a dynamic decision model in which acts cause consequences and are causally interconnected. The model provides a causal interpretation of Savage's conceptual framework, solves some of its paradoxes and clarifies certain aspects. It leads us to considering uncertainty with regard to a problem's causal structure as the source of ambiguity in decision-making, an interpretation which corresponds to a

  19. Introduction of risk size in the determination of uncertainty factor UFL in risk assessment

    International Nuclear Information System (INIS)

    Xue Jinling; Lu Yun; Velasquez, Natalia; Hu Hongying; Yu Ruozhen; Liu Zhengtao; Meng Wei

    2012-01-01

    The methodology for using uncertainty factors in health risk assessment has been developed for several decades. A default value is usually applied for the uncertainty factor UF L , which is used to extrapolate from LOAEL (lowest observed adverse effect level) to NAEL (no adverse effect level). Here, we have developed a new method that establishes a linear relationship between UF L and the additional risk level at LOAEL based on the dose–response information, which represents a very important factor that should be carefully considered. This linear formula makes it possible to select UF L properly in the additional risk range from 5.3% to 16.2%. Also the results remind us that the default value 10 may not be conservative enough when the additional risk level at LOAEL exceeds 16.2%. Furthermore, this novel method not only provides a flexible UF L instead of the traditional default value, but also can ensure a conservative estimation of the UF L with fewer errors, and avoid the benchmark response selection involved in the benchmark dose method. These advantages can improve the estimation of the extrapolation starting point in the risk assessment. (letter)

  20. Integrated flexible capacity and inventory management under flexible capacity uncertainty

    OpenAIRE

    Paç, Mehmet Fazıl

    2006-01-01

    Cataloged from PDF version of article. In a manufacturing environment with volatile demand, inventory management can be coupled with dynamic capacity adjustments for handling the fluctuations more effectively. In this study we consider the integrated management of inventory and flexible capacity management under seasonal stochastic demand and uncertain labor supply. The capacity planning problem is investigated from the workforce planning perspective. We consider a manufactu...

  1. Quantification of uncertainty in flood risk assessment for flood protection planning: a Bayesian approach

    Science.gov (United States)

    Dittes, Beatrice; Špačková, Olga; Ebrahimian, Negin; Kaiser, Maria; Rieger, Wolfgang; Disse, Markus; Straub, Daniel

    2017-04-01

    Flood risk estimates are subject to significant uncertainties, e.g. due to limited records of historic flood events, uncertainty in flood modeling, uncertain impact of climate change or uncertainty in the exposure and loss estimates. In traditional design of flood protection systems, these uncertainties are typically just accounted for implicitly, based on engineering judgment. In the AdaptRisk project, we develop a fully quantitative framework for planning of flood protection systems under current and future uncertainties using quantitative pre-posterior Bayesian decision analysis. In this contribution, we focus on the quantification of the uncertainties and study their relative influence on the flood risk estimate and on the planning of flood protection systems. The following uncertainty components are included using a Bayesian approach: 1) inherent and statistical (i.e. limited record length) uncertainty; 2) climate uncertainty that can be learned from an ensemble of GCM-RCM models; 3) estimates of climate uncertainty components not covered in 2), such as bias correction, incomplete ensemble, local specifics not captured by the GCM-RCM models; 4) uncertainty in the inundation modelling; 5) uncertainty in damage estimation. We also investigate how these uncertainties are possibly reduced in the future when new evidence - such as new climate models, observed extreme events, and socio-economic data - becomes available. Finally, we look into how this new evidence influences the risk assessment and effectivity of flood protection systems. We demonstrate our methodology for a pre-alpine catchment in southern Germany: the Mangfall catchment in Bavaria that includes the city of Rosenheim, which suffered significant losses during the 2013 flood event.

  2. Uncertainty Reduction Via Parameter Design of A Fast Digital Integrator for Magnetic Field Measurement

    CERN Document Server

    Arpaia, P; Lucariello, G; Spiezia, G

    2007-01-01

    At European Centre of Nuclear Research (CERN), within the new Large Hadron Collider (LHC) project, measurements of magnetic flux with uncertainty of 10 ppm at a few of decades of Hz for several minutes are required. With this aim, a new Fast Digital Integrator (FDI) has been developed in cooperation with University of Sannio, Italy [1]. This paper deals with the final design tuning for achieving target uncertainty by means of experimental statistical parameter design.

  3. Uncertainty and sensitivity analysis of flood risk management decisions based on stationary and nonstationary model choices

    Directory of Open Access Journals (Sweden)

    Rehan Balqis M.

    2016-01-01

    Full Text Available Current practice in flood frequency analysis assumes that the stochastic properties of extreme floods follow that of stationary conditions. As human intervention and anthropogenic climate change influences in hydrometeorological variables are becoming evident in some places, there have been suggestions that nonstationary statistics would be better to represent the stochastic properties of the extreme floods. The probabilistic estimation of non-stationary models, however, is surrounded with uncertainty related to scarcity of observations and modelling complexities hence the difficulty to project the future condition. In the face of uncertain future and the subjectivity of model choices, this study attempts to demonstrate the practical implications of applying a nonstationary model and compares it with a stationary model in flood risk assessment. A fully integrated framework to simulate decision makers’ behaviour in flood frequency analysis is thereby developed. The framework is applied to hypothetical flood risk management decisions and the outcomes are compared with those of known underlying future conditions. Uncertainty of the economic performance of the risk-based decisions is assessed through Monte Carlo simulations. Sensitivity of the results is also tested by varying the possible magnitude of future changes. The application provides quantitative and qualitative comparative results that satisfy a preliminary analysis of whether the nonstationary model complexity should be applied to improve the economic performance of decisions. Results obtained from the case study shows that the relative differences of competing models for all considered possible future changes are small, suggesting that stationary assumptions are preferred to a shift to nonstationary statistics for practical application of flood risk management. Nevertheless, nonstationary assumption should also be considered during a planning stage in addition to stationary assumption

  4. An optimization methodology for identifying robust process integration investments under uncertainty

    International Nuclear Information System (INIS)

    Svensson, Elin; Berntsson, Thore; Stroemberg, Ann-Brith; Patriksson, Michael

    2009-01-01

    Uncertainties in future energy prices and policies strongly affect decisions on investments in process integration measures in industry. In this paper, we present a five-step methodology for the identification of robust investment alternatives incorporating explicitly such uncertainties in the optimization model. Methods for optimization under uncertainty (or, stochastic programming) are thus combined with a deep understanding of process integration and process technology in order to achieve a framework for decision-making concerning the investment planning of process integration measures under uncertainty. The proposed methodology enables the optimization of investments in energy efficiency with respect to their net present value or an environmental objective. In particular, as a result of the optimization approach, complex investment alternatives, allowing for combinations of energy efficiency measures, can be analyzed. Uncertainties as well as time-dependent parameters, such as energy prices and policies, are modelled using a scenario-based approach, enabling the identification of robust investment solutions. The methodology is primarily an aid for decision-makers in industry, but it will also provide insight for policy-makers into how uncertainties regarding future price levels and policy instruments affect the decisions on investments in energy efficiency measures. (author)

  5. An optimization methodology for identifying robust process integration investments under uncertainty

    Energy Technology Data Exchange (ETDEWEB)

    Svensson, Elin; Berntsson, Thore [Department of Energy and Environment, Division of Heat and Power Technology, Chalmers University of Technology, SE-412 96 Goeteborg (Sweden); Stroemberg, Ann-Brith [Fraunhofer-Chalmers Research Centre for Industrial Mathematics, Chalmers Science Park, SE-412 88 Gothenburg (Sweden); Patriksson, Michael [Department of Mathematical Sciences, Chalmers University of Technology and Department of Mathematical Sciences, University of Gothenburg, SE-412 96 Goeteborg (Sweden)

    2009-02-15

    Uncertainties in future energy prices and policies strongly affect decisions on investments in process integration measures in industry. In this paper, we present a five-step methodology for the identification of robust investment alternatives incorporating explicitly such uncertainties in the optimization model. Methods for optimization under uncertainty (or, stochastic programming) are thus combined with a deep understanding of process integration and process technology in order to achieve a framework for decision-making concerning the investment planning of process integration measures under uncertainty. The proposed methodology enables the optimization of investments in energy efficiency with respect to their net present value or an environmental objective. In particular, as a result of the optimization approach, complex investment alternatives, allowing for combinations of energy efficiency measures, can be analyzed. Uncertainties as well as time-dependent parameters, such as energy prices and policies, are modelled using a scenario-based approach, enabling the identification of robust investment solutions. The methodology is primarily an aid for decision-makers in industry, but it will also provide insight for policy-makers into how uncertainties regarding future price levels and policy instruments affect the decisions on investments in energy efficiency measures. (author)

  6. Uncertainty and Risk Assessment in the Design Process for Wind

    Energy Technology Data Exchange (ETDEWEB)

    Damiani, Rick R. [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2018-02-09

    This report summarizes the concepts and opinions that emerged from an initial study on the subject of uncertainty in wind design that included expert elicitation during a workshop held at the National Wind Technology Center at the National Renewable Energy Laboratory July 12-13, 2016. In this paper, five major categories of uncertainties are identified. The first category is associated with direct impacts on turbine loads, (i.e., the inflow including extreme events, aero-hydro-servo-elastic response, soil-structure inter- action, and load extrapolation). The second category encompasses material behavior and strength. Site suitability and due-diligence aspects pertain to the third category. Calibration of partial safety factors and optimal reliability levels make up the fourth one. And last but not least, is the category associated with uncertainties in computational modeling. The main sections of this paper follow this organization.

  7. Uncertainty in exposure of underground miners to radon daughters and the effect of uncertainty on risk estimates

    International Nuclear Information System (INIS)

    1989-10-01

    Studies of underground miners provide the principal basis for assessing the risk from radon daughter exposure. An important problem in all epidemiological studies of underground miners is the reliability of the estimates of the miners' exposures. This study examines the various sources of uncertainty in exposure estimation for the principal epidemiologic studies reported in the literature including the temporal and spatial variability of radon sources and, with the passage of time, changes to both mining methods and ventilation conditions. Uncertainties about work histories and the role of other hard rock mining experience are also discussed. The report also describes two statistical approaches, both based on Bayesian methods, by which the effects on the estimated risk coefficient of uncertainty in exposure (WLM) can be examined. One approach requires only an estimate of the cumulative WLM exposure of a group of miners, an estimate of the number of (excess) lung cancers potentially attributable to that exposure, and a specification of the uncertainty about the cumulative exposure of the group. The second approach is based on a linear regression model which incorporates errors (uncertainty) in the independent variable (WLM) and allows the dependent variable (cases) to be Poisson distributed. The method permits the calculation of marginal probability distributions for either slope (risk coefficient) or intercept. The regression model approach is applied to several published data sets from epidemiological studies of miners. Specific results are provided for each data set and apparent differences in risk coefficients are discussed. The studies of U.S. uranium miners, Ontario uranium miners and Czechoslovakian uranium miners are argued to provide the best basis for risk estimation at this time. In general terms, none of the analyses performed are inconsistent with a linear exposure-effect relation. Based on analyses of the overall miner groups, the most likely ranges

  8. Application of RELAP/SCDAPSIM with integrated uncertainty options to research reactor systems thermal hydraulic analysis

    International Nuclear Information System (INIS)

    Allison, C.M.; Hohorst, J.K.; Perez, M.; Reventos, F.

    2010-01-01

    The RELAP/SCDAPSIM/MOD4.0 code, designed to predict the behavior of reactor systems during normal and accident conditions, is being developed as part of the international SCDAP Development and Training Program (SDTP). RELAP/SCDAPSIM/MOD4.0, which is the first version of RELAP5 completely rewritten to FORTRAN 90/95/2000 standards, uses publicly available RELAP5 and SCDAP models in combination with advanced programming and numerical techniques and other SDTP-member modeling/user options. One such member developed option is an integrated uncertainty analysis package being developed jointly by the Technical University of Catalonia (UPC) and Innovative Systems Software (ISS). This paper briefly summarizes the features of RELAP/SCDAPSIM/MOD4.0 and the integrated uncertainty analysis package, and then presents an example of how the integrated uncertainty package can be setup and used for a simple pipe flow problem. (author)

  9. Distribution of uncertainties at the municipality level for flood risk modelling along the river Meuse: implications for policy-making

    Science.gov (United States)

    Pirotton, Michel; Stilmant, Frédéric; Erpicum, Sébastien; Dewals, Benjamin; Archambeau, Pierre

    2016-04-01

    Flood risk modelling has been conducted for the whole course of the river Meuse in Belgium. Major cities, such as Liege (200,000 inh.) and Namur (110,000 inh.), are located in the floodplains of river Meuse. Particular attention has been paid to uncertainty analysis and its implications for decision-making. The modelling chain contains flood frequency analysis, detailed 2D hydraulic computations, damage modelling and risk calculation. The relative importance of each source of uncertainty to the overall results uncertainty has been estimated by considering several alternate options for each step of the analysis: different distributions were considered in the flood frequency analysis; the influence of modelling assumptions and boundary conditions (e.g., steady vs. unsteady) were taken into account for the hydraulic computation; two different landuse classifications and two sets of damage functions were used; the number of exceedance probabilities involved in the risk calculation (by integration of the risk-curves) was varied. In addition, the sensitivity of the results with respect to increases in flood discharges was assessed. The considered increases are consistent with a "wet" climate change scenario for the time horizons 2021-2050 and 2071-2100 (Detrembleur et al., 2015). The results of hazard computation differ significantly between the upper and lower parts of the course of river Meuse in Belgium. In the former, inundation extents grow gradually as the considered flood discharge is increased (i.e. the exceedance probability is reduced), while in the downstream part, protection structures (mainly concrete walls) prevent inundation for flood discharges corresponding to exceedance probabilities of 0.01 and above (in the present climate). For higher discharges, large inundation extents are obtained in the floodplains. The highest values of risk (mean annual damage) are obtained in the municipalities which undergo relatively frequent flooding (upper part of the

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

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

    International Nuclear Information System (INIS)

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

    2015-01-01

    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

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

    Energy Technology Data Exchange (ETDEWEB)

    Jacobs, Rianne, E-mail: rianne.jacobs@wur.nl; Voet, Hilko van der; Braak, Cajo J. F. ter [Wageningen University and Research Centre, Biometris (Netherlands)

    2015-06-15

    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.

  14. The MIT Integrated Global System Model: A facility for Assessing and Communicating Climate Change Uncertainty (Invited)

    Science.gov (United States)

    Prinn, R. G.

    2013-12-01

    The world is facing major challenges that create tensions between human development and environmental sustenance. In facing these challenges, computer models are invaluable tools for addressing the need for probabilistic approaches to forecasting. To illustrate this, I use the MIT Integrated Global System Model framework (IGSM; http://globalchange.mit.edu ). The IGSM consists of a set of coupled sub-models of global economic and technological development and resultant emissions, and physical, dynamical and chemical processes in the atmosphere, land, ocean and ecosystems (natural and managed). Some of the sub-models have both complex and simplified versions available, with the choice of which version to use being guided by the questions being addressed. Some sub-models (e.g.urban air pollution) are reduced forms of complex ones created by probabilistic collocation with polynomial chaos bases. Given the significant uncertainties in the model components, it is highly desirable that forecasts be probabilistic. We achieve this by running 400-member ensembles (Latin hypercube sampling) with different choices for key uncertain variables and processes within the human and natural system model components (pdfs of inputs estimated by model-observation comparisons, literature surveys, or expert elicitation). The IGSM has recently been used for probabilistic forecasts of climate, each using 400-member ensembles: one ensemble assumes no explicit climate mitigation policy and others assume increasingly stringent policies involving stabilization of greenhouse gases at various levels. These forecasts indicate clearly that the greatest effect of these policies is to lower the probability of extreme changes. The value of such probability analyses for policy decision-making lies in their ability to compare relative (not just absolute) risks of various policies, which are less affected by the earth system model uncertainties. Given the uncertainties in forecasts, it is also clear that

  15. Integrating uncertainty propagation in GNSS radio occultation retrieval: from excess phase to atmospheric bending angle profiles

    Directory of Open Access Journals (Sweden)

    J. Schwarz

    2018-05-01

    Full Text Available Global Navigation Satellite System (GNSS radio occultation (RO observations are highly accurate, long-term stable data sets and are globally available as a continuous record from 2001. Essential climate variables for the thermodynamic state of the free atmosphere – such as pressure, temperature, and tropospheric water vapor profiles (involving background information – can be derived from these records, which therefore have the potential to serve as climate benchmark data. However, to exploit this potential, atmospheric profile retrievals need to be very accurate and the remaining uncertainties quantified and traced throughout the retrieval chain from raw observations to essential climate variables. The new Reference Occultation Processing System (rOPS at the Wegener Center aims to deliver such an accurate RO retrieval chain with integrated uncertainty propagation. Here we introduce and demonstrate the algorithms implemented in the rOPS for uncertainty propagation from excess phase to atmospheric bending angle profiles, for estimated systematic and random uncertainties, including vertical error correlations and resolution estimates. We estimated systematic uncertainty profiles with the same operators as used for the basic state profiles retrieval. The random uncertainty is traced through covariance propagation and validated using Monte Carlo ensemble methods. The algorithm performance is demonstrated using test day ensembles of simulated data as well as real RO event data from the satellite missions CHAllenging Minisatellite Payload (CHAMP; Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC; and Meteorological Operational Satellite A (MetOp. The results of the Monte Carlo validation show that our covariance propagation delivers correct uncertainty quantification from excess phase to bending angle profiles. The results from the real RO event ensembles demonstrate that the new uncertainty estimation chain performs

  16. Integrating uncertainty propagation in GNSS radio occultation retrieval: from excess phase to atmospheric bending angle profiles

    Science.gov (United States)

    Schwarz, Jakob; Kirchengast, Gottfried; Schwaerz, Marc

    2018-05-01

    Global Navigation Satellite System (GNSS) radio occultation (RO) observations are highly accurate, long-term stable data sets and are globally available as a continuous record from 2001. Essential climate variables for the thermodynamic state of the free atmosphere - such as pressure, temperature, and tropospheric water vapor profiles (involving background information) - can be derived from these records, which therefore have the potential to serve as climate benchmark data. However, to exploit this potential, atmospheric profile retrievals need to be very accurate and the remaining uncertainties quantified and traced throughout the retrieval chain from raw observations to essential climate variables. The new Reference Occultation Processing System (rOPS) at the Wegener Center aims to deliver such an accurate RO retrieval chain with integrated uncertainty propagation. Here we introduce and demonstrate the algorithms implemented in the rOPS for uncertainty propagation from excess phase to atmospheric bending angle profiles, for estimated systematic and random uncertainties, including vertical error correlations and resolution estimates. We estimated systematic uncertainty profiles with the same operators as used for the basic state profiles retrieval. The random uncertainty is traced through covariance propagation and validated using Monte Carlo ensemble methods. The algorithm performance is demonstrated using test day ensembles of simulated data as well as real RO event data from the satellite missions CHAllenging Minisatellite Payload (CHAMP); Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC); and Meteorological Operational Satellite A (MetOp). The results of the Monte Carlo validation show that our covariance propagation delivers correct uncertainty quantification from excess phase to bending angle profiles. The results from the real RO event ensembles demonstrate that the new uncertainty estimation chain performs robustly. Together

  17. Coping with Economic Uncertainty: Focus on Key Risks Essential

    Science.gov (United States)

    Sander, Laura

    2009-01-01

    During this period of continued economic uncertainty, higher-education institutions are facing a variety of challenges that by now are very familiar to governing boards and institutional leaders, including poor investment returns, reduced liquidity, limited choices in how they structure debt issues, and threats to flexibility in tuition pricing.…

  18. Risk analysis: assessing uncertainties beyond expected values and probabilities

    National Research Council Canada - National Science Library

    Aven, T. (Terje)

    2008-01-01

    ... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 How to describe risk quantitatively . . . . . . . . . . . . . . . . . 2.2.1 Description of risk in a financial context . . . . . . . . . 2.2.2 Description...

  19. Can Bayesian Belief Networks help tackling conceptual model uncertainties in contaminated site risk assessment?

    DEFF Research Database (Denmark)

    Troldborg, Mads; Thomsen, Nanna Isbak; McKnight, Ursula S.

    different conceptual models may describe the same contaminated site equally well. In many cases, conceptual model uncertainty has been shown to be one of the dominant sources for uncertainty and is therefore essential to account for when quantifying uncertainties in risk assessments. We present here......A key component in risk assessment of contaminated sites is the formulation of a conceptual site model. The conceptual model is a simplified representation of reality and forms the basis for the mathematical modelling of contaminant fate and transport at the site. A conceptual model should...... a Bayesian Belief Network (BBN) approach for evaluating the uncertainty in risk assessment of groundwater contamination from contaminated sites. The approach accounts for conceptual model uncertainty by considering multiple conceptual models, each of which represents an alternative interpretation of the site...

  20. Integrated uncertainty analysis using RELAP/SCDAPSIM/MOD4.0

    International Nuclear Information System (INIS)

    Perez, M.; Reventos, F.; Wagner, R.; Allison, C.

    2009-01-01

    The RELAP/SCDAPSIM/MOD4.0 code, designed to predict the behavior of reactor systems during normal and accident conditions, is being developed as part of an international nuclear technology Software Development and Training Program (SDTP). RELAP/SCDAPSIM/MOD4.0, which is the first version of RELAP5 completely rewritten to FORTRAN 90/95/2000 standards, uses the publicly available RELAP5 and SCDAP models in combination with (a) advanced programming and numerical techniques, (b) advanced SDTP-member-developed models for LWR, HWR, and research reactor analysis, and (c) a variety of other member-developed computational packages. One such computational package is an integrated uncertainty analysis package being developed jointly by the Technical University of Catalunya (UPC) and Innovative Systems Software (ISS). The integrated uncertainty analysis approach used in the package uses the following steps: 1. Selection of the plant; 2. Selection of the scenario; 3. Selection of the safety criteria; 4. Identification and ranking of the relevant phenomena based on the safety criteria; 5. Selection of the appropriate code parameters to represent those phenomena; 6. Association of uncertainty by means of Probability Distribution Functions (PDFs) for each selected parameter; 7. Random sampling of the selected parameters according to its PDF and performing multiple computer runs to obtain uncertainty bands with a certain percentile and confidence level; 8. Processing the results of the multiple computer runs to estimate the uncertainty bands for the computed quantities associated with the selected safety criteria. The first four steps are performed by the user prior to the RELAP/SCDAPSIM/MOD4.0 analysis. The remaining steps are included with the MOD4.0 integrated uncertainty analysis (IUA) package. This paper briefly describes the integrated uncertainty analysis package including (a) the features of the package, (b) the implementation of the package into RELAP/SCDAPSIM/MOD4.0, and

  1. Real-Time Optimal Flood Control Decision Making and Risk Propagation Under Multiple Uncertainties

    Science.gov (United States)

    Zhu, Feilin; Zhong, Ping-An; Sun, Yimeng; Yeh, William W.-G.

    2017-12-01

    Multiple uncertainties exist in the optimal flood control decision-making process, presenting risks involving flood control decisions. This paper defines the main steps in optimal flood control decision making that constitute the Forecast-Optimization-Decision Making (FODM) chain. We propose a framework for supporting optimal flood control decision making under multiple uncertainties and evaluate risk propagation along the FODM chain from a holistic perspective. To deal with uncertainties, we employ stochastic models at each link of the FODM chain. We generate synthetic ensemble flood forecasts via the martingale model of forecast evolution. We then establish a multiobjective stochastic programming with recourse model for optimal flood control operation. The Pareto front under uncertainty is derived via the constraint method coupled with a two-step process. We propose a novel SMAA-TOPSIS model for stochastic multicriteria decision making. Then we propose the risk assessment model, the risk of decision-making errors and rank uncertainty degree to quantify the risk propagation process along the FODM chain. We conduct numerical experiments to investigate the effects of flood forecast uncertainty on optimal flood control decision making and risk propagation. We apply the proposed methodology to a flood control system in the Daduhe River basin in China. The results indicate that the proposed method can provide valuable risk information in each link of the FODM chain and enable risk-informed decisions with higher reliability.

  2. Health risks of climate change: An assessment of uncertainties and its implications for adaption policies

    NARCIS (Netherlands)

    Wardekker, J.A.; de Jong, A.; van Bree, L.; Turkenburg, W.C.; van der Sluijs, J.P.

    2012-01-01

    Background: Projections of health risks of climate change are surrounded with uncertainties in knowledge. Understanding of these uncertainties will help the selection of appropriate adaptation policies. Methods: We made an inventory of conceivable health impacts of climate change, explored the type

  3. Considerations on Integrating Risk and Quality Management

    Directory of Open Access Journals (Sweden)

    Maria POPESCU

    2011-03-01

    Full Text Available This paper aims to highlight the links between risk management and quality management and to study the possibility of their integrated approach. The study reviews the evolution of risk approach within organizations and stresses the need to increase the effectiveness of this approach by incorporating risk management methodology in the quality management system. Starting from this idea, the authors present the current state of risk approach into quality management, basic rules of integrated quality-risk management and major difficulties which may arise in the implementation of integrated quality–risk systems.

  4. Sensitivity, uncertainty, and importance analysis of a risk assessment

    International Nuclear Information System (INIS)

    Andsten, R.S.; Vaurio, J.K.

    1992-01-01

    In this paper a number of supplementary studies and applications associated with probabilistic safety assessment (PSA) are described, including sensitivity and importance evaluations of failures, errors, systems, and groups of components. The main purpose is to illustrate the usefulness of a PSA for making decisions about safety improvements, training, allowed outage times, and test intervals. A useful measure of uncertainty importance is presented, and it points out areas needing development, such as reactor vessel aging phenomena, for reducing overall uncertainty. A time-dependent core damage frequency is also presented, illustrating the impact of testing scenarios and intervals. Tea methods and applications presented are based on the Level 1 PSA carried out for the internal initiating event of the Loviisa 1 nuclear power station. Steam generator leakages and associated operator actions are major contributors to the current core-damage frequency estimate of 2 x10 -4 /yr. The results are used to improve the plant and procedures and to guide future improvements

  5. Influence of resonance parameters' correlations on the resonance integral uncertainty; 55Mn case

    International Nuclear Information System (INIS)

    Zerovnik, Gasper; Trkov, Andrej; Capote, Roberto; Rochman, Dimitri

    2011-01-01

    For nuclides with a large number of resonances the covariance matrix of resonance parameters can become very large and expensive to process in terms of the computation time. By converting covariance matrix of resonance parameters into covariance matrices of background cross-section in a more or less coarse group structure a considerable amount of computer time and memory can be saved. The question is how important is the information that is discarded in the process. First, the uncertainty of the 55 Mn resonance integral was estimated in narrow resonance approximation for different levels of self-shielding using Bondarenko method by random sampling of resonance parameters according to their covariance matrices from two different 55 Mn evaluations: one from Nuclear Research and Consultancy Group NRG (with large uncertainties but no correlations between resonances), the other from Oak Ridge National Laboratory (with smaller uncertainties but full covariance matrix). We have found out that if all (or at least significant part of the) resonance parameters are correlated, the resonance integral uncertainty greatly depends on the level of self-shielding. Second, it was shown that the commonly used 640-group SAND-II representation cannot describe the increase of the resonance integral uncertainty. A much finer energy mesh for the background covariance matrix would have to be used to take the resonance structure into account explicitly, but then the objective of a more compact data representation is lost.

  6. Risk, probability and uncertainty in the calculations of gas cooled reactor of PBMR type. Part 2

    International Nuclear Information System (INIS)

    Serbanescu, Dan

    2004-01-01

    The paper presents the main conclusions of the insights to a cooled gas reactor from the perspective of the following notions: probability, uncertainty, entropy and risk. Some results of the on-going comparison between the insights obtained from three models and approaches are presented. The approaches consider the Pebble Bed Module Reactor (PBMR) NPP as a thermodynamic installation and as hierarchical system with or without considering the information exchange between its various levels. The existing model was a basis for a PRA going on in phases for PBMR. In the first part of this paper results from phase II of this PRA were presented. Further activities going on in the preparation for phase II PRA and for the development of a specific application of using PRA during the design phases for PBMR are undergoing with some preliminary results and conclusions. However, for the purposes of this paper and the comparative review of various models in the part two one presents the risk model (model B) based on the assumption and ideas laid down at the basis of the future inter-comparison of this model with other plant models. The assumptions concern: the uncertainties for the quantification of frequencies; list of initiated events; interfaces with the deterministic calculation; integrated evaluation of all the plant states; risk of the release of radionuclide; the balance between the number and function of the active systems and the passive systems; systems interdependencies in PBMR PRA; use of PRA for the evaluation of the impact of various design changes on plant risk. The model B allows basically evaluating the level of risk of the plant by calculating it as a result of acceptance challenge to the plant. By using this model the departure from a reference state is given by the variation in the risk metrics adopted for the study. The paper present also the synergetic model (model C). The evaluation of risk in the model C is considering also the information process. The

  7. Uncertainty assessment of integrated distributed hydrological models using GLUE with Markov chain Monte Carlo sampling

    DEFF Research Database (Denmark)

    Blasone, Roberta-Serena; Madsen, Henrik; Rosbjerg, Dan

    2008-01-01

    uncertainty estimation (GLUE) procedure based on Markov chain Monte Carlo sampling is applied in order to improve the performance of the methodology in estimating parameters and posterior output distributions. The description of the spatial variations of the hydrological processes is accounted for by defining......In recent years, there has been an increase in the application of distributed, physically-based and integrated hydrological models. Many questions regarding how to properly calibrate and validate distributed models and assess the uncertainty of the estimated parameters and the spatially......-site validation must complement the usual time validation. In this study, we develop, through an application, a comprehensive framework for multi-criteria calibration and uncertainty assessment of distributed physically-based, integrated hydrological models. A revised version of the generalized likelihood...

  8. An interdisciplinary approach to volcanic risk reduction under conditions of uncertainty: a case study of Tristan da Cunha

    Science.gov (United States)

    Hicks, A.; Barclay, J.; Simmons, P.; Loughlin, S.

    2014-07-01

    The uncertainty brought about by intermittent volcanic activity is fairly common at volcanoes worldwide. While better knowledge of any one volcano's behavioural characteristics has the potential to reduce this uncertainty, the subsequent reduction of risk from volcanic threats is only realised if that knowledge is pertinent to stakeholders and effectively communicated to inform good decision making. Success requires integration of methods, skills and expertise across disciplinary boundaries. This research project develops and trials a novel interdisciplinary approach to volcanic risk reduction on the remote volcanic island of Tristan da Cunha (South Atlantic). For the first time, volcanological techniques, probabilistic decision support and social scientific methods were integrated in a single study. New data were produced that (1) established no spatio-temporal pattern to recent volcanic activity; (2) quantified the high degree of scientific uncertainty around future eruptive scenarios; (3) analysed the physical vulnerability of the community as a consequence of their geographical isolation and exposure to volcanic hazards; (4) evaluated social and cultural influences on vulnerability and resilience; and (5) evaluated the effectiveness of a scenario planning approach, both as a method for integrating the different strands of the research and as a way of enabling on-island decision makers to take ownership of risk identification and management, and capacity building within their community. The paper provides empirical evidence of the value of an innovative interdisciplinary framework for reducing volcanic risk. It also provides evidence for the strength that comes from integrating social and physical sciences with the development of effective, tailored engagement and communication strategies in volcanic risk reduction.

  9. Climate change, uncertainty and investment in flood risk reduction

    NARCIS (Netherlands)

    Pol, van der T.D.

    2015-01-01

    Economic analysis of flood risk management strategies has become more complex due to climate change. This thesis investigates the impact of climate change on investment in flood risk reduction, and applies optimisation methods to support identification of optimal flood risk management strategies.

  10. Everyday Uncertainties: Reframing Perceptions of Risk in Outdoor Free Play

    Science.gov (United States)

    Niehues, Anita Nelson; Bundy, Anita; Broom, Alex; Tranter, Paul; Ragen, Jo; Engelen, Lina

    2013-01-01

    This paper reports the results of risk reframing, an intervention to offer parents and educators a context for building new and complex perceptions of risk in children's outdoor free play. Our objective was to alter these adults' perceptions of risk to increase the sustainability of an innovative child-centred playground intervention. Qualitative…

  11. Interpretations of alternative uncertainty representations in a reliability and risk analysis context

    International Nuclear Information System (INIS)

    Aven, T.

    2011-01-01

    Probability is the predominant tool used to measure uncertainties in reliability and risk analyses. However, other representations also exist, including imprecise (interval) probability, fuzzy probability and representations based on the theories of evidence (belief functions) and possibility. Many researchers in the field are strong proponents of these alternative methods, but some are also sceptical. In this paper, we address one basic requirement set for quantitative measures of uncertainty: the interpretation needed to explain what an uncertainty number expresses. We question to what extent the various measures meet this requirement. Comparisons are made with probabilistic analysis, where uncertainty is represented by subjective probabilities, using either a betting interpretation or a reference to an uncertainty standard interpretation. By distinguishing between chances (expressing variation) and subjective probabilities, new insights are gained into the link between the alternative uncertainty representations and probability.

  12. Consideration of uncertainties in CCDF risk curves in safety oriented decision making processes

    International Nuclear Information System (INIS)

    Stern, E.; Tadmor, J.

    1988-01-01

    In recent years, some of the results of Probabilistic Risk Assessment (i.e. the magnitudes of the various adverse health effects and other effects of potential accidents in nuclear power plants) have usually been presented in Complementary Cumulative Distribution Function curves, widely known as CCDF risk curves. CCDF curves are characteristic of probabilistic accident analyses and consequence calculations, although, in many cases, the codes producing the CCDF curves consist of a mixture of both probabilistic and deterministic calculations. One of the main difficulties in the process of PRA is the problem of uncertainties associated with the risk assessments. The uncertainties, as expressed in CCDF risk curves can be classified into two main categories: (a) uncertainties expressed by the CCDF risk curve itself due to its probabilistic nature and - (b) the uncertainty band of CCDF risk curves. The band consists of a ''family of CCDF curves'' which represents the risks (e.g. early/late fatalities) evaluated at various levels of confidence for a specific Plant-Site Combination (PSC) i.e. a certain nuclear power plant located at a certain site. The reasons why a family of curves rather than a single curve represents the risk of a certain PSC have been discussed. Generally, the uncertainty band of CCDF curves is limited by the 95% (''conservative'') and the 5% curves. In most cases the 50% (median, ''best estimate'') curve is also shown because scientists tend to believe that it represents the ''realistic'' (or real) risk of the plant

  13. Framing risk and uncertainty in social science articles on climate change, 1995–2012

    OpenAIRE

    Shaw, Chris; Hellsten, Iina; Nerlich, Brigitte

    2016-01-01

    The issue of climate change is intimately linked to notions of risk and uncertainty, concepts that pose challenges to climate science, climate change communication, and science-society interactions. While a large majority of climate scientists are increasingly certain about the causes of climate change and the risks posed by its impacts (see IPCC, 2013 and 2014), public perception of climate change is still largely framed by uncertainty, especially regarding impacts (Poortinga et al., 2011). ...

  14. Risk, rationality, and regret: responding to the uncertainty of childhood food anaphylaxis.

    Science.gov (United States)

    Hu, W; Kerridge, I; Kemp, A

    2005-06-01

    Risk and uncertainty are unavoidable in clinical medicine. In the case of childhood food allergy, the dysphoric experience of uncertainty is heightened by the perception of unpredictable danger to young children. Medicine has tended to respond to uncertainty with forms of rational decision making. Rationality cannot, however, resolve uncertainty and provides an insufficient account of risk. This paper compares the medical and parental accounts of two peanut allergic toddlers to highlight the value of emotions in decision making. One emotion in particular, regret, assists in explaining the actions taken to prevent allergic reactions, given the diffuse nature of responsibility for children. In this light, the assumption that doctors make rational judgments while patients have emotion led preferences is a false dichotomy. Reconciling medical and lay accounts requires acknowledgement of the interrelationship between the rational and the emotional, and may lead to more appropriate clinical decision making under conditions of uncertainty.

  15. Epistemic uncertainties and natural hazard risk assessment - Part 1: A review of the issues

    Science.gov (United States)

    Beven, K. J.; Aspinall, W. P.; Bates, P. D.; Borgomeo, E.; Goda, K.; Hall, J. W.; Page, T.; Phillips, J. C.; Rougier, J. T.; Simpson, M.; Stephenson, D. B.; Smith, P. J.; Wagener, T.; Watson, M.

    2015-12-01

    Uncertainties in natural hazard risk assessment are generally dominated by the sources arising from lack of knowledge or understanding of the processes involved. There is a lack of knowledge about frequencies, process representations, parameters, present and future boundary conditions, consequences and impacts, and the meaning of observations in evaluating simulation models. These are the epistemic uncertainties that can be difficult to constrain, especially in terms of event or scenario probabilities, even as elicited probabilities rationalized on the basis of expert judgements. This paper reviews the issues raised by trying to quantify the effects of epistemic uncertainties. Such scientific uncertainties might have significant influence on decisions that are made for risk management, so it is important to communicate the meaning of an uncertainty estimate and to provide an audit trail of the assumptions on which it is based. Some suggestions for good practice in doing so are made.

  16. Brine migration resulting from CO2 injection into saline aquifers – An approach to risk estimation including various levels of uncertainty

    DEFF Research Database (Denmark)

    Walter, Lena; Binning, Philip John; Oladyshkin, Sergey

    2012-01-01

    resulting from displaced brine. Quantifying risk on the basis of numerical simulations requires consideration of different kinds of uncertainties and this study considers both, scenario uncertainty and statistical uncertainty. Addressing scenario uncertainty involves expert opinion on relevant geological......Comprehensive risk assessment is a major task for large-scale projects such as geological storage of CO2. Basic hazards are damage to the integrity of caprocks, leakage of CO2, or reduction of groundwater quality due to intrusion of fluids. This study focuses on salinization of freshwater aquifers...... for large-scale 3D models including complex physics. Therefore, we apply a model reduction based on arbitrary polynomial chaos expansion combined with probabilistic collocation method. It is shown that, dependent on data availability, both types of uncertainty can be equally significant. The presented study...

  17. Risk Assessment and Decision-Making under Uncertainty in Tunnel and Underground Engineering

    Directory of Open Access Journals (Sweden)

    Yuanpu Xia

    2017-10-01

    Full Text Available The impact of uncertainty on risk assessment and decision-making is increasingly being prioritized, especially for large geotechnical projects such as tunnels, where uncertainty is often the main source of risk. Epistemic uncertainty, which can be reduced, is the focus of attention. In this study, the existing entropy-risk decision model is first discussed and analyzed, and its deficiencies are improved upon and overcome. Then, this study addresses the fact that existing studies only consider parameter uncertainty and ignore the influence of the model uncertainty. Here, focus is on the issue of model uncertainty and differences in risk consciousness with different decision-makers. The utility theory is introduced in the model. Finally, a risk decision model is proposed based on the sensitivity analysis and the tolerance cost, which can improve decision-making efficiency. This research can provide guidance or reference for the evaluation and decision-making of complex systems engineering problems, and indicate a direction for further research of risk assessment and decision-making issues.

  18. Some considerations on the treatment of uncertainties in risk assessment for practical decision making

    International Nuclear Information System (INIS)

    Aven, Terje; Zio, Enrico

    2011-01-01

    This paper discusses the challenges involved in the representation and treatment of uncertainties in risk assessment, taking the point of view of its use in support to decision making. Two main issues are addressed: (1) how to faithfully represent and express the knowledge available to best support the decision making and (2) how to best inform the decision maker. A general risk-uncertainty framework is presented which provides definitions and interpretations of the key concepts introduced. The framework covers probability theory as well as alternative representations of uncertainty, including interval probability, possibility and evidence theory.

  19. The role of uncertainty analysis in dose reconstruction and risk assessment

    International Nuclear Information System (INIS)

    Hoffman, F.O.; Simon, S.L.; Thiessen. K.M.

    1996-01-01

    Dose reconstruction and risk assessment rely heavily on the use of mathematical models to extrapolate information beyond the realm of direct observation. Because models are merely approximations of real systems, their predictions are inherently uncertain. As a result, full disclosure of uncertainty in dose and risk estimates is essential to achieve scientific credibility and to build public trust. The need for formal analysis of uncertainty in model predictions was presented during the nineteenth annual meeting of the NCRP. At that time, quantitative uncertainty analysis was considered a relatively new and difficult subject practiced by only a few investigators. Today, uncertainty analysis has become synonymous with the assessment process itself. When an uncertainty analysis is used iteratively within the assessment process, it can guide experimental research to refine dose and risk estimates, deferring potentially high cost or high consequence decisions until uncertainty is either acceptable or irreducible. Uncertainty analysis is now mandated for all ongoing dose reconstruction projects within the United States, a fact that distinguishes dose reconstruction from other types of exposure and risk assessments. 64 refs., 6 figs., 1 tab

  20. An evaluation of the treatment of risk and uncertainties in the IPCC reports on climate change.

    Science.gov (United States)

    Aven, Terje; Renn, Ortwin

    2015-04-01

    Few global threats rival global climate change in scale and potential consequence. The principal international authority assessing climate risk is the Intergovernmental Panel on Climate Change (IPCC). Through repeated assessments the IPCC has devoted considerable effort and interdisciplinary competence to articulating a common characterization of climate risk and uncertainties. We have reviewed the assessment and its foundation for the Fifth Assessment Reports published in 2013 and 2014, in particular the guidance note for lead authors of the fifth IPCC assessment report on consistent treatment of uncertainties. Our analysis shows that the work carried out by the ICPP is short of providing a theoretically and conceptually convincing foundation on the treatment of risk and uncertainties. The main reasons for our assessment are: (i) the concept of risk is given a too narrow definition (a function of consequences and probability/likelihood); and (ii) the reports lack precision in delineating their concepts and methods. The goal of this article is to contribute to improving the handling of uncertainty and risk in future IPCC studies, thereby obtaining a more theoretically substantiated characterization as well as enhanced scientific quality for risk analysis in this area. Several suggestions for how to improve the risk and uncertainty treatment are provided. © 2014 Society for Risk Analysis.

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

    Science.gov (United States)

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

    2015-04-01

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

  2. Improved Genetic Algorithm-Based Unit Commitment Considering Uncertainty Integration Method

    Directory of Open Access Journals (Sweden)

    Kyu-Hyung Jo

    2018-05-01

    Full Text Available In light of the dissemination of renewable energy connected to the power grid, it has become necessary to consider the uncertainty in the generation of renewable energy as a unit commitment (UC problem. A methodology for solving the UC problem is presented by considering various uncertainties, which are assumed to have a normal distribution, by using a Monte Carlo simulation. Based on the constructed scenarios for load, wind, solar, and generator outages, a combination of scenarios is found that meets the reserve requirement to secure the power balance of the power grid. In those scenarios, the uncertainty integration method (UIM identifies the best combination by minimizing the additional reserve requirements caused by the uncertainty of power sources. An integration process for uncertainties is formulated for stochastic unit commitment (SUC problems and optimized by the improved genetic algorithm (IGA. The IGA is composed of five procedures and finds the optimal combination of unit status at the scheduled time, based on the determined source data. According to the number of unit systems, the IGA demonstrates better performance than the other optimization methods by applying reserve repairing and an approximation process. To account for the result of the proposed method, various UC strategies are tested with a modified 24-h UC test system and compared.

  3. The neural substrate and functional integration of uncertainty in decision making: an information theory approach.

    Science.gov (United States)

    Goñi, Joaquín; Aznárez-Sanado, Maite; Arrondo, Gonzalo; Fernández-Seara, María; Loayza, Francis R; Heukamp, Franz H; Pastor, María A

    2011-03-09

    Decision making can be regarded as the outcome of cognitive processes leading to the selection of a course of action among several alternatives. Borrowing a central measurement from information theory, Shannon entropy, we quantified the uncertainties produced by decisions of participants within an economic decision task under different configurations of reward probability and time. These descriptors were used to obtain blood oxygen level-dependent (BOLD) signal correlates of uncertainty and two clusters codifying the Shannon entropy of task configurations were identified: a large cluster including parts of the right middle cingulate cortex (MCC) and left and right pre-supplementary motor areas (pre-SMA) and a small cluster at the left anterior thalamus. Subsequent functional connectivity analyses using the psycho-physiological interactions model identified areas involved in the functional integration of uncertainty. Results indicate that clusters mostly located at frontal and temporal cortices experienced an increased connectivity with the right MCC and left and right pre-SMA as the uncertainty was higher. Furthermore, pre-SMA was also functionally connected to a rich set of areas, most of them associative areas located at occipital and parietal lobes. This study provides a map of the human brain segregation and integration (i.e., neural substrate and functional connectivity respectively) of the uncertainty associated to an economic decision making paradigm.

  4. The neural substrate and functional integration of uncertainty in decision making: an information theory approach.

    Directory of Open Access Journals (Sweden)

    Joaquín Goñi

    Full Text Available Decision making can be regarded as the outcome of cognitive processes leading to the selection of a course of action among several alternatives. Borrowing a central measurement from information theory, Shannon entropy, we quantified the uncertainties produced by decisions of participants within an economic decision task under different configurations of reward probability and time. These descriptors were used to obtain blood oxygen level-dependent (BOLD signal correlates of uncertainty and two clusters codifying the Shannon entropy of task configurations were identified: a large cluster including parts of the right middle cingulate cortex (MCC and left and right pre-supplementary motor areas (pre-SMA and a small cluster at the left anterior thalamus. Subsequent functional connectivity analyses using the psycho-physiological interactions model identified areas involved in the functional integration of uncertainty. Results indicate that clusters mostly located at frontal and temporal cortices experienced an increased connectivity with the right MCC and left and right pre-SMA as the uncertainty was higher. Furthermore, pre-SMA was also functionally connected to a rich set of areas, most of them associative areas located at occipital and parietal lobes. This study provides a map of the human brain segregation and integration (i.e., neural substrate and functional connectivity respectively of the uncertainty associated to an economic decision making paradigm.

  5. Risk, Robustness and Water Resources Planning Under Uncertainty

    Science.gov (United States)

    Borgomeo, Edoardo; Mortazavi-Naeini, Mohammad; Hall, Jim W.; Guillod, Benoit P.

    2018-03-01

    Risk-based water resources planning is based on the premise that water managers should invest up to the point where the marginal benefit of risk reduction equals the marginal cost of achieving that benefit. However, this cost-benefit approach may not guarantee robustness under uncertain future conditions, for instance under climatic changes. In this paper, we expand risk-based decision analysis to explore possible ways of enhancing robustness in engineered water resources systems under different risk attitudes. Risk is measured as the expected annual cost of water use restrictions, while robustness is interpreted in the decision-theoretic sense as the ability of a water resource system to maintain performance—expressed as a tolerable risk of water use restrictions—under a wide range of possible future conditions. Linking risk attitudes with robustness allows stakeholders to explicitly trade-off incremental increases in robustness with investment costs for a given level of risk. We illustrate the framework through a case study of London's water supply system using state-of-the -art regional climate simulations to inform the estimation of risk and robustness.

  6. Methods to Quantify Uncertainty in Human Health Risk Assessment

    National Research Council Canada - National Science Library

    Aurelius, Lea

    1998-01-01

    ...) and other health professionals, such as the Bioenviroumental Engineer, to identify the appropriate use of probabilistic techniques for a site, and the methods by which probabilistic risk assessment...

  7. Propagation of uncertainty and sensitivity analysis in an integral oil-gas plume model

    KAUST Repository

    Wang, Shitao

    2016-05-27

    Polynomial Chaos expansions are used to analyze uncertainties in an integral oil-gas plume model simulating the Deepwater Horizon oil spill. The study focuses on six uncertain input parameters—two entrainment parameters, the gas to oil ratio, two parameters associated with the droplet-size distribution, and the flow rate—that impact the model\\'s estimates of the plume\\'s trap and peel heights, and of its various gas fluxes. The ranges of the uncertain inputs were determined by experimental data. Ensemble calculations were performed to construct polynomial chaos-based surrogates that describe the variations in the outputs due to variations in the uncertain inputs. The surrogates were then used to estimate reliably the statistics of the model outputs, and to perform an analysis of variance. Two experiments were performed to study the impacts of high and low flow rate uncertainties. The analysis shows that in the former case the flow rate is the largest contributor to output uncertainties, whereas in the latter case, with the uncertainty range constrained by aposteriori analyses, the flow rate\\'s contribution becomes negligible. The trap and peel heights uncertainties are then mainly due to uncertainties in the 95% percentile of the droplet size and in the entrainment parameters.

  8. Propagation of uncertainty and sensitivity analysis in an integral oil-gas plume model

    KAUST Repository

    Wang, Shitao; Iskandarani, Mohamed; Srinivasan, Ashwanth; Thacker, W. Carlisle; Winokur, Justin; Knio, Omar

    2016-01-01

    Polynomial Chaos expansions are used to analyze uncertainties in an integral oil-gas plume model simulating the Deepwater Horizon oil spill. The study focuses on six uncertain input parameters—two entrainment parameters, the gas to oil ratio, two parameters associated with the droplet-size distribution, and the flow rate—that impact the model's estimates of the plume's trap and peel heights, and of its various gas fluxes. The ranges of the uncertain inputs were determined by experimental data. Ensemble calculations were performed to construct polynomial chaos-based surrogates that describe the variations in the outputs due to variations in the uncertain inputs. The surrogates were then used to estimate reliably the statistics of the model outputs, and to perform an analysis of variance. Two experiments were performed to study the impacts of high and low flow rate uncertainties. The analysis shows that in the former case the flow rate is the largest contributor to output uncertainties, whereas in the latter case, with the uncertainty range constrained by aposteriori analyses, the flow rate's contribution becomes negligible. The trap and peel heights uncertainties are then mainly due to uncertainties in the 95% percentile of the droplet size and in the entrainment parameters.

  9. Analysis of parameter uncertainties in the assessment of seismic risk for nuclear power plants

    International Nuclear Information System (INIS)

    Yucemen, S.M.

    1981-04-01

    Probabilistic and statistical methods are used to develop a procedure by which the seismic risk at a specific site can be systematically analyzed. The proposed probabilistic procedure provides a consisted method for the modelling, analysis and updating of uncertainties that are involved in the seismic risk analysis for nuclear power plants. Methods are proposed for including these uncertainties in the final value of calculated risks. Two specific case studies are presented in detail to illustrate the application of the probabilistic method of seismic risk evaluation and to investigate the sensitivity of results to different assumptions

  10. Planning uncertainties, market risks and new environmental choices: Winning least cost planning combinations

    International Nuclear Information System (INIS)

    Violette, D.; Lang, C.

    1990-01-01

    Utility demand and supply-side planners will face new challenges from environmental regulations. Under current proposals, every ton of pollutant will have a cost to utilities, not just the tons that put them over the allowable limit. Planners will have to account for these new costs. To do this, planners need to start tracking emissions implementation actions today, and begin strategies for future regulatory changes. Current legislative proposals include a tax on the carbon content of fuels to curb emissions of greenhouse gases and substantial reductions in sulfur dioxide and nitrogen oxide emissions. The important issue for planners is the flexible compliance requirements within these regulatory changes. The acid rain proposals, for example, include a market-based emissions trading system for emissions allowances. Whenever there is a competitive market, there are market risks, and potential winners and losers. Utilities need to be prepared to analyze and mitigate these risks. Integrated least cost planing is one way a utility will have to meet this challenge. Planning involves uncertainty and risk. The wide array of compliance choices create countless combinations of strategies for utilities to comply with the new emissions regulations. This paper discusses new compliance strategies, demand-side management (DSM) as a compliance strategy, solutions to DSM traps, and the compliance strategy game

  11. Uncertainty, supply risk management and their impact on performance

    NARCIS (Netherlands)

    Hoffmann, Petra; Schiele, Holger; Krabbendam, Johannes Jacobus

    2013-01-01

    The purpose of this research is to identify the antecedents of supply risk management performance. Speed consortium benchmarking is used to explore the concepts of supply risk monitoring and mitigation. In addition, a survey yielding 207 responses is used to test our hypothesized antecedents of

  12. Software Uncertainty in Integrated Environmental Modelling: the role of Semantics and Open Science

    Science.gov (United States)

    de Rigo, Daniele

    2013-04-01

    Computational aspects increasingly shape environmental sciences [1]. Actually, transdisciplinary modelling of complex and uncertain environmental systems is challenging computational science (CS) and also the science-policy interface [2-7]. Large spatial-scale problems falling within this category - i.e. wide-scale transdisciplinary modelling for environment (WSTMe) [8-10] - often deal with factors (a) for which deep-uncertainty [2,11-13] may prevent usual statistical analysis of modelled quantities and need different ways for providing policy-making with science-based support. Here, practical recommendations are proposed for tempering a peculiar - not infrequently underestimated - source of uncertainty. Software errors in complex WSTMe may subtly affect the outcomes with possible consequences even on collective environmental decision-making. Semantic transparency in CS [2,8,10,14,15] and free software [16,17] are discussed as possible mitigations (b) . Software uncertainty, black-boxes and free software. Integrated natural resources modelling and management (INRMM) [29] frequently exploits chains of nontrivial data-transformation models (D- TM), each of them affected by uncertainties and errors. Those D-TM chains may be packaged as monolithic specialized models, maybe only accessible as black-box executables (if accessible at all) [50]. For end-users, black-boxes merely transform inputs in the final outputs, relying on classical peer-reviewed publications for describing the internal mechanism. While software tautologically plays a vital role in CS, it is often neglected in favour of more theoretical aspects. This paradox has been provocatively described as "the invisibility of software in published science. Almost all published papers required some coding, but almost none mention software, let alone include or link to source code" [51]. Recently, this primacy of theory over reality [52-54] has been challenged by new emerging hybrid approaches [55] and by the

  13. Propagation of Nuclear Data Uncertainties in Integral Measurements by Monte-Carlo Calculations

    Energy Technology Data Exchange (ETDEWEB)

    Noguere, G.; Bernard, D.; De Saint-Jean, C. [CEA Cadarache, 13 - Saint Paul lez Durance (France)

    2006-07-01

    Full text of the publication follows: The generation of Multi-group cross sections together with relevant uncertainties is fundamental to assess the quality of integral data. The key information that are needed to propagate the microscopic experimental uncertainties to macroscopic reactor calculations are (1) the experimental covariance matrices, (2) the correlations between the parameters of the model and (3) the covariance matrices for the multi-group cross sections. The propagation of microscopic errors by Monte-Carlo technique was applied to determine the accuracy of the integral trends provided by the OSMOSE experiment carried out in the MINERVE reactor of the CEA Cadarache. The technique consists in coupling resonance shape analysis and deterministic codes. The integral trend and its accuracy obtained on the {sup 237}Np(n,{gamma}) reaction will be presented. (author)

  14. Geostatistical integration and uncertainty in pollutant concentration surface under preferential sampling

    Directory of Open Access Journals (Sweden)

    Laura Grisotto

    2016-04-01

    Full Text Available In this paper the focus is on environmental statistics, with the aim of estimating the concentration surface and related uncertainty of an air pollutant. We used air quality data recorded by a network of monitoring stations within a Bayesian framework to overcome difficulties in accounting for prediction uncertainty and to integrate information provided by deterministic models based on emissions meteorology and chemico-physical characteristics of the atmosphere. Several authors have proposed such integration, but all the proposed approaches rely on representativeness and completeness of existing air pollution monitoring networks. We considered the situation in which the spatial process of interest and the sampling locations are not independent. This is known in the literature as the preferential sampling problem, which if ignored in the analysis, can bias geostatistical inferences. We developed a Bayesian geostatistical model to account for preferential sampling with the main interest in statistical integration and uncertainty. We used PM10 data arising from the air quality network of the Environmental Protection Agency of Lombardy Region (Italy and numerical outputs from the deterministic model. We specified an inhomogeneous Poisson process for the sampling locations intensities and a shared spatial random component model for the dependence between the spatial location of monitors and the pollution surface. We found greater predicted standard deviation differences in areas not properly covered by the air quality network. In conclusion, in this context inferences on prediction uncertainty may be misleading when geostatistical modelling does not take into account preferential sampling.

  15. Risk management: integration of social and technical risk variables into safety assessments of LWR'S

    International Nuclear Information System (INIS)

    Turnage, J.J.; Husseiny, A.A.

    1980-01-01

    A risk management methodology is developed here to formalize the acceptability levels of commercial LWR power plants via the estimation of risk levels acceptable to the public and the integration of such estimates into risk-benefit analysis. Utility theory is used for developing preference models based on value trade-offs among multiple objectives and uncertainties about the impact of alternatives. The method involves reducing the various variables affecting safety acceptability decisions to a single function that provides a metric for acceptability levels. The function accomondates for technical criteria related to design and licensing decisions, as well as public reactions to certain choices

  16. Review of Polynomial Chaos-Based Methods for Uncertainty Quantification in Modern Integrated Circuits

    Directory of Open Access Journals (Sweden)

    Arun Kaintura

    2018-02-01

    Full Text Available Advances in manufacturing process technology are key ensembles for the production of integrated circuits in the sub-micrometer region. It is of paramount importance to assess the effects of tolerances in the manufacturing process on the performance of modern integrated circuits. The polynomial chaos expansion has emerged as a suitable alternative to standard Monte Carlo-based methods that are accurate, but computationally cumbersome. This paper provides an overview of the most recent developments and challenges in the application of polynomial chaos-based techniques for uncertainty quantification in integrated circuits, with particular focus on high-dimensional problems.

  17. Advanced uncertainty modelling for container port risk analysis.

    Science.gov (United States)

    Alyami, Hani; Yang, Zaili; Riahi, Ramin; Bonsall, Stephen; Wang, Jin

    2016-08-13

    Globalization has led to a rapid increase of container movements in seaports. Risks in seaports need to be appropriately addressed to ensure economic wealth, operational efficiency, and personnel safety. As a result, the safety performance of a Container Terminal Operational System (CTOS) plays a growing role in improving the efficiency of international trade. This paper proposes a novel method to facilitate the application of Failure Mode and Effects Analysis (FMEA) in assessing the safety performance of CTOS. The new approach is developed through incorporating a Fuzzy Rule-Based Bayesian Network (FRBN) with Evidential Reasoning (ER) in a complementary manner. The former provides a realistic and flexible method to describe input failure information for risk estimates of individual hazardous events (HEs) at the bottom level of a risk analysis hierarchy. The latter is used to aggregate HEs safety estimates collectively, allowing dynamic risk-based decision support in CTOS from a systematic perspective. The novel feature of the proposed method, compared to those in traditional port risk analysis lies in a dynamic model capable of dealing with continually changing operational conditions in ports. More importantly, a new sensitivity analysis method is developed and carried out to rank the HEs by taking into account their specific risk estimations (locally) and their Risk Influence (RI) to a port's safety system (globally). Due to its generality, the new approach can be tailored for a wide range of applications in different safety and reliability engineering and management systems, particularly when real time risk ranking is required to measure, predict, and improve the associated system safety performance. Copyright © 2016 Elsevier Ltd. All rights reserved.

  18. Social and Environmental Determinants of Risk and Uncertainties Reporting

    OpenAIRE

    Camelia Iuliana LUNGU; Chiraţa CARAIANI; Cornelia DASCĂLU; Gina Raluca GUŞE

    2009-01-01

    Recently, risk reporting has gained interest in financial reporting practice, regulation, and international research. Social and environmental reporting is seen to benefit shareholders more by reducing risk than by increasing return. The researchers showed that the annual report is the most favoured channel of disclosure, along with presentation to investors. The general message is that, as far as annual reports go, quantified, verifiable disclosures have the most credibility and relevance. O...

  19. Risk management for sulfur dioxide abatement under multiple uncertainties

    Science.gov (United States)

    Dai, C.; Sun, W.; Tan, Q.; Liu, Y.; Lu, W. T.; Guo, H. C.

    2016-03-01

    In this study, interval-parameter programming, two-stage stochastic programming (TSP), and conditional value-at-risk (CVaR) were incorporated into a general optimization framework, leading to an interval-parameter CVaR-based two-stage programming (ICTP) method. The ICTP method had several advantages: (i) its objective function simultaneously took expected cost and risk cost into consideration, and also used discrete random variables and discrete intervals to reflect uncertain properties; (ii) it quantitatively evaluated the right tail of distributions of random variables which could better calculate the risk of violated environmental standards; (iii) it was useful for helping decision makers to analyze the trade-offs between cost and risk; and (iv) it was effective to penalize the second-stage costs, as well as to capture the notion of risk in stochastic programming. The developed model was applied to sulfur dioxide abatement in an air quality management system. The results indicated that the ICTP method could be used for generating a series of air quality management schemes under different risk-aversion levels, for identifying desired air quality management strategies for decision makers, and for considering a proper balance between system economy and environmental quality.

  20. Risk-informed regulation: handling uncertainty for a rational management of safety

    International Nuclear Information System (INIS)

    Zio, Enrico

    2008-01-01

    A risk-informed regulatory approach implies that risk insights be used as supplement of deterministic information for safety decision-making purposes. In this view, the use of risk assessment techniques is expected to lead to improved safety and a more rational allocation of the limited resources available. On the other hand, it is recognized that uncertainties affect both the deterministic safety analyses and the risk assessments. In order for the risk-informed decision making process to be effective, the adequate representation and treatment of such uncertainties is mandatory. In this paper, the risk-informed regulatory framework is considered under the focus of the uncertainty issue. Traditionally, probability theory has provided the language and mathematics for the representation and treatment of uncertainty. More recently, other mathematical structures have been introduced. In particular, the Dempster-Shafer theory of evidence is here illustrated as a generalized framework encompassing probability theory and possibility theory. The special case of probability theory is only addressed as term of comparison, given that it is a well known subject. On the other hand, the special case of possibility theory is amply illustrated. An example of the combination of probability and possibility for treating the uncertainty in the parameters of an event tree is illustrated

  1. Uncertainty Quantification Reveals the Importance of Data Variability and Experimental Design Considerations for in Silico Proarrhythmia Risk Assessment

    Directory of Open Access Journals (Sweden)

    Kelly C. Chang

    2017-11-01

    Full Text Available The Comprehensive in vitro Proarrhythmia Assay (CiPA is a global initiative intended to improve drug proarrhythmia risk assessment using a new paradigm of mechanistic assays. Under the CiPA paradigm, the relative risk of drug-induced Torsade de Pointes (TdP is assessed using an in silico model of the human ventricular action potential (AP that integrates in vitro pharmacology data from multiple ion channels. Thus, modeling predictions of cardiac risk liability will depend critically on the variability in pharmacology data, and uncertainty quantification (UQ must comprise an essential component of the in silico assay. This study explores UQ methods that may be incorporated into the CiPA framework. Recently, we proposed a promising in silico TdP risk metric (qNet, which is derived from AP simulations and allows separation of a set of CiPA training compounds into Low, Intermediate, and High TdP risk categories. The purpose of this study was to use UQ to evaluate the robustness of TdP risk separation by qNet. Uncertainty in the model parameters used to describe drug binding and ionic current block was estimated using the non-parametric bootstrap method and a Bayesian inference approach. Uncertainty was then propagated through AP simulations to quantify uncertainty in qNet for each drug. UQ revealed lower uncertainty and more accurate TdP risk stratification by qNet when simulations were run at concentrations below 5× the maximum therapeutic exposure (Cmax. However, when drug effects were extrapolated above 10× Cmax, UQ showed that qNet could no longer clearly separate drugs by TdP risk. This was because for most of the pharmacology data, the amount of current block measured was <60%, preventing reliable estimation of IC50-values. The results of this study demonstrate that the accuracy of TdP risk prediction depends both on the intrinsic variability in ion channel pharmacology data as well as on experimental design considerations that preclude an

  2. Uncertainty and sensitivity analyses for age-dependent unavailability model integrating test and maintenance

    International Nuclear Information System (INIS)

    Kančev, Duško; Čepin, Marko

    2012-01-01

    Highlights: ► Application of analytical unavailability model integrating T and M, ageing, and test strategy. ► Ageing data uncertainty propagation on system level assessed via Monte Carlo simulation. ► Uncertainty impact is growing with the extension of the surveillance test interval. ► Calculated system unavailability dependence on two different sensitivity study ageing databases. ► System unavailability sensitivity insights regarding specific groups of BEs as test intervals extend. - Abstract: The interest in operational lifetime extension of the existing nuclear power plants is growing. Consequently, plants life management programs, considering safety components ageing, are being developed and employed. Ageing represents a gradual degradation of the physical properties and functional performance of different components consequently implying their reduced availability. Analyses, which are being made in the direction of nuclear power plants lifetime extension are based upon components ageing management programs. On the other side, the large uncertainties of the ageing parameters as well as the uncertainties associated with most of the reliability data collections are widely acknowledged. This paper addresses the uncertainty and sensitivity analyses conducted utilizing a previously developed age-dependent unavailability model, integrating effects of test and maintenance activities, for a selected stand-by safety system in a nuclear power plant. The most important problem is the lack of data concerning the effects of ageing as well as the relatively high uncertainty associated to these data, which would correspond to more detailed modelling of ageing. A standard Monte Carlo simulation was coded for the purpose of this paper and utilized in the process of assessment of the component ageing parameters uncertainty propagation on system level. The obtained results from the uncertainty analysis indicate the extent to which the uncertainty of the selected

  3. Modeling risk and uncertainty in designing reverse logistics problem

    Directory of Open Access Journals (Sweden)

    Aida Nazari Gooran

    2018-01-01

    Full Text Available Increasing attention to environmental problems and social responsibility lead to appear reverse logistic (RL issues in designing supply chain which, in most recently, has received considerable attention from both academicians and practitioners. In this paper, a multi-product reverse logistic network design model is developed; then a hybrid method including Chance-constrained programming, Genetic algorithm and Monte Carlo simulation, are proposed to solve the developed model. The proposed model is solved for risk-averse and risk-seeking decision makers by conditional value at risk, sum of the excepted value and standard deviation, respectively. Comparisons of the results show that minimizing the costs had no direct relation with the kind of decision makers; however, in the most cases, risk-seeking decision maker gained more return products than risk-averse ones. It is clear that by increasing returned products to the chain, production costs of new products and material will be reduced and also by this act, environmental benefits will be created.

  4. The effect of integrated reporting on integrated thinking between risk ...

    African Journals Online (AJOL)

    IIRC (2013b: 3), integrated thinking takes into account the connectivity and ... historical information and provides investors and other stakeholders with .... in the disclosure of risks and opportunities by using a sample of the top 100 JSE-.

  5. The uncertainty cascade in flood risk assessment under changing climatic conditions - the Biala Tarnowska case study

    Science.gov (United States)

    Doroszkiewicz, Joanna; Romanowicz, Renata

    2016-04-01

    Uncertainty in the results of the hydraulic model is not only associated with the limitations of that model and the shortcomings of data. An important factor that has a major impact on the uncertainty of the flood risk assessment in a changing climate conditions is associated with the uncertainty of future climate scenarios (IPCC WG I, 2013). Future climate projections provided by global climate models are used to generate future runoff required as an input to hydraulic models applied in the derivation of flood risk maps. Biala Tarnowska catchment, situated in southern Poland is used as a case study. Future discharges at the input to a hydraulic model are obtained using the HBV model and climate projections obtained from the EUROCORDEX project. The study describes a cascade of uncertainty related to different stages of the process of derivation of flood risk maps under changing climate conditions. In this context it takes into account the uncertainty of future climate projections, an uncertainty of flow routing model, the propagation of that uncertainty through the hydraulic model, and finally, the uncertainty related to the derivation of flood risk maps. One of the aims of this study is an assessment of a relative impact of different sources of uncertainty on the uncertainty of flood risk maps. Due to the complexity of the process, an assessment of total uncertainty of maps of inundation probability might be very computer time consuming. As a way forward we present an application of a hydraulic model simulator based on a nonlinear transfer function model for the chosen locations along the river reach. The transfer function model parameters are estimated based on the simulations of the hydraulic model at each of the model cross-section. The study shows that the application of the simulator substantially reduces the computer requirements related to the derivation of flood risk maps under future climatic conditions. Acknowledgements: This work was supported by the

  6. An overview of the risk uncertainty assessment process for the Cassini space mission

    International Nuclear Information System (INIS)

    Wyss, G.D.

    1996-01-01

    The Cassini spacecraft is a deep space probe whose mission is to explore the planet Saturn and its moons. Since the spacecraft's electrical requirements will be supplied by radioisotope thermoelectric generators (RTGs), the spacecraft designers and mission planners must assure that potential accidents involving the spacecraft do not pose significant human risk. The Cassini risk analysis team is seeking to perform a quantitative uncertainty analysis as a part of the overall mission risk assessment program. This paper describes the uncertainty analysis methodology to be used for the Cassini mission and compares it to the methods that were originally developed for evaluation of commercial nuclear power reactors

  7. Job Exposure Matrix for Electric Shock Risks with Their Uncertainties

    Science.gov (United States)

    Vergara, Ximena P.; Fischer, Heidi J.; Yost, Michael; Silva, Michael; Lombardi, David A.; Kheifets, Leeka

    2015-01-01

    We present an update to an electric shock job exposure matrix (JEM) that assigned ordinal electric shocks exposure for 501 occupational titles based on electric shocks and electrocutions from two available data sources and expert judgment. Using formal expert elicitation and starting with data on electric injury, we arrive at a consensus-based JEM. In our new JEM, we quantify exposures by adding three new dimensions: (1) the elicited median proportion; (2) the elicited 25th percentile; and (3) and the elicited 75th percentile of those experiencing occupational electric shocks in a working lifetime. We construct the relative interquartile range (rIQR) based on uncertainty interval and the median. Finally, we describe overall results, highlight examples demonstrating the impact of cut point selection on exposure assignment, and evaluate potential impacts of such selection on epidemiologic studies of the electric work environment. In conclusion, novel methods allowed for consistent exposure estimates that move from qualitative to quantitative measures in this population-based JEM. Overlapping ranges of median exposure in various categories reflect our limited knowledge about this exposure. PMID:25856552

  8. Job Exposure Matrix for Electric Shock Risks with Their Uncertainties

    Directory of Open Access Journals (Sweden)

    Ximena P. Vergara

    2015-04-01

    Full Text Available We present an update to an electric shock job exposure matrix (JEM that assigned ordinal electric shocks exposure for 501 occupational titles based on electric shocks and electrocutions from two available data sources and expert judgment. Using formal expert elicitation and starting with data on electric injury, we arrive at a consensus-based JEM. In our new JEM, we quantify exposures by adding three new dimensions: (1 the elicited median proportion; (2 the elicited 25th percentile; and (3 and the elicited 75th percentile of those experiencing occupational electric shocks in a working lifetime. We construct the relative interquartile range (rIQR based on uncertainty interval and the median. Finally, we describe overall results, highlight examples demonstrating the impact of cut point selection on exposure assignment, and evaluate potential impacts of such selection on epidemiologic studies of the electric work environment. In conclusion, novel methods allowed for consistent exposure estimates that move from qualitative to quantitative measures in this population-based JEM. Overlapping ranges of median exposure in various categories reflect our limited knowledge about this exposure.

  9. Advances in Financial Risk Management and Economic Policy Uncertainty: An Overview

    NARCIS (Netherlands)

    S.M. Hammoudeh (Shawkat); M.J. McAleer (Michael)

    2014-01-01

    markdownabstract__Abstract__ Financial risk management is difficult at the best of times, but especially so in the presence of economic uncertainty and financial crises. The purpose of this special issue on “Advances in Financial Risk Management and Economic Policy Uncertainty” is to highlight

  10. Tolerance of uncertainty: Conceptual analysis, integrative model, and implications for healthcare.

    Science.gov (United States)

    Hillen, Marij A; Gutheil, Caitlin M; Strout, Tania D; Smets, Ellen M A; Han, Paul K J

    2017-05-01

    Uncertainty tolerance (UT) is an important, well-studied phenomenon in health care and many other important domains of life, yet its conceptualization and measurement by researchers in various disciplines have varied substantially and its essential nature remains unclear. The objectives of this study were to: 1) analyze the meaning and logical coherence of UT as conceptualized by developers of UT measures, and 2) develop an integrative conceptual model to guide future empirical research regarding the nature, causes, and effects of UT. A narrative review and conceptual analysis of 18 existing measures of Uncertainty and Ambiguity Tolerance was conducted, focusing on how measure developers in various fields have defined both the "uncertainty" and "tolerance" components of UT-both explicitly through their writings and implicitly through the items constituting their measures. Both explicit and implicit conceptual definitions of uncertainty and tolerance vary substantially and are often poorly and inconsistently specified. A logically coherent, unified understanding or theoretical model of UT is lacking. To address these gaps, we propose a new integrative definition and multidimensional conceptual model that construes UT as the set of negative and positive psychological responses-cognitive, emotional, and behavioral-provoked by the conscious awareness of ignorance about particular aspects of the world. This model synthesizes insights from various disciplines and provides an organizing framework for future research. We discuss how this model can facilitate further empirical and theoretical research to better measure and understand the nature, determinants, and outcomes of UT in health care and other domains of life. Uncertainty tolerance is an important and complex phenomenon requiring more precise and consistent definition. An integrative definition and conceptual model, intended as a tentative and flexible point of departure for future research, adds needed breadth

  11. Overview of methods for uncertainty analysis and sensitivity analysis in probabilistic risk assessment

    International Nuclear Information System (INIS)

    Iman, R.L.; Helton, J.C.

    1985-01-01

    Probabilistic Risk Assessment (PRA) is playing an increasingly important role in the nuclear reactor regulatory process. The assessment of uncertainties associated with PRA results is widely recognized as an important part of the analysis process. One of the major criticisms of the Reactor Safety Study was that its representation of uncertainty was inadequate. The desire for the capability to treat uncertainties with the MELCOR risk code being developed at Sandia National Laboratories is indicative of the current interest in this topic. However, as yet, uncertainty analysis and sensitivity analysis in the context of PRA is a relatively immature field. In this paper, available methods for uncertainty analysis and sensitivity analysis in a PRA are reviewed. This review first treats methods for use with individual components of a PRA and then considers how these methods could be combined in the performance of a complete PRA. In the context of this paper, the goal of uncertainty analysis is to measure the imprecision in PRA outcomes of interest, and the goal of sensitivity analysis is to identify the major contributors to this imprecision. There are a number of areas that must be considered in uncertainty analysis and sensitivity analysis for a PRA: (1) information, (2) systems analysis, (3) thermal-hydraulic phenomena/fission product behavior, (4) health and economic consequences, and (5) display of results. Each of these areas and the synthesis of them into a complete PRA are discussed

  12. Research approaches to address uncertainties in the risk assessment of arsenic in drinking water

    International Nuclear Information System (INIS)

    Hughes, Michael F.; Kenyon, Elaina M.; Kitchin, Kirk T.

    2007-01-01

    Inorganic arsenic (iAs), an environmental drinking water contaminant, is a human toxicant and carcinogen. The public health community has developed recommendations and regulations that limit human exposure to iAs in drinking water. Although there is a vast amount of information available to regulators on the exposure, disposition and the health-related effects of iAs, there is still critical information about the toxicology of this metalloid that is needed. This necessary information includes identification of the chemical species of arsenic that is (are) the active toxicant(s), the mode(s) of action for its various toxicities and information on potentially susceptible populations. Because of these unknown factors, the risk assessment of iAs still incorporates default assumptions, leading to uncertainties in the overall assessment. The characteristics of a scientifically defensible risk assessment for iAs are that it must: (1) quantitatively link exposure and target tissue dose of active metabolites to key events in the mode of action for major health effects and (2) identify sources of variation in susceptibility to arsenic-induced health effects and quantitatively evaluate their impact wherever possible. Integration of research to address these goals will better protect the health of iAs-exposed populations

  13. Emotion regulation and decision making under risk and uncertainty.

    Science.gov (United States)

    Heilman, Renata M; Crişan, Liviu G; Houser, Daniel; Miclea, Mircea; Miu, Andrei C

    2010-04-01

    It is well established that emotion plays a key role in human social and economic decision making. The recent literature on emotion regulation (ER), however, highlights that humans typically make efforts to control emotion experiences. This leaves open the possibility that decision effects previously attributed to acute emotion may be a consequence of acute ER strategies such as cognitive reappraisal and expressive suppression. In Study 1, we manipulated ER of laboratory-induced fear and disgust, and found that the cognitive reappraisal of these negative emotions promotes risky decisions (reduces risk aversion) in the Balloon Analogue Risk Task and is associated with increased performance in the prehunch/hunch period of the Iowa Gambling Task. In Study 2, we found that naturally occurring negative emotions also increase risk aversion in Balloon Analogue Risk Task, but the incidental use of cognitive reappraisal of emotions impedes this effect. We offer evidence that the increased effectiveness of cognitive reappraisal in reducing the experience of emotions underlies its beneficial effects on decision making. Copyright 2010 APA, all rights reserved.

  14. The effect of integrated reporting on integrated thinking between risk ...

    African Journals Online (AJOL)

    ... between strategy and the risks and opportunities faced by the organisation. For this purpose, a web-based research questionnaire was sent to high-level implementers of integrated reporting at companies listed on the Johannesburg Stock Exchange (JSE) in South Africa, where integrated reporting is a listing requirement.

  15. RISK MANAGEMENT: AN INTEGRATED APPROACH TO RISK MANAGEMENT AND ASSESSMENT

    Directory of Open Access Journals (Sweden)

    Szabo Alina

    2012-12-01

    Full Text Available Purpose: The objective of this paper is to offer an overview over risk management cycle by focusing on prioritization and treatment, in order to ensure an integrated approach to risk management and assessment, and establish the ‘top 8-12’ risks report within the organization. The interface with Internal Audit is ensured by the implementation of the scoring method to prioritize risks collected from previous generated risk report. Methodology/approach: Using evidence from other research in the area and the professional expertise, this article outlines an integrated approach to risk assessment and risk management reporting processes, by separating the risk in two main categories: strategic and operational risks. The focus is on risk prioritization and scoring; the final output will comprise a mix of strategic and operational (‘top 8-12’ risks, which should be used to establish the annual Internal Audit plan. Originality/value: By using an integrated approach to risk assessment and risk management will eliminate the need for a separate Internal Audit risk assessment over prevailing risks. It will reduce the level of risk assessment overlap by different functions (Tax, Treasury, Information System over the same risk categories as a single methodology, is used and will align timings of risk assessment exercises. The risk prioritization by usage of risk and control scoring criteria highlights the combination between financial and non-financial impact criteria allowing risks that do not naturally lend themselves to a financial amount to be also assessed consistently. It is emphasized the usage of score method to prioritize the risks included in the annual audit plan in order to increase accuracy and timelines.

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

    Science.gov (United States)

    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

  17. Managing Uncertainty and Risk in Public-sector Investments

    Science.gov (United States)

    2007-04-30

    private sector, Capital Asset Pricing Models ( CAPM ) models provide valuation tools, of which the Black-Scholes equation is the most well known and...maximized mean of discounted cash flows on the assumption that the risk to underlying investment options can be replicated by assets in a financial... assumptions seldom apply for large-scale infra-modernization programs, in either the public or the private sector. In addition, NPV investment is

  18. Nuclear Power: Understanding the Economic Risks and Uncertainties

    OpenAIRE

    Kessides, Ioannis N.

    2010-01-01

    This paper identifies the fundamental elements and critical research tasks of a comprehensive analysis of the costs and benefits of nuclear power relative to investments in alternative baseload technologies. The proposed framework seeks to: (i) identify the set of expected parameter values under which nuclear power becomes cost competitive relative to alternative generating technologies; (ii) identify the main risk drivers and quantify their impacts on the costs of nuclear power; (iii) estima...

  19. Risk and uncertainty in the structure of management decision support

    International Nuclear Information System (INIS)

    Valeca, Serban Constantin

    2002-01-01

    The monograph is structured into five chapters addressing the following subject matters: 1 - The risk descriptor implied by the power systems with nuclear injection; 1.1 - Concepts and operators for describing the nuclear power risk; 1.2 - Risk approach in a holistic conception; 2 - Modelling the risk in the frame of re-engineering concept; 2.1 - Defining and interpreting the power re-engineering; 2.2 - Managerial re-engineering of power production systems; 3 - Informatics system of managing the power objectives with nuclear injection; 3.1 - Informatics systems for risk at the level of CANDU - 600 nuclear plant; 3.2. - Expert function structure applicable to the management of power objectives with nuclear injection; 4 - Assisting support in the operation of nuclear facilities; 4.1 - Assisting support system for nuclear plant operation; 4.2 - Program products for dedicated drivers; 5 - The management decision activities at the level of power systems with nuclear injection; 5.1 - Preliminaries in making power decision; 5.2 - Applications of decision models of sustainable power systems with nuclear injection; 5.3 - Re-engineering of power decision in the frame of maximal utility theory. The successful application of re-engineering concept is based on knowledge and managing capacity of design leadership and its ability of dealing the error generating sources. The main stages of implementing successfully the re-engineering are: - Replacing the pollution processes instead of adjusting measures; - Raising the designer responsibility by radical innovation of processes' architecture; - Re-designing the processes by basic changes at the level of the management functions and structures; - Raising the personnel professionalism by motivation as optimal way of improving the workers mentalities; - Accurate definition of objectives in the frame of re-engineering program; - Application of re-engineering in industrial units starting from the management level; - Selecting as general

  20. Sustainability Risk Evaluation for Large-Scale Hydropower Projects with Hybrid Uncertainty

    Directory of Open Access Journals (Sweden)

    Weiyao Tang

    2018-01-01

    Full Text Available As large-scale hydropower projects are influenced by many factors, risk evaluations are complex. This paper considers a hydropower project as a complex system from the perspective of sustainability risk, and divides it into three subsystems: the natural environment subsystem, the eco-environment subsystem and the socioeconomic subsystem. Risk-related factors and quantitative dimensions of each subsystem are comprehensively analyzed considering uncertainty of some quantitative dimensions solved by hybrid uncertainty methods, including fuzzy (e.g., the national health degree, the national happiness degree, the protection of cultural heritage, random (e.g., underground water levels, river width, and fuzzy random uncertainty (e.g., runoff volumes, precipitation. By calculating the sustainability risk-related degree in each of the risk-related factors, a sustainable risk-evaluation model is built. Based on the calculation results, the critical sustainability risk-related factors are identified and targeted to reduce the losses caused by sustainability risk factors of the hydropower project. A case study at the under-construction Baihetan hydropower station is presented to demonstrate the viability of the risk-evaluation model and to provide a reference for the sustainable risk evaluation of other large-scale hydropower projects.

  1. Economic Exposure and Integrated Risk Management

    OpenAIRE

    Miller, Kent D.

    1994-01-01

    Most corporate risk management research focuses on particular risk exposures to the exclusion of other interrelated exposures. By contrast, this study models corporate risk exposures using a multivariate approach integrating the distinct exposures of interest to finance and strategy researchers. The paper addresses the implications of multivariate modeling for corporate risk management, some key methodological issues arising in empirical estimation of corporate economic exposrues, and direc...

  2. Ignoring correlation in uncertainty and sensitivity analysis in life cycle assessment: what is the risk?

    Energy Technology Data Exchange (ETDEWEB)

    Groen, E.A., E-mail: Evelyne.Groen@gmail.com [Wageningen University, P.O. Box 338, Wageningen 6700 AH (Netherlands); Heijungs, R. [Vrije Universiteit Amsterdam, De Boelelaan 1105, Amsterdam 1081 HV (Netherlands); Leiden University, Einsteinweg 2, Leiden 2333 CC (Netherlands)

    2017-01-15

    Life cycle assessment (LCA) is an established tool to quantify the environmental impact of a product. A good assessment of uncertainty is important for making well-informed decisions in comparative LCA, as well as for correctly prioritising data collection efforts. Under- or overestimation of output uncertainty (e.g. output variance) will lead to incorrect decisions in such matters. The presence of correlations between input parameters during uncertainty propagation, can increase or decrease the the output variance. However, most LCA studies that include uncertainty analysis, ignore correlations between input parameters during uncertainty propagation, which may lead to incorrect conclusions. Two approaches to include correlations between input parameters during uncertainty propagation and global sensitivity analysis were studied: an analytical approach and a sampling approach. The use of both approaches is illustrated for an artificial case study of electricity production. Results demonstrate that both approaches yield approximately the same output variance and sensitivity indices for this specific case study. Furthermore, we demonstrate that the analytical approach can be used to quantify the risk of ignoring correlations between input parameters during uncertainty propagation in LCA. We demonstrate that: (1) we can predict if including correlations among input parameters in uncertainty propagation will increase or decrease output variance; (2) we can quantify the risk of ignoring correlations on the output variance and the global sensitivity indices. Moreover, this procedure requires only little data. - Highlights: • Ignoring correlation leads to under- or overestimation of the output variance. • We demonstrated that the risk of ignoring correlation can be quantified. • The procedure proposed is generally applicable in life cycle assessment. • In some cases, ignoring correlation has a minimal effect on decision-making tools.

  3. Dealing with unquantifiable uncertainties in landslide modelling for urban risk reduction in developing countries

    Science.gov (United States)

    Almeida, Susana; Holcombe, Liz; Pianosi, Francesca; Wagener, Thorsten

    2016-04-01

    Landslides have many negative economic and societal impacts, including the potential for significant loss of life and damage to infrastructure. Slope stability assessment can be used to guide decisions about the management of landslide risk, but its usefulness can be challenged by high levels of uncertainty in predicting landslide occurrence. Prediction uncertainty may be associated with the choice of model that is used to assess slope stability, the quality of the available input data, or a lack of knowledge of how future climatic and socio-economic changes may affect future landslide risk. While some of these uncertainties can be characterised by relatively well-defined probability distributions, for other uncertainties, such as those linked to climate change, no probability distribution is available to characterise them. This latter type of uncertainty, often referred to as deep uncertainty, means that robust policies need to be developed that are expected to perform acceptably well over a wide range of future conditions. In our study the impact of deep uncertainty on slope stability predictions is assessed in a quantitative and structured manner using Global Sensitivity Analysis (GSA) and the Combined Hydrology and Stability Model (CHASM). In particular, we use several GSA methods including the Method of Morris, Regional Sensitivity Analysis and Classification and Regression Trees (CART), as well as advanced visualization tools, to assess the combination of conditions that may lead to slope failure. Our example application is a slope in the Caribbean, an area that is naturally susceptible to landslides due to a combination of high rainfall rates during the hurricane season, steep slopes, and highly weathered residual soils. Rapid unplanned urbanisation and changing climate may further exacerbate landslide risk in the future. Our example shows how we can gain useful information in the presence of deep uncertainty by combining physically based models with GSA in

  4. Risk, Uncertainty and Precaution in Science: The Threshold of the Toxicological Concern Approach in Food Toxicology.

    Science.gov (United States)

    Bschir, Karim

    2017-04-01

    Environmental risk assessment is often affected by severe uncertainty. The frequently invoked precautionary principle helps to guide risk assessment and decision-making in the face of scientific uncertainty. In many contexts, however, uncertainties play a role not only in the application of scientific models but also in their development. Building on recent literature in the philosophy of science, this paper argues that precaution should be exercised at the stage when tools for risk assessment are developed as well as when they are used to inform decision-making. The relevance and consequences of this claim are discussed in the context of the threshold of the toxicological concern approach in food toxicology. I conclude that the approach does not meet the standards of an epistemic version of the precautionary principle.

  5. Risk Analysis of Reservoir Flood Routing Calculation Based on Inflow Forecast Uncertainty

    Directory of Open Access Journals (Sweden)

    Binquan Li

    2016-10-01

    Full Text Available Possible risks in reservoir flood control and regulation cannot be objectively assessed by deterministic flood forecasts, resulting in the probability of reservoir failure. We demonstrated a risk analysis of reservoir flood routing calculation accounting for inflow forecast uncertainty in a sub-basin of Huaihe River, China. The Xinanjiang model was used to provide deterministic flood forecasts, and was combined with the Hydrologic Uncertainty Processor (HUP to quantify reservoir inflow uncertainty in the probability density function (PDF form. Furthermore, the PDFs of reservoir water level (RWL and the risk rate of RWL exceeding a defined safety control level could be obtained. Results suggested that the median forecast (50th percentiles of HUP showed better agreement with observed inflows than the Xinanjiang model did in terms of the performance measures of flood process, peak, and volume. In addition, most observations (77.2% were bracketed by the uncertainty band of 90% confidence interval, with some small exceptions of high flows. Results proved that this framework of risk analysis could provide not only the deterministic forecasts of inflow and RWL, but also the fundamental uncertainty information (e.g., 90% confidence band for the reservoir flood routing calculation.

  6. An integrated bi-level optimization model for air quality management of Beijing's energy system under uncertainty.

    Science.gov (United States)

    Jin, S W; Li, Y P; Nie, S

    2018-05-15

    In this study, an interval chance-constrained bi-level programming (ICBP) method is developed for air quality management of municipal energy system under uncertainty. ICBP can deal with uncertainties presented as interval values and probability distributions as well as examine the risk of violating constraints. Besides, a leader-follower decision strategy is incorporated into the optimization process where two decision makers with different goals and preferences are involved. To solve the proposed model, a bi-level interactive algorithm based on satisfactory degree is introduced into the decision-making processes. Then, an ICBP based energy and environmental systems (ICBP-EES) model is formulated for Beijing, in which air quality index (AQI) is used for evaluating the integrated air quality of multiple pollutants. Result analysis can help different stakeholders adjust their tolerances to achieve the overall satisfaction of EES planning for the study city. Results reveal that natural gas is the main source for electricity-generation and heating that could lead to a potentially increment of imported energy for Beijing in future. Results also disclose that PM 10 is the major contributor to AQI. These findings can help decision makers to identify desired alternatives for EES planning and provide useful information for regional air quality management under uncertainty. Copyright © 2018 Elsevier B.V. All rights reserved.

  7. Deep Uncertainty Surrounding Coastal Flood Risk Projections: A Case Study for New Orleans

    Science.gov (United States)

    Wong, Tony E.; Keller, Klaus

    2017-10-01

    Future sea-level rise drives severe risks for many coastal communities. Strategies to manage these risks hinge on a sound characterization of the uncertainties. For example, recent studies suggest that large fractions of the Antarctic ice sheet (AIS) may rapidly disintegrate in response to rising global temperatures, leading to potentially several meters of sea-level rise during the next few centuries. It is deeply uncertain, for example, whether such an AIS disintegration will be triggered, how much this would increase sea-level rise, whether extreme storm surges intensify in a warming climate, or which emissions pathway future societies will choose. Here, we assess the impacts of these deep uncertainties on projected flooding probabilities for a levee ring in New Orleans, LA. We use 18 scenarios, presenting probabilistic projections within each one, to sample key deeply uncertain future projections of sea-level rise, radiative forcing pathways, storm surge characterization, and contributions from rapid AIS mass loss. The implications of these deep uncertainties for projected flood risk are thus characterized by a set of 18 probability distribution functions. We use a global sensitivity analysis to assess which mechanisms contribute to uncertainty in projected flood risk over the course of a 50-year design life. In line with previous work, we find that the uncertain storm surge drives the most substantial risk, followed by general AIS dynamics, in our simple model for future flood risk for New Orleans.

  8. Inexact stochastic risk-aversion optimal day-ahead dispatch model for electricity system management with wind power under uncertainty

    International Nuclear Information System (INIS)

    Ji, Ling; Huang, Guo-He; Huang, Lu-Cheng; Xie, Yu-Lei; Niu, Dong-Xiao

    2016-01-01

    High penetration of wind power generation and deregulated electricity market brings a great challenge to the electricity system operators. It is crucial to make optimal strategy among various generation units and spinning reserve for supporting the system safety operation. By integrating interval two-stage programming and stochastic robust programming, this paper proposes a novel robust model for day-ahead dispatch and risk-aversion management under uncertainties. In the proposed model, the uncertainties are expressed as interval values with different scenario probability. The proposed method requires low computation, and still retains the complete information. A case study is to validate the effectiveness of this approach. Facing the uncertainties of future demand and electricity price, the system operators need to make optimal dispatch strategy for thermal power units and wind turbine, and arrange proper spinning reserve and flexible demand response program to mitigate wind power forecasting error. The optimal strategies provide the system operators with better trade-off between the maximum benefits and the minimum system risk. In additional, two different market rules are compared. The results show that extra financial penalty for the wind power dispatch deviation is another efficient way to enhance the risk consciousness of decision makers and lead to more conservative strategy. - Highlights: • An inexact two-stage stochastic robust programming model for electricity system with wind power penetration. • Uncertainties expressed as discrete intervals and probability distributions. • Demand response program was introduced to adjust the deviation in real-time market. • Financial penalty for imbalance risk from wind power generation was evaluated.

  9. Future Forests. Sustainable Strategies under Uncertainty and Risk

    Energy Technology Data Exchange (ETDEWEB)

    2009-07-01

    Climate change, globalization, and increased consumption of materials and energy leads to higher pressure on forest resources. The task of intensifying forestry to produce more timber, paper, and energy, while at the same time ensuring ecosystem services, such as biodiversity and recreation, is a complex one. Difficult decisions have to be made if we are to strike a balance between these demands. These decisions have to be supported by scientifically-based land-use strategies to deal with tradeoffs on different scales. The vision of Future Forests is to take a significant step forward in this complicated task. The Program has a long-term perspective (50-100 years) and will consider changes in climate, as well as global and market development as major factors likely to have a strong influence on forest management and forest landscapes in the future. In this context, uncertainties, vulnerability, and the adaptive capacity of social-ecological systems must also be considered. The Program's promise to society is: Future Forests will create knowledge and tools to enable sustainable decisions for the future of one of our most important resources - our forests. To fulfill this promise, the Program has the ambition to constitute a platform where researchers from different disciplines, and practitioners from several sectors, can interact. The program will combine empirical research with modeling, scenario analysis, and synthesis work in order to produce excellent science and applications. Much of the multidisciplinary research performed in the Program will be done in the Component Projects. These research groups will be responsible for producing detailed, high quality scientific results that can both be incorporated into the scenarios and be directly relevant for our stakeholders. The Center for Forest System Analyses and Synthesis (ForSA) will form a unifying force in Future Forests. The main goal for this center is to develop skills in scenario analyses and to

  10. Climate induced changes on the hydrology of Mediterranean basins - assessing uncertainties and quantifying risks

    Science.gov (United States)

    Ludwig, Ralf

    2014-05-01

    According to current climate projections, the Mediterranean area is at high risk for severe changes in the hydrological budget and extremes. With innovative scientific measures, integrated hydrological modeling and novel field geophysical field monitoring techniques, the FP7 project CLIMB (Climate Induced Changes on the Hydrology of Mediterranean Basins; GA: 244151) assessed the impacts of climate change on the hydrology in seven basins in the Mediterranean area, in Italy, France, Turkey, Tunisia, Egypt and the Gaza Strip, and quantified uncertainties and risks for the main stakeholders of each test site. Intensive climate model auditing selected four regional climate models, whose data was bias corrected and downscaled to serve as climate forcing for a set of hydrological models in each site. The results of the multi-model hydro-climatic ensemble and socio-economic factor analysis were applied to develop a risk model building upon spatial vulnerability and risk assessment. Findings generally reveal an increasing risk for water resources management in the test sites, yet at different rates and severity in the investigated sectors, with highest impacts likely to occur in the transition months. Most important elements of this research include the following aspects: • Climate change contributes, yet in strong regional variation, to water scarcity in the Mediterranean; other factors, e.g. pollution or poor management practices, are regionally still dominant pressures on water resources. • Rain-fed agriculture needs to adapt to seasonal changes; stable or increasing productivity likely depends on additional irrigation. • Tourism could benefit in shoulder seasons, but may expect income losses in the summer peak season due to increasing heat stress. • Local & regional water managers and water users, lack, as yet, awareness of climate change induced risks; emerging focus areas are supplies of domestic drinking water, irrigation, hydropower and livestock. • Data

  11. Characterising agrometeorological climate risks and uncertainties: Crop production in Uganda

    DEFF Research Database (Denmark)

    Mubiru, Drake N.; Komutunga, Everline; Agona, Ambrose

    2012-01-01

    , the number of rainy days during this critical period of crop growth is decreasing, which possibly means that crops grown in this season are prone to climatic risks and therefore in need of appropriate adaptation measures. A time-series analysis of the maximum daily temperature clearly revealed an increase......Uganda is vulnerable to climate change as most of its agriculture is rain-fed; agriculture is also the backbone of the economy, and the livelihoods of many people depend upon it. Variability in rainfall may be reflected in the productivity of agricultural systems and pronounced variability may...... in temperature, with the lower limits of the ranges of daily maximums increasing faster than the upper limits. Finally, this study has generated information on seasonal rainfall characteristics that will be vital in exploiting the possibilities offered by climatic variability and also offers opportunities...

  12. Preimplantation genetic diagnosis and rational choice under risk or uncertainty.

    Science.gov (United States)

    Zuradzki, Tomasz

    2014-11-01

    In this paper I present an argument in favour of a parental duty to use preimplantation genetic diagnosis (PGD). I argue that if embryos created in vitro were able to decide for themselves in a rational manner, they would sometimes choose PGD as a method of selection. Couples, therefore, should respect their hypothetical choices on a principle similar to that of patient autonomy. My thesis shows that no matter which moral doctrine couples subscribe to, they ought to conduct the PGD procedure in the situations when it is impossible to implant all of the created embryos and if there is a significant risk for giving birth to a child with a serious condition. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  13. Management of uncertainties and the role of risk in Andra programme

    International Nuclear Information System (INIS)

    Grevoz, A.

    2004-01-01

    This paper aims at presenting some aspects of the management of uncertainties in the programmes of Andra for the study of a deep geological repository for high level, long-lived wastes. After presenting very briefly the context of risk-management in the French safety rules, it will discuss how Andra has attempted to link the notions of uncertainties and risk in its 'Dossier 2001' for the clay medium, how this could be made compatible with a deterministic safety approach, what feedback it got from this first exercise, and what are the perspectives for future work. (author)

  14. Collaborative Knowledge Building and Integral Theory: On Perspectives, Uncertainty, and Mutual Regard

    Directory of Open Access Journals (Sweden)

    Tom Murray

    2006-06-01

    Full Text Available Uncertainty in knowing and communicating affect all aspects of modern life. Ubiquitous and inevitable uncertainty, including ambiguity and paradox, is particularly salient and important in knowledge building communities. Because knowledge building communities represent and evolve knowledge explicitly, the causes, effects, and approaches to this “epistemological indeterminacy” can be directly addressed in knowledge building practices. Integral theory’s approach (including “methodological pluralism” involves accepting and integrating diverse perspectives in ways that transcend and include them. This approach accentuates the problems of epistemological indeterminacy and highlights the general need to deal creatively with it. This article begins with a cursory analysis of textual dialogs among integral theorists, showing that, while integral theory itself points to leading-edge ways of dealing with epistemological indeterminacy, the knowledge building practices of integral theorists, by and large, exhibit the same limitations as traditional intellectual discourses. Yet, due to its values and core methods, the integral theory community is in a unique position to develop novel and more adequate modes of inquiry and dialog. This text explores how epistemological indeterminacy impacts the activities and products of groups engaged in collaborative knowledge building. Approaching the issue from three perspectives–mutual understanding, mutual agreement, and mutual regard—I show the interdependence of those perspectives and ground them in relation to integral theory’s concerns. This article proposes three phases of developing constructive alternatives drawn from the knowledge building field: awareness of the phenomena, understanding the phenomena, and offering some tools (and some hope for dealing with it. Though here I focus on the integral theory community (or communities, the conclusions of the article are meant to be applicable to any

  15. Collaborative Knowledge Building and Integral Theory:On Perspectives,Uncertainty, and Mutual Regard

    Directory of Open Access Journals (Sweden)

    Tom Murray

    2006-06-01

    Full Text Available Uncertainty in knowing and communicating affect all aspects of modern life. Ubiquitous and inevitable uncertainty, including ambiguity and paradox, is particularly salient and important in knowledge building communities. Because knowledge building communities represent and evolve knowledge explicitly, the causes, effects, and approaches to this “epistemological indeterminacy” can be directly addressed in knowledge building practices. Integral theory's approach (including “methodological pluralism” involves accepting and integrating diverse perspectives in ways that transcend and include them. This approach accentuates the problems of epistemological indeterminacy and highlights the general need to deal creatively with it. This article begins with a cursory analysis of textual dialogs among integral theorists, showing that, while integral theory itself points to leading-edge ways of dealing with epistemological indeterminacy, the knowledge building practices of integral theorists, by and large, exhibit the same limitations as traditional intellectual discourses. Yet, due to its values and core methods, the integral theory community is in a unique position to develop novel and more adequate modes of inquiry and dialog. This text explores how epistemological indeterminacy impacts the activities and products of groups engaged in collaborative knowledge building. Approaching the issue from three perspectives—mutual understanding, mutual agreement, and mutual regard—I show the interdependence of those perspectives and ground them in relation to integral theory’s concerns. This article proposes three phases of developing constructive alternatives drawn from the knowledge building field: awareness of the phenomena, understanding the phenomena, and offering some tools (and some hope for dealing with it. Though here I focus on the integral theory community (or communities, the conclusions of the article are meant to be applicable to any

  16. Method for estimating effects of unknown correlations in spectral irradiance data on uncertainties of spectrally integrated colorimetric quantities

    Science.gov (United States)

    Kärhä, Petri; Vaskuri, Anna; Mäntynen, Henrik; Mikkonen, Nikke; Ikonen, Erkki

    2017-08-01

    Spectral irradiance data are often used to calculate colorimetric properties, such as color coordinates and color temperatures of light sources by integration. The spectral data may contain unknown correlations that should be accounted for in the uncertainty estimation. We propose a new method for estimating uncertainties in such cases. The method goes through all possible scenarios of deviations using Monte Carlo analysis. Varying spectral error functions are produced by combining spectral base functions, and the distorted spectra are used to calculate the colorimetric quantities. Standard deviations of the colorimetric quantities at different scenarios give uncertainties assuming no correlations, uncertainties assuming full correlation, and uncertainties for an unfavorable case of unknown correlations, which turn out to be a significant source of uncertainty. With 1% standard uncertainty in spectral irradiance, the expanded uncertainty of the correlated color temperature of a source corresponding to the CIE Standard Illuminant A may reach as high as 37.2 K in unfavorable conditions, when calculations assuming full correlation give zero uncertainty, and calculations assuming no correlations yield the expanded uncertainties of 5.6 K and 12.1 K, with wavelength steps of 1 nm and 5 nm used in spectral integrations, respectively. We also show that there is an absolute limit of 60.2 K in the error of the correlated color temperature for Standard Illuminant A when assuming 1% standard uncertainty in the spectral irradiance. A comparison of our uncorrelated uncertainties with those obtained using analytical methods by other research groups shows good agreement. We re-estimated the uncertainties for the colorimetric properties of our 1 kW photometric standard lamps using the new method. The revised uncertainty of color temperature is a factor of 2.5 higher than the uncertainty assuming no correlations.

  17. Divide and Conquer: A Valid Approach for Risk Assessment and Decision Making under Uncertainty for Groundwater-Related Diseases

    Science.gov (United States)

    Sanchez-Vila, X.; de Barros, F.; Bolster, D.; Nowak, W.

    2010-12-01

    Assessing the potential risk of hydro(geo)logical supply systems to human population is an interdisciplinary field. It relies on the expertise in fields as distant as hydrogeology, medicine, or anthropology, and needs powerful translation concepts to provide decision support and policy making. Reliable health risk estimates need to account for the uncertainties in hydrological, physiological and human behavioral parameters. We propose the use of fault trees to address the task of probabilistic risk analysis (PRA) and to support related management decisions. Fault trees allow decomposing the assessment of health risk into individual manageable modules, thus tackling a complex system by a structural “Divide and Conquer” approach. The complexity within each module can be chosen individually according to data availability, parsimony, relative importance and stage of analysis. The separation in modules allows for a true inter- and multi-disciplinary approach. This presentation highlights the three novel features of our work: (1) we define failure in terms of risk being above a threshold value, whereas previous studies used auxiliary events such as exceedance of critical concentration levels, (2) we plot an integrated fault tree that handles uncertainty in both hydrological and health components in a unified way, and (3) we introduce a new form of stochastic fault tree that allows to weaken the assumption of independent subsystems that is required by a classical fault tree approach. We illustrate our concept in a simple groundwater-related setting.

  18. Quantifying Correlation Uncertainty Risk in Credit Derivatives Pricing

    Directory of Open Access Journals (Sweden)

    Colin Turfus

    2018-04-01

    Full Text Available We propose a simple but practical methodology for the quantification of correlation risk in the context of credit derivatives pricing and credit valuation adjustment (CVA, where the correlation between rates and credit is often uncertain or unmodelled. We take the rates model to be Hull–White (normal and the credit model to be Black–Karasinski (lognormal. We summarise recent work furnishing highly accurate analytic pricing formulae for credit default swaps (CDS including with defaultable Libor flows, extending this to the situation where they are capped and/or floored. We also consider the pricing of contingent CDS with an interest rate swap underlying. We derive therefrom explicit expressions showing how the dependence of model prices on the uncertain parameter(s can be captured in analytic formulae that are readily amenable to computation without recourse to Monte Carlo or lattice-based computation. In so doing, we crucially take into account the impact on model calibration of the uncertain (or unmodelled parameters.

  19. Risk at Low Doses: Scientific knowledge, uncertainties and management

    International Nuclear Information System (INIS)

    Giusssani, A.; Ballarini, F.; Ottolenghi, A.

    2002-01-01

    Most of the applications of ionizing radiation in the medical field, for the exposed workers as well as the majority of patients undergoing diagnostic examinations, can be seen as low situations. Epidemiological information is however available for dose and dose rates higher than the values typical of most medical situation. Main source of information is the Life Span Study (LSS) of Japanese. A-bomb survivors, supplemented by studies of selected groups of exposed workers (uranium miners, radium painters) or radiotherapy patients with a detailed follow-up history. All of these group studies, however, suffer from one or more of the following limitations: - lack of adequate dosimetry - lack of a reliable control group for the necessary comparison - influence of concomitant factors (not always easy to find out) - influence of social conditions. In addition exposed study populations are different than the population of patients for which the risk estimates are needed in the medical situation. Recent studies aimed to evaluate the available data on the cohorts of the inhabitants of the Techa river settlements as well as of the workers of the Mayak nuclear facilities may provide in the future useful information on large populations chronically exposed to relatively low doses. (Author)

  20. Environmental impact and risk assessments and key factors contributing to the overall uncertainties.

    Science.gov (United States)

    Salbu, Brit

    2016-01-01

    There is a significant number of nuclear and radiological sources that have contributed, are still contributing, or have the potential to contribute to radioactive contamination of the environment in the future. To protect the environment from radioactive contamination, impact and risk assessments are performed prior to or during a release event, short or long term after deposition or prior and after implementation of countermeasures. When environmental impact and risks are assessed, however, a series of factors will contribute to the overall uncertainties. To provide environmental impact and risk assessments, information on processes, kinetics and a series of input variables is needed. Adding problems such as variability, questionable assumptions, gaps in knowledge, extrapolations and poor conceptual model structures, a series of factors are contributing to large and often unacceptable uncertainties in impact and risk assessments. Information on the source term and the release scenario is an essential starting point in impact and risk models; the source determines activity concentrations and atom ratios of radionuclides released, while the release scenario determine the physico-chemical forms of released radionuclides such as particle size distribution, structure and density. Releases will most often contain other contaminants such as metals, and due to interactions, contaminated sites should be assessed as a multiple stressor scenario. Following deposition, a series of stressors, interactions and processes will influence the ecosystem transfer of radionuclide species and thereby influence biological uptake (toxicokinetics) and responses (toxicodynamics) in exposed organisms. Due to the variety of biological species, extrapolation is frequently needed to fill gaps in knowledge e.g., from effects to no effects, from effects in one organism to others, from one stressor to mixtures. Most toxtests are, however, performed as short term exposure of adult organisms

  1. Adaptive Governance, Uncertainty, and Risk: Policy Framing and Responses to Climate Change, Drought, and Flood.

    Science.gov (United States)

    Hurlbert, Margot; Gupta, Joyeeta

    2016-02-01

    As climate change impacts result in more extreme events (such as droughts and floods), the need to understand which policies facilitate effective climate change adaptation becomes crucial. Hence, this article answers the question: How do governments and policymakers frame policy in relation to climate change, droughts, and floods and what governance structures facilitate adaptation? This research interrogates and analyzes through content analysis, supplemented by semi-structured qualitative interviews, the policy response to climate change, drought, and flood in relation to agricultural producers in four case studies in river basins in Chile, Argentina, and Canada. First, an epistemological explanation of risk and uncertainty underscores a brief literature review of adaptive governance, followed by policy framing in relation to risk and uncertainty, and an analytical model is developed. Pertinent findings of the four cases are recounted, followed by a comparative analysis. In conclusion, recommendations are made to improve policies and expand adaptive governance to better account for uncertainty and risk. This article is innovative in that it proposes an expanded model of adaptive governance in relation to "risk" that can help bridge the barrier of uncertainty in science and policy. © 2015 Society for Risk Analysis.

  2. On the influence of uncertainties in estimating risk aversion and working interest

    International Nuclear Information System (INIS)

    MacKay, J.A.; Lerche, I.

    1996-01-01

    The influence of uncertainties in costs, value, success probability, risk tolerance and mandated working interest are evaluated for their impact on assessing probable ranges of uncertainty on risk adjusted value, RAV, using different models. The relative importance of different factors in contributing to the uncertainty in RAV is analyzed, as is the influence of different probability distributions for the intrinsic variables entering the RAV model formulae. Numerical illustrations indicate how the RAV probabilities depend not only on the model functions (Cozzolino, hyperbolic tangent) used to provide RAV estimates, but also on the intrinsic shapes of the probability distributions from which are drawn input parameter values for Monte Carlo simulations. In addition, a mandated range of working interest can be addressed as an extra variable contributing to the probabilistic range of RAV; while negative RAV values for high-cost project can be used to assess the probable buy-out amount one should be prepared to pay depending on corporate risk philosophy. Also, the procedures illustrate how the relative contributions of scientific factors influence uncertainty of reserve assessments, allowing one to determine where to concentrate effort to improve the ranges of uncertainty. (Author)

  3. A new approach to reduce uncertainties in space radiation cancer risk predictions.

    Directory of Open Access Journals (Sweden)

    Francis A Cucinotta

    Full Text Available The prediction of space radiation induced cancer risk carries large uncertainties with two of the largest uncertainties being radiation quality and dose-rate effects. In risk models the ratio of the quality factor (QF to the dose and dose-rate reduction effectiveness factor (DDREF parameter is used to scale organ doses for cosmic ray proton and high charge and energy (HZE particles to a hazard rate for γ-rays derived from human epidemiology data. In previous work, particle track structure concepts were used to formulate a space radiation QF function that is dependent on particle charge number Z, and kinetic energy per atomic mass unit, E. QF uncertainties where represented by subjective probability distribution functions (PDF for the three QF parameters that described its maximum value and shape parameters for Z and E dependences. Here I report on an analysis of a maximum QF parameter and its uncertainty using mouse tumor induction data. Because experimental data for risks at low doses of γ-rays are highly uncertain which impacts estimates of maximum values of relative biological effectiveness (RBEmax, I developed an alternate QF model, denoted QFγAcute where QFs are defined relative to higher acute γ-ray doses (0.5 to 3 Gy. The alternate model reduces the dependence of risk projections on the DDREF, however a DDREF is still needed for risk estimates for high-energy protons and other primary or secondary sparsely ionizing space radiation components. Risk projections (upper confidence levels (CL for space missions show a reduction of about 40% (CL∼50% using the QFγAcute model compared the QFs based on RBEmax and about 25% (CL∼35% compared to previous estimates. In addition, I discuss how a possible qualitative difference leading to increased tumor lethality for HZE particles compared to low LET radiation and background tumors remains a large uncertainty in risk estimates.

  4. Environmental impact and risk assessments and key factors contributing to the overall uncertainties

    International Nuclear Information System (INIS)

    Salbu, Brit

    2016-01-01

    There is a significant number of nuclear and radiological sources that have contributed, are still contributing, or have the potential to contribute to radioactive contamination of the environment in the future. To protect the environment from radioactive contamination, impact and risk assessments are performed prior to or during a release event, short or long term after deposition or prior and after implementation of countermeasures. When environmental impact and risks are assessed, however, a series of factors will contribute to the overall uncertainties. To provide environmental impact and risk assessments, information on processes, kinetics and a series of input variables is needed. Adding problems such as variability, questionable assumptions, gaps in knowledge, extrapolations and poor conceptual model structures, a series of factors are contributing to large and often unacceptable uncertainties in impact and risk assessments. Information on the source term and the release scenario is an essential starting point in impact and risk models; the source determines activity concentrations and atom ratios of radionuclides released, while the release scenario determine the physico-chemical forms of released radionuclides such as particle size distribution, structure and density. Releases will most often contain other contaminants such as metals, and due to interactions, contaminated sites should be assessed as a multiple stressor scenario. Following deposition, a series of stressors, interactions and processes will influence the ecosystem transfer of radionuclide species and thereby influence biological uptake (toxicokinetics) and responses (toxicodynamics) in exposed organisms. Due to the variety of biological species, extrapolation is frequently needed to fill gaps in knowledge e.g., from effects to no effects, from effects in one organism to others, from one stressor to mixtures. Most toxtests are, however, performed as short term exposure of adult organisms

  5. Accounting for predictive uncertainty in a risk analysis focusing on radiological contamination of groundwater

    International Nuclear Information System (INIS)

    Andricevic, R.; Jacobson, R.L.; Daniels, J.I.

    1994-12-01

    This study focuses on the probabilistic travel time approach for predicting transport of radionuclides by groundwater velocity considering parameter uncertainty. The principal entity in the presented model is a travel time probability density function (pdf) conditioned on the set of parameters used to describe different transport processes like advection, dispersion, sorption, and decay. The model is applied to predict the arrival time of radionuclides in groundwater from the Nevada Test Site (NTS) at possible locations of potential human receptors nearby. Because of the lack of sorption the Tritium is found to provide the largest risk. Inclusion of sorption processes indicate that the parameter uncertainty and especially negative correlation between the mean velocity and the sorption strength is instrumental in evaluating the radionuclides arrival time at the prespecified accessible environment. Our analysis of potential health risks takes into consideration uncertainties in physiological attributes, as well as in committed effective dose and the estimate of physical detriment per unit Committed Effective Dose

  6. Unit commitment with wind power generation: integrating wind forecast uncertainty and stochastic programming.

    Energy Technology Data Exchange (ETDEWEB)

    Constantinescu, E. M.; Zavala, V. M.; Rocklin, M.; Lee, S.; Anitescu, M. (Mathematics and Computer Science); (Univ. of Chicago); (New York Univ.)

    2009-10-09

    We present a computational framework for integrating the state-of-the-art Weather Research and Forecasting (WRF) model in stochastic unit commitment/energy dispatch formulations that account for wind power uncertainty. We first enhance the WRF model with adjoint sensitivity analysis capabilities and a sampling technique implemented in a distributed-memory parallel computing architecture. We use these capabilities through an ensemble approach to model the uncertainty of the forecast errors. The wind power realizations are exploited through a closed-loop stochastic unit commitment/energy dispatch formulation. We discuss computational issues arising in the implementation of the framework. In addition, we validate the framework using real wind speed data obtained from a set of meteorological stations. We also build a simulated power system to demonstrate the developments.

  7. Integrating geophysics and hydrology for reducing the uncertainty of groundwater model predictions and improved prediction performance

    DEFF Research Database (Denmark)

    Christensen, Nikolaj Kruse; Christensen, Steen; Ferre, Ty

    the integration of geophysical data in the construction of a groundwater model increases the prediction performance. We suggest that modelers should perform a hydrogeophysical “test-bench” analysis of the likely value of geophysics data for improving groundwater model prediction performance before actually...... and the resulting predictions can be compared with predictions from the ‘true’ model. By performing this analysis we expect to give the modeler insight into how the uncertainty of model-based prediction can be reduced.......A major purpose of groundwater modeling is to help decision-makers in efforts to manage the natural environment. Increasingly, it is recognized that both the predictions of interest and their associated uncertainties should be quantified to support robust decision making. In particular, decision...

  8. Integration of QFD, AHP, and LPP methods in supplier development problems under uncertainty

    Science.gov (United States)

    Shad, Zahra; Roghanian, Emad; Mojibian, Fatemeh

    2014-04-01

    Quality function deployment (QFD) is a customer-driven approach, widely used to develop or process new product to maximize customer satisfaction. Last researches used linear physical programming (LPP) procedure to optimize QFD; however, QFD issue involved uncertainties, or fuzziness, which requires taking them into account for more realistic study. In this paper, a set of fuzzy data is used to address linguistic values parameterized by triangular fuzzy numbers. Proposed integrated approach including analytic hierarchy process (AHP), QFD, and LPP to maximize overall customer satisfaction under uncertain conditions and apply them in the supplier development problem. The fuzzy AHP approach is adopted as a powerful method to obtain the relationship between the customer requirements and engineering characteristics (ECs) to construct house of quality in QFD method. LPP is used to obtain the optimal achievement level of the ECs and subsequently the customer satisfaction level under different degrees of uncertainty. The effectiveness of proposed method will be illustrated by an example.

  9. Risk assessment of integrated electronic health records.

    Science.gov (United States)

    Bjornsson, Bjarni Thor; Sigurdardottir, Gudlaug; Stefansson, Stefan Orri

    2010-01-01

    The paper describes the security concerns related to Electronic Health Records (EHR) both in registration of data and integration of systems. A description of the current state of EHR systems in Iceland is provided, along with the Ministry of Health's future vision and plans. New legislation provides the opportunity for increased integration of EHRs and further collaboration between institutions. Integration of systems, along with greater availability and access to EHR data, requires increased security awareness since additional risks are introduced. The paper describes the core principles of information security as it applies to EHR systems and data. The concepts of confidentiality, integrity, availability, accountability and traceability are introduced and described. The paper discusses the legal requirements and importance of performing risk assessment for EHR data. Risk assessment methodology according to the ISO/IEC 27001 information security standard is described with examples on how it is applied to EHR systems.

  10. Flood risk assessment and robust management under deep uncertainty: Application to Dhaka City

    Science.gov (United States)

    Mojtahed, Vahid; Gain, Animesh Kumar; Giupponi, Carlo

    2014-05-01

    The socio-economic changes as well as climatic changes have been the main drivers of uncertainty in environmental risk assessment and in particular flood. The level of future uncertainty that researchers face when dealing with problems in a future perspective with focus on climate change is known as Deep Uncertainty (also known as Knightian uncertainty), since nobody has already experienced and undergone those changes before and our knowledge is limited to the extent that we have no notion of probabilities, and therefore consolidated risk management approaches have limited potential.. Deep uncertainty is referred to circumstances that analysts and experts do not know or parties to decision making cannot agree on: i) the appropriate models describing the interaction among system variables, ii) probability distributions to represent uncertainty about key parameters in the model 3) how to value the desirability of alternative outcomes. The need thus emerges to assist policy-makers by providing them with not a single and optimal solution to the problem at hand, such as crisp estimates for the costs of damages of natural hazards considered, but instead ranges of possible future costs, based on the outcomes of ensembles of assessment models and sets of plausible scenarios. Accordingly, we need to substitute optimality as a decision criterion with robustness. Under conditions of deep uncertainty, the decision-makers do not have statistical and mathematical bases to identify optimal solutions, while instead they should prefer to implement "robust" decisions that perform relatively well over all conceivable outcomes out of all future unknown scenarios. Under deep uncertainty, analysts cannot employ probability theory or other statistics that usually can be derived from observed historical data and therefore, we turn to non-statistical measures such as scenario analysis. We construct several plausible scenarios with each scenario being a full description of what may happen

  11. Allocating risk capital for a brownfields redevelopment project under hydrogeological and financial uncertainty.

    Science.gov (United States)

    Yu, Soonyoung; Unger, Andre J A; Parker, Beth; Kim, Taehee

    2012-06-15

    In this study, we defined risk capital as the contingency fee or insurance premium that a brownfields redeveloper needs to set aside from the sale of each house in case they need to repurchase it at a later date because the indoor air has been detrimentally affected by subsurface contamination. The likelihood that indoor air concentrations will exceed a regulatory level subject to subsurface heterogeneity and source zone location uncertainty is simulated by a physics-based hydrogeological model using Monte Carlo realizations, yielding the probability of failure. The cost of failure is the future value of the house indexed to the stochastic US National Housing index. The risk capital is essentially the probability of failure times the cost of failure with a surcharge to compensate the developer against hydrogeological and financial uncertainty, with the surcharge acting as safety loading reflecting the developers' level of risk aversion. We review five methodologies taken from the actuarial and financial literature to price the risk capital for a highly stylized brownfield redevelopment project, with each method specifically adapted to accommodate our notion of the probability of failure. The objective of this paper is to develop an actuarially consistent approach for combining the hydrogeological and financial uncertainty into a contingency fee that the brownfields developer should reserve (i.e. the risk capital) in order to hedge their risk exposure during the project. Results indicate that the price of the risk capital is much more sensitive to hydrogeological rather than financial uncertainty. We use the Capital Asset Pricing Model to estimate the risk-adjusted discount rate to depreciate all costs to present value for the brownfield redevelopment project. A key outcome of this work is that the presentation of our risk capital valuation methodology is sufficiently generalized for application to a wide variety of engineering projects. Copyright © 2012 Elsevier

  12. Risk assessment through drinking water pathway via uncertainty modeling of contaminant transport using soft computing

    International Nuclear Information System (INIS)

    Datta, D.; Ranade, A.K.; Pandey, M.; Sathyabama, N.; Kumar, Brij

    2012-01-01

    The basic objective of an environmental impact assessment (EIA) is to build guidelines to reduce the associated risk or mitigate the consequences of the reactor accident at its source to prevent deterministic health effects, to reduce the risk of stochastic health effects (eg. cancer and severe hereditary effects) as much as reasonable achievable by implementing protective actions in accordance with IAEA guidance (IAEA Safety Series No. 115, 1996). The measure of exposure being the basic tool to take any appropriate decisions related to risk reduction, EIA is traditionally expressed in terms of radiation exposure to the member of the public. However, models used to estimate the exposure received by the member of the public are governed by parameters some of which are deterministic with relative uncertainty and some of which are stochastic as well as imprecise (insufficient knowledge). In an admixture environment of this type, it is essential to assess the uncertainty of a model to estimate the bounds of the exposure to the public to invoke a decision during an event of nuclear or radiological emergency. With a view to this soft computing technique such as evidence theory based assessment of model parameters is addressed to compute the risk or exposure to the member of the public. The possible pathway of exposure to the member of the public in the aquatic food stream is the drinking of water. Accordingly, this paper presents the uncertainty analysis of exposure via uncertainty analysis of the contaminated water. Evidence theory finally addresses the uncertainty in terms of lower bound as belief measure and upper bound of exposure as plausibility measure. In this work EIA is presented using evidence theory. Data fusion technique is used to aggregate the knowledge on the uncertain information. Uncertainty of concentration and exposure is expressed as an interval of belief, plausibility

  13. Micropollutants throughout an integrated urban drainage model: Sensitivity and uncertainty analysis

    Science.gov (United States)

    Mannina, Giorgio; Cosenza, Alida; Viviani, Gaspare

    2017-11-01

    The paper presents the sensitivity and uncertainty analysis of an integrated urban drainage model which includes micropollutants. Specifically, a bespoke integrated model developed in previous studies has been modified in order to include the micropollutant assessment (namely, sulfamethoxazole - SMX). The model takes into account also the interactions between the three components of the system: sewer system (SS), wastewater treatment plant (WWTP) and receiving water body (RWB). The analysis has been applied to an experimental catchment nearby Palermo (Italy): the Nocella catchment. Overall, five scenarios, each characterized by different uncertainty combinations of sub-systems (i.e., SS, WWTP and RWB), have been considered applying, for the sensitivity analysis, the Extended-FAST method in order to select the key factors affecting the RWB quality and to design a reliable/useful experimental campaign. Results have demonstrated that sensitivity analysis is a powerful tool for increasing operator confidence in the modelling results. The approach adopted here can be used for blocking some non-identifiable factors, thus wisely modifying the structure of the model and reducing the related uncertainty. The model factors related to the SS have been found to be the most relevant factors affecting the SMX modeling in the RWB when all model factors (scenario 1) or model factors of SS (scenarios 2 and 3) are varied. If the only factors related to the WWTP are changed (scenarios 4 and 5), the SMX concentration in the RWB is mainly influenced (till to 95% influence of the total variance for SSMX,max) by the aerobic sorption coefficient. A progressive uncertainty reduction from the upstream to downstream was found for the soluble fraction of SMX in the RWB.

  14. Impact of Hydrogeological Uncertainty on Estimation of Environmental Risks Posed by Hydrocarbon Transportation Networks

    Science.gov (United States)

    Ciriello, V.; Lauriola, I.; Bonvicini, S.; Cozzani, V.; Di Federico, V.; Tartakovsky, Daniel M.

    2017-11-01

    Ubiquitous hydrogeological uncertainty undermines the veracity of quantitative predictions of soil and groundwater contamination due to accidental hydrocarbon spills from onshore pipelines. Such predictions, therefore, must be accompanied by quantification of predictive uncertainty, especially when they are used for environmental risk assessment. We quantify the impact of parametric uncertainty on quantitative forecasting of temporal evolution of two key risk indices, volumes of unsaturated and saturated soil contaminated by a surface spill of light nonaqueous-phase liquids. This is accomplished by treating the relevant uncertain parameters as random variables and deploying two alternative probabilistic models to estimate their effect on predictive uncertainty. A physics-based model is solved with a stochastic collocation method and is supplemented by a global sensitivity analysis. A second model represents the quantities of interest as polynomials of random inputs and has a virtually negligible computational cost, which enables one to explore any number of risk-related contamination scenarios. For a typical oil-spill scenario, our method can be used to identify key flow and transport parameters affecting the risk indices, to elucidate texture-dependent behavior of different soils, and to evaluate, with a degree of confidence specified by the decision-maker, the extent of contamination and the correspondent remediation costs.

  15. A Minimax Regret Analysis of Flood Risk Management Strategies Under Climate Change Uncertainty and Emerging Information

    NARCIS (Netherlands)

    Pol, van der T.D.; Gabbert, S.; Weikard, H.P.; Ierland, van E.C.; Hendrix, E.M.T.

    2017-01-01

    This paper studies the dynamic application of the minimax regret (MR) decision criterion to identify robust flood risk management strategies under climate change uncertainty and emerging information. An MR method is developed that uses multiple learning scenarios, for example about sea level rise

  16. Identifying Selected Behavioral Determinants of Risk and Uncertainty on the Real Estate Market

    Directory of Open Access Journals (Sweden)

    Brzezicka Justyna

    2014-07-01

    Full Text Available Various market behaviors can be characterized as risky or uncertain, thus their observation is important to the real estate market system. The extensive use of behavioral factors facilitates their implementation and studies in relation to the real estate market system. The behavioral approach has established its own instrumentation which enables elements of risk and uncertainty to be quantified.

  17. Framing risk and uncertainty in social science articles on climate change, 1995-2012

    NARCIS (Netherlands)

    Shaw, C.; Hellsten, I.; Nerlich, B.; Crichton, J.; Candlin, C.N.; Firkins, A.S.

    2016-01-01

    The issue of climate change is intimately linked to notions of risk and uncertainty, concepts that pose challenges to climate science, climate change communication, and science-society interactions. While a large majority of climate scientists are increasingly certain about the causes of climate

  18. RISK MANAGEMENT: AN INTEGRATED APPROACH TO RISK MANAGEMENT AND ASSESSMENT

    OpenAIRE

    Szabo Alina

    2012-01-01

    Purpose: The objective of this paper is to offer an overview over risk management cycle by focusing on prioritization and treatment, in order to ensure an integrated approach to risk management and assessment, and establish the ‘top 8-12’ risks report within the organization. The interface with Internal Audit is ensured by the implementation of the scoring method to prioritize risks collected from previous generated risk report. Methodology/approach: Using evidence from other research in ...

  19. Technical and governance considerations for advanced metering infrastructure/smart meters: Technology, security, uncertainty, costs, benefits, and risks

    International Nuclear Information System (INIS)

    McHenry, Mark P.

    2013-01-01

    The fundamental role of policymakers when considering Advanced Metering Infrastructure (AMI), or ‘smart meters for energy and water infrastructure is to investigate a broad range of complex interrelated issues. These include alternative technical and non-technical options and deployment needs, the cost and benefits of the infrastructure (risks and mitigation measures), and the impact of a number of stakeholders: consumers, distributors, retailers, competitive market operators, competing technology companies, etc. The scale and number of potential variables in the AMI space is an almost unprecedented challenge to policymakers, with the anticipation of new ancillary products and services, associated market contestability, related regulatory and policy amendments, and the adequacy of consumer protection, education, and safety considerations requiring utmost due-diligence. Embarking on AMI investment entails significant technical, implementation, and strategic risk for governments and administering bodies, and an active effort is required to ensure AMI governance and planning maximises the potential benefits, and minimise uncertainties, costs, and risks to stakeholders. This work seeks to clarify AMI fundamentals and discusses the technical and related governance considerations from a dispassionate perspective, yet acknowledges many stakeholders tend to dichotomise debate, and obfuscate both advantages and benefits, and the converse. - Highlights: • AMI presents an almost unprecedented technical and governance policy challenge. • AMI enables vertical integration of electricity, gas, water, IT, and telco entities • AMI investments involve major technical, implementation, and strategic decisions. • Adequacy of consumer education, safety, privacy, and protection is paramount. • Policy must maximise AMI benefits and minimise uncertainties, costs, and risks

  20. RISK INTEGRATION MECHANISMS AND APPROACHES IN BANKING INDUSTRY

    OpenAIRE

    JIANPING LI; JICHUANG FENG; XIAOLEI SUN; MINGLU LI

    2012-01-01

    Recently, the number of consultative documents and research papers that discuss risk integration has grown considerably. This paper presents a comprehensive review of the work done on risk integration in the banking industry. This survey includes: (1) risk integration methods within regulatory frameworks and the banking industry; (2) challenges of risk integration; (3) risk interaction mechanisms; (4) development of risk integration approaches; (5) risk interaction results: diversification ve...

  1. Economics versus psychology.Risk, uncertainty and the expected utility theory

    OpenAIRE

    Schilirò, Daniele

    2017-01-01

    The present contribution examines the emergence of expected utility theory by John von Neumann and Oskar Morgenstern, the subjective the expected utility theory by Savage, and the problem of choice under risk and uncertainty, focusing in particular on the seminal work “The Utility Analysis of Choices involving Risk" (1948) by Milton Friedman and Leonard Savage to show how the evolution of the theory of choice has determined a separation of economics from psychology.

  2. Uncertainty analysis of an integrated energy system based on information theory

    International Nuclear Information System (INIS)

    Fu, Xueqian; Sun, Hongbin; Guo, Qinglai; Pan, Zhaoguang; Xiong, Wen; Wang, Li

    2017-01-01

    Currently, a custom-designed configuration of different renewable technologies named the integrated energy system (IES) has become popular due to its high efficiency, benefiting from complementary multi-energy technologies. This paper proposes an information entropy approach to quantify uncertainty in an integrated energy system based on a stochastic model that drives a power system model derived from an actual network on Barry Island. Due to the complexity of co-behaviours between generators, a copula-based approach is utilized to articulate the dependency structure of the generator outputs with regard to such factors as weather conditions. Correlation coefficients and mutual information, which are effective for assessing the dependence relationships, are applied to judge whether the stochastic IES model is correct. The calculated information values can be used to analyse the impacts of the coupling of power and heat on power flows and heat flows, and this approach will be helpful for improving the operation of IES. - Highlights: • The paper explores uncertainty of an integrated energy system. • The dependent weather model is verified from the perspective of correlativity. • The IES model considers the dependence between power and heat. • The information theory helps analyse the complexity of IES operation. • The application of the model is studied using an operational system on Barry Island.

  3. [Status Quo, Uncertainties and Trends Analysis of Environmental Risk Assessment for PFASs].

    Science.gov (United States)

    Hao, Xue-wen; Li, Li; Wang, Jie; Cao, Yan; Liu, Jian-guo

    2015-08-01

    This study systematically combed the definition and change of terms, category and application of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in international academic, focusing on the environmental risk and exposure assessment of PFASs, to comprehensively analyze the current status, uncertainties and trends of PFASs' environmental risk assessment. Overall, the risk assessment of PFASs is facing a complicated situation involving complex substance pedigrees, various types, complex derivative relations, confidential business information and risk uncertainties. Although the environmental risk of long-chain PFASs has been widely recognized, the short-chain PFASs and short-chain fluorotelomers as their alternatives still have many research gaps and uncertainties in environmental hazards, environmental fate and exposure risk. The scope of risk control of PFASs in the international community is still worth discussing. Due to trade secrets and market competition, the chemical structure and risk information of PFASs' alternatives are generally lack of openness and transparency. The environmental risk of most fluorinated and non-fluorinated alternatives is not clear. In total, the international research on PFASs risk assessment gradually transfer from long-chain perfluoroalkyl acids (PFAAs) represented by perfluorooctane sulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) to short-chain PFAAs, and then extends to other PFASs. The main problems to be solved urgently and researched continuously are: the environmental hazardous assessment indexes, such as bioaccumulation and environmental migration, optimization method, the environmental release and multimedia environmental fate of short-chain PFASs; the environmental fate of neutral PFASs and the transformation and contribution as precursors of short-chain PFASs; the risk identification and assessment of fluorinated and non-fluorinated alternatives of PFASs.

  4. Efficient uncertainty quantification in fully-integrated surface and subsurface hydrologic simulations

    Science.gov (United States)

    Miller, K. L.; Berg, S. J.; Davison, J. H.; Sudicky, E. A.; Forsyth, P. A.

    2018-01-01

    Although high performance computers and advanced numerical methods have made the application of fully-integrated surface and subsurface flow and transport models such as HydroGeoSphere common place, run times for large complex basin models can still be on the order of days to weeks, thus, limiting the usefulness of traditional workhorse algorithms for uncertainty quantification (UQ) such as Latin Hypercube simulation (LHS) or Monte Carlo simulation (MCS), which generally require thousands of simulations to achieve an acceptable level of accuracy. In this paper we investigate non-intrusive polynomial chaos for uncertainty quantification, which in contrast to random sampling methods (e.g., LHS and MCS), represents a model response of interest as a weighted sum of polynomials over the random inputs. Once a chaos expansion has been constructed, approximating the mean, covariance, probability density function, cumulative distribution function, and other common statistics as well as local and global sensitivity measures is straightforward and computationally inexpensive, thus making PCE an attractive UQ method for hydrologic models with long run times. Our polynomial chaos implementation was validated through comparison with analytical solutions as well as solutions obtained via LHS for simple numerical problems. It was then used to quantify parametric uncertainty in a series of numerical problems with increasing complexity, including a two-dimensional fully-saturated, steady flow and transient transport problem with six uncertain parameters and one quantity of interest; a one-dimensional variably-saturated column test involving transient flow and transport, four uncertain parameters, and two quantities of interest at 101 spatial locations and five different times each (1010 total); and a three-dimensional fully-integrated surface and subsurface flow and transport problem for a small test catchment involving seven uncertain parameters and three quantities of interest at

  5. Uncertainty of angular displacement measurement with a MEMS gyroscope integrated in a smartphone

    International Nuclear Information System (INIS)

    De Campos Porath, Maurício; Dolci, Ricardo

    2015-01-01

    Low-cost inertial sensors have recently gained popularity and are now widely used in electronic devices such as smartphones and tablets. In this paper we present the results of a set of experiments aiming to assess the angular displacement measurement errors of a gyroscope integrated in a smartphone of a recent model. The goal is to verify whether these sensors could substitute dedicated electronic inclinometers for the measurement of angular displacement. We estimated a maximum error of 0.3° (sum of expanded uncertainty and maximum absolute bias) for the roll and pitch axes, for a measurement time without referencing up to 1 h. (paper)

  6. Integrated presentation of ecological risk from multiple stressors

    Science.gov (United States)

    Goussen, Benoit; Price, Oliver R.; Rendal, Cecilie; Ashauer, Roman

    2016-10-01

    Current environmental risk assessments (ERA) do not account explicitly for ecological factors (e.g. species composition, temperature or food availability) and multiple stressors. Assessing mixtures of chemical and ecological stressors is needed as well as accounting for variability in environmental conditions and uncertainty of data and models. Here we propose a novel probabilistic ERA framework to overcome these limitations, which focusses on visualising assessment outcomes by construct-ing and interpreting prevalence plots as a quantitative prediction of risk. Key components include environmental scenarios that integrate exposure and ecology, and ecological modelling of relevant endpoints to assess the effect of a combination of stressors. Our illustrative results demonstrate the importance of regional differences in environmental conditions and the confounding interactions of stressors. Using this framework and prevalence plots provides a risk-based approach that combines risk assessment and risk management in a meaningful way and presents a truly mechanistic alternative to the threshold approach. Even whilst research continues to improve the underlying models and data, regulators and decision makers can already use the framework and prevalence plots. The integration of multiple stressors, environmental conditions and variability makes ERA more relevant and realistic.

  7. Integrated presentation of ecological risk from multiple stressors.

    Science.gov (United States)

    Goussen, Benoit; Price, Oliver R; Rendal, Cecilie; Ashauer, Roman

    2016-10-26

    Current environmental risk assessments (ERA) do not account explicitly for ecological factors (e.g. species composition, temperature or food availability) and multiple stressors. Assessing mixtures of chemical and ecological stressors is needed as well as accounting for variability in environmental conditions and uncertainty of data and models. Here we propose a novel probabilistic ERA framework to overcome these limitations, which focusses on visualising assessment outcomes by construct-ing and interpreting prevalence plots as a quantitative prediction of risk. Key components include environmental scenarios that integrate exposure and ecology, and ecological modelling of relevant endpoints to assess the effect of a combination of stressors. Our illustrative results demonstrate the importance of regional differences in environmental conditions and the confounding interactions of stressors. Using this framework and prevalence plots provides a risk-based approach that combines risk assessment and risk management in a meaningful way and presents a truly mechanistic alternative to the threshold approach. Even whilst research continues to improve the underlying models and data, regulators and decision makers can already use the framework and prevalence plots. The integration of multiple stressors, environmental conditions and variability makes ERA more relevant and realistic.

  8. Assessment of uncertainties in risk analysis of chemical establishments. The ASSURANCE project. Final summary report

    DEFF Research Database (Denmark)

    Lauridsen, K.; Kozine, Igor; Markert, Frank

    2002-01-01

    and led the comparison of results in order to reveal the causes for differences between the partners' results. The results of the project point to an increased awareness of the potential uncertainties in riskanalyses and highlight a number of important sources of such uncertainties. In the hazard......This report summarises the results obtained in the ASSURANCE project (EU contract number ENV4-CT97-0627). Seven teams have performed risk analyses for the same chemical facility, an ammonia storage. The EC's Joint Research Centre at Ispra and RisøNational Laboratory co-ordinated the exercise...

  9. Analyzing climate change impacts on water resources under uncertainty using an integrated simulation-optimization approach

    Science.gov (United States)

    Zhuang, X. W.; Li, Y. P.; Nie, S.; Fan, Y. R.; Huang, G. H.

    2018-01-01

    An integrated simulation-optimization (ISO) approach is developed for assessing climate change impacts on water resources. In the ISO, uncertainties presented as both interval numbers and probability distributions can be reflected. Moreover, ISO permits in-depth analyses of various policy scenarios that are associated with different levels of economic consequences when the promised water-allocation targets are violated. A snowmelt-precipitation-driven watershed (Kaidu watershed) in northwest China is selected as the study case for demonstrating the applicability of the proposed method. Results of meteorological projections disclose that the incremental trend of temperature (e.g., minimum and maximum values) and precipitation exist. Results also reveal that (i) the system uncertainties would significantly affect water resources allocation pattern (including target and shortage); (ii) water shortage would be enhanced from 2016 to 2070; and (iii) the more the inflow amount decreases, the higher estimated water shortage rates are. The ISO method is useful for evaluating climate change impacts within a watershed system with complicated uncertainties and helping identify appropriate water resources management strategies hedging against drought.

  10. Economic–Environmental Sustainability in Building Projects: Introducing Risk and Uncertainty in LCCE and LCCA

    Directory of Open Access Journals (Sweden)

    Elena Fregonara

    2018-06-01

    Full Text Available The aim of this paper is to propose a methodology for supporting decision-making in the design stages of new buildings or in the retrofitting of existing heritages. The focus is on the evaluation of economic–environmental sustainability, considering the presence of risk and uncertainty. An application of risk analysis in conjunction with Life-Cycle Cost Analysis (LCCA is proposed for selecting the preferable solution between technological options, which represents a recent and poorly explored context of analysis. It is assumed that there is a presence of uncertainty in cost estimating, in terms of the Life-Cycle Cost Estimates (LCCEs and uncertainty in the technical performance of the life-cycle cost analysis. According to the probability analysis, which was solved through stochastic simulation and the Monte Carlo Method (MCM, risk and uncertainty are modeled as stochastic variables or as “stochastic relevant cost drivers”. Coherently, the economic–financial and energy–environmental sustainability is analyzed through the calculation of a conjoint “economic–environmental indicator”, in terms of the stochastic global cost. A case study of the multifunctional building glass façade project in Northern Italy is proposed. The application demonstrates that introducing flexibility into the input data and the duration of the service lives of components and the economic and environmental behavior of alternative scenarios can lead to opposite results compared to a deterministic analysis. The results give full evidence of the environmental variables’ capacity to significantly perturb the model output.

  11. A risk-averse optimization model for trading wind energy in a market environment under uncertainty

    International Nuclear Information System (INIS)

    Pousinho, H.M.I.; Mendes, V.M.F.; Catalao, J.P.S.

    2011-01-01

    In this paper, a stochastic programming approach is proposed for trading wind energy in a market environment under uncertainty. Uncertainty in the energy market prices is the main cause of high volatility of profits achieved by power producers. The volatile and intermittent nature of wind energy represents another source of uncertainty. Hence, each uncertain parameter is modeled by scenarios, where each scenario represents a plausible realization of the uncertain parameters with an associated occurrence probability. Also, an appropriate risk measurement is considered. The proposed approach is applied on a realistic case study, based on a wind farm in Portugal. Finally, conclusions are duly drawn. -- Highlights: → We model uncertainties on energy market prices and wind power production. → A hybrid intelligent approach generates price-wind power scenarios. → Risk aversion is also incorporated in the proposed stochastic programming approach. → A realistic case study, based on a wind farm in Portugal, is provided. → Our approach allows selecting the best solution according to the desired risk exposure level.

  12. Risk newsboy: approach for addressing uncertainty in developing action levels and cleanup limits

    International Nuclear Information System (INIS)

    Cooke, Roger; MacDonell, Margaret

    2007-01-01

    Site cleanup decisions involve developing action levels and residual limits for key contaminants, to assure health protection during the cleanup period and into the long term. Uncertainty is inherent in the toxicity information used to define these levels, based on incomplete scientific knowledge regarding dose-response relationships across various hazards and exposures at environmentally relevant levels. This problem can be addressed by applying principles used to manage uncertainty in operations research, as illustrated by the newsboy dilemma. Each day a newsboy must balance the risk of buying more papers than he can sell against the risk of not buying enough. Setting action levels and cleanup limits involves a similar concept of balancing and distributing risks and benefits in the face of uncertainty. The newsboy approach can be applied to develop health-based target concentrations for both radiological and chemical contaminants, with stakeholder input being crucial to assessing 'regret' levels. Associated tools include structured expert judgment elicitation to quantify uncertainty in the dose-response relationship, and mathematical techniques such as probabilistic inversion and iterative proportional fitting. (authors)

  13. Risk Informed Structural Systems Integrity Management

    DEFF Research Database (Denmark)

    Nielsen, Michael Havbro Faber

    2017-01-01

    The present paper is predominantly a conceptual contribution with an appraisal of major developments in risk informed structural integrity management for offshore installations together with a discussion of their merits and the challenges which still lie ahead. Starting point is taken in a selected...... overview of research and development contributions which have formed the basis for Risk Based Inspection Planning (RBI) as we know it today. Thereafter an outline of the methodical basis for risk informed structural systems integrity management, i.e. the Bayesian decision analysis is provided in summary....... The main focus is here directed on RBI for offshore facilities subject to fatigue damages. New ideas and methodical frameworks in the area of robustness and resilience modeling of structural systems are then introduced, and it is outlined how these may adequately be utilized to enhance Structural Integrity...

  14. A risk explicit interval linear programming model for uncertainty-based environmental economic optimization in the Lake Fuxian watershed, China.

    Science.gov (United States)

    Zhang, Xiaoling; Huang, Kai; Zou, Rui; Liu, Yong; Yu, Yajuan

    2013-01-01

    The conflict of water environment protection and economic development has brought severe water pollution and restricted the sustainable development in the watershed. A risk explicit interval linear programming (REILP) method was used to solve integrated watershed environmental-economic optimization problem. Interval linear programming (ILP) and REILP models for uncertainty-based environmental economic optimization at the watershed scale were developed for the management of Lake Fuxian watershed, China. Scenario analysis was introduced into model solution process to ensure the practicality and operability of optimization schemes. Decision makers' preferences for risk levels can be expressed through inputting different discrete aspiration level values into the REILP model in three periods under two scenarios. Through balancing the optimal system returns and corresponding system risks, decision makers can develop an efficient industrial restructuring scheme based directly on the window of "low risk and high return efficiency" in the trade-off curve. The representative schemes at the turning points of two scenarios were interpreted and compared to identify a preferable planning alternative, which has the relatively low risks and nearly maximum benefits. This study provides new insights and proposes a tool, which was REILP, for decision makers to develop an effectively environmental economic optimization scheme in integrated watershed management.

  15. A Risk Explicit Interval Linear Programming Model for Uncertainty-Based Environmental Economic Optimization in the Lake Fuxian Watershed, China

    Directory of Open Access Journals (Sweden)

    Xiaoling Zhang

    2013-01-01

    Full Text Available The conflict of water environment protection and economic development has brought severe water pollution and restricted the sustainable development in the watershed. A risk explicit interval linear programming (REILP method was used to solve integrated watershed environmental-economic optimization problem. Interval linear programming (ILP and REILP models for uncertainty-based environmental economic optimization at the watershed scale were developed for the management of Lake Fuxian watershed, China. Scenario analysis was introduced into model solution process to ensure the practicality and operability of optimization schemes. Decision makers’ preferences for risk levels can be expressed through inputting different discrete aspiration level values into the REILP model in three periods under two scenarios. Through balancing the optimal system returns and corresponding system risks, decision makers can develop an efficient industrial restructuring scheme based directly on the window of “low risk and high return efficiency” in the trade-off curve. The representative schemes at the turning points of two scenarios were interpreted and compared to identify a preferable planning alternative, which has the relatively low risks and nearly maximum benefits. This study provides new insights and proposes a tool, which was REILP, for decision makers to develop an effectively environmental economic optimization scheme in integrated watershed management.

  16. Evaluation of mechanical precision and alignment uncertainties for an integrated CT/LINAC system

    International Nuclear Information System (INIS)

    Court, Laurence; Rosen, Isaac; Mohan, Radhe; Dong Lei

    2003-01-01

    A new integrated CT/LINAC combination, in which the CT scanner is inside the radiation therapy treatment room and the same patient couch is used for CT scanning and treatment (after a 180-degree couch rotation), should allow for accurate correction of interfractional setup errors. The purpose of this study was to evaluate the sources of uncertainties, and to measure the overall precision of this system. The following sources of uncertainty were identified: (1) the patient couch position on the LINAC side after a rotation, (2) the patient couch position on the CT side after a rotation, (3) the patient couch position as indicated by its digital readout, (4) the difference in couch sag between the CT and LINAC positions, (5) the precision of the CT coordinates, (6) the identification of fiducial markers from CT images, (7) the alignment of contours with structures in the CT images, and (8) the alignment with setup lasers. The largest single uncertainties (one standard deviation or 1 SD) were found in couch position on the CT side after a rotation (0.5 mm in the RL direction) and the alignment of contours with the CT images (0.4 mm in the SI direction). All other sources of uncertainty are less than 0.3 mm (1 SD). The overall precision of two setup protocols was investigated in a controlled phantom study. A protocol that relies heavily on the mechanical integrity of the system, and assumes a fixed relationship between the LINAC isocenter and the CT images, gave a predicted precision (1 SD) of 0.6, 0.7, and 0.6 mm in the SI, RL and AP directions, respectively. The second protocol reduces reliance on the mechanical precision of the total system, particularly the patient couch, by using radio-opaque fiducial markers to transfer the isocenter information from the LINAC side to the CT images. This protocol gave a slightly improved predicted precision of 0.5, 0.4, and 0.4 mm in the SI, RL and AP directions, respectively. The distribution of phantom position after CT

  17. Integrative evaluation for sustainable decisions of urban wastewater system management under uncertainty

    Science.gov (United States)

    Hadjimichael, A.; Corominas, L.; Comas, J.

    2017-12-01

    With sustainable development as their overarching goal, urban wastewater system (UWS) managers need to take into account multiple social, economic, technical and environmental facets related to their decisions. In this complex decision-making environment, uncertainty can be formidable. It is present both in the ways the system is interpreted stochastically, but also in its natural ever-shifting behavior. This inherent uncertainty suggests that wiser decisions would be made under an adaptive and iterative decision-making regime. No decision-support framework has been presented in the literature to effectively addresses all these needs. The objective of this work is to describe such a conceptual framework to evaluate and compare alternative solutions for various UWS challenges within an adaptive management structure. Socio-economic aspects such as externalities are taken into account, along with other traditional criteria as necessary. Robustness, reliability and resilience analyses test the performance of the system against present and future variability. A valuation uncertainty analysis incorporates uncertain valuation assumptions in the decision-making process. The framework is demonstrated with an application to a case study presenting a typical problem often faced by managers: poor river water quality, increasing population, and more stringent water quality legislation. The application of the framework made use of: i) a cost-benefit analysis including monetized environmental benefits and damages; ii) a robustness analysis of system performance against future conditions; iii) reliability and resilience analyses of the system given contextual variability; and iv) a valuation uncertainty analysis of model parameters. The results suggest that the installation of bigger volumes would give rise to increased benefits despite larger capital costs, as well as increased robustness and resilience. Population numbers appear to affect the estimated benefits most, followed by

  18. Modeling the Near-Term Risk of Climate Uncertainty: Interdependencies among the U.S. States

    Science.gov (United States)

    Lowry, T. S.; Backus, G.; Warren, D.

    2010-12-01

    Decisions made to address climate change must start with an understanding of the risk of an uncertain future to human systems, which in turn means understanding both the consequence as well as the probability of a climate induced impact occurring. In other words, addressing climate change is an exercise in risk-informed policy making, which implies that there is no single correct answer or even a way to be certain about a single answer; the uncertainty in future climate conditions will always be present and must be taken as a working-condition for decision making. In order to better understand the implications of uncertainty on risk and to provide a near-term rationale for policy interventions, this study estimates the impacts from responses to climate change on U.S. state- and national-level economic activity by employing a risk-assessment methodology for evaluating uncertain future climatic conditions. Using the results from the Intergovernmental Panel on Climate Change’s (IPCC) Fourth Assessment Report (AR4) as a proxy for climate uncertainty, changes in hydrology over the next 40 years were mapped and then modeled to determine the physical consequences on economic activity and to perform a detailed 70-industry analysis of the economic impacts among the interacting lower-48 states. The analysis determines industry-level effects, employment impacts at the state level, interstate population migration, consequences to personal income, and ramifications for the U.S. trade balance. The conclusions show that the average risk of damage to the U.S. economy from climate change is on the order of $1 trillion over the next 40 years, with losses in employment equivalent to nearly 7 million full-time jobs. Further analysis shows that an increase in uncertainty raises this risk. This paper will present the methodology behind the approach, a summary of the underlying models, as well as the path forward for improving the approach.

  19. In uncertainty we trust: a median voter model with risk aversion

    Directory of Open Access Journals (Sweden)

    Pavel A. Yakovlev

    2011-12-01

    Full Text Available The principal-agent problem and uncertainty are some of the key factors affecting financial and political markets. Fear of the unknown plays an important role in human decision making, including voting. This article describes a theoretical model where voter risk aversion towards uncertainty gives political incumbents a significant advantage over their challengers, exacerbating the principal-agent problem between voters and legislators. The model presented predicts that a rise in voter uncertainty concerning the challenger allows the incumbent to deviate from the median voter’s policy preference without losing the election. This model reconciles the paradoxical coexistence of ideological shirking and high incumbent reelection rates without abandoning the elegant median voter framework.

  20. Climate change, uncertainty, and resilient fisheries: Institutional responses through integrative science

    DEFF Research Database (Denmark)

    Miller, K.; Charles, A.; Barange, M.

    2010-01-01

    This paper explores the importance of a focus on the fundamental goals of resilience and adaptive capacity in the governance of uncertain fishery systems, particularly in the context of climate change. Climate change interacts strongly with fishery systems, and adds to the inherent uncertainty...... that understanding these aspects of fishery systems and fishery governance is valuable even in the absence of climate-induced processes of change, but that attention to climate change both reinforces the need for, and facilitates the move toward, implementation of integrative science for improved fishery governance....... and processes – to support suitable institutional responses, a broader planning perspective, and development of suitable resilience-building strategies. The paper explores how synergies between institutional change and integrative science can facilitate the development of more effective fisheries policy...

  1. Stochastic fuzzy environmental risk characterization of uncertainty and variability in risk assessments: A case study of polycyclic aromatic hydrocarbons in soil at a petroleum-contaminated site in China

    International Nuclear Information System (INIS)

    Hu, Yan; Wang, Zesen; Wen, Jingya; Li, Yu

    2016-01-01

    Highlights: • Deal with environmental quality guidelines absence in risk characterization. • Quantitative represention of uncertainty from environmental quality guidelines. • Quantitative represention of variability from contaminant exposure concentrations. • Establishment of stochastic-fuzzy environmental risk characterization approach framework. - Abstract: Better decisions are made using risk assessment models when uncertainty and variability are explicitly acknowledged. Uncertainty caused by a lack of uniform and scientifically supported environmental quality guidelines and variability in the degree of exposure of environmental systems to contaminants are here incorporated in a stochastic fuzzy environmental risk characterization (SFERC) approach. The approach is based on quotient probability distribution and environmental risk level fuzzy membership function methods. The SFERC framework was used to characterize the environmental risks posed by 16 priority polycyclic aromatic hydrocarbons (PAHs) in soil at a typical petroleum-contaminated site in China. This relied on integrating data from the literature and field and laboratory experiments. The environmental risk levels posed by the PAHs under four risk scenarios were determined using the SFERC approach, using “residential land” and “industrial land” environmental quality guidelines under “loose” and “strict” strictness parameters. The results showed that environmental risks posed by PAHs in soil are primarily caused by oil exploitation, traffic emissions, and coal combustion. The SFERC approach is an effective tool for characterizing uncertainty and variability in environmental risk assessments and for managing contaminated sites.

  2. Stochastic fuzzy environmental risk characterization of uncertainty and variability in risk assessments: A case study of polycyclic aromatic hydrocarbons in soil at a petroleum-contaminated site in China

    Energy Technology Data Exchange (ETDEWEB)

    Hu, Yan [MOE Key Laboratory of Regional Energy Systems Optimization, Resources and Environmental Research Academy, North China Electric Power University, Beijing 102206 (China); State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environment Sciences, Beijing 100012 (China); Wang, Zesen [MOE Key Laboratory of Regional Energy Systems Optimization, Resources and Environmental Research Academy, North China Electric Power University, Beijing 102206 (China); Wen, Jingya [MOE Key Laboratory of Regional Energy Systems Optimization, Resources and Environmental Research Academy, North China Electric Power University, Beijing 102206 (China); Institute of Hydropower and Environment Research, Beijing 100012 (China); Li, Yu, E-mail: liyuxx8@hotmail.com [MOE Key Laboratory of Regional Energy Systems Optimization, Resources and Environmental Research Academy, North China Electric Power University, Beijing 102206 (China)

    2016-10-05

    Highlights: • Deal with environmental quality guidelines absence in risk characterization. • Quantitative represention of uncertainty from environmental quality guidelines. • Quantitative represention of variability from contaminant exposure concentrations. • Establishment of stochastic-fuzzy environmental risk characterization approach framework. - Abstract: Better decisions are made using risk assessment models when uncertainty and variability are explicitly acknowledged. Uncertainty caused by a lack of uniform and scientifically supported environmental quality guidelines and variability in the degree of exposure of environmental systems to contaminants are here incorporated in a stochastic fuzzy environmental risk characterization (SFERC) approach. The approach is based on quotient probability distribution and environmental risk level fuzzy membership function methods. The SFERC framework was used to characterize the environmental risks posed by 16 priority polycyclic aromatic hydrocarbons (PAHs) in soil at a typical petroleum-contaminated site in China. This relied on integrating data from the literature and field and laboratory experiments. The environmental risk levels posed by the PAHs under four risk scenarios were determined using the SFERC approach, using “residential land” and “industrial land” environmental quality guidelines under “loose” and “strict” strictness parameters. The results showed that environmental risks posed by PAHs in soil are primarily caused by oil exploitation, traffic emissions, and coal combustion. The SFERC approach is an effective tool for characterizing uncertainty and variability in environmental risk assessments and for managing contaminated sites.

  3. Assessing risks and uncertainties in forest dynamics under different management scenarios and climate change

    Directory of Open Access Journals (Sweden)

    Matthias Albert

    2015-05-01

    Full Text Available Background Forest management faces a climate induced shift in growth potential and increasing current and emerging new risks. Vulnerability analysis provides decision support based on projections of natural resources taking risks and uncertainties into account. In this paper we (1 characterize differences in forest dynamics under three management scenarios, (2 analyse the effects of the three scenarios on two risk factors, windthrow and drought stress, and (3 quantify the effects and the amount of uncertainty arising from climate projections on height increment and drought stress. Methods In four regions in northern Germany, we apply three contrasting management scenarios and project forest development under climate change until 2070. Three climate runs (minimum, median, maximum based on the emission scenario RCP 8.5 control the site-sensitive forest growth functions. The minimum and maximum climate run define the range of prospective climate development. Results The projections of different management regimes until 2070 show the diverging medium-term effects of thinnings and harvests and long-term effects of species conversion on a regional scale. Examples of windthrow vulnerability and drought stress reveal how adaptation measures depend on the applied management path and the decision-maker’s risk attitude. Uncertainty analysis shows the increasing variability of drought risk projections with time. The effect of climate projections on height growth are quantified and uncertainty analysis reveals that height growth of young trees is dominated by the age-trend whereas the climate signal in height increment of older trees is decisive. Conclusions Drought risk is a serious issue in the eastern regions independent of the applied silvicultural scenario, but adaptation measures are limited as the proportion of the most drought tolerant species Scots pine is already high. Windthrow risk is no serious overall threat in any region, but adequate

  4. An interdisciplinary approach to volcanic risk reduction under conditions of uncertainty: a case study of Tristan da Cunha

    Science.gov (United States)

    Hicks, A.; Barclay, J.; Simmons, P.; Loughlin, S.

    2013-12-01

    This research project adopted an interdisciplinary approach to volcanic risk reduction on the remote volcanic island of Tristan da Cunha (South Atlantic). New data were produced that: (1) established no spatio-temporal pattern to recent volcanic activity; (2) quantified the high degree of scientific uncertainty around future eruptive scenarios; (3) analysed the physical vulnerability of the community as a consequence of their geographical isolation and exposure to volcanic hazards; (4) evaluated social and cultural influences on vulnerability and resilience. Despite their isolation and prolonged periods of hardship, islanders have demonstrated an ability to cope with and recover from adverse events. This resilience is likely a function of remoteness, strong kinship ties, bonding social capital, and persistence of shared values and principles established at community inception. While there is good knowledge of the styles of volcanic activity on Tristan, given the high degree of scientific uncertainty about the timing, size and location of future volcanism, a qualitative scenario planning approach was used as a vehicle to convey this information to the islanders. This deliberative, anticipatory method allowed on-island decision makers to take ownership of risk identification, management and capacity building within their community. This paper demonstrates the value of integrating social and physical sciences with development of effective, tailored communication strategies in volcanic risk reduction.

  5. CLIMB - Climate induced changes on the hydrology of mediterranean basins - Reducing uncertainties and quantifying risk

    Science.gov (United States)

    Ludwig, Ralf

    2010-05-01

    According to future climate projections, Mediterranean countries are at high risk for an even pronounced susceptibility to changes in the hydrological budget and extremes. These changes are expected to have severe direct impacts on the management of water resources. Threats include severe droughts and extreme flooding, salinization of coastal aquifers, degradation of fertile soils and desertification due to poor and unsustainable water management practices. It can be foreseen that, unless appropriate adaptation measures are undertaken, the changes in the hydrologic cycle will give rise to an increasing potential for tension and conflict among the political and economic actors in this vulnerable region. The presented project initiative CLIMB, funded under EC's 7th Framework Program (FP7-ENV-2009-1), has started in January 2010. In its 4-year design, it shall analyze ongoing and future climate induced changes in hydrological budgets and extremes across the Mediterranean and neighboring regions. This is undertaken in study sites located in Sardinia, Northern Italy, Southern France, Tunisia, Egypt and the Palestinian-administered area Gaza. The work plan is targeted to selected river or aquifer catchments, where the consortium will employ a combination of novel field monitoring and remote sensing concepts, data assimilation, integrated hydrologic (and biophysical) modeling and socioeconomic factor analyses to reduce existing uncertainties in climate change impact analysis. Advanced climate scenario analysis will be employed and available ensembles of regional climate model simulations will be downscaling. This process will provide the drivers for an ensemble of hydro(-geo)logical models with different degrees of complexity in terms of process description and level of integration. The results of hydrological modeling and socio-economic factor analysis will enable the development of a GIS-based Vulnerability and Risk Assessment Tool. This tool will serve as a platform

  6. An integrated, probabilistic model for improved seasonal forecasting of agricultural crop yield under environmental uncertainty

    Directory of Open Access Journals (Sweden)

    Nathaniel K. Newlands

    2014-06-01

    Full Text Available We present a novel forecasting method for generating agricultural crop yield forecasts at the seasonal and regional-scale, integrating agroclimate variables and remotely-sensed indices. The method devises a multivariate statistical model to compute bias and uncertainty in forecasted yield at the Census of Agricultural Region (CAR scale across the Canadian Prairies. The method uses robust variable-selection to select the best predictors within spatial subregions. Markov-Chain Monte Carlo (MCMC simulation and random forest-tree machine learning techniques are then integrated to generate sequential forecasts through the growing season. Cross-validation of the model was performed by hindcasting/backcasting it and comparing its forecasts against available historical data (1987-2011 for spring wheat (Triticum aestivum L.. The model was also validated for the 2012 growing season by comparing its forecast skill at the CAR, provincial and Canadian Prairie region scales against available statistical survey data. Mean percent departures between wheat yield forecasted were under-estimated by 1-4 % in mid-season and over-estimated by 1 % at the end of the growing season. This integrated methodology offers a consistent, generalizable approach for sequentially forecasting crop yield at the regional-scale. It provides a statistically robust, yet flexible way to concurrently adjust to data-rich and data-sparse situations, adaptively select different predictors of yield to changing levels of environmental uncertainty, and to update forecasts sequentially so as to incorporate new data as it becomes available. This integrated method also provides additional statistical support for assessing the accuracy and reliability of model-based crop yield forecasts in time and space.

  7. The effect of weather uncertainty on the financial risk of green electricity producers under various renewable policies

    Energy Technology Data Exchange (ETDEWEB)

    Nagl, Stephan

    2013-06-15

    In recent years, many countries have implemented policies to incentivize renewable power generation. In this paper, we analyze the variance in profits of renewable-based electricity producers due to weather uncertainty under a 'feed-in tariff' policy, a 'fixed bonus' incentive and a 'renewable quota' obligation. In a first step, we discuss the price effects of fluctuations in the feed-in from renewables and their impact on the risk for green electricity producers. In a second step, we numerically solve the problem by applying a spatial stochastic equilibrium model to the European electricity market. The simulation results allow us to discuss the variance in profits under the different renewable support mechanisms and how different technologies are affected by weather uncertainty. The analysis suggests that wind producers benefit from market integration, whereas producers from biomass and solar plants face a larger variance in profits. Furthermore, the simulation indicates that highly volatile green certificate prices occur when introducing a renewable quota obligation without the option of banking and borrowing. Thus, all renewable producers face a higher variance in profits, as the price effect of weather uncertainty on green certificates overcompensates the negatively correlated fluctuations in production and prices.

  8. Risk management in architectural design control of uncertainty over building use and maintenance

    CERN Document Server

    Martani, Claudio

    2015-01-01

    This book analyzes the risk management process in relation to building design and operation and on this basis proposes a method and a set of tools that will improve the planning and evaluation of design solutions in order to control risks in the operation and management phase. Particular attention is paid to the relationship between design choices and the long-term performance of buildings in meeting requirements expressing user and client needs. A risk dashboard is presented as a risk measurement framework that identifies and addresses areas of uncertainty surrounding the satisfaction of particularly relevant requirements over time. This risk dashboard will assist both designers and clients. It will support designers by enabling them to improve the maintainability of project performance and will aid clients both in devising a brief that emphasizes the most relevant aspects of maintainability and in evaluating project proposals according to long-term risks. The results of assessment of the proposed method and...

  9. Contaminated site risk and uncertainty assessment for impacts on surface and groundwater

    DEFF Research Database (Denmark)

    Thomsen, Nanna Isbak

    available between sites and choosing between the need for further investigation or remediation. This is a question of prioritizing the sites that pose the greatest risk, and it is a matter of making decisions under uncertainty. Both tasks require a structured assessment of the risk posed by the contaminated...... sites. In a conventional risk assessment of a contaminated site, risk is evaluated by assessing whether a concentration guideline is exceeded at a specific point of compliance in the water resource of interest. If the guideline is exceeded, it is concluded that the site poses a risk. However......, a contaminated site may pose a threat to multiple water resources, or multiple contaminated sites may threaten a single water resource. For more advanced risk assessments, it is therefore relevant to develop methods that can handle this challenge. In this thesis, four contributions are made to the field...

  10. Value at risk (VaR in uncertainty: Analysis with parametric method and black & scholes simulations

    Directory of Open Access Journals (Sweden)

    Humberto Banda Ortiz

    2014-07-01

    Full Text Available VaR is the most accepted risk measure worldwide and the leading reference in any risk management assessment. However, its methodology has important limitations which makes it unreliable in contexts of crisis or high uncertainty. For this reason, the aim of this work is to test the VaR accuracy when is employed in contexts of volatility, for which we compare the VaR outcomes in scenarios of both stability and uncertainty, using the parametric method and a historical simulation based on data generated with the Black & Scholes model. VaR main objective is the prediction of the highest expected loss for any given portfolio, but even when it is considered a useful tool for risk management under conditions of markets stability, we found that it is substantially inaccurate in contexts of crisis or high uncertainty. In addition, we found that the Black & Scholes simulations lead to underestimate the expected losses, in comparison with the parametric method and we also found that those disparities increase substantially in times of crisis. In the first section of this work we present a brief context of risk management in finance. In section II we present the existent literature relative to the VaR concept, its methods and applications. In section III we describe the methodology and assumptions used in this work. Section IV is dedicated to expose the findings. And finally, in Section V we present our conclusions.

  11. Local scale multiple quantitative risk assessment and uncertainty evaluation in a densely urbanised area (Brescia, Italy

    Directory of Open Access Journals (Sweden)

    S. Lari

    2012-11-01

    Full Text Available The study of the interactions between natural and anthropogenic risks is necessary for quantitative risk assessment in areas affected by active natural processes, high population density and strong economic activities.

    We present a multiple quantitative risk assessment on a 420 km2 high risk area (Brescia and surroundings, Lombardy, Northern Italy, for flood, seismic and industrial accident scenarios. Expected economic annual losses are quantified for each scenario and annual exceedance probability-loss curves are calculated. Uncertainty on the input variables is propagated by means of three different methodologies: Monte-Carlo-Simulation, First Order Second Moment, and point estimate.

    Expected losses calculated by means of the three approaches show similar values for the whole study area, about 64 000 000 € for earthquakes, about 10 000 000 € for floods, and about 3000 € for industrial accidents. Locally, expected losses assume quite different values if calculated with the three different approaches, with differences up to 19%.

    The uncertainties on the expected losses and their propagation, performed with the three methods, are compared and discussed in the paper. In some cases, uncertainty reaches significant values (up to almost 50% of the expected loss. This underlines the necessity of including uncertainty in quantitative risk assessment, especially when it is used as a support for territorial planning and decision making. The method is developed thinking at a possible application at a regional-national scale, on the basis of data available in Italy over the national territory.

  12. Incorporating uncertainties into risk assessment with an application to the exploratory studies facilities at Yucca Mountain

    International Nuclear Information System (INIS)

    Fathauer, P.M.

    1995-08-01

    A methodology that incorporates variability and reducible sources of uncertainty into the probabilistic and consequence components of risk was developed. The method was applied to the north tunnel of the Exploratory Studies Facility at Yucca Mountain in Nevada. In this assessment, variability and reducible sources of uncertainty were characterized and propagated through the risk assessment models using a Monte Carlo based software package. The results were then manipulated into risk curves at the 5% and 95% confidence levels for both the variability and overall uncertainty analyses, thus distinguishing between variability and reducible sources of uncertainty. In the Yucca Mountain application, the designation of the north tunnel as an item important to public safety, as defined by 10 CFR 60, was determined. Specifically, the annual frequency of a rock fall breaching a waste package causing an off-site dose of 500 mrem (5x10 -3 Sv) was calculated. The annual frequency, taking variability into account, ranged from 1.9x10 -9 per year at the 5% confidence level to 2.5x10 -9 per year at the 95% confidence level. The frequency range after including all uncertainty was 9.5x10 -10 to 1.8x10 -8 per year. The maximum observable frequency, at the 100% confidence level, was 4.9x10 -8 per year. This is below the 10 -6 per year frequency criteria of 10 CFR 60. Therefore, based on this work, the north tunnel does not fall under the items important to public safety designation for the event studied

  13. A risk-based method for planning of bus–subway corridor evacuation under hybrid uncertainties

    International Nuclear Information System (INIS)

    Lv, Y.; Yan, X.D.; Sun, W.; Gao, Z.Y.

    2015-01-01

    Emergencies involved in a bus–subway corridor system are associated with many processes and factors with social and economic implications. These processes and factors and their interactions are related to a variety of uncertainties. In this study, an interval chance-constrained integer programming (EICI) method is developed in response to such challenges for bus–subway corridor based evacuation planning. The method couples a chance-constrained programming with an interval integer programming model framework. It can thus deal with interval uncertainties that cannot be quantified with specified probability distribution functions. Meanwhile, it can also reflect stochastic features of traffic flow capacity, and thereby help examine the related violation risk of constraint. The EICI method is applied to a subway incident based evacuation case study. It is solved through an interactive algorithm that does not lead to more complicated intermediate submodels and has a relatively low computational requirement. A number of decision alternatives could be directly generated based on results from the EICI method. It is indicated that the solutions cannot only help decision makers identify desired population evacuation and vehicle dispatch schemes under hybrid uncertainties, but also provide bases for in-depth analyses of tradeoffs among evacuation plans, total evacuation time, and constraint-violation risks. - Highlights: • An inexact model is developed for the bus–subway corridor evacuation management. • It tackles stochastic and interval uncertainties in an integer programming problem. • It can examine violation risk of the roadway flow capacity related constraint. • It will help identify evacuation schemes under hybrid uncertainties

  14. A new kind of uncertainty for a new kind of modernity? Expertise in an age of risk.

    Science.gov (United States)

    Munk, A.

    2009-04-01

    Modernity is not what it used to be (see for example Giddens 1991, Beck 1992, Bauman 2000, Luhman 2005). It has, so the sociologists tell us, mutated in order to thrive in a new age of risk and uncertainty. Some might say that it is not quite thriving yet. Whereas old modernity relied on experts to evaluate the problems opposing society and devise solutions for them - savoir pour prevoir, prevoir pour pouvoir - new modernity can no longer indulge in such straightforwardness. The hazards facing us have become so undeniably complex and in multiple ways produced by the very social activities they threaten, that uncontroversial fixes based on indisputable evidence can no longer be assumed. What role for expertise, then, in this increasingly complicated social landscape? As a starting point for thinking about this question, the paper sets out to explore the concept of uncertainty. After all, when it comes to hazards, this is what experts are expected to handle. Has it mutated as well? Does it make sense to speak of a new kind of uncertainty for a new kind of modernity? In its first modernity setting, uncertainty was what had to be transformed into some sort of certainty (see for example Latour 1999). In the case of the inherent uncertainties related to hazards and risk this task was accomplished with the emergence of probability theory and actuarial science (see for example Hacking 1979, 1990). Expertise in old modernity thus acquired a lot of its straightforwardness from its belief in uncomplicating uncertainty by transforming it into certainty. So, why is it still complicated? A crucial point in Latour's argument is that expertise works by reducing complexity in order to amplify facts (certainties). This requires a sense of direction and an agreement as to what is deemed important. Markets, for example, possess this. So do scientific communities and political institutions. But do the combined constituencies implicated by the complex risks facing society possess it

  15. Integral Risk Management for DBFM Tenders and Contracts in the Netherlands

    NARCIS (Netherlands)

    Wong, J.; Berkelaar, R.; Pekelharing, H.

    2015-01-01

    This paper presents an overview of an integral risk management approach with emphasis on the relationships with the costing and scheduling processes. Forms of uncertainty related to project planning are classified and implemented in the probabilistic costing and scheduling processes. Furthermore,

  16. Crop modelling for integrated assessment of risk to food production from climate change

    Czech Academy of Sciences Publication Activity Database

    Ewert, F.; Rötter, R. P.; Bindi, M.; Weber, H.; Trnka, Miroslav; Kersebaum, K. C.; Olesen, J. E.; van Ittersum, M. K.; Janssen, S.; Rivingtom, M.; Semenov, M. A.; Wallach, D.; Porter, J. R.; Stewart, D.; Vegahen, J.; Gaiser, T.; Palouso, T.; Tao, F.; Nendel, C.; Roggero, P. P.; Bartošová, Lenka; Asseng, S.

    2015-01-01

    Roč. 72, oct (2015), s. 287-303 ISSN 1364-8152 R&D Projects: GA MZe QJ1310123; GA MŠk(CZ) EE2.3.20.0248 Institutional support: RVO:67179843 Keywords : uncertainty * scaling * integrated assessment * risk assessment * adaptation * crop models Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 4.207, year: 2015

  17. Assessment and presentation of uncertainties in probabilistic risk assessment: how should this be done

    International Nuclear Information System (INIS)

    Garlick, A.R.; Holloway, N.J.

    1987-01-01

    Despite continuing improvements in probabilistic risk assessment (PRA) techniques, PRA results, particularly those including degraded core analysis, will have maximum uncertainties of several orders of magnitude. This makes the expression of results, a matter no less important than their estimation. We put forward some ideas on the assessment and expression of highly uncertain quantities, such as probabilities of outcomes of a severe accident. These do not form a consistent set, but rather a number of alternative approaches aimed at stimulating discussion. These include non-probability expressions, such as fuzzy logic or Schafer's support and plausibility which abandon the purely probabilistic expression of risk for a more flexible type of expression, in which other types of measure are possible. The 'risk equivalent plant' concepts represent the opposite approach. Since uncertainty in a risk measure is in itself a form of risk, an attempt is made to define a 'risk equivalent' which is a risk with perfectly defined parameters, regarded (by means of suitable methods of judgement) as 'equally undesirable' with the actual plant. Some guidelines are given on the use of Bayesian methods in data-free or limited data situations. (author)

  18. How to manage project opportunity and risk why uncertainty management can be a much better approach than risk management

    CERN Document Server

    Ward, Stephen

    2011-01-01

    Since I wrote the Foreword for the second edition of this book, risk management processes have become much more widely used, but controversy about what should be done and how best to do it has grown. Managing risk is a risky business. Chapman and Ward provide an in-depth explanation of why it is important to understand and manage underlying uncertainty in all its forms, in order to realise opportunities more fully and enhance corporate performance. They show what best practice should look like. The implications go well beyond the conventional wisdom of project risk management, providing an enl

  19. Integrating spaceflight human system risk research

    Science.gov (United States)

    Mindock, Jennifer; Lumpkins, Sarah; Anton, Wilma; Havenhill, Maria; Shelhamer, Mark; Canga, Michael

    2017-10-01

    NASA is working to increase the likelihood of exploration mission success and to maintain crew health, both during exploration missions and long term after return to Earth. To manage the risks in achieving these goals, a system modelled after a Continuous Risk Management framework is in place. ;Human System Risks; (Risks) have been identified, and 32 are currently being actively addressed by NASA's Human Research Program (HRP). Research plans for each of HRP's Risks have been developed and are being executed. Inter-disciplinary ties between the research efforts supporting each Risk have been identified; however, efforts to identify and benefit from these connections have been mostly ad hoc. There is growing recognition that solutions developed to address the full set of Risks covering medical, physiological, behavioural, vehicle, and organizational aspects of exploration missions must be integrated across Risks and disciplines. This paper discusses how a framework of factors influencing human health and performance in space is being applied as the backbone for bringing together sometimes disparate information relevant to the individual Risks. The resulting interrelated information enables identification and visualization of connections between Risks and research efforts in a systematic and standardized manner. This paper also discusses the applications of the visualizations and insights into research planning, solicitation, and decision-making processes.

  20. Role of calibration, validation, and relevance in multi-level uncertainty integration

    International Nuclear Information System (INIS)

    Li, Chenzhao; Mahadevan, Sankaran

    2016-01-01

    Calibration of model parameters is an essential step in predicting the response of a complicated system, but the lack of data at the system level makes it impossible to conduct this quantification directly. In such a situation, system model parameters are estimated using tests at lower levels of complexity which share the same model parameters with the system. For such a multi-level problem, this paper proposes a methodology to quantify the uncertainty in the system level prediction by integrating calibration, validation and sensitivity analysis at different levels. The proposed approach considers the validity of the models used for parameter estimation at lower levels, as well as the relevance at the lower level to the prediction at the system level. The model validity is evaluated using a model reliability metric, and models with multivariate output are considered. The relevance is quantified by comparing Sobol indices at the lower level and system level, thus measuring the extent to which a lower level test represents the characteristics of the system so that the calibration results can be reliably used in the system level. Finally the results of calibration, validation and relevance analysis are integrated in a roll-up method to predict the system output. - Highlights: • Relevance analysis to quantify the closeness of two models. • Stochastic model reliability metric to integrate multiple validation experiments. • Extend the model reliability metric to deal with multivariate output. • Roll-up formula to integrate calibration, validation, and relevance.

  1. Uncertainty reduction of gravity and magnetic inversion through the integration of petrophysical constraints and geological data

    Science.gov (United States)

    Giraud, Jérémie; Jessell, Mark; Lindsay, Mark; Martin, Roland; Pakyuz-Charrier, Evren; Ogarko, Vitaliy

    2016-04-01

    We introduce and test a workflow that integrates petrophysical constraints and geological data in geophysical inversion to decrease the uncertainty and non-uniqueness of the results. We show that the integration of geological information and petrophysical constraints in geophysical inversion can improve inversion results in terms of both uncertainty reduction and resolution. This workflow uses statistical petrophysical properties to constrain the values retrieved by the geophysical inversion and geological prior information to decrease the effect of non-uniqueness. Surface geological data are used to generate geological models as a source of geometrical prior information. Petrophysical measurements are used to derive the statistical laws used for the petrophysical constraints. We integrate the different sources of information in a Bayesian framework, which will take into account these states of information. This permits us to quantify the posterior state of knowledge, the reduction of the uncertainty and to calculate the influence of prior information. To quantify the influence of petrophysical constraints and geological data we compare results obtained with several levels of constraints. We start by inverting data without petrophysical constraints and geological prior information. Then, we add petrophysical constraints before using geological prior information. The results of the inversion are characterized using fixed-point statistics. Various indicators such as model and data misfits, resolution matrices and statistical fit to the petrophysical data are calculated. The resolution matrices are used to plot sensitivity maps. We calculate the posterior covariance matrices to estimate the uncertainty of the model. This workflow was first tested using very simple synthetic datasets before using a subset of the Mansfield area data (Victoria, Australia). The geological model is derived from geological field data. We simulate petrophysical properties based on field

  2. Assessing Extinction Risk: Integrating Genetic Information

    Directory of Open Access Journals (Sweden)

    Jason Dunham

    1999-06-01

    Full Text Available Risks of population extinction have been estimated using a variety of methods incorporating information from different spatial and temporal scales. We briefly consider how several broad classes of extinction risk assessments, including population viability analysis, incidence functions, and ranking methods integrate information on different temporal and spatial scales. In many circumstances, data from surveys of neutral genetic variability within, and among, populations can provide information useful for assessing extinction risk. Patterns of genetic variability resulting from past and present ecological and demographic events, can indicate risks of extinction that are otherwise difficult to infer from ecological and demographic analyses alone. We provide examples of how patterns of neutral genetic variability, both within, and among populations, can be used to corroborate and complement extinction risk assessments.

  3. Uncertainty analysis of the 35% reactor inlet header break in a CANDU 6 reactor using RELAP/SCDAPSIM/MOD4.0 with integrated uncertainty analysis option

    Energy Technology Data Exchange (ETDEWEB)

    Dupleac, D., E-mail: danieldu@cne.pub.ro [Politehnica Univ. of Bucharest (Romania); Perez, M.; Reventos, F., E-mail: marina.perez@upc.edu, E-mail: francesc.reventos@upc.edu [Technical Univ. of Catalonia (Spain); Allison, C., E-mail: iss@cableone.net [Innovative Systems Software (United States)

    2011-07-01

    The RELAP/SCDAPSIM/MOD4.0 code, designed to predict the behavior of reactor systems during normal and accident conditions, is being developed as part of an international nuclear technology Software Development and Training Program (SDTP). RELAP/SCDAPSIM/MOD4.0, which is the first version of RELAP5 completely rewritten to FORTRAN 90/95/2000 standards, uses the publicly available RELAP5 and SCDAP models in combination with (a) advanced programming and numerical techniques, (b) advanced SDTP-member-developed models for LWR, HWR, and research reactor analysis, and (c) a variety of other member-developed computational packages. One such computational package is an integrated uncertainty analysis (IUA) package being developed jointly by the Technical University of Catalonia (UPC) and Innovative Systems Software (ISS). RELAP/SCDAPSIM/MOD4.0(IUA) follows the input-propagation approach using probability distribution functions to define the uncertainty of the input parameters. The main steps for this type of methodologies, often referred as to statistical approaches or Wilks’ methods, are the ones that follow: 1. Selection of the plant; 2. Selection of the scenario; 3. Selection of the safety criteria; 4. Identification and ranking of the relevant phenomena based on the safety criteria; 5. Selection of the appropriate code parameters to represent those phenomena; 6. Association of uncertainty by means of Probability Distribution Functions (PDFs) for each selected parameter; 7. Random sampling of the selected parameters according to its PDF and performing multiple computer runs to obtain uncertainty bands with a certain percentile and confidence level; 8. Processing the results of the multiple computer runs to estimate the uncertainty bands for the computed quantities associated with the selected safety criteria. RELAP/SCDAPSIM/MOD4.0(IUA) calculates the number of required code runs given the desired percentile and confidence level, performs the sampling process for the

  4. Uncertainty analysis of the 35% reactor inlet header break in a CANDU 6 reactor using RELAP/SCDAPSIM/MOD4.0 with integrated uncertainty analysis option

    International Nuclear Information System (INIS)

    Dupleac, D.; Perez, M.; Reventos, F.; Allison, C.

    2011-01-01

    The RELAP/SCDAPSIM/MOD4.0 code, designed to predict the behavior of reactor systems during normal and accident conditions, is being developed as part of an international nuclear technology Software Development and Training Program (SDTP). RELAP/SCDAPSIM/MOD4.0, which is the first version of RELAP5 completely rewritten to FORTRAN 90/95/2000 standards, uses the publicly available RELAP5 and SCDAP models in combination with (a) advanced programming and numerical techniques, (b) advanced SDTP-member-developed models for LWR, HWR, and research reactor analysis, and (c) a variety of other member-developed computational packages. One such computational package is an integrated uncertainty analysis (IUA) package being developed jointly by the Technical University of Catalonia (UPC) and Innovative Systems Software (ISS). RELAP/SCDAPSIM/MOD4.0(IUA) follows the input-propagation approach using probability distribution functions to define the uncertainty of the input parameters. The main steps for this type of methodologies, often referred as to statistical approaches or Wilks’ methods, are the ones that follow: 1. Selection of the plant; 2. Selection of the scenario; 3. Selection of the safety criteria; 4. Identification and ranking of the relevant phenomena based on the safety criteria; 5. Selection of the appropriate code parameters to represent those phenomena; 6. Association of uncertainty by means of Probability Distribution Functions (PDFs) for each selected parameter; 7. Random sampling of the selected parameters according to its PDF and performing multiple computer runs to obtain uncertainty bands with a certain percentile and confidence level; 8. Processing the results of the multiple computer runs to estimate the uncertainty bands for the computed quantities associated with the selected safety criteria. RELAP/SCDAPSIM/MOD4.0(IUA) calculates the number of required code runs given the desired percentile and confidence level, performs the sampling process for the

  5. County-Level Climate Uncertainty for Risk Assessments: Volume 25 Appendix X - Forecast Sea Ice Age.

    Energy Technology Data Exchange (ETDEWEB)

    Backus, George A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Lowry, Thomas Stephen [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Jones, Shannon M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Walker, La Tonya Nicole [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Roberts, Barry L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Malczynski, Leonard A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-05-01

    This report uses the CMIP5 series of climate model simulations to produce country- level uncertainty distributions for use in socioeconomic risk assessments of climate change impacts. It provides appropriate probability distributions, by month, for 169 countries and autonomous-areas on temperature, precipitation, maximum temperature, maximum wind speed, humidity, runoff, soil moisture and evaporation for the historical period (1976-2005), and for decadal time periods to 2100. It also provides historical and future distributions for the Arctic region on ice concentration, ice thickness, age of ice, and ice ridging in 15-degree longitude arc segments from the Arctic Circle to 80 degrees latitude, plus two polar semicircular regions from 80 to 90 degrees latitude. The uncertainty is meant to describe the lack of knowledge rather than imprecision in the physical simulation because the emphasis is on unfalsified risk and its use to determine potential socioeconomic impacts. The full report is contained in 27 volumes.

  6. County-Level Climate Uncertainty for Risk Assessments: Volume 26 Appendix Y - Historical Ridging Rate.

    Energy Technology Data Exchange (ETDEWEB)

    Backus, George A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Lowry, Thomas Stephen [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Jones, Shannon M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Walker, La Tonya Nicole [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Roberts, Barry L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Malczynski, Leonard A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-05-01

    This report uses the CMIP5 series of climate model simulations to produce country- level uncertainty distributions for use in socioeconomic risk assessments of climate change impacts. It provides appropriate probability distributions, by month, for 169 countries and autonomous-areas on temperature, precipitation, maximum temperature, maximum wind speed, humidity, runoff, soil moisture and evaporation for the historical period (1976-2005), and for decadal time periods to 2100. It also provides historical and future distributions for the Arctic region on ice concentration, ice thickness, age of ice, and ice ridging in 15-degree longitude arc segments from the Arctic Circle to 80 degrees latitude, plus two polar semicircular regions from 80 to 90 degrees latitude. The uncertainty is meant to describe the lack of knowledge rather than imprecision in the physical simulation because the emphasis is on unfalsified risk and its use to determine potential socioeconomic impacts. The full report is contained in 27 volumes.

  7. County-Level Climate Uncertainty for Risk Assessments: Volume 23 Appendix V - Forecast Sea Ice Thickness

    Energy Technology Data Exchange (ETDEWEB)

    Backus, George A.; Lowry, Thomas Stephen; Jones, Shannon M; Walker, La Tonya Nicole; Roberts, Barry L; Malczynski, Leonard A.

    2017-04-01

    This report uses the CMIP5 series of climate model simulations to produce country- level uncertainty distributions for use in socioeconomic risk assessments of climate change impacts. It provides appropriate probability distributions, by month, for 169 countries and autonomous-areas on temperature, precipitation, maximum temperature, maximum wind speed, humidity, runoff, soil moisture and evaporation for the historical period (1976-2005), and for decadal time periods to 2100. It also provides historical and future distributions for the Arctic region on ice concentration, ice thickness, age of ice, and ice ridging in 15-degree longitude arc segments from the Arctic Circle to 80 degrees latitude, plus two polar semicircular regions from 80 to 90 degrees latitude. The uncertainty is meant to describe the lack of knowledge rather than imprecision in the physical simulation because the emphasis is on unfalsified risk and its use to determine potential socioeconomic impacts. The full report is contained in 27 volumes.

  8. County-Level Climate Uncertainty for Risk Assessments: Volume 27 Appendix Z - Forecast Ridging Rate.

    Energy Technology Data Exchange (ETDEWEB)

    Backus, George A.; Lowry, Thomas Stephen; Jones, Shannon M; Walker, La Tonya Nicole; Roberts, Barry L; Malczynski, Leonard A.

    2017-06-01

    This report uses the CMIP5 series of climate model simulations to produce country- level uncertainty distributions for use in socioeconomic risk assessments of climate change impacts. It provides appropriate probability distributions, by month, for 169 countries and autonomous-areas on temperature, precipitation, maximum temperature, maximum wind speed, humidity, runoff, soil moisture and evaporation for the historical period (1976-2005), and for decadal time periods to 2100. It also provides historical and future distributions for the Arctic region on ice concentration, ice thickness, age of ice, and ice ridging in 15-degree longitude arc segments from the Arctic Circle to 80 degrees latitude, plus two polar semicircular regions from 80 to 90 degrees latitude. The uncertainty is meant to describe the lack of knowledge rather than imprecision in the physical simulation because the emphasis is on unfalsified risk and its use to determine potential socioeconomic impacts. The full report is contained in 27 volumes.

  9. County-Level Climate Uncertainty for Risk Assessments: Volume 24 Appendix W - Historical Sea Ice Age.

    Energy Technology Data Exchange (ETDEWEB)

    Backus, George A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Lowry, Thomas Stephen [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Jones, Shannon M [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Walker, La Tonya Nicole [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Roberts, Barry L [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Malczynski, Leonard A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-05-01

    This report uses the CMIP5 series of climate model simulations to produce country- level uncertainty distributions for use in socioeconomic risk assessments of climate change impacts. It provides appropriate probability distributions, by month, for 169 countries and autonomous-areas on temperature, precipitation, maximum temperature, maximum wind speed, humidity, runoff, soil moisture and evaporation for the historical period (1976-2005), and for decadal time periods to 2100. It also provides historical and future distributions for the Arctic region on ice concentration, ice thickness, age of ice, and ice ridging in 15-degree longitude arc segments from the Arctic Circle to 80 degrees latitude, plus two polar semicircular regions from 80 to 90 degrees latitude. The uncertainty is meant to describe the lack of knowledge rather than imprecision in the physical simulation because the emphasis is on unfalsified risk and its use to determine potential socioeconomic impacts. The full report is contained in 27 volumes.

  10. 'In-between' and other reasonable ways to deal with risk and uncertainty: A review article.

    Science.gov (United States)

    Zinn, Jens O

    2016-11-16

    How people deal with risk and uncertainty has fuelled public and academic debate in recent decades. Researchers have shown that common distinctions between rational and 'irrational' strategies underestimate the complexity of how people approach an uncertain future. I suggested in 2008 that strategies in-between do not follow standards of instrumental rationality nor they are 'irrational' but follow their own logic which works well under particular circumstances. Strategies such as trust, intuition and emotion are an important part of the mix when people deal with risk and uncertainty. In this article, I develop my original argument. It explores in-between strategies to deal with possible undesired outcomes of decisions. I examine 'non-rational strategies' and in particular the notions of active, passive and reflexive hope. Furthermore, I argue that my original typology should be seen as a triangular of reasonable strategies which work well under specific circumstances. Finally, I highlight a number of different ways in which these strategies combine.

  11. County-Level Climate Uncertainty for Risk Assessments: Volume 17 Appendix P - Forecast Soil Moisture

    Energy Technology Data Exchange (ETDEWEB)

    Backus, George A.; Lowry, Thomas Stephen; Jones, Shannon M; Walker, La Tonya Nicole; Roberts, Barry L; Malczynski, Leonard A.

    2017-04-01

    This report uses the CMIP5 series of climate model simulations to produce country- level uncertainty distributions for use in socioeconomic risk assessments of climate change impacts. It provides appropriate probability distributions, by month, for 169 countries and autonomous-areas on temperature, precipitation, maximum temperature, maximum wind speed, humidity, runoff, soil moisture and evaporation for the historical period (1976-2005), and for decadal time periods to 2100. It also provides historical and future distributions for the Arctic region on ice concentration, ice thickness, age of ice, and ice ridging in 15-degree longitude arc segments from the Arctic Circle to 80 degrees latitude, plus two polar semicircular regions from 80 to 90 degrees latitude. The uncertainty is meant to describe the lack of knowledge rather than imprecision in the physical simulation because the emphasis is on unfalsified risk and its use to determine potential socioeconomic impacts. The full report is contained in 27 volumes.

  12. The shape of uncertainty: underwriting decisions in the face of catastrophic risk

    International Nuclear Information System (INIS)

    Keykhah, M.

    1998-01-01

    This paper will explore how insurance and re-insurance underwriters price catastrophe risk from natural perils. It will first describe the theoretical nature of pricing risk, and outline studies of underwriting that propose analyzing decision making from a more behavioral than rational choice perspective. The paper then argues that in order to provide the appropriate context for probability (which is the focus of the studies on decision making under uncertainty), it may be helpful to look at the nature of choice within a market and organizational context. Moreover, the nature of probability itself is explored with a review to construct a broader analysis. Finally, it will be argued that the causal framework of the underwriter, in addition to inductive reasoning, provides a shape to uncertainty. (author)

  13. County-Level Climate Uncertainty for Risk Assessments: Volume 15 Appendix N - Forecast Surface Runoff.

    Energy Technology Data Exchange (ETDEWEB)

    Backus, George A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Lowry, Thomas Stephen [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Jones, Shannon M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Walker, La Tonya Nicole [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Roberts, Barry L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Malczynski, Leonard A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-05-01

    This report uses the CMIP5 series of climate model simulations to produce country- level uncertainty distributions for use in socioeconomic risk assessments of climate change impacts. It provides appropriate probability distributions, by month, for 169 countries and autonomous-areas on temperature, precipitation, maximum temperature, maximum wind speed, humidity, runoff, soil moisture and evaporation for the historical period (1976-2005), and for decadal time periods to 2100. It also provides historical and future distributions for the Arctic region on ice concentration, ice thickness, age of ice, and ice ridging in 15-degree longitude arc segments from the Arctic Circle to 80 degrees latitude, plus two polar semicircular regions from 80 to 90 degrees latitude. The uncertainty is meant to describe the lack of knowledge rather than imprecision in the physical simulation because the emphasis is on unfalsified risk and its use to determine potential socioeconomic impacts. The full report is contained in 27 volumes.

  14. County-Level Climate Uncertainty for Risk Assessments: Volume 10 Appendix I - Historical Evaporation.

    Energy Technology Data Exchange (ETDEWEB)

    Backus, George A.; Lowry, Thomas Stephen; Jones, Shannon M; Walker, La Tonya Nicole; Roberts, Barry L; Malczynski, Leonard A.

    2017-06-01

    This report uses the CMIP5 series of climate model simulations to produce country- level uncertainty distributions for use in socioeconomic risk assessments of climate change impacts. It provides appropriate probability distributions, by month, for 169 countries and autonomous-areas on temperature, precipitation, maximum temperature, maximum wind speed, humidity, runoff, soil moisture and evaporation for the historical period (1976-2005), and for decadal time periods to 2100. It also provides historical and future distributions for the Arctic region on ice concentration, ice thickness, age of ice, and ice ridging in 15-degree longitude arc segments from the Arctic Circle to 80 degrees latitude, plus two polar semicircular regions from 80 to 90 degrees latitude. The uncertainty is meant to describe the lack of knowledge rather than imprecision in the physical simulation because the emphasis is on unfalsified risk and its use to determine potential socioeconomic impacts. The full report is contained in 27 volumes.

  15. County-Level Climate Uncertainty for Risk Assessments: Volume 14 Appendix M - Historical Surface Runoff.

    Energy Technology Data Exchange (ETDEWEB)

    Backus, George A.; Lowry, Thomas Stephen; Jones, Shannon M; Walker, La Tonya Nicole; Roberts, Barry L; Malczynski, Leonard A.

    2017-06-01

    This report uses the CMIP5 series of climate model simulations to produce country- level uncertainty distributions for use in socioeconomic risk assessments of climate change impacts. It provides appropriate probability distributions, by month, for 169 countries and autonomous-areas on temperature, precipitation, maximum temperature, maximum wind speed, humidity, runoff, soil moisture and evaporation for the historical period (1976-2005), and for decadal time periods to 2100. It also provides historical and future distributions for the Arctic region on ice concentration, ice thickness, age of ice, and ice ridging in 15-degree longitude arc segments from the Arctic Circle to 80 degrees latitude, plus two polar semicircular regions from 80 to 90 degrees latitude. The uncertainty is meant to describe the lack of knowledge rather than imprecision in the physical simulation because the emphasis is on unfalsified risk and its use to determine potential socioeconomic impacts. The full report is contained in 27 volumes.

  16. County-Level Climate Uncertainty for Risk Assessments: Volume 8 Appendix G - Historical Precipitation.

    Energy Technology Data Exchange (ETDEWEB)

    Backus, George A.; Lowry, Thomas Stephen; Jones, Shannon M; Walker, La Tonya Nicole; Roberts, Barry L; Malczynski, Leonard A.

    2017-06-01

    This report uses the CMIP5 series of climate model simulations to produce country- level uncertainty distributions for use in socioeconomic risk assessments of climate change impacts. It provides appropriate probability distributions, by month, for 169 countries and autonomous-areas on temperature, precipitation, maximum temperature, maximum wind speed, humidity, runoff, soil moisture and evaporation for the historical period (1976-2005), and for decadal time periods to 2100. It also provides historical and future distributions for the Arctic region on ice concentration, ice thickness, age of ice, and ice ridging in 15-degree longitude arc segments from the Arctic Circle to 80 degrees latitude, plus two polar semicircular regions from 80 to 90 degrees latitude. The uncertainty is meant to describe the lack of knowledge rather than imprecision in the physical simulation because the emphasis is on unfalsified risk and its use to determine potential socioeconomic impacts. The full report is contained in 27 volumes.

  17. County-Level Climate Uncertainty for Risk Assessments: Volume 12 Appendix K - Historical Rel. Humidity.

    Energy Technology Data Exchange (ETDEWEB)

    Backus, George A.; Lowry, Thomas Stephen; Jones, Shannon M; Walker, La Tonya Nicole; Roberts, Barry L; Malczynski, Leonard A.

    2017-06-01

    This report uses the CMIP5 series of climate model simulations to produce country- level uncertainty distributions for use in socioeconomic risk assessments of climate change impacts. It provides appropriate probability distributions, by month, for 169 countries and autonomous-areas on temperature, precipitation, maximum temperature, maximum wind speed, humidity, runoff, soil moisture and evaporation for the historical period (1976-2005), and for decadal time periods to 2100. It also provides historical and future distributions for the Arctic region on ice concentration, ice thickness, age of ice, and ice ridging in 15-degree longitude arc segments from the Arctic Circle to 80 degrees latitude, plus two polar semicircular regions from 80 to 90 degrees latitude. The uncertainty is meant to describe the lack of knowledge rather than imprecision in the physical simulation because the emphasis is on unfalsified risk and its use to determine potential socioeconomic impacts. The full report is contained in 27 volumes.

  18. County-Level Climate Uncertainty for Risk Assessments: Volume 16 Appendix O - Historical Soil Moisture.

    Energy Technology Data Exchange (ETDEWEB)

    Backus, George A.; Lowry, Thomas Stephen; Jones, Shannon M; Walker, La Tonya Nicole; Roberts, Barry L; Malczynski, Leonard A.

    2017-06-01

    This report uses the CMIP5 series of climate model simulations to produce country- level uncertainty distributions for use in socioeconomic risk assessments of climate change impacts. It provides appropriate probability distributions, by month, for 169 countries and autonomous-areas on temperature, precipitation, maximum temperature, maximum wind speed, humidity, runoff, soil moisture and evaporation for the historical period (1976-2005), and for decadal time periods to 2100. It also provides historical and future distributions for the Arctic region on ice concentration, ice thickness, age of ice, and ice ridging in 15-degree longitude arc segments from the Arctic Circle to 80 degrees latitude, plus two polar semicircular regions from 80 to 90 degrees latitude. The uncertainty is meant to describe the lack of knowledge rather than imprecision in the physical simulation because the emphasis is on unfalsified risk and its use to determine potential socioeconomic impacts. The full report is contained in 27 volumes.

  19. County-Level Climate Uncertainty for Risk Assessments: Volume 22 Appendix U - Historical Sea Ice Thickness

    Energy Technology Data Exchange (ETDEWEB)

    Backus, George A.; Lowry, Thomas Stephen; Jones, Shannon M; Walker, La Tonya Nicole; Roberts, Barry L; Malczynski, Leonard A.

    2017-06-01

    This report uses the CMIP5 series of climate model simulations to produce country- level uncertainty distributions for use in socioeconomic risk assessments of climate change impacts. It provides appropriate probability distributions, by month, for 169 countries and autonomous-areas on temperature, precipitation, maximum temperature, maximum wind speed, humidity, runoff, soil moisture and evaporation for the historical period (1976-2005), and for decadal time periods to 2100. It also provides historical and future distributions for the Arctic region on ice concentration, ice thickness, age of ice, and ice ridging in 15-degree longitude arc segments from the Arctic Circle to 80 degrees latitude, plus two polar semicircular regions from 80 to 90 degrees latitude. The uncertainty is meant to describe the lack of knowledge rather than imprecision in the physical simulation because the emphasis is on unfalsified risk and its use to determine potential socioeconomic impacts. The full report is contained in 27 volumes.

  20. Blockchain to Rule the Waves - Nascent Design Principles for Reducing Risk and Uncertainty in Decentralized Environments

    DEFF Research Database (Denmark)

    Nærland, Kristoffer; Müller-Bloch, Christoph; Beck, Roman

    2017-01-01

    Many decentralized, inter-organizational environments such as supply chains are characterized by high transactional uncertainty and risk. At the same time, blockchain technology promises to mitigate these issues by introducing certainty into economic transactions. This paper discusses the findings...... of a Design Science Research project involving the construction and evaluation of an information technology artifact in collaboration with Maersk, a leading international shipping company, where central documents in shipping, such as the Bill of Lading, are turned into a smart contract on blockchain. Based...... on our insights from the project, we provide first evidence for preliminary design principles for applications that aim to mitigate the transactional risk and uncertainty in decentralized environments using blockchain. Both the artifact and the first evidence for emerging design principles are novel...

  1. A comparison of integrated safety analysis and probabilistic risk assessment

    International Nuclear Information System (INIS)

    Damon, Dennis R.; Mattern, Kevin S.

    2013-01-01

    The U.S. Nuclear Regulatory Commission conducted a comparison of two standard tools for risk informing the regulatory process, namely, the Probabilistic Risk Assessment (PRA) and the Integrated Safety Analysis (ISA). PRA is a calculation of risk metrics, such as Large Early Release Frequency (LERF), and has been used to assess the safety of all commercial power reactors. ISA is an analysis required for fuel cycle facilities (FCFs) licensed to possess potentially critical quantities of special nuclear material. A PRA is usually more detailed and uses more refined models and data than an ISA, in order to obtain reasonable quantitative estimates of risk. PRA is considered fully quantitative, while most ISAs are typically only partially quantitative. The extension of PRA methodology to augment or supplant ISAs in FCFs has long been considered. However, fuel cycle facilities have a wide variety of possible accident consequences, rather than a few surrogates like LERF or core damage as used for reactors. It has been noted that a fuel cycle PRA could be used to better focus attention on the most risk-significant structures, systems, components, and operator actions. ISA and PRA both identify accident sequences; however, their treatment is quite different. ISA's identify accidents that lead to high or intermediate consequences, as defined in 10 Code of Federal Regulations (CFR) 70, and develop a set of Items Relied on For Safety (IROFS) to assure adherence to performance criteria. PRAs identify potential accident scenarios and estimate their frequency and consequences to obtain risk metrics. It is acceptable for ISAs to provide bounding evaluations of accident consequences and likelihoods in order to establish acceptable safety; but PRA applications usually require a reasonable quantitative estimate, and often obtain metrics of uncertainty. This paper provides the background, features, and methodology associated with the PRA and ISA. The differences between the

  2. Uncertainty Analysis of A Flood Risk Mapping Procedure Applied In Urban Areas

    Science.gov (United States)

    Krause, J.; Uhrich, S.; Bormann, H.; Diekkrüger, B.

    In the framework of IRMA-Sponge program the presented study was part of the joint research project FRHYMAP (flood risk and hydrological mapping). A simple con- ceptual flooding model (FLOODMAP) has been developed to simulate flooded areas besides rivers within cities. FLOODMAP requires a minimum of input data (digital el- evation model (DEM), river line, water level plain) and parameters and calculates the flood extent as well as the spatial distribution of flood depths. of course the simulated model results are affected by errors and uncertainties. Possible sources of uncertain- ties are the model structure, model parameters and input data. Thus after the model validation (comparison of simulated water to observed extent, taken from airborne pictures) the uncertainty of the essential input data set (digital elevation model) was analysed. Monte Carlo simulations were performed to assess the effect of uncertain- ties concerning the statistics of DEM quality and to derive flooding probabilities from the set of simulations. The questions concerning a minimum resolution of a DEM re- quired for flood simulation and concerning the best aggregation procedure of a given DEM was answered by comparing the results obtained using all available standard GIS aggregation procedures. Seven different aggregation procedures were applied to high resolution DEMs (1-2m) in three cities (Bonn, Cologne, Luxembourg). Basing on this analysis the effect of 'uncertain' DEM data was estimated and compared with other sources of uncertainties. Especially socio-economic information and monetary transfer functions required for a damage risk analysis show a high uncertainty. There- fore this study helps to analyse the weak points of the flood risk and damage risk assessment procedure.

  3. Sunway Medical Laboratory Quality Control Plans Based on Six Sigma, Risk Management and Uncertainty.

    Science.gov (United States)

    Jairaman, Jamuna; Sakiman, Zarinah; Li, Lee Suan

    2017-03-01

    Sunway Medical Centre (SunMed) implemented Six Sigma, measurement uncertainty, and risk management after the CLSI EP23 Individualized Quality Control Plan approach. Despite the differences in all three approaches, each implementation was beneficial to the laboratory, and none was in conflict with another approach. A synthesis of these approaches, built on a solid foundation of quality control planning, can help build a strong quality management system for the entire laboratory. Copyright © 2016 Elsevier Inc. All rights reserved.

  4. Blockchain to Rule the Waves - Nascent Design Principles for Reducing Risk and Uncertainty in Decentralized Environments

    OpenAIRE

    Nærland, Kristoffer; Müller-Bloch, Christoph; Beck, Roman; Palmund, Søren

    2017-01-01

    Many decentralized, inter-organizational environments such as supply chains are characterized by high transactional uncertainty and risk. At the same time, blockchain technology promises to mitigate these issues by introducing certainty into economic transactions. This paper discusses the findings of a Design Science Research project involving the construction and evaluation of an information technology artifact in collaboration with Maersk, a leading international shipping company, where cen...

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

    Science.gov (United States)

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

    2017-10-01

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

  6. Climate uncertainty and implications for U.S. state-level risk assessment through 2050.

    Energy Technology Data Exchange (ETDEWEB)

    Loose, Verne W.; Lowry, Thomas Stephen; Malczynski, Leonard A.; Tidwell, Vincent Carroll; Stamber, Kevin Louis; Kelic, Andjelka; Backus, George A.; Warren, Drake E.; Zagonel, Aldo A.; Ehlen, Mark Andrew; Klise, Geoffrey T.; Vargas, Vanessa N.

    2009-10-01

    Decisions for climate policy will need to take place in advance of climate science resolving all relevant uncertainties. Further, if the concern of policy is to reduce risk, then the best-estimate of climate change impacts may not be so important as the currently understood uncertainty associated with realizable conditions having high consequence. This study focuses on one of the most uncertain aspects of future climate change - precipitation - to understand the implications of uncertainty on risk and the near-term justification for interventions to mitigate the course of climate change. We show that the mean risk of damage to the economy from climate change, at the national level, is on the order of one trillion dollars over the next 40 years, with employment impacts of nearly 7 million labor-years. At a 1% exceedance-probability, the impact is over twice the mean-risk value. Impacts at the level of individual U.S. states are then typically in the multiple tens of billions dollar range with employment losses exceeding hundreds of thousands of labor-years. We used results of the Intergovernmental Panel on Climate Change's (IPCC) Fourth Assessment Report 4 (AR4) climate-model ensemble as the referent for climate uncertainty over the next 40 years, mapped the simulated weather hydrologically to the county level for determining the physical consequence to economic activity at the state level, and then performed a detailed, seventy-industry, analysis of economic impact among the interacting lower-48 states. We determined industry GDP and employment impacts at the state level, as well as interstate population migration, effect on personal income, and the consequences for the U.S. trade balance.

  7. Cognitive Processes in Decisions Under Risk Are Not the Same As in Decisions Under Uncertainty

    Directory of Open Access Journals (Sweden)

    Kirsten G Volz

    2012-07-01

    Full Text Available We deal with risk versus uncertainty, a distinction that is of fundamental importance for cognitive neuroscience yet largely neglected. In a world of risk (small world, all alternatives, consequences, and probabilities are known. In uncertain (large worlds, some of this information is unknown or unknowable. Most of cognitive neuroscience studies exclusively study the neural correlates for decisions under risk (e.g., lotteries, with the tacit implication that understanding these would lead to an understanding of decision making in general. First, we show that normative strategies for decisions under risk do not generalize to uncertain worlds, where simple heuristics are often the more accurate strategies. Second, we argue that the cognitive processes for making decisions in a world of risk are not the same as those for dealing with uncertainty. Because situations with known risks are the exception rather than the rule in human evolution, it is unlikely that our brains are adapted to them. We therefore suggest a paradigm shift towards studying decision processes in uncertain worlds and provide first examples.

  8. Economic policy uncertainty, credit risks and banks lending decisions: Evidence from Chinese commercial banks

    Institute of Scientific and Technical Information of China (English)

    Qinwei Chi; Wenjing Li

    2017-01-01

    Using data for Chinese commercial banks from 2000 to 2014, this paper examines the effects of economic policy uncertainty(EPU) on banks’ credit risks and lending decisions. The results reveal significantly positive connections among EPU and non-performing loan ratios, loan concentrations and the normal loan migration rate. This indicates that EPU increases banks’ credit risks and negatively influences loan size, especially for joint-equity banks. Given the increasing credit risks generated by EPU, banks can improve operational performance by reducing loan sizes. Further research indicates that the effects of EPU on banks’ credit risks and lending decisions are moderated by the marketization level, with financial depth moderating the effect on banks’ credit risks and strengthening it on lending decisions.

  9. Risk, uncertainty and prophet: The psychological insights of Frank H. Knight

    Directory of Open Access Journals (Sweden)

    Tim Rakow

    2010-10-01

    Full Text Available Economist Frank H. Knight (1885--1972 is commonly credited with defining the distinction between decisions under ``risk'' (known chance and decisions under ``uncertainty'' (unmeasurable probability in his 1921 book Risk, Uncertainty and Profit. A closer reading of Knight (1921 reveals a host of psychological insights beyond this risk-uncertainty distinction, many of which foreshadow revolutionary advances in psychological decision theory from the latter half of the 20th century. Knight's description of economic decision making shared much with Simon's (1955, 1956 notion of bounded rationality, whereby choice behavior is regulated by cognitive and environmental constraints. Knight described features of risky choice that were to become key components of prospect theory (Kahneman and Tversky, 1979: the reference dependent valuation of outcomes, and the non-linear weighting of probabilities. Knight also discussed several biases in human decision making, and pointed to two systems of reasoning: one quick, intuitive but error prone, and a slower, more deliberate, rule-based system. A discussion of Knight's potential contribution to psychological decision theory emphasises the importance of a historical perspective on theory development, and the potential value of sourcing ideas from other disciplines or from earlier periods of time.

  10. Health risks of climate change: An assessment of uncertainties and its implications for adaptation policies

    Science.gov (United States)

    2012-01-01

    Background Projections of health risks of climate change are surrounded with uncertainties in knowledge. Understanding of these uncertainties will help the selection of appropriate adaptation policies. Methods We made an inventory of conceivable health impacts of climate change, explored the type and level of uncertainty for each impact, and discussed its implications for adaptation policy. A questionnaire-based expert elicitation was performed using an ordinal scoring scale. Experts were asked to indicate the level of precision with which health risks can be estimated, given the present state of knowledge. We assessed the individual scores, the expertise-weighted descriptive statistics, and the argumentation given for each score. Suggestions were made for how dealing with uncertainties could be taken into account in climate change adaptation policy strategies. Results The results showed that the direction of change could be indicated for most anticipated health effects. For several potential effects, too little knowledge exists to indicate whether any impact will occur, or whether the impact will be positive or negative. For several effects, rough ‘order-of-magnitude’ estimates were considered possible. Factors limiting health impact quantification include: lack of data, multi-causality, unknown impacts considering a high-quality health system, complex cause-effect relations leading to multi-directional impacts, possible changes of present-day response-relations, and difficulties in predicting local climate impacts. Participants considered heat-related mortality and non-endemic vector-borne diseases particularly relevant for climate change adaptation. Conclusions For possible climate related health impacts characterised by ignorance, adaptation policies that focus on enhancing the health system’s and society’s capability of dealing with possible future changes, uncertainties and surprises (e.g. through resilience, flexibility, and adaptive capacity) are

  11. Reconciling uncertainties in integrated science and policy models: Applications to global climate change

    Energy Technology Data Exchange (ETDEWEB)

    Kandlikar, Milind [Carnegie Mellon Univ., Pittsburgh, PA (United States)

    1994-12-01

    In this thesis tools of data reconciliation are used to integrate available information into scientific and policy models of greenhouse gases. The role of uncertainties in scientific and policy models of global climate change is examined, and implications for global change policy are drawn. Methane is the second most important greenhouse gas. Global sources and sinks of methane have significant uncertainties. A chance constrained methodology was developed and used to perform inversions on the global methane cycle. Budgets of methane that are consistent with source fluxes, isotopic and ice core measurements were determined. While it is not possible to come up with a single budget for CH{sub 4}, performing the calculation with a number of sets of assumed priors suggests a convergence in the allowed range for sources. In some cases -- wetlands (70-130 Tg/yr), rice paddies (60-125 Tg/yr) a significant reduction in the uncertainty of the source estimate is achieved. Our results compare favorably with the most recent measurements of flux estimates. For comparison, a similar analysis using bayes monte carlo simulation was performed. The question of the missing sink for carbon remains unresolved. Two analyses that attempt to quantify the missing sink were performed. First, a steady state analysis of the carbon cycle was used to determine the pre-industrial inter-hemispheric carbon concentration gradient. Second, a full blown dynamic inversion of the carbon cycle was performed. An advection diffusion ocean model with surface chemistry, coupled to box models of the atmosphere and the biosphere was inverted to fit available measurements of {sup 12}C and {sup 14}C carbon isotopes using Differential-Algebraic Optimization. The model effectively suggests that the {open_quotes}missing{close_quotes} sink for carbon is hiding in the biosphere. Scenario dependent trace gas indices were calculated for CH{sub 4}, N{sub 2}O, HCFC-22.

  12. Risk regulation in environment, health and safety : Decision in the face of uncertainty

    Energy Technology Data Exchange (ETDEWEB)

    Ettlinger, L A [The Oxford Group, Baltimore, MD (United States)

    1999-12-01

    Regulations that use or refer to the concept of 'risk' are becoming more popular with both the U.S. Congress and Government agencies -- and are often being challenged in the courts. Proponents of stronger regulation suggest that there are significant threats to life and health that receive little or no attention from both elected officials and regulators, whereas advocates of less intensive government intervention point to regulations that impose high costs with little or no benefit. Usually, both the costs and the benefits are highly uncertain. This paper assumes for the purpose of argument that both proponents and opponents can find many cases where their respective arguments have merit. We also assume that both criticisms of the status quo have a large constituency within the public. If these assumption are valid, then a policy problem is created whereby decision makers are being asked, in the face of significant uncertainty, when to regulate, and at what level of specificity to regulate. The purposes of this paper are to offer some fresh ideas about why these problems arise, shed some light on decision making within the Congress, the regulatory agencies and the courts, and offer some practical steps that could be taken to reform the present system of regulation. Our central observation is that disputes arise as to the efficacy of risk regulations (in the face of uncertainty) because of the difficulties citizens face in determining whether either those who cause risks or those who are responsible for mitigating them are acting in the citizen's best interest. These regulations contain issues which typically deal with subjects containing substantial, unresolvable technical and scientific uncertainties. Because of this inherent uncertainty, the relationships between citizens and regulators, with elected officials in the middle, becomes an especially difficult form of agent relationship. We conclude that the problems associated with this agent relationship are

  13. Risk regulation in environment, health and safety : Decision in the face of uncertainty

    Energy Technology Data Exchange (ETDEWEB)

    Ettlinger, L.A. [The Oxford Group, Baltimore, MD (United States)

    1999-12-01

    Regulations that use or refer to the concept of 'risk' are becoming more popular with both the U.S. Congress and Government agencies -- and are often being challenged in the courts. Proponents of stronger regulation suggest that there are significant threats to life and health that receive little or no attention from both elected officials and regulators, whereas advocates of less intensive government intervention point to regulations that impose high costs with little or no benefit. Usually, both the costs and the benefits are highly uncertain. This paper assumes for the purpose of argument that both proponents and opponents can find many cases where their respective arguments have merit. We also assume that both criticisms of the status quo have a large constituency within the public. If these assumption are valid, then a policy problem is created whereby decision makers are being asked, in the face of significant uncertainty, when to regulate, and at what level of specificity to regulate. The purposes of this paper are to offer some fresh ideas about why these problems arise, shed some light on decision making within the Congress, the regulatory agencies and the courts, and offer some practical steps that could be taken to reform the present system of regulation. Our central observation is that disputes arise as to the efficacy of risk regulations (in the face of uncertainty) because of the difficulties citizens face in determining whether either those who cause risks or those who are responsible for mitigating them are acting in the citizen's best interest. These regulations contain issues which typically deal with subjects containing substantial, unresolvable technical and scientific uncertainties. Because of this inherent uncertainty, the relationships between citizens and regulators, with elected officials in the middle, becomes an especially difficult form of agent relationship. We conclude that the problems associated with this agent

  14. Risk regulation in environment, health and safety : Decision in the face of uncertainty

    International Nuclear Information System (INIS)

    Ettlinger, L.A.

    1999-01-01

    Regulations that use or refer to the concept of 'risk' are becoming more popular with both the U.S. Congress and Government agencies -- and are often being challenged in the courts. Proponents of stronger regulation suggest that there are significant threats to life and health that receive little or no attention from both elected officials and regulators, whereas advocates of less intensive government intervention point to regulations that impose high costs with little or no benefit. Usually, both the costs and the benefits are highly uncertain. This paper assumes for the purpose of argument that both proponents and opponents can find many cases where their respective arguments have merit. We also assume that both criticisms of the status quo have a large constituency within the public. If these assumption are valid, then a policy problem is created whereby decision makers are being asked, in the face of significant uncertainty, when to regulate, and at what level of specificity to regulate. The purposes of this paper are to offer some fresh ideas about why these problems arise, shed some light on decision making within the Congress, the regulatory agencies and the courts, and offer some practical steps that could be taken to reform the present system of regulation. Our central observation is that disputes arise as to the efficacy of risk regulations (in the face of uncertainty) because of the difficulties citizens face in determining whether either those who cause risks or those who are responsible for mitigating them are acting in the citizen's best interest. These regulations contain issues which typically deal with subjects containing substantial, unresolvable technical and scientific uncertainties. Because of this inherent uncertainty, the relationships between citizens and regulators, with elected officials in the middle, becomes an especially difficult form of agent relationship. We conclude that the problems associated with this agent relationship are

  15. Disruptive event uncertainties in a perturbation approach to nuclear waste repository risk analysis

    Energy Technology Data Exchange (ETDEWEB)

    Harvey, T.F.

    1980-09-01

    A methodology is developed for incorporating a full range of the principal forecasting uncertainties into a risk analysis of a nuclear waste repository. The result of this methodology is a set of risk curves similar to those used by Rasmussen in WASH-1400. The set of curves is partially derived from a perturbation approach to analyze potential disruptive event sequences. Such a scheme could be useful in truncating the number of disruptive event scenarios and providing guidance to those establishing data-base development priorities.

  16. Combination for differential and integral data: Sensitivity and uncertainty analysis of reactor performance parameters

    International Nuclear Information System (INIS)

    Marable, J.H.; de Saussure, G.; Weisbin, C.R.

    1982-01-01

    This chapter attempts to show how the various types of data presented and discussed in previous chapters can be combined and applied to the calculation of performance parameters of a reactor design model. Discusses derivation of least-squares adjustment; input data to the adjustment; the results of adjustment; and application to an LMFBR. Demonstrates that the least-squares formulae represent a logical, well-founded method for combining the results of integral and differential experiments. Includes calculational bias factors and their uncertainties. Concludes that the adjustment technique is a valuable tool, and that significant progress has been made with respect to its development and its applications. Recommends further work on the evaluation of covariance files, especially for calculational biases, and the inclusion of specific shielding factors as variables to be adjusted. The appendix features a calculation whose goal is to find the form of the projection operator which projects perpendicular to the calculational manifold

  17. Optimization under uncertainty of a biomass-integrated renewable energy microgrid with energy storage

    DEFF Research Database (Denmark)

    Zheng, Yingying; Jenkins, Bryan M.; Kornbluth, Kurt

    2018-01-01

    Deterministic constrained optimization and stochastic optimization approaches were used to evaluate uncertainties in biomass-integrated microgrids supplying both electricity and heat. An economic linear programming model with a sliding time window was developed to assess design and scheduling...... of biomass combined heat and power (BCHP) based microgrid systems. Other available technologies considered within the microgrid were small-scale wind turbines, photovoltaic modules (PV), producer gas storage, battery storage, thermal energy storage and heat-only boilers. As an illustrative example, a case...... study was examined for a conceptual utility grid-connected microgrid application in Davis, California. The results show that for the assumptions used, a BCHP/PV with battery storage combination is the most cost effective design based on the assumed energy load profile, local climate data, utility tariff...

  18. Integrated forward/reverse logistics network design under uncertainty with pricing for collection of used products

    DEFF Research Database (Denmark)

    Fattahi, Mohammad; Govindan, Kannan

    2017-01-01

    This paper addresses design and planning of an integrated forward/reverse logistics network over a planning horizon with multiple tactical periods. In the network, demand for new products and potential return of used products are stochastic. Furthermore, collection amounts of used products...... with different quality levels are assumed dependent on offered acquisition prices to customer zones. A uniform distribution function defines the expected price of each customer zone for one unit of each used product. Using two-stage stochastic programming, a mixed-integer linear programming model is proposed....... To cope with demand and potential return uncertainty, Latin Hypercube Sampling method is applied to generate fan of scenarios and then, backward scenario reduction technique is used to reduce the number of scenarios. Due to the problem complexity, a novel simulation-based simulated annealing algorithm...

  19. Accounting for uncertainty and risk in assessments of impacts for offshore oil and gas leasing proposals

    International Nuclear Information System (INIS)

    Wildermann, R.; Beittel, R.

    1993-01-01

    The Minerals Management Service (MMS) of the US Department of the Interior prepares an environmental impact statement (EIS) for each proposal to lease a portion of the Outer Continental Shelf (OCS) for oil and gas exploration and development. The nature, magnitude, and timing of the activities that would ultimately result from leasing are subject to wide speculation, primarily because of uncertainties about the locations and amounts of petroleum hydrocarbons that exist on most potential leases. These uncertainties create challenges in preparing EIS's that meet National Environmental Policy Act requirements and provide information useful to decision-makers. This paper examines the constraints that uncertainty places on the detail and reliability of assessments of impacts from potential OCS development. It further describes how the MMS accounts for uncertainty in developing reasonable scenarios of future events that can be evaluated in the EIS. A process for incorporating the risk of accidental oil spills into assessments of expected impacts is also presented. Finally, the paper demonstrates through examination of case studies how a balance can be achieved between the need for an EIS to present impacts in sufficient detail to allow a meaningful comparison of alternatives and the tendency to push the analysis beyond credible limits

  20. Knowledge management system for risk mitigation in supply chain uncertainty: case from automotive battery supply chain

    Science.gov (United States)

    Marie, I. A.; Sugiarto, D.; Surjasa, D.; Witonohadi, A.

    2018-01-01

    Automotive battery supply chain include battery manufacturer, sulphuric acid suppliers, polypropylene suppliers, lead suppliers, transportation service providers, warehouses, retailers and even customers. Due to the increasingly dynamic condition of the environment, supply chain actors were required to improve their ability to overcome various uncertainty issues in the environment. This paper aims to describe the process of designing a knowledge management system for risk mitigation in supply chain uncertainty. The design methodology began with the identification of the knowledge needed to solve the problems associated with uncertainty and analysis of system requirements. The design of the knowledge management system was described in the form of a data flow diagram. The results of the study indicated that key knowledge area that needs to be managed were the knowledge to maintain the stability of process in sulphuric acid process and knowledge to overcome the wastes in battery manufacturing process. The system was expected to be a media acquisition, dissemination and storage of knowledge associated with the uncertainty in the battery supply chain and increase the supply chain performance.

  1. Future bloom and blossom frost risk for Malus domestica considering climate model and impact model uncertainties.

    Science.gov (United States)

    Hoffmann, Holger; Rath, Thomas

    2013-01-01

    The future bloom and risk of blossom frosts for Malus domestica were projected using regional climate realizations and phenological ( = impact) models. As climate impact projections are susceptible to uncertainties of climate and impact models and model concatenation, the significant horizon of the climate impact signal was analyzed by applying 7 impact models, including two new developments, on 13 climate realizations of the IPCC emission scenario A1B. Advancement of phenophases and a decrease in blossom frost risk for Lower Saxony (Germany) for early and late ripeners was determined by six out of seven phenological models. Single model/single grid point time series of bloom showed significant trends by 2021-2050 compared to 1971-2000, whereas the joint signal of all climate and impact models did not stabilize until 2043. Regarding blossom frost risk, joint projection variability exceeded the projected signal. Thus, blossom frost risk cannot be stated to be lower by the end of the 21st century despite a negative trend. As a consequence it is however unlikely to increase. Uncertainty of temperature, blooming date and blossom frost risk projection reached a minimum at 2078-2087. The projected phenophases advanced by 5.5 d K(-1), showing partial compensation of delayed fulfillment of the winter chill requirement and faster completion of the following forcing phase in spring. Finally, phenological model performance was improved by considering the length of day.

  2. A scenario-based modeling approach for emergency evacuation management and risk analysis under multiple uncertainties

    Energy Technology Data Exchange (ETDEWEB)

    Lv, Y., E-mail: lvyying@hotmail.com [School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044 (China); Faculty of Engineering and Applied Science, University of Regina, Regina, Saskatchewan S4S 0A2 (Canada); Huang, G.H., E-mail: huang@iseis.org [Faculty of Engineering and Applied Science, University of Regina, Regina, Saskatchewan S4S 0A2 (Canada); Guo, L., E-mail: guoli8658@hotmail.com [Faculty of Engineering and Applied Science, University of Regina, Regina, Saskatchewan S4S 0A2 (Canada); Li, Y.P., E-mail: yongping.li@iseis.org [MOE Key Laboratory of Regional Energy and Environmental Systems Optimization, Resources and Environmental Research Academy, North China Electric Power University, Beijing 102206 (China); Dai, C., E-mail: daichao321@gmail.com [College of Environmental Sciences and Engineering, Peking University, Beijing 100871 (China); Wang, X.W., E-mail: wangxingwei0812@gamil.com [State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875 (China); Sun, W., E-mail: sunwei@iseis.org [Faculty of Engineering and Applied Science, University of Regina, Regina, Saskatchewan S4S 0A2 (Canada)

    2013-02-15

    Highlights: ► An interval-parameter joint-probabilistic integer programming method is developed. ► It is useful for nuclear emergency management practices under uncertainties. ► It can schedule optimal routes with maximizing evacuees during a finite time. ► Scenario-based analysis enhances robustness in controlling system risk. ► The method will help to improve the capability of disaster responses. -- Abstract: Nuclear emergency evacuation is important to prevent radioactive harms by hazardous materials and to limit the accidents’ consequences; however, uncertainties are involved in the components and processes of such a management system. In the study, an interval-parameter joint-probabilistic integer programming (IJIP) method is developed for emergency evacuation management under uncertainties. Optimization techniques of interval-parameter programming (IPP) and joint-probabilistic constrained (JPC) programming are incorporated into an integer linear programming framework, so that the approach can deal with uncertainties expressed as joint probability and interval values. The IJIP method can schedule the optimal routes to guarantee the maximum population evacuated away from the effected zone during a finite time. Furthermore, it can also facilitate post optimization analysis to enhance robustness in controlling system violation risk imposed on the joint-probabilistic constraints. The developed method has been applied to a case study of nuclear emergency management; meanwhile, a number of scenarios under different system conditions have been analyzed. It is indicated that the solutions are useful for evacuation management practices. The result of the IJIP method can not only help to raise the capability of disaster responses in a systematic manner, but also provide an insight into complex relationships among evacuation planning, resources utilizations, policy requirements and system risks.

  3. Risk assessments of regional climate change over Europe: generation of probabilistic ensemble and uncertainty assessment for EURO-CODEX

    Science.gov (United States)

    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

  4. Integrated Reliability and Risk Analysis System (IRRAS)

    International Nuclear Information System (INIS)

    Russell, K.D.; McKay, M.K.; Sattison, M.B.; Skinner, N.L.; Wood, S.T.; Rasmuson, D.M.

    1992-01-01

    The Integrated Reliability and Risk Analysis System (IRRAS) is a state-of-the-art, microcomputer-based probabilistic risk assessment (PRA) model development and analysis tool to address key nuclear plant safety issues. IRRAS is an integrated software tool that gives the user the ability to create and analyze fault trees and accident sequences using a microcomputer. This program provides functions that range from graphical fault tree construction to cut set generation and quantification. Version 1.0 of the IRRAS program was released in February of 1987. Since that time, many user comments and enhancements have been incorporated into the program providing a much more powerful and user-friendly system. This version has been designated IRRAS 4.0 and is the subject of this Reference Manual. Version 4.0 of IRRAS provides the same capabilities as Version 1.0 and adds a relational data base facility for managing the data, improved functionality, and improved algorithm performance

  5. Investing in finite-life carbon emissions reduction program under risk and idiosyncratic uncertainty

    International Nuclear Information System (INIS)

    Fouilloux, Jessica; Moraux, Franck; Viviani, Jean-Laurent

    2015-01-01

    This paper aims at emphasizing the ability of new frameworks of real option model to highlight key characteristics of industrial Carbon Emissions Reduction Program investment decision. We develop both theoretical arguments and numerical simulations with structural parameters calibrated on real-life data. We find that both radical uncertainty and risk lead to speed-up green investments, compared to the predictions of real option models that are normally used in green investment literature. The conventional “wait and see” attitude, questioned in recent developments of the real option theory, is not validated. In conclusion, our results should foster companies to implement green investments and help governments to define appropriate incentives to encourage green investments. Of particular note, the paper highlights that finance theory is not necessarily an obstacle to green investment decisions. -- Highlights: •We use real option model to identify key features of CERP investment decision. •We determine the optimal carbon price threshold to undertake a CERP. •Investment decision is a non-monotonic function of idiosyncratic uncertainty. •Increasing uncertainty until a moderate level can accelerate investment decision. •Decreasing idiosyncratic risk can accelerate investment decision

  6. A Study of the Impact of Underground Economy on Integral Tax Burden in the Proportional Growth Model under Uncertainty

    Directory of Open Access Journals (Sweden)

    Akif Musayev

    2018-01-01

    Full Text Available Economic processes are naturally characterized by imprecise and uncertain relevant information. One of the main reasons is existence of an underground economy. However, in existing works, real-world imprecision and uncertainty of economic conditions are not taken into account. In this paper we consider a problem of calculation of a taxation base to assess tax burden for proportionally growing economy under uncertainty. In order to account for imprecision and uncertainty of economic processes, we use the theory of fuzzy sets. A fuzzy integral equation is used to identify an integral tax burden taking into account the contribution of the underground economy for a certain financial (tax year. It is also assumed that dynamics of gross domestic product are modeled by fuzzy linear differential equation. An optimal value of tax burden is determined as a solution to the considered fuzzy integral equation. An example is provided to illustrate validity of the proposed study.

  7. Assessing uncertainty in extreme events: Applications to risk-based decision making in interdependent infrastructure sectors

    International Nuclear Information System (INIS)

    Barker, Kash; Haimes, Yacov Y.

    2009-01-01

    Risk-based decision making often relies upon expert probability assessments, particularly in the consequences of disruptive events and when such events are extreme or catastrophic in nature. Naturally, such expert-elicited probability distributions can be fraught with errors, as they describe events which occur very infrequently and for which only sparse data exist. This paper presents a quantitative framework, the extreme event uncertainty sensitivity impact method (EE-USIM), for measuring the sensitivity of extreme event consequences to uncertainties in the parameters of the underlying probability distribution. The EE-USIM is demonstrated with the Inoperability input-output model (IIM), a model with which to evaluate the propagation of inoperability throughout an interdependent set of economic and infrastructure sectors. The EE-USIM also makes use of a two-sided power distribution function generated by expert elicitation of extreme event consequences

  8. ENTERPRISE OPERATION PLANNING IN THE CONDITIONS OF RISK AND UNCERTAINTY IN THE EXTERNAL AND INTERNAL ENVIRONMENT

    Directory of Open Access Journals (Sweden)

    Titov V. V.

    2017-09-01

    Full Text Available Optimization of the enterprise activity planning taking into account the risk and uncertainty of the external and internal environment is a complex scientific and methodological problem. Its solution is important for the planning practice. Therefore, the relevance of this research topic is beyond doubt. Planning is based on the use of a multilevel system of models. At the top level, the achievement of key strategic indicators is ensured by the development and implementation of innovations, mainly related to the planning of the release of new high-tech products. However, it is at this level that the risks and uncertainties have the greatest impact on the planning processes for the development, production and marketing of new products. In the scientific literature it is proposed to use the stochastic graphs with returns for this purpose. This idea is also supported in this work. However, the implementation of such an idea requires additional methodological developments and quantitative calculations. The coordination of strategic decisions with tactical plans is based on the idea of eliminating the economic and other risks associated with the economic activity of the enterprise in tactical planning, by creating the stochastic reserves based on the implementation of additional innovations that ensure the receipt of above-target sales volumes, profits and other indicators of the strategic plan. The organization of operational management of production is represented by an iterative, sliding process (reducing risks in production, which is realized taking into account the limitations of tactical control.

  9. Optimal hydro scheduling and offering strategies considering price uncertainty and risk management

    International Nuclear Information System (INIS)

    Catalão, J.P.S.; Pousinho, H.M.I.; Contreras, J.

    2012-01-01

    Hydro energy represents a priority in the energy policy of Portugal, with the aim of decreasing the dependence on fossil fuels. In this context, optimal hydro scheduling acquires added significance in moving towards a sustainable environment. A mixed-integer nonlinear programming approach is considered to enable optimal hydro scheduling for the short-term time horizon, including the effect of head on power production, start-up costs related to the units, multiple regions of operation, and constraints on discharge variation. As new contributions to the field, market uncertainty is introduced in the model via price scenarios and risk management is included using Conditional Value-at-Risk to limit profit volatility. Moreover, plant scheduling and pool offering by the hydro power producer are simultaneously considered to solve a realistic cascaded hydro system. -- Highlights: ► A mixed-integer nonlinear programming approach is considered for optimal hydro scheduling. ► Market uncertainty is introduced in the model via price scenarios. ► Risk management is included using conditional value-at-risk. ► Plant scheduling and pool offering by the hydro power producer are simultaneously considered. ► A realistic cascaded hydro system is solved.

  10. Uncertainty Analysis on the Health Risk Caused by a Radiological Terror

    International Nuclear Information System (INIS)

    Jeong, Hyojoon; Hwang, Wontae; Kim, Eunhan; Han, Moonhee

    2010-01-01

    Atmospheric dispersion modeling and uncertainty analysis were carried out support the decision making in case of radiological emergency events. The risk caused by inhalation is highly dependent on air concentrations for radionuclides, therefore air monitoring and dispersion modeling have to be performed carefully to reduce the uncertainty of the health risk assessment for the public. When an intentional release of radioactive materials occurs in an urban area, air quality for radioactive materials in the environment is of great importance to take action for countermeasures and environmental risk assessments. Atmospheric modeling is part of the decision making tasks and that it is particularly important for emergency managers as they often need to take actions quickly on very inadequate information. In this study, we assume an 137 Cs explosion of 50 TBq using RDDs in the metropolitan area of Soul, South Korea. California Puff Model is used to calculate an atmospheric dispersion and transport for 137 Cs, and environmental risk analysis is performed using the Monte Carlo method

  11. A dominance-based approach to map risks of ecological invasions in the presence of severe uncertainty

    Science.gov (United States)

    Denys Yemshanov; Frank H. Koch; D. Barry Lyons; Mark Ducey; Klaus Koehler

    2012-01-01

    Aim Uncertainty has been widely recognized as one of the most critical issues in predicting the expansion of ecological invasions. The uncertainty associated with the introduction and spread of invasive organisms influences how pest management decision makers respond to expanding incursions. We present a model-based approach to map risk of ecological invasions that...

  12. Economic risk-based analysis: Effect of technical and market price uncertainties on the production of glycerol-based isobutanol

    DEFF Research Database (Denmark)

    Loureiro da Costa Lira Gargalo, Carina; Gernaey, Krist; Sin, Gürkan

    2016-01-01

    to propagate the market price and technical uncertainties to the economic indicator calculations and to quantify the respective economic risk. The results clearly indicated that under the given market price uncertainties, the probability of obtaining a negative NPV is 0.95. This is a very high probability...

  13. A Convex Model of Risk-Based Unit Commitment for Day-Ahead Market Clearing Considering Wind Power Uncertainty

    DEFF Research Database (Denmark)

    Zhang, Ning; Kang, Chongqing; Xia, Qing

    2015-01-01

    The integration of wind power requires the power system to be sufficiently flexible to accommodate its forecast errors. In the market clearing process, the scheduling of flexibility relies on the manner in which the wind power uncertainty is addressed in the unit commitment (UC) model. This paper...... and are considered in both the objective functions and the constraints. The RUC model is shown to be convex and is transformed into a mixed integer linear programming (MILP) problem using relaxation and piecewise linearization. The proposed RUC model is tested using a three-bus system and an IEEE RTS79 system...... that the risk modeling facilitates a strategic market clearing procedure with a reasonable computational expense....

  14. Baseline development, economic risk, and schedule risk: An integrated approach

    International Nuclear Information System (INIS)

    Tonkinson, J.A.

    1994-01-01

    The economic and schedule risks of Environmental Restoration (ER) projects are commonly analyzed toward the end of the baseline development process. Risk analysis is usually performed as the final element of the scheduling or estimating processes for the purpose of establishing cost and schedule contingency. However, there is an opportunity for earlier assessment of risks, during development of the technical scope and Work Breakdown Structure (WBS). Integrating the processes of risk management and baselining provides for early incorporation of feedback regarding schedule and cost risk into the proposed scope of work. Much of the information necessary to perform risk analysis becomes available during development of the technical baseline, as the scope of work and WBS are being defined. The analysis of risk can actually be initiated early on during development of the technical baseline and continue throughout development of the complete project baseline. Indeed, best business practices suggest that information crucial to the success of a project be analyzed and incorporated into project planning as soon as it is available and usable

  15. Uncertainty analysis comes to integrated assessment models for climate change…and conversely

    NARCIS (Netherlands)

    Cooke, R.M.

    2012-01-01

    This article traces the development of uncertainty analysis through three generations punctuated by large methodology investments in the nuclear sector. Driven by a very high perceived legitimation burden, these investments aimed at strengthening the scientific basis of uncertainty quantification.

  16. Explicitly integrating parameter, input, and structure uncertainties into Bayesian Neural Networks for probabilistic hydrologic forecasting

    KAUST Repository

    Zhang, Xuesong; Liang, Faming; Yu, Beibei; Zong, Ziliang

    2011-01-01

    Estimating uncertainty of hydrologic forecasting is valuable to water resources and other relevant decision making processes. Recently, Bayesian Neural Networks (BNNs) have been proved powerful tools for quantifying uncertainty of streamflow

  17. Integrating Risk Analyses and Tools at the DOE Hanford Site

    International Nuclear Information System (INIS)

    LOBER, R.W.

    2002-01-01

    Risk assessment and environmental impact analysis at the U.S. Department of Energy (DOE) Hanford Site in Washington State has made significant progress in refining the strategy for using risk analysis to support closing of several hundred waste sites plus 149 single-shell tanks at the Hanford Site. A Single-Shell Tank System Closure Work Plan outlines the current basis for closing the single-shell tank systems. An analogous site approach has been developed to address closure of aggregated groups of similar waste sites. Because of the complexity, decision time frames, proximity of non-tank farm waste sites to tank farms, scale, and regulatory considerations, various projects are providing integrated assessments to support risk analyses and decision-making. Projects and the tools that are being developed and applied at Hanford to support retrieval and cleanup decisions include: (1) Life Cycle Model (LCM) and Risk Receptor Model (RRM)--A site-level set of tools to support strategic analyses through scoping level risk management to assess different alternatives and options for tank closure. (2) Systems Assessment Capability for Integrated Groundwater Nadose Zone (SAC) and the Site-Wide Groundwater Model (SWGM)--A site-wide groundwater modeling system coupled with a risk-based uncertainty analysis of inventory, vadose zone, groundwater, and river interactions for evaluating cumulative impacts from individual and aggregate waste sites. (3) Retrieval Performance Evaluation (RPE)--A site-specific, risk-based methodology developed to evaluate performance of waste retrieval, leak detection and closure on a tank-specific basis as a function of past tank Leaks, potential leakage during retrieval operations, and remaining residual waste inventories following completion of retrieval operations. (4) Field Investigation Report (FIR)--A corrective action program to investigate the nature and extent of past tank leaks through characterization activities and assess future impacts to

  18. Mean-variance model for portfolio optimization with background risk based on uncertainty theory

    Science.gov (United States)

    Zhai, Jia; Bai, Manying

    2018-04-01

    The aim of this paper is to develop a mean-variance model for portfolio optimization considering the background risk, liquidity and transaction cost based on uncertainty theory. In portfolio selection problem, returns of securities and assets liquidity are assumed as uncertain variables because of incidents or lacking of historical data, which are common in economic and social environment. We provide crisp forms of the model and a hybrid intelligent algorithm to solve it. Under a mean-variance framework, we analyze the portfolio frontier characteristic considering independently additive background risk. In addition, we discuss some effects of background risk and liquidity constraint on the portfolio selection. Finally, we demonstrate the proposed models by numerical simulations.

  19. Bayesian Monte Carlo and Maximum Likelihood Approach for Uncertainty Estimation and Risk Management: Application to Lake Oxygen Recovery Model

    Science.gov (United States)

    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...

  20. Radical uncertainty, non-predictability, antifragility and risk-sharing Islamic finance

    Directory of Open Access Journals (Sweden)

    Umar Rafi

    2016-12-01

    Full Text Available Under conditions of radical uncertainty, risk sharing renders financial systems anti-fragile. Our goal in this paper is to show that risk-sharing Islamic finance (RSIF shares the characteristics defined by Taleb for an anti-fragile system, by mapping some characteristics of anti-fragility onto those of risk-sharing Islamic finance. A key insight around which such a connection can be established is by relating the principle of “no risk-no gain”from Islamic finance to the concept of skin-in-the-game from anti-fragility theory. The relationship is then extended to other characteristics of the two frameworks, to show that RSIF overlaps with anti-fragility over many dimensions. The broader case for an antifragile system includes another important characteristic, namely “soul in the game” and concern for social justice. It is the authors’ hope that emerging research on anti-fragility, combined with the emerging research on RSIF, can have a lasting impact on the field of finance by laying the foundations for a compelling case that it is time for humanity to replace the dominant debt-based risk transfer/risk shifting financial system with a system in which everyone shares the risks faced by society. JEL: D81, D89, E44, F34, G32

  1. Dealing with uncertainty and pursuing superior technology options in risk management-The inherency risk analysis

    International Nuclear Information System (INIS)

    Helland, Aasgeir

    2009-01-01

    Current regulatory systems focus on the state of scientific evidence as the predominant factor for how to handle risks to human health and the environment. However, production and assessment of risk information are costly and time-consuming, and firms have an intrinsic disincentive to produce and distribute information about risks of their products as this could endanger their production opportunities and sales. An emphasis on more or better science may result in insufficient thought and attention going into the exploration of technology alternatives, and that risk management policies miss out on the possible achievement of a more favorable set of consequences. In this article, a method is proposed that combines risk assessment with the search for alternative technological options as a part of the risk management procedure. The method proposed is the inherency risk analysis where the first stage focuses on the original agent subject to investigation, the second stage focuses on identifying technological options whereas the third stage reviews the different alternatives, searching for the most attractive tradeoffs between costs and inherent safety. This is then used as a fundament for deciding which technology option to pursue. This method aims at providing a solution-focused, systematic technology-based approach for addressing and setting priorities for environmental problems. By combining risk assessment with a structured approach to identify superior technology options within a risk management system, the result could very well be a win-win situation for both company and the environment.

  2. Evaluation of pull production control strategies under uncertainty: An integrated fuzzy AHP-TOPSIS approach

    Directory of Open Access Journals (Sweden)

    Aydin Torkabadi

    2018-03-01

    Full Text Available Purpose: Just-In-Time (JIT production has continuously been considered by industrial practitioners and researchers as a leading strategy for the yet popular Lean production. Pull Production Control Policies (PPCPs are the major enablers of JIT that locally control the level of inventory by authorizing the production in each station. Aiming to improve the PPCPs, three authorization mechanisms: Kanban, constant-work-in-process (ConWIP, and a hybrid system, are evaluated by considering uncertainty. Design/methodology/approach: Multi-Criteria Decision Making (MCDM methods are successful in evaluating alternatives with respect to several objectives. The proposed approach of this study applies the fuzzy set theory together with an integrated Analytical Hierarchy Process (AHP and a Technique for Order Performance by Similarity to Ideal Solution (TOPSIS method. Findings: The study finds that hybrid Kanban-ConWIP pull production control policies have a better performance in controlling the studied multi-layer multi-stage manufacturing and assembly system. Practical implications: To examine the approach a real case from automobile electro mechanical part production industry is studied. The production system consists of multiple levels of manufacturing, feeding a multi-stage assembly line with stochastic processing times to satisfy the changing demand. Originality/value: This study proposes the integrated Kanban-ConWIP hybrid pull control policies and implements several alternatives on a multi-stage and multi-layer manufacturing and assembly production system. An integrated Fuzzy AHP TOPSIS method is developed to evaluate the alternatives with respect to several JIT criteria.

  3. Analysis of decision fusion algorithms in handling uncertainties for integrated health monitoring systems

    Science.gov (United States)

    Zein-Sabatto, Saleh; Mikhail, Maged; Bodruzzaman, Mohammad; DeSimio, Martin; Derriso, Mark; Behbahani, Alireza

    2012-06-01

    It has been widely accepted that data fusion and information fusion methods can improve the accuracy and robustness of decision-making in structural health monitoring systems. It is arguably true nonetheless, that decision-level is equally beneficial when applied to integrated health monitoring systems. Several decisions at low-levels of abstraction may be produced by different decision-makers; however, decision-level fusion is required at the final stage of the process to provide accurate assessment about the health of the monitored system as a whole. An example of such integrated systems with complex decision-making scenarios is the integrated health monitoring of aircraft. Thorough understanding of the characteristics of the decision-fusion methodologies is a crucial step for successful implementation of such decision-fusion systems. In this paper, we have presented the major information fusion methodologies reported in the literature, i.e., probabilistic, evidential, and artificial intelligent based methods. The theoretical basis and characteristics of these methodologies are explained and their performances are analyzed. Second, candidate methods from the above fusion methodologies, i.e., Bayesian, Dempster-Shafer, and fuzzy logic algorithms are selected and their applications are extended to decisions fusion. Finally, fusion algorithms are developed based on the selected fusion methods and their performance are tested on decisions generated from synthetic data and from experimental data. Also in this paper, a modeling methodology, i.e. cloud model, for generating synthetic decisions is presented and used. Using the cloud model, both types of uncertainties; randomness and fuzziness, involved in real decision-making are modeled. Synthetic decisions are generated with an unbiased process and varying interaction complexities among decisions to provide for fair performance comparison of the selected decision-fusion algorithms. For verification purposes

  4. Methodological Bases for Describing Risks of the Enterprise Business Model in Integrated Reporting

    Directory of Open Access Journals (Sweden)

    Nesterenko Oksana O.

    2017-12-01

    Full Text Available The aim of the article is to substantiate the methodological bases for describing the business and accounting risks of an enterprise business model in integrated reporting for their timely detection and assessment, and develop methods for their leveling or minimizing and possible prevention. It is proposed to consider risks in the process of forming integrated reporting from two sides: first, risks that arise in the business model of an organization and should be disclosed in its integrated report; second, accounting risks of integrated reporting, which should be taken into account by members of the cross-sectoral working group and management personnel in the process of forming and promulgating integrated reporting. To develop an adequate accounting and analytical tool for disclosure of information about the risks of the business model and integrated reporting, their leveling or minimization, in the article a terminological analysis of the essence of entrepreneurial and accounting risks is carried out. The entrepreneurial risk is defined as an objective-subjective economic category that characterizes the probability of negative or positive consequences of economic-social-ecological activity within the framework of the business model of an enterprise under uncertainty. The accounting risk is suggested to be understood as the probability of unfavorable consequences as a result of organizational, methodological errors in the integrated accounting system, which present threat to the quality, accuracy and reliability of the reporting information on economic, social and environmental activities in integrated reporting as well as threat of inappropriate decision-making by stakeholders based on the integrated report. For the timely identification of business risks and maximum leveling of the influence of accounting risks on the process of formation and publication of integrated reporting, in the study the place of entrepreneurial and accounting risks in

  5. Optimizing an Investment Solution in Conditions of Uncertainty and Risk as a Multicriterial Task

    Directory of Open Access Journals (Sweden)

    Kotsyuba Oleksiy S.

    2017-10-01

    Full Text Available The article is concerned with the methodology for optimizing investment decisions in conditions of uncertainty and risk. The subject area of the study relates, first of all, to real investment. The problem of modeling an optimal investment solution is considered to be a multicriterial task. Also, the constructive part of the publication is based on the position that the multicriteriality of objectives of investment projecting is the result, first, of the complex nature of the category of economic attractiveness (efficiency of real investment, and secondly, of the need to take into account the risk factor, which is a vector measure, in the preparation of an investment solution. An attempt has been made to develop an instrumentarium to optimize investment decisions in a situation of uncertainty and the risk it engenders, based on the use of roll-up of the local criteria. As a result of its implementation, a model has been proposed, which has the advantage that it takes into account, to a greater extent than is the case for standardized roll-up options, the contensive and formal features of the local (detailed criteria.

  6. Assessing the near-term risk of climate uncertainty : interdependencies among the U.S. states.

    Energy Technology Data Exchange (ETDEWEB)

    Loose, Verne W.; Lowry, Thomas Stephen; Malczynski, Leonard A.; Tidwell, Vincent Carroll; Stamber, Kevin Louis; Reinert, Rhonda K.; Backus, George A.; Warren, Drake E.; Zagonel, Aldo A.; Ehlen, Mark Andrew; Klise, Geoffrey T.; Vargas, Vanessa N.

    2010-04-01

    Policy makers will most likely need to make decisions about climate policy before climate scientists have resolved all relevant uncertainties about the impacts of climate change. This study demonstrates a risk-assessment methodology for evaluating uncertain future climatic conditions. We estimate the impacts of climate change on U.S. state- and national-level economic activity from 2010 to 2050. To understand the implications of uncertainty on risk and to provide a near-term rationale for policy interventions to mitigate the course of climate change, we focus on precipitation, one of the most uncertain aspects of future climate change. We use results of the climate-model ensemble from the Intergovernmental Panel on Climate Change's (IPCC) Fourth Assessment Report 4 (AR4) as a proxy for representing climate uncertainty over the next 40 years, map the simulated weather from the climate models hydrologically to the county level to determine the physical consequences on economic activity at the state level, and perform a detailed 70-industry analysis of economic impacts among the interacting lower-48 states. We determine the industry-level contribution to the gross domestic product and employment impacts at the state level, as well as interstate population migration, effects on personal income, and consequences for the U.S. trade balance. We show that the mean or average risk of damage to the U.S. economy from climate change, at the national level, is on the order of $1 trillion over the next 40 years, with losses in employment equivalent to nearly 7 million full-time jobs.

  7. A nonparametric approach to medical survival data: Uncertainty in the context of risk in mortality analysis

    International Nuclear Information System (INIS)

    Janurová, Kateřina; Briš, Radim

    2014-01-01

    Medical survival right-censored data of about 850 patients are evaluated to analyze the uncertainty related to the risk of mortality on one hand and compare two basic surgery techniques in the context of risk of mortality on the other hand. Colorectal data come from patients who underwent colectomy in the University Hospital of Ostrava. Two basic surgery operating techniques are used for the colectomy: either traditional (open) or minimally invasive (laparoscopic). Basic question arising at the colectomy operation is, which type of operation to choose to guarantee longer overall survival time. Two non-parametric approaches have been used to quantify probability of mortality with uncertainties. In fact, complement of the probability to one, i.e. survival function with corresponding confidence levels is calculated and evaluated. First approach considers standard nonparametric estimators resulting from both the Kaplan–Meier estimator of survival function in connection with Greenwood's formula and the Nelson–Aalen estimator of cumulative hazard function including confidence interval for survival function as well. The second innovative approach, represented by Nonparametric Predictive Inference (NPI), uses lower and upper probabilities for quantifying uncertainty and provides a model of predictive survival function instead of the population survival function. The traditional log-rank test on one hand and the nonparametric predictive comparison of two groups of lifetime data on the other hand have been compared to evaluate risk of mortality in the context of mentioned surgery techniques. The size of the difference between two groups of lifetime data has been considered and analyzed as well. Both nonparametric approaches led to the same conclusion, that the minimally invasive operating technique guarantees the patient significantly longer survival time in comparison with the traditional operating technique

  8. TREATING UNCERTAINTIES IN A NUCLEAR SEISMIC PROBABILISTIC RISK ASSESSMENT BY MEANS OF THE DEMPSTER-SHAFER THEORY OF EVIDENCE

    OpenAIRE

    Lo , Chung-Kung; Pedroni , N.; Zio , Enrico

    2014-01-01

    International audience; The analyses carried out within the Seismic Probabilistic Risk Assessments (SPRAs) of Nuclear Power Plants (NPPs) are affected by significant aleatory and epistemic uncertainties. These uncertainties have to be represented and quantified coherently with the data, information and knowledge available, to provide reasonable assurance that related decisions can be taken robustly and with confidence. The amount of data, information and knowledge available for seismic risk a...

  9. Integrated Level 3 risk assessment for the LaSalle Unit 2 nuclear power plant

    International Nuclear Information System (INIS)

    Payne, A.C. Jr.; Brown, T.D.; Miller, L.A.

    1991-01-01

    An integrated Level 3 probabilistic risk assessment (PRA) was performed on the LaSalle County Station nuclear power plant using state-of-the-art PRA analysis techniques. The objective of this study was to provide an estimate of the risk to the offsite population during full power operation of the plant and to include a characterization of the uncertainties in the calculated risk values. Uncertainties were included in the accident frequency analysis, accident progression analysis, and the source term analysis. Only weather uncertainties were included in the consequence analysis. In this paper selected results from the accident frequency, accident progression, source term, consequence, and integrated risk analyses are discussed and the methods used to perform a fully integrated Level 3 PRA are examined. LaSalle County Station is a two-unit nuclear power plant located 55 miles southwest of Chicago, Illinois. Each unit utilizes a Mark 2 containment to house a General Electric 3323 MWt BWR-5 reactor. This PRA, which was performed on Unit 2, included internal as well as external events. External events that were propagated through the risk analysis included earthquakes, fires, and floods. The internal event accident scenarios included transients, transient-induced LOCAs (inadvertently stuck open relief valves), anticipated transients without scram, and loss of coolant accidents

  10. Time of Concentration equations: the role of morphometric uncertainties in flood risk analysis and management

    Science.gov (United States)

    Martins, Luciano; Díez-Herrero, Andrés; Bodoque, Jose M.; Bateira, Carlos

    2016-04-01

    The perception of flood risk by the responsible authorities on the flood management disasters and mitigation strategies should be based on an overall evaluation of the uncertainties associated with the procedures for risk assessment and mapping production. This contribution presents the results of the development of mapping evaluation of the time of concentration (tc). This parameter reflects the time-space at which a watershed responds to rainfall events and is the most frequently utilized time parameter, and is of great importance in many hydrologic analysis. Accurate estimates of the tc are very important, for instance, if tc is under-estimated, the result is an over-estimated peak discharge and vice versa, resulting significant variations on the flooded areas, and could have important consequences in terms of the land use and occupation of territory, as management's own flood risk. The methology used evaluate 20 different empirical, semi-empirical and kinematics equations of tc calculation, due to different cartographic scales (1:200000; 1:100000; 1:25000; LIDAR 5x5m &1x1m) in in two hydrographic basins with distinct dimensions and geomorphological characteristics, located in the Gredos Mountain range (Spain). The results suggest that the changes in the cartographic scale, has not influence as significant as one might expect. The most important variations occur in the characteristics of the fequations, use different morphometricparameters in the calculations. Some just are based on geomorphological criteria and other magnify the hydraulic characteristics of the channels, resulting in very different tc values. However, we highlighting the role of cartographic scale particularly in the application of semi-empirical equations that take into account changes in land use and occupation. In this case, the determination of parameters, such as flow coefficient, curve number and roughness coefficient are very sensitive to cartographic scale. Sensitivity analysis

  11. The management of uncertainties in the French regulation on deep disposal: the development of a non-risk based approach

    International Nuclear Information System (INIS)

    Raimbault, P.

    2004-01-01

    The development of a safety case for disposal of high level and medium level long-lived waste in a geological formation has to handle two main difficulties: - uncertainties associated to natural systems; - uncertainties associated to the consideration of long time scales. Licensing of the different steps leading to geological disposal implies thus that a sufficient level of confidence in the safety case will be obtained, at each step, among the different stakeholders. The confidence in the safety case relies on the whole set of arguments of different natures which complement each other and build up the file. This means that, to be defensible, the safety case should be organised in such a way that it can be reviewed and scrutinized in a structured manner. This also means that individual elements of the safety case will have to be considered separately even if all elements should fit well in the integrated safety case. This segregation implies some inherent decoupling of parts of the system, of its evolution over time and of the events that may impact on it. This decoupling will thus introduce inherent uncertainties that risk or non-risk based approaches have to deal with since both approaches have to introduce transparency in the analysis. In the non-risk based or deterministic approach this segregation is pushed further in order to put into perspective the different elements of appreciation that allow to judge the safety case as a whole. The French regulation on deep disposal presented in the basic safety rule RFS III.3.f, issued in 1991, takes these points into consideration to set the basis for the safety case in the framework of a deterministic approach. This basic safety rule is currently being revised in order to clarify some concepts and to take account evolution of ideas at the national and international level. However the basic rationale behind the safety assessment methodology will remain the same. The approach presented in RFS III.2.f implies that at

  12. Emotion and decision-making under uncertainty: Physiological arousal predicts increased gambling during ambiguity but not risk.

    Science.gov (United States)

    FeldmanHall, Oriel; Glimcher, Paul; Baker, Augustus L; Phelps, Elizabeth A

    2016-10-01

    Uncertainty, which is ubiquitous in decision-making, can be fractionated into known probabilities (risk) and unknown probabilities (ambiguity). Although research has illustrated that individuals more often avoid decisions associated with ambiguity compared to risk, it remains unclear why ambiguity is perceived as more aversive. Here we examine the role of arousal in shaping the representation of value and subsequent choice under risky and ambiguous decisions. To investigate the relationship between arousal and decisions of uncertainty, we measure skin conductance response-a quantifiable measure reflecting sympathetic nervous system arousal-during choices to gamble under risk and ambiguity. To quantify the discrete influences of risk and ambiguity sensitivity and the subjective value of each option under consideration, we model fluctuating uncertainty, as well as the amount of money that can be gained by taking the gamble. Results reveal that although arousal tracks the subjective value of a lottery regardless of uncertainty type, arousal differentially contributes to the computation of value-that is, choice-depending on whether the uncertainty is risky or ambiguous: Enhanced arousal adaptively decreases risk-taking only when the lottery is highly risky but increases risk-taking when the probability of winning is ambiguous (even after controlling for subjective value). Together, this suggests that the role of arousal during decisions of uncertainty is modulatory and highly dependent on the context in which the decision is framed. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  13. Approaches to cancer assessment in EPA's Integrated Risk Information System.

    Science.gov (United States)

    Gehlhaus, Martin W; Gift, Jeffrey S; Hogan, Karen A; Kopylev, Leonid; Schlosser, Paul M; Kadry, Abdel-Razak

    2011-07-15

    The U.S. Environmental Protection Agency's (EPA) Integrated Risk Information System (IRIS) Program develops assessments of health effects that may result from chronic exposure to chemicals in the environment. The IRIS database contains more than 540 assessments. When supported by available data, IRIS assessments provide quantitative analyses of carcinogenic effects. Since publication of EPA's 2005 Guidelines for Carcinogen Risk Assessment, IRIS cancer assessments have implemented new approaches recommended in these guidelines and expanded the use of complex scientific methods to perform quantitative dose-response assessments. Two case studies of the application of the mode of action framework from the 2005 Cancer Guidelines are presented in this paper. The first is a case study of 1,2,3-trichloropropane, as an example of a chemical with a mutagenic mode of carcinogenic action thus warranting the application of age-dependent adjustment factors for early-life exposure; the second is a case study of ethylene glycol monobutyl ether, as an example of a chemical with a carcinogenic action consistent with a nonlinear extrapolation approach. The use of physiologically based pharmacokinetic (PBPK) modeling to quantify interindividual variability and account for human parameter uncertainty as part of a quantitative cancer assessment is illustrated using a case study involving probabilistic PBPK modeling for dichloromethane. We also discuss statistical issues in assessing trends and model fit for tumor dose-response data, analysis of the combined risk from multiple types of tumors, and application of life-table methods for using human data to derive cancer risk estimates. These issues reflect the complexity and challenges faced in assessing the carcinogenic risks from exposure to environmental chemicals, and provide a view of the current trends in IRIS carcinogenicity risk assessment. Copyright © 2011. Published by Elsevier Inc.

  14. Approaches to cancer assessment in EPA's Integrated Risk Information System

    International Nuclear Information System (INIS)

    Gehlhaus, Martin W.; Gift, Jeffrey S.; Hogan, Karen A.; Kopylev, Leonid; Schlosser, Paul M.; Kadry, Abdel-Razak

    2011-01-01

    The U.S. Environmental Protection Agency's (EPA) Integrated Risk Information System (IRIS) Program develops assessments of health effects that may result from chronic exposure to chemicals in the environment. The IRIS database contains more than 540 assessments. When supported by available data, IRIS assessments provide quantitative analyses of carcinogenic effects. Since publication of EPA's 2005 Guidelines for Carcinogen Risk Assessment, IRIS cancer assessments have implemented new approaches recommended in these guidelines and expanded the use of complex scientific methods to perform quantitative dose-response assessments. Two case studies of the application of the mode of action framework from the 2005 Cancer Guidelines are presented in this paper. The first is a case study of 1,2,3-trichloropropane, as an example of a chemical with a mutagenic mode of carcinogenic action thus warranting the application of age-dependent adjustment factors for early-life exposure; the second is a case study of ethylene glycol monobutyl ether, as an example of a chemical with a carcinogenic action consistent with a nonlinear extrapolation approach. The use of physiologically based pharmacokinetic (PBPK) modeling to quantify interindividual variability and account for human parameter uncertainty as part of a quantitative cancer assessment is illustrated using a case study involving probabilistic PBPK modeling for dichloromethane. We also discuss statistical issues in assessing trends and model fit for tumor dose-response data, analysis of the combined risk from multiple types of tumors, and application of life-table methods for using human data to derive cancer risk estimates. These issues reflect the complexity and challenges faced in assessing the carcinogenic risks from exposure to environmental chemicals, and provide a view of the current trends in IRIS carcinogenicity risk assessment.

  15. Hazardous waste transportation risk assessment: Benefits of a combined deterministic and probabilistic Monte Carlo approach in expressing risk uncertainty

    International Nuclear Information System (INIS)

    Policastro, A.J.; Lazaro, M.A.; Cowen, M.A.; Hartmann, H.M.; Dunn, W.E.; Brown, D.F.

    1995-01-01

    This paper presents a combined deterministic and probabilistic methodology for modeling hazardous waste transportation risk and expressing the uncertainty in that risk. Both the deterministic and probabilistic methodologies are aimed at providing tools useful in the evaluation of alternative management scenarios for US Department of Energy (DOE) hazardous waste treatment, storage, and disposal (TSD). The probabilistic methodology can be used to provide perspective on and quantify uncertainties in deterministic predictions. The methodology developed has been applied to 63 DOE shipments made in fiscal year 1992, which contained poison by inhalation chemicals that represent an inhalation risk to the public. Models have been applied to simulate shipment routes, truck accident rates, chemical spill probabilities, spill/release rates, dispersion, population exposure, and health consequences. The simulation presented in this paper is specific to trucks traveling from DOE sites to their commercial TSD facilities, but the methodology is more general. Health consequences are presented as the number of people with potentially life-threatening health effects. Probabilistic distributions were developed (based on actual item data) for accident release amounts, time of day and season of the accident, and meteorological conditions

  16. Risk-Aversion: Understanding Teachers' Resistance to Technology Integration

    Science.gov (United States)

    Howard, Sarah K.

    2013-01-01

    Teachers who do not integrate technology are often labelled as "resistant" to change. Yet, considerable uncertainties remain about appropriate uses and actual value of technology in teaching and learning, which can make integration and change seem risky. The purpose of this article is to explore the nature of teachers' analytical and…

  17. The effect of an integrated education model on anxiety and uncertainty in patients undergoing cervical disc herniation surgery.

    Science.gov (United States)

    Chuang, Mei-Fang; Tung, Heng-Hsin; Clinciu, Daniel L; Huang, Jing-Shan; Iqbal, Usman; Chang, Chih-Ju; Su, I-Chang; Lai, Fu-Chih; Li, Yu-Chuan

    2016-09-01

    Educating patients about receiving surgical procedures is becoming an important issue, as it can reduce anxiety and uncertainty while helping to hasten decisions for undergoing time sensitive surgeries. We evaluated a new integrated education model for patients undergoing cervical disc herniation surgery using a quasi-experimental design. The participants were grouped into either the new integrated educational model (n = 32) or the standard group (n = 32) on the basis of their ward numbers assigned at admission. Anxiety, uncertainty, and patient satisfaction were measured before (pre-test) and after the educational intervention (post-test-1) and post-surgery (post-test-2) to assess the effectiveness of the model in this intervention. We found that the generalized estimating equation modeling demonstrated this new integrated education model was more effective than the conventional model in reducing patients' anxiety and uncertainty (p approach to individual health. This novel systemic educational model enhances patient's understanding of the medical condition and surgery while promoting patient-caregiver interaction for optimal patient health outcomes. We present a comprehensive and consistent platform for educational purposes in patients undergoing surgery as well as reducing the psychological burden from anxiety and uncertainty. Integrating medicine, nursing, and new technologies into an e-practice and e-learning platform offers the potential of easier understanding and usage. It could revolutionize patient education in the future. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  18. A research on verification of the CONTAIN CODE model and the uncertainty reduction method for containment integrity

    Energy Technology Data Exchange (ETDEWEB)

    Park, Jae Hong [Korea Institute of Nuclear Safety, Taejon (Korea, Republic of); Kim, Moo Hwan; Kang, Seok Hun; Seo, Kyoung Woo [Pohang University of Science and Technology, Pohang (Korea, Republic of)

    1999-03-15

    The final goal of this research is to verify methodology for evaluating more accurately the integrity of containment and develop the methodology to reduce the uncertainty using the data of the operating PWR, KSNPP, KNGR during a severe accident. Therefore, the research selected an indispensable factor about DCH, and analysed sensitivity test at this year.

  19. Quantifying uncertainty in pest risk maps and assessments: adopting a risk-averse decision maker’s perspective

    Directory of Open Access Journals (Sweden)

    Denys Yemshanov

    2013-09-01

    Full Text Available Pest risk maps are important decision support tools when devising strategies to minimize introductions of invasive organisms and mitigate their impacts. When possible management responses to an invader include costly or socially sensitive activities, decision-makers tend to follow a more certain (i.e., risk-averse course of action. We presented a new mapping technique that assesses pest invasion risk from the perspective of a risk-averse decision maker.We demonstrated the method by evaluating the likelihood that an invasive forest pest will be transported to one of the U.S. states or Canadian provinces in infested firewood by visitors to U.S. federal campgrounds. We tested the impact of the risk aversion assumption using distributions of plausible pest arrival scenarios generated with a geographically explicit model developed from data documenting camper travel across the study area. Next, we prioritized regions of high and low pest arrival risk via application of two stochastic ordering techniques that employed, respectively, first- and second-degree stochastic dominance rules, the latter of which incorporated the notion of risk aversion. We then identified regions in the study area where the pest risk value changed considerably after incorporating risk aversion.While both methods identified similar areas of highest and lowest risk, they differed in how they demarcated moderate-risk areas. In general, the second-order stochastic dominance method assigned lower risk rankings to moderate-risk areas. Overall, this new method offers a better strategy to deal with the uncertainty typically associated with risk assessments and provides a tractable way to incorporate decision-making preferences into final risk estimates, and thus helps to better align these estimates with particular decision-making scenarios about a pest organism of concern. Incorporation of risk aversion also helps prioritize the set of locations to target for inspections and

  20. Integrating uncertainties to the combined environmental and economic assessment of algal biorefineries: A Monte Carlo approach.

    Science.gov (United States)

    Pérez-López, Paula; Montazeri, Mahdokht; Feijoo, Gumersindo; Moreira, María Teresa; Eckelman, Matthew J

    2018-06-01

    The economic and environmental performance of microalgal processes has been widely analyzed in recent years. However, few studies propose an integrated process-based approach to evaluate economic and environmental indicators simultaneously. Biodiesel is usually the single product and the effect of environmental benefits of co-products obtained in the process is rarely discussed. In addition, there is wide variation of the results due to inherent variability of some parameters as well as different assumptions in the models and limited knowledge about the processes. In this study, two standardized models were combined to provide an integrated simulation tool allowing the simultaneous estimation of economic and environmental indicators from a unique set of input parameters. First, a harmonized scenario was assessed to validate the joint environmental and techno-economic model. The findings were consistent with previous assessments. In a second stage, a Monte Carlo simulation was applied to evaluate the influence of variable and uncertain parameters in the model output, as well as the correlations between the different outputs. The simulation showed a high probability of achieving favorable environmental performance for the evaluated categories and a minimum selling price ranging from $11gal -1 to $106gal -1 . Greenhouse gas emissions and minimum selling price were found to have the strongest positive linear relationship, whereas eutrophication showed weak correlations with the other indicators (namely greenhouse gas emissions, cumulative energy demand and minimum selling price). Process parameters (especially biomass productivity and lipid content) were the main source of variation, whereas uncertainties linked to the characterization methods and economic parameters had limited effect on the results. Copyright © 2018 Elsevier B.V. All rights reserved.

  1. Are Polish firms risk-averting or risk-loving? : evidence on demand uncertainty and the capital-labour ratio in a transition economy

    NARCIS (Netherlands)

    Lensink, Robert; Murinde, Victor; Green, Christopher J.

    1999-01-01

    This paper investigates the effect of demand uncertainty on the capital-labour ratio of non-financial firms in Poland in order to infer the firms’ risk behaviour. A generic model is used to characterise a utility maximising firm in a transition economy with demand uncertainty and imperfect

  2. An integrated location inventory routing model in supply chain network designing under uncertainty

    Directory of Open Access Journals (Sweden)

    Hojat Angazi

    2016-09-01

    Full Text Available In this study an integrated model is proposed for the location inventory routing problem under uncertainty. This problem involves determining the location of distribution centers (DCs in a three echelon supply chain. The DCs receive orders from the customer and according to a continuous review inventory replenishment policy place orders to the supplier. The products are directly shipped from the supplier to the DCs. The vehicles start from the DCs to fulfill the demands of the customers. Determining the routing of the vehicles is one of the decisions involved in this problem. The demands of customers are stochastically distributed and the capacity of DCs are limited. If one of the DCs undergo a disruption and is unable to fulfill the demands of the customers, shortage may occur. Moreover in the proposed model the shortage is considered as partial backlogging. This means that if shortage occurs, some of the orders result in lost sales and other orders are fulfilled in the next period. In order to optimally solve the proposed model a nonlinear integer programming (INLP model is developed. However, since the problem is NP-hard, the mathematical formulation cannot be efficiently solved for large sized instances of the problem. Therefore an outer approximation method is developed to solve the problem more efficiently. The computational results show the efficiency of the proposed method.

  3. Regulatory risk assessments: Is there a need to reduce uncertainty and enhance robustness?

    Science.gov (United States)

    Snodin, D J

    2015-12-01

    A critical evaluation of several recent regulatory risk assessments has been undertaken. These relate to propyl paraben (as a food additive, cosmetic ingredient or pharmaceutical excipient), cobalt (in terms of a safety-based limit for pharmaceuticals) and the cancer Threshold of Toxicological Concern as applied to food contaminants and pharmaceutical impurities. In all cases, a number of concerns can be raised regarding the reliability of the current assessments, some examples being absence of data audits, use of single-dose and/or non-good laboratory practice studies to determine safety metrics, use of a biased data set and questionable methodology and lack of consistency with precedents and regulatory guidance. Drawing on these findings, a set of recommendations is provided to reduce uncertainty and improve the quality and robustness of future regulatory risk assessments. © The Author(s) 2015.

  4. Communicating Uncertainty about Climate Change for Application to Security Risk Management

    Science.gov (United States)

    Gulledge, J. M.

    2011-12-01

    The science of climate change has convincingly demonstrated that human activities, including the release of greenhouse gases, land-surface changes, particle emissions, and redistribution of water, are changing global and regional climates. Consequently, key institutions are now concerned about the potential social impacts of climate change. For example, the 2010 Quadrennial Defense Review Report from the U.S. Department of Defense states that "climate change, energy security, and economic stability are inextricably linked." Meanwhile, insured losses from climate and weather-related natural disasters have risen dramatically over the past thirty years. Although these losses stem largely from socioeconomic trends, insurers are concerned that climate change could exacerbate this trend and render certain types of climate risk non-diversifiable. Meanwhile, the climate science community-broadly defined as physical, biological, and social scientists focused on some aspect of climate change-remains largely focused scholarly activities that are valued in the academy but not especially useful to decision makers. On the other hand, climate scientists who engage in policy discussions have generally permitted vested interests who support or oppose climate policies to frame the discussion of climate science within the policy arena. Such discussions focus on whether scientific uncertainties are sufficiently resolved to justify policy and the vested interests overstate or understate key uncertainties to support their own agendas. Consequently, the scientific community has become absorbed defending scientific findings to the near exclusion of developing novel tools to aid in risk-based decision-making. For example, the Intergovernmental Panel on Climate Change (IPCC), established expressly for the purpose of informing governments, has largely been engaged in attempts to reduce unavoidable uncertainties rather than helping the world's governments define a science-based risk

  5. Application of probability distributions for quantifying uncertainty in radionuclide source terms for Seabrook risk assessment

    International Nuclear Information System (INIS)

    Walker, D.H.; Savin, N.L.

    1985-01-01

    The calculational models developed for the Reactor Safety Study (RSS) have traditionally been used to generate 'point estimate values' for radionuclide release to the environment for nuclear power plant risk assessments. The point estimate values so calculated are acknowledged by most knowledgeable individuals to be conservatively high. Further, recent evaluations of the overall uncertainties in the various components that make up risk estimates for nuclear electric generating stations show that one of the large uncertainties is associated with the magnitude of the radionuclide release to the environment. In the approach developed for the RSS, values for fission product release from the fuel are derived from data obtained from small experiments. A reappraisal of the RSS release fractions was published in 1981 in NUREG-0772. Estimates of fractional releases from fuel are similar to those of the RSS. In the RSS approach, depletion during transport from the core (where the fission products are released) to the containment is assumed to be zero for calculation purposes. In the containment, the CORRAL code is applied to calculate radioactivity depletion by containment processes and to calculate the quantity and timing of release to the environment

  6. Benefits of using an optimization methodology for identifying robust process integration investments under uncertainty-A pulp mill example

    International Nuclear Information System (INIS)

    Svensson, Elin; Berntsson, Thore; Stroemberg, Ann-Brith

    2009-01-01

    This paper presents a case study on the optimization of process integration investments in a pulp mill considering uncertainties in future electricity and biofuel prices and CO 2 emissions charges. The work follows the methodology described in Svensson et al. [Svensson, E., Berntsson, T., Stroemberg, A.-B., Patriksson, M., 2008b. An optimization methodology for identifying robust process integration investments under uncertainty. Energy Policy, in press, (doi:10.1016/j.enpol.2008.10.023)] where a scenario-based approach is proposed for the modelling of uncertainties. The results show that the proposed methodology provides a way to handle the time dependence and the uncertainties of the parameters. For the analyzed case, a robust solution is found which turns out to be a combination of two opposing investment strategies. The difference between short-term and strategic views for the investment decision is analyzed and it is found that uncertainties are increasingly important to account for as a more strategic view is employed. Furthermore, the results imply that the obvious effect of policy instruments aimed at decreasing CO 2 emissions is, in applications like this, an increased profitability for all energy efficiency investments, and not as much a shift between different alternatives

  7. Benefits of using an optimization methodology for identifying robust process integration investments under uncertainty-A pulp mill example

    Energy Technology Data Exchange (ETDEWEB)

    Svensson, Elin [Department of Energy and Environment, Division of Heat and Power Technology, Chalmers University of Technology, SE-412 96 Goeteborg (Sweden)], E-mail: elin.svensson@chalmers.se; Berntsson, Thore [Department of Energy and Environment, Division of Heat and Power Technology, Chalmers University of Technology, SE-412 96 Goeteborg (Sweden); Stroemberg, Ann-Brith [Fraunhofer-Chalmers Research Centre for Industrial Mathematics, Chalmers Science Park, SE-412 88 Gothenburg (Sweden)

    2009-03-15

    This paper presents a case study on the optimization of process integration investments in a pulp mill considering uncertainties in future electricity and biofuel prices and CO{sub 2} emissions charges. The work follows the methodology described in Svensson et al. [Svensson, E., Berntsson, T., Stroemberg, A.-B., Patriksson, M., 2008b. An optimization methodology for identifying robust process integration investments under uncertainty. Energy Policy, in press, (doi:10.1016/j.enpol.2008.10.023)] where a scenario-based approach is proposed for the modelling of uncertainties. The results show that the proposed methodology provides a way to handle the time dependence and the uncertainties of the parameters. For the analyzed case, a robust solution is found which turns out to be a combination of two opposing investment strategies. The difference between short-term and strategic views for the investment decision is analyzed and it is found that uncertainties are increasingly important to account for as a more strategic view is employed. Furthermore, the results imply that the obvious effect of policy instruments aimed at decreasing CO{sub 2} emissions is, in applications like this, an increased profitability for all energy efficiency investments, and not as much a shift between different alternatives.

  8. Benefits of using an optimization methodology for identifying robust process integration investments under uncertainty. A pulp mill example

    Energy Technology Data Exchange (ETDEWEB)

    Svensson, Elin; Berntsson, Thore [Department of Energy and Environment, Division of Heat and Power Technology, Chalmers University of Technology, SE-412 96 Goeteborg (Sweden); Stroemberg, Ann-Brith [Fraunhofer-Chalmers Research Centre for Industrial Mathematics, Chalmers Science Park, SE-412 88 Gothenburg (Sweden)

    2009-03-15

    This paper presents a case study on the optimization of process integration investments in a pulp mill considering uncertainties in future electricity and biofuel prices and CO{sub 2} emissions charges. The work follows the methodology described in Svensson et al. [Svensson, E., Berntsson, T., Stroemberg, A.-B., Patriksson, M., 2008b. An optimization methodology for identifying robust process integration investments under uncertainty. Energy Policy, in press, doi:10.1016/j.enpol.2008.10.023] where a scenario-based approach is proposed for the modelling of uncertainties. The results show that the proposed methodology provides a way to handle the time dependence and the uncertainties of the parameters. For the analyzed case, a robust solution is found which turns out to be a combination of two opposing investment strategies. The difference between short-term and strategic views for the investment decision is analyzed and it is found that uncertainties are increasingly important to account for as a more strategic view is employed. Furthermore, the results imply that the obvious effect of policy instruments aimed at decreasing CO{sub 2} emissions is, in applications like this, an increased profitability for all energy efficiency investments, and not as much a shift between different alternatives. (author)

  9. Appropriate modelling for integrated flood risk assessment

    NARCIS (Netherlands)

    Huang, Y.

    2005-01-01

    Another issue of how to obtain and evaluate a DSS's overall performance is addressed by the use of Uncertainty Analysis (UA). Amongst the various approaches, UA is commonly found to be an important methodology for evaluating DSS performance. UA can provide insight into uncertainty contributions from

  10. Uncertainty assessment of climate change adaptation using an economic pluvial flood risk framework

    DEFF Research Database (Denmark)

    Zhou, Qianqian; Arnbjerg-Nielsen, Karsten

    2012-01-01

    It is anticipated that climate change is likely to lead to an increasing risk level of flooding in cities in northern Europe. One challenging question is how to best address the increasing flood risk and assess the costs and benefits of adapting to such changes. We established an integrated...... approach for identification and assessment of climate change adaptation options by incorporating climate change impacts, flood inundation modelling, economic tool and risk assessment and management. The framework is further extended and adapted by embedding a Monte Carlo simulation to estimate the total...

  11. Risk management & organizational uncertainty implications for the assessment of high consequence organizations

    Energy Technology Data Exchange (ETDEWEB)

    Bennett, C.T.

    1995-02-23

    Post hoc analyses have demonstrated clearly that macro-system, organizational processes have played important roles in such major catastrophes as Three Mile Island, Bhopal, Exxon Valdez, Chernobyl, and Piper Alpha. How can managers of such high-consequence organizations as nuclear power plants and nuclear explosives handling facilities be sure that similar macro-system processes are not operating in their plants? To date, macro-system effects have not been integrated into risk assessments. Part of the reason for not using macro-system analyses to assess risk may be the impression that standard organizational measurement tools do not provide hard data that can be managed effectively. In this paper, I argue that organizational dimensions, like those in ISO 9000, can be quantified and integrated into standard risk assessments.

  12. A dynamic multimedia fuzzy-stochastic integrated environmental risk assessment approach for contaminated sites management

    International Nuclear Information System (INIS)

    Hu, Yan; Wen, Jing-ya; Li, Xiao-li; Wang, Da-zhou; Li, Yu

    2013-01-01

    Highlights: • Using interval mathematics to describe spatial and temporal variability and parameter uncertainty. • Using fuzzy theory to quantify variability of environmental guideline values. • Using probabilistic approach to integrate interval concentrations and fuzzy environmental guideline. • Establishment of dynamic multimedia environmental integrated risk assessment framework. -- Abstract: A dynamic multimedia fuzzy-stochastic integrated environmental risk assessment approach was developed for contaminated sites management. The contaminant concentrations were simulated by a validated interval dynamic multimedia fugacity model, and different guideline values for the same contaminant were represented as a fuzzy environmental guideline. Then, the probability of violating environmental guideline (Pv) can be determined by comparison between the modeled concentrations and the fuzzy environmental guideline, and the constructed relationship between the Pvs and environmental risk levels was used to assess the environmental risk level. The developed approach was applied to assess the integrated environmental risk at a case study site in China, simulated from 1985 to 2020. Four scenarios were analyzed, including “residential land” and “industrial land” environmental guidelines under “strict” and “loose” strictness. It was found that PAH concentrations will increase steadily over time, with soil found to be the dominant sink. Source emission in soil was the leading input and atmospheric sedimentation was the dominant transfer process. The integrated environmental risks primarily resulted from petroleum spills and coke ovens, while the soil environmental risks came from coal combustion. The developed approach offers an effective tool for quantifying variability and uncertainty in the dynamic multimedia integrated environmental risk assessment and the contaminated site management

  13. A dynamic multimedia fuzzy-stochastic integrated environmental risk assessment approach for contaminated sites management

    Energy Technology Data Exchange (ETDEWEB)

    Hu, Yan; Wen, Jing-ya; Li, Xiao-li; Wang, Da-zhou; Li, Yu, E-mail: liyuxx8@hotmail.com

    2013-10-15

    Highlights: • Using interval mathematics to describe spatial and temporal variability and parameter uncertainty. • Using fuzzy theory to quantify variability of environmental guideline values. • Using probabilistic approach to integrate interval concentrations and fuzzy environmental guideline. • Establishment of dynamic multimedia environmental integrated risk assessment framework. -- Abstract: A dynamic multimedia fuzzy-stochastic integrated environmental risk assessment approach was developed for contaminated sites management. The contaminant concentrations were simulated by a validated interval dynamic multimedia fugacity model, and different guideline values for the same contaminant were represented as a fuzzy environmental guideline. Then, the probability of violating environmental guideline (Pv) can be determined by comparison between the modeled concentrations and the fuzzy environmental guideline, and the constructed relationship between the Pvs and environmental risk levels was used to assess the environmental risk level. The developed approach was applied to assess the integrated environmental risk at a case study site in China, simulated from 1985 to 2020. Four scenarios were analyzed, including “residential land” and “industrial land” environmental guidelines under “strict” and “loose” strictness. It was found that PAH concentrations will increase steadily over time, with soil found to be the dominant sink. Source emission in soil was the leading input and atmospheric sedimentation was the dominant transfer process. The integrated environmental risks primarily resulted from petroleum spills and coke ovens, while the soil environmental risks came from coal combustion. The developed approach offers an effective tool for quantifying variability and uncertainty in the dynamic multimedia integrated environmental risk assessment and the contaminated site management.

  14. Model structural uncertainty quantification and hydrogeophysical data integration using airborne electromagnetic data (Invited)

    DEFF Research Database (Denmark)

    Minsley, Burke; Christensen, Nikolaj Kruse; Christensen, Steen

    of airborne electromagnetic (AEM) data to estimate large-scale model structural geometry, i.e. the spatial distribution of different lithological units based on assumed or estimated resistivity-lithology relationships, and the uncertainty in those structures given imperfect measurements. Geophysically derived...... estimates of model structural uncertainty are then combined with hydrologic observations to assess the impact of model structural error on hydrologic calibration and prediction errors. Using a synthetic numerical model, we describe a sequential hydrogeophysical approach that: (1) uses Bayesian Markov chain...... Monte Carlo (McMC) methods to produce a robust estimate of uncertainty in electrical resistivity parameter values, (2) combines geophysical parameter uncertainty estimates with borehole observations of lithology to produce probabilistic estimates of model structural uncertainty over the entire AEM...

  15. Economic Sustainability of Organic Aloe Vera Farming in Greece under Risk and Uncertainty

    Directory of Open Access Journals (Sweden)

    Angelos Liontakis

    2016-04-01

    Full Text Available During the last decade, an encouraging environment for the restructuring and modernization of the agricultural sector has formed in Greece. The diversification into higher-value crops can be a promising option for small and average-sized farms, particularly during the current economic crisis. One of the most promising alternative crops that have been recently established in Greece is the organic Aloe vera crop. The main advantage of this crop is that it can utilize poor farmlands and, therefore, can facilitate rural development in marginal areas. This study explores the economic sustainability of the Aloe vera crop, considering the embedded risk and uncertainty. The results indicate that organic aloe farming is a promising alternative to “traditional” crops in Greece, particularly for family farms in rural areas. In contrast, this activity is not advisable to the most entrepreneurial type of farmers, unless their crop size allows economies of scales. Finally, the Stochastic Efficiency with Respect to a Function (SERF analysis associates farmers’ risk attitude with their willingness to be involved in organic Aloe vera farming. SERF analysis highlights the crucial role of farmers’ risk aversion and concludes that, above a certain level of risk aversion, farmers have no incentive to adopt this economic activity.

  16. Equilibria in the competitive retail electricity market considering uncertainty and risk management

    International Nuclear Information System (INIS)

    Kharrati, Saeed; Kazemi, Mostafa; Ehsan, Mehdi

    2016-01-01

    In a medium term planning horizon, a retailer should determine its forward contracting and pool participating strategies as well as the selling price to be offered to the customers. Considering a competitive retail electricity market, the number of clients being supplied by any retailer is a function of the selling prices and some other characteristics of all the retailers. This paper presents an equilibrium problem formulation to model the retailer's medium term decision making problem considering the strategy of other retailers. Decision making of any single retailer is formulated as a risk constraint stochastic programming problem. Uncertainty of pool prices and clients' demands is modeled with scenario generation method and CVaR (conditional value at risk) is used as the risk measure. The resulting single retailer planning problem is a quadratic constrained programming problem which is solved using the Lagrangian relaxation method and the Nash equilibrium point of the competitive retailers is achieved by successive solving of this problem for all the retailers. The performance of the proposed method is demonstrated using a realistic case study of Texas electricity market. - Highlights: • Presenting an equilibrium problem formulation for the retailer's decision-making. • Modeling consumer's retail choice behavior with an econometric model. • Managing the retailer's risk caused by rivals' strategy through CVaR. • Approximating the nonlinear price-quota curve with a piecewise-linear function. • Decomposing the nonlinear optimization problem using Lagrangian relaxation method.

  17. Uncertainty Quantification in the Reliability and Risk Assessment of Generation IV Reactors: Final Scientific/Technical Report

    International Nuclear Information System (INIS)

    Vierow, Karen; Aldemir, Tunc

    2009-01-01

    The project entitled, 'Uncertainty Quantification in the Reliability and Risk Assessment of Generation IV Reactors', was conducted as a DOE NERI project collaboration between Texas A and M University and The Ohio State University between March 2006 and June 2009. The overall goal of the proposed project was to develop practical approaches and tools by which dynamic reliability and risk assessment techniques can be used to augment the uncertainty quantification process in probabilistic risk assessment (PRA) methods and PRA applications for Generation IV reactors. This report is the Final Scientific/Technical Report summarizing the project.

  18. Uncertainty Quantification in the Reliability and Risk Assessment of Generation IV Reactors: Final Scientific/Technical Report

    Energy Technology Data Exchange (ETDEWEB)

    Vierow, Karen; Aldemir, Tunc

    2009-09-10

    The project entitled, “Uncertainty Quantification in the Reliability and Risk Assessment of Generation IV Reactors”, was conducted as a DOE NERI project collaboration between Texas A&M University and The Ohio State University between March 2006 and June 2009. The overall goal of the proposed project was to develop practical approaches and tools by which dynamic reliability and risk assessment techniques can be used to augment the uncertainty quantification process in probabilistic risk assessment (PRA) methods and PRA applications for Generation IV reactors. This report is the Final Scientific/Technical Report summarizing the project.

  19. Uncertainty and Sensitivity of Direct Economic Flood Damages: the FloodRisk Free and Open-Source Software

    Science.gov (United States)

    Albano, R.; Sole, A.; Mancusi, L.; Cantisani, A.; Perrone, A.

    2017-12-01

    The considerable increase of flood damages in the the past decades has shifted in Europe the attention from protection against floods to managing flood risks. In this context, the expected damages assessment represents a crucial information within the overall flood risk management process. The present paper proposes an open source software, called FloodRisk, that is able to operatively support stakeholders in the decision making processes with a what-if approach by carrying out the rapid assessment of the flood consequences, in terms of direct economic damage and loss of human lives. The evaluation of the damage scenarios, trough the use of the GIS software proposed here, is essential for cost-benefit or multi-criteria analysis of risk mitigation alternatives. However, considering that quantitative assessment of flood damages scenarios is characterized by intrinsic uncertainty, a scheme has been developed to identify and quantify the role of the input parameters in the total uncertainty of flood loss model application in urban areas with mild terrain and complex topography. By the concept of parallel models, the contribution of different module and input parameters to the total uncertainty is quantified. The results of the present case study have exhibited a high epistemic uncertainty on the damage estimation module and, in particular, on the type and form of the utilized damage functions, which have been adapted and transferred from different geographic and socio-economic contexts because there aren't depth-damage functions that are specifically developed for Italy. Considering that uncertainty and sensitivity depend considerably on local characteristics, the epistemic uncertainty associated with the risk estimate is reduced by introducing additional information into the risk analysis. In the light of the obtained results, it is evident the need to produce and disseminate (open) data to develop micro-scale vulnerability curves. Moreover, the urgent need to push

  20. Accounting for Epistemic Uncertainty in Mission Supportability Assessment: A Necessary Step in Understanding Risk and Logistics Requirements

    Science.gov (United States)

    Owens, Andrew; De Weck, Olivier L.; Stromgren, Chel; Goodliff, Kandyce; Cirillo, William

    2017-01-01

    Future crewed missions to Mars present a maintenance logistics challenge that is unprecedented in human spaceflight. Mission endurance – defined as the time between resupply opportunities – will be significantly longer than previous missions, and therefore logistics planning horizons are longer and the impact of uncertainty is magnified. Maintenance logistics forecasting typically assumes that component failure rates are deterministically known and uses them to represent aleatory uncertainty, or uncertainty that is inherent to the process being examined. However, failure rates cannot be directly measured; rather, they are estimated based on similarity to other components or statistical analysis of observed failures. As a result, epistemic uncertainty – that is, uncertainty in knowledge of the process – exists in failure rate estimates that must be accounted for. Analyses that neglect epistemic uncertainty tend to significantly underestimate risk. Epistemic uncertainty can be reduced via operational experience; for example, the International Space Station (ISS) failure rate estimates are refined using a Bayesian update process. However, design changes may re-introduce epistemic uncertainty. Thus, there is a tradeoff between changing a design to reduce failure rates and operating a fixed design to reduce uncertainty. This paper examines the impact of epistemic uncertainty on maintenance logistics requirements for future Mars missions, using data from the ISS Environmental Control and Life Support System (ECLS) as a baseline for a case study. Sensitivity analyses are performed to investigate the impact of variations in failure rate estimates and epistemic uncertainty on spares mass. The results of these analyses and their implications for future system design and mission planning are discussed.

  1. Optimal combined purchasing strategies for a risk-averse manufacturer under price uncertainty

    Directory of Open Access Journals (Sweden)

    Qiao Wu

    2015-09-01

    Full Text Available Purpose: The purpose of our paper is to analyze optimal purchasing strategies when a manufacturer can buy raw materials from a long-term contract supplier and a spot market under spot price uncertainty. Design/methodology/approach: This procurement model can be solved by using dynamic programming. First, we maximize the DM’s utility of the second period, obtaining the optimal contract quantity and spot quantity for the second period. Then, maximize the DM’s utility of both periods, obtaining the optimal purchasing strategy for the first period. We use a numerical method to compare the performance level of a pure spot sourcing strategy with that of a mixed strategy. Findings: Our results show that optimal purchasing strategies vary with the trend of contract prices. If the contract price falls, the total quantity purchased in period 1 will decrease in the degree of risk aversion. If the contract price increases, the total quantity purchased in period 1 will increase in the degree of risk aversion. The relationship between the optimal contract quantity and the degree of risk aversion depends on whether the expected spot price or the contract price is larger in period 2. Finally, we compare the performance levels between a combined strategy and a spot sourcing strategy. It shows that a combined strategy is optimal for a risk-averse buyer. Originality/value: It’s challenging to deal with a two-period procurement problem with risk consideration. We have obtained results of a two-period procurement problem with two sourcing options, namely contract procurement and spot purchases. Our model incorporates the buyer’s risk aversion factor and the change of contract prices, which are not addressed in early studies.

  2. [Uncertainty characterization approaches for ecological risk assessment of polycyclic aromatic hydrocarbon in Taihu Lake].

    Science.gov (United States)

    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.

  3. Unquestioned answers or unanswered questions: beliefs about science guide responses to uncertainty in climate change risk communication.

    Science.gov (United States)

    Rabinovich, Anna; Morton, Thomas A

    2012-06-01

    In two experimental studies we investigated the effect of beliefs about the nature and purpose of science (classical vs. Kuhnian models of science) on responses to uncertainty in scientific messages about climate change risk. The results revealed a significant interaction between both measured (Study 1) and manipulated (Study 2) beliefs about science and the level of communicated uncertainty on willingness to act in line with the message. Specifically, messages that communicated high uncertainty were more persuasive for participants who shared an understanding of science as debate than for those who believed that science is a search for absolute truth. In addition, participants who had a concept of science as debate were more motivated by higher (rather than lower) uncertainty in climate change messages. The results suggest that achieving alignment between the general public's beliefs about science and the style of the scientific messages is crucial for successful risk communication in science. Accordingly, rather than uncertainty always undermining the effectiveness of science communication, uncertainty can enhance message effects when it fits the audience's understanding of what science is. © 2012 Society for Risk Analysis.

  4. The influence of climate change on flood risks in France - first estimates and uncertainty analysis

    Science.gov (United States)

    Dumas, P.; Hallegatte, S.; Quintana-Seguì, P.; Martin, E.

    2013-03-01

    This paper proposes a methodology to project the possible evolution of river flood damages due to climate change, and applies it to mainland France. Its main contributions are (i) to demonstrate a methodology to investigate the full causal chain from global climate change to local economic flood losses; (ii) to show that future flood losses may change in a very significant manner over France; (iii) to show that a very large uncertainty arises from the climate downscaling technique, since two techniques with comparable skills at reproducing reference river flows give very different estimates of future flows, and thus of future local losses. The main conclusion is thus that estimating future flood losses is still out of reach, especially at local scale, but that future national-scale losses may change significantly over this century, requiring policy changes in terms of risk management and land-use planning.

  5. Radon contents in groundwater and the uncertainty related to risk assessment

    Energy Technology Data Exchange (ETDEWEB)

    Fukui, Masami [Kyoto Univ. (Japan)

    1997-02-01

    The United States has proposed 11 Bq/l (300 pCi/l) as the maximum contaminant levels (MCLs) of radon. Japan has not set up the standards for drinking water. The problems about evaluation of effects of radon on organism and MCLs of radon in groundwater and drinking water in 12 countries were reported. The local area content the high concentrations of radon, but generally it`s low levels were observed in Nigeria, China and Mexico. The countries which content high concentration of radon were Greek, Slovakia, Bornholm Island and Scotland. There are high and low concentration area in US and Japan. I proposed an uncertainty scheme on risk assessment for the exposure by radon. (S.Y.)

  6. Stochastic Risk and Uncertainty Analysis for Shale Gas Extraction in the Karoo Basin of South Africa

    Directory of Open Access Journals (Sweden)

    Abdon Atangana

    2014-01-01

    Full Text Available We made use of groundwater flow and mass transport equations to investigate the crucial potential risk of water pollution from hydraulic fracturing especially in the case of the Karoo system in South Africa. This paper shows that the upward migration of fluids will depend on the apertures of the cement cracks and fractures in the rock formation. The greater the apertures, the quicker the movement of the fluid. We presented a novel sampling method, which is the combination of the Monte Carlo and the Latin hypercube sampling. The method was used for uncertainties analysis of the apertures in the groundwater and mass transport equations. The study reveals that, in the case of the Karoo, fracking will only be successful if and only if the upward methane and fracking fluid migration can be controlled, for example, by plugging the entire fracked reservoir with cement.

  7. Irrigation, risk aversion, and water right priority under water supply uncertainty

    Science.gov (United States)

    Li, Man; Xu, Wenchao; Rosegrant, Mark W.

    2017-09-01

    This paper explores the impacts of a water right's allocative priority—as an indicator of farmers' risk-bearing ability—on land irrigation under water supply uncertainty. We develop and use an economic model to simulate farmers' land irrigation decision and associated economic returns in eastern Idaho. Results indicate that the optimal acreage of land irrigated increases with water right priority when hydroclimate risk exhibits a negatively skewed or right-truncated distribution. Simulation results suggest that prior appropriation enables senior water rights holders to allocate a higher proportion of their land to irrigation, 6 times as much as junior rights holders do, creating a gap in the annual expected net revenue reaching up to 141.4 acre-1 or 55,800 per farm between the two groups. The optimal irrigated acreage, expected net revenue, and shadow value of a water right's priority are subject to substantial changes under a changing climate in the future, where temporal variation in water supply risks significantly affects the profitability of agricultural land use under the priority-based water sharing mechanism.

  8. On the adequacy of the format proposed to communicate risk and uncertainty. Deliverable D17

    International Nuclear Information System (INIS)

    Bolado, R.

    2009-12-01

    A template was developed in the first part of the ARGONA project to communicate the risk associated to a SNF/HLW repository. As a result of two sets of meetings, the format has evolved into two different formats. The first format has been designed to address an audience composed of people with a good education level (good background in mathematics), while the second one addresses a generic audience containing lay stakeholders. Both formats are implemented as verbal presentations supported by a PowerPoint file containing graphic supporting material and include the following sections: - the concept of risk and its steering role to assess repository safety, - what is a repository and how it works (small differences between formats 1 and 2 in the level of detail), - regulatory limits, - uncertainty sources and the way to tackle them, and - key results from a Safety Case/Safety Assessment to communicate (two different levels of communication of results, which make the most important difference between formats 1 and 2). The preferred output variable to communicate risk is the peak total dose and the preferred graphic representation is the boxplot. The selection of this output variable is a conservative option that reports the worst situation in each Monte Carlo simulation which, additionally, avoids the introduction of time in the results to communicate. The boxplot has been selected because of its easy interpretation and its suitability to facilitate the comparison of results from different scenarios

  9. Assessment of Uncertainty-Based Screening Volumes for NASA Robotic LEO and GEO Conjunction Risk Assessment

    Science.gov (United States)

    Narvet, Steven W.; Frigm, Ryan C.; Hejduk, Matthew D.

    2011-01-01

    Conjunction Assessment operations require screening assets against the space object catalog by placing a pre-determined spatial volume around each asset and predicting when another object will violate that volume. The selection of the screening volume used for each spacecraft is a trade-off between observing all conjunction events that may pose a potential risk to the primary spacecraft and the ability to analyze those predicted events. If the screening volumes are larger, then more conjunctions can be observed and therefore the probability of a missed detection of a high risk conjunction event is small; however, the amount of data which needs to be analyzed increases. This paper characterizes the sensitivity of screening volume size to capturing typical orbit uncertainties and the expected number of conjunction events observed. These sensitivities are quantified in the form of a trade space that allows for selection of appropriate screen-ing volumes to fit the desired concept of operations, system limitations, and tolerable analyst workloads. This analysis will specifically highlight the screening volume determination and selection process for use in the NASA Conjunction Assessment Risk Analysis process but will also provide a general framework for other Owner / Operators faced with similar decisions.

  10. Risk Assessment and Integration Team (RAIT) Portfolio Risk Analysis Strategy

    Science.gov (United States)

    Edwards, Michelle

    2010-01-01

    Impact at management level: Qualitative assessment of risk criticality in conjunction with risk consequence, likelihood, and severity enable development of an "investment policy" towards managing a portfolio of risks. Impact at research level: Quantitative risk assessments enable researchers to develop risk mitigation strategies with meaningful risk reduction results. Quantitative assessment approach provides useful risk mitigation information.

  11. Explicitly integrating parameter, input, and structure uncertainties into Bayesian Neural Networks for probabilistic hydrologic forecasting

    KAUST Repository

    Zhang, Xuesong

    2011-11-01

    Estimating uncertainty of hydrologic forecasting is valuable to water resources and other relevant decision making processes. Recently, Bayesian Neural Networks (BNNs) have been proved powerful tools for quantifying uncertainty of streamflow forecasting. In this study, we propose a Markov Chain Monte Carlo (MCMC) framework (BNN-PIS) to incorporate the uncertainties associated with parameters, inputs, and structures into BNNs. This framework allows the structure of the neural networks to change by removing or adding connections between neurons and enables scaling of input data by using rainfall multipliers. The results show that the new BNNs outperform BNNs that only consider uncertainties associated with parameters and model structures. Critical evaluation of posterior distribution of neural network weights, number of effective connections, rainfall multipliers, and hyper-parameters shows that the assumptions held in our BNNs are not well supported. Further understanding of characteristics of and interactions among different uncertainty sources is expected to enhance the application of neural networks for uncertainty analysis of hydrologic forecasting. © 2011 Elsevier B.V.

  12. Do (un)certainty appraisal tendencies reverse the influence of emotions on risk taking in sequential tasks?

    Science.gov (United States)

    Bagneux, Virginie; Bollon, Thierry; Dantzer, Cécile

    2012-01-01

    According to the Appraisal-Tendency Framework (Han, Lerner, & Keltner, 2007), certainty-associated emotions increase risk taking compared with uncertainty-associated emotions. To date, this general effect has only been shown in static judgement and decision-making paradigms; therefore, the present study tested the effect of certainty on risk taking in a sequential decision-making task. We hypothesised that the effect would be reversed due to the kind of processing involved, as certainty is considered to encourage heuristic processing that takes into account the emotional cues arising from previous decisions, whereas uncertainty leads to more systematic processing. One hundred and one female participants were induced to feel one of three emotions (film clips) before performing a decision-making task involving risk (Game of Dice Task; Brand et al., 2005). As expected, the angry and happy participants (certainty-associated emotions) were more likely than the fearful participants (uncertainty-associated emotion) to make safe decisions (vs. risky decisions).

  13. Assessing temporal uncertainties in integrated groundwater management: an opportunity for change?

    Science.gov (United States)

    Anglade, J. A.; Billen, G.; Garnier, J.

    2013-12-01

    aquifer of about 25 years. Uncertainties about the time delay for positive results created a shock among the involved actors that motivated them to re-launch the dialogue, and enter into a new phase of the iterative decision making process to determine up to date long term strategies. Secondly, a diagnostic of recommended solutions in the existing agreements based on the soil surface balance method has raised alert about the inefficiency of agricultural best practices set up to deliver sub-root water concentration meeting the European drinking standard. According to the scientific committee, only a shift to organic farming could reconcile water and food production, with the pre-condition that this agricultural transition takes place in a territorial project which goes beyond the catchment borders. This proposal offers possibilities for re-structuring the issue for the different sides. This example underlines that integrated groundwater management could impose a time delay of several decades to cope with complex biophysical processes, construct coordination and modify individual practices. This time needed to build collaborative agreement is all the more difficult to control as part of an evolving regulatory framework.

  14. Use of screening techniques to reduce uncertainty in risk assessment at a former manufactured gas plant site

    International Nuclear Information System (INIS)

    Logan, C.M.; Walden, R.H.; Baker, S.R.; Pekar, Z.; LaKind, J.S.; MacFarlane, I.D.

    1995-01-01

    Preliminary analysis of risks from a former manufactured gas plant (MGP) site revealed six media associated with potential exposure pathways: soils, air, surface water, groundwater, estuarine sediments, and aquatic biota. Contaminants of concern (COCs) include polycyclic aromatic hydrocarbons, volatile organic hydrocarbons, metals, cyanide, and PCBs. Available chemical data, including site-specific measurements and existing data from other sources (e.g., agency monitoring programs, Chesapeake Bay Program), were evaluated for potential utility in risk assessment. Where sufficient data existed, risk calculations were performed using central tendency and reasonable maximum exposure estimates. Where site-specific data were not available, risks were estimated using conservatively high default assumptions for dose and/or exposure duration. Because of the large number of potential exposure pathways and COCs, a sensitivity analysis was conducted to determine which information most influences risk assessment outcome so that any additional data collection to reduce uncertainty can be cost-effectively targeted. The sensitivity analysis utilized two types of information: (1) the impact that uncertainty in risk input values has on output risk estimates, and (2) the potential improvement in key risk input values, and consequently output values, if better site-specific data were available. A decision matrix using both quantitative and qualitative information was developed to prioritize sampling strategies to minimize uncertainty in the final risk assessment

  15. Risk and Ambiguity in Information Seeking: Eye Gaze Patterns Reveal Contextual Behavior in Dealing with Uncertainty.

    Science.gov (United States)

    Wittek, Peter; Liu, Ying-Hsang; Darányi, Sándor; Gedeon, Tom; Lim, Ik Soo

    2016-01-01

    Information foraging connects optimal foraging theory in ecology with how humans search for information. The theory suggests that, following an information scent, the information seeker must optimize the tradeoff between exploration by repeated steps in the search space vs. exploitation, using the resources encountered. We conjecture that this tradeoff characterizes how a user deals with uncertainty and its two aspects, risk and ambiguity in economic theory. Risk is related to the perceived quality of the actually visited patch of information, and can be reduced by exploiting and understanding the patch to a better extent. Ambiguity, on the other hand, is the opportunity cost of having higher quality patches elsewhere in the search space. The aforementioned tradeoff depends on many attributes, including traits of the user: at the two extreme ends of the spectrum, analytic and wholistic searchers employ entirely different strategies. The former type focuses on exploitation first, interspersed with bouts of exploration, whereas the latter type prefers to explore the search space first and consume later. Our findings from an eye-tracking study of experts' interactions with novel search interfaces in the biomedical domain suggest that user traits of cognitive styles and perceived search task difficulty are significantly correlated with eye gaze and search behavior. We also demonstrate that perceived risk shifts the balance between exploration and exploitation in either type of users, tilting it against vs. in favor of ambiguity minimization. Since the pattern of behavior in information foraging is quintessentially sequential, risk and ambiguity minimization cannot happen simultaneously, leading to a fundamental limit on how good such a tradeoff can be. This in turn connects information seeking with the emergent field of quantum decision theory.

  16. Combination of uncertainty theories and decision-aiding methods for natural risk management in a context of imperfect information

    Science.gov (United States)

    Tacnet, Jean-Marc; Dupouy, Guillaume; Carladous, Simon; Dezert, Jean; Batton-Hubert, Mireille

    2017-04-01

    In mountain areas, natural phenomena such as snow avalanches, debris-flows and rock-falls, put people and objects at risk with sometimes dramatic consequences. Risk is classically considered as a combination of hazard, the combination of the intensity and frequency of the phenomenon, and vulnerability which corresponds to the consequences of the phenomenon on exposed people and material assets. Risk management consists in identifying the risk level as well as choosing the best strategies for risk prevention, i.e. mitigation. In the context of natural phenomena in mountainous areas, technical and scientific knowledge is often lacking. Risk management decisions are therefore based on imperfect information. This information comes from more or less reliable sources ranging from historical data, expert assessments, numerical simulations etc. Finally, risk management decisions are the result of complex knowledge management and reasoning processes. Tracing the information and propagating information quality from data acquisition to decisions are therefore important steps in the decision-making process. One major goal today is therefore to assist decision-making while considering the availability, quality and reliability of information content and sources. A global integrated framework is proposed to improve the risk management process in a context of information imperfection provided by more or less reliable sources: uncertainty as well as imprecision, inconsistency and incompleteness are considered. Several methods are used and associated in an original way: sequential decision context description, development of specific multi-criteria decision-making methods, imperfection propagation in numerical modeling and information fusion. This framework not only assists in decision-making but also traces the process and evaluates the impact of information quality on decision-making. We focus and present two main developments. The first one relates to uncertainty and imprecision

  17. A multi-reservoir based water-hydroenergy management model for identifying the risk horizon of regional resources-energy policy under uncertainties

    International Nuclear Information System (INIS)

    Zeng, X.T.; Zhang, S.J.; Feng, J.; Huang, G.H.; Li, Y.P.; Zhang, P.; Chen, J.P.; Li, K.L.

    2017-01-01

    Highlights: • A multi-reservoir system can handle water/energy deficit, flood and sediment damage. • A MWH model is developed for planning a water allocation and energy generation issue. • A mixed fuzzy-stochastic risk analysis method (MFSR) can handle uncertainties in MWH. • A hybrid MWH model can plan human-recourse-energy with a robust and effective manner. • Results ca