WorldWideScience

Sample records for projects uncertainties risk

  1. 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.

  2. 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...

  3. 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...

  4. 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.

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. Uncertainty in oil projects

    International Nuclear Information System (INIS)

    Limperopoulos, G.J.

    1995-01-01

    This report presents an oil project valuation under uncertainty by means of two well-known financial techniques: The Capital Asset Pricing Model (CAPM) and The Black-Scholes Option Pricing Formula. CAPM gives a linear positive relationship between expected rate of return and risk but does not take into consideration the aspect of flexibility which is crucial for an irreversible investment as an oil price is. Introduction of investment decision flexibility by using real options can increase the oil project value substantially. Some simple tests for the importance of uncertainty in stock market for oil investments are performed. Uncertainty in stock returns is correlated with aggregate product market uncertainty according to Pindyck (1991). The results of the tests are not satisfactory due to the short data series but introducing two other explanatory variables the interest rate and Gross Domestic Product make the situation better. 36 refs., 18 figs., 6 tabs

  11. 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.

  12. 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.

  13. 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...

  14. 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

  15. 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.

  16. 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

  17. Managing Risk and Uncertainty in Large-Scale University Research Projects

    Science.gov (United States)

    Moore, Sharlissa; Shangraw, R. F., Jr.

    2011-01-01

    Both publicly and privately funded research projects managed by universities are growing in size and scope. Complex, large-scale projects (over $50 million) pose new management challenges and risks for universities. This paper explores the relationship between project success and a variety of factors in large-scale university projects. First, we…

  18. 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.

  19. Modelling of Transport Projects Uncertainties

    DEFF Research Database (Denmark)

    Salling, Kim Bang; Leleur, Steen

    2009-01-01

    This paper proposes a new way of handling the uncertainties present in transport decision making based on infrastructure appraisals. The paper suggests to combine the principle of Optimism Bias, which depicts the historical tendency of overestimating transport related benefits and underestimating...... to supplement Optimism Bias and the associated Reference Class Forecasting (RCF) technique with a new technique that makes use of a scenario-grid. We tentatively introduce and refer to this as Reference Scenario Forecasting (RSF). The final RSF output from the CBA-DK model consists of a set of scenario......-based graphs which function as risk-related decision support for the appraised transport infrastructure project....

  20. 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

  1. Framework for managing uncertainty in property projects

    NARCIS (Netherlands)

    Reymen, I.M.M.J.; Dewulf, G.P.M.R.; Blokpoel, S.B.

    2008-01-01

    A primary task of property development (or real estate development, RED) is making assessments and managing risks and uncertainties. Property managers cope with a wide range of uncertainties, particularly in the early project phases. Although the existing literature addresses the management of

  2. Climate Projections and Uncertainty Communication.

    Science.gov (United States)

    Joslyn, Susan L; LeClerc, Jared E

    2016-01-01

    Lingering skepticism about climate change might be due in part to the way climate projections are perceived by members of the public. Variability between scientists' estimates might give the impression that scientists disagree about the fact of climate change rather than about details concerning the extent or timing. Providing uncertainty estimates might clarify that the variability is due in part to quantifiable uncertainty inherent in the prediction process, thereby increasing people's trust in climate projections. This hypothesis was tested in two experiments. Results suggest that including uncertainty estimates along with climate projections leads to an increase in participants' trust in the information. Analyses explored the roles of time, place, demographic differences (e.g., age, gender, education level, political party affiliation), and initial belief in climate change. Implications are discussed in terms of the potential benefit of adding uncertainty estimates to public climate projections. Copyright © 2015 Cognitive Science Society, Inc.

  3. Modelling of Transport Projects Uncertainties

    DEFF Research Database (Denmark)

    Salling, Kim Bang; Leleur, Steen

    2012-01-01

    This paper proposes a new way of handling the uncertainties present in transport decision making based on infrastructure appraisals. The paper suggests to combine the principle of Optimism Bias, which depicts the historical tendency of overestimating transport related benefits and underestimating...... to supplement Optimism Bias and the associated Reference Class Forecasting (RCF) technique with a new technique that makes use of a scenario-grid. We tentatively introduce and refer to this as Reference Scenario Forecasting (RSF). The final RSF output from the CBA-DK model consists of a set of scenario......-based graphs which functions as risk-related decision support for the appraised transport infrastructure project. The presentation of RSF is demonstrated by using an appraisal case concerning a new airfield in the capital of Greenland, Nuuk....

  4. Estimating the Economic Attractiveness of Investment Projects in Conditions of Uncertainty and Risk with the Use of Sensitivity Analysis

    Directory of Open Access Journals (Sweden)

    Kotsyuba Oleksiy S.

    2018-02-01

    Full Text Available The article is concerned with the methodology of economic substantiation of real investments in case of considerable lack of information on possible fluctuations of initial parameters and the resulting risk. The analysis of sensitivity as the main instrument for accounting the risk in the indicated problem situation is the focus of the presented research. In the publication, on the basis of the apparatus of interval mathematics, a set of models for comparative estimation of economic attractiveness (efficiency of alternative investment projects in conditions of uncertainty and risk is formulated, using the sensitivity analysis. The developed instrumentarium assumes both mono- and poly-interval version of the sensitivity analysis. As the risk component in the constructed models is used: in some – values of the specially developed sensitivity coefficient, in others – the worst values, which are based on the interval estimations of the partial criteria of efficiency. The sensitivity coefficient, according to the approach proposed in the publication, is the ratio of the target semi-range of variation to the increase (economy of efficiency, which is provided when the basic level of the analyzed partial criterion of economic attractiveness in comparison with some of its threshold (limit value is being reached.

  5. Deep Uncertainties in Sea-Level Rise and Storm Surge Projections: Implications for Coastal Flood Risk Management.

    Science.gov (United States)

    Oddo, Perry C; Lee, Ben S; Garner, Gregory G; Srikrishnan, Vivek; Reed, Patrick M; Forest, Chris E; Keller, Klaus

    2017-09-05

    Sea levels are rising in many areas around the world, posing risks to coastal communities and infrastructures. Strategies for managing these flood risks present decision challenges that require a combination of geophysical, economic, and infrastructure models. Previous studies have broken important new ground on the considerable tensions between the costs of upgrading infrastructure and the damages that could result from extreme flood events. However, many risk-based adaptation strategies remain silent on certain potentially important uncertainties, as well as the tradeoffs between competing objectives. Here, we implement and improve on a classic decision-analytical model (Van Dantzig 1956) to: (i) capture tradeoffs across conflicting stakeholder objectives, (ii) demonstrate the consequences of structural uncertainties in the sea-level rise and storm surge models, and (iii) identify the parametric uncertainties that most strongly influence each objective using global sensitivity analysis. We find that the flood adaptation model produces potentially myopic solutions when formulated using traditional mean-centric decision theory. Moving from a single-objective problem formulation to one with multiobjective tradeoffs dramatically expands the decision space, and highlights the need for compromise solutions to address stakeholder preferences. We find deep structural uncertainties that have large effects on the model outcome, with the storm surge parameters accounting for the greatest impacts. Global sensitivity analysis effectively identifies important parameter interactions that local methods overlook, and that could have critical implications for flood adaptation strategies. © 2017 Society for Risk Analysis.

  6. 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...

  7. 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....

  8. 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....

  9. Managing the continuum certainty, uncertainty, unpredictability in large engineering projects

    CERN Document Server

    Caron, Franco

    2013-01-01

    The brief will describe how to develop a risk analysis applied to a project , through a sequence of steps: risk management planning, risk identification, risk classification, risk assessment, risk quantification, risk response planning, risk monitoring and control, process close out and lessons learning. The project risk analysis and management process will be applied to large engineering projects, in particular related to the oil and gas industry. The brief will address the overall range of possible events affecting the project moving from certainty (project issues) through uncertainty (project risks) to unpredictability (unforeseeable events), considering both negative and positive events. Some quantitative techniques (simulation, event tree, Bayesian inference, etc.) will be used to develop risk quantification. The brief addresses a typical subject in the area of project management, with reference to large engineering projects concerning the realization of large plants and infrastructures. These projects a...

  10. 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.

  11. 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

  12. 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

  13. Uncertainties in projecting climate-change impacts in marine ecosystems

    DEFF Research Database (Denmark)

    Payne, Mark; Barange, Manuel; Cheung, William W. L.

    2016-01-01

    with a projection and building confidence in its robustness. We review how uncertainties in such projections are handled in marine science. We employ an approach developed in climate modelling by breaking uncertainty down into (i) structural (model) uncertainty, (ii) initialization and internal variability......Projections of the impacts of climate change on marine ecosystems are a key prerequisite for the planning of adaptation strategies, yet they are inevitably associated with uncertainty. Identifying, quantifying, and communicating this uncertainty is key to both evaluating the risk associated...... and highlight the opportunities and challenges associated with doing a better job. We find that even within a relatively small field such as marine science, there are substantial differences between subdisciplines in the degree of attention given to each type of uncertainty. We find that initialization...

  14. 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

  15. Uncertainties in Transport Project Evaluation: Editorial

    DEFF Research Database (Denmark)

    Salling, Kim Bang; Nielsen, Otto Anker

    2015-01-01

    University of Denmark, September 2013. The conference was held under the auspices of the projectUncertainties in transport project evaluation’ (UNITE) which is a research project (2009-2014) financed by the Danish Strategic Research Agency. UNITE was coordinated by the Department of Transport......This following special issue of the European Journal of Transport Infrastructure Research (EJTIR) containing five scientific papers is the result of an open call for papers at the 1st International Conference on Uncertainties in Transport Project Evaluation that took place at the Technical...

  16. 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.

  17. Using Options to Manage Dynamic Uncertainty in Acquisition Projects

    National Research Council Canada - National Science Library

    Ceylan, B. K; Ford, David N

    2002-01-01

    Uncertainty in acquisition projects and environments can degrade performance. Traditional project planning, management tools, and methods can effectively deal with uncertainties in relatively stable environments...

  18. Managing uncertainty for sustainability of complex projects

    DEFF Research Database (Denmark)

    Brink, Tove

    2017-01-01

    Purpose – The purpose of this paper is to reveal how management of uncertainty can enable sustainability of complex projects. Design/methodology/approach – The research was conducted from June 2014 to May 2015 using a qualitative deductive approach among operation and maintenance actors in offshore...... wind farms. The research contains a focus group interview with 11 companies, 20 individual interviews and a seminar presenting preliminary findings with 60 participants. Findings – The findings reveal the need for management of uncertainty through two different paths. First, project management needs...... to join efforts. Research limitations/implications – Further research is needed to reveal the generalisability of the findings in other complex project contexts containing “unknown unknowns”. Practical implications – The research leads to the development of a tool for uncertainty management...

  19. 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

  20. 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.

  1. 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…

  2. Value of Uncertainty: The Lost Opportunities in Large Projects

    Directory of Open Access Journals (Sweden)

    Agnar Johansen

    2016-08-01

    Full Text Available The uncertainty management theory has become well established over the last 20–30 years. However, the authors suggest that it does not fully address why opportunities often remain unexploited. Empirical studies show a stronger focus on mitigating risks than exploiting opportunities. This paper therefore addresses why so few opportunities are explored in large projects. The theory claims that risks and opportunities should be equally managed in the same process. In two surveys, conducted in six (private and public companies over a four-year period, project managers stated that uncertainty management is about managing risk and opportunities. However, two case studies from 12 projects from the same companies revealed that all of them had their main focus on risks, and most of the opportunities were left unexploited. We have developed a theoretical explanation model to shed light on this phenomena. The concept is a reflection based on findings from our empirical data up against current project management, uncertainty, risk and stakeholder literature. Our model shows that the threshold for pursuing a potential opportunity is high. If a potential opportunity should be considered, it must be extremely interesting, since it may require contract changes, and the project must abandon an earlier-accepted best solution.

  3. 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)

  4. Managing risks in the project pipeline.

    Science.gov (United States)

    2013-08-01

    This research focuses on how to manage the risks of project costs and revenue uncertainties over the long-term, and identifies significant : process improvements to ensure projects are delivered on time and as intended, thus maximizing the miles pave...

  5. 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.

  6. 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

  7. 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

  8. 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.

  9. 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

  10. 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

  11. 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.

  12. 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

  13. 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

  14. 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

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. Decision management - projects subject to uncertainty

    Directory of Open Access Journals (Sweden)

    A.E. Paterson

    2003-12-01

    Full Text Available The human mind is normally unable to grasp more than five to nine aspects relating to the same decision circumstances simultaneously. It has been demonstrated that only between four and eight variables significantly affect return on engineering projects (at the 90% level irrespective of scale. The most powerful means of isolating these significant variables is by computer simulation. This is demonstrated through the application of the interactive CASPAR programme to a simulated mining project. The significant variables are separated into controllable, influence able and uncontrollable categories for decision and control purposes since the nature of the speculative risk differs. The managerial treatment of each category is discussed.

  20. Uncertainty in project phases: A framework for organisational change management

    DEFF Research Database (Denmark)

    Kreye, Melanie; Balangalibun, Sarah

    2015-01-01

    in the early stage of the change project but was delayed until later phases. Furthermore, the sources of uncertainty were found to be predominantly within the organisation that initiated the change project and connected to the project scope. Based on these findings, propositions for future research are defined......Uncertainty is an integral challenge when managing organisational change projects (OCPs). Current literature highlights the importance of uncertainty; however, falls short of giving insights into the nature of uncertainty and suggestions for managing it. Specifically, no insights exist on how...... uncertainty develops over the different phases of OCPs. This paper presents case-based evidence on different sources of uncertainty in OCPs and how these develop over the different project phases. The results showed some surprising findings as the majority of the uncertainty did not manifest itself...

  1. Project Risk Management

    Science.gov (United States)

    Jr., R. F. Miles

    1995-01-01

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

  2. 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

  3. 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.

  4. 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.

  5. Evaluation on uncertainty sources in projecting hydrological changes over the Xijiang River basin in South China

    Science.gov (United States)

    Yuan, Fei; Zhao, Chongxu; Jiang, Yong; Ren, Liliang; Shan, Hongcui; Zhang, Limin; Zhu, Yonghua; Chen, Tao; Jiang, Shanhu; Yang, Xiaoli; Shen, Hongren

    2017-11-01

    Projections of hydrological changes are associated with large uncertainties from different sources, which should be quantified for an effective implementation of water management policies adaptive to future climate change. In this study, a modeling chain framework to project future hydrological changes and the associated uncertainties in the Xijiang River basin, South China, was established. The framework consists of three emission scenarios (ESs), four climate models (CMs), four statistical downscaling (SD) methods, four hydrological modeling (HM) schemes, and four probability distributions (PDs) for extreme flow frequency analyses. Direct variance method was adopted to analyze the manner by which uncertainty sources such as ES, CM, SD, and HM affect the estimates of future evapotranspiration (ET) and streamflow, and to quantify the uncertainties of PDs in future flood and drought risk assessment. Results show that ES is one of the least important uncertainty sources in most situations. CM, in general, is the dominant uncertainty source for the projections of monthly ET and monthly streamflow during most of the annual cycle, daily streamflow below the 99.6% quantile level, and extreme low flow. SD is the most predominant uncertainty source in the projections of extreme high flow, and has a considerable percentage of uncertainty contribution in monthly streamflow projections in July-September. The effects of SD in other cases are negligible. HM is a non-ignorable uncertainty source that has the potential to produce much larger uncertainties for the projections of low flow and ET in warm and wet seasons than for the projections of high flow. PD contributes a larger percentage of uncertainty in extreme flood projections than it does in extreme low flow estimates. Despite the large uncertainties in hydrological projections, this work found that future extreme low flow would undergo a considerable reduction, and a noticeable increase in drought risk in the Xijiang

  6. 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

  7. An assessment of uncertainty in forest carbon budget projections

    Science.gov (United States)

    Linda S. Heath; James E. Smith

    2000-01-01

    Estimates of uncertainty are presented for projections of forest carbon inventory and average annual net carbon flux on private timberland in the US using the model FORCARB. Uncertainty in carbon inventory was approximately ±9% (2000 million metric tons) of the estimated median in the year 2000, rising to 11% (2800 million metric tons) in projection year 2040...

  8. Risk assessment and management in IOR projects

    International Nuclear Information System (INIS)

    Goodyear, S.G.; Gregory, A.T.

    1994-01-01

    The application of IOR techniques is one of the investment opportunities open to Exploration and Production companies. A project will only go forward if the perceived balance between the rewards and the risks is acceptable. IOR projects may be ruled out because they are considered to involve significantly higher risks than conventional developments. Therefore, some means of evaluating the actual level of risk may be required if the full economic benefits from IOR techniques are to be realized. Risk assessment is a key element in safety cases, where a well-established methodology for quantifying risk exists. This paper discusses the extension of these methods to IOR project risk assessment. Combining reservoir and IOR technique uncertainties with their impact on project performance allows project risk to be better quantified. The results of the risk assessment are presented in terms of a risk-reward diagram that plots the probability surface for possible project outcomes as a function of NPV (reward) and exposure (risk)

  9. Real options and volume uncertainty by field development projects

    International Nuclear Information System (INIS)

    Ekern, S.; Stensland, G.

    1993-12-01

    The report concerns a study on the use of option methodology in field development projects. The report shows how the value of flexibility in the different decision processes is to be found by means of real option methodology. Particular attention is laid on the uncertainty concerning the volume of reserves and production capacity. The results from the study were based on the research project dubbed ''Use of real options in field development projects''. The project is partially connected to another project dubbed ''Decisive behaviour and alternative action under uncertainty in the petroleum sector''. Main topics cover as follow: Example with volume uncertainty; real options and volume uncertainty; gradual disclosure of uncertainty in the production; value of flexible production equipment. 33 refs., 19 figs., 17 tabs

  10. Inflated Uncertainty in Multimodel-Based Regional Climate Projections

    Science.gov (United States)

    Madsen, Marianne Sloth; Langen, Peter L.; Boberg, Fredrik; Christensen, Jens Hesselbjerg

    2017-11-01

    Multimodel ensembles are widely analyzed to estimate the range of future regional climate change projections. For an ensemble of climate models, the result is often portrayed by showing maps of the geographical distribution of the multimodel mean results and associated uncertainties represented by model spread at the grid point scale. Here we use a set of CMIP5 models to show that presenting statistics this way results in an overestimation of the projected range leading to physically implausible patterns of change on global but also on regional scales. We point out that similar inconsistencies occur in impact analyses relying on multimodel information extracted using statistics at the regional scale, for example, when a subset of CMIP models is selected to represent regional model spread. Consequently, the risk of unwanted impacts may be overestimated at larger scales as climate change impacts will never be realized as the worst (or best) case everywhere.

  11. Projected uranium measurement uncertainties for the Gas Centrifuge Enrichment Plant

    International Nuclear Information System (INIS)

    Younkin, J.M.

    1979-02-01

    An analysis was made of the uncertainties associated with the measurements of the declared uranium streams in the Portsmouth Gas Centrifuge Enrichment Plant (GCEP). The total uncertainty for the GCEP is projected to be from 54 to 108 kg 235 U/year out of a measured total of 200,000 kg 235 U/year. The systematic component of uncertainty of the UF 6 streams is the largest and the dominant contributor to the total uncertainty. A possible scheme for reducing the total uncertainty is given

  12. 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 ...

  13. 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.

  14. 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...

  15. 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.

  16. Uncertainty contributions to low flow projections in Austria

    Science.gov (United States)

    Parajka, J.; Blaschke, A. P.; Blöschl, G.; Haslinger, K.; Hepp, G.; Laaha, G.; Schöner, W.; Trautvetter, H.; Viglione, A.; Zessner, M.

    2015-11-01

    The main objective of the paper is to understand the contributions to the uncertainty in low flow projections resulting from hydrological model uncertainty and climate projection uncertainty. Model uncertainty is quantified by different parameterizations of a conceptual semi-distributed hydrologic model (TUWmodel) using 11 objective functions in three different decades (1976-1986, 1987-1997, 1998-2008), which allows disentangling the effect of modeling uncertainty and temporal stability of model parameters. Climate projection uncertainty is quantified by four future climate scenarios (ECHAM5-A1B, A2, B1 and HADCM3-A1B) using a delta change approach. The approach is tested for 262 basins in Austria. The results indicate that the seasonality of the low flow regime is an important factor affecting the performance of model calibration in the reference period and the uncertainty of Q95 low flow projections in the future period. In Austria, the calibration uncertainty in terms of Q95 is larger in basins with summer low flow regime than in basins with winter low flow regime. Using different calibration periods may result in a range of up to 60 % in simulated Q95 low flows. The low flow projections show an increase of low flows in the Alps, typically in the range of 10-30 % and a decrease in the south-eastern part of Austria mostly in the range -5 to -20 % for the period 2021-2050 relative the reference period 1976-2008. The change in seasonality varies between scenarios, but there is a tendency for earlier low flows in the Northern Alps and later low flows in Eastern Austria. In 85 % of the basins, the uncertainty in Q95 from model calibration is larger than the uncertainty from different climate scenarios. The total uncertainty of Q95 projections is the largest in basins with winter low flow regime and, in some basins, exceeds 60 %. In basins with summer low flows and the total uncertainty is mostly less than 20 %. While the calibration uncertainty dominates over climate

  17. 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

  18. Finite Project Life and Uncertainty Effects on Investment

    NARCIS (Netherlands)

    Gryglewicz, S.; Huisman, K.J.M.; Kort, P.M.

    2006-01-01

    This paper revisits the important result of the real options approach to investment under uncertainty, which states that increased uncertainty raises the value of waiting and thus decelerates investment.Typically in this literature projects are assumed to be perpetual.However, in today.s economy

  19. A hierarchical approach to multi-project planning under uncertainty

    NARCIS (Netherlands)

    Leus, R.; Wullink, Gerhard; Hans, Elias W.; Herroelen, W.

    2004-01-01

    We survey several viewpoints on the management of the planning complexity of multi-project organisations under uncertainty. A positioning framework is proposed to distinguish between different types of project-driven organisations, which is meant to aid project management in the choice between the

  20. A hierarchical approach to multi-project planning under uncertainty

    NARCIS (Netherlands)

    Hans, Elias W.; Herroelen, W.; Wullink, Gerhard; Leus, R.

    2007-01-01

    We survey several viewpoints on the management of the planning complexity of multi-project organisations under uncertainty. Based on these viewpoints we propose a positioning framework to distinguish between different types of project-driven organisations. This framework is meant to aid project

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. Uncertainty Analyses for Back Projection Methods

    Science.gov (United States)

    Zeng, H.; Wei, S.; Wu, W.

    2017-12-01

    So far few comprehensive error analyses for back projection methods have been conducted, although it is evident that high frequency seismic waves can be easily affected by earthquake depth, focal mechanisms and the Earth's 3D structures. Here we perform 1D and 3D synthetic tests for two back projection methods, MUltiple SIgnal Classification (MUSIC) (Meng et al., 2011) and Compressive Sensing (CS) (Yao et al., 2011). We generate synthetics for both point sources and finite rupture sources with different depths, focal mechanisms, as well as 1D and 3D structures in the source region. The 3D synthetics are generated through a hybrid scheme of Direct Solution Method and Spectral Element Method. Then we back project the synthetic data using MUSIC and CS. The synthetic tests show that the depth phases can be back projected as artificial sources both in space and time. For instance, for a source depth of 10km, back projection gives a strong signal 8km away from the true source. Such bias increases with depth, e.g., the error of horizontal location could be larger than 20km for a depth of 40km. If the array is located around the nodal direction of direct P-waves the teleseismic P-waves are dominated by the depth phases. Therefore, back projections are actually imaging the reflection points of depth phases more than the rupture front. Besides depth phases, the strong and long lasted coda waves due to 3D effects near trench can lead to additional complexities tested here. The strength contrast of different frequency contents in the rupture models also produces some variations to the back projection results. In the synthetic tests, MUSIC and CS derive consistent results. While MUSIC is more computationally efficient, CS works better for sparse arrays. In summary, our analyses indicate that the impact of various factors mentioned above should be taken into consideration when interpreting back projection images, before we can use them to infer the earthquake rupture physics.

  6. Managing uncertainty in flood protection planning with climate projections

    Science.gov (United States)

    Dittes, Beatrice; Špačková, Olga; Schoppa, Lukas; Straub, Daniel

    2018-04-01

    Technical flood protection is a necessary part of integrated strategies to protect riverine settlements from extreme floods. Many technical flood protection measures, such as dikes and protection walls, are costly to adapt after their initial construction. This poses a challenge to decision makers as there is large uncertainty in how the required protection level will change during the measure lifetime, which is typically many decades long. Flood protection requirements should account for multiple future uncertain factors: socioeconomic, e.g., whether the population and with it the damage potential grows or falls; technological, e.g., possible advancements in flood protection; and climatic, e.g., whether extreme discharge will become more frequent or not. This paper focuses on climatic uncertainty. Specifically, we devise methodology to account for uncertainty associated with the use of discharge projections, ultimately leading to planning implications. For planning purposes, we categorize uncertainties as either visible, if they can be quantified from available catchment data, or hidden, if they cannot be quantified from catchment data and must be estimated, e.g., from the literature. It is vital to consider the hidden uncertainty, since in practical applications only a limited amount of information (e.g., a finite projection ensemble) is available. We use a Bayesian approach to quantify the visible uncertainties and combine them with an estimate of the hidden uncertainties to learn a joint probability distribution of the parameters of extreme discharge. The methodology is integrated into an optimization framework and applied to a pre-alpine case study to give a quantitative, cost-optimal recommendation on the required amount of flood protection. The results show that hidden uncertainty ought to be considered in planning, but the larger the uncertainty already present, the smaller the impact of adding more. The recommended planning is robust to moderate changes in

  7. Managing uncertainty during r&d projects: a case study

    NARCIS (Netherlands)

    Wouters, Marc; Roorda, Berend; Gal, Ruud

    2011-01-01

    Firms make signifi cant investments in R&D projects, yet the economic return is often diffi cult to predict because of signifi cant technological and commercial uncertainty. We present an innovative and practical method for managing R&D projects, and we discuss its application to a large R&D

  8. Risk management methodology for RBMN project

    International Nuclear Information System (INIS)

    Borssatto, Maria F.B.; Tello, Cledola C.O.; Uemura, George

    2013-01-01

    RBMN Project has been developed to design, construct and commission a national repository to dispose the low- and intermediate-level radioactive wastes from the operation of nuclear power plants and other industries that use radioactive sources and materials. Risk is a characteristic of all projects. The risks arise from uncertainties due to assumptions associated with the project and the environment in which it is executed. Risk management is the method by which these uncertainties are systematically monitored to ensure that the objectives of the project will be achieved. Considering the peculiarities of the Project, that is, comprehensive scope, multidisciplinary team, apparently polemic due to the unknowing of the subject by the stake holders, especially the community, it is being developed a specific methodology for risk management of this Project. This methodology will be critical for future generations who will be responsible for the final stages of the repository. It will provide greater guarantee to the processes already implemented and will maintain a specific list of risks and solutions for this Project, ensuring safety and security of the repository throughout its life cycle that is the planned to last at least three hundred years. This paper presents the tools and processes already defined, management actions aimed at developing a culture of proactive risk in order to minimize threats to this Project and promote actions that bring opportunities to its success. The methodology is based on solid research on the subject, considering methodologies already established and globally recognized as best practices for project management. (author)

  9. 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

  10. Adaptively Addressing Uncertainty in Estuarine and Near Coastal Restoration Projects

    Energy Technology Data Exchange (ETDEWEB)

    Thom, Ronald M.; Williams, Greg D.; Borde, Amy B.; Southard, John A.; Sargeant, Susan L.; Woodruff, Dana L.; Laufle, Jeffrey C.; Glasoe, Stuart

    2005-03-01

    Restoration projects have an uncertain outcome because of a lack of information about current site conditions, historical disturbance levels, effects of landscape alterations on site development, unpredictable trajectories or patterns of ecosystem structural development, and many other factors. A poor understanding of the factors that control the development and dynamics of a system, such as hydrology, salinity, wave energies, can also lead to an unintended outcome. Finally, lack of experience in restoring certain types of systems (e.g., rare or very fragile habitats) or systems in highly modified situations (e.g., highly urbanized estuaries) makes project outcomes uncertain. Because of these uncertainties, project costs can rise dramatically in an attempt to come closer to project goals. All of the potential sources of error can be addressed to a certain degree through adaptive management. The first step is admitting that these uncertainties can exist, and addressing as many of the uncertainties with planning and directed research prior to implementing the project. The second step is to evaluate uncertainties through hypothesis-driven experiments during project implementation. The third step is to use the monitoring program to evaluate and adjust the project as needed to improve the probability of the project to reach is goal. The fourth and final step is to use the information gained in the project to improve future projects. A framework that includes a clear goal statement, a conceptual model, and an evaluation framework can help in this adaptive restoration process. Projects and programs vary in their application of adaptive management in restoration, and it is very difficult to be highly prescriptive in applying adaptive management to projects that necessarily vary widely in scope, goal, ecosystem characteristics, and uncertainties. Very large ecosystem restoration programs in the Mississippi River delta (Coastal Wetlands Planning, Protection, and Restoration

  11. 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

  12. 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.)

  13. Uncertainty Quantification for Ice Sheet Science and Sea Level Projections

    Science.gov (United States)

    Boening, C.; Schlegel, N.; Limonadi, D.; Schodlok, M.; Seroussi, H. L.; Larour, E. Y.; Watkins, M. M.

    2017-12-01

    In order to better quantify uncertainties in global mean sea level rise projections and in particular upper bounds, we aim at systematically evaluating the contributions from ice sheets and potential for extreme sea level rise due to sudden ice mass loss. Here, we take advantage of established uncertainty quantification tools embedded within the Ice Sheet System Model (ISSM) as well as sensitivities to ice/ocean interactions using melt rates and melt potential derived from MITgcm/ECCO2. With the use of these tools, we conduct Monte-Carlo style sampling experiments on forward simulations of the Antarctic ice sheet, by varying internal parameters and boundary conditions of the system over both extreme and credible worst-case ranges. Uncertainty bounds for climate forcing are informed by CMIP5 ensemble precipitation and ice melt estimates for year 2100, and uncertainty bounds for ocean melt rates are derived from a suite of regional sensitivity experiments using MITgcm. Resulting statistics allow us to assess how regional uncertainty in various parameters affect model estimates of century-scale sea level rise projections. The results inform efforts to a) isolate the processes and inputs that are most responsible for determining ice sheet contribution to sea level; b) redefine uncertainty brackets for century-scale projections; and c) provide a prioritized list of measurements, along with quantitative information on spatial and temporal resolution, required for reducing uncertainty in future sea level rise projections. Results indicate that ice sheet mass loss is dependent on the spatial resolution of key boundary conditions - such as bedrock topography and melt rates at the ice-ocean interface. This work is performed at and supported by the California Institute of Technology's Jet Propulsion Laboratory. Supercomputing time is also supported through a contract with the National Aeronautics and Space Administration's Cryosphere program.

  14. Subjective risk assessment for planning conservation projects

    International Nuclear Information System (INIS)

    Game, Edward T; Fitzsimons, James A; Lipsett-Moore, Geoff; McDonald-Madden, Eve

    2013-01-01

    Conservation projects occur under many types of uncertainty. Where this uncertainty can affect achievement of a project’s objectives, there is risk. Understanding risks to project success should influence a range of strategic and tactical decisions in conservation, and yet, formal risk assessment rarely features in the guidance or practice of conservation planning. We describe how subjective risk analysis tools can be framed to facilitate the rapid identification and assessment of risks to conservation projects, and how this information should influence conservation planning. Our approach is illustrated with an assessment of risks to conservation success as part of a conservation plan for the work of The Nature Conservancy in northern Australia. Risks can be both internal and external to a project, and occur across environmental, social, economic and political systems. Based on the relative importance of a risk and the level of certainty in its assessment we propose a series of appropriate, project level responses including research, monitoring, and active amelioration. Explicit identification, prioritization, and where possible, management of risks are important elements of using conservation resources in an informed and accountable manner. (letter)

  15. 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

  16. Partitioning uncertainty in streamflow projections under nonstationary model conditions

    Science.gov (United States)

    Chawla, Ila; Mujumdar, P. P.

    2018-02-01

    Assessing the impacts of Land Use (LU) and climate change on future streamflow projections is necessary for efficient management of water resources. However, model projections are burdened with significant uncertainty arising from various sources. Most of the previous studies have considered climate models and scenarios as major sources of uncertainty, but uncertainties introduced by land use change and hydrologic model assumptions are rarely investigated. In this paper an attempt is made to segregate the contribution from (i) general circulation models (GCMs), (ii) emission scenarios, (iii) land use scenarios, (iv) stationarity assumption of the hydrologic model, and (v) internal variability of the processes, to overall uncertainty in streamflow projections using analysis of variance (ANOVA) approach. Generally, most of the impact assessment studies are carried out with unchanging hydrologic model parameters in future. It is, however, necessary to address the nonstationarity in model parameters with changing land use and climate. In this paper, a regression based methodology is presented to obtain the hydrologic model parameters with changing land use and climate scenarios in future. The Upper Ganga Basin (UGB) in India is used as a case study to demonstrate the methodology. The semi-distributed Variable Infiltration Capacity (VIC) model is set-up over the basin, under nonstationary conditions. Results indicate that model parameters vary with time, thereby invalidating the often-used assumption of model stationarity. The streamflow in UGB under the nonstationary model condition is found to reduce in future. The flows are also found to be sensitive to changes in land use. Segregation results suggest that model stationarity assumption and GCMs along with their interactions with emission scenarios, act as dominant sources of uncertainty. This paper provides a generalized framework for hydrologists to examine stationarity assumption of models before considering them

  17. 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

  18. 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.

  19. Managing uncertainty in flood protection planning with climate projections

    Directory of Open Access Journals (Sweden)

    B. Dittes

    2018-04-01

    Full Text Available Technical flood protection is a necessary part of integrated strategies to protect riverine settlements from extreme floods. Many technical flood protection measures, such as dikes and protection walls, are costly to adapt after their initial construction. This poses a challenge to decision makers as there is large uncertainty in how the required protection level will change during the measure lifetime, which is typically many decades long. Flood protection requirements should account for multiple future uncertain factors: socioeconomic, e.g., whether the population and with it the damage potential grows or falls; technological, e.g., possible advancements in flood protection; and climatic, e.g., whether extreme discharge will become more frequent or not. This paper focuses on climatic uncertainty. Specifically, we devise methodology to account for uncertainty associated with the use of discharge projections, ultimately leading to planning implications. For planning purposes, we categorize uncertainties as either visible, if they can be quantified from available catchment data, or hidden, if they cannot be quantified from catchment data and must be estimated, e.g., from the literature. It is vital to consider the hidden uncertainty, since in practical applications only a limited amount of information (e.g., a finite projection ensemble is available. We use a Bayesian approach to quantify the visible uncertainties and combine them with an estimate of the hidden uncertainties to learn a joint probability distribution of the parameters of extreme discharge. The methodology is integrated into an optimization framework and applied to a pre-alpine case study to give a quantitative, cost-optimal recommendation on the required amount of flood protection. The results show that hidden uncertainty ought to be considered in planning, but the larger the uncertainty already present, the smaller the impact of adding more. The recommended planning is

  20. 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.

  1. 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

  2. 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)

  3. 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

  4. 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)

  5. 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.

  6. 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)

  7. Uncertainty in projected impacts of climate change on biodiversity

    DEFF Research Database (Denmark)

    Garcia, Raquel A.

    Evidence for shifts in the phenologies and distributions of species over recent decades has often been attributed to climate change. The prospect of greater and faster changes in climate during the 21st century has spurred a stream of studies anticipating future biodiversity impacts. Yet, uncerta......Evidence for shifts in the phenologies and distributions of species over recent decades has often been attributed to climate change. The prospect of greater and faster changes in climate during the 21st century has spurred a stream of studies anticipating future biodiversity impacts. Yet......, uncertainty is inherent to both projected climate changes and their effects on biodiversity, and needs to be understood before projections can be used. This thesis seeks to elucidate some of the uncertainties clouding assessments of biodiversity impacts from climate change, and explores ways to address them...... models, are shown to be affected by multiple uncertainties. Different model algorithms produce different outputs, as do alternative future climate models and scenarios of future emissions of greenhouse gases. Another uncertainty arises due to omission of species with small sample sizes, which...

  8. 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

  9. 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...

  10. Topology optimization for optical projection lithography with manufacturing uncertainties

    DEFF Research Database (Denmark)

    Zhou, Mingdong; Lazarov, Boyan Stefanov; Sigmund, Ole

    2014-01-01

    to manufacturing without additional optical proximity correction (OPC). The performance of the optimized device is robust toward the considered process variations. With the proposed unified approach, the design for photolithography is achieved by considering the optimal device performance and manufacturability......This article presents a topology optimization approach for micro-and nano-devices fabricated by optical projection lithography. Incorporating the photolithography process and the manufacturing uncertainties into the topology optimization process results in a binary mask that can be sent directly...

  11. Uncertainty of future projections of species distributions in mountainous regions.

    Directory of Open Access Journals (Sweden)

    Ying Tang

    Full Text Available Multiple factors introduce uncertainty into projections of species distributions under climate change. The uncertainty introduced by the choice of baseline climate information used to calibrate a species distribution model and to downscale global climate model (GCM simulations to a finer spatial resolution is a particular concern for mountainous regions, as the spatial resolution of climate observing networks is often insufficient to detect the steep climatic gradients in these areas. Using the maximum entropy (MaxEnt modeling framework together with occurrence data on 21 understory bamboo species distributed across the mountainous geographic range of the Giant Panda, we examined the differences in projected species distributions obtained from two contrasting sources of baseline climate information, one derived from spatial interpolation of coarse-scale station observations and the other derived from fine-spatial resolution satellite measurements. For each bamboo species, the MaxEnt model was calibrated separately for the two datasets and applied to 17 GCM simulations downscaled using the delta method. Greater differences in the projected spatial distributions of the bamboo species were observed for the models calibrated using the different baseline datasets than between the different downscaled GCM simulations for the same calibration. In terms of the projected future climatically-suitable area by species, quantification using a multi-factor analysis of variance suggested that the sum of the variance explained by the baseline climate dataset used for model calibration and the interaction between the baseline climate data and the GCM simulation via downscaling accounted for, on average, 40% of the total variation among the future projections. Our analyses illustrate that the combined use of gridded datasets developed from station observations and satellite measurements can help estimate the uncertainty introduced by the choice of baseline

  12. 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.

  13. 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

  14. 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.

  15. 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

  16. 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

  17. 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

  18. 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.

  19. 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)

  20. 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

  1. 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

  2. Risk management in nuclear projects

    International Nuclear Information System (INIS)

    Salles, Claudio J.R.

    2002-01-01

    The risk management will be defined by different aspects: danger or loss possibility, or responsibility for damage. The risk management is one stage of project management. The risk management is a continuous process of planning, identification, quantification, answer and risk control to maximize the success potential of activity. The reduction of risk is part of priority establishment. This work will indicate how introduce this important instrument in the management of nuclear projects. (author)

  3. 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

  4. On Best Practices for Risk Management in Complex Projects

    Directory of Open Access Journals (Sweden)

    Dan BENTA

    2011-01-01

    Full Text Available Risk management shall be proactive. This is one of the key preliminaries to cope with the challenges of complex projects. An overarching and consistent view on project risks and uncertainties is necessary to follow a holistic approach in project risk management. Uncertainty is inevitable since projects are unique and temporary undertakings based on assumptions and constraints, delivering project results to multiple stakeholders with different requirements. Project management can be seen as an attempt to control this uncertain environment, through the use of structured and disciplined techniques such as estimating, planning, cost control, task allocation, earned value analysis, monitoring, and review meetings. Each of these elements of project management has a role in defining or controlling inherent variability in projects. Project risk management provides approaches by which uncertainty can be understood, assessed, and managed within projects. A number of associations (e.g., Project Management Institute – PMI®, International Project Management Association – IPMA,or Network of Nordic Project Management Associations - NORDNET work constantly in acquiring, improving, and standardizing best practices in project management.Based on the industrial practice, this paper outlines strategies to identify, prioritize, and mitigate risks for achievement of project’ or organizational objectives.

  5. 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...

  6. 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.

  7. 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.)

  8. 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

  9. Uncertainty in Twenty-First-Century CMIP5 Sea Level Projections

    Science.gov (United States)

    Little, Christopher M.; Horton, Radley M.; Kopp, Robert E.; Oppenheimer, Michael; Yip, Stan

    2015-01-01

    The representative concentration pathway (RCP) simulations included in phase 5 of the Coupled Model Intercomparison Project (CMIP5) quantify the response of the climate system to different natural and anthropogenic forcing scenarios. These simulations differ because of 1) forcing, 2) the representation of the climate system in atmosphere-ocean general circulation models (AOGCMs), and 3) the presence of unforced (internal) variability. Global and local sea level rise projections derived from these simulations, and the emergence of distinct responses to the four RCPs depend on the relative magnitude of these sources of uncertainty at different lead times. Here, the uncertainty in CMIP5 projections of sea level is partitioned at global and local scales, using a 164-member ensemble of twenty-first-century simulations. Local projections at New York City (NYSL) are highlighted. The partition between model uncertainty, scenario uncertainty, and internal variability in global mean sea level (GMSL) is qualitatively consistent with that of surface air temperature, with model uncertainty dominant for most of the twenty-first century. Locally, model uncertainty is dominant through 2100, with maxima in the North Atlantic and the Arctic Ocean. The model spread is driven largely by 4 of the 16 AOGCMs in the ensemble; these models exhibit outlying behavior in all RCPs and in both GMSL and NYSL. The magnitude of internal variability varies widely by location and across models, leading to differences of several decades in the local emergence of RCPs. The AOGCM spread, and its sensitivity to model exclusion and/or weighting, has important implications for sea level assessments, especially if a local risk management approach is utilized.

  10. 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...

  11. 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...

  12. 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.)

  13. 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.

  14. 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.

  15. 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

  16. Risk Management for New Product Development Projects in Food Industry

    Directory of Open Access Journals (Sweden)

    Porananond, D.

    2014-07-01

    Full Text Available Project risk management provides a guideline for decision making in new product development (NPD projects, reducing uncertainty and increasing success rate. However, the acceptance of formal risk management applications in industry, especially for NPD projects is still in question. A study of a food conglomerate in Thailand found that only 9% of NPD projects used a systematic approach for managing risk. 61% of the projects realised the importance of risk management, while the remaining 30% did not involve risk management at all. This study aims to develop a risk management model for NPD projects in the food industry. The first section of this paper reviews the literature on risk management theory, including international standards for risk and project management (ISO31000 and ISO21500, publications for the Project Management Body of Knowledge (PMBOK, by a professional organisation the Project Management Institute (PMI, and also academic research. 182 academic papers, published between January 2002 and August 2012 were selected. The second part interviews conducted with eight NPD experts from five of the major food manufacturers in Thailand to examine their risk management practices and problems. Conclusions are made on five topics : classification of research method, project type and industrial segment, distribution of articles by region, tools & techniques for risk management and risk factors in projects. Specific requirements of risk management for NPD projects in the food industry are identified. A risk management model and the concept of risk management applications for the food industry are proposed.

  17. Consideration of Risk in PPP-Projects

    Directory of Open Access Journals (Sweden)

    Josef Zimmermann

    2014-06-01

    Full Text Available Risk management has become a core competence for companies operating in construction services. In particular regarding Real Estate Development and Construction Management the fundamental knowledge and the dedicated ap- plication of risk assessment turn out to be critical. Construction Management deals with a multitude of local and temporal issues which are unknown or only given by statistical evaluation while conducting a unique construction project within a very tight frame of budget and time. Real Estate projects focus on the predictability of profitable operation for a fairly long period in advance and are therefore subject to many more and more voluminous uncertainties. With PPP-projects a more or less complete federal task is awarded to a private company. Its extent varies but com- prises at least design, construction and operation of a real estate project, e.g. a toll road, bridge, tunnel or other infrastructural object. Durations of such contracts of- ten extend to some 20 to 30 years. In this article the applicability of traditional means of risk management is inves- tigated for the use on PPP-projects and limits of risk consequences are pointed out. Finally we come to the conclusion, that the resulting unavertable risks tend to exceed every surcharge that could be successfully placed on a market.

  18. Default risk in project finance

    NARCIS (Netherlands)

    Klompjan, R.; Wouters, Marc

    2002-01-01

    Understanding default risk in project finance is relevant to investors. This article investigates which factors are most strongly associated with the occurrence of project finance default, using data from 210 projects, of which 37 were in default. The authors found that the use of proven technology,

  19. 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

  20. 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.

  1. 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

  2. Effective Project Risk management in Micro Companies : Case study for Persona Optima Iceland ehf.

    OpenAIRE

    Bražinskaitė, Justina

    2011-01-01

    This study is meant to be a guide for micro companies regarding effective project risk management. The main purpose of this thesis is to introduce project risk management and build a user-friendly managerial model toward effective project risk management in micro companies. The research is based on a case company Persona Optima Iceland ehf. analysis. The study investigates risk management, uncertainties and risks in projects, project risk management, its models and particularities in orde...

  3. New product development projects evaluation under time uncertainty

    Directory of Open Access Journals (Sweden)

    Thiago Augusto de Oliveira Silva

    2009-12-01

    Full Text Available The development time is one of the key factors that contribute to the new product development success. In spite of that, the impact of the time uncertainty on the development has been not fully exploited, as far as decision supporting models to evaluate this kind of projects is concerned. In this context, the objective of the present paper is to evaluate the development process of new technologies under time uncertainty. We introduce a model which captures this source of uncertainty and develop an algorithm to evaluate projects that incorporates Monte Carlo Simulation and Dynamic Programming. The novelty in our approach is to thoroughly blend the stochastic time with a formal approach to the problem, which preserves the Markov property. We base our model on the distinction between the decision epoch and the stochastic time. We discuss and illustrate the applicability of our model through an empirical example.O tempo de desenvolvimento é um dos fatores-chave que contribuem para o sucesso do desenvolvimento de novos produtos. Apesar disso, o impacto da incerteza de tempo no desenvolvimento tem sido pouco considerado em modelos de avaliação e valoração deste tipo de projetos. Neste contexto, este trabalho tem como objetivo avaliar projetos de desenvolvimento de novas tecnologias mediante o tempo incerto. Introduzimos um modelo capaz de captar esta fonte de incerteza e desenvolvemos um algoritmo para a valoração do projeto que integra Simulação de Monte Carlo e Programação Dinâmica. A novidade neste trabalho é conseguir integrar meticulosamente o tempo estocástico a uma estrutura formal para tomada de decisão que preserva a propriedade de Markov. O principal ponto para viabilizar este fato é distinção entre o momento de revisão e o tempo estocástico. Ilustramos e discutimos a aplicabilidade deste modelo por meio de um exemplo empírico.

  4. 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

  5. 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.

  6. Risk-informed ranking of engineering projects

    International Nuclear Information System (INIS)

    Jyrkama, M.; Pandey, M.

    2011-01-01

    at the same time using sound probabilistic principles and models. Sensitivity analysis can also be performed instantly, by changing key model parameters, such as escalation factors, failure costs, repair times, etc. The uncertainty with each project can further be quantified through the concepts of value-at-risk (VaR) and expected shortfall (ES) given uncertainties in the model input parameters. The benefits of the developed methodology are demonstrated by a simple example application involving a small number of competing projects.

  7. 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.

  8. 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

  9. Renewable fuels: Policy effectiveness and project risk

    International Nuclear Information System (INIS)

    Leach, Andrew; Doucet, Joseph; Nickel, Trevor

    2011-01-01

    This paper examines the impact of government policy on the risk profile of a small ethanol production facility. We derive four key results from a simulation model. First, we show that commodity price risk may discourage investment in a project, despite a positive expected rate of return. Second, we show that political uncertainty may have significant impacts on the risk profile of a project. Next, we show that using only production subsidies to attract investors is expensive, since the financial assistance is paid regardless of whether the plant is operating under positive or negative financial conditions. Finally, we show that a capital grant provides a valuable complement to a subsidy, because the grant reduces the amount of value investors must put at risk, and increases their leverage thereby enhancing returns, while the subsidy mitigates commodity price risk. Our results show that compared to a subsidy-only approach, a grant and subsidy combination provides an investment environment with similar downside protection and expected returns for less than 60% of the cost. Further, we show that the two policy tools combined yield a superior investment environment to that created by an equivalent or greater total investment deployed entirely in either of the policy tools without the other. - Research highlights: → We find that government policy may increase both project returns and risk. → We find a policy of capital grants combined with an output price support to be preferred. → Price supports alone will tend to reward those plants which need them the least.

  10. Characteristics of Criteria for Selecting Investment Projects under Uncertainty

    Directory of Open Access Journals (Sweden)

    Adrian ENCIU

    2011-07-01

    Full Text Available Within financial theory and practice, there are used five main criteria for selecting investment projects: the net present value (NPV criterion, the internal rate of return (IRR criterion, the return term (RT criterion, the profitability ratio (PR criterion and the supplementary return (SR criterion. The assay will emphasize several new properties of said indexes for investment assessment, having as starting point the hypotheses of (approximately normal repartition of cash-flows generated by an investment project. The obtained results point to the fact that the NPV indexes (the analysis of this criterion was carried out in the article “The NPV Criterion for Valuing Investments under Uncertainty”, Daniel Armeanu, Leonard Lache, Economic Computation and Economic Cybernetics Studies and Research no. 4/2009, pp. 133-143, IRR, PR, RT and SR register normal repartitions, therefore simplifying the investment analysis under economic uncertainty, by the capacity of building confidence intervals and assessing probabilities for the inferior limits of said investment assessment indexes.

  11. 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

  12. RISK MANAGEMENT USING PROJECT RECON

    Science.gov (United States)

    2016-11-28

    centralized database . • Project Recon (formerly Risk Recon) is designed to be used by all Program Management Offices, Integrated Project Teams and any...Create growth plans to proactively capture benefits • Customize reports to group opportunities by programmatic, technical, business, contracting, and

  13. 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.

  14. 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.

  15. Girassol I. Girassol development: project challenges and reservoir uncertainties

    Energy Technology Data Exchange (ETDEWEB)

    Bancelin, J.P.; Pelleau, R.; Serceau, A. [TotalFinaElf, la Defense 6, 92 - Courbevoie (France)

    2002-10-01

    The Girassol Field is located 210 km northwest of Luanda, the Angolan capital, and about 150 km from shore. Girassol was the first discovery made in the prolific Block 17. This was followed by Dalia, Rosa, Lirio, Jasmim, Cravo, Orchidea, etc. April 1996: Girassol field is discovered on Block 17 in deep waters, offshore Angola. July 1998: The Girassol development project is approved by all parties. December 2001: Less than three and a half years after approval, Girassol comes on-stream. By the end of 2001, daily production is 100000 b/d with the production plateau of 200000 b/d to be reached by April 2002. The reservoir, located in 1,400 m water depth, is large (10 km by 14 km). Estimated oil in place is 1,550 mmbbls with recoverable reserves put at 725 mmbbls. The oil quality of 32 deg API is close to Brent specifications. The Girassol development scheme is based on 39 sub-sea wells - 23 oil producers, 14 water injectors and two gas injectors. The field will be developed in two phases: the first phase, completed in December 2001, includes 11 wells - eight oil producers, two water injectors and one gas injector. The second phase development is ongoing and will be completed mid-2003. The overall investment for the two phases of the Girassol development is US$ 2.8 bn. The Girassol project team had to fulfill three main objectives: first priority was given to technical quality; second priority was to closely monitor the development budget and contain the final cost; third priority was to achieve first oil as early as possible. Describe the Girassol reservoir and explain the main subsurface uncertainties; describe the selected development scheme; explain Girassol's major challenges; describe the contractual strategy information on cost, schedule and the project organisation are given. (authors)

  16. Technology Uncertainty and Project Managers' Information Sharing - A comparative case study of two new product development projects

    DEFF Research Database (Denmark)

    Jepsen, Lisbeth Brøde; Dietrich, Perttu

    2014-01-01

    uncertainty during various phases of new product development (NPD) projects. In this study, we compare two longitudinal NPD sub-projects that differ in uncertainty within the same large NPD project, in which the data source is the complete email exchange between a project manager and various actors...... (consisting of 3979 emails). The results show high levels of information sharing with the customer in both the early and late phases of high uncertainty. Interestingly, in the low uncertainty project, information sharing with the production department and the supplier is higher during the late phase...... of the NPD project. Unexpectedly, in both sub-projects, the project manager shares information with a wider range of both intra- and inter-organization actors in the early phases of the projects than in the late phases....

  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. 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...

  20. Development of funding project risk management tools.

    Science.gov (United States)

    2013-11-01

    Funding project risk management is a process for identifying, assessing, and prioritizing project funding risks. To plan to : minimize or eliminate the impact of negative events, one must identify what projects have higher risk to respond to potentia...

  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. 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)

  3. Stakeholder-driven multi-attribute analysis for energy project selection under uncertainty

    International Nuclear Information System (INIS)

    Read, Laura; Madani, Kaveh; Mokhtari, Soroush; Hanks, Catherine

    2017-01-01

    In practice, selecting an energy project for development requires balancing criteria and competing stakeholder priorities to identify the best alternative. Energy source selection can be modeled as multi-criteria decision-maker problems to provide quantitative support to reconcile technical, economic, environmental, social, and political factors with respect to the stakeholders' interests. Decision making among these complex interactions should also account for the uncertainty present in the input data. In response, this work develops a stochastic decision analysis framework to evaluate alternatives by involving stakeholders to identify both quantitative and qualitative selection criteria and performance metrics which carry uncertainties. The developed framework is illustrated using a case study from Fairbanks, Alaska, where decision makers and residents must decide on a new source of energy for heating and electricity. We approach this problem in a five step methodology: (1) engaging experts (role players) to develop criteria of project performance; (2) collecting a range of quantitative and qualitative input information to determine the performance of each proposed solution according to the selected criteria; (3) performing a Monte-Carlo analysis to capture uncertainties given in the inputs; (4) applying multi-criteria decision-making, social choice (voting), and fallback bargaining methods to account for three different levels of cooperation among the stakeholders; and (5) computing an aggregate performance index (API) score for each alternative based on its performance across criteria and cooperation levels. API scores communicate relative performance between alternatives. In this way, our methodology maps uncertainty from the input data to reflect risk in the decision and incorporates varying degrees of cooperation into the analysis to identify an optimal and practical alternative. - Highlights: • We develop an applicable stakeholder-driven framework for

  4. 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.

  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. 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)

  7. 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...

  8. Feedback from uncertainties propagation research projects conducted in different hydraulic fields: outcomes for engineering projects and nuclear safety assessment.

    Science.gov (United States)

    Bacchi, Vito; Duluc, Claire-Marie; Bertrand, Nathalie; Bardet, Lise

    2017-04-01

    different contexts, as river flooding on the Rhône River (Nguyen et al., 2015) and on the Garonne River, for the studying of local rainfall (Abily et al., 2016) or for tsunami generation, in the framework of the ANR-research project TANDEM. The feedback issued from these previous studies is analyzed (technical problems, limitations, interesting results, etc…) and the perspectives and a discussion on how a probabilistic approach of uncertainties should improve the actual deterministic methodology for risk assessment (also for other engineering applications) will be finally given.

  9. 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...

  10. Risk Management of NASA Projects

    Science.gov (United States)

    Sarper, Hueseyin

    1997-01-01

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

  11. 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

  12. 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.)

  13. 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.

  14. 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.

  15. 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.

  16. 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

  17. 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.

  18. 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.

  19. Decomposing the uncertainty in climate impact projections of Dynamic Vegetation Models: a test with the forest models LANDCLIM and FORCLIM

    Science.gov (United States)

    Cailleret, Maxime; Snell, Rebecca; von Waldow, Harald; Kotlarski, Sven; Bugmann, Harald

    2015-04-01

    Different levels of uncertainty should be considered in climate impact projections by Dynamic Vegetation Models (DVMs), particularly when it comes to managing climate risks. Such information is useful to detect the key processes and uncertainties in the climate model - impact model chain and may be used to support recommendations for future improvements in the simulation of both climate and biological systems. In addition, determining which uncertainty source is dominant is an important aspect to recognize the limitations of climate impact projections by a multi-model ensemble mean approach. However, to date, few studies have clarified how each uncertainty source (baseline climate data, greenhouse gas emission scenario, climate model, and DVM) affects the projection of ecosystem properties. Focusing on one greenhouse gas emission scenario, we assessed the uncertainty in the projections of a forest landscape model (LANDCLIM) and a stand-scale forest gap model (FORCLIM) that is caused by linking climate data with an impact model. LANDCLIM was used to assess the uncertainty in future landscape properties of the Visp valley in Switzerland that is due to (i) the use of different 'baseline' climate data (gridded data vs. data from weather stations), and (ii) differences in climate projections among 10 GCM-RCM chains. This latter point was also considered for the projections of future forest properties by FORCLIM at several sites along an environmental gradient in Switzerland (14 GCM-RCM chains), for which we also quantified the uncertainty caused by (iii) the model chain specific statistical properties of the climate time-series, and (iv) the stochasticity of the demographic processes included in the model, e.g., the annual number of saplings that establish, or tree mortality. Using methods of variance decomposition analysis, we found that (i) The use of different baseline climate data strongly impacts the prediction of forest properties at the lowest and highest, but

  20. 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.

  1. Role of uncertainty in the basalt waste isolation project

    International Nuclear Information System (INIS)

    Knepp, A.J.; Dahlem, D.H.

    1989-01-01

    The current national Civilian Radioactive Waste Management (CRWM) Program to select a mined geologic repository will likely require the extensive use of probabilistic techniques to quantify uncertainty in predictions of repository isolation performance. Performance of nonhomogeneous, geologic hydrologic, and chemical systems must be predicted over time frames of thousands of years and therefore will likely contain significant uncertainty. A qualitative assessment of our limited ability to interrogate the site in a nondestructive manner coupled with the early stage of development in the pertinent geosciences support this statement. The success of the approach to incorporate what currently appears to be an appreciable element of uncertainty into the predictions of repository performance will play an important role in acquiring a license to operate and in establishing the level of safety associated with the concept of long-term geologic storage of nuclear waste. This paper presents a brief background on the Hanford Site and the repository program, references the sources that establish the legislative requirement to quantify uncertainties in performance predictions, and summarized the present and future program at the Hanford Site in this area. The decision to quantify significant sources of uncertainties has had a major impact on the direction of the site characterization program here at Hanford. The paper concludes with a number of observations on the impacts of this decision

  2. 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.

  3. 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 ...

  4. 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

  5. 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

  6. 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.

  7. Risk Evaluation on UHV Power Transmission Construction Project Based on AHP and FCE Method

    OpenAIRE

    Huiru Zhao; Sen Guo

    2014-01-01

    Ultra high voltage (UHV) power transmission construction project is a high-tech power grid construction project which faces many risks and uncertainty. Identifying the risk of UHV power transmission construction project can help mitigate the risk loss and promote the smooth construction. The risk evaluation on “Zhejiang-Fuzhou” UHV power transmission construction project was performed based on analytic hierarchy process (AHP) and fuzzy comprehensive evaluation (FCE) method in this paper. Afte...

  8. 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

  9. Risk assessment for construction projects of transport infrastructure objects

    Science.gov (United States)

    Titarenko, Boris

    2017-10-01

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

  10. Integrated project risk management of nuclear power projects

    International Nuclear Information System (INIS)

    Wang Xiaohui; Xu Yuanhui

    2001-01-01

    The concept and the features of risks in nuclear power projects are introduced, and in terms of nuclear power projects' own features, the Nuclear Power Project Integrated Risk Management Model is presented. The identification, estimation, evaluation, response plan development, control of risks and the theoretical basis of risk management are discussed. The model has feedback and control functions in order to control and manage the risks dynamically

  11. Uncertainties in the Dutch Reference Projections. Background information for the report 'Reference Projections Energy and Emissions 2005-2020'

    International Nuclear Information System (INIS)

    Seebregts, A.J.; Gijsen, A.

    2005-09-01

    The Dutch targets for greenhouse gases, ammonia and non-methane VOCs will likely be met in 2010 according to our calculations from an uncertainty analysis in the framework of the project on Reference Projections for energy, climate and acidifying emissions. However, it is unlikely that the targets for sulphur dioxide and nitrogen oxide will be attained This study distinguished between sources of uncertainty in the input variables of the Reference Projections. These sources were quantified with the help of the 'Guidance for Uncertainty Assessment and Communication' and 'expert judgement'. With the aid of a statistical Monte Carlo analysis, margins and probability distributions were determined for the most important outcomes of the Reference Projections. These probability distributions led, for example, to several statements being made on the chances of meeting certain targets. The use of 'Guidance for Uncertainty Assessment and Communication' was also evaluated [nl

  12. Elusive drought: uncertainty in observed trends and short- and long-term CMIP5 projections

    Directory of Open Access Journals (Sweden)

    B. Orlowsky

    2013-05-01

    of uncertainty. Our results highlight the inherent difficulty of drought quantification and the considerable likelihood range of drought projections, but also indicate regions where drought is consistently found to increase. In other regions, wide likelihood range should not be equated with low drought risk, since potential scenarios include large drought increases in key agricultural and ecosystem regions.

  13. 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.

  14. 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.

  15. 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.

  16. Uncertainty in greenhouse-gas emission scenario projections: Experiences from Mexico and South Africa

    DEFF Research Database (Denmark)

    Puig, Daniel

    This report outlines approaches to quantify the uncertainty associated with national greenhouse-gas emission scenario projections. It does so by describing practical applications of those approaches in two countries – Mexico and South Africa. The goal of the report is to promote uncertainty...

  17. 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

  18. 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

  19. 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.

  20. The strategy of parallel approaches in projects with unforeseeable uncertainty: the Manhattan case in retrospect

    OpenAIRE

    Sylvain Lenfle

    2011-01-01

    International audience; This paper discusses the literature on the management of projects with unforeseeable uncertainty. Recent work demonstrates that, when confronted with unforeseeable uncertainties, managers can adopt either a learning, trial-and-error-based strategy, or a parallel approach. In the latter, different solutions are developed in parallel and the best one is chosen when enough information becomes available. Studying the case of the Manhattan Project, which historically exempl...

  1. Process-based project proposal risk management

    Directory of Open Access Journals (Sweden)

    Alok Kumar

    2016-12-01

    Full Text Available We all are aware of the organizational omnipresence. Projects within the organizations are ubiquitous too. Projects achieve their goals successfully if they are planned, scheduled, controlled and implemented well. The project lifecycle of initiating, planning, scheduling, controlling and implementing are very well-planned by project managers and the organizations. Successful projects have well-developed risk management plans to deal with situations impacting projects. Like any other organisation, a university does try to access funds for different purposes too. For such organisations, running a project is not the issue, rather getting a project proposal approved to fund a project is the key. Project proposal processing is done by the nodal office in every organisation. Usually, these nodal offices help in administration and submission of a project proposal for accessing funds. Seldom are these nodal project offices within the organizations facilitate a project proposal approval by proactively reaching out to the project managers. And as project managers prepare project proposals, little or no attention is made to prepare a project proposal risk plan so as to maximise project acquisition. Risk plans are submitted while preparing proposals but these risk plans cater to a requirement to address actual projects upon approval. Hence, a risk management plan for project proposal is either missing or very little effort is made to treat the risks inherent in project acquisition. This paper is an integral attempt to highlight the importance of risk treatment for project proposal stage as an extremely important step to preparing the risk management plan made for projects corresponding to their lifecycle phases. Several tools and techniques have been proposed in the paper to help and guide either the project owner (proposer or the main organisational unit responsible for project management. Development of tools and techniques to further enhance project

  2. Risk management in product innovation projects

    NARCIS (Netherlands)

    Halman, J.I.M.; Keizer, J.A.

    1993-01-01

    In product innovation projects risk management has become increasingly important. Technological and commercial developments ask for effective and efficient product innovation. Systematic diagnosing and management of risks can help to make product innovation projects successful. In this paper a

  3. Streamlining project delivery through risk analysis.

    Science.gov (United States)

    2015-08-01

    Project delivery is a significant area of concern and is subject to several risks throughout Plan Development : Process (PDP). These risks are attributed to major areas of project development, such as environmental : analysis, right-of-way (ROW) acqu...

  4. Systems approach to project risk management

    Energy Technology Data Exchange (ETDEWEB)

    Kindinger, J. P. (John P.)

    2002-01-01

    This paper describes the need for better performance in the planning and execution of projects and examines the capabilities of two different project risk analysis methods for improving project performance. A quantitative approach based on concepts and tools adopted from the disciplines of systems analysis, probabilistic risk analysis, and other fields is advocated for managing risk in large and complex research & development projects. This paper also provides an overview of how this system analysis approach for project risk management is being used at Los Alamos National Laboratory along with examples of quantitative risk analysis results and their application to improve project performance.

  5. Risks management in project planning

    OpenAIRE

    Stankevičiūtė, Roberta

    2017-01-01

    Project management consists of two very important aspects – managing the right project and managing the project right. To know that you are managing the right project you need to ensure that your project is based on an actual requirement and that your project goal is relevant and beneficial. And professional project planning assists in managing project the right way. The project planning process is very time consuming and is one of the most important parts of the project management process. T...

  6. Cost benchmarking of railway projects in Europe – dealing with uncertainties in cost estimates

    DEFF Research Database (Denmark)

    Trabo, Inara

    Past experiences in the construction of high-speed railway projects demontrate either positive or negative financial outcomes of the actual project’s budget. Usually some uncertainty value is included into initial budget calculations. Uncertainty is related to the increase of material prices...... per main cost drivers were compared and analyzed. There were observed nine railway projects, comparable to the Copenhagen-Ringsted project. The results of this comparison provided a certain overview on the cost range in different budget disciplines. The Copenhagen-Ringsted project is positioned right...

  7. Managing Uncertainty and Conflict in IT Project Portfolio Management

    DEFF Research Database (Denmark)

    Pedersen, Keld; Agger Nielsen, Jeppe

    2011-01-01

    Maximizing the outcome of IT project investments has been a major concern for years. Several approaches have been suggested one of them being Project Portfolio Management (PPM). Even though PPM offers valuable techniques for aligning IT project portfolios with organizational needs and maximizing...... rational decision-making ideals and incorporating other decision-making styles more aligned with decision-making practices in organizations might ease PPM implementation and improve the outcome of systematic PPM efforts. The research is based upon a multisite case study from public sector organizations...

  8. 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.

  9. Uncertainty in projected climate change arising from uncertain fossil-fuel emission factors

    Science.gov (United States)

    Quilcaille, Y.; Gasser, T.; Ciais, P.; Lecocq, F.; Janssens-Maenhout, G.; Mohr, S.

    2018-04-01

    Emission inventories are widely used by the climate community, but their uncertainties are rarely accounted for. In this study, we evaluate the uncertainty in projected climate change induced by uncertainties in fossil-fuel emissions, accounting for non-CO2 species co-emitted with the combustion of fossil-fuels and their use in industrial processes. Using consistent historical reconstructions and three contrasted future projections of fossil-fuel extraction from Mohr et al we calculate CO2 emissions and their uncertainties stemming from estimates of fuel carbon content, net calorific value and oxidation fraction. Our historical reconstructions of fossil-fuel CO2 emissions are consistent with other inventories in terms of average and range. The uncertainties sum up to a ±15% relative uncertainty in cumulative CO2 emissions by 2300. Uncertainties in the emissions of non-CO2 species associated with the use of fossil fuels are estimated using co-emission ratios varying with time. Using these inputs, we use the compact Earth system model OSCAR v2.2 and a Monte Carlo setup, in order to attribute the uncertainty in projected global surface temperature change (ΔT) to three sources of uncertainty, namely on the Earth system’s response, on fossil-fuel CO2 emission and on non-CO2 co-emissions. Under the three future fuel extraction scenarios, we simulate the median ΔT to be 1.9, 2.7 or 4.0 °C in 2300, with an associated 90% confidence interval of about 65%, 52% and 42%. We show that virtually all of the total uncertainty is attributable to the uncertainty in the future Earth system’s response to the anthropogenic perturbation. We conclude that the uncertainty in emission estimates can be neglected for global temperature projections in the face of the large uncertainty in the Earth system response to the forcing of emissions. We show that this result does not hold for all variables of the climate system, such as the atmospheric partial pressure of CO2 and the

  10. 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

  11. 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

  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. Investigation of Back-Projection Uncertainties with M6 Earthquakes

    Science.gov (United States)

    Fan, W.; Shearer, P. M.

    2017-12-01

    We investigate possible biasing effects of inaccurate timing corrections on teleseismic P-wave back-projection imaging of large earthquake ruptures. These errors occur because empirically-estimated time shifts based on aligning P-wave first arrivals are exact only at the hypocenter and provide approximate corrections for other parts of the rupture. Using the Japan subduction zone as a test region, we analyze 46 M6-7 earthquakes over a ten-year period, including many aftershocks of the 2011 M9 Tohoku earthquake, performing waveform cross-correlation of their initial P-wave arrivals to obtain hypocenter timing corrections to global seismic stations. We then compare back-projection images for each earthquake using its own timing corrections with those obtained using the time corrections for other earthquakes. This provides a measure of how well sub-events can be resolved with back-projection of a large rupture as a function of distance from the hypocenter. Our results show that back-projection is generally very robust and that sub-event location errors average about 20 km across the entire study region ( 700 km). The back-projection coherence loss and location errors do not noticeably converge to zero even when the event pairs are very close (<20 km). This indicates that most of the timing differences are due to 3D structure close to each of the hypocenter regions, which limits the effectiveness of attempts to refine back-projection images using aftershock calibration, at least in this region.

  15. General risks for tunnelling projects: An overview

    Science.gov (United States)

    Siang, Lee Yong; Ghazali, Farid E. Mohamed; Zainun, Noor Yasmin; Ali, Roslinda

    2017-10-01

    Tunnels are indispensable when installing new infrastructure as well as when enhancing the quality of existing urban living due to their unique characteristics and potential applications. Over the past few decades, there has been a significant increase in the building of tunnels, world-wide. Tunnelling projects are complex endeavors, and risk assessment for tunnelling projects is likewise a complex process. Risk events are often interrelated. Occurrence of a technical risk usually carries cost and schedule consequences. Schedule risks typically impact cost escalation and project overhead. One must carefully consider the likelihood of a risk's occurrence and its impact in the context of a specific set of project conditions and circumstances. A project's goals, organization, and environment impacts in the context of a specific set of project conditions and circumstances. Some projects are primarily schedule driven; other projects are primarily cost or quality driven. Whether a specific risk event is perceived fundamentally as a cost risk or a schedule risk is governed by the project-specific context. Many researchers have pointed out the significance of recognition and control of the complexity, and risks of tunnelling projects. Although all general information on a project such as estimated duration, estimated cost, and stakeholders can be obtained, it is still quite difficult to accurately understand, predict and control the overall situation and development trends of the project, leading to the risks of tunnelling projects. This paper reviews all the key risks for tunnelling projects from several case studies that have been carried out by other researchers. These risks have been identified and reviewed in this paper. As a result, the current risk management plan in tunnelling projects can be enhanced by including all these reviewed risks as key information.

  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. 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

  19. Prototype Biology-Based Radiation Risk Module Project

    Science.gov (United States)

    Terrier, Douglas; Clayton, Ronald G.; Patel, Zarana; Hu, Shaowen; Huff, Janice

    2015-01-01

    Biological effects of space radiation and risk mitigation are strategic knowledge gaps for the Evolvable Mars Campaign. The current epidemiology-based NASA Space Cancer Risk (NSCR) model contains large uncertainties (HAT #6.5a) due to lack of information on the radiobiology of galactic cosmic rays (GCR) and lack of human data. The use of experimental models that most accurately replicate the response of human tissues is critical for precision in risk projections. Our proposed study will compare DNA damage, histological, and cell kinetic parameters after irradiation in normal 2D human cells versus 3D tissue models, and it will use a multi-scale computational model (CHASTE) to investigate various biological processes that may contribute to carcinogenesis, including radiation-induced cellular signaling pathways. This cross-disciplinary work, with biological validation of an evolvable mathematical computational model, will help reduce uncertainties within NSCR and aid risk mitigation for radiation-induced carcinogenesis.

  20. Toolbox for uncertainty; Introduction of adaptive heuristics as strategies for project decision making

    DEFF Research Database (Denmark)

    Stingl, Verena; Geraldi, Joana

    2017-01-01

    This article presents adaptive heuristics as an alternative approach to navigate uncertainty in project decision-making. Adaptive heuristic are a class of simple decision strategies that have received only scant attention in project studies. Yet, they can strive in contexts of high uncertainty...... they are ‘ecologically rational’. The model builds on the individual definitions of ecological rationality and organizes them according to two types of uncertainty (‘knowable’ and ‘unknowable’). Decision problems and heuristics are furthermore grouped by decision task (choice and judgement). The article discusses...... and limited information, which are the typical project decision context. This article develops a conceptual model that supports a systematic connection between adaptive heuristics and project decisions. Individual adaptive heuristics succeed only in specific decision environments, in which...

  1. 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.

  2. Impacts of Process and Prediction Uncertainties on Projected Hanford Waste Glass Amount

    Energy Technology Data Exchange (ETDEWEB)

    Gervasio, V.; Kim, D. S.; Vienna, J. D.; Kruger, A. A.

    2018-03-08

    Analyses were performed to evaluate the impacts of using the advanced glass models, constraints (Vienna et al. 2016), and uncertainty descriptions on projected Hanford glass mass. The maximum allowable waste oxide loading (WOL) was estimated for waste compositions while simultaneously satisfying all applicable glass property and composition constraints with sufficient confidence. Different components of prediction and composition/process uncertainties were systematically included in the calculations to evaluate their impacts on glass mass. The analyses estimated the production of 23,360 MT of immobilized high-level waste (IHLW) glass when no uncertainties were taken into account. Accounting for prediction and composition/process uncertainties resulted in 5.01 relative percent increase in estimated glass mass of 24,531 MT. Roughly equal impacts were found for prediction uncertainties (2.58 RPD) and composition/process uncertainties (2.43 RPD). The immobilized low-activity waste (ILAW) mass was predicted to be 282,350 MT without uncertainty and with waste loading “line” rules in place. Accounting for prediction and composition/process uncertainties resulted in only 0.08 relative percent increase in estimated glass mass of 282,562 MT. Without application of line rules the glass mass decreases by 10.6 relative percent (252,490 MT) for the case with no uncertainties. Addition of prediction uncertainties increases glass mass by 1.32 relative percent and the addition of composition/process uncertainties increase glass mass by an additional 7.73 relative percent (9.06 relative percent increase combined). The glass mass estimate without line rules (275,359 MT) was 2.55 relative percent lower than that with the line rules (282,562 MT), after accounting for all applicable uncertainties.

  3. Impacts of Process and Prediction Uncertainties on Projected Hanford Waste Glass Amount

    Energy Technology Data Exchange (ETDEWEB)

    Gervasio, Vivianaluxa [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Vienna, John D. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Kim, Dong-Sang [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Kruger, Albert A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2018-02-19

    Analyses were performed to evaluate the impacts of using the advanced glass models, constraints (Vienna et al. 2016), and uncertainty descriptions on projected Hanford glass mass. The maximum allowable WOL was estimated for waste compositions while simultaneously satisfying all applicable glass property and composition constraints with sufficient confidence. Different components of prediction and composition/process uncertainties were systematically included in the calculations to evaluate their impacts on glass mass. The analyses estimated the production of 23,360 MT of IHLW glass when no uncertainties were taken into accound. Accounting for prediction and composition/process uncertainties resulted in 5.01 relative percent increase in estimated glass mass 24,531 MT. Roughly equal impacts were found for prediction uncertainties (2.58 RPD) and composition/process uncertainties (2.43 RPD). ILAW mass was predicted to be 282,350 MT without uncertainty and with weaste loading “line” rules in place. Accounting for prediction and composition/process uncertainties resulted in only 0.08 relative percent increase in estimated glass mass of 282,562 MTG. Without application of line rules the glass mass decreases by 10.6 relative percent (252,490 MT) for the case with no uncertainties. Addition of prediction uncertainties increases glass mass by 1.32 relative percent and the addition of composition/process uncertainties increase glass mass by an additional 7.73 relative percent (9.06 relative percent increase combined). The glass mass estimate without line rules (275,359 MT) was 2.55 relative percent lower than that with the line rules (282,562 MT), after accounting for all applicable uncertainties.

  4. 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

  5. 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

  6. 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...

  7. Project Scheduling Based on Risk of Gas Transmission Pipe

    Science.gov (United States)

    Silvianita; Nurbaity, A.; Mulyadi, Y.; Suntoyo; Chamelia, D. M.

    2018-03-01

    The planning of a project has a time limit on which must be completed before or right at a predetermined time. Thus, in a project planning, it is necessary to have scheduling management that is useful for completing a project to achieve maximum results by considering the constraints that will exists. Scheduling management is undertaken to deal with uncertainties and negative impacts of time and cost in project completion. This paper explains about scheduling management in gas transmission pipeline project Gresik-Semarang to find out which scheduling plan is most effectively used in accordance with its risk value. Scheduling management in this paper is assissted by Microsoft Project software to find the critical path of existing project scheduling planning data. Critical path is the longest scheduling path with the fastest completion time. The result is found a critical path on project scheduling with completion time is 152 days. Furthermore, the calculation of risk is done by using House of Risk (HOR) method and it is found that the critical path has a share of 40.98 percent of all causes of the occurence of risk events that will be experienced.

  8. Projecting future air pollution-related mortality under a changing climate: progress, uncertainties and research needs.

    Science.gov (United States)

    Madaniyazi, Lina; Guo, Yuming; Yu, Weiwei; Tong, Shilu

    2015-02-01

    Climate change may affect mortality associated with air pollutants, especially for fine particulate matter (PM2.5) and ozone (O3). Projection studies of such kind involve complicated modelling approaches with uncertainties. We conducted a systematic review of researches and methods for projecting future PM2.5-/O3-related mortality to identify the uncertainties and optimal approaches for handling uncertainty. A literature search was conducted in October 2013, using the electronic databases: PubMed, Scopus, ScienceDirect, ProQuest, and Web of Science. The search was limited to peer-reviewed journal articles published in English from January 1980 to September 2013. Fifteen studies fulfilled the inclusion criteria. Most studies reported that an increase of climate change-induced PM2.5 and O3 may result in an increase in mortality. However, little research has been conducted in developing countries with high emissions and dense populations. Additionally, health effects induced by PM2.5 may dominate compared to those caused by O3, but projection studies of PM2.5-related mortality are fewer than those of O3-related mortality. There is a considerable variation in approaches of scenario-based projection researches, which makes it difficult to compare results. Multiple scenarios, models and downscaling methods have been used to reduce uncertainties. However, few studies have discussed what the main source of uncertainties is and which uncertainty could be most effectively reduced. Projecting air pollution-related mortality requires a systematic consideration of assumptions and uncertainties, which will significantly aid policymakers in efforts to manage potential impacts of PM2.5 and O3 on mortality in the context of climate change. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

  9. CMIP5-downscaled projections for the NW European Shelf Seas: initial results and insights into uncertainties

    Science.gov (United States)

    Tinker, Jonathan; Palmer, Matthew; Lowe, Jason; Howard, Tom

    2017-04-01

    The North Sea, and wider Northwest European Shelf seas (NWS) are economically, environmentally, and culturally important for a number of European countries. They are protected by European legislation, often with specific reference to the potential impacts of climate change. Coastal climate change projections are an important source of information for effective management of European Shelf Seas. For example, potential changes in the marine environment are a key component of the climate change risk assessments (CCRAs) carried out under the UK Climate Change Act We use the NEMO shelf seas model combined with CMIP5 climate model and EURO-CORDEX regional atmospheric model data to generate new simulations of the NWS. Building on previous work using a climate model perturbed physics ensemble and the POLCOMS, this new model setup is used to provide first indication of the uncertainties associated with: (i) the driving climate model; (ii) the atmospheric downscaling model (iii) the shelf seas downscaling model; (iv) the choice of climate change scenario. Our analysis considers a range of physical marine impacts and the drivers of coastal variability and change, including sea level and the propagation of open ocean signals onto the shelf. The simulations are being carried out as part of the UK Climate Projections 2018 (UKCP18) and will feed into the following UK CCRA.

  10. Impacts of representing sea-level rise uncertainty on future flood risks: An example from San Francisco Bay.

    Science.gov (United States)

    Ruckert, Kelsey L; Oddo, Perry C; Keller, Klaus

    2017-01-01

    Rising sea levels increase the probability of future coastal flooding. Many decision-makers use risk analyses to inform the design of sea-level rise (SLR) adaptation strategies. These analyses are often silent on potentially relevant uncertainties. For example, some previous risk analyses use the expected, best, or large quantile (i.e., 90%) estimate of future SLR. Here, we use a case study to quantify and illustrate how neglecting SLR uncertainties can bias risk projections. Specifically, we focus on the future 100-yr (1% annual exceedance probability) coastal flood height (storm surge including SLR) in the year 2100 in the San Francisco Bay area. We find that accounting for uncertainty in future SLR increases the return level (the height associated with a probability of occurrence) by half a meter from roughly 2.2 to 2.7 m, compared to using the mean sea-level projection. Accounting for this uncertainty also changes the shape of the relationship between the return period (the inverse probability that an event of interest will occur) and the return level. For instance, incorporating uncertainties shortens the return period associated with the 2.2 m return level from a 100-yr to roughly a 7-yr return period (∼15% probability). Additionally, accounting for this uncertainty doubles the area at risk of flooding (the area to be flooded under a certain height; e.g., the 100-yr flood height) in San Francisco. These results indicate that the method of accounting for future SLR can have considerable impacts on the design of flood risk management strategies.

  11. Impacts of representing sea-level rise uncertainty on future flood risks: An example from San Francisco Bay.

    Directory of Open Access Journals (Sweden)

    Kelsey L Ruckert

    Full Text Available Rising sea levels increase the probability of future coastal flooding. Many decision-makers use risk analyses to inform the design of sea-level rise (SLR adaptation strategies. These analyses are often silent on potentially relevant uncertainties. For example, some previous risk analyses use the expected, best, or large quantile (i.e., 90% estimate of future SLR. Here, we use a case study to quantify and illustrate how neglecting SLR uncertainties can bias risk projections. Specifically, we focus on the future 100-yr (1% annual exceedance probability coastal flood height (storm surge including SLR in the year 2100 in the San Francisco Bay area. We find that accounting for uncertainty in future SLR increases the return level (the height associated with a probability of occurrence by half a meter from roughly 2.2 to 2.7 m, compared to using the mean sea-level projection. Accounting for this uncertainty also changes the shape of the relationship between the return period (the inverse probability that an event of interest will occur and the return level. For instance, incorporating uncertainties shortens the return period associated with the 2.2 m return level from a 100-yr to roughly a 7-yr return period (∼15% probability. Additionally, accounting for this uncertainty doubles the area at risk of flooding (the area to be flooded under a certain height; e.g., the 100-yr flood height in San Francisco. These results indicate that the method of accounting for future SLR can have considerable impacts on the design of flood risk management strategies.

  12. 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

  13. European drought under climate change and an assessment of the uncertainties in projections

    Science.gov (United States)

    Yu, R. M. S.; Osborn, T.; Conway, D.; Warren, R.; Hankin, R.

    2012-04-01

    Extreme weather/climate events have significant environmental and societal impacts, and anthropogenic climate change has and will continue to alter their characteristics (IPCC, 2011). Drought is one of the most damaging natural hazards through its effects on agricultural, hydrological, ecological and socio-economic systems. Climate change is stimulating demand, from public and private sector decision-makers and also other stakeholders, for better understanding of potential future drought patterns which could facilitate disaster risk management. There remain considerable levels of uncertainty in climate change projections, particularly in relation to extreme events. Our incomplete understanding of the behaviour of the climate system has led to the development of various emission scenarios, carbon cycle models and global climate models (GCMs). Uncertainties arise also from the different types and definitions of drought. This study examines climate change-induced changes in European drought characteristics, and illustrates the robustness of these projections by quantifying the effects of using different emission scenarios, carbon cycle models and GCMs. This is achieved by using the multi-institutional modular "Community Integrated Assessment System (CIAS)" (Warren et al., 2008), a flexible integrated assessment system for modelling climate change. Simulations generated by the simple climate model MAGICC6.0 are assessed. These include ten C4MIP carbon cycle models and eighteen CMIP3 GCMs under five IPCC SRES emission scenarios, four Representative Concentration Pathway (RCP) scenarios, and three mitigation scenarios with CO2-equivalent levels stabilising at 550 ppm, 500 ppm and 450 ppm. Using an ensemble of 2160 future precipitation scenarios, we present an analysis on both short (3-month) and long (12-month) meteorological droughts based on the Standardised Precipitation Index (SPI) for the baseline period (1951-2000) and two future periods of 2001-2050 and 2051

  14. NASA Space Radiation Risk Project: Overview and Recent Results

    Science.gov (United States)

    Blattnig, Steve R.; Chappell, Lori J.; George, Kerry A.; Hada, Megumi; Hu, Shaowen; Kidane, Yared H.; Kim, Myung-Hee Y.; Kovyrshina, Tatiana; Norman, Ryan B.; Nounu, Hatem N.; hide

    2015-01-01

    The NASA Space Radiation Risk project is responsible for integrating new experimental and computational results into models to predict risk of cancer and acute radiation syndrome (ARS) for use in mission planning and systems design, as well as current space operations. The project has several parallel efforts focused on proving NASA's radiation risk projection capability in both the near and long term. This presentation will give an overview, with select results from these efforts including the following topics: verification, validation, and streamlining the transition of models to use in decision making; relative biological effectiveness and dose rate effect estimation using a combination of stochastic track structure simulations, DNA damage model calculations and experimental data; ARS model improvements; pathway analysis from gene expression data sets; solar particle event probabilistic exposure calculation including correlated uncertainties for use in design optimization.

  15. Sound transit climate risk reduction project.

    Science.gov (United States)

    2013-09-01

    The Climate Risk Reduction Project assessed how climate change may affect Sound Transit commuter rail, light rail, and express bus : services. The project identified potential climate change impacts on agency operations, assets, and long-term plannin...

  16. 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.

  17. 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…

  18. Projecting species' vulnerability to climate change: Which uncertainty sources matter most and extrapolate best?

    Science.gov (United States)

    Steen, Valerie; Sofaer, Helen R; Skagen, Susan K; Ray, Andrea J; Noon, Barry R

    2017-11-01

    Species distribution models (SDMs) are commonly used to assess potential climate change impacts on biodiversity, but several critical methodological decisions are often made arbitrarily. We compare variability arising from these decisions to the uncertainty in future climate change itself. We also test whether certain choices offer improved skill for extrapolating to a changed climate and whether internal cross-validation skill indicates extrapolative skill. We compared projected vulnerability for 29 wetland-dependent bird species breeding in the climatically dynamic Prairie Pothole Region, USA. For each species we built 1,080 SDMs to represent a unique combination of: future climate, class of climate covariates, collinearity level, and thresholding procedure. We examined the variation in projected vulnerability attributed to each uncertainty source. To assess extrapolation skill under a changed climate, we compared model predictions with observations from historic drought years. Uncertainty in projected vulnerability was substantial, and the largest source was that of future climate change. Large uncertainty was also attributed to climate covariate class with hydrological covariates projecting half the range loss of bioclimatic covariates or other summaries of temperature and precipitation. We found that choices based on performance in cross-validation improved skill in extrapolation. Qualitative rankings were also highly uncertain. Given uncertainty in projected vulnerability and resulting uncertainty in rankings used for conservation prioritization, a number of considerations appear critical for using bioclimatic SDMs to inform climate change mitigation strategies. Our results emphasize explicitly selecting climate summaries that most closely represent processes likely to underlie ecological response to climate change. For example, hydrological covariates projected substantially reduced vulnerability, highlighting the importance of considering whether water

  19. 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.

  20. Modelling financial risk in open pit mine projects: Implications for strategic decision-making

    OpenAIRE

    Abdel Sabour, S.A.; Wood, G.

    2009-01-01

    Strategic decisions in the mining industry are made under multiple technical and market uncertainties. Therefore, to reach the best possible decision, based on information available, it is necessary to integrate uncertainty about the input variables and model financial risk of the project's merit measures. However, this rovides few useful insights to decision-makers unless accompanied by modeling management responses to uncertainty resolutions. It is widely acknowledged that conventional deci...

  1. Research into specific risk assessment in project financing

    Directory of Open Access Journals (Sweden)

    Ivana Bestvina Bukvić

    2013-12-01

    Full Text Available An assessment of investment justification in terms of risk enables the decision maker (investor to select, among available alternatives, the one with the most favourable correlation between the expected profit and assumed risk. At the micro level, the uncertainty of business success is extremely high in production activities, which is an additional incentive for taking a comprehensive approach to the issue of investment decision-making and the development of risk assessment techniques applicable in this particular segment of industry. Given the complexity of the manufacturing process, the length of the production cycle, market conditions, and entity-specific risks (which are difficult to measure, projects in manufacturing industry require a detailed and comprehensive assessment of specific risk factors and their cost-effectiveness. Ne - vertheless, since specific risks can be diversified, investment proposal assessments in practice usually do not cover their quantification and analysis. However, the majority of business entities do not have enough active projects in various industries to be able to fully diversify their business and thus minimize the level of specific risks. The impact of specific factors becomes one of the most important elements for business success. This paper analyses how far risk assessment methods regarding specific risks are used in practice. Furthermore, it analyses the significance of specific risks for total investment risk. This study gives new insi - ghts into the significance of specific risks to the overall investment assessment and the need for permanent development of traditionally used investment assessment models.

  2. Climate change adaptation accounting for huge uncertainties in future projections - the case of urban drainage

    Science.gov (United States)

    Willems, Patrick

    2015-04-01

    Hydrological design parameters, which are currently used in the guidelines for the design of urban drainage systems (Willems et al., 2013) have been revised, taking the Flanders region of Belgium as case study. The revision involved extrapolation of the design rainfall statistics, taking into account the current knowledge on future climate change trends till 2100. Uncertainties in these trend projections have been assessed after statistically analysing and downscaling by a quantile perturbation tool based on a broad ensemble set of climate model simulation results (44 regional + 69 global control-scenario climate model run combinations for different greenhouse gas scenarios). The impact results of the climate scenarios were investigated as changes to rainfall intensity-duration-frequency (IDF) curves. Thereafter, the climate scenarios and related changes in rainfall statistics were transferred to changes in flood frequencies of sewer systems and overflow frequencies of storage facilities. This has been done based on conceptual urban drainage models. Also the change in storage capacity required to exceed a given overflow return period, has been calculated for a range of return periods and infiltration or throughflow rates. These results were used on the basis of the revision of the hydraulic design rules of urban drainage systems. One of the major challenges while formulating these policy guidelines was the consideration of the huge uncertainties in the future climate change projections and impact assessments; see also the difficulties and pitfalls reported by the IWA/IAHR Joint Committee on Urban Drainage - Working group on urban rainfall (Willems et al., 2012). We made use of the risk concept, and found it a very useful approach to deal with the high uncertainties. It involves an impact study of the different climate projections, or - for practical reasons - a reduced set of climate scenarios tailored for the specific type of impact considered (urban floods in our

  3. WAYS TO IMPROVE RISK MANAGEMENT IN COMPLEX PROJECTS

    Directory of Open Access Journals (Sweden)

    Emilia IORDACHE

    2012-01-01

    Full Text Available Risk is present in all human activities; it can be associated with health, security, economy or environment. The goal of risk management is to control, prevent or decrease potential damages. Technically speaking, risk management means all the activities coordinated so as to orient and monitor an organization from the risk perspective. Risk management helps formulate the most adequate decisions by taking account of uncertainties and their effects upon the accomplishment of proposed goals, and argues the need to lay down and implement coercive, preventive actions typical of the management of a company. The benefits of good risk management and also the consequences of bad management shall undoubtedly be felt by an organization’s board, employees, shareholders, customers as well as by all other entities concerned with organizational performance. Projects generally include a number of risks in common with those in business as well as certain typical ones. In complex projects, it is this very feature – complexity – which generates the need to implement risk management for the purpose to diminish, remove, and monitor the risks which can influence the development of a project.

  4. Risk Assessment in Financial Feasibility of Tanker Project Using Monte Carlo Simulation

    Directory of Open Access Journals (Sweden)

    Muhammad Badrus Zaman

    2017-09-01

    Full Text Available Every ship project would not be apart from risk and uncertainty issues. The inappropriate risk assessment process would have long-term impact, such as financial loss. Thus, risk and uncertainties analysis would be a very important process in financial feasibility determination of the project. This study analyzes the financial feasibility of 17,500 LTDW tanker project. Risk and uncertainty are two differentiated terminologies in this study, where risk focuses on operational risk due to shipbuilding process nonconformity to shipowner finance, while uncertainty focuses on variable costs that affect project cash flows. There are three funding scenarios in this study, where the percentage of funding with own capital and bank loan in scenario 1 is 100% : 0%, scenario 2 is 75% : 25%, and scenario 3 is 50% : 50%. Monte Carlo simulation method was applied to simulate the acceptance criteria, such as net present value (NPV, internal rate of return (IRR, payback period (PP, and profitability index (PI. The results of simulation show that 17,500 LTDW tanker project funding by scenario 1, 2 and 3 are feasible to run, where probability of each acceptance criteria was greater than 50%. Charter rate being the most sensitive uncertainty over project's financial feasibility parameters.

  5. 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

  6. Understanding Pre-Quantitative Risk in Projects

    Science.gov (United States)

    Cooper, Lynne P.

    2011-01-01

    Standard approaches to risk management in projects depend on the ability of teams to identify risks and quantify the probabilities and consequences of these risks (e.g., the 5 x 5 risk matrix). However, long before quantification does - or even can - occur, and long after, teams make decisions based on their pre-quantitative understanding of risk. These decisions can have long-lasting impacts on the project. While significant research has looked at the process of how to quantify risk, our understanding of how teams conceive of and manage pre-quantitative risk is lacking. This paper introduces the concept of pre-quantitative risk and discusses the implications of addressing pre-quantitative risk in projects.

  7. 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)

  8. Uncertainty of runoff projections under changing climate in Wami River sub-basin

    Directory of Open Access Journals (Sweden)

    Frank Joseph Wambura

    2015-09-01

    New Hydrological Insights for the Region: The results of projected streamflow shows that the baseline annual climatology flow (ACF is 98 m3/s and for the future, the median ACF is projected to be 81 m3/s. At 100% uncertainty of skilled projections, the ACF from the sub-basin is projected to range between −47% and +36% from the baseline ACF. However, the midstream of the sub-basin shows reliable water availability for foreseen water uses expansion up to the year 2039.

  9. Water shortage risk assessment considering large-scale regional transfers: a copula-based uncertainty case study in Lunan, China.

    Science.gov (United States)

    Gao, Xueping; Liu, Yinzhu; Sun, Bowen

    2018-06-05

    The risk of water shortage caused by uncertainties, such as frequent drought, varied precipitation, multiple water resources, and different water demands, brings new challenges to the water transfer projects. Uncertainties exist for transferring water and local surface water; therefore, the relationship between them should be thoroughly studied to prevent water shortage. For more effective water management, an uncertainty-based water shortage risk assessment model (UWSRAM) is developed to study the combined effect of multiple water resources and analyze the shortage degree under uncertainty. The UWSRAM combines copula-based Monte Carlo stochastic simulation and the chance-constrained programming-stochastic multiobjective optimization model, using the Lunan water-receiving area in China as an example. Statistical copula functions are employed to estimate the joint probability of available transferring water and local surface water and sampling from the multivariate probability distribution, which are used as inputs for the optimization model. The approach reveals the distribution of water shortage and is able to emphasize the importance of improving and updating transferring water and local surface water management, and examine their combined influence on water shortage risk assessment. The possible available water and shortages can be calculated applying the UWSRAM, also with the corresponding allocation measures under different water availability levels and violating probabilities. The UWSRAM is valuable for mastering the overall multi-water resource and water shortage degree, adapting to the uncertainty surrounding water resources, establishing effective water resource planning policies for managers and achieving sustainable development.

  10. 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

  11. Effect of risk aversion on prioritizing conservation projects.

    Science.gov (United States)

    Tulloch, Ayesha I T; Maloney, Richard F; Joseph, Liana N; Bennett, Joseph R; Di Fonzo, Martina M I; Probert, William J M; O'Connor, Shaun M; Densem, Jodie P; Possingham, Hugh P

    2015-04-01

    Conservation outcomes are uncertain. Agencies making decisions about what threat mitigation actions to take to save which species frequently face the dilemma of whether to invest in actions with high probability of success and guaranteed benefits or to choose projects with a greater risk of failure that might provide higher benefits if they succeed. The answer to this dilemma lies in the decision maker's aversion to risk--their unwillingness to accept uncertain outcomes. Little guidance exists on how risk preferences affect conservation investment priorities. Using a prioritization approach based on cost effectiveness, we compared 2 approaches: a conservative probability threshold approach that excludes investment in projects with a risk of management failure greater than a fixed level, and a variance-discounting heuristic used in economics that explicitly accounts for risk tolerance and the probabilities of management success and failure. We applied both approaches to prioritizing projects for 700 of New Zealand's threatened species across 8303 management actions. Both decision makers' risk tolerance and our choice of approach to dealing with risk preferences drove the prioritization solution (i.e., the species selected for management). Use of a probability threshold minimized uncertainty, but more expensive projects were selected than with variance discounting, which maximized expected benefits by selecting the management of species with higher extinction risk and higher conservation value. Explicitly incorporating risk preferences within the decision making process reduced the number of species expected to be safe from extinction because lower risk tolerance resulted in more species being excluded from management, but the approach allowed decision makers to choose a level of acceptable risk that fit with their ability to accommodate failure. We argue for transparency in risk tolerance and recommend that decision makers accept risk in an adaptive management

  12. 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

  13. 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

  14. Risk variables in evaluation of transport projects

    Science.gov (United States)

    Vařbuchta, Petr; Kovářová, Hana; Hromádka, Vít; Vítková, Eva

    2017-09-01

    Depending on the constantly increasing demands on assessment of investment projects, especially assessment of large-scale projects in transport and important European projects with wide impacts, there is constantly increasing focus on risk management, whether to find mitigations, creating corrective measures or their implementation in assessment, especially in the context of Cost-Benefit analysis. To project assessment is often used implementation of certain risk variables, which can generate negative impacts of project outputs in framework of assess. Especially in case of transportation infrastructure projects is taken much emphasis on the influence of risk variables. However, currently in case of assessment of transportation projects is in Czech Republic used a few risk variables, which occur in the most projects. This leads to certain limitation in framework of impact assessment of risk variables. This papers aims to specify a new risk variables and process of applying them to already executed project assessment. Based on changes generated by new risk variables will be evaluated differences between original and adapted assessment.

  15. Diagnosing risks in product-innovation projects

    NARCIS (Netherlands)

    Halman, Johannes I.M.; Keizer, J.A.

    A new method of diagnosing risks in product-innovation projects is introduced in the paper. The method is an improvement on existing risk methods used on product-innovation projects, such as potential problem analysis and failure mode and effects analysis. Technological, organizational and

  16. Diagnosing risks in product-innovation projects

    NARCIS (Netherlands)

    Halman, J.I.M.; Keizer, J.A.

    1994-01-01

    A new method of diagnosing risks in product-innovation projects is introduced in the paper. The method is an improvement on existing risk methods used on product-innovation projects, such as potential problem analysis and failure mode and effects analysis. Technological, organizational and

  17. Modeling Research Project Risks with Fuzzy Maps

    Science.gov (United States)

    Bodea, Constanta Nicoleta; Dascalu, Mariana Iuliana

    2009-01-01

    The authors propose a risks evaluation model for research projects. The model is based on fuzzy inference. The knowledge base for fuzzy process is built with a causal and cognitive map of risks. The map was especially developed for research projects, taken into account their typical lifecycle. The model was applied to an e-testing research…

  18. Balancing uncertainty of context in ERP project estimation: an approach and a case study

    NARCIS (Netherlands)

    Daneva, Maia

    2010-01-01

    The increasing demand for Enterprise Resource Planning (ERP) solutions as well as the high rates of troubled ERP implementations and outright cancellations calls for developing effort estimation practices to systematically deal with uncertainties in ERP projects. This paper describes an approach -

  19. Spatial regression methods capture prediction uncertainty in species distribution model projections through time

    Science.gov (United States)

    Alan K. Swanson; Solomon Z. Dobrowski; Andrew O. Finley; James H. Thorne; Michael K. Schwartz

    2013-01-01

    The uncertainty associated with species distribution model (SDM) projections is poorly characterized, despite its potential value to decision makers. Error estimates from most modelling techniques have been shown to be biased due to their failure to account for spatial autocorrelation (SAC) of residual error. Generalized linear mixed models (GLMM) have the ability to...

  20. 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.

  1. Transport project evaluation: feasibility risk assessment and scenario forecasting

    DEFF Research Database (Denmark)

    Salling, Kim Bang; Leleur, Steen

    2017-01-01

    This paper presents a new approach to transport project assessment in terms of feasibility risk assessment and reference class forecasting. Conventionally, transport project assessment is based upon a Cost-Benefit Analysis (CBA) where evaluation criteria such as Benefit Cost Ratios (BCR...... on the preliminary construction cost estimates. Hereafter, a quantitative risk analysis is provided making use of Monte Carlo simulation. This approach facilitates random input parameters based upon reference class forecasting, hence, a parameter data fit has been performed in order to obtain validated probability...... Scenario Forecasting (RSF) frame. The RSF is anchored in the cost-benefit analysis; thus, it provides decision-makers with a quantitative mean of assessing the transport infrastructure project. First, the RSF method introduces uncertainties within the CBA by applying Optimism Bias uplifts...

  2. 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

  3. Levels of uncertainty, decision making and risk communication: the siting of nuclear waste in France and the United Kingdom

    International Nuclear Information System (INIS)

    Poumadere, M.

    1999-01-01

    The social demand for increased risk control is considered here as it applies to nuclear waste management. Britain's Sellafield Repository Project and France's Mediation Mission to site underground research laboratories are compared. While both management approaches show evolution away from an authoritarian model of decision making and towards implementation of a more socially responsive model, distinct methods of dealing with scientific and social uncertainty appear as well. (author)

  4. Levels of uncertainty, decision making and risk communication: the siting of nuclear waste in France and the United Kingdom

    Energy Technology Data Exchange (ETDEWEB)

    Poumadere, M

    1999-11-01

    The social demand for increased risk control is considered here as it applies to nuclear waste management. Britain`s Sellafield Repository Project and France`s Mediation Mission to site underground research laboratories are compared. While both management approaches show evolution away from an authoritarian model of decision making and towards implementation of a more socially responsive model, distinct methods of dealing with scientific and social uncertainty appear as well. (author)

  5. 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.

  6. Security Risk Assessment in Software Development Projects

    OpenAIRE

    Svendsen, Heidi

    2017-01-01

    Software security is increasing in importance, linearly with vulnerabilities caused by software flaws. It is not possible to spend all the project s resources on software security. To spend the resources given to security in an effective way, one should know what is most important to protect. By performing a risk analysis the project know which vulnerabilities they face. A risk analysis will prioritise the vulnerabilities, and when the vulnerabilities are prioritised the project know where th...

  7. 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.

  8. 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.…

  9. 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...

  10. HTGR reactor physics, thermal-hydraulics and depletion uncertainty analysis: a proposed IAEA coordinated research project

    International Nuclear Information System (INIS)

    Tyobeka, Bismark; Reitsma, Frederik; Ivanov, Kostadin

    2011-01-01

    The continued development of High Temperature Gas Cooled Reactors (HTGRs) requires verification of HTGR design and safety features with reliable high fidelity physics models and robust, efficient, and accurate codes. The predictive capability of coupled neutronics/thermal hydraulics and depletion simulations for reactor design and safety analysis can be assessed with sensitivity analysis and uncertainty analysis methods. In order to benefit from recent advances in modeling and simulation and the availability of new covariance data (nuclear data uncertainties) extensive sensitivity and uncertainty studies are needed for quantification of the impact of different sources of uncertainties on the design and safety parameters of HTGRs. Uncertainty and sensitivity studies are an essential component of any significant effort in data and simulation improvement. In February 2009, the Technical Working Group on Gas-Cooled Reactors recommended that the proposed IAEA Coordinated Research Project (CRP) on the HTGR Uncertainty Analysis in Modeling be implemented. In the paper the current status and plan are presented. The CRP will also benefit from interactions with the currently ongoing OECD/NEA Light Water Reactor (LWR) UAM benchmark activity by taking into consideration the peculiarities of HTGR designs and simulation requirements. (author)

  11. 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...

  12. Managing Uncertainties Associated With Radioactive Waste Disposal: Task Group 4 Of The IAEA PRISM Project

    International Nuclear Information System (INIS)

    Seitz, R.

    2011-01-01

    It is widely recognized that the results of safety assessment calculations provide an important contribution to the safety arguments for a disposal facility, but cannot in themselves adequately demonstrate the safety of the disposal system. The safety assessment and a broader range of arguments and activities need to be considered holistically to justify radioactive waste disposal at any particular site. Many programs are therefore moving towards the production of what has become known as a Safety Case, which includes all of the different activities that are conducted to demonstrate the safety of a disposal concept. Recognizing the growing interest in the concept of a Safety Case, the International Atomic Energy Agency (IAEA) is undertaking an intercomparison and harmonization project called PRISM (Practical Illustration and use of the Safety Case Concept in the Management of Near-surface Disposal). The PRISM project is organized into four Task Groups that address key aspects of the Safety Case concept: Task Group 1 - Understanding the Safety Case; Task Group 2 - Disposal facility design; Task Group 3 - Managing waste acceptance; and Task Group 4 - Managing uncertainty. This paper addresses the work of Task Group 4, which is investigating approaches for managing the uncertainties associated with near-surface disposal of radioactive waste and their consideration in the context of the Safety Case. Emphasis is placed on identifying a wide variety of approaches that can and have been used to manage different types of uncertainties, especially non-quantitative approaches that have not received as much attention in previous IAEA projects. This paper includes discussions of the current results of work on the task on managing uncertainty, including: the different circumstances being considered, the sources/types of uncertainties being addressed and some initial proposals for approaches that can be used to manage different types of uncertainties.

  13. 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.

  14. 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.

  15. Effects of climate model interdependency on the uncertainty quantification of extreme reinfall projections

    DEFF Research Database (Denmark)

    Sunyer Pinya, Maria Antonia; Madsen, H.; Rosbjerg, Dan

    are independent. This study investigates the validity of this assumption and its effects on the estimated probabilistic projections of the changes in the 95% quantile of wet days. The methodology is divided in two main parts. First, the interdependency of the ENSEMBLES RCMs is estimated using the methodology...... developed by Pennell and Reichler (2011). The results show that the projections from the ENSEMBLES RCMs cannot be assumed independent. This result is then used to estimate the uncertainty in climate model projections. A Bayesian approach has been developed using the procedure suggested by Tebaldi et al...

  16. Effects of climate model interdependency on the uncertainty quantification of extreme rainfall projections

    DEFF Research Database (Denmark)

    Sunyer, M. A.; Rosbjerg, Dan; Arnbjerg-Nielsen, Karsten

    2017-01-01

    are independent. This study investigates the validity of this assumption and its effects on the estimated probabilistic projections of the changes in the 95% quantile of wet days. The methodology is divided in two main parts. First, the interdependency of the ENSEMBLES RCMs is estimated using the methodology...... developed by Pennell and Reichler (2011). The results show that the projections from the ENSEMBLES RCMs cannot be assumed independent. This result is then used to estimate the uncertainty in climate model projections. A Bayesian approach has been developed using the procedure suggested by Tebaldi et al...

  17. 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

  18. Influence of the Risk-Contributing Factors on the Financing of the Investment Project for Building of Intelligent Buildings

    Directory of Open Access Journals (Sweden)

    Voytolovskiy Nikolay

    2017-01-01

    Full Text Available This article provides the generic classification of risks of the investment projects for the construction of intelligent buildings which differ by the detachment of the subjective perception of risk by the investor. Risk and uncertainty were justified as system characteristics of the investment projects for the construction of intelligent buildings. Characteristics of the development was given in the context of project management. Methodical schemes of the development of the investment project risks were specified on the basis of interconnection of risk and project effectiveness. Risk management procedure at realization of the developer project was developed.

  19. Research on Risk Manage of Power Construction Project Based on Bayesian Network

    Science.gov (United States)

    Jia, Zhengyuan; Fan, Zhou; Li, Yong

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

  20. Hole cleaning: new project criteria by uncertainties consideration; Limpeza de pocos: novos criterios de projeto atraves da consideracao de incertezas

    Energy Technology Data Exchange (ETDEWEB)

    Holzberg, Bruno B.; Costa, Suzana S.; Fontoura, Sergio A.B. da [Pontificia Univ. Catolica do Rio de Janeiro (PUC-Rio), RJ (Brazil). Dept. de Engenharia Civil. Grupo de Tecnologia e Engenharia de Petroleo; Martins, Andre L. [PETROBRAS, Rio de Janeiro, RJ (Brazil). Centro de Pesquisas

    2004-07-01

    The current work presents a probabilistic modeling of drilling cuttings removal, an operation known as hole cleaning. This operation is yet a critical issue on high inclined well drilling, especially on the sea. Problems as stuck pipe and eventual well deviation can be caused by the inefficacy of this operation. The proposed analysis aims quantify the risk of occurrence of theses problems. The drilling program must refuse situation that may present risks bigger than the determined by the project. The probabilistic approach is justified by the fact that some of the more relevant parameters of hole cleaning model present associated uncertainties. These uncertainties can be caused by fluctuation of the parameters while drilling, intrinsic variations of rock properties or by the imprecision of the estimative methods. For considering these uncertainties, the Monte Carlo simulation method is applied to the hole cleaning problem. Through the proposed analysis, one can quantify the probability to occur a bed height bigger than a height considered critical for the operation and the probability to occur a solid concentration on the drilling fluid bigger than a concentration considered critic. The valuation of these probabilities is then suggested as a tool for the elaboration of new criteria's that will help in decision-making during well planning. (author)

  1. 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

  2. COORDINATES OF A RISK MANAGEMENT PROJECT

    OpenAIRE

    ALEXANDRU OLTEANU; MĂDĂLINA ANTOANETA RĂDOI

    2013-01-01

    High risk – high benefit: a well-known correlation both in the economic field and in the day-to-day life. Another correlation, on which this article is based: large project – numerous participants – increased risks and other malfunctions. The risk management concept is challenged by those projects and is forced to find the most adequate “customized” ways for each project at its turn. In this respect, the assessment of management has followed the trend of the last three decades, marked by movi...

  3. 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

  4. Internal dose assessments: Uncertainty studies and update of ideas guidelines and databases within CONRAD project

    International Nuclear Information System (INIS)

    Marsh, J. W.; Castellani, C. M.; Hurtgen, C.; Lopez, M. A.; Andrasi, A.; Bailey, M. R.; Birchall, A.; Blanchardon, E.; Desai, A. D.; Dorrian, M. D.; Doerfel, H.; Koukouliou, V.; Luciani, A.; Malatova, I.; Molokanov, A.; Puncher, M.; Vrba, T.

    2008-01-01

    The work of Task Group 5.1 (uncertainty studies and revision of IDEAS guidelines) and Task Group 5.5 (update of IDEAS databases) of the CONRAD project is described. Scattering factor (SF) values (i.e. measurement uncertainties) have been calculated for different radionuclides and types of monitoring data using real data contained in the IDEAS Internal Contamination Database. Based upon this work and other published values, default SF values are suggested. Uncertainty studies have been carried out using both a Bayesian approach as well as a frequentist (classical) approach. The IDEAS guidelines have been revised in areas relating to the evaluation of an effective AMAD, guidance is given on evaluating wound cases with the NCRP wound model and suggestions made on the number and type of measurements required for dose assessment. (authors)

  5. 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.

  6. 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…

  7. 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.

  8. 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

  9. 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). ...

  10. 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...

  11. 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.

  12. 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.

  13. New Method of Selecting Efficient Project Portfolios in the Presence of Hybrid Uncertainty

    Directory of Open Access Journals (Sweden)

    Bogdan Rębiasz

    2016-01-01

    Full Text Available A new methods of selecting efficient project portfolios in the presence of hybrid uncertainty has been presented. Pareto optimal solutions have been defined by an algorithm for generating project portfolios. The method presented allows us to select efficient project portfolios taking into account statistical and economic dependencies between projects when some of the parameters used in the calculation of effectiveness can be expressed in the form of an interactive possibility distribution and some in the form of a probability distribution. The procedure for processing such hybrid data combines stochastic simulation with nonlinear programming. The interaction between data are modeled by correlation matrices and the interval regression. Economic dependences are taken into account by the equations balancing the production capacity of the company. The practical example presented indicates that an interaction between projects has a significant impact on the results of calculations. (original abstract

  14. Risk management integration into complex project organizations

    Science.gov (United States)

    Fisher, K.; Greanias, G.; Rose, J.; Dumas, R.

    2002-01-01

    This paper describes the approach used in designing and adapting the SIRTF prototype, discusses some of the lessons learned in developing the SIRTF prototype, and explains the adaptability of the risk management database to varying levels project complexity.

  15. Risk management for independent power projects

    International Nuclear Information System (INIS)

    Owen, J.L.

    1993-01-01

    Independent Power, where electric utilities or other bulk electric power users contract with individual electric power generation facilities to meet their projected long term power needs, has grown dramatically over the past ten years or more. This concept, to contract with Independent Power Producers (IPP), is not a new concept and in fact goes back to the early formation of the electric power industry in this country and worldwide. Successful Risk Management is the foundation for ultimate project completion and operation in fulfilling the expectations of all parties. The primary risks associated with the development of Independent Power projects include: predicting long term fuel availability and cost; predicting long term price for the deliverable of electricity; site selection, site characteristics and permitting; innovative or evolving technology; project execution (design and construction), and; lifetime O ampersand M costs and plant reliability. This paper focuses on the risks inherent in the development of IPPs and addresses the management of these risks

  16. 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.

  17. 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.

  18. Project Documentation as a Risk for Public Projects

    Directory of Open Access Journals (Sweden)

    Vladěna Štěpánková

    2015-08-01

    Full Text Available Purpose of the article: The paper presents the different methodologies used for creating documentation and focuses on public projects and their requirements for this documentation. Since documentation is also incorporated in the overall planning of the project and its duration is estimated using expert qualified estimate, can any change in this documentation lead to project delays, or increase its cost as a result of consuming administration, and therefore the documentation is seen as a risk, which may threaten the project as a public contract by which a company trying to achieve and obtains it, and generally any project. Methodology/methods: There are used methods of obtaining information in this paper. These are mainly structured interviews in combination with a brainstorming, furthermore also been used questionnaire for companies dealing with public procurement. As a data processing program was used MS Excel and basic statistical methods based on regression analysis. Scientific aim: The article deals with the construction market in the Czech Republic and examines the impact of changes in project documentation of public projects on their turnover. Findings: In this paper we summarize the advantages and disadvantages of having project documentation. In the case of public contracts and changes in legislation it is necessary to focus on creating documentation in advance, follow the new requirements and try to reach them in the shortest possible time. Conclusions: The paper concludes with recommendations on how to proceed, if these changes and how to reduce costs, which may cause the risk of documentation.

  19. COORDINATES OF A RISK MANAGEMENT PROJECT

    Directory of Open Access Journals (Sweden)

    ALEXANDRU OLTEANU

    2013-05-01

    Full Text Available High risk – high benefit: a well-known correlation both in the economic field and in the day-to-day life. Another correlation, on which this article is based: large project – numerous participants – increased risks and other malfunctions. The risk management concept is challenged by those projects and is forced to find the most adequate “customized” ways for each project at its turn. In this respect, the assessment of management has followed the trend of the last three decades, marked by moving of management profit analysis by risk intermediation, respectively the transition from managing profit to risk-return relationship management. Such trend assumes the obligation of participants to identify objectives and expected benefits of the project on the basis of the strategies laid-down, the elements of risk management policies, in conjunction with the indication of the most negative scenarios which they may provide. This activity must take into consideration the process of obtaining and combining human, financial, physical and information resources in order to accomplish the primary goal of the proposed and wanted project by a certain segment of population. Project participants are directed to evaluate their own activities in terms of revenues and risks from the business access, opportunity, operating mode, as well as the limitations and boundaries on certain sides of activity. The paper focuses on the analysis and evaluation of incomes and risks, on simulations to streamline the activities and the determination of the optimal model of project choice. Also, the paper treats the risks that can be taken over by the sponsors, especially those related to implied guaranties, even implied guaranties.

  20. 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

  1. 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.

  2. Uncertainty Assessment of the NASA Earth Exchange Global Daily Downscaled Climate Projections (NEX-GDDP) Dataset

    Science.gov (United States)

    Wang, Weile; Nemani, Ramakrishna R.; Michaelis, Andrew; Hashimoto, Hirofumi; Dungan, Jennifer L.; Thrasher, Bridget L.; Dixon, Keith W.

    2016-01-01

    The NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset is comprised of downscaled climate projections that are derived from 21 General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 5 (CMIP5) and across two of the four greenhouse gas emissions scenarios (RCP4.5 and RCP8.5). Each of the climate projections includes daily maximum temperature, minimum temperature, and precipitation for the periods from 1950 through 2100 and the spatial resolution is 0.25 degrees (approximately 25 km x 25 km). The GDDP dataset has received warm welcome from the science community in conducting studies of climate change impacts at local to regional scales, but a comprehensive evaluation of its uncertainties is still missing. In this study, we apply the Perfect Model Experiment framework (Dixon et al. 2016) to quantify the key sources of uncertainties from the observational baseline dataset, the downscaling algorithm, and some intrinsic assumptions (e.g., the stationary assumption) inherent to the statistical downscaling techniques. We developed a set of metrics to evaluate downscaling errors resulted from bias-correction ("quantile-mapping"), spatial disaggregation, as well as the temporal-spatial non-stationarity of climate variability. Our results highlight the spatial disaggregation (or interpolation) errors, which dominate the overall uncertainties of the GDDP dataset, especially over heterogeneous and complex terrains (e.g., mountains and coastal area). In comparison, the temporal errors in the GDDP dataset tend to be more constrained. Our results also indicate that the downscaled daily precipitation also has relatively larger uncertainties than the temperature fields, reflecting the rather stochastic nature of precipitation in space. Therefore, our results provide insights in improving statistical downscaling algorithms and products in the future.

  3. 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.

  4. 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...

  5. Communicating mega-projects in the face of uncertainties: Israeli mass media treatment of the Dead Sea Water Canal.

    Science.gov (United States)

    Fischhendler, Itay; Cohen-Blankshtain, Galit; Shuali, Yoav; Boykoff, Max

    2015-10-01

    Given the potential for uncertainties to influence mega-projects, this study examines how mega-projects are deliberated in the public arena. The paper traces the strategies used to promote the Dead Sea Water Canal. Findings show that the Dead Sea mega-project was encumbered by ample uncertainties. Treatment of uncertainties in early coverage was dominated by economics and raised primarily by politicians, while more contemporary media discourses have been dominated by ecological uncertainties voiced by environmental non-governmental organizations. This change in uncertainty type is explained by the changing nature of the project and by shifts in societal values over time. The study also reveals that 'uncertainty reduction' and to a lesser degree, 'project cancellation', are still the strategies most often used to address uncertainties. Statistical analysis indicates that although uncertainties and strategies are significantly correlated, there may be other intervening variables that affect this correlation. This research also therefore contributes to wider and ongoing considerations of uncertainty in the public arena through various media representational practices. © The Author(s) 2013.

  6. 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

  7. Uncertainties in Navigation of Elderly People in Towns - the Assistant Project

    Science.gov (United States)

    Kainz, W.; Kalian, K.

    2013-05-01

    The ASSISTANT project contributes to maintaining the mobility of older people in Europe, in order to safeguard their social and economic participation in an increasingly ageing society. It does this by helping them to travel safely and independently by public transport. This three-year project develops an application for the home PC and smartphone that designed to help older travelers to plan their public transport journeys and then receive guidance during their journey. This guidance will help them to find the vehicle they need, warn them when to get off, when and where to change to another route, and will provide assistance if something goes wrong. There are several stages in the guidance where uncertainties play a major role and have an effect on the quality of the trip. The major uncertainty is with the location services when GPS reception in poor or impossible due to urban canyons or the user being under ground or in a tunnel. In addition, when waiting at a stop where for instance several buses might arrive at the same time, it could be difficult to identify the correct bus to board. This paper explains the overall design of the ASSISTANT project and addresses some of the issues related to positional uncertainties.

  8. Assessing the social sustainability contribution of an infrastructure project under conditions of uncertainty

    International Nuclear Information System (INIS)

    Sierra, Leonardo A.; Yepes, Víctor; Pellicer, Eugenio

    2017-01-01

    Assessing the viability of a public infrastructure includes economic, technical and environmental aspects; however, on many occasions, the social aspects are not always adequately considered. This article proposes a procedure to estimate the social sustainability of infrastructure projects under conditions of uncertainty, based on a multicriteria deterministic method. The variability of the method inputs is contributed by the decision-makers. Uncertain inputs are treated through uniform and beta PERT distributions. The Monte Carlo method is used to propagate uncertainty in the method. A case study of a road infrastructure improvement in El Salvador is used to illustrate this treatment. The main results determine the variability of the short and long-term social improvement indices by infrastructure and the probability of the position in the prioritization of the alternatives. The proposed mechanism improves the reliability of the decision making early in infrastructure projects, taking their social contribution into account. The results can complement environmental and economic sustainability assessments. - Highlights: •Estimate the social sustainability of infrastructure projects under conditions of uncertainty •The method uses multicriteria and Monte Carlo techniques and beta PERT distributions •Determines variability of the short and long term social improvement •Determines probability in the prioritization of alternatives •Improves reliability of decision making considering the social contribution

  9. 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

  10. Effects of climate model interdependency on the uncertainty quantification of extreme rainfall projections

    DEFF Research Database (Denmark)

    Sunyer Pinya, Maria Antonia; Madsen, H.; Rosbjerg, Dan

    Climate Models (RCMs) and General Circulation Models (GCMs). These multi-model ensembles provide the information needed to estimate probabilistic climate change projections. Several probabilistic methods have been suggested. One common assumption in most of these methods is that the climate models...... are independent. The effects of this assumption on the uncertainty quantification of extreme rainfall projections are addressed in this study. First, the interdependency of the 95% quantile of wet days in the ENSEMBLES RCMs is estimated. For this statistic and the region studied, the RCMs cannot be assumed...

  11. Quantifying the sources of uncertainty in an ensemble of hydrological climate-impact projections

    Science.gov (United States)

    Aryal, Anil; Shrestha, Sangam; Babel, Mukand S.

    2018-01-01

    The objective of this paper is to quantify the various sources of uncertainty in the assessment of climate change impact on hydrology in the Tamakoshi River Basin, located in the north-eastern part of Nepal. Multiple climate and hydrological models were used to simulate future climate conditions and discharge in the basin. The simulated results of future climate and river discharge were analysed for the quantification of sources of uncertainty using two-way and three-way ANOVA. The results showed that temperature and precipitation in the study area are projected to change in near- (2010-2039), mid- (2040-2069) and far-future (2070-2099) periods. Maximum temperature is likely to rise by 1.75 °C under Representative Concentration Pathway (RCP) 4.5 and by 3.52 °C under RCP 8.5. Similarly, the minimum temperature is expected to rise by 2.10 °C under RCP 4.5 and by 3.73 °C under RCP 8.5 by the end of the twenty-first century. Similarly, the precipitation in the study area is expected to change by - 2.15% under RCP 4.5 and - 2.44% under RCP 8.5 scenarios. The future discharge in the study area was projected using two hydrological models, viz. Soil and Water Assessment Tool (SWAT) and Hydrologic Engineering Center's Hydrologic Modelling System (HEC-HMS). The SWAT model projected discharge is expected to change by small amount, whereas HEC-HMS model projected considerably lower discharge in future compared to the baseline period. The results also show that future climate variables and river hydrology contain uncertainty due to the choice of climate models, RCP scenarios, bias correction methods and hydrological models. During wet days, more uncertainty is observed due to the use of different climate models, whereas during dry days, the use of different hydrological models has a greater effect on uncertainty. Inter-comparison of the impacts of different climate models reveals that the REMO climate model shows higher uncertainty in the prediction of precipitation and

  12. 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.

  13. Project risk management in complex petrochemical system

    Directory of Open Access Journals (Sweden)

    Kirin Snežana

    2012-01-01

    Full Text Available Investigation of risk in complex industrial systems, as well as evaluation of main factors influencing decision making and implementation process using large petrochemical company as an example, has proved the importance of successful project risk management. This is even more emphasized when analyzing systems with complex structure, i.e. with several organizational units. It has been shown that successful risk management requires modern methods, based on adequate application of statistical analysis methods.

  14. 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.

  15. 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...

  16. A mathematical model for crashing projects by considering time, cost, quality and risk

    Directory of Open Access Journals (Sweden)

    Amin Mahmoudi

    2017-01-01

    Full Text Available Employers are looking for reducing execution time and maintaining the quality of the projects that are the main objective of the projects. In this article, we focus on crashing projects by con-sidering different factors such as cost, time, quality and risk. For the proposed integer linear model, cost of conformance and cost of non-conformance are considered as parts of the costs of quality of deliverables in projects. The cost of conformance consists of the costs of training the project team, inspection and test of deliverables. The cost of non-conformance also includes costs of rework and scrap. Project risk management is one of the important aspects of the pro-jects. The present study also considers the impact of risks, which is highly applicable in projects with a high level of uncertainty. Results are presented using integer programming approach with the aim of minimizing the costs of the project.

  17. 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.

  18. 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

  19. Regional Sea Level Scenarios for Coastal Risk Management: Managing the Uncertainty of Future Sea Level Change and Extreme Water Levels for Department of Defense Coastal Sites Worldwide

    Science.gov (United States)

    2016-04-01

    authors and do not necessarily reflect the view of the authors’ Agencies. MANAGING THE UNCERTAINTY OF FUTURE SEA LEVEL CHANGE AND EXTREME WATER LEVELS FOR...COASTAL RISK MANAGEMENT 2-20 contingent probabilities given their dependence on non-probabilistic emissions futures, have extended the ranges of...flood risk provides confidence in the associated projection as a true minimum value for risk management purposes. The contemporary rate observed by

  20. Estimate of the uncertainties in the relative risk of secondary malignant neoplasms following proton therapy and intensity-modulated photon therapy

    International Nuclear Information System (INIS)

    Fontenot, Jonas D; Bloch, Charles; Followill, David; Titt, Uwe; Newhauser, Wayne D

    2010-01-01

    Theoretical calculations have shown that proton therapy can reduce the incidence of radiation-induced secondary malignant neoplasms (SMN) compared with photon therapy for patients with prostate cancer. However, the uncertainties associated with calculations of SMN risk had not been assessed. The objective of this study was to quantify the uncertainties in projected risks of secondary cancer following contemporary proton and photon radiotherapies for prostate cancer. We performed a rigorous propagation of errors and several sensitivity tests to estimate the uncertainty in the ratio of relative risk (RRR) due to the largest contributors to the uncertainty: the radiation weighting factor for neutrons, the dose-response model for radiation carcinogenesis and interpatient variations in absorbed dose. The interval of values for the radiation weighting factor for neutrons and the dose-response model were derived from the literature, while interpatient variations in absorbed dose were taken from actual patient data. The influence of each parameter on a baseline RRR value was quantified. Our analysis revealed that the calculated RRR was insensitive to the largest contributors to the uncertainty. Uncertainties in the radiation weighting factor for neutrons, the shape of the dose-risk model and interpatient variations in therapeutic and stray doses introduced a total uncertainty of 33% to the baseline RRR calculation.

  1. 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.

  2. 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

  3. Clean development mechanism projects and portfolio risks

    International Nuclear Information System (INIS)

    Matsuhashi, Ryuji; Fujisawa, Sei; Mitamura, Wataru; Momobayashi, Yutaka; Yoshida, Yoshikuni

    2004-01-01

    Clean development mechanism (CDM) is expected to facilitate technology transfer from developed to developing countries as well as to economically reduce greenhouse gas emissions. In this article, we explore effective institutions to activate CDM projects. For this purpose, we have estimated internal rate of return (IRR) and other indicators on profitability for 42 CDM or JI projects, taking account of volatilities in the price of certified emission reductions (CER). As a result of Monte Carlo simulations, expected values and standard deviations in the IRR of the projects were quantitatively shown. Then we evaluated various risks in CDM, concluding that diversification of investment is an effective way to suppress these risks. Therefore securitization of CDM finance is proposed as a means of facilitating the diversification of investment. Namely, we present the concept of a CDM bond, which is a project bond with CER. We also investigated the role of governments to suppress risks in CDM. Referring to CERUPT, initiated by the Netherlands' government, the institution of 'insured CERUPT' is proposed to suppress downside risks in the IRR of the projects. We concluded that it is possible to make CDM projects viable by the 'insured CERUPT' and CDM bond

  4. 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

  5. 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.

  6. 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

  7. 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

  8. 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

  9. 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.

  10. Project Portfolio Risk Identification and Analysis, Considering Project Risk Interactions and Using Bayesian Networks

    Directory of Open Access Journals (Sweden)

    Foroogh Ghasemi

    2018-05-01

    Full Text Available An organization’s strategic objectives are accomplished through portfolios. However, the materialization of portfolio risks may affect a portfolio’s sustainable success and the achievement of those objectives. Moreover, project interdependencies and cause–effect relationships between risks create complexity for portfolio risk analysis. This paper presents a model using Bayesian network (BN methodology for modeling and analyzing portfolio risks. To develop this model, first, portfolio-level risks and risks caused by project interdependencies are identified. Then, based on their cause–effect relationships all portfolio risks are organized in a BN. Conditional probability distributions for this network are specified and the Bayesian networks method is used to estimate the probability of portfolio risk. This model was applied to a portfolio of a construction company located in Iran and proved effective in analyzing portfolio risk probability. Furthermore, the model provided valuable information for selecting a portfolio’s projects and making strategic decisions.

  11. 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

  12. Accounting for downscaling and model uncertainty in fine-resolution seasonal climate projections over the Columbia River Basin

    Science.gov (United States)

    Ahmadalipour, Ali; Moradkhani, Hamid; Rana, Arun

    2018-01-01

    Climate change is expected to have severe impacts on natural systems as well as various socio-economic aspects of human life. This has urged scientific communities to improve the understanding of future climate and reduce the uncertainties associated with projections. In the present study, ten statistically downscaled CMIP5 GCMs at 1/16th deg. spatial resolution from two different downscaling procedures are utilized over the Columbia River Basin (CRB) to assess the changes in climate variables and characterize the associated uncertainties. Three climate variables, i.e. precipitation, maximum temperature, and minimum temperature, are studied for the historical period of 1970-2000 as well as future period of 2010-2099, simulated with representative concentration pathways of RCP4.5 and RCP8.5. Bayesian Model Averaging (BMA) is employed to reduce the model uncertainty and develop a probabilistic projection for each variable in each scenario. Historical comparison of long-term attributes of GCMs and observation suggests a more accurate representation for BMA than individual models. Furthermore, BMA projections are used to investigate future seasonal to annual changes of climate variables. Projections indicate significant increase in annual precipitation and temperature, with varied degree of change across different sub-basins of CRB. We then characterized uncertainty of future projections for each season over CRB. Results reveal that model uncertainty is the main source of uncertainty, among others. However, downscaling uncertainty considerably contributes to the total uncertainty of future projections, especially in summer. On the contrary, downscaling uncertainty appears to be higher than scenario uncertainty for precipitation.

  13. Global assessment of water policy vulnerability under uncertainty in water scarcity projections

    Science.gov (United States)

    Greve, Peter; Kahil, Taher; Satoh, Yusuke; Burek, Peter; Fischer, Günther; Tramberend, Sylvia; Byers, Edward; Flörke, Martina; Eisner, Stephanie; Hanasaki, Naota; Langan, Simon; Wada, Yoshihide

    2017-04-01

    Water scarcity is a critical environmental issue worldwide, which has been driven by the significant increase in water extractions during the last century. In the coming decades, climate change is projected to further exacerbate water scarcity conditions in many regions around the world. At present, one important question for policy debate is the identification of water policy interventions that could address the mounting water scarcity problems. Main interventions include investing in water storage infrastructures, water transfer canals, efficient irrigation systems, and desalination plants, among many others. This type of interventions involve long-term planning, long-lived investments and some irreversibility in choices which can shape development of countries for decades. Making decisions on these water infrastructures requires anticipating the long term environmental conditions, needs and constraints under which they will function. This brings large uncertainty in the decision-making process, for instance from demographic or economic projections. But today, climate change is bringing another layer of uncertainty that make decisions even more complex. In this study, we assess in a probabilistic approach the uncertainty in global water scarcity projections following different socioeconomic pathways (SSPs) and climate scenarios (RCPs) within the first half of the 21st century. By utilizing an ensemble of 45 future water scarcity projections based on (i) three state-of-the-art global hydrological models (PCR-GLOBWB, H08, and WaterGAP), (ii) five climate models, and (iii) three water scenarios, we have assessed changes in water scarcity and the associated uncertainty distribution worldwide. The water scenarios used here are developed by IIASA's Water Futures and Solutions (WFaS) Initiative. The main objective of this study is to improve the contribution of hydro-climatic information to effective policymaking by identifying spatial and temporal policy

  14. 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

  15. 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

  16. 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...

  17. 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

  18. 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

  19. Managing geotechnical risk on US design-build transport projects

    Directory of Open Access Journals (Sweden)

    Kevin McLain

    2014-03-01

    Full Text Available Awarding design-build (DB contracts before a complete subsurface investigation is completed, makes mitigating the risk of differing site conditions difficult, if not impossible. The purpose of the study was to identify effective practices for managing geotechnical risk in DB projects, and it reports the results of a survey that included responses from 42 of 50 US state departments of transportation and a content analysis of DB requests for proposals from 26 states to gauge the client’s perspective, as well as 11 structured interviews with DB contractors to obtain the perspective from the other side of the DB contract.  A suite of DB geotechnical risk manage tools is presented based on the results of the analysis. Effective practices were found in three areas: enhancing communications on geotechnical issues before final proposals are submitted; the use of project-specific differing site conditions clauses; and expediting geotechnical design reviews after award. The major finding is that contract verbiage alone is not sufficient to transfer the risk of changed site conditions. The agency must actively communicate all the geotechnical information on hand at the time of the DB procurement and develop a contract strategy that reduces/retires the risk of geotechnical uncertainty as expeditiously as possible after award.

  20. Method ranks competing projects by priorities, risk

    International Nuclear Information System (INIS)

    Moeckel, D.R.

    1993-01-01

    A practical, objective guide for ranking projects based on risk-based priorities has been developed by Sun Pipe Line Co. The deliberately simple system guides decisions on how to allocate scarce company resources because all managers employ the same criteria in weighing potential risks to the company versus benefits. Managers at all levels are continuously having to comply with an ever growing amount of legislative and regulatory requirements while at the same time trying to run their businesses effectively. The system primarily is designed for use as a compliance oversight and tracking process to document, categorize, and follow-up on work concerning various issues or projects. That is, the system consists of an electronic database which is updated periodically, and is used by various levels of management to monitor progress of health, safety, environmental and compliance-related projects. Criteria used in determining a risk factor and assigning a priority also have been adapted and found useful for evaluating other types of projects. The process enables management to better define potential risks and/or loss of benefits that are being accepted when a project is rejected from an immediate work plan or budget. In times of financial austerity, it is extremely important that the right decisions are made at the right time

  1. Risk-profile modification of energy projects

    International Nuclear Information System (INIS)

    Larson, B.O.

    1992-01-01

    The commodity futures and swaps markets are thought to be the invention of speculators, the bane of the oil business, or possibly something confined to finance departments of major corporations. In actuality, they should be considered more as an insurance vehicle and can be used at the project level to modify the risk profile of a property. In this context, an increased familiarity with them can be useful for an engineer. Either futures of swaps can be used to guarantee or modify product prices. While this does not necessarily maximize cash flow or present worth, it can protect a project or company for several years from downside price risk, thereby reducing the risk of the venture. This can be particularly important if lower product prices would cause unacceptable cash flows or net incomes. This paper reports that reducing risk by limiting downside price exposure could alter budgeting decisions, allow continued or expanded operations of a particular property, or increase debt capacity

  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. Financial risks in major investment projects

    International Nuclear Information System (INIS)

    Segelod, Esbjoern

    2006-01-01

    We have probably all read about large projects which proved far more expensive than anticipated, projects such as the Channel tunnel which cost 80% more than planned, and the oil pipeline between the oil field in Prudhoe Bay in Northern Alaska and the oil terminal in Vadez in the south which overran its budget by 1,000%. The purpose of this paper is to summarise our knowledge of the risk of cost escalation. Which projects are more likely than others to be hit by cost escalation, and why

  6. 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

  7. 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.

  8. Revealing, Reducing, and Representing Uncertainties in New Hydrologic Projections for Climate-changed Futures

    Science.gov (United States)

    Arnold, Jeffrey; Clark, Martyn; Gutmann, Ethan; Wood, Andy; Nijssen, Bart; Rasmussen, Roy

    2016-04-01

    The United States Army Corps of Engineers (USACE) has had primary responsibility for multi-purpose water resource operations on most of the major river systems in the U.S. for more than 200 years. In that time, the USACE projects and programs making up those operations have proved mostly robust against the range of natural climate variability encountered over their operating life spans. However, in some watersheds and for some variables, climate change now is known to be shifting the hydroclimatic baseline around which that natural variability occurs and changing the range of that variability as well. This makes historical stationarity an inappropriate basis for assessing continued project operations under climate-changed futures. That means new hydroclimatic projections are required at multiple scales to inform decisions about specific threats and impacts, and for possible adaptation responses to limit water-resource vulnerabilities and enhance operational resilience. However, projections of possible future hydroclimatologies have myriad complex uncertainties that require explicit guidance for interpreting and using them to inform those decisions about climate vulnerabilities and resilience. Moreover, many of these uncertainties overlap and interact. Recent work, for example, has shown the importance of assessing the uncertainties from multiple sources including: global model structure [Meehl et al., 2005; Knutti and Sedlacek, 2013]; internal climate variability [Deser et al., 2012; Kay et al., 2014]; climate downscaling methods [Gutmann et al., 2012; Mearns et al., 2013]; and hydrologic models [Addor et al., 2014; Vano et al., 2014; Mendoza et al., 2015]. Revealing, reducing, and representing these uncertainties is essential for defining the plausible quantitative climate change narratives required to inform water-resource decision-making. And to be useful, such quantitative narratives, or storylines, of climate change threats and hydrologic impacts must sample

  9. Influence of the Risk-Contributing Factors on the Financing of the Investment Project for Building of Intelligent Buildings

    OpenAIRE

    Voytolovskiy Nikolay; Trebukhin Anatoliy; Shoshinov Vitaly

    2017-01-01

    This article provides the generic classification of risks of the investment projects for the construction of intelligent buildings which differ by the detachment of the subjective perception of risk by the investor. Risk and uncertainty were justified as system characteristics of the investment projects for the construction of intelligent buildings. Characteristics of the development was given in the context of project management. Methodical schemes of the development of the investment projec...

  10. Management and minimisation of uncertainties and errors in numerical aerodynamics results of the German collaborative project MUNA

    CERN Document Server

    Barnewitz, Holger; Fritz, Willy; Thiele, Frank

    2013-01-01

    This volume reports results from the German research initiative MUNA (Management and Minimization of Errors and Uncertainties in Numerical Aerodynamics), which combined development activities of the German Aerospace Center (DLR), German universities and German aircraft industry. The main objective of this five year project was the development of methods and procedures aiming at reducing various types of uncertainties that are typical of numerical flow simulations. The activities were focused on methods for grid manipulation, techniques for increasing the simulation accuracy, sensors for turbulence modelling, methods for handling uncertainties of the geometry and grid deformation as well as stochastic methods for quantifying aleatoric uncertainties.

  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. Overcoming the risk of inaction from emissions uncertainty in smallholder agriculture

    Science.gov (United States)

    Berry, N. J.; Ryan, C. M.

    2013-03-01

    research to other areas with similar land uses and environmental conditions, or to combine information on land use activities with process-based models that describe expected emissions and carbon accumulation under specified conditions. Unfortunately long-term studies that have measured biomass and soil organic carbon accumulation in smallholder agriculture are scarce, and default values developed for national level emissions assessments (IPCC 2006) fail to capture local variability and may not scale linearly, so cannot be applied at the project scale without introducing considerable uncertainty and the potential for bias. If there is reliable information on the agricultural activities and environmental conditions at a project site, process-based models can provide accurate estimations of agricultural greenhouse gas fluxes that capture temporal and spatial variability (Olander 2012) but collecting the necessary data to parameterize and drive the models can be costly and time consuming. Assessing and monitoring greenhouse gas fluxes in smallholder agriculture therefore involves a balance between the resources required to collect information from thousands of smallholders across large areas, and the accuracy and precision of model predictions. Accuracy, or the absence of bias, is clearly an important consideration in the quantification of mitigation benefits for performance-based finance since a bias towards over-estimation of mitigation achieved would risk misallocating limited finance to projects that have not achieved mitigation benefits. Such a bias would also lead to a net increase in emissions if credits were used to offset emissions elsewhere. The accuracy of model predictions is related to uncertainty in model input data, which affects the precision of predictions, and errors in the model structure (Olander 2012). To limit the risk that projects receive credit for mitigation benefits that are not real, a precise-or-conservative approach to carbon accounting has

  14. 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)

  15. The influence of perceived uncertainty on entrepreneurial action in emerging renewable energy technology; biomass gasification projects in the Netherlands

    International Nuclear Information System (INIS)

    Meijer, Ineke S.M.; Hekkert, Marko P.; Koppenjan, Joop F.M.

    2007-01-01

    Emerging renewable energy technologies cannot break through without the involvement of entrepreneurs who dare to take action amidst uncertainty. The uncertainties that the entrepreneurs involved perceive will greatly affect their innovation decisions and can prevent them from engaging in innovation projects aimed at developing and implementing emerging renewable energy technologies. This article analyzes how perceived uncertainties and motivation influence an entrepreneur's decision to act, using empirical data on biomass gasification projects in the Netherlands. Our empirical results show that technological, political and resource uncertainty are the most dominant sources of perceived uncertainty influencing entrepreneurial decision-making. By performing a dynamic analysis, we furthermore demonstrate that perceived uncertainties and motivation are not stable, but evolve over time. We identify critical factors in the project's internal and external environment which influence these changes in perceived uncertainties and motivation, and describe how various interactions between the different variables in the conceptual model (internal and external factors, perceived uncertainty, motivation and previous actions of the entrepreneurs) positively or negatively influence the decision of entrepreneurs to continue entrepreneurial action. We discuss how policymakers can use these insights for stimulating the development and diffusion of emerging renewable energy technologies

  16. 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....

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

    Energy Technology Data Exchange (ETDEWEB)

    Walter, Lena Sophie

    2013-07-01

    Carbon capture and storage (CCS) in deep geological formations is one possible option to mitigate the greenhouse gas effect by reducing CO{sub 2} emissions into the atmosphere. The assessment of the risks related to CO{sub 2} storage is an important task. Events such as CO{sub 2} leakage and brine displacement could result in hazards for human health and the environment. In this thesis, a systematic and comprehensive risk assessment concept is presented to investigate various levels of uncertainties and to assess risks using numerical simulations. Depending on the risk and the processes, which should be assessed, very complex models, large model domains, large time scales, and many simulations runs for estimating probabilities are required. To reduce the resulting high computational costs, a model reduction technique (the arbitrary polynomial chaos expansion) and a method for model coupling in space are applied. The different levels of uncertainties are: statistical uncertainty in parameter distributions, scenario uncertainty, e.g. different geological features, and recognized ignorance due to assumptions in the conceptual model set-up. Recognized ignorance and scenario uncertainty are investigated by simulating well defined model set-ups and scenarios. According to damage values, which are defined as a model output, the set-ups and scenarios can be compared and ranked. For statistical uncertainty probabilities can be determined by running Monte Carlo simulations with the reduced model. The results are presented in various ways: e.g., mean damage, probability density function, cumulative distribution function, or an overall risk value by multiplying the damage with the probability. If the model output (damage) cannot be compared to provided criteria (e.g. water quality criteria), analytical approximations are presented to translate the damage into comparable values. The overall concept is applied for the risks related to brine displacement and infiltration into

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

    International Nuclear Information System (INIS)

    Walter, Lena Sophie

    2013-01-01

    Carbon capture and storage (CCS) in deep geological formations is one possible option to mitigate the greenhouse gas effect by reducing CO 2 emissions into the atmosphere. The assessment of the risks related to CO 2 storage is an important task. Events such as CO 2 leakage and brine displacement could result in hazards for human health and the environment. In this thesis, a systematic and comprehensive risk assessment concept is presented to investigate various levels of uncertainties and to assess risks using numerical simulations. Depending on the risk and the processes, which should be assessed, very complex models, large model domains, large time scales, and many simulations runs for estimating probabilities are required. To reduce the resulting high computational costs, a model reduction technique (the arbitrary polynomial chaos expansion) and a method for model coupling in space are applied. The different levels of uncertainties are: statistical uncertainty in parameter distributions, scenario uncertainty, e.g. different geological features, and recognized ignorance due to assumptions in the conceptual model set-up. Recognized ignorance and scenario uncertainty are investigated by simulating well defined model set-ups and scenarios. According to damage values, which are defined as a model output, the set-ups and scenarios can be compared and ranked. For statistical uncertainty probabilities can be determined by running Monte Carlo simulations with the reduced model. The results are presented in various ways: e.g., mean damage, probability density function, cumulative distribution function, or an overall risk value by multiplying the damage with the probability. If the model output (damage) cannot be compared to provided criteria (e.g. water quality criteria), analytical approximations are presented to translate the damage into comparable values. The overall concept is applied for the risks related to brine displacement and infiltration into drinking water

  19. 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.

  20. 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)

  1. Bayesian-network-based safety risk analysis in construction projects

    International Nuclear Information System (INIS)

    Zhang, Limao; Wu, Xianguo; Skibniewski, Miroslaw J.; Zhong, Jingbing; Lu, Yujie

    2014-01-01

    This paper presents a systemic decision support approach for safety risk analysis under uncertainty in tunnel construction. Fuzzy Bayesian Networks (FBN) is used to investigate causal relationships between tunnel-induced damage and its influential variables based upon the risk/hazard mechanism analysis. Aiming to overcome limitations on the current probability estimation, an expert confidence indicator is proposed to ensure the reliability of the surveyed data for fuzzy probability assessment of basic risk factors. A detailed fuzzy-based inference procedure is developed, which has a capacity of implementing deductive reasoning, sensitivity analysis and abductive reasoning. The “3σ criterion” is adopted to calculate the characteristic values of a triangular fuzzy number in the probability fuzzification process, and the α-weighted valuation method is adopted for defuzzification. The construction safety analysis progress is extended to the entire life cycle of risk-prone events, including the pre-accident, during-construction continuous and post-accident control. A typical hazard concerning the tunnel leakage in the construction of Wuhan Yangtze Metro Tunnel in China is presented as a case study, in order to verify the applicability of the proposed approach. The results demonstrate the feasibility of the proposed approach and its application potential. A comparison of advantages and disadvantages between FBN and fuzzy fault tree analysis (FFTA) as risk analysis tools is also conducted. The proposed approach can be used to provide guidelines for safety analysis and management in construction projects, and thus increase the likelihood of a successful project in a complex environment. - Highlights: • A systemic Bayesian network based approach for safety risk analysis is developed. • An expert confidence indicator for probability fuzzification is proposed. • Safety risk analysis progress is extended to entire life cycle of risk-prone events. • A typical

  2. 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

  3. A risk-based evaluation of the impact of key uncertainties on the prediction of severe accident source terms - STU

    International Nuclear Information System (INIS)

    Ang, M.L.; Grindon, E.; Dutton, L.M.C.; Garcia-Sedano, P.; Santamaria, C.S.; Centner, B.; Auglaire, M.; Routamo, T.; Outa, S.; Jokiniemi, J.; Gustavsson, V.; Wennerstrom, H.; Spanier, L.; Gren, M.; Boschiero, M-H; Droulas, J-L; Friederichs, H-G; Sonnenkalb, M.

    2001-01-01

    The purpose of this project is to address the key uncertainties associated with a number of fission product release and transport phenomena in a wider context and to assess their relevance to key severe accident sequences. This project is a wide-based analysis involving eight reactor designs that are representative of the reactors currently operating in the European Union (EU). In total, 20 accident sequences covering a wide range of conditions have been chosen to provide the basis for sensitivity studies. The appraisal is achieved through a systematic risk-based framework developed within this project. Specifically, this is a quantitative interpretation of the sensitivity calculations on the basis of 'significance indicators', applied above defined threshold values. These threshold values represent a good surrogate for 'large release', which is defined in a number of EU countries. In addition, the results are placed in the context of in-containment source term limits, for advanced light water reactor designs, as defined by international guidelines. Overall, despite the phenomenological uncertainties, the predicted source terms (both into the containment, and subsequently, into the environment) do not display a high degree of sensitivity to the individual fission product issues addressed in this project. This is due, mainly, to the substantial capacity for the attenuation of airborne fission products by the designed safety provisions and the natural fission product retention mechanisms within the containment

  4. 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

  5. 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.

  6. The Role of Type and Source of Uncertainty on the Processing of Climate Models Projections.

    Science.gov (United States)

    Benjamin, Daniel M; Budescu, David V

    2018-01-01

    Scientists agree that the climate is changing due to human activities, but there is less agreement about the specific consequences and their timeline. Disagreement among climate projections is attributable to the complexity of climate models that differ in their structure, parameters, initial conditions, etc. We examine how different sources of uncertainty affect people's interpretation of, and reaction to, information about climate change by presenting participants forecasts from multiple experts. Participants viewed three types of sets of sea-level rise projections: (1) precise, but conflicting ; (2) imprecise , but agreeing, and (3) hybrid that were both conflicting and imprecise. They estimated the most likely sea-level rise, provided a range of possible values and rated the sets on several features - ambiguity, credibility, completeness, etc. In Study 1, everyone saw the same hybrid set. We found that participants were sensitive to uncertainty between sources, but not to uncertainty about which model was used. The impacts of conflict and imprecision were combined for estimation tasks and compromised for feature ratings . Estimates were closer to the experts' original projections, and sets were rated more favorably under imprecision. Estimates were least consistent with (narrower than) the experts in the hybrid condition, but participants rated the conflicting set least favorably. In Study 2, we investigated the hybrid case in more detail by creating several distinct interval sets that combine conflict and imprecision. Two factors drive perceptual differences: overlap - the structure of the forecast set (whether intersecting, nested, tangent, or disjoint) - and a symmetry - the balance of the set. Estimates were primarily driven by asymmetry, and preferences were primarily driven by overlap. Asymmetric sets were least consistent with the experts: estimated ranges were narrower, and estimates of the most likely value were shifted further below the set mean

  7. The study of the risk management model of construction project

    International Nuclear Information System (INIS)

    Jiang Bo; Feng Yanping; Liu Changbin

    2010-01-01

    The paper first analyzed the development of the risk management of construction project and the risk management processes, and then briefly introduced the risk management experience of foreign project management. From the project management by objectives point of view, the greatest risk came from the lack of clarity of the objectives in the project management, which led to the project's risk emergence. In the analysis of the principles of the project objectives identification and risk allocation, the paper set up a project management model which insurance companies involved in the whole process of the project management, and simply analyzed the roles of insurance company at last. (authors)

  8. Comparisons on International Approaches of Business and Project Risk Management

    OpenAIRE

    Nadia Carmen ENE

    2005-01-01

    In this article we intend to present a comparative approach between three recognized international methodologies for risk management: RISKMAN, Project Management Institute Methodology-PMBoK and Project Risk Analysis and Management Guide (produced by Association for Project Management).

  9. 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

  10. 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

  11. 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

  12. PROJECT MANAGER SKILLS, RISK MANAGEMENT TOOLS

    Directory of Open Access Journals (Sweden)

    Vladut Iacob

    2013-12-01

    Full Text Available Although the projects are different from each other there are many common things that contribute to their success. Looked overall, the success of a project is the result of a multitude of factors. This person is considered the "engine" of the project. The man who makes the action set for the achievement of project objectives to be brought to an end. The project manager must have the technical knowledge and economic diverse. He should be able to choose a team and lead. You must be tenacious, combative, to know how to communicate both within the team and beyond. In a word, the project manager must have an impressive stock of knowledge, skills and abilities and appreciate as Peter Drucker, to "exist for the organization. To be its servant. Any management who forget this will only cause damage to the organization. "This study will focus on highlighting the skills of the project manager and their role in managing difficult situations or risk.

  13. 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

  14. Using prior risk-related knowledge to support risk management decisions: lessons learnt from a tunneling project.

    Science.gov (United States)

    Cárdenas, Ibsen Chivatá; Al-Jibouri, Saad S H; Halman, Johannes I M; van de Linde, Wim; Kaalberg, Frank

    2014-10-01

    The authors of this article have developed six probabilistic causal models for critical risks in tunnel works. The details of the models' development and evaluation were reported in two earlier publications of this journal. Accordingly, as a remaining step, this article is focused on the investigation into the use of these models in a real case study project. The use of the models is challenging given the need to provide information on risks that usually are both project and context dependent. The latter is of particular concern in underground construction projects. Tunnel risks are the consequences of interactions between site- and project-specific factors. Large variations and uncertainties in ground conditions as well as project singularities give rise to particular risk factors with very specific impacts. These circumstances mean that existing risk information, gathered from previous projects, is extremely difficult to use in other projects. This article considers these issues and addresses the extent to which prior risk-related knowledge, in the form of causal models, as the models developed for the investigation, can be used to provide useful risk information for the case study project. The identification and characterization of the causes and conditions that lead to failures and their interactions as well as their associated probabilistic information is assumed to be risk-related knowledge in this article. It is shown that, irrespective of existing constraints on using information and knowledge from past experiences, construction risk-related knowledge can be transferred and used from project to project in the form of comprehensive models based on probabilistic-causal relationships. The article also shows that the developed models provide guidance as to the use of specific remedial measures by means of the identification of critical risk factors, and therefore they support risk management decisions. Similarly, a number of limitations of the models are

  15. 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.

  16. 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.

  17. 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

  18. 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.

  19. 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

  20. On quantifying uncertainty for project selection: the case of renewable energy sources' investment

    International Nuclear Information System (INIS)

    Kirytopoulos, Konstantinos; Rentizelas, Athanassios; Tziralis, Georgios

    2006-01-01

    The selection of a project among different alternatives, considering the limited resources of a company (organisation), is an added value process that determines the prosperity of an undertaken project (investment). This applies also to the 'boming' Renewable Energy Sector, especially under the circumstances established by the recent activation of the Kyoto protocal and by the plethora of available choices for renewable energy sources (RES) projjects. The need for a reliable project selection method among the various alternatives is, therefore, highlighted and, in this context, the paper proposes the NPV function as one of possible criteria for the selection of a RES project. Furthermore, it differentiates from the typical NPV calculation process by adding the concept of a probabilistic NPV approach through Monte Carlo simulation. Reality is non-deterministic, so any attempt of modelling it by using a deterministic approach is by definition erroneous. The paper ultimately proposes a process of substituting the point with a range estimation, capable of quantifying the various uncertainty factors and in this way elucidate the accomplishment possibilities of eligible scenarious. The paper is enhanced by case study showing how the proposed method can be practically applied to support the investment decision, thus enabling the decision makers to judge its effectiveness and usefulness.(Author)

  1. Model Evaluation and Uncertainty in Agricultural Impacts Assessments: Results and Strategies from the Agricultural Model Intercomparison and Improvement Project (AgMIP)

    Science.gov (United States)

    Rosenzweig, C.; Hatfield, J.; Jones, J. W.; Ruane, A. C.

    2012-12-01

    The Agricultural Model Intercomparison and Improvement Project (AgMIP) is an international effort to assess the state of global agricultural modeling and to understand climate impacts on the agricultural sector. AgMIP connects the climate science, crop modeling, and agricultural economic modeling communities to generate probabilistic projections of current and future climate impacts. The goals of AgMIP are to improve substantially the characterization of risk of hunger and world food security due to climate change and to enhance adaptation capacity in both developing and developed countries. This presentation will describe the general approach of AgMIP, highlight AgMIP efforts to evaluate climate, crop, and economic models, and discuss AgMIP uncertainty assessments. Model evaluation efforts will be outlined using examples from various facets of AgMIP, including climate scenario generation, the wheat crop model intercomparison, and the global agricultural economics model intercomparison being led in collaboration with the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP). Strategies developed to quantify uncertainty in each component of AgMIP, as well as the propagation of uncertainty through the climate-crop-economic modeling framework, will be detailed and preliminary uncertainty assessments that highlight crucial areas requiring improved models and data collection will be introduced.

  2. 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.

  3. A scaling approach to project regional sea level rise and its uncertainties

    Directory of Open Access Journals (Sweden)

    M. Perrette

    2013-01-01

    Full Text Available Climate change causes global mean sea level to rise due to thermal expansion of seawater and loss of land ice from mountain glaciers, ice caps and ice sheets. Locally, sea level can strongly deviate from the global mean rise due to changes in wind and ocean currents. In addition, gravitational adjustments redistribute seawater away from shrinking ice masses. However, the land ice contribution to sea level rise (SLR remains very challenging to model, and comprehensive regional sea level projections, which include appropriate gravitational adjustments, are still a nascent field (Katsman et al., 2011; Slangen et al., 2011. Here, we present an alternative approach to derive regional sea level changes for a range of emission and land ice melt scenarios, combining probabilistic forecasts of a simple climate model (MAGICC6 with the new CMIP5 general circulation models. The contribution from ice sheets varies considerably depending on the assumptions for the ice sheet projections, and thus represents sizeable uncertainties for future sea level rise. However, several consistent and robust patterns emerge from our analysis: at low latitudes, especially in the Indian Ocean and Western Pacific, sea level will likely rise more than the global mean (mostly by 10–20%. Around the northeastern Atlantic and the northeastern Pacific coasts, sea level will rise less than the global average or, in some rare cases, even fall. In the northwestern Atlantic, along the American coast, a strong dynamic sea level rise is counteracted by gravitational depression due to Greenland ice melt; whether sea level will be above- or below-average will depend on the relative contribution of these two factors. Our regional sea level projections and the diagnosed uncertainties provide an improved basis for coastal impact analysis and infrastructure planning for adaptation to climate change.

  4. [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.

  5. Hotspots of uncertainty in land-use and land-cover change projections: a global-scale model comparison.

    Science.gov (United States)

    Prestele, Reinhard; Alexander, Peter; Rounsevell, Mark D A; Arneth, Almut; Calvin, Katherine; Doelman, Jonathan; Eitelberg, David A; Engström, Kerstin; Fujimori, Shinichiro; Hasegawa, Tomoko; Havlik, Petr; Humpenöder, Florian; Jain, Atul K; Krisztin, Tamás; Kyle, Page; Meiyappan, Prasanth; Popp, Alexander; Sands, Ronald D; Schaldach, Rüdiger; Schüngel, Jan; Stehfest, Elke; Tabeau, Andrzej; Van Meijl, Hans; Van Vliet, Jasper; Verburg, Peter H

    2016-12-01

    Model-based global projections of future land-use and land-cover (LULC) change are frequently used in environmental assessments to study the impact of LULC change on environmental services and to provide decision support for policy. These projections are characterized by a high uncertainty in terms of quantity and allocation of projected changes, which can severely impact the results of environmental assessments. In this study, we identify hotspots of uncertainty, based on 43 simulations from 11 global-scale LULC change models representing a wide range of assumptions of future biophysical and socioeconomic conditions. We attribute components of uncertainty to input data, model structure, scenario storyline and a residual term, based on a regression analysis and analysis of variance. From this diverse set of models and scenarios, we find that the uncertainty varies, depending on the region and the LULC type under consideration. Hotspots of uncertainty appear mainly at the edges of globally important biomes (e.g., boreal and tropical forests). Our results indicate that an important source of uncertainty in forest and pasture areas originates from different input data applied in the models. Cropland, in contrast, is more consistent among the starting conditions, while variation in the projections gradually increases over time due to diverse scenario assumptions and different modeling approaches. Comparisons at the grid cell level indicate that disagreement is mainly related to LULC type definitions and the individual model allocation schemes. We conclude that improving the quality and consistency of observational data utilized in the modeling process and improving the allocation mechanisms of LULC change models remain important challenges. Current LULC representation in environmental assessments might miss the uncertainty arising from the diversity of LULC change modeling approaches, and many studies ignore the uncertainty in LULC projections in assessments of LULC

  6. Risk evaluation and mitigation in domestic photovoltaic projects: According to the UK climate polcy

    OpenAIRE

    Atigeh Chian, Milan

    2013-01-01

    2013 dissertation for MSc in Project Management. Selected by academic staff as a good example of a masters level dissertation. \\ud \\ud In the wake of financial crisis, many investors are faced with the uncertainty\\ud in investment decision as a result of the volatility in the market. In an\\ud attempt to reduce this risk of uncertainties, investors have therefore\\ud provided different method of risk management.\\ud Past studies has shown the importance of fund managers in the management\\ud of f...

  7. 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.

  8. 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.

  9. 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)

  10. Quantifying Carbon Financial Risk in the International Greenhouse Gas Market: An Application Using Remotely-Sensed Data to Align Scientific Uncertainty with Financial Decisions

    Science.gov (United States)

    Hultman, N. E.

    2002-12-01

    A common complaint about environmental policy is that regulations inadequately reflect scientific uncertainty and scientific consensus. While the causes of this phenomenon are complex and hard to discern, we know that corporations are the primary implementers of environmental regulations; therefore, focusing on how policy relates scientific knowledge to corporate decisions can provide valuable insights. Within the context of the developing international market for greenhouse gas emissions, I examine how corporations would apply finance theory into their investment decisions for carbon abatement projects. Using remotely-sensed ecosystem scale carbon flux measurements, I show how to determine much financial risk of carbon is diversifiable. I also discuss alternative, scientifically sound methods for hedging the non-diversifiable risks in carbon abatement projects. In providing a quantitative common language for scientific and corporate uncertainties, the concept of carbon financial risk provides an opportunity for expanding communication between these elements essential to successful climate policy.

  11. Lobatto-Milstein Numerical Method in Application of Uncertainty Investment of Solar Power Projects

    Directory of Open Access Journals (Sweden)

    Mahmoud A. Eissa

    2017-01-01

    Full Text Available Recently, there has been a growing interest in the production of electricity from renewable energy sources (RES. The RES investment is characterized by uncertainty, which is long-term, costly and depends on feed-in tariff and support schemes. In this paper, we address the real option valuation (ROV of a solar power plant investment. The real option framework is investigated. This framework considers the renewable certificate price and, further, the cost of delay between establishing and operating the solar power plant. The optimal time of launching the project and assessing the value of the deferred option are discussed. The new three-stage numerical methods are constructed, the Lobatto3C-Milstein (L3CM methods. The numerical methods are integrated with the concept of Black–Scholes option pricing theory and applied in option valuation for solar energy investment with uncertainty. The numerical results of the L3CM, finite difference and Monte Carlo methods are compared to show the efficiency of our methods. Our dataset refers to the Arab Republic of Egypt.

  12. Applied software risk management a guide for software project managers

    CERN Document Server

    Pandian, C Ravindranath

    2006-01-01

    Few software projects are completed on time, on budget, and to their original specifications. Focusing on what practitioners need to know about risk in the pursuit of delivering software projects, Applied Software Risk Management: A Guide for Software Project Managers covers key components of the risk management process and the software development process, as well as best practices for software risk identification, risk planning, and risk analysis. Written in a clear and concise manner, this resource presents concepts and practical insight into managing risk. It first covers risk-driven project management, risk management processes, risk attributes, risk identification, and risk analysis. The book continues by examining responses to risk, the tracking and modeling of risks, intelligence gathering, and integrated risk management. It concludes with details on drafting and implementing procedures. A diary of a risk manager provides insight in implementing risk management processes.Bringing together concepts ...

  13. Correlational Study of Risk Management and Information Technology Project Success

    Science.gov (United States)

    Gillespie, Seth J.

    2014-01-01

    Many IT projects fail despite the best efforts to keep these projects within budget, schedule, and scope. Few studies have looked at the effect of project risk management tools and techniques on project success. The primary focus of this study was to examine the extent to which utilization of project risk management processes influence project…

  14. Spatial uncertainty in bias corrected climate change projections and hydrogeological impacts

    DEFF Research Database (Denmark)

    Seaby, Lauren Paige; Refsgaard, Jens Christian; Sonnenborg, Torben

    2015-01-01

    Model pairing, this paper analyses the relationship between complexity and robustness of three distribution-based scaling (DBS) bias correction methods applied to daily precipitation at various spatial scales. Hydrological simulations are forced by CM inputs to assess the spatial uncertainty......The question of which climate model bias correction methods and spatial scales for correction are optimal for both projecting future hydrological changes as well as removing initial model bias has so far received little attention. For 11 climate models (CMs), or GCM/RCM – Global/Regional Climate...... signals. The magnitude of spatial bias seen in precipitation inputs does not necessarily correspond to the magnitude of biases seen in hydrological outputs. Variables that integrate basin responses over time and space are more sensitive to mean spatial biases and less so on extremes. Hydrological...

  15. PECULIARITIES OF ASSESSMENT AND RISK MANAGEMENT IN INNOVATIVE PROJECTS

    Directory of Open Access Journals (Sweden)

    Victor V. Guzhov

    2014-01-01

    Full Text Available The methodological and methodicalbases of risk management in innovativeprojects. Classification of risks. Types of risks depending on the stage of realizationof the innovative project. Investigated thefactors contributing to the emergence ofrisk situations. The basic techniques of risk management of innovation projects.Proposed criteria for the choice of the innovative project to implement in the realsector of the economy.

  16. Dynamic modeling of uncertainty in the planned values of investments in petrochemical and refining projects

    International Nuclear Information System (INIS)

    Vianello, Juliano Melquiades; Costa, Leticia; Teixeira, José Paulo

    2014-01-01

    There is a large gap between the planned value of investment in a project and its financial implementation. This fact creates a mismatch between the planned and effectively achieved net present value (NPV) of the project. Considering the project portfolio of a company, this could even threaten your solvency in the future. Therefore, a quantitative-risk analysis that takes into account different possible scenarios for these values of investment is extremely important to measure statistically the real value of a project. The aim of this paper is to present the reasons for this mismatch between planned and executed investments and, from this study, obtain a suitable stochastic process to generate different scenarios for these investments in the oil industry. Although the results are valid for projects in the petrochemical and refining sector, also called in the oil industry as downstream, the methodology can be applied to the upstream or even other branches of industry. - Highlights: • We measure statistically the real value of an investment project. • We present the reasons for the mismatch between planned and executed investments. • We obtain a stochastic process to generate scenarios for oil industry investments. • Results are valid for projects in the petrochemical and refining sector, downstream. • The methodology can be applied to the upstream or even other branches of industry

  17. 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.

  18. 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.

  19. Fast computation of statistical uncertainty for spatiotemporal distributions estimated directly from dynamic cone beam SPECT projections

    International Nuclear Information System (INIS)

    Reutter, Bryan W.; Gullberg, Grant T.; Huesman, Ronald H.

    2001-01-01

    The estimation of time-activity curves and kinetic model parameters directly from projection data is potentially useful for clinical dynamic single photon emission computed tomography (SPECT) studies, particularly in those clinics that have only single-detector systems and thus are not able to perform rapid tomographic acquisitions. Because the radiopharmaceutical distribution changes while the SPECT gantry rotates, projections at different angles come from different tracer distributions. A dynamic image sequence reconstructed from the inconsistent projections acquired by a slowly rotating gantry can contain artifacts that lead to biases in kinetic parameters estimated from time-activity curves generated by overlaying regions of interest on the images. If cone beam collimators are used and the focal point of the collimators always remains in a particular transaxial plane, additional artifacts can arise in other planes reconstructed using insufficient projection samples [1]. If the projection samples truncate the patient's body, this can result in additional image artifacts. To overcome these sources of bias in conventional image based dynamic data analysis, we and others have been investigating the estimation of time-activity curves and kinetic model parameters directly from dynamic SPECT projection data by modeling the spatial and temporal distribution of the radiopharmaceutical throughout the projected field of view [2-8]. In our previous work we developed a computationally efficient method for fully four-dimensional (4-D) direct estimation of spatiotemporal distributions from dynamic SPECT projection data [5], which extended Formiconi's least squares algorithm for reconstructing temporally static distributions [9]. In addition, we studied the biases that result from modeling various orders temporal continuity and using various time samplings [5]. the present work, we address computational issues associated with evaluating the statistical uncertainty of

  20. 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.

  1. Evaluation of Projected Agricultural Climate Risk over the Contiguous US

    Science.gov (United States)

    Zhu, X.; Troy, T. J.; Devineni, N.

    2017-12-01

    Food demands are rising due to an increasing population with changing food preferences, which places pressure on agricultural production. Additionally, climate extremes have recently highlighted the vulnerability of our agricultural system to climate variability. This study seeks to fill two important gaps in current knowledge: how does the widespread response of irrigated crops differ from rainfed and how can we best account for uncertainty in yield responses. We developed a stochastic approach to evaluate climate risk quantitatively to better understand the historical impacts of climate change and estimate the future impacts it may bring about to agricultural system. Our model consists of Bayesian regression, distribution fitting, and Monte Carlo simulation to simulate rainfed and irrigated crop yields at the US county level. The model was fit using historical data for 1970-2010 and was then applied over different climate regions in the contiguous US using the CMIP5 climate projections. The relative importance of many major growing season climate indices, such as consecutive dry days without rainfall or heavy precipitation, was evaluated to determine what climate indices play a role in affecting future crop yields. The statistical modeling framework also evaluated the impact of irrigation by using county-level irrigated and rainfed yields separately. Furthermore, the projected years with negative yield anomalies were specifically evaluated in terms of magnitude, trend and potential climate drivers. This framework provides estimates of the agricultural climate risk for the 21st century that account for the full uncertainty of climate occurrences, range of crop response, and spatial correlation in climate. The results of this study can contribute to decision making about crop choice and water use in an uncertain future climate.

  2. Gold and Displacement in Eastern Europe: Risks and Uncertainty at Roşia Montană

    Directory of Open Access Journals (Sweden)

    FILIP ALEXANDRESCU

    2011-01-01

    Full Text Available The Canadian-Romanian gold mining project at Roşia Montanǎ in Romania is known as the largest opencast gold mine being planned now in Europe. It involves the displacement of several thousand inhabitants, mostly former gold miners and a smaller number of farmers. The land and houses of more than three quarters of this population have already been acquired by the project owners, although the project has not yet received its formal environmental clearance. The paper analyzes the risks facing the displaced population of Roşia Montană, employing as analytical methodology the Impoverishment Risks and Reconstruction (IRR model, developed by Michael M. Cernea. The paper argues for an expansion of the IRR model. By taking into account the macro (extralocal forces that shape displacement and paying closer attention to the micro (subjective experience of this process, it becomes possible to understand the effects of uncertainty and vulnerability in displacement. The author's participant observations and in-depth interviews with local families are complemented with secondary analyses of data from several other socio-economic surveys and with the analysis of the Resettlement and Relocation Action Plan of the project owners.

  3. The influence of climate change on flood risks in France ­- first estimates and uncertainty analysis

    OpenAIRE

    Dumas , Patrice; Hallegatte , Sréphane; Quintana-Seguí , Pere; Martin , Eric

    2013-01-01

    International audience; Abstract. 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...

  4. 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...

  5. 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.

  6. 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.

  7. 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

  8. 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

  9. 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)

  10. Risk profile modification of energy projects

    International Nuclear Information System (INIS)

    Larson, B.O.

    1992-01-01

    The commodity futures and swaps markets are thought by some to be the invention of speculators, the bane of the oil business, or possibly something confined to finance departments of major corporations. In actuality, they should be considered more as insurance and can be utilized at the project level to modify the risk profile of a property. In this context, an increased familiarity with them can be useful for an engineer. This paper reports that either futures or swaps can be used to guarantee or modify product prices, an accomplishment very difficult or impossible to duplicate through other means, particularly with such integrity. Participation in futures or swaps does not necessarily maximize cashflow or present worth, it can either guarantee the price, put a minimum price in place or offer a combination of the above. A project or company can be protected for several years from downside price risk using swaps. Not being subject to market price swings substantially reduces the risk of the venture. This can be particularly important if lower product prices would cause unacceptable cashflows or net incomes

  11. Risk Factors in ERP Implementation Projects for Process Oriented

    Directory of Open Access Journals (Sweden)

    Andrzej Partyka

    2009-09-01

    Full Text Available This paper present review and analysis of risk factors, which could affect successful implementation of ERP system, for project performed in project oriented organizations. Presented risk breakdown structure and the list of common risk factors, are well-suited for ERP implementation projects. Considered risk categories allow for complex risk analysis. Additionally, mapping of risk importance for particular implementation phases is presented. Making presented model an important input for project risk management process, especially for the beginning phases which require identification of risk factors.

  12. 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

  13. Remarkable link between projected uncertainties of Arctic sea-ice decline and winter Eurasian climate

    Science.gov (United States)

    Cheung, Hoffman H. N.; Keenlyside, Noel; Omrani, Nour-Eddine; Zhou, Wen

    2018-01-01

    We identify that the projected uncertainty of the pan-Arctic sea-ice concentration (SIC) is strongly coupled with the Eurasian circulation in the boreal winter (December-March; DJFM), based on a singular value decomposition (SVD) analysis of the forced response of 11 CMIP5 models. In the models showing a stronger sea-ice decline, the Polar cell becomes weaker and there is an anomalous increase in the sea level pressure (SLP) along 60°N, including the Urals-Siberia region and the Iceland low region. There is an accompanying weakening of both the midlatitude westerly winds and the Ferrell cell, where the SVD signals are also related to anomalous sea surface temperature warming in the midlatitude North Atlantic. In the Mediterranean region, the anomalous circulation response shows a decreasing SLP and increasing precipitation. The anomalous SLP responses over the Euro-Atlantic region project on to the negative North Atlantic Oscillation-like pattern. Altogether, pan-Arctic SIC decline could strongly impact the winter Eurasian climate, but we should be cautious about the causality of their linkage.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. '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.

  20. 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.

  1. 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)

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. Financial feasibility analysis on small medium reactor nuclear power plant (SMR NPP) project in Indonesia under uncertainty

    International Nuclear Information System (INIS)

    Nuryanti; Suparman; Mochamad Nasrullah; Elok Satiti Amitayani; Wiku Lulus Widodo

    2015-01-01

    NPP SMR is one alternative to overcome the Outside Java Bali region's dependence on diesel power plant. One crucial issue in the NPP project (including SMR) would be financing, associated with the capital-intensive nature of the project. In addition, the SMR NPP project also be vulnerable in occurrence of some uncertainties. Therefore, this study aimed to analyze the financial feasibility of SMR NPP project by accommodating the possibility of the uncertainties. The methodology used is probabilistic analysis which was performed by Monte Carlo technique. This technique simulates the relationship between the uncertainty variables with financial feasibility indicators. The results showed that in probabilistic approach, SMR NPP project is considered feasible on the 'most probable value' of electricity selling price of 15 cents/kWh, indicated by positive average value of NPV (US$ 135,324,004) and the average value of both of IRRs are bigger than MARR (IRR project = 10.65 %, IRR Equity = 14.29 %, while MARR = 10 %). The probability of rejection of the SMR project was about 20 %. The three main variables that are most influential in the project were: selling price of electricity, investment cost and inflation rate. (author)

  10. Effects of Risk Management Practices on IT Project Success

    Directory of Open Access Journals (Sweden)

    Pimchangthong Daranee

    2017-03-01

    Full Text Available Successful management of an information technology (IT project is the most desirable for all organisations and stakeholders. Many researchers elaborated that risk management is a key part of project management for any project size. Risk management is so critical because it provides project managers with a forward-looking view of both threats and opportunities to improve the project success. The objectives of this research are to explore organisational factors affecting IT project success and risk management practices influencing IT project success. Risk management practices include risk identification, risk analysis, risk response planning, and risk monitoring and control. The IT project success is measured by process performance and product performance. Data are collected from 200 project managers, IT managers, and IT analysts in IT firms through questionnaires and analysed using Independent Sample t-test, One-way ANOVA, and Multiple Linear Regression at the statistical significance level of 0.05. The results show that the differences in organisational types affect IT project success in all aspects, while the differences on organisational sizes affect IT project success in the aspect of product performance and total aspects. Risk identification and risk response planning influence the process performance and the total aspects of IT project success. Risk identification has the highest positive influence on product performance, followed closely by risk response, while risk analysis negatively influences product performance.

  11. Information technology project risk management in Peru

    OpenAIRE

    Del Carpio Gallegos, Javier

    2014-01-01

    This article shows how some principles, uses, and practices of risk management are applied in information technology projects in Peru; in the last four years, in representative sectors like manufacturing, banking, information and communications, academics institutions, construction, government, consulting, services, and others. El presente artículo muestra algunos principios, usos y prácticas de cómo la gestión de riesgos de proyectos de tecnología se ha llevado a cabo en los últimos cuatr...

  12. 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.

  13. 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.

  14. 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.

  15. Review of the project risk management plan in the capital projects organization at ConocoPhillips

    OpenAIRE

    Meidell, Camilla

    2011-01-01

    Master's thesis in Risk management Project Risk Management (PRM) has in recent years become an important aspect of business organization and project management. There has always been a requirement for some risk management at COPNO. However about 3 years ago the process became much more defined and has become a requirement for the contingency used on projects to be based upon the risking process. Since risk management in projects is a requirement in the CP organization it is ...

  16. 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.

  17. 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.

  18. 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.

  19. On the Application of Science Systems Engineering and Uncertainty Quantification for Ice Sheet Science and Sea Level Projections

    Science.gov (United States)

    Schlegel, Nicole-Jeanne; Boening, Carmen; Larour, Eric; Limonadi, Daniel; Schodlok, Michael; Seroussi, Helene; Watkins, Michael

    2017-04-01

    Research and development activities at the Jet Propulsion Laboratory (JPL) currently support the creation of a framework to formally evaluate the observational needs within earth system science. One of the pilot projects of this effort aims to quantify uncertainties in global mean sea level rise projections, due to contributions from the continental ice sheets. Here, we take advantage of established uncertainty quantification tools embedded within the JPL-University of California at Irvine Ice Sheet System Model (ISSM). We conduct sensitivity and Monte-Carlo style sampling experiments on forward simulations of the Greenland and Antarctic ice sheets. By varying internal parameters and boundary conditions of the system over both extreme and credible worst-case ranges, we assess the impact of the different parameter ranges on century-scale sea level rise projections. The results inform efforts to a) isolate the processes and inputs that are most responsible for determining ice sheet contribution to sea level; b) redefine uncertainty brackets for century-scale projections; and c) provide a prioritized list of measurements, along with quantitative information on spatial and temporal resolution, required for reducing uncertainty in future sea level rise projections. Results indicate that ice sheet mass loss is dependent on the spatial resolution of key boundary conditions - such as bedrock topography and melt rates at the ice-ocean interface. This work is performed at and supported by the California Institute of Technology's Jet Propulsion Laboratory. Supercomputing time is also supported through a contract with the National Aeronautics and Space Administration's Cryosphere program.

  20. Risk managements' communicative effects influencing IT project success

    NARCIS (Netherlands)

    de Bakker, Karel; Boonstra, Albert; Wortmann, Hans

    The central question of this research is if, and how, risk management contributes to the success of IS/IT projects. Risk management is used regularly in IT projects, despite indications in literature that risk management only occasionally contributes to IT project success. Drawing on Habermas we

  1. 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

  2. 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

  3. 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

  4. 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...

  5. 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.

  6. 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

  7. 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.

  8. 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.

  9. Modelling of risk events with uncertain likelihoods and impacts in large infrastructure projects

    DEFF Research Database (Denmark)

    Schjær-Jacobsen, Hans

    2010-01-01

    to prevent future budget overruns. One of the central ideas is to introduce improved risk management processes and the present paper addresses this particular issue. A relevant cost function in terms of unit prices and quantities is developed and an event impact matrix with uncertain impacts from independent......This paper presents contributions to the mathematical core of risk and uncertainty management in compliance with the principles of New Budgeting laid out in 2008 by the Danish Ministry of Transport to be used in large infrastructure projects. Basically, the new principles are proposed in order...... uncertain risk events is used to calculate the total uncertain risk budget. Cost impacts from the individual risk events on the individual project activities are kept precisely track of in order to comply with the requirements of New Budgeting. Additionally, uncertain likelihoods for the occurrence of risk...

  10. An exploration of the option space in student design projects for uncertainty and sensitivity analysis with performance simulation

    NARCIS (Netherlands)

    Struck, C.; Wilde, de P.J.C.J.; Hopfe, C.J.; Hensen, J.L.M.

    2008-01-01

    This paper describes research conducted to gather empirical evidence on extent, character and content of the option space in building design projects, from the perspective of a climate engineer using building performance simulation for concept evaluation. The goal is to support uncertainty analysis

  11. 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

  12. Communicating Low-Probability High-Consequence Risk, Uncertainty and Expert Confidence: Induced Seismicity of Deep Geothermal Energy and Shale Gas.

    Science.gov (United States)

    Knoblauch, Theresa A K; Stauffacher, Michael; Trutnevyte, Evelina

    2018-04-01

    Subsurface energy activities entail the risk of induced seismicity including low-probability high-consequence (LPHC) events. For designing respective risk communication, the scientific literature lacks empirical evidence of how the public reacts to different written risk communication formats about such LPHC events and to related uncertainty or expert confidence. This study presents findings from an online experiment (N = 590) that empirically tested the public's responses to risk communication about induced seismicity and to different technology frames, namely deep geothermal energy (DGE) and shale gas (between-subject design). Three incrementally different formats of written risk communication were tested: (i) qualitative, (ii) qualitative and quantitative, and (iii) qualitative and quantitative with risk comparison. Respondents found the latter two the easiest to understand, the most exact, and liked them the most. Adding uncertainty and expert confidence statements made the risk communication less clear, less easy to understand and increased concern. Above all, the technology for which risks are communicated and its acceptance mattered strongly: respondents in the shale gas condition found the identical risk communication less trustworthy and more concerning than in the DGE conditions. They also liked the risk communication overall less. For practitioners in DGE or shale gas projects, the study shows that the public would appreciate efforts in describing LPHC risks with numbers and optionally risk comparisons. However, there seems to be a trade-off between aiming for transparency by disclosing uncertainty and limited expert confidence, and thereby decreasing clarity and increasing concern in the view of the public. © 2017 Society for Risk Analysis.

  13. Construction strategies and lifetime uncertainties for nuclear projects: A real option analysis

    Energy Technology Data Exchange (ETDEWEB)

    Jain, Shashi, E-mail: s.jain@cwi.nl [TU Delft, Delft Institute of Applied Mathematics, Delft (Netherlands); Nuclear Research Group, Petten (Netherlands); Roelofs, Ferry, E-mail: roelofs@nrg.eu [Nuclear Research Group, Petten (Netherlands); Oosterlee, Cornelis W., E-mail: c.w.oosterlee@cwi.nl [CWI – Centrum Wiskunde and Informatica, Amsterdam (Netherlands); TU Delft, Delft Institute of Applied Mathematics, Delft (Netherlands)

    2013-12-15

    Highlights: • Real options can be used to value flexibility of modular reactors. • Value of NPPs increases with implementation of long term cost reductions. • Levels of uncertainties affect the choice between projects. -- Abstract: Small and medium sized reactors, SMRs (according to IAEA, ‘small’ are reactors with power less than 300 MWe, and ‘medium’ with power less than 700 MWe) are considered as an attractive option for investment in nuclear power plants. SMRs may benefit from flexibility of investment, reduced upfront expenditure, and easy integration with small sized grids. Large reactors on the other hand have been an attractive option due to economy of scale. In this paper we focus on the advantages of flexibility due to modular construction of SMRs. Using real option analysis (ROA) we help a utility determine the value of sequential modular SMRs. Numerical results under different considerations, like possibility of rare events, learning, uncertain lifetimes are reported for a single large unit and modular SMRs.

  14. Construction strategies and lifetime uncertainties for nuclear projects: A real option analysis

    International Nuclear Information System (INIS)

    Jain, Shashi; Roelofs, Ferry; Oosterlee, Cornelis W.

    2013-01-01

    Highlights: • Real options can be used to value flexibility of modular reactors. • Value of NPPs increases with implementation of long term cost reductions. • Levels of uncertainties affect the choice between projects. -- Abstract: Small and medium sized reactors, SMRs (according to IAEA, ‘small’ are reactors with power less than 300 MWe, and ‘medium’ with power less than 700 MWe) are considered as an attractive option for investment in nuclear power plants. SMRs may benefit from flexibility of investment, reduced upfront expenditure, and easy integration with small sized grids. Large reactors on the other hand have been an attractive option due to economy of scale. In this paper we focus on the advantages of flexibility due to modular construction of SMRs. Using real option analysis (ROA) we help a utility determine the value of sequential modular SMRs. Numerical results under different considerations, like possibility of rare events, learning, uncertain lifetimes are reported for a single large unit and modular SMRs

  15. 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.

  16. Tank Waste Remediation System Characterization Project Programmatic Risk Management Plan

    International Nuclear Information System (INIS)

    Baide, D.G.; Webster, T.L.

    1995-12-01

    The TWRS Characterization Project has developed a process and plan in order to identify, manage and control the risks associated with tank waste characterization activities. The result of implementing this process is a defined list of programmatic risks (i.e. a risk management list) that are used by the Project as management tool. This concept of risk management process is a commonly used systems engineering approach which is being applied to all TWRS program and project elements. The Characterization Project risk management plan and list are subset of the overall TWRS risk management plan and list

  17. 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

  18. 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.

  19. 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.

  20. 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

  1. 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...

  2. 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...

  3. On ISSM and leveraging the Cloud towards faster quantification of the uncertainty in ice-sheet mass balance projections

    Science.gov (United States)

    Larour, E.; Schlegel, N.

    2016-11-01

    With the Amazon EC2 Cloud becoming available as a viable platform for parallel computing, Earth System Models are increasingly interested in leveraging its capabilities towards improving climate projections. In particular, faced with long wait periods on high-end clusters, the elasticity of the Cloud presents a unique opportunity of potentially "infinite" availability of small-sized clusters running on high-performance instances. Among specific applications of this new paradigm, we show here how uncertainty quantification in climate projections of polar ice sheets (Antarctica and Greenland) can be significantly accelerated using the Cloud. Indeed, small-sized clusters are very efficient at delivering sensitivity and sampling analysis, core tools of uncertainty quantification. We demonstrate how this approach was used to carry out an extensive analysis of ice-flow projections on one of the largest basins in Greenland, the North-East Greenland Glacier, using the Ice Sheet System Model, the public-domain NASA-funded ice-flow modeling software. We show how errors in the projections were accurately quantified using Monte-Carlo sampling analysis on the EC2 Cloud, and how a judicious mix of high-end parallel computing and Cloud use can best leverage existing infrastructures, and significantly accelerate delivery of potentially ground-breaking climate projections, and in particular, enable uncertainty quantification that were previously impossible to achieve.

  4. 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...

  5. 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.

  6. Overlapping Boundaries of the Project Time Management and Project Risk Management

    Directory of Open Access Journals (Sweden)

    Marius PODEAN

    2010-01-01

    Full Text Available Based on utility function, milestones during project and/or the end of projects or programme may be categorized in what are called soft-deadline and hard-deadline. In contrast with the soft-end projects, the hard-end projects posses a decrease of utility function with a vertical asymptote character around the deadline for project completion. In extreme situations, the utility function itself may fall under zero (projects may generate losses to both constructor and customer. Existing risk analysis methodologies observe risks from monetary terms. The typical risks are correlated with an increase in final project costs. In order to estimate harddeadline milestones and/or end of projects or programme is critical to employ the time dimension rather than the typical cost-based risk analysis. Here, we comprehensively describe a structured methodology that focuses on minimizing and mitigating project specific delay risks. The method may supplement existing cost-based risk analysis in projects. We aim to elegantly combine moderation techniques to reveal the intrinsic risk of the projects. In addition to the technical risks, the moderation techniques are able to bring evidence of risks as the team efficacy, diverse un-correlations or miss-understanding about the roles of the team members in the team – most of the project soft risk. Described methodology encourages the common understanding of risks for participants, crystallizing the essence of what can go wrong in complex situations and where the opportunities can be unlocked.

  7. An Assessment of risk response strategies practiced in software projects

    Directory of Open Access Journals (Sweden)

    Vanita Bhoola

    2014-11-01

    Full Text Available Risk management and success in projects are highly intertwined – better approaches to project risk management tend to increase chances of project success in terms of achieving scope & quality, schedule and cost targets. The process of responding to risk factors during a project’s life cycle is a crucial aspect of risk management referred to as risk response strategies, in this paper. The current research explores the status of risk response strategies applied in the software development projects in India. India provides a young IT-savvy English-speaking population, which is also cost effective. Other than the workforce, the environment for implementation of software projects in India is different from the matured economies. Risk management process is a commonly discussed theme, though its implementation in practice has a huge scope for improvement in India. The paper talks about four fundamental treatments to risk response – Avoidance, Transference, Mitigation and Acceptance (ATMA. From a primary data of 302 project managers, the paper attempts to address the risk response factors that lead to successful achievement of project scope & quality, schedule and cost targets, by using a series of regressions followed with Seemingly Unrelated Regression Equations (SURE modelling. Mitigation emerged as the most significant risk response strategy to achieve project targets. Acceptance, transference, and avoidance of risk were mostly manifested in the forms of transparency in communication across stakeholders, careful study of the nature of risks and close coordination between project team, customers/end-users and top management.

  8. 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...

  9. 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

  10. 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.

  11. Study on Risk Approaches in Software Development Projects

    Directory of Open Access Journals (Sweden)

    Claudiu BRANDAS

    2012-01-01

    Full Text Available Risk approaches in project development led to the integration in the IT project management methodologies and software development of activities and processes of risk management. The diversity and the advanced level of the used technologies in IT projects with increasing com-plexity leads to an exponential diversification of risk factors.The purpose of this research is to identify the level of the risk approach in IT projects both at the IT project management and software development methodologies level and the level of the perception of IT project man-agers, IT managers and IT analysts in Romanian IT companies. Thus, we want to determine the correlation between the use of a project management or software development methodology and the overall level of risk perceived by the project managers using these methodologies.

  12. Project finance risks - getting it right first time

    International Nuclear Information System (INIS)

    Bain, F.

    1996-01-01

    Bankers seeking to invest in the construction of new power stations by independent power producers, face greater risks than those lending to companies. Independent risk and insurance advisers are used to assess project risk. ''Project finance'' has become increasingly popular as it allows projects to go ahead that could not be supported from sponsors' own resources. In addition, project finance means that various equity partners can join together in a joint venture company and limit their individual risk. Project finance can be delayed by differences between the needs of sponsors, financiers and insurers. The process can be speeded up by foreknowledge of bankers' requirements. (UK)

  13. 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.

  14. 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

  15. Simple steps help minimize costs, risks in project contracts

    International Nuclear Information System (INIS)

    Camps, J.A.

    1996-01-01

    Contrary to prevailing opinion, risks and project financing costs can be higher for lump sum (LS) project contracts than under reimbursable-type contracts. An element-by-element analysis of the risks and costs associated with a project enables investors to develop variations of reimbursable contracts. Project managers can use this three-step procedure, along with other recommendations, to measure the hidden project costs and risks associated with LS contracts. The author bases his conclusions on case studies of recent projects in the petroleum refining and petrochemical industries. The findings, however, are general enough to be applicable in other industrial sectors

  16. 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.

  17. 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...

  18. Post-Probabilistic Uncertainty Quantification: Discussion of Potential Use in Product Development Risk Management

    DEFF Research Database (Denmark)

    Tegeltija, Miroslava; Oehmen, Josef; Kozin, Igor

    2016-01-01

    made by PD managers and engineers have a significant impact on the strategic value of the asset delivered, and these decisions depend on the quality of information on which they are based [Ewejeet al. 2012]. Uncertainty plays an important role in decision making. Decision making quality improves...... that addresses the different ways in which factual statements may be interpreted by different individuals [Klinke and Renn 2002].[Flyvbjerg 2007] observed that the main challenges of large projects, including PD projects, are inadequate, unreliable or misleading information; and conflicts between decision making......, policy and planning. It has been proven by empirical studies (e.g. [Levi 1990], [Sahlin 2012]) that the amount and quality of information behind probabilities and utilities is an important factor when making decisions, in other words, people tend to make different decisions if they are aware...

  19. Project Structuring and Risk Allocation for NPP Construction

    International Nuclear Information System (INIS)

    Kaser, Greg

    2013-01-01

    This presentation treats of the project risks and how to mitigate major risks and structure a new project. It also talks about the contract implications to handle the specificities of a new project: design complexities, interface between the engineering, procurement and constructing contractors, and finally discusses the necessity of a stable regulatory environment and the role of government

  20. RISK MANAGEMENT APPROACHES AND PRACTICES IN IT PROJECTS

    Directory of Open Access Journals (Sweden)

    BRANDAS Claudiu

    2012-07-01

    Full Text Available Risk is identified in project management literature as an important factor influencing IT projects success, and it is relevant for both academic and practitionersn#8217; communities. The paper presents the past and current approaches to risk management in IT projects. The objective of this paper is to compare the different approaches and relate them to existing practices. Project management literature and practice have brought different approaches to risk management, and as a result, many projects ended in failure. We present how risk management is considered in the literature, and we compare the main two approaches: the evaluation approach and the management approach. The contingency approach does not consider risk management to be a specific process as it is an embedded process in the other project management processes. Then, we present the main practices in risk management. The methodology applied is based on documentary study review and analysis of the concepts used by the literature. We analyzed the literature published between 1978 and 2011 from the main journals for IT project management and found out that the essence of project management is risk management. The risk management practices have a considerable influence on stakeholdersn#8217; perception of project success. But, regardless of the chosen approach, a standard method for identifying, assessing, and responding to risks should be included in any project as this influences the outcome of the project.

  1. 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.

  2. 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.

  3. Improvement of the projection models for radiogenic cancer risk

    International Nuclear Information System (INIS)

    Tong Jian

    2005-01-01

    Calculations of radiogenic cancer risk are based on the risk projection models for specific cancer sites. Improvement has been made for the parameters used in the previous models including introductions of mortality and morbidity risk coefficients, and age-/ gender-specific risk coefficients. These coefficients have been applied to calculate the radiogenic cancer risks for specific organs and radionuclides under different exposure scenarios. (authors)

  4. 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).

  5. Risk Management in Information Technology Project: An Empirical Study

    Directory of Open Access Journals (Sweden)

    Kornelius Irfandhi

    2016-09-01

    Full Text Available The companies are facing some risks due to changes in a dynamic environment. If risks are not managed properly, it will have some negative impacts on the companies at the present and the future. One important function of the Information Technology (IT governance is risk management. Risk management in IT project aims to provide a safe environment for IT projects undertaken. Risk management becomes an important process for the success of IT projects. This article discussed the risk of IT project and whether there was a relationship between risk management and the success of the project. The method used was performing a literature review of several scientific articles which published between 2010 and 2014. The results of this study are the presence of risk management and risk manager influence the success of the project. Risk analysis and risk monitoring and control also have a relationship with the subjective performance of IT projects. If risk management is applied properly, the chance of the success of the projects undertaken can be increased. 

  6. 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

  7. Uncertainties in hydrological extremes projections and its effects on decision-making processes in an Amazonian sub-basin.

    Science.gov (United States)

    Andres Rodriguez, Daniel; Garofolo, Lucas; Lazaro Siqueira Junior, Jose

    2013-04-01

    Uncertainties in Climate Change projections are affected by irreducible uncertainties due to knowledge's limitations, chaotic nature of climate system and human decision-making process. Such uncertainties affect the impact studies, complicating the decision-making process aimed at mitigation and adaptation. However, these uncertainties allow the possibility to develop exploratory analyses on system's vulnerability to different sceneries. Through these kinds of analyses it is possible to identify critical issues, which must be deeper studied. For this study we used several future's projections from General Circulation Models to feed a Hydrological Model, applied to the Amazonian sub-basin of Ji-Paraná. Hydrological Model integrations are performed for present historical time (1970-1990) and for future period (2010-2100). Extreme values analyses are performed to each simulated time series and results are compared with extremes events in present time. A simple approach to identify potential vulnerabilities consists of evaluating the hydrologic system response to climate variability and extreme events observed in the past, comparing them with the conditions projected for the future. Thus it is possible to identify critical issues that need attention and more detailed studies. For the goal of this work, we used socio-economic data from Brazilian Institute of Geography and Statistics, the Operator of the National Electric System, the Brazilian National Water Agency and scientific and press published information. This information is used to characterize impacts associated to extremes hydrological events in the basin during the present historical time and to evaluate potential impacts in the future face to the different hydrological projections. Results show inter-model variability results in a broad dispersion on projected extreme's values. The impact of such dispersion is differentiated for different aspects of socio-economic and natural systems and must be carefully

  8. Integrated Risk Management Within NASA Programs/Projects

    Science.gov (United States)

    Connley, Warren; Rad, Adrian; Botzum, Stephen

    2004-01-01

    As NASA Project Risk Management activities continue to evolve, the need to successfully integrate risk management processes across the life cycle, between functional disciplines, stakeholders, various management policies, and within cost, schedule and performance requirements/constraints become more evident and important. Today's programs and projects are complex undertakings that include a myriad of processes, tools, techniques, management arrangements and other variables all of which must function together in order to achieve mission success. The perception and impact of risk may vary significantly among stakeholders and may influence decisions that may have unintended consequences on the project during a future phase of the life cycle. In these cases, risks may be unintentionally and/or arbitrarily transferred to others without the benefit of a comprehensive systemic risk assessment. Integrating risk across people, processes, and project requirements/constraints serves to enhance decisions, strengthen communication pathways, and reinforce the ability of the project team to identify and manage risks across the broad spectrum of project management responsibilities. The ability to identify risks in all areas of project management increases the likelihood a project will identify significant issues before they become problems and allows projects to make effective and efficient use of shrinking resources. By getting a total team integrated risk effort, applying a disciplined and rigorous process, along with understanding project requirements/constraints provides the opportunity for more effective risk management. Applying an integrated approach to risk management makes it possible to do a better job at balancing safety, cost, schedule, operational performance and other elements of risk. This paper will examine how people, processes, and project requirements/constraints can be integrated across the project lifecycle for better risk management and ultimately improve the