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...

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

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

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.

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

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.

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.

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

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

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)

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.

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

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.

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

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.

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

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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.

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.

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)

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.

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.

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...

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

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....

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

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...

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.

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 project ‘Uncertainties 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...

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

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.

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…

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

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

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)

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.

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....

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...

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.

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.

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.

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.

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...

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.

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...

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…

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

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...

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.

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.

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)

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.

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.

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

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.

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.

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.

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

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...

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....

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.

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.

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.

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.

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.

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...

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

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)

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.

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.

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

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.

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.

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...

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.

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.

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

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...

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.

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

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

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

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)

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

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

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)

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

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

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

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.

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.

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.

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.

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.

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.

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...

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.

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

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

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

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.

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.

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

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.

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...

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...

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

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

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

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

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.;

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

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

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

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...

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.

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 ...

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.

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.)

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

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

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.

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.

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

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

MANAGEMENT OF TRANSURANIC (TRU) WASTE RETRIEVAL PROJECT RISKS SUCCESSES IN THE STARTUP OF THE HANFORD 200 AREA TRU WASTE RETRIEVAL PROJECT

International Nuclear Information System (INIS)

GREENWLL, R.D.

2005-01-01

A risk identification and mitigation method applied to the Transuranic (TRU) Waste Retrieval Project performed at the Hanford 200 Area burial grounds is described. Retrieval operations are analyzed using process flow diagramming. and the anticipated project contingencies are included in the Authorization Basis and operational plans. Examples of uncertainties assessed include degraded container integrity, bulged drums, unknown containers, and releases to the environment. Identification and mitigation of project risks contributed to the safe retrieval of over 1700 cubic meters of waste without significant work stoppage and below the targeted cost per cubic meter retrieved. This paper will be of interest to managers, project engineers, regulators, and others who are responsible for successful performance of waste retrieval and other projects with high safety and performance risks

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

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...

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

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...

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

Risk Consideration and Cost Estimation in Construction Projects Using Monte Carlo Simulation

Directory of Open Access Journals (Sweden)

Claudius A. Peleskei

2015-06-01

Full Text Available Construction projects usually involve high investments. It is, therefore, a risky adventure for companies as actual costs of construction projects nearly always exceed the planed scenario. This is due to the various risks and the large uncertainty existing within this industry. Determination and quantification of risks and their impact on project costs within the construction industry is described to be one of the most difficult areas. This paper analyses how the cost of construction projects can be estimated using Monte Carlo Simulation. It investigates if the different cost elements in a construction project follow a specific probability distribution. The research examines the effect of correlation between different project costs on the result of the Monte Carlo Simulation. The paper finds out that Monte Carlo Simulation can be a helpful tool for risk managers and can be used for cost estimation of construction projects. The research has shown that cost distributions are positively skewed and cost elements seem to have some interdependent relationships.

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

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...

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...

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

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.

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.)

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.

FIDIC contracts: analysis of the impact of general and particular conditions on the financial risk management in Romanian infrastructure projects

Directory of Open Access Journals (Sweden)

Constanţa-Nicoleta Bodea

2016-12-01

Full Text Available Construction projects are characterized by risks and uncertainties mainly due to technical and economic complexity. Risk management is an important tool in making decisions involving the identification and reduction, avoidance or transfer risk and uncertainties consequences of events that occurs during project implementation. For this reason, the objective of the contract between the beneficiary and the contractor is the allocation of risk. The distribution of risk in contracts for the execution of construction works was and is an ongoing challenge faced by parties having a significant impact on the type of contract is used. On the one hand, the beneficiaries tend to transfer to the contractors as many of the project risks and uncertainties, on the other hand, the contractors look to exploit any weakness contract, so as to reduce their impact on the expected profit. One of the most important risks assumed by the contractor by signing the contract which is also increasingly common in the current economic situation is the reduced financial capacity to support the project. A purely legal or purely technical interpretation is not meant to describe the complexity of issues related to implementation of construction projects. For this reason the authors have adopted a multi-disciplinary approach, which includes the legal issues related to the nature of the contract, but also the financial and technical aspects of construction projects. The paper aims to analyze how special contract clauses can influence the implementation of construction projects and in particular the financial management of contractors. The authors propose a model for analyzing the impact of FIDIC contract conditions applied on a case study of five transport infrastructure projects.

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.

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

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.

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.

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

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.

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

On treatment of uncertainty in system planning

International Nuclear Information System (INIS)

Flage, R.; Aven, T.

2009-01-01

In system planning and operation considerable efforts and resources are spent to reduce uncertainties, as a part of project management, uncertainty management and safety management. The basic idea seems to be that uncertainties are purely negative and should be reduced. In this paper we challenge this way of thinking, using a common industry practice as an example. In accordance with this industry practice, three uncertainty interval categories are used: ±40% intervals for the feasibility phase, ±30% intervals for the concept development phase and ±20% intervals for the engineering phase. The problem is that such a regime could easily lead to a conservative management regime encouraging the use of existing methods and tools, as new activities and novel solutions and arrangements necessarily mean increased uncertainties. In the paper we suggest an alternative approach based on uncertainty and risk descriptions, but having no predefined uncertainty reduction structures. The approach makes use of risk assessments and economic optimisation tools such as the expected net present value, but acknowledges the need for broad risk management processes which extend beyond the analyses. Different concerns need to be balanced, including economic aspects, uncertainties and risk, and practicability

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.

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.

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.

Incorporating parametric uncertainty into population viability analysis models

Science.gov (United States)

McGowan, Conor P.; Runge, Michael C.; Larson, Michael A.

2011-01-01

Uncertainty in parameter estimates from sampling variation or expert judgment can introduce substantial uncertainty into ecological predictions based on those estimates. However, in standard population viability analyses, one of the most widely used tools for managing plant, fish and wildlife populations, parametric uncertainty is often ignored in or discarded from model projections. We present a method for explicitly incorporating this source of uncertainty into population models to fully account for risk in management and decision contexts. Our method involves a two-step simulation process where parametric uncertainty is incorporated into the replication loop of the model and temporal variance is incorporated into the loop for time steps in the model. Using the piping plover, a federally threatened shorebird in the USA and Canada, as an example, we compare abundance projections and extinction probabilities from simulations that exclude and include parametric uncertainty. Although final abundance was very low for all sets of simulations, estimated extinction risk was much greater for the simulation that incorporated parametric uncertainty in the replication loop. Decisions about species conservation (e.g., listing, delisting, and jeopardy) might differ greatly depending on the treatment of parametric uncertainty in population models.

Risk management in the project of implantation of the repository for low and intermediate level radioactive waste

International Nuclear Information System (INIS)

Borssatto, Maria de Fatima B.; Tello, Cledola Cassia O. de; Uemura, George

2011-01-01

Project RBMN is part of the Brazilian solution for the storage of radioactive waste generated by the activities of nuclear energy in Brazil. The aim of RBMN is to implement the National Repository to dispose the low and intermediate-level radioactive waste. Risk is a characteristic of all projects, and it is originated from uncertainties, assumptions and the environment of execution of the project. Risk management is the way to monitor systematically these uncertainties and a guaranty that the goals of the project will be attained. A specific methodology for the risk management of the Project RBMN is under development, which integrates models and processes for identification and analysis of risks, reactions, monitoring, control and planning of risk management. This methodology is fundamental and will be of primordial importance for future generations who will be responsible for the operation at final stages, closure and institutional control during the post-closure of the repository. It will provide greater safety to executed processes and safeguarding risks and specific solutions for this enterprise, guaranteeing the safety of the repository in its life cycle, which has a foreseen duration of at least three hundred years. The aim of this paper is to present the preliminary analysis of the opportunities, threats, strong points and weak points identified up to now, that will provide support to implement risk management procedures. The methodology will be based on the PMBOK R - Project Management Board of Knowledge - and will take into consideration the best practices for project management.(author)

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

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.

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

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...

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.

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...

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.

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

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.

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.

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.

Quantification of uncertainty and of profitability in petroleum and natural gas exploration and production

Energy Technology Data Exchange (ETDEWEB)

Voegl, E

1970-07-01

This study is to acquaint the oil geologist, reservoir engineer, and manager with modern methods of appraising geological/technical projects and decision problems under uncertainty. Uncertainty attaches to any appraisal of investment projects whose income lies in the future. The greater that uncertainty, the less important become the appraisal methods proper while the computation procedures concerning uncertainty gain in significance. There are briefly discussed the tools of risk determination, i.e., mathematical statistics and probability theory, and some of the most common methods of quantifying the uncertainty are explained. The best known methods of decision finding under multivalent or uncertain expectations, such as conditional and sensibility analyses, minimax and minimax-risk rule, and preference theory are set forth. The risk is defined, and the most common methods of genuine risk determination in exploration and exploitation are discussed. Practical examples illustrate the solution of decision problems under uncertainty, and examples of genuine risk determination are furnished. (29 refs.)

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

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.

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

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

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

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

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.

Uncertainty and Decision Making: Examples of Some Possible New Frontiers

Science.gov (United States)

Silliman, S. E.; Rodak, C. M.; Bolster, D.; Saavedra, K.; Evans, W.

2011-12-01

The concept of decision making under uncertainty for groundwater systems represents an exciting area of research and application. In this presentation, three examples are briefly introduced which represent possible new applications of risk and decision making under uncertainty. In the most classic of the three examples, a probabilistic strategy is considered within the context of management / assessment of proposed changes in land-use in the vicinity of a public water-supply well. Focused on health-risk related to contamination at the well, the analysis includes uncertainties in source location / strength, groundwater flow / transport, human exposure, and human health risk. The second example involves application of Probabilistic Risk Assessment (PRA) to the evaluation of development projects in rural regions of developing countries. PRA combined with Fault Tree Analysis provides a structure for analysis of the impact of data uncertainties on the estimation of health risk resulting from failure of multiple components of new water-resource systems. The third is an extension of the concept of "risk compensation" to the analysis of potential long-term risk associated with new water resource projects. Of direct interest here is the appearance of new risk to the public, such as introduction of new disease pathways or new sources of contamination of the source waters. As a result of limitations on conceptual model and/or limitations on data, this type of risk is often difficult to identify / assess, and is therefore not commonly included in formal decision-making efforts: it may however seriously impact the long-term net benefit of a water resource project. The goal of presenting these three examples is to illustrate the breadth of possible application of uncertainty / risk analyses beyond the more classic applications to groundwater remediation and protection.

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...

Management of uncertainties on parameters elicited by experts - Applications to sea-level rise and to CO2 storage operations risk assessment

Science.gov (United States)

Manceau, Jean-Charles; Loschetter, Annick; Rohmer, Jérémy; Le Cozannet, Gonéri; Lary Louis, de; Guénan Thomas, Le; Ken, Hnottavange-Telleen

2017-04-01

-Shafer theory has been used to represent and aggregate these pieces of information. The results of different aggregation rules as well as those of a classical probabilistic approach are compared with the purpose of highlighting the elements each of them could provide to the decision-maker (Manceau et al., 2016). The second example focuses on projections of future sea-level rise. Based on IPCC's constraints on the projection quantiles, and on the scientific community consensus level on the physical limits to future sea-level rise, a possibility distribution of the projections by 2100 under the RCP 8.5 scenario has been established. This possibility distribution has been confronted with a set of previously published probabilistic sea-level projections, with a focus on their ability to explore high ranges of sea-level rise (Le Cozannet et al., 2016). These two examples are complementary in the sense that they allow to address various aspects of the problem (e.g. representation of different types of information, conflict among experts, sources dependence). Moreover, we believe that the issues faced during these two experiences can be generalized to many risks/hazards assessment situations. References Manceau, JC., Loschetter, A., Rohmer, J., de Lary, L., Le Guénan, T., Hnottavange-Telleen, K. (2016). Dealing with uncertainty on parameters elicited from a pool of experts for CCS risk assessment. Congrès λμ 20 (St-Malo, France). Le Cozannet G., Manceau JC., Rohmer, J. (2016). Bounding probabilistic sea-level rise projections within the framework of the possibility theory. Accepted in Environmental Research Letters.

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

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

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

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.

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

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.

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.

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...

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.

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...

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.

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.

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

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

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

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

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

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

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

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)

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

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.

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

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.

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...

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...

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.

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...

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.

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

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...

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

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

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

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…

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...

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

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

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.

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.

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.

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.

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.

Project Investment and Project Financing: A study on Business Case and Financing Models

OpenAIRE

Wang, Simiao

2012-01-01

Uncertainty is a very significant factor that must be taken into consideration in project front-end phase management. By taking into uncertainty, the planners can to a great extent make sure that the business case could be accurate between specific intervals, hence business case can be based on to make decision. In a highly uncertain environment; the project sponsors should prefer other means to finance the project rather than using debt. Risk management is extremely important in project fina...

Cassini Spacecraft Uncertainty Analysis Data and Methodology Review and Update/Volume 1: Updated Parameter Uncertainty Models for the Consequence Analysis

Energy Technology Data Exchange (ETDEWEB)

WHEELER, TIMOTHY A.; WYSS, GREGORY D.; HARPER, FREDERICK T.

2000-11-01

Uncertainty distributions for specific parameters of the Cassini General Purpose Heat Source Radioisotope Thermoelectric Generator (GPHS-RTG) Final Safety Analysis Report consequence risk analysis were revised and updated. The revisions and updates were done for all consequence parameters for which relevant information exists from the joint project on Probabilistic Accident Consequence Uncertainty Analysis by the United States Nuclear Regulatory Commission and the Commission of European Communities.

Evaluating the Impact of Risk on Contractor’s Tender Figure in Public Buildings Projects in Northern Nigeria

Directory of Open Access Journals (Sweden)

L. O. Oyewobi

2012-01-01

Full Text Available It has become almost impossible to have projects completed within the initial cost and time in Nigeria; this is as a result of many factors the construction industry is being plagued with ranging from estimating risk to time and cost overruns. The construction industry is widely associated with a high degree of risk and uncertainty due to the nature of its operating heterogeneous environment. The paper aimed at evaluating the impact of estimating risk on contractor’s tender sum with a view of ensuring efficient delivery of projects in the Northern part of Nigeria. A survey was conducted using questionnaire and a total of four headings of risk factors were identified. Research findings showed defects in design, inflation, contractor’s competence and political uncertainty as well as changes in government had greatest impact on contractor’s tender figure whereas likely trend in wages rates over the period, excessive approval procedure in administration government department, unavailability of sufficient amount of unskilled labor and technical manpower and resources of the company were the most significant factors to be considered by contractors when estimating the pricing risk. The paper recommends that construction professionals should identify and adequately quantify project estimating risk factors. Adding a risk premium to quotation and time estimation has to be supported by governmental owner organizations and other agencies in the local construction sector. Competent contractors should be allowed to tender so as to see the incidence of these estimating risks as an important aspect that requires attention while evaluating contractor’s tender sum.

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)

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.

Probabilistic accident consequence uncertainty analysis: Food chain uncertainty assessment. Volume 1: Main report

Energy Technology Data Exchange (ETDEWEB)

Brown, J. [National Radiological Protection Board (United Kingdom); Goossens, L.H.J.; Kraan, B.C.P. [Delft Univ. of Technology (Netherlands)] [and others

1997-06-01

This volume is the first of a two-volume document that summarizes a joint project conducted by the US Nuclear Regulatory Commission and the European Commission to assess uncertainties in the MACCS and COSYMA probabilistic accident consequence codes. These codes were developed primarily for estimating the risks presented by nuclear reactors based on postulated frequencies and magnitudes of potential accidents. This document reports on an ongoing project to assess uncertainty in the MACCS and COSYMA calculations for the offsite consequences of radionuclide releases by hypothetical nuclear power plant accidents. A panel of sixteen experts was formed to compile credible and traceable uncertainty distributions for food chain variables that affect calculations of offsite consequences. The expert judgment elicitation procedure and its outcomes are described in these volumes. Other panels were formed to consider uncertainty in other aspects of the codes. Their results are described in companion reports. Volume 1 contains background information and a complete description of the joint consequence uncertainty study. Volume 2 contains appendices that include (1) a summary of the MACCS and COSYMA consequence codes, (2) the elicitation questionnaires and case structures for both panels, (3) the rationales and results for the panels on soil and plant transfer and animal transfer, (4) short biographies of the experts, and (5) the aggregated results of their responses.

Probabilistic accident consequence uncertainty analysis: Food chain uncertainty assessment. Volume 1: Main report

International Nuclear Information System (INIS)

Brown, J.; Goossens, L.H.J.; Kraan, B.C.P.

1997-06-01

This volume is the first of a two-volume document that summarizes a joint project conducted by the US Nuclear Regulatory Commission and the European Commission to assess uncertainties in the MACCS and COSYMA probabilistic accident consequence codes. These codes were developed primarily for estimating the risks presented by nuclear reactors based on postulated frequencies and magnitudes of potential accidents. This document reports on an ongoing project to assess uncertainty in the MACCS and COSYMA calculations for the offsite consequences of radionuclide releases by hypothetical nuclear power plant accidents. A panel of sixteen experts was formed to compile credible and traceable uncertainty distributions for food chain variables that affect calculations of offsite consequences. The expert judgment elicitation procedure and its outcomes are described in these volumes. Other panels were formed to consider uncertainty in other aspects of the codes. Their results are described in companion reports. Volume 1 contains background information and a complete description of the joint consequence uncertainty study. Volume 2 contains appendices that include (1) a summary of the MACCS and COSYMA consequence codes, (2) the elicitation questionnaires and case structures for both panels, (3) the rationales and results for the panels on soil and plant transfer and animal transfer, (4) short biographies of the experts, and (5) the aggregated results of their responses

Risk management in a large-scale CO2 geosequestration pilot project, Illinois, USA

Science.gov (United States)

Hnottavange-Telleen, K.; Chabora, E.; Finley, R.J.; Greenberg, S.E.; Marsteller, S.

2011-01-01

Like most large-scale infrastructure projects, carbon dioxide (CO 2) geological sequestration (GS) projects have multiple success criteria and multiple stakeholders. In this context "risk evaluation" encompasses multiple scales. Yet a risk management program aims to maximize the chance of project success by assessing, monitoring, minimizing all risks in a consistent framework. The 150,000-km2 Illinois Basin underlies much of the state of Illinois, USA, and parts of adjacent Kentucky and Indiana. Its potential for CO2 storage is first-rate among basins in North America, an impression that has been strengthened by early testing of the injection well of the Midwest Geological Sequestration Consortium's (MGSC's) Phase III large scale demonstration project, the Illinois Basin - Decatur Project (IBDP). The IBDP, funded by the U.S. Department of Energy's National Energy Technology Laboratory (NETL), represents a key trial of GS technologies and project-management techniques. Though risks are specific to each site and project, IBDP risk management methodologies provide valuable experience for future GS projects. IBDP views risk as the potential for negative impact to any of these five values: health and safety, environment, financial, advancing the viability and public acceptability of a GS industry, and research. Research goals include monitoring one million metric tonnes of injected CO2 in the subsurface. Risk management responds to the ways in which any values are at risk: for example, monitoring is designed to reduce uncertainties in parameter values that are important for research and system control, and is also designed to provide public assurance. Identified risks are the primary basis for risk-reduction measures: risks linked to uncertainty in geologic parameters guide further characterization work and guide simulations applied to performance evaluation. Formally, industry defines risk (more precisely risk criticality) as the product L*S, the Likelihood multiplied

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

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.

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.

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.

[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.

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)

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)

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

Model-specification uncertainty in future forest pest outbreak.

Science.gov (United States)

Boulanger, Yan; Gray, David R; Cooke, Barry J; De Grandpré, Louis

2016-04-01

Climate change will modify forest pest outbreak characteristics, although there are disagreements regarding the specifics of these changes. A large part of this variability may be attributed to model specifications. As a case study, we developed a consensus model predicting spruce budworm (SBW, Choristoneura fumiferana [Clem.]) outbreak duration using two different predictor data sets and six different correlative methods. The model was used to project outbreak duration and the uncertainty associated with using different data sets and correlative methods (=model-specification uncertainty) for 2011-2040, 2041-2070 and 2071-2100, according to three forcing scenarios (RCP 2.6, RCP 4.5 and RCP 8.5). The consensus model showed very high explanatory power and low bias. The model projected a more important northward shift and decrease in outbreak duration under the RCP 8.5 scenario. However, variation in single-model projections increases with time, making future projections highly uncertain. Notably, the magnitude of the shifts in northward expansion, overall outbreak duration and the patterns of outbreaks duration at the southern edge were highly variable according to the predictor data set and correlative method used. We also demonstrated that variation in forcing scenarios contributed only slightly to the uncertainty of model projections compared with the two sources of model-specification uncertainty. Our approach helped to quantify model-specification uncertainty in future forest pest outbreak characteristics. It may contribute to sounder decision-making by acknowledging the limits of the projections and help to identify areas where model-specification uncertainty is high. As such, we further stress that this uncertainty should be strongly considered when making forest management plans, notably by adopting adaptive management strategies so as to reduce future risks. © 2015 Her Majesty the Queen in Right of Canada Global Change Biology © 2015 Published by John

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

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

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.

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.

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)

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)

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

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)

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

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.

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

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.

Value change in oil and gas production: V. Incorporation of uncertainties and determination of relative importance

International Nuclear Information System (INIS)

Lerche, I.; Noeth, S.

2002-01-01

The influence of two fundamentally different types of uncertainty on the value of oil field production are investigated here. First considered is the uncertainty caused by the fact that the expected value estimate is not one of the possible outcomes. To correctly allow for the risk attendant upon using the expected value as a measure of worth, even with statistically sharp parameters, one needs to incorporate the uncertainty of the expected value. Using a simple example we show how such incorporation allows for a clear determination of the relative risk of projects that may have the same expected value but very different risks. We also show how each project can be risked on its own using the expected value and variance. This uncertainty type is due to the possible pathways for different outcomes even when parameters categorizing the system are taken to be known. Second considered is the risk due to the fact that parameters in oil field estimates are just estimates and, as such, have their own intrinsic errors that influence the possible outcomes and make them less certain. This sort of risk depends upon the uncertainty of each parameter, and also the type of distribution the parameters are taken to be drawn from. In addition, not all uncertainties in parameters values are of equal importance in influencing an outcome probability. We show how can determine the relative importance for the parameters and so determine where to place effort to resolve the dominant contributions to risk if it is possible to do so. Considerations of whether to acquire new information, and also whether to undertake further studies under such an uncertain environment, are used as vehicles to address these concerns of risk due to uncertainty. In general, an oil field development project has to contend with all the above types of risk and uncertainty. It is therefore of importance to have quantitative measures of risk so that one can compare and contrast the various effects, and so that

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)

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

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...

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.

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.

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.

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

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

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...

Project risk management: A review of an institutional project life cycle

Directory of Open Access Journals (Sweden)

Wanjiru Gachie

2017-11-01

Full Text Available This article is a desktop analysis of project risk management involving a project management institutional restructuring. The pragmatic nature of this research allows for the literature review and the document analysis to be integrated and presented as both a descriptive and analytical research. The analysis demonstrates that the project committee did not proactively manage project risk. The restructuring was a change management project, entailing the implementation of many organisational changes, such as restructuring, lay-off of some part of the administrative workforce, adoption of new technology, provision of new approaches to well-established procedures, and implementation of new performance initiative, the process which should have been managed with an effective integrated risk strategy and plan. Analysis of the restructuring project risk management exhibits little evidence of a systematic (computer based or manual record that should have provided policies, procedures, and structures for managing risk. The article concludes that the restructuring risk process was inadequate and it could not have ensured a successful project. An analysis of the restructuring project risk monitoring and control exhibits a reactive rather than proactive application of risk management procedures. The analysis further indicates that the committee failed to make use of the various project risk management processes, standards, and guidelines. Based on the conclusions, the article recommends that project risk planning, strategy, control, and monitoring should be put in place for future institutional projects. The project management team should also put in place procedures for primary stakeholders engagements, identify and address their nature of interest and power in future risk management projects

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.

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.

Comparison of additive (absolute) risk projection models and multiplicative (relative) risk projection models in estimating radiation-induced lifetime cancer risk

International Nuclear Information System (INIS)

Kai, Michiaki; Kusama, Tomoko

1990-01-01

Lifetime cancer risk estimates depend on risk projection models. While the increasing lengths of follow-up observation periods of atomic bomb survivors in Hiroshima and Nagasaki bring about changes in cancer risk estimates, the validity of the two risk projection models, the additive risk projection model (AR) and multiplicative risk projection model (MR), comes into question. This paper compares the lifetime risk or loss of life-expectancy between the two projection models on the basis of BEIR-III report or recently published RERF report. With Japanese cancer statistics the estimates of MR were greater than those of AR, but a reversal of these results was seen when the cancer hazard function for India was used. When we investigated the validity of the two projection models using epidemiological human data and animal data, the results suggested that MR was superior to AR with respect to temporal change, but there was little evidence to support its validity. (author)

Addressing Uncertainties in Cost Estimates for Decommissioning Nuclear Facilities

International Nuclear Information System (INIS)

Benjamin, Serge; Descures, Sylvain; Du Pasquier, Louis; Francois, Patrice; Buonarotti, Stefano; Mariotti, Giovanni; Tarakonov, Jurij; Daniska, Vladimir; Bergh, Niklas; Carroll, Simon; AaSTRoeM, Annika; Cato, Anna; De La Gardie, Fredrik; Haenggi, Hannes; Rodriguez, Jose; Laird, Alastair; Ridpath, Andy; La Guardia, Thomas; O'Sullivan, Patrick; ); Weber, Inge; )

2017-01-01

The cost estimation process of decommissioning nuclear facilities has continued to evolve in recent years, with a general trend towards demonstrating greater levels of detail in the estimate and more explicit consideration of uncertainties, the latter of which may have an impact on decommissioning project costs. The 2012 report on the International Structure for Decommissioning Costing (ISDC) of Nuclear Installations, a joint recommendation by the Nuclear Energy Agency (NEA), the International Atomic Energy Agency (IAEA) and the European Commission, proposes a standardised structure of cost items for decommissioning projects that can be used either directly for the production of cost estimates or for mapping of cost items for benchmarking purposes. The ISDC, however, provides only limited guidance on the treatment of uncertainty when preparing cost estimates. Addressing Uncertainties in Cost Estimates for Decommissioning Nuclear Facilities, prepared jointly by the NEA and IAEA, is intended to complement the ISDC, assisting cost estimators and reviewers in systematically addressing uncertainties in decommissioning cost estimates. Based on experiences gained in participating countries and projects, the report describes how uncertainty and risks can be analysed and incorporated in decommissioning cost estimates, while presenting the outcomes in a transparent manner

Production scheduling of a lignite mine under quality and reserves uncertainty

International Nuclear Information System (INIS)

Galetakis, Michael; Roumpos, Christos; Alevizos, George; Vamvuka, Despina

2011-01-01

The effect of uncertainty sources to the stochastic optimization of the combined project of a new surface lignite mine exploitation and power plant operation for electricity generation is investigated. Major sources of uncertainty that were considered are the reserves and the quality of the lignite. Since probability distribution functions for these uncertainties were estimated during the detailed exploration phase of the deposit, the overall goal is then to determine the optimal capacity of the power plant and consequently the optimal production rate of the mine over the time. The optimization objective that was selected is the maximization of the net present value of the project. Emphasis is placed on the sensitivity analysis for the investigation of the effect of quality and reserves uncertainty on project optimization, on the mathematical formulation of risk attitude strategy and on increasing the efficiency of the optimization process by creating a limited set of feasible solutions applying empirical rules. The developed methodology was applied for the determination of the optimal annual production rate of a new surface lignite mine in the area of Ptolemais–Amynteon in Northern Greece. - Highlights: ► Quality and reserves uncertainty affects considerably the production scheduling. ► Stochastic optimization is greatly accelerated by incorporating Taylor's rule. ► Decisions can be made considering different risk level attitudes.

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.

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.

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).

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.

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.

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

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.

Space Radiation Cancer, Circulatory Disease and CNS Risks for Near Earth Asteroid and Mars Missions: Uncertainty Estimates for Never-Smokers

Science.gov (United States)

Cucinotta, Francis A.; Chappell, Lori J.; Wang, Minli; Kim, Myung-Hee

2011-01-01

The uncertainties in estimating the health risks from galactic cosmic rays (GCR) and solar particle events (SPE) are a major limitation to the length of space missions and the evaluation of potential risk mitigation approaches. NASA limits astronaut exposures to a 3% risk of exposure induced cancer death (REID), and protects against uncertainties in risks projections using an assessment of 95% confidence intervals after propagating the error from all model factors (environment and organ exposure, risk coefficients, dose-rate modifiers, and quality factors). Because there are potentially significant late mortality risks from diseases of the circulatory system and central nervous system (CNS) which are less well defined than cancer risks, the cancer REID limit is not necessarily conservative. In this report, we discuss estimates of lifetime risks from space radiation and new estimates of model uncertainties are described. The key updates to the NASA risk projection model are: 1) Revised values for low LET risk coefficients for tissue specific cancer incidence, with incidence rates transported to an average U.S. population to estimate the probability of Risk of Exposure Induced Cancer (REIC) and REID. 2) An analysis of smoking attributable cancer risks for never-smokers that shows significantly reduced lung cancer risk as well as overall cancer risks from radiation compared to risk estimated for the average U.S. population. 3) Derivation of track structure based quality functions depends on particle fluence, charge number, Z and kinetic energy, E. 4) The assignment of a smaller maximum in quality function for leukemia than for solid cancers. 5) The use of the ICRP tissue weights is shown to over-estimate cancer risks from SPEs by a factor of 2 or more. Summing cancer risks for each tissue is recommended as a more accurate approach to estimate SPE cancer risks. 6) Additional considerations on circulatory and CNS disease risks. Our analysis shows that an individual s

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.

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

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.

Evaluating high risks in large-scale projects using an extended VIKOR method under a fuzzy environment

Directory of Open Access Journals (Sweden)

S. Ebrahimnejad

2012-04-01

Full Text Available The complexity of large-scale projects has led to numerous risks in their life cycle. This paper presents a new risk evaluation approach in order to rank the high risks in large-scale projects and improve the performance of these projects. It is based on the fuzzy set theory that is an effective tool to handle uncertainty. It is also based on an extended VIKOR method that is one of the well-known multiple criteria decision-making (MCDM methods. The proposed decision-making approach integrates knowledge and experience acquired from professional experts, since they perform the risk identification and also the subjective judgments of the performance rating for high risks in terms of conflicting criteria, including probability, impact, quickness of reaction toward risk, event measure quantity and event capability criteria. The most notable difference of the proposed VIKOR method with its traditional version is just the use of fuzzy decision-matrix data to calculate the ranking index without the need to ask the experts. Finally, the proposed approach is illustrated with a real-case study in an Iranian power plant project, and the associated results are compared with two well-known decision-making methods under a fuzzy environment.

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.

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

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

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.

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.

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

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

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

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.

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.)

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

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

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). ...

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

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...

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...

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.

Risk Management Capability Maturity and Performance of Complex Product and System (CoPS Projects with an Asian Perspective

Directory of Open Access Journals (Sweden)

Ren, Y.

2014-07-01

Full Text Available Complex Products and Systems (CoPS are high value, technology and engineering-intensive capital goods. The motivation of this study is the persistent high failure rate of CoPS projects, Asian CoPS provider’s weak capability and lack of specific research on CoPS risk management. This paper evaluates risk management maturity level of CoPS projects against a general CoPS risk management capability maturity model (RM-CMM developed by the authors. An Asian based survey was conducted to investigate the value of RM to project performance, and Asian (non-Japanese CoPS implementers’ perceived application of RM practices, their strengths and weaknesses. The survey result shows that higher RM maturity level leads to higher CoPS project performance. It also shows project complexity and uncertainty moderates the relationship between some RM practices and project performance, which implies that a contingency approach should be adopted to manage CoPS risks effectively. In addition, it shows that Asian CoPS implementers are weak in RM process and there are also rooms for improvement in the softer aspects of organizational capabilities and robustness.

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.

The Challenge of Integrating OHS into Industrial Project Risk Management: Proposal of a Methodological Approach to Guide Future Research (Case of Mining Projects in Quebec, Canada

Directory of Open Access Journals (Sweden)

Adel Badri

2015-06-01

Full Text Available Although risk management tools are put to good use in many industrial sectors, some large projects have been met with numerous problems due to failure to take occupational health and safety (OHS into consideration. In spite of the high level of risk and uncertainty associated with many industrial projects, the number of studies of methods for managing all known risks systematically remains small. Under effervescent economic conditions, industries must meet several challenges associated with frequent project start-ups. In highly complex and uncertain environments, rigorous management of risk remains indispensable for avoiding threats to the success of projects. Many businesses seek continually to create and improve integrated approaches to risk management. This article puts into perspective the complexity of the challenge of integrating OHS into industrial project risk management. A conceptual and methodological approach is proposed to guide future research focused on meeting this challenge. The approach is based on applying multi-disciplinary research modes to a complex industrial context in order to identify all scenarios likely to contain threats to humans or the environment. A case study is used to illustrate the potential of the proposed approach for application and its contribution to meeting the challenge of taking OHS into consideration. On-site researchers were able to develop a new approach that helped two mining companies in Quebec (Canada to achieve successful integration of OHS into expansion projects.

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.

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.

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)

Evaluating shielding effectiveness for reducing space radiation cancer risks

International Nuclear Information System (INIS)

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

2006-01-01

We discuss calculations of probability distribution functions (PDF) representing uncertainties in projecting fatal cancer risk from galactic cosmic rays (GCR) and solar particle events (SPE). The PDFs are used in significance tests for evaluating the effectiveness of potential radiation shielding approaches. Uncertainties in risk coefficients determined from epidemiology data, dose and dose-rate reduction factors, quality factors, and physics models of radiation environments are considered in models of cancer risk PDFs. Competing mortality risks and functional correlations in radiation quality factor uncertainties are included in the calculations. We show that the cancer risk uncertainty, defined as the ratio of the upper value of 95% confidence interval (CI) to the point estimate is about 4-fold for lunar and Mars mission risk projections. For short-stay lunar missions ( 180d) or Mars missions, GCR risks may exceed radiation risk limits that are based on acceptable levels of risk. For example, the upper 95% CI exceeding 10% fatal risk for males and females on a Mars mission. For reducing GCR cancer risks, shielding materials are marginally effective because of the penetrating nature of GCR and secondary radiation produced in tissue by relativistic particles. At the present time, polyethylene or carbon composite shielding cannot be shown to significantly reduce risk compared to aluminum shielding based on a significance test that accounts for radiobiology uncertainties in GCR risk projection

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

Risk Evaluation of a UHV Power Transmission Construction Project Based on a Cloud Model and FCE Method for Sustainability

Directory of Open Access Journals (Sweden)

Huiru Zhao

2015-03-01

Full Text Available In order to achieve the sustainable development of energy, Ultra High Voltage (UHV power transmission construction projects are being established in China currently. Their high-tech nature, the massive amount of money involved, and the need for multi-agent collaboration as well as complex construction environments bring many challenges and risks. Risk management, therefore, is critical to reduce the risks and realize sustainable development of projects. Unfortunately, many traditional risk assessment methods may not perform well due to the great uncertainty and randomness inherent in UHV power construction projects. This paper, therefore, proposes a risk evaluation index system and a hybrid risk evaluation model to evaluate the risk of UHV projects and find out the key risk factors. This model based on a cloud model and fuzzy comprehensive evaluation (FCE method combines the superiority of the cloud model for reflecting randomness and discreteness with the advantages of the fuzzy comprehensive evaluation method in handling uncertain and vague issues. For the sake of proving our framework, an empirical study of “Zhejiang-Fuzhou” UHV power transmission construction project is presented. As key contributions, we find the risk of this project lies at a “middle” to “high” level and closer to a “middle” level; the “management risk” and “social risk” are identified as the most important risk factors requiring more attention; and some risk control recommendations are proposed. This article demonstrates the value of our approach in risk identification, which seeks to improve the risk control level and the sustainable development of UHV power transmission construction projects.

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.

Uncertainty as Knowledge: Constraints on Policy Choices Provided by Analysis of Uncertainty

Science.gov (United States)

Lewandowsky, S.; Risbey, J.; Smithson, M.; Newell, B. R.

2012-12-01

Uncertainty forms an integral part of climate science, and it is often cited in connection with arguments against mitigative action. We argue that an analysis of uncertainty must consider existing knowledge as well as uncertainty, and the two must be evaluated with respect to the outcomes and risks associated with possible policy options. Although risk judgments are inherently subjective, an analysis of the role of uncertainty within the climate system yields two constraints that are robust to a broad range of assumptions. Those constraints are that (a) greater uncertainty about the climate system is necessarily associated with greater expected damages from warming, and (b) greater uncertainty translates into a greater risk of the failure of mitigation efforts. These ordinal constraints are unaffected by subjective or cultural risk-perception factors, they are independent of the discount rate, and they are independent of the magnitude of the estimate for climate sensitivity. The constraints mean that any appeal to uncertainty must imply a stronger, rather than weaker, need to cut greenhouse gas emissions than in the absence of uncertainty.

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.

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

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

Assessing Risk in Costing High-energy Accelerators: from Existing Projects to the Future Linear Collider

CERN Document Server

Lebrun, Philippe

2010-01-01

High-energy accelerators are large projects funded by public money, developed over the years and constructed via major industrial contracts both in advanced technology and in more conventional domains such as civil engineering and infrastructure, for which they often constitute one-of markets. Assessing their cost, as well as the risk and uncertainty associated with this assessment is therefore an essential part of project preparation and a justified requirement by the funding agencies. Stemming from the experience with large circular colliders at CERN, LEP and LHC, as well as with the Main Injector, the Tevatron Collider Experiments and Accelerator Upgrades, and the NOvA Experiment at Fermilab, we discuss sources of cost variance and derive cost risk assessment methods applicable to the future linear collider, through its two technical approaches for ILC and CLIC. We also address disparities in cost risk assessment imposed by regional differences in regulations, procedures and practices.

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

International Nuclear Information System (INIS)

Harper, F.T.; Young, M.L.; Miller, L.A.; Hora, S.C.; Lui, C.H.; Goossens, L.H.J.; Cooke, R.M.; Paesler-Sauer, J.; Helton, J.C.

1995-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

Harper, F.T.; Young, M.L.; Miller, L.A. [Sandia National Labs., Albuquerque, NM (United States); Hora, S.C. [Univ. of Hawaii, Hilo, HI (United States); Lui, C.H. [Nuclear Regulatory Commission, Washington, DC (United States); Goossens, L.H.J.; Cooke, R.M. [Delft Univ. of Technology (Netherlands); Paesler-Sauer, J. [Research Center, Karlsruhe (Germany); Helton, J.C. [and others

1995-01-01

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

Uncertainty and Sensitivity of Direct Economic Flood Damages: the FloodRisk Free and Open-Source Software

Science.gov (United States)

Albano, R.; Sole, A.; Mancusi, L.; Cantisani, A.; Perrone, A.

2017-12-01

The considerable increase of flood damages in the the past decades has shifted in Europe the attention from protection against floods to managing flood risks. In this context, the expected damages assessment represents a crucial information within the overall flood risk management process. The present paper proposes an open source software, called FloodRisk, that is able to operatively support stakeholders in the decision making processes with a what-if approach by carrying out the rapid assessment of the flood consequences, in terms of direct economic damage and loss of human lives. The evaluation of the damage scenarios, trough the use of the GIS software proposed here, is essential for cost-benefit or multi-criteria analysis of risk mitigation alternatives. However, considering that quantitative assessment of flood damages scenarios is characterized by intrinsic uncertainty, a scheme has been developed to identify and quantify the role of the input parameters in the total uncertainty of flood loss model application in urban areas with mild terrain and complex topography. By the concept of parallel models, the contribution of different module and input parameters to the total uncertainty is quantified. The results of the present case study have exhibited a high epistemic uncertainty on the damage estimation module and, in particular, on the type and form of the utilized damage functions, which have been adapted and transferred from different geographic and socio-economic contexts because there aren't depth-damage functions that are specifically developed for Italy. Considering that uncertainty and sensitivity depend considerably on local characteristics, the epistemic uncertainty associated with the risk estimate is reduced by introducing additional information into the risk analysis. In the light of the obtained results, it is evident the need to produce and disseminate (open) data to develop micro-scale vulnerability curves. Moreover, the urgent need to push

Unquestioned answers or unanswered questions: beliefs about science guide responses to uncertainty in climate change risk communication.

Science.gov (United States)

Rabinovich, Anna; Morton, Thomas A

2012-06-01

In two experimental studies we investigated the effect of beliefs about the nature and purpose of science (classical vs. Kuhnian models of science) on responses to uncertainty in scientific messages about climate change risk. The results revealed a significant interaction between both measured (Study 1) and manipulated (Study 2) beliefs about science and the level of communicated uncertainty on willingness to act in line with the message. Specifically, messages that communicated high uncertainty were more persuasive for participants who shared an understanding of science as debate than for those who believed that science is a search for absolute truth. In addition, participants who had a concept of science as debate were more motivated by higher (rather than lower) uncertainty in climate change messages. The results suggest that achieving alignment between the general public's beliefs about science and the style of the scientific messages is crucial for successful risk communication in science. Accordingly, rather than uncertainty always undermining the effectiveness of science communication, uncertainty can enhance message effects when it fits the audience's understanding of what science is. © 2012 Society for Risk Analysis.

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.

Reprint of: Production scheduling of a lignite mine under quality and reserves uncertainty

International Nuclear Information System (INIS)

Galetakis, Michael; Roumpos, Christos; Alevizos, George; Vamvuka, Despina

2012-01-01

The effect of uncertainty sources to the stochastic optimization of the combined project of a new surface lignite mine exploitation and power plant operation for electricity generation is investigated. Major sources of uncertainty that were considered are the reserves and the quality of the lignite. Since probability distribution functions for these uncertainties were estimated during the detailed exploration phase of the deposit, the overall goal is then to determine the optimal capacity of the power plant and consequently the optimal production rate of the mine over the time. The optimization objective that was selected is the maximization of the net present value of the project. Emphasis is placed on the sensitivity analysis for the investigation of the effect of quality and reserves uncertainty on project optimization, on the mathematical formulation of risk attitude strategy and on increasing the efficiency of the optimization process by creating a limited set of feasible solutions applying empirical rules. The developed methodology was applied for the determination of the optimal annual production rate of a new surface lignite mine in the area of Ptolemais–Amynteon in Northern Greece. - Highlights: ► Quality and reserves uncertainty affects considerably the production scheduling. ► Stochastic optimization is greatly accelerated by incorporating Taylor's rule. ► Decisions can be made considering different risk level attitudes.

Optimization under Uncertainty

KAUST Repository

Lopez, Rafael H.

2016-01-06

The goal of this poster is to present the main approaches to optimization of engineering systems in the presence of uncertainties. We begin by giving an insight about robust optimization. Next, we detail how to deal with probabilistic constraints in optimization, the so called the reliability based design. Subsequently, we present the risk optimization approach, which includes the expected costs of failure in the objective function. After that the basic description of each approach is given, the projects developed by CORE are presented. Finally, the main current topic of research of CORE is described.

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.

Assessment of the Appalachian Basin Geothermal Field: Combining Risk Factors to Inform Development of Low Temperature Projects

Science.gov (United States)

Smith, J. D.; Whealton, C.; Camp, E. R.; Horowitz, F.; Frone, Z. S.; Jordan, T. E.; Stedinger, J. R.

2015-12-01

Exploration methods for deep geothermal energy projects must primarily consider whether or not a location has favorable thermal resources. Even where the thermal field is favorable, other factors may impede project development and success. A combined analysis of these factors and their uncertainty is a strategy for moving geothermal energy proposals forward from the exploration phase at the scale of a basin to the scale of a project, and further to design of geothermal systems. For a Department of Energy Geothermal Play Fairway Analysis we assessed quality metrics, which we call risk factors, in the Appalachian Basin of New York, Pennsylvania, and West Virginia. These included 1) thermal field variability, 2) productivity of natural reservoirs from which to extract heat, 3) potential for induced seismicity, and 4) presence of thermal utilization centers. The thermal field was determined using a 1D heat flow model for 13,400 bottomhole temperatures (BHT) from oil and gas wells. Steps included the development of i) a set of corrections to BHT data and ii) depth models of conductivity stratigraphy at each borehole based on generalized stratigraphy that was verified for a select set of wells. Wells are control points in a spatial statistical analysis that resulted in maps of the predicted mean thermal field properties and of the standard error of the predicted mean. Seismic risk was analyzed by comparing earthquakes and stress orientations in the basin to gravity and magnetic potential field edges at depth. Major edges in the potential fields served as interpolation boundaries for the thermal maps (Figure 1). Natural reservoirs were identified from published studies, and productivity was determined based on the expected permeability and dimensions of each reservoir. Visualizing the natural reservoirs and population centers on a map of the thermal field communicates options for viable pilot sites and project designs (Figure 1). Furthermore, combining the four risk

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

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

Communicating Uncertainty about Climate Change for Application to Security Risk Management

Science.gov (United States)

Gulledge, J. M.

2011-12-01

The science of climate change has convincingly demonstrated that human activities, including the release of greenhouse gases, land-surface changes, particle emissions, and redistribution of water, are changing global and regional climates. Consequently, key institutions are now concerned about the potential social impacts of climate change. For example, the 2010 Quadrennial Defense Review Report from the U.S. Department of Defense states that "climate change, energy security, and economic stability are inextricably linked." Meanwhile, insured losses from climate and weather-related natural disasters have risen dramatically over the past thirty years. Although these losses stem largely from socioeconomic trends, insurers are concerned that climate change could exacerbate this trend and render certain types of climate risk non-diversifiable. Meanwhile, the climate science community-broadly defined as physical, biological, and social scientists focused on some aspect of climate change-remains largely focused scholarly activities that are valued in the academy but not especially useful to decision makers. On the other hand, climate scientists who engage in policy discussions have generally permitted vested interests who support or oppose climate policies to frame the discussion of climate science within the policy arena. Such discussions focus on whether scientific uncertainties are sufficiently resolved to justify policy and the vested interests overstate or understate key uncertainties to support their own agendas. Consequently, the scientific community has become absorbed defending scientific findings to the near exclusion of developing novel tools to aid in risk-based decision-making. For example, the Intergovernmental Panel on Climate Change (IPCC), established expressly for the purpose of informing governments, has largely been engaged in attempts to reduce unavoidable uncertainties rather than helping the world's governments define a science-based risk

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.

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.

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.

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.

Multi-Model Projections of River Flood Risk in Europe under Global Warming

Directory of Open Access Journals (Sweden)

Lorenzo Alfieri

2018-01-01

Full Text Available Knowledge on the costs of natural disasters under climate change is key information for planning adaptation and mitigation strategies of future climate policies. Impact models for large scale flood risk assessment have made leaps forward in the past few years, thanks to the increased availability of high resolution climate projections and of information on local exposure and vulnerability to river floods. Yet, state-of-the-art flood impact models rely on a number of input data and techniques that can substantially influence their results. This work compares estimates of river flood risk in Europe from three recent case studies, assuming global warming scenarios of 1.5, 2, and 3 degrees Celsius from pre-industrial levels. The assessment is based on comparing ensemble projections of expected damage and population affected at country level. Differences and common points between the three cases are shown, to point out main sources of uncertainty, strengths, and limitations. In addition, the multi-model comparison helps identify regions with the largest agreement on specific changes in flood risk. Results show that global warming is linked to substantial increase in flood risk over most countries in Central and Western Europe at all warming levels. In Eastern Europe, the average change in flood risk is smaller and the multi-model agreement is poorer.

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.

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.

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.

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)

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

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.

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 -

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.

Uncertainty Analysis and Overtopping Risk Evaluation of Maroon Dam withMonte Carlo and Latin Hypercube Methods

Directory of Open Access Journals (Sweden)

J. M. Vali Samani

2016-02-01

Full Text Available Introduction: The greatest part of constructed dams belongs to embankment dams and there are many examples of their failures throughout history. About one-third of the world’s dam failures have been caused by flood overtopping, which indicates that flood overtopping is an important factor affecting reservoir projects’ safety. Moreover, because of a poor understanding of the randomness of floods, reservoir water levels during flood seasons are often lowered artificially in order to avoid overtopping and protect the lives and property of downstream residents. So, estimation of dam overtopping risk with regard to uncertainties is more important than achieving the dam’s safety. This study presents the procedure for risk evaluation of dam overtopping due to various uncertaintiess in inflows and reservoir initial condition. Materials and Methods: This study aims to present a practical approach and compare the different uncertainty analysis methods in the evaluation of dam overtopping risk due to flood. For this purpose, Monte Carlo simulation and Latin hypercube sampling methods were used to calculate the overtopping risk, evaluate the uncertainty, and calculate the highest water level during different flood events. To assess these methods from a practical point of view, the Maroon dam was chosen for the case study. Figure. 1 indicates the work procedure, including three parts: 1 Identification and evaluation of effective factors on flood routing and dam overtopping, 2 Data collection and analysis for reservoir routing and uncertainty analysis, 3 Uncertainty and risk analysis. Figure 1- Diagram of dam overtopping risk evaluation Results and Discussion: Figure 2 shows the results of the computed overtopping risks for the Maroon Dam without considering the wind effect, for the initial water level of 504 m as an example. As it is shown in Figure. 2, the trends of the risk curves computed by the different uncertainty analysis methods are similar