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Sample records for effects uncertainty assessment

  1. Probabilistic accident consequence uncertainty analysis -- Early health effects uncertainty assessment. Volume 2: Appendices

    Energy Technology Data Exchange (ETDEWEB)

    Haskin, F.E. [Univ. of New Mexico, Albuquerque, NM (United States); Harper, F.T. [Sandia National Labs., Albuquerque, NM (United States); Goossens, L.H.J.; Kraan, B.C.P. [Delft Univ. of Technology (Netherlands)

    1997-12-01

    The development of two new probabilistic accident consequence codes, MACCS and COSYMA, was completed in 1990. These codes estimate the consequence from the accidental releases of radiological material from hypothesized accidents at nuclear installations. In 1991, the US Nuclear Regulatory Commission and the Commission of the European Communities began cosponsoring a joint uncertainty analysis of the two codes. The ultimate objective of this joint effort was to systematically develop credible and traceable uncertainty distributions for the respective code input variables. A formal expert judgment elicitation and evaluation process was identified as the best technology available for developing a library of uncertainty distributions for these consequence parameters. This report focuses on the results of the study to develop distribution for variables related to the MACCS and COSYMA early health effects models. This volume contains appendices that include (1) a summary of the MACCS and COSYMA consequence codes, (2) the elicitation questionnaires and case structures, (3) the rationales and results for the panel on early health effects, (4) short biographies of the experts, and (5) the aggregated results of their responses.

  2. A systematic framework for effective uncertainty assessment of severe accident calculations; Hybrid qualitative and quantitative methodology

    International Nuclear Information System (INIS)

    Hoseyni, Seyed Mohsen; Pourgol-Mohammad, Mohammad; Tehranifard, Ali Abbaspour; Yousefpour, Faramarz

    2014-01-01

    This paper describes a systematic framework for characterizing important phenomena and quantifying the degree of contribution of each parameter to the output in severe accident uncertainty assessment. The proposed methodology comprises qualitative as well as quantitative phases. The qualitative part so called Modified PIRT, being a robust process of PIRT for more precise quantification of uncertainties, is a two step process for identifying and ranking based on uncertainty importance in severe accident phenomena. In this process identified severe accident phenomena are ranked according to their effect on the figure of merit and their level of knowledge. Analytical Hierarchical Process (AHP) serves here as a systematic approach for severe accident phenomena ranking. Formal uncertainty importance technique is used to estimate the degree of credibility of the severe accident model(s) used to represent the important phenomena. The methodology uses subjective justification by evaluating available information and data from experiments, and code predictions for this step. The quantitative part utilizes uncertainty importance measures for the quantification of the effect of each input parameter to the output uncertainty. A response surface fitting approach is proposed for estimating associated uncertainties with less calculation cost. The quantitative results are used to plan in reducing epistemic uncertainty in the output variable(s). The application of the proposed methodology is demonstrated for the ACRR MP-2 severe accident test facility. - Highlights: • A two stage framework for severe accident uncertainty analysis is proposed. • Modified PIRT qualitatively identifies and ranks uncertainty sources more precisely. • Uncertainty importance measure quantitatively calculates effect of each uncertainty source. • Methodology is applied successfully on ACRR MP-2 severe accident test facility

  3. Critical loads - assessment of uncertainty

    Energy Technology Data Exchange (ETDEWEB)

    Barkman, A.

    1998-10-01

    The effects of data uncertainty in applications of the critical loads concept were investigated on different spatial resolutions in Sweden and northern Czech Republic. Critical loads of acidity (CL) were calculated for Sweden using the biogeochemical model PROFILE. Three methods with different structural complexity were used to estimate the adverse effects of S0{sub 2} concentrations in northern Czech Republic. Data uncertainties in the calculated critical loads/levels and exceedances (EX) were assessed using Monte Carlo simulations. Uncertainties within cumulative distribution functions (CDF) were aggregated by accounting for the overlap between site specific confidence intervals. Aggregation of data uncertainties within CDFs resulted in lower CL and higher EX best estimates in comparison with percentiles represented by individual sites. Data uncertainties were consequently found to advocate larger deposition reductions to achieve non-exceedance based on low critical loads estimates on 150 x 150 km resolution. Input data were found to impair the level of differentiation between geographical units at all investigated resolutions. Aggregation of data uncertainty within CDFs involved more constrained confidence intervals for a given percentile. Differentiation as well as identification of grid cells on 150 x 150 km resolution subjected to EX was generally improved. Calculation of the probability of EX was shown to preserve the possibility to differentiate between geographical units. Re-aggregation of the 95%-ile EX on 50 x 50 km resolution generally increased the confidence interval for each percentile. Significant relationships were found between forest decline and the three methods addressing risks induced by S0{sub 2} concentrations. Modifying S0{sub 2} concentrations by accounting for the length of the vegetation period was found to constitute the most useful trade-off between structural complexity, data availability and effects of data uncertainty. Data

  4. Uncertainty analysis in safety assessment

    International Nuclear Information System (INIS)

    Lemos, Francisco Luiz de; Sullivan, Terry

    1997-01-01

    Nuclear waste disposal is a very complex subject which requires the study of many different fields of science, like hydro geology, meteorology, geochemistry, etc. In addition, the waste disposal facilities are designed to last for a very long period of time. Both of these conditions make safety assessment projections filled with uncertainty. This paper addresses approaches for treatment of uncertainties in the safety assessment modeling due to the variability of data and some current approaches used to deal with this problem. (author)

  5. Dispelling urban myths about default uncertainty factors in chemical risk assessment--sufficient protection against mixture effects?

    Science.gov (United States)

    Martin, Olwenn V; Martin, Scholze; Kortenkamp, Andreas

    2013-07-01

    Assessing the detrimental health effects of chemicals requires the extrapolation of experimental data in animals to human populations. This is achieved by applying a default uncertainty factor of 100 to doses not found to be associated with observable effects in laboratory animals. It is commonly assumed that the toxicokinetic and toxicodynamic sub-components of this default uncertainty factor represent worst-case scenarios and that the multiplication of those components yields conservative estimates of safe levels for humans. It is sometimes claimed that this conservatism also offers adequate protection from mixture effects. By analysing the evolution of uncertainty factors from a historical perspective, we expose that the default factor and its sub-components are intended to represent adequate rather than worst-case scenarios. The intention of using assessment factors for mixture effects was abandoned thirty years ago. It is also often ignored that the conservatism (or otherwise) of uncertainty factors can only be considered in relation to a defined level of protection. A protection equivalent to an effect magnitude of 0.001-0.0001% over background incidence is generally considered acceptable. However, it is impossible to say whether this level of protection is in fact realised with the tolerable doses that are derived by employing uncertainty factors. Accordingly, it is difficult to assess whether uncertainty factors overestimate or underestimate the sensitivity differences in human populations. It is also often not appreciated that the outcome of probabilistic approaches to the multiplication of sub-factors is dependent on the choice of probability distributions. Therefore, the idea that default uncertainty factors are overly conservative worst-case scenarios which can account both for the lack of statistical power in animal experiments and protect against potential mixture effects is ill-founded. We contend that precautionary regulation should provide an

  6. Dispelling urban myths about default uncertainty factors in chemical risk assessment – sufficient protection against mixture effects?

    Science.gov (United States)

    2013-01-01

    Assessing the detrimental health effects of chemicals requires the extrapolation of experimental data in animals to human populations. This is achieved by applying a default uncertainty factor of 100 to doses not found to be associated with observable effects in laboratory animals. It is commonly assumed that the toxicokinetic and toxicodynamic sub-components of this default uncertainty factor represent worst-case scenarios and that the multiplication of those components yields conservative estimates of safe levels for humans. It is sometimes claimed that this conservatism also offers adequate protection from mixture effects. By analysing the evolution of uncertainty factors from a historical perspective, we expose that the default factor and its sub-components are intended to represent adequate rather than worst-case scenarios. The intention of using assessment factors for mixture effects was abandoned thirty years ago. It is also often ignored that the conservatism (or otherwise) of uncertainty factors can only be considered in relation to a defined level of protection. A protection equivalent to an effect magnitude of 0.001-0.0001% over background incidence is generally considered acceptable. However, it is impossible to say whether this level of protection is in fact realised with the tolerable doses that are derived by employing uncertainty factors. Accordingly, it is difficult to assess whether uncertainty factors overestimate or underestimate the sensitivity differences in human populations. It is also often not appreciated that the outcome of probabilistic approaches to the multiplication of sub-factors is dependent on the choice of probability distributions. Therefore, the idea that default uncertainty factors are overly conservative worst-case scenarios which can account both for the lack of statistical power in animal experiments and protect against potential mixture effects is ill-founded. We contend that precautionary regulation should provide an

  7. Model uncertainty in safety assessment

    International Nuclear Information System (INIS)

    Pulkkinen, U.; Huovinen, T.

    1996-01-01

    The uncertainty analyses are an essential part of any risk assessment. Usually the uncertainties of reliability model parameter values are described by probability distributions and the uncertainty is propagated through the whole risk model. In addition to the parameter uncertainties, the assumptions behind the risk models may be based on insufficient experimental observations and the models themselves may not be exact descriptions of the phenomena under analysis. The description and quantification of this type of uncertainty, model uncertainty, is the topic of this report. The model uncertainty is characterized and some approaches to model and quantify it are discussed. The emphasis is on so called mixture models, which have been applied in PSAs. Some of the possible disadvantages of the mixture model are addressed. In addition to quantitative analyses, also qualitative analysis is discussed shortly. To illustrate the models, two simple case studies on failure intensity and human error modeling are described. In both examples, the analysis is based on simple mixture models, which are observed to apply in PSA analyses. (orig.) (36 refs., 6 figs., 2 tabs.)

  8. Model uncertainty in safety assessment

    Energy Technology Data Exchange (ETDEWEB)

    Pulkkinen, U; Huovinen, T [VTT Automation, Espoo (Finland). Industrial Automation

    1996-01-01

    The uncertainty analyses are an essential part of any risk assessment. Usually the uncertainties of reliability model parameter values are described by probability distributions and the uncertainty is propagated through the whole risk model. In addition to the parameter uncertainties, the assumptions behind the risk models may be based on insufficient experimental observations and the models themselves may not be exact descriptions of the phenomena under analysis. The description and quantification of this type of uncertainty, model uncertainty, is the topic of this report. The model uncertainty is characterized and some approaches to model and quantify it are discussed. The emphasis is on so called mixture models, which have been applied in PSAs. Some of the possible disadvantages of the mixture model are addressed. In addition to quantitative analyses, also qualitative analysis is discussed shortly. To illustrate the models, two simple case studies on failure intensity and human error modeling are described. In both examples, the analysis is based on simple mixture models, which are observed to apply in PSA analyses. (orig.) (36 refs., 6 figs., 2 tabs.).

  9. Uncertainty analysis in safety assessment

    Energy Technology Data Exchange (ETDEWEB)

    Lemos, Francisco Luiz de [Centro de Desenvolvimento da Tecnologia Nuclear (CDTN), Belo Horizonte, MG (Brazil); Sullivan, Terry [Brookhaven National Lab., Upton, NY (United States)

    1997-12-31

    Nuclear waste disposal is a very complex subject which requires the study of many different fields of science, like hydro geology, meteorology, geochemistry, etc. In addition, the waste disposal facilities are designed to last for a very long period of time. Both of these conditions make safety assessment projections filled with uncertainty. This paper addresses approaches for treatment of uncertainties in the safety assessment modeling due to the variability of data and some current approaches used to deal with this problem. (author) 13 refs.; e-mail: lemos at bnl.gov; sulliva1 at bnl.gov

  10. Uncertainties in radioecological assessment models

    International Nuclear Information System (INIS)

    Hoffman, F.O.; Miller, C.W.; Ng, Y.C.

    1983-01-01

    Environmental radiological assessments rely heavily on the use of mathematical models. The predictions of these models are inherently uncertain because models are inexact representations of real systems. The major sources of this uncertainty are related to bias in model formulation and imprecision in parameter estimation. The magnitude of uncertainty is a function of the questions asked of the model and the specific radionuclides and exposure pathways of dominant importance. It is concluded that models developed as research tools should be distinguished from models developed for assessment applications. Furthermore, increased model complexity does not necessarily guarantee increased accuracy. To improve the realism of assessment modeling, stochastic procedures are recommended that translate uncertain parameter estimates into a distribution of predicted values. These procedures also permit the importance of model parameters to be ranked according to their relative contribution to the overall predicted uncertainty. Although confidence in model predictions can be improved through site-specific parameter estimation and increased model validation, health risk factors and internal dosimetry models will probably remain important contributors to the amount of uncertainty that is irreducible. 41 references, 4 figures, 4 tables

  11. Probabilistic accident consequence uncertainty analysis -- Late health effects uncertain assessment. Volume 2: Appendices

    Energy Technology Data Exchange (ETDEWEB)

    Little, M.P.; Muirhead, C.R. [National Radiological Protection Board (United Kingdom); Goossens, L.H.J.; Kraan, B.C.P.; Cooke, R.M. [Delft Univ. of Technology (Netherlands); Harper, F.T. [Sandia National Labs., Albuquerque, NM (United States); Hora, S.C. [Univ. of Hawaii, Hilo, HI (United States)

    1997-12-01

    The development of two new probabilistic accident consequence codes, MACCS and COSYMA, was completed in 1990. These codes estimate the consequence from the accidental releases of radiological material from hypothesized accidents at nuclear installations. In 1991, the US Nuclear Regulatory Commission and the Commission of the European Communities began cosponsoring a joint uncertainty analysis of the two codes. The ultimate objective of this joint effort was to systematically develop credible and traceable uncertainty distributions for the respective code input variables. A formal expert judgment elicitation and evaluation process was identified as the best technology available for developing a library of uncertainty distributions for these consequence parameters. This report focuses on the results of the study to develop distribution for variables related to the MACCS and COSYMA late health effects models. This volume contains appendices that include (1) a summary of the MACCS and COSYMA consequence codes, (2) the elicitation questionnaires and case structures, (3) the rationales and results for the expert panel on late health effects, (4) short biographies of the experts, and (5) the aggregated results of their responses.

  12. 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.

  13. Incorporating Plutonium Particle Size Effects in the Assessment of Active Mode Measurement Uncertainty in Passive-Active Neutron Radioassay Systems

    International Nuclear Information System (INIS)

    Blackwood, Larry G.; Harker, Yale D.

    2002-01-01

    Assessment of active mode measurement uncertainty in passive-active neutron radioassay systems used to measure Pu content in nuclear waste is severely hampered by lack of knowledge of the waste Pu particle size distribution, which is a major factor in determining bias in active mode measurements. The sensitivity of active mode measurements to particle size precludes using simulations or surrogate waste forms to estimate uncertainty in active mode measurements when the particle size distribution is not precisely known or inadequately reproduced. An alternative approach is based on a statistical comparison of active and passive mode results in the mass range for which both active and passive mode analyses produce useable measurements. Because passive mode measurements are not particularly sensitive to particle size effects, their uncertainty can be more easily assessed. Once bias corrected, passive mode measurements can serve as confirmatory measurements for the estimation of active mode bias. Further statistical analysis of the errors in measurements leads to precision estimates for the active mode

  14. Advanced LOCA code uncertainty assessment

    International Nuclear Information System (INIS)

    Wickett, A.J.; Neill, A.P.

    1990-11-01

    This report describes a pilot study that identified, quantified and combined uncertainties for the LOBI BL-02 3% small break test. A ''dials'' version of TRAC-PF1/MOD1, called TRAC-F, was used. (author)

  15. Effect of activation cross-section uncertainties on the radiological assessment of the MFE/DEMO first wall

    International Nuclear Information System (INIS)

    Cabellos, O.; Reyes, S.; Sanz, J.; Rodriguez, A.; Youssef, M.; Sawan, M.

    2006-01-01

    A Monte Carlo procedure has been applied in this work in order to address the impact of activation cross-sections (XS) uncertainties on contact dose rate and decay heat calculations for the outboard first wall (FW) of a magnetic fusion energy (MFE) demonstration (DEMO) reactor. The XSs inducing the major uncertainty in the prediction of activation related quantities have been identified. Results have shown that for times corresponding to maintenance activities the uncertainties effect is insignificant since the dominant XSs involved in these calculations are based on accurate experimental data evaluations. However, for times corresponding to waste management/recycling activities, the errors induced by the XSs uncertainties, which in this case are evaluated using systematic models, must be considered. It has been found that two particular isotopes, 6 Co and 94 Nb, are key contributors to the global DEMO FW activation uncertainty results. In these cases, the benefit from further improvements in the accuracy of the critical reaction XSs is discussed

  16. Assessment of measurement result uncertainty in determination of 210Pb with the focus on matrix composition effect in gamma-ray spectrometry

    International Nuclear Information System (INIS)

    Iurian, A.R.; Pitois, A.; Kis-Benedek, G.; Migliori, A.; Padilla-Alvarez, R.; Ceccatelli, A.

    2016-01-01

    Reference materials were used to assess measurement result uncertainty in determination of 210 Pb by gamma-ray spectrometry, liquid scintillation counting, or indirectly by alpha-particle spectrometry, using its daughter 210 Po in radioactive equilibrium. Combined standard uncertainties of 210 Pb massic activities obtained by liquid scintillation counting are in the range 2–12%, depending on matrices and massic activity values. They are in the range 1–3% for the measurement of its daughter 210 Po using alpha-particle spectrometry. Three approaches (direct computation of counting efficiency and efficiency transfer approaches based on the computation and, respectively, experimental determination of the efficiency transfer factors) were applied for the evaluation of 210 Pb using gamma-ray spectrometry. Combined standard uncertainties of gamma-ray spectrometry results were found in the range 2–17%. The effect of matrix composition on self-attenuation was investigated and a detailed assessment of uncertainty components was performed. - Highlights: • Confirmed 210 Pb certified values by LSC and alpha-particle spectrometry ( 210 Po). • Assessed 210 Po measurement result uncertainty by alpha-particle spectrometry. • Matrix composition effect on gamma-ray spectrometry measurement result uncertainty. • Assessment of 210 Pb measurement result uncertainty by gamma-ray spectrometry. • Comparison of techniques and approaches: ‘fit-for-purpose’ considerations.

  17. 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.

  18. How to manage uncertainty in future Life Cycle Assessment (LCA) scenarios addressing the effect of climate change in crop production

    DEFF Research Database (Denmark)

    Niero, Monia; Ingvordsen, Cathrine Heinz; Bagger Jørgensen, Rikke

    2015-01-01

    When Life Cycle Assessment (LCA) is used to provide insights on how to pursue future food demand, it faces the challenge to describe scenarios of the future in which the environmental impacts occur. In the case of future crop production, the effects of climate change should be considered. In this......When Life Cycle Assessment (LCA) is used to provide insights on how to pursue future food demand, it faces the challenge to describe scenarios of the future in which the environmental impacts occur. In the case of future crop production, the effects of climate change should be considered....... In this context, the objectives of this paper are two-fold: (i) to recommend an approach to deal with uncertainty in scenario analysis for LCA of crop production in a changed climate, when the goal of the study is to suggest strategies for adaptation of crop cultivation practices towards low environmental impacts...... climate, soil, water loss and production parameters. Secondly, the handling of these factors in the inventory modeling is discussed and finally implemented in the case study. Our approach follows a 3-step procedure consisting of: (1) definition of a baseline scenario at the Life Cycle Inventory (LCI...

  19. Estimating uncertainty of data limited stock assessments

    DEFF Research Database (Denmark)

    Kokkalis, Alexandros; Eikeset, Anne Maria; Thygesen, Uffe Høgsbro

    2017-01-01

    -limited. Particular emphasis is put on providing uncertainty estimates of the data-limited assessment. We assess four cod stocks in the North-East Atlantic and compare our estimates of stock status (F/Fmsy) with the official assessments. The estimated stock status of all four cod stocks followed the established stock...

  20. Effect of activation cross-section uncertainties on the radiological assessment of the MFE/DEMO first wall

    Energy Technology Data Exchange (ETDEWEB)

    Cabellos, O. [Instituto de Fusion Nuclear, Universidad Politecnica de Madrid, Madrid (Spain)]. E-mail: cabellos@din.upm.es; Reyes, S. [Lawrence Livermore National Laboratory, Livermore, CA (United States); Sanz, J. [Instituto de Fusion Nuclear, Universidad Politecnica de Madrid, Madrid (Spain); University Nacional Educacion a Distancia, Dep. Ingenieria Energetica, Juan del Rosal 12, 28040 Madrid (Spain); Rodriguez, A. [University Nacional Educacion a Distancia, Dep. Ingenieria Energetica, Juan del Rosal 12, 28040 Madrid (Spain); Youssef, M. [University of California, Los Angeles, CA (United States); Sawan, M. [University of Wisconsin, Madison, WI (United States)

    2006-02-15

    A Monte Carlo procedure has been applied in this work in order to address the impact of activation cross-sections (XS) uncertainties on contact dose rate and decay heat calculations for the outboard first wall (FW) of a magnetic fusion energy (MFE) demonstration (DEMO) reactor. The XSs inducing the major uncertainty in the prediction of activation related quantities have been identified. Results have shown that for times corresponding to maintenance activities the uncertainties effect is insignificant since the dominant XSs involved in these calculations are based on accurate experimental data evaluations. However, for times corresponding to waste management/recycling activities, the errors induced by the XSs uncertainties, which in this case are evaluated using systematic models, must be considered. It has been found that two particular isotopes, {sup 6}Co and {sup 94}Nb, are key contributors to the global DEMO FW activation uncertainty results. In these cases, the benefit from further improvements in the accuracy of the critical reaction XSs is discussed.

  1. Assessment of SFR Wire Wrap Simulation Uncertainties

    Energy Technology Data Exchange (ETDEWEB)

    Delchini, Marc-Olivier G. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Reactor and Nuclear Systems Division; Popov, Emilian L. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Reactor and Nuclear Systems Division; Pointer, William David [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Reactor and Nuclear Systems Division; Swiler, Laura P. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2016-09-30

    Predictive modeling and simulation of nuclear reactor performance and fuel are challenging due to the large number of coupled physical phenomena that must be addressed. Models that will be used for design or operational decisions must be analyzed for uncertainty to ascertain impacts to safety or performance. Rigorous, structured uncertainty analyses are performed by characterizing the model’s input uncertainties and then propagating the uncertainties through the model to estimate output uncertainty. This project is part of the ongoing effort to assess modeling uncertainty in Nek5000 simulations of flow configurations relevant to the advanced reactor applications of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. Three geometries are under investigation in these preliminary assessments: a 3-D pipe, a 3-D 7-pin bundle, and a single pin from the Thermal-Hydraulic Out-of-Reactor Safety (THORS) facility. Initial efforts have focused on gaining an understanding of Nek5000 modeling options and integrating Nek5000 with Dakota. These tasks are being accomplished by demonstrating the use of Dakota to assess parametric uncertainties in a simple pipe flow problem. This problem is used to optimize performance of the uncertainty quantification strategy and to estimate computational requirements for assessments of complex geometries. A sensitivity analysis to three turbulent models was conducted for a turbulent flow in a single wire wrapped pin (THOR) geometry. Section 2 briefly describes the software tools used in this study and provides appropriate references. Section 3 presents the coupling interface between Dakota and a computational fluid dynamic (CFD) code (Nek5000 or STARCCM+), with details on the workflow, the scripts used for setting up the run, and the scripts used for post-processing the output files. In Section 4, the meshing methods used to generate the THORS and 7-pin bundle meshes are explained. Sections 5, 6 and 7 present numerical results

  2. Assessment of uncertainties in Neutron Multiplicity Counting

    International Nuclear Information System (INIS)

    Peerani, P.; Marin Ferrer, M.

    2008-01-01

    This paper describes a methodology for a complete and correct assessment of the errors coming from the uncertainty of each individual component on the final result. A general methodology accounting for all the main sources of error (both type-A and type-B) will be outlined. In order to better illustrate the method, a practical example applying it to the uncertainty estimation for a special case of multiplicity counter, the SNMC developed at JRC, will be given

  3. Uncertainties in risk assessment and decision making

    International Nuclear Information System (INIS)

    Starzec, Peter; Purucker, Tom; Stewart, Robert

    2008-02-01

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

  4. A review of uncertainty research in impact assessment

    International Nuclear Information System (INIS)

    Leung, Wanda; Noble, Bram; Gunn, Jill; Jaeger, Jochen A.G.

    2015-01-01

    This paper examines uncertainty research in Impact Assessment (IA) and the focus of attention of the IA scholarly literature. We do so by first exploring ‘outside’ the IA literature, identifying three main themes of uncertainty research, and then apply these themes to examine the focus of scholarly research on uncertainty ‘inside’ IA. Based on a search of the database Scopus, we identified 134 journal papers published between 1970 and 2013 that address uncertainty in IA, 75% of which were published since 2005. We found that 90% of IA research addressing uncertainty focused on uncertainty in the practice of IA, including uncertainty in impact predictions, models and managing environmental impacts. Notwithstanding early guidance on uncertainty treatment in IA from the 1980s, we found no common, underlying conceptual framework that was guiding research on uncertainty in IA practice. Considerably less attention, only 9% of papers, focused on uncertainty communication, disclosure and decision-making under uncertain conditions, the majority of which focused on the need to disclose uncertainties as opposed to providing guidance on how to do so and effectively use that information to inform decisions. Finally, research focused on theory building for explaining human behavior with respect to uncertainty avoidance constituted only 1% of the IA published literature. We suggest the need for further conceptual framework development for researchers focused on identifying and addressing uncertainty in IA practice; the need for guidance on how best to communicate uncertainties in practice, versus criticizing practitioners for not doing so; research that explores how best to interpret and use disclosures about uncertainty when making decisions about project approvals, and the implications of doing so; and academic theory building and exploring the utility of existing theories to better understand and explain uncertainty avoidance behavior in IA. - Highlights: • We

  5. A review of uncertainty research in impact assessment

    Energy Technology Data Exchange (ETDEWEB)

    Leung, Wanda, E-mail: wanda.leung@usask.ca [Department of Geography and Planning, University of Saskatchewan, 117 Science Place, Saskatoon, Saskatchewan S7N 5A5 (Canada); Noble, Bram, E-mail: b.noble@usask.ca [Department of Geography and Planning, School of Environment and Sustainability, University of Saskatchewan, 117 Science Place, Saskatoon, Saskatchewan S7N 5A5 (Canada); Gunn, Jill, E-mail: jill.gunn@usask.ca [Department of Geography and Planning, University of Saskatchewan, 117 Science Place, Saskatoon, Saskatchewan S7N 5A5 (Canada); Jaeger, Jochen A.G., E-mail: jochen.jaeger@concordia.ca [Department of Geography, Planning and Environment, Concordia University, 1455 de Maisonneuve W., Suite 1255, Montreal, Quebec H3G 1M8 (Canada); Loyola Sustainability Research Centre, Concordia University, 7141 Sherbrooke W., AD-502, Montreal, Quebec H4B 1R6 (Canada)

    2015-01-15

    This paper examines uncertainty research in Impact Assessment (IA) and the focus of attention of the IA scholarly literature. We do so by first exploring ‘outside’ the IA literature, identifying three main themes of uncertainty research, and then apply these themes to examine the focus of scholarly research on uncertainty ‘inside’ IA. Based on a search of the database Scopus, we identified 134 journal papers published between 1970 and 2013 that address uncertainty in IA, 75% of which were published since 2005. We found that 90% of IA research addressing uncertainty focused on uncertainty in the practice of IA, including uncertainty in impact predictions, models and managing environmental impacts. Notwithstanding early guidance on uncertainty treatment in IA from the 1980s, we found no common, underlying conceptual framework that was guiding research on uncertainty in IA practice. Considerably less attention, only 9% of papers, focused on uncertainty communication, disclosure and decision-making under uncertain conditions, the majority of which focused on the need to disclose uncertainties as opposed to providing guidance on how to do so and effectively use that information to inform decisions. Finally, research focused on theory building for explaining human behavior with respect to uncertainty avoidance constituted only 1% of the IA published literature. We suggest the need for further conceptual framework development for researchers focused on identifying and addressing uncertainty in IA practice; the need for guidance on how best to communicate uncertainties in practice, versus criticizing practitioners for not doing so; research that explores how best to interpret and use disclosures about uncertainty when making decisions about project approvals, and the implications of doing so; and academic theory building and exploring the utility of existing theories to better understand and explain uncertainty avoidance behavior in IA. - Highlights: • We

  6. Uncertainty quantification in flood risk assessment

    Science.gov (United States)

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

    2017-04-01

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

  7. Uncertainty and validation. Effect of model complexity on uncertainty estimates

    International Nuclear Information System (INIS)

    Elert, M.

    1996-09-01

    In the Model Complexity subgroup of BIOMOVS II, models of varying complexity have been applied to the problem of downward transport of radionuclides in soils. A scenario describing a case of surface contamination of a pasture soil was defined. Three different radionuclides with different environmental behavior and radioactive half-lives were considered: Cs-137, Sr-90 and I-129. The intention was to give a detailed specification of the parameters required by different kinds of model, together with reasonable values for the parameter uncertainty. A total of seven modelling teams participated in the study using 13 different models. Four of the modelling groups performed uncertainty calculations using nine different modelling approaches. The models used range in complexity from analytical solutions of a 2-box model using annual average data to numerical models coupling hydrology and transport using data varying on a daily basis. The complex models needed to consider all aspects of radionuclide transport in a soil with a variable hydrology are often impractical to use in safety assessments. Instead simpler models, often box models, are preferred. The comparison of predictions made with the complex models and the simple models for this scenario show that the predictions in many cases are very similar, e g in the predictions of the evolution of the root zone concentration. However, in other cases differences of many orders of magnitude can appear. One example is the prediction of the flux to the groundwater of radionuclides being transported through the soil column. Some issues that have come to focus in this study: There are large differences in the predicted soil hydrology and as a consequence also in the radionuclide transport, which suggests that there are large uncertainties in the calculation of effective precipitation and evapotranspiration. The approach used for modelling the water transport in the root zone has an impact on the predictions of the decline in root

  8. 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.

  9. 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

  10. Uncertainty and validation. Effect of model complexity on uncertainty estimates

    Energy Technology Data Exchange (ETDEWEB)

    Elert, M. [Kemakta Konsult AB, Stockholm (Sweden)] [ed.

    1996-09-01

    In the Model Complexity subgroup of BIOMOVS II, models of varying complexity have been applied to the problem of downward transport of radionuclides in soils. A scenario describing a case of surface contamination of a pasture soil was defined. Three different radionuclides with different environmental behavior and radioactive half-lives were considered: Cs-137, Sr-90 and I-129. The intention was to give a detailed specification of the parameters required by different kinds of model, together with reasonable values for the parameter uncertainty. A total of seven modelling teams participated in the study using 13 different models. Four of the modelling groups performed uncertainty calculations using nine different modelling approaches. The models used range in complexity from analytical solutions of a 2-box model using annual average data to numerical models coupling hydrology and transport using data varying on a daily basis. The complex models needed to consider all aspects of radionuclide transport in a soil with a variable hydrology are often impractical to use in safety assessments. Instead simpler models, often box models, are preferred. The comparison of predictions made with the complex models and the simple models for this scenario show that the predictions in many cases are very similar, e g in the predictions of the evolution of the root zone concentration. However, in other cases differences of many orders of magnitude can appear. One example is the prediction of the flux to the groundwater of radionuclides being transported through the soil column. Some issues that have come to focus in this study: There are large differences in the predicted soil hydrology and as a consequence also in the radionuclide transport, which suggests that there are large uncertainties in the calculation of effective precipitation and evapotranspiration. The approach used for modelling the water transport in the root zone has an impact on the predictions of the decline in root

  11. Assessing flood forecast uncertainty with fuzzy arithmetic

    Directory of Open Access Journals (Sweden)

    de Bruyn Bertrand

    2016-01-01

    Full Text Available Providing forecasts for flow rates and water levels during floods have to be associated with uncertainty estimates. The forecast sources of uncertainty are plural. For hydrological forecasts (rainfall-runoff performed using a deterministic hydrological model with basic physics, two main sources can be identified. The first obvious source is the forcing data: rainfall forecast data are supplied in real time by meteorological forecasting services to the Flood Forecasting Service within a range between a lowest and a highest predicted discharge. These two values define an uncertainty interval for the rainfall variable provided on a given watershed. The second source of uncertainty is related to the complexity of the modeled system (the catchment impacted by the hydro-meteorological phenomenon, the number of variables that may describe the problem and their spatial and time variability. The model simplifies the system by reducing the number of variables to a few parameters. Thus it contains an intrinsic uncertainty. This model uncertainty is assessed by comparing simulated and observed rates for a large number of hydro-meteorological events. We propose a method based on fuzzy arithmetic to estimate the possible range of flow rates (and levels of water making a forecast based on possible rainfalls provided by forcing and uncertainty model. The model uncertainty is here expressed as a range of possible values. Both rainfall and model uncertainties are combined with fuzzy arithmetic. This method allows to evaluate the prediction uncertainty range. The Flood Forecasting Service of Oise and Aisne rivers, in particular, monitors the upstream watershed of the Oise at Hirson. This watershed’s area is 310 km2. Its response time is about 10 hours. Several hydrological models are calibrated for flood forecasting in this watershed and use the rainfall forecast. This method presents the advantage to be easily implemented. Moreover, it permits to be carried out

  12. Assessing student understanding of measurement and uncertainty

    Science.gov (United States)

    Jirungnimitsakul, S.; Wattanakasiwich, P.

    2017-09-01

    The objectives of this study were to develop and assess student understanding of measurement and uncertainty. A test has been adapted and translated from the Laboratory Data Analysis Instrument (LDAI) test, consists of 25 questions focused on three topics including measures of central tendency, experimental errors and uncertainties, and fitting regression lines. The test was evaluated its content validity by three physics experts in teaching physics laboratory. In the pilot study, Thai LDAI was administered to 93 freshmen enrolled in a fundamental physics laboratory course. The final draft of the test was administered to three groups—45 freshmen taking fundamental physics laboratory, 16 sophomores taking intermediated physics laboratory and 21 juniors taking advanced physics laboratory at Chiang Mai University. As results, we found that the freshmen had difficulties in experimental errors and uncertainties. Most students had problems with fitting regression lines. These results will be used to improve teaching and learning physics laboratory for physics students in the department.

  13. 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.

  14. Uncertainty Assessments in Fast Neutron Activation Analysis

    International Nuclear Information System (INIS)

    W. D. James; R. Zeisler

    2000-01-01

    Fast neutron activation analysis (FNAA) carried out with the use of small accelerator-based neutron generators is routinely used for major/minor element determinations in industry, mineral and petroleum exploration, and to some extent in research. While the method shares many of the operational procedures and therefore errors inherent to conventional thermal neutron activation analysis, its unique implementation gives rise to additional specific concerns that can result in errors or increased uncertainties of measured quantities. The authors were involved in a recent effort to evaluate irreversible incorporation of oxygen into a standard reference material (SRM) by direct measurement of oxygen by FNAA. That project required determination of oxygen in bottles of the SRM stored in varying environmental conditions and a comparison of the results. We recognized the need to accurately describe the total uncertainty of the measurements to accurately characterize any differences in the resulting average concentrations. It is our intent here to discuss the breadth of potential parameters that have the potential to contribute to the random and nonrandom errors of the method and provide estimates of the magnitude of uncertainty introduced. In addition, we will discuss the steps taken in this recent FNAA project to control quality, assess the uncertainty of the measurements, and evaluate results based on the statistical reproducibility

  15. Subspace-based Inverse Uncertainty Quantification for Nuclear Data Assessment

    Energy Technology Data Exchange (ETDEWEB)

    Khuwaileh, B.A., E-mail: bakhuwai@ncsu.edu; Abdel-Khalik, H.S.

    2015-01-15

    Safety analysis and design optimization depend on the accurate prediction of various reactor attributes. Predictions can be enhanced by reducing the uncertainty associated with the attributes of interest. An inverse problem can be defined and solved to assess the sources of uncertainty, and experimental effort can be subsequently directed to further improve the uncertainty associated with these sources. In this work a subspace-based algorithm for inverse sensitivity/uncertainty quantification (IS/UQ) has been developed to enable analysts account for all sources of nuclear data uncertainties in support of target accuracy assessment-type analysis. An approximate analytical solution of the optimization problem is used to guide the search for the dominant uncertainty subspace. By limiting the search to a subspace, the degrees of freedom available for the optimization search are significantly reduced. A quarter PWR fuel assembly is modeled and the accuracy of the multiplication factor and the fission reaction rate are used as reactor attributes whose uncertainties are to be reduced. Numerical experiments are used to demonstrate the computational efficiency of the proposed algorithm. Our ongoing work is focusing on extending the proposed algorithm to account for various forms of feedback, e.g., thermal-hydraulics and depletion effects.

  16. Uncertainty Assessment: What Good Does it Do? (Invited)

    Science.gov (United States)

    Oreskes, N.; Lewandowsky, S.

    2013-12-01

    The scientific community has devoted considerable time and energy to understanding, quantifying and articulating the uncertainties related to anthropogenic climate change. However, informed decision-making and good public policy arguably rely far more on a central core of understanding of matters that are scientifically well established than on detailed understanding and articulation of all relevant uncertainties. Advocates of vaccination, for example, stress its overall efficacy in preventing morbidity and mortality--not the uncertainties over how long the protective effects last. Advocates for colonoscopy for cancer screening stress its capacity to detect polyps before they become cancerous, with relatively little attention paid to the fact that many, if not most, polyps, would not become cancerous even if left unremoved. So why has the climate science community spent so much time focused on uncertainty? One reason, of course, is that articulation of uncertainty is a normal and appropriate part of scientific work. However, we argue that there is another reason that involves the pressure that the scientific community has experienced from individuals and groups promoting doubt about anthropogenic climate change. Specifically, doubt-mongering groups focus public attention on scientific uncertainty as a means to undermine scientific claims, equating uncertainty with untruth. Scientists inadvertently validate these arguments by agreeing that much of the science is uncertain, and thus seemingly implying that our knowledge is insecure. The problem goes further, as the scientific community attempts to articulate more clearly, and reduce, those uncertainties, thus, seemingly further agreeing that the knowledge base is insufficient to warrant public and governmental action. We refer to this effect as 'seepage,' as the effects of doubt-mongering seep into the scientific community and the scientific agenda, despite the fact that addressing these concerns does little to alter

  17. Treatment of uncertainty in low-level waste performance assessment

    International Nuclear Information System (INIS)

    Kozak, M.W.; Olague, N.E.; Gallegos, D.P.; Rao, R.R.

    1991-01-01

    Uncertainties arise from a number of different sources in low-level waste performance assessment. In this paper the types of uncertainty are reviewed, and existing methods for quantifying and reducing each type of uncertainty are discussed. These approaches are examined in the context of the current low-level radioactive waste regulatory performance objectives, which are deterministic. The types of uncertainty discussed in this paper are model uncertainty, uncertainty about future conditions, and parameter uncertainty. The advantages and disadvantages of available methods for addressing uncertainty in low-level waste performance assessment are presented. 25 refs

  18. Uncertainty and validation. Effect of user interpretation on uncertainty estimates

    International Nuclear Information System (INIS)

    Kirchner, G.; Peterson, R.

    1996-11-01

    dependent behaviour of a model endpoint may be disguised as an accurate time integrated prediction when compared to the time-integrated observation. Agreement of predictions with observed concentrations in milk was often the result of compensatory errors. Although the effect of the user's assumptions on uncertainties was expected to be important, the wide variability of the predictions came as a surprise. A recommendation for assessments would be that at least two users, perhaps even with the same model, should calculate predictions before any decisions are made. Choices of parameter values and other assumptions should be made through a process of expert elicitation

  19. Uncertainty and validation. Effect of user interpretation on uncertainty estimates

    Energy Technology Data Exchange (ETDEWEB)

    Kirchner, G. [Univ. of Bremen (Germany); Peterson, R. [AECL, Chalk River, ON (Canada)] [and others

    1996-11-01

    time dependent behaviour of a model endpoint may be disguised as an accurate time integrated prediction when compared to the time-integrated observation. Agreement of predictions with observed concentrations in milk was often the result of compensatory errors. Although the effect of the user's assumptions on uncertainties was expected to be important, the wide variability of the predictions came as a surprise. A recommendation for assessments would be that at least two users, perhaps even with the same model, should calculate predictions before any decisions are made. Choices of parameter values and other assumptions should be made through a process of expert elicitation.

  20. Risk assessment under deep uncertainty: A methodological comparison

    International Nuclear Information System (INIS)

    Shortridge, Julie; Aven, Terje; Guikema, Seth

    2017-01-01

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

  1. 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.

  2. Effects of Uncertainty and Spatial Variability on Seepage into Drifts in the Yucca Mountain Total system Performance Assessment Model

    International Nuclear Information System (INIS)

    Kalinich, D. A.; Wilson, M. L.

    2001-01-01

    Seepage into the repository drifts is an important factor in total-system performance. Uncertainty and spatial variability are considered in the seepage calculations. The base-case results show 13.6% of the waste packages (WPs) have seepage. For 5th percentile uncertainty, 4.5% of the WPs have seepage and the seepage flow decreased by a factor of 2. For 95th percentile uncertainty, 21.5% of the WPs have seepage and the seepage flow increased by a factor of 2. Ignoring spatial variability resulted in seepage on 100% of the WPs, with a factor of 3 increase in the seepage flow

  3. 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

  4. Probabilistic Radiological Performance Assessment Modeling and Uncertainty

    Science.gov (United States)

    Tauxe, J.

    2004-12-01

    A generic probabilistic radiological Performance Assessment (PA) model is presented. The model, built using the GoldSim systems simulation software platform, concerns contaminant transport and dose estimation in support of decision making with uncertainty. Both the U.S. Nuclear Regulatory Commission (NRC) and the U.S. Department of Energy (DOE) require assessments of potential future risk to human receptors of disposal of LLW. Commercially operated LLW disposal facilities are licensed by the NRC (or agreement states), and the DOE operates such facilities for disposal of DOE-generated LLW. The type of PA model presented is probabilistic in nature, and hence reflects the current state of knowledge about the site by using probability distributions to capture what is expected (central tendency or average) and the uncertainty (e.g., standard deviation) associated with input parameters, and propagating through the model to arrive at output distributions that reflect expected performance and the overall uncertainty in the system. Estimates of contaminant release rates, concentrations in environmental media, and resulting doses to human receptors well into the future are made by running the model in Monte Carlo fashion, with each realization representing a possible combination of input parameter values. Statistical summaries of the results can be compared to regulatory performance objectives, and decision makers are better informed of the inherently uncertain aspects of the model which supports their decision-making. While this information may make some regulators uncomfortable, they must realize that uncertainties which were hidden in a deterministic analysis are revealed in a probabilistic analysis, and the chance of making a correct decision is now known rather than hoped for. The model includes many typical features and processes that would be part of a PA, but is entirely fictitious. This does not represent any particular site and is meant to be a generic example. A

  5. Confronting Uncertainty in Life Cycle Assessment Used for Decision Support

    DEFF Research Database (Denmark)

    Herrmann, Ivan Tengbjerg; Hauschild, Michael Zwicky; Sohn, Michael D.

    2014-01-01

    the decision maker (DM) in making the best possible choice for the environment. At present, some DMs do not trust the LCA to be a reliable decisionsupport tool—often because DMs consider the uncertainty of an LCA to be too large. The standard evaluation of uncertainty in LCAs is an ex-post approach that can...... regarding which type of LCA study to employ for the decision context at hand. This taxonomy enables the derivation of an LCA classification matrix to clearly identify and communicate the type of a given LCA. By relating the LCA classification matrix to statistical principles, we can also rank the different......The aim of this article is to help confront uncertainty in life cycle assessments (LCAs) used for decision support. LCAs offer a quantitative approach to assess environmental effects of products, technologies, and services and are conducted by an LCA practitioner or analyst (AN) to support...

  6. Methodology for qualitative uncertainty assessment of climate impact indicators

    Science.gov (United States)

    Otto, Juliane; Keup-Thiel, Elke; Rechid, Diana; Hänsler, Andreas; Pfeifer, Susanne; Roth, Ellinor; Jacob, Daniela

    2016-04-01

    The FP7 project "Climate Information Portal for Copernicus" (CLIPC) is developing an integrated platform of climate data services to provide a single point of access for authoritative scientific information on climate change and climate change impacts. In this project, the Climate Service Center Germany (GERICS) has been in charge of the development of a methodology on how to assess the uncertainties related to climate impact indicators. Existing climate data portals mainly treat the uncertainties in two ways: Either they provide generic guidance and/or express with statistical measures the quantifiable fraction of the uncertainty. However, none of the climate data portals give the users a qualitative guidance how confident they can be in the validity of the displayed data. The need for such guidance was identified in CLIPC user consultations. Therefore, we aim to provide an uncertainty assessment that provides the users with climate impact indicator-specific guidance on the degree to which they can trust the outcome. We will present an approach that provides information on the importance of different sources of uncertainties associated with a specific climate impact indicator and how these sources affect the overall 'degree of confidence' of this respective indicator. To meet users requirements in the effective communication of uncertainties, their feedback has been involved during the development process of the methodology. Assessing and visualising the quantitative component of uncertainty is part of the qualitative guidance. As visual analysis method, we apply the Climate Signal Maps (Pfeifer et al. 2015), which highlight only those areas with robust climate change signals. Here, robustness is defined as a combination of model agreement and the significance of the individual model projections. Reference Pfeifer, S., Bülow, K., Gobiet, A., Hänsler, A., Mudelsee, M., Otto, J., Rechid, D., Teichmann, C. and Jacob, D.: Robustness of Ensemble Climate Projections

  7. Improved method for considering PMU’s uncertainty and its effect on real-time stability assessment methods based on Thevenin equivalent

    DEFF Research Database (Denmark)

    Perez, Angel; Jóhannsson, Hjörtur; Østergaard, Jacob

    2015-01-01

    This article characterizes experimentally the relation between phase and magnitude error from Phasor Measurement Units (PMU) in steady state and study its effect on real-time stability assessment methods. This is achieved by a set of laboratory tests applied to four different devices, where...... a bivariate Gaussian mixture distribution was used to represent the error, obtained experimentally, and later include it in the synthesized PMU measurement using the Monte Carlo Method. Two models for including uncertainty are compared and the results show that taking into account the correlation between...

  8. Assessing Power System Stability Following Load Changes and Considering Uncertainty

    Directory of Open Access Journals (Sweden)

    D. V. Ngo

    2018-04-01

    Full Text Available An increase in load capacity during the operation of a power system usually causes voltage drop and leads to system instability, so it is necessary to monitor the effect of load changes. This article presents a method of assessing the power system stability according to the load node capacity considering uncertainty factors in the system. The proposed approach can be applied to large-scale power systems for voltage stability assessment in real-time.

  9. Effect of activation cross section uncertainties in the assessment of primary damage for MFE/IFE low-activation steels irradiated in IFMIF

    International Nuclear Information System (INIS)

    Cabellos, O.; Sanz, J.; Garcia-Herranz, N.; Otero, B.

    2009-01-01

    The present study is mainly aimed to provide the primary damage (displacements per atom, generation of solid transmutants and gas production rates) of structural materials irradiated in the high and medium flux test modules of the International Fusion Materials Irradiation Facility (IFMIF). We have investigated if the change of the composition during the irradiation time has effect on the prediction of the atomic displacements. The effect of the activation cross section uncertainties in the assessment of both solid transmutants and hydrogen and helium production is also analyzed. The results are provided element-by-element, so that the primary damage of any material irradiated in such neutron environments can be easily assessed; in this paper, we have predicted the primary damage of the low activation steel Eurofer.

  10. Effect of activation cross section uncertainties in the assessment of primary damage for MFE/IFE low-activation steels irradiated in IFMIF

    Energy Technology Data Exchange (ETDEWEB)

    Cabellos, O. [Instituto de Fusion Nuclear, Universidad Politecnica de Madrid (UPM), C/Jose Gutierrez Abascal, n2, 28006 Madrid (Spain); Dept. de Ingenieria Nuclear, Universidad Politecnica de Madrid, 28006 Madrid (Spain)], E-mail: cabellos@din.upm.es; Sanz, J. [Instituto de Fusion Nuclear, Universidad Politecnica de Madrid (UPM), C/Jose Gutierrez Abascal, n2, 28006 Madrid (Spain); Dept. de Ingenieria Energetica, Universidad Nacional de Educacion a Distancia, 28045 Madrid (Spain); Garcia-Herranz, N. [Instituto de Fusion Nuclear, Universidad Politecnica de Madrid (UPM), C/Jose Gutierrez Abascal, n2, 28006 Madrid (Spain); Dept. de Ingenieria Nuclear, Universidad Politecnica de Madrid, 28006 Madrid (Spain); Otero, B. [Dept. de Ingenieria Nuclear, Universidad Politecnica de Madrid, 28006 Madrid (Spain)

    2009-04-30

    The present study is mainly aimed to provide the primary damage (displacements per atom, generation of solid transmutants and gas production rates) of structural materials irradiated in the high and medium flux test modules of the International Fusion Materials Irradiation Facility (IFMIF). We have investigated if the change of the composition during the irradiation time has effect on the prediction of the atomic displacements. The effect of the activation cross section uncertainties in the assessment of both solid transmutants and hydrogen and helium production is also analyzed. The results are provided element-by-element, so that the primary damage of any material irradiated in such neutron environments can be easily assessed; in this paper, we have predicted the primary damage of the low activation steel Eurofer.

  11. Notes on the effect of dose uncertainty

    International Nuclear Information System (INIS)

    Morris, M.D.

    1987-01-01

    The apparent dose-response relationship between amount of exposure to acute radiation and level of mortality in humans is affected by uncertainties in the dose values. It is apparent that one of the greatest concerns regarding the human data from Hiroshima and Nagasaki is the unexpectedly shallow slope of the dose response curve. This may be partially explained by uncertainty in the dose estimates. Some potential effects of dose uncertainty on the apparent dose-response relationship are demonstrated

  12. Uncertainty estimation in nuclear power plant probabilistic safety assessment

    International Nuclear Information System (INIS)

    Guarro, S.B.; Cummings, G.E.

    1989-01-01

    Probabilistic Risk Assessment (PRA) was introduced in the nuclear industry and the nuclear regulatory process in 1975 with the publication of the Reactor Safety Study by the U.S. Nuclear Regulatory Commission. Almost fifteen years later, the state-of-the-art in this field has been expanded and sharpened in many areas, and about thirty-five plant-specific PRAs (Probabilistic Risk Assessments) have been performed by the nuclear utility companies or by the U.S. Nuclear Regulatory commission. Among the areas where the most evident progress has been made in PRA and PSA (Probabilistic Safety Assessment, as these studies are more commonly referred to in the international community outside the U.S.) is the development of a consistent framework for the identification of sources of uncertainty and the estimation of their magnitude as it impacts various risk measures. Techniques to propagate uncertainty in reliability data through the risk models and display its effect on the top level risk estimates were developed in the early PRAs. The Seismic Safety Margin Research Program (SSMRP) study was the first major risk study to develop an approach to deal explicitly with uncertainty in risk estimates introduced not only by uncertainty in component reliability data, but by the incomplete state of knowledge of the assessor(s) with regard to basic phenomena that may trigger and drive a severe accident. More recently NUREG-1150, another major study of reactor risk sponsored by the NRC, has expanded risk uncertainty estimation and analysis into the realm of model uncertainty related to the relatively poorly known post-core-melt phenomena which determine the behavior of the molten core and of the rector containment structures

  13. Coping with uncertainty in environmental impact assessments: Open techniques

    NARCIS (Netherlands)

    Chivatá Cárdenas, Ibsen; Halman, Johannes I.M.

    2016-01-01

    Uncertainty is virtually unavoidable in environmental impact assessments (EIAs). From the literature related to treating and managing uncertainty, we have identified specific techniques for coping with uncertainty in EIAs. Here, we have focused on basic steps in the decision-making process that take

  14. Uncertainty Assessment in Urban Storm Water Drainage Modelling

    DEFF Research Database (Denmark)

    Thorndahl, Søren

    The object of this paper is to make an overall description of the author's PhD study, concerning uncertainties in numerical urban storm water drainage models. Initially an uncertainty localization and assessment of model inputs and parameters as well as uncertainties caused by different model...

  15. 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

  16. 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.)

  17. Potential effects of organizational uncertainty on safety

    International Nuclear Information System (INIS)

    Durbin, N.E.; Lekberg, A.; Melber, B.D.

    2001-12-01

    When organizations face significant change - reorganization, mergers, acquisitions, down sizing, plant closures or decommissioning - both the organizations and the workers in those organizations experience significant uncertainty about the future. This uncertainty affects the organization and the people working in the organization - adversely affecting morale, reducing concentration on safe operations, and resulting in the loss of key staff. Hence, organizations, particularly those using high risk technologies, which are facing significant change need to consider and plan for the effects of organizational uncertainty on safety - as well as planning for other consequences of change - technical, economic, emotional, and productivity related. This paper reviews some of what is known about the effects of uncertainty on organizations and individuals, discusses the potential consequences of uncertainty on organizational and individual behavior, and presents some of the implications for safety professionals

  18. Potential effects of organizational uncertainty on safety

    Energy Technology Data Exchange (ETDEWEB)

    Durbin, N.E. [MPD Consulting Group, Kirkland, WA (United States); Lekberg, A. [Swedish Nuclear Power Inspectorate, Stockholm (Sweden); Melber, B.D. [Melber Consulting, Seattle WA (United States)

    2001-12-01

    When organizations face significant change - reorganization, mergers, acquisitions, down sizing, plant closures or decommissioning - both the organizations and the workers in those organizations experience significant uncertainty about the future. This uncertainty affects the organization and the people working in the organization - adversely affecting morale, reducing concentration on safe operations, and resulting in the loss of key staff. Hence, organizations, particularly those using high risk technologies, which are facing significant change need to consider and plan for the effects of organizational uncertainty on safety - as well as planning for other consequences of change - technical, economic, emotional, and productivity related. This paper reviews some of what is known about the effects of uncertainty on organizations and individuals, discusses the potential consequences of uncertainty on organizational and individual behavior, and presents some of the implications for safety professionals.

  19. Assessing measurement uncertainty in meteorology in urban environments

    International Nuclear Information System (INIS)

    Curci, S; Lavecchia, C; Frustaci, G; Pilati, S; Paganelli, C; Paolini, R

    2017-01-01

    Measurement uncertainty in meteorology has been addressed in a number of recent projects. In urban environments, uncertainty is also affected by local effects which are more difficult to deal with than for synoptic stations. In Italy, beginning in 2010, an urban meteorological network (Climate Network ® ) was designed, set up and managed at national level according to high metrological standards and homogeneity criteria to support energy applications. The availability of such a high-quality operative automatic weather station network represents an opportunity to investigate the effects of station siting and sensor exposure and to estimate the related measurement uncertainty. An extended metadata set was established for the stations in Milan, including siting and exposure details. Statistical analysis on an almost 3-year-long operational period assessed network homogeneity, quality and reliability. Deviations from reference mean values were then evaluated in selected low-gradient local weather situations in order to investigate siting and exposure effects. In this paper the methodology is depicted and preliminary results of its application to air temperature discussed; this allowed the setting of an upper limit of 1 °C for the added measurement uncertainty at the top of the urban canopy layer. (paper)

  20. Assessing measurement uncertainty in meteorology in urban environments

    Science.gov (United States)

    Curci, S.; Lavecchia, C.; Frustaci, G.; Paolini, R.; Pilati, S.; Paganelli, C.

    2017-10-01

    Measurement uncertainty in meteorology has been addressed in a number of recent projects. In urban environments, uncertainty is also affected by local effects which are more difficult to deal with than for synoptic stations. In Italy, beginning in 2010, an urban meteorological network (Climate Network®) was designed, set up and managed at national level according to high metrological standards and homogeneity criteria to support energy applications. The availability of such a high-quality operative automatic weather station network represents an opportunity to investigate the effects of station siting and sensor exposure and to estimate the related measurement uncertainty. An extended metadata set was established for the stations in Milan, including siting and exposure details. Statistical analysis on an almost 3-year-long operational period assessed network homogeneity, quality and reliability. Deviations from reference mean values were then evaluated in selected low-gradient local weather situations in order to investigate siting and exposure effects. In this paper the methodology is depicted and preliminary results of its application to air temperature discussed; this allowed the setting of an upper limit of 1 °C for the added measurement uncertainty at the top of the urban canopy layer.

  1. 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

  2. Enlarged level-1 PSA in regard to assessment of cross-cutting effects of hazards and consideration of their uncertainties for a KONVOI type PWR reference plant

    International Nuclear Information System (INIS)

    Haider, C.; Hofer, E.; Kloos, M.; Kuntze, W.; Liemersdorf, H.; Roewekamp, M.; Schwinges, B.; Tuerschmann, M.; Brenig, H.W.; Sommerfeld, H.

    2001-01-01

    In the frame of supporting BMU regarding generic questions concerning probabilistic safety analyses for nuclear power plants as well as regarding evaluation of nuclear specific standards and guidelines the significant contributions to damage states resulting from plant internal and external hazards had to be estimated for a German Konvoi type PWR reference plant. Furthermore, the suitability of the available methods for assessing these hazards should be checked. In the report presented hereafter, only the plant internal hazard Fire out of all the hazards to be considered was probabilistically analysed in detail First of all, screening analyses were carried out for identifying relevant plant areas and to assess their respective efficiency for a proper selection procedure. For a selected, plant area identified to be relevant (area of the cable distributions inside the reactor containment) an indepth analysis was performed. This analysis included all the steps of the probabilistic assessment, starting from the estimation of the fire occurrence frequency, followed by investigations on the fire effects and fire propagation, up to the determination of the fire induced failure probabilities of safety related equipment including the consequences on systems. In addition, the analyses contained particular uncertainty and sensitivity studies, for which aleatoric and epistemic uncertainties were distinguished. As a result of the screening analyses as well as of the in-depth investigations regarding the fire hazard, no significant contributions for the total frequencies for system, core, or plant damage states have been found. In this context, it has to be noticed that the study presented hereafter does not cover a complete fire PSA. With respect to assessing the available methods it has been found that improvements concerning the screening process as well as concerning the probabilistic fire event tree analyses are necessary. With regard to further hazards, a site specific

  3. Uncertainties

    Indian Academy of Sciences (India)

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

  4. Reliability assessment of complex electromechanical systems under epistemic uncertainty

    International Nuclear Information System (INIS)

    Mi, Jinhua; Li, Yan-Feng; Yang, Yuan-Jian; Peng, Weiwen; Huang, Hong-Zhong

    2016-01-01

    The appearance of macro-engineering and mega-project have led to the increasing complexity of modern electromechanical systems (EMSs). The complexity of the system structure and failure mechanism makes it more difficult for reliability assessment of these systems. Uncertainty, dynamic and nonlinearity characteristics always exist in engineering systems due to the complexity introduced by the changing environments, lack of data and random interference. This paper presents a comprehensive study on the reliability assessment of complex systems. In view of the dynamic characteristics within the system, it makes use of the advantages of the dynamic fault tree (DFT) for characterizing system behaviors. The lifetime of system units can be expressed as bounded closed intervals by incorporating field failures, test data and design expertize. Then the coefficient of variation (COV) method is employed to estimate the parameters of life distributions. An extended probability-box (P-Box) is proposed to convey the present of epistemic uncertainty induced by the incomplete information about the data. By mapping the DFT into an equivalent Bayesian network (BN), relevant reliability parameters and indexes have been calculated. Furthermore, the Monte Carlo (MC) simulation method is utilized to compute the DFT model with consideration of system replacement policy. The results show that this integrated approach is more flexible and effective for assessing the reliability of complex dynamic systems. - Highlights: • A comprehensive study on the reliability assessment of complex system is presented. • An extended probability-box is proposed to convey the present of epistemic uncertainty. • The dynamic fault tree model is built. • Bayesian network and Monte Carlo simulation methods are used. • The reliability assessment of a complex electromechanical system is performed.

  5. Uncertainty on faecal analysis on dose assessment

    Energy Technology Data Exchange (ETDEWEB)

    Juliao, Ligia M.Q.C.; Melo, Dunstana R.; Sousa, Wanderson de O.; Santos, Maristela S.; Fernandes, Paulo Cesar P. [Instituto de Radioprotecao e Dosimetria, Comissao Nacional de Energia Nuclear, Av. Salvador Allende s/n. Via 9, Recreio, CEP 22780-160, Rio de Janeiro, RJ (Brazil)

    2007-07-01

    Monitoring programmes for internal dose assessment may need to have a combination of bioassay techniques, e.g. urine and faecal analysis, especially in workplaces where compounds of different solubilities are handled and also in cases of accidental intakes. Faecal analysis may be an important data for assessment of committed effective dose due to exposure to insoluble compounds, since the activity excreted by urine may not be detectable, unless a very sensitive measurement system is available. This paper discusses the variability of the daily faecal excretion based on data from just one daily collection; collection during three consecutive days: samples analysed individually and samples analysed as a pool. The results suggest that just 1 d collection is not appropriate for dose assessment, since the 24 h uranium excretion may vary by a factor of 40. On the basis of this analysis, the recommendation should be faecal collection during three consecutive days, and samples analysed as a pool, it is more economic and faster. (authors)

  6. Assessing framing of uncertainties in water management practice

    NARCIS (Netherlands)

    Isendahl, N.; Dewulf, A.; Brugnach, M.; Francois, G.; Möllenkamp, S.; Pahl-Wostl, C.

    2009-01-01

    Dealing with uncertainties in water management is an important issue and is one which will only increase in light of global changes, particularly climate change. So far, uncertainties in water management have mostly been assessed from a scientific point of view, and in quantitative terms. In this

  7. Avoiding climate change uncertainties in Strategic Environmental Assessment

    DEFF Research Database (Denmark)

    Larsen, Sanne Vammen; Kørnøv, Lone; Driscoll, Patrick Arthur

    2013-01-01

    This article is concerned with how Strategic Environmental Assessment (SEA) practice handles climate change uncertainties within the Danish planning system. First, a hypothetical model is set up for how uncertainty is handled and not handled in decision-making. The model incorporates the strategies...

  8. Dealing with uncertainties in environmental burden of disease assessment

    Directory of Open Access Journals (Sweden)

    van der Sluijs Jeroen P

    2009-04-01

    Full Text Available Abstract Disability Adjusted Life Years (DALYs combine the number of people affected by disease or mortality in a population and the duration and severity of their condition into one number. The environmental burden of disease is the number of DALYs that can be attributed to environmental factors. Environmental burden of disease estimates enable policy makers to evaluate, compare and prioritize dissimilar environmental health problems or interventions. These estimates often have various uncertainties and assumptions which are not always made explicit. Besides statistical uncertainty in input data and parameters – which is commonly addressed – a variety of other types of uncertainties may substantially influence the results of the assessment. We have reviewed how different types of uncertainties affect environmental burden of disease assessments, and we give suggestions as to how researchers could address these uncertainties. We propose the use of an uncertainty typology to identify and characterize uncertainties. Finally, we argue that uncertainties need to be identified, assessed, reported and interpreted in order for assessment results to adequately support decision making.

  9. 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.

  10. Uncertainty assessment for accelerator-driven systems

    International Nuclear Information System (INIS)

    Finck, P. J.; Gomes, I.; Micklich, B.; Palmiotti, G.

    1999-01-01

    The concept of a subcritical system driven by an external source of neutrons provided by an accelerator ADS (Accelerator Driver System) has been recently revived and is becoming more popular in the world technical community with active programs in Europe, Russia, Japan, and the U.S. A general consensus has been reached in adopting for the subcritical component a fast spectrum liquid metal cooled configuration. Both a lead-bismuth eutectic, sodium and gas are being considered as a coolant; each has advantages and disadvantages. The major expected advantage is that subcriticality avoids reactivity induced transients. The potentially large subcriticality margin also should allow for the introduction of very significant quantities of waste products (minor Actinides and Fission Products) which negatively impact the safety characteristics of standard cores. In the U.S. these arguments are the basis for the development of the Accelerator Transmutation of Waste (ATW), which has significant potential in reducing nuclear waste levels. Up to now, neutronic calculations have not attached uncertainties on the values of the main nuclear integral parameters that characterize the system. Many of these parameters (e.g., degree of subcriticality) are crucial to demonstrate the validity and feasibility of this concept. In this paper we will consider uncertainties related to nuclear data only. The present knowledge of the cross sections of many isotopes that are not usually utilized in existing reactors (like Bi, Pb-207, Pb-208, and also Minor Actinides and Fission Products) suggests that uncertainties in the integral parameters will be significantly larger than for conventional reactor systems, and this raises concerns on the neutronic performance of those systems

  11. 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.

  12. Uncertainties in life cycle assessment of waste management systems

    DEFF Research Database (Denmark)

    Clavreul, Julie; Christensen, Thomas Højlund

    2011-01-01

    Life cycle assessment has been used to assess environmental performances of waste management systems in many studies. The uncertainties inherent to its results are often pointed out but not always quantified, which should be the case to ensure a good decisionmaking process. This paper proposes...... a method to assess all parameter uncertainties and quantify the overall uncertainty of the assessment. The method is exemplified in a case study, where the goal is to determine if anaerobic digestion of organic waste is more beneficial than incineration in Denmark, considering only the impact on global...... warming. The sensitivity analysis pointed out ten parameters particularly highly influencing the result of the study. In the uncertainty analysis, the distributions of these ten parameters were used in a Monte Carlo analysis, which concluded that incineration appeared more favourable than anaerobic...

  13. Uncertainty of a hydrological climate change impact assessment - Is it really all about climate uncertainty?

    Science.gov (United States)

    Honti, Mark; Reichert, Peter; Scheidegger, Andreas; Stamm, Christian

    2013-04-01

    Climate change impact assessments have become more and more popular in hydrology since the middle 1980's with another boost after the publication of the IPCC AR4 report. During hundreds of impact studies a quasi-standard methodology emerged, which is mainly shaped by the growing public demand for predicting how water resources management or flood protection should change in the close future. The ``standard'' workflow considers future climate under a specific IPCC emission scenario simulated by global circulation models (GCMs), possibly downscaled by a regional climate model (RCM) and/or a stochastic weather generator. The output from the climate models is typically corrected for bias before feeding it into a calibrated hydrological model, which is run on the past and future meteorological data to analyse the impacts of climate change on the hydrological indicators of interest. The impact predictions are as uncertain as any forecast that tries to describe the behaviour of an extremely complex system decades into the future. Future climate predictions are uncertain due to the scenario uncertainty and the GCM model uncertainty that is obvious on finer resolution than continental scale. Like in any hierarchical model system, uncertainty propagates through the descendant components. Downscaling increases uncertainty with the deficiencies of RCMs and/or weather generators. Bias correction adds a strong deterministic shift to the input data. Finally the predictive uncertainty of the hydrological model ends the cascade that leads to the total uncertainty of the hydrological impact assessment. There is an emerging consensus between many studies on the relative importance of the different uncertainty sources. The prevailing perception is that GCM uncertainty dominates hydrological impact studies. There are only few studies, which found that the predictive uncertainty of hydrological models can be in the same range or even larger than climatic uncertainty. We carried out a

  14. 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)

  15. Quantifying uncertainties in wind energy assessment

    Science.gov (United States)

    Patlakas, Platon; Galanis, George; Kallos, George

    2015-04-01

    The constant rise of wind energy production and the subsequent penetration in global energy markets during the last decades resulted in new sites selection with various types of problems. Such problems arise due to the variability and the uncertainty of wind speed. The study of the wind speed distribution lower and upper tail may support the quantification of these uncertainties. Such approaches focused on extreme wind conditions or periods below the energy production threshold are necessary for a better management of operations. Towards this direction, different methodologies are presented for the credible evaluation of potential non-frequent/extreme values for these environmental conditions. The approaches used, take into consideration the structural design of the wind turbines according to their lifespan, the turbine failures, the time needed for repairing as well as the energy production distribution. In this work, a multi-parametric approach for studying extreme wind speed values will be discussed based on tools of Extreme Value Theory. In particular, the study is focused on extreme wind speed return periods and the persistence of no energy production based on a weather modeling system/hind cast/10-year dataset. More specifically, two methods (Annual Maxima and Peaks Over Threshold) were used for the estimation of extreme wind speeds and their recurrence intervals. Additionally, two different methodologies (intensity given duration and duration given intensity, both based on Annual Maxima method) were implied to calculate the extreme events duration, combined with their intensity as well as the event frequency. The obtained results prove that the proposed approaches converge, at least on the main findings, for each case. It is also remarkable that, despite the moderate wind speed climate of the area, several consequent days of no energy production are observed.

  16. Uncertainty Estimation Cheat Sheet for Probabilistic Risk Assessment

    Science.gov (United States)

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

    2017-01-01

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

  17. Analytical Propagation of Uncertainty in Life Cycle Assessment Using Matrix Formulation

    DEFF Research Database (Denmark)

    Imbeault-Tétreault, Hugues; Jolliet, Olivier; Deschênes, Louise

    2013-01-01

    with Monte Carlo results. The sensitivity and contribution of input parameters to output uncertainty were also analytically calculated. This article outlines an uncertainty analysis of the comparison between two case study scenarios. We conclude that the analytical method provides a good approximation...... on uncertainty calculation. This article shows the importance of the analytical method in uncertainty calculation, which could lead to a more complete uncertainty analysis in LCA practice....... uncertainty assessment is not a regular step in LCA. An analytical approach based on Taylor series expansion constitutes an effective means to overcome the drawbacks of the Monte Carlo method. This project aimed to test the approach on a real case study, and the resulting analytical uncertainty was compared...

  18. 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

  19. Avoiding climate change uncertainties in Strategic Environmental Assessment

    Energy Technology Data Exchange (ETDEWEB)

    Larsen, Sanne Vammen, E-mail: sannevl@plan.aau.dk [The Danish Centre for Environmental Assessment, Aalborg University-Copenhagen, A.C. Meyers Vænge 15, 2450 København SV (Denmark); Kørnøv, Lone, E-mail: lonek@plan.aau.dk [The Danish Centre for Environmental Assessment, Aalborg University, Skibbrogade 5, 1. Sal, 9000 Aalborg (Denmark); Driscoll, Patrick, E-mail: patrick@plan.aau.dk [The Danish Centre for Environmental Assessment, Aalborg University-Copenhagen, A.C. Meyers Vænge 15, 2450 København SV (Denmark)

    2013-11-15

    This article is concerned with how Strategic Environmental Assessment (SEA) practice handles climate change uncertainties within the Danish planning system. First, a hypothetical model is set up for how uncertainty is handled and not handled in decision-making. The model incorporates the strategies ‘reduction’ and ‘resilience’, ‘denying’, ‘ignoring’ and ‘postponing’. Second, 151 Danish SEAs are analysed with a focus on the extent to which climate change uncertainties are acknowledged and presented, and the empirical findings are discussed in relation to the model. The findings indicate that despite incentives to do so, climate change uncertainties were systematically avoided or downplayed in all but 5 of the 151 SEAs that were reviewed. Finally, two possible explanatory mechanisms are proposed to explain this: conflict avoidance and a need to quantify uncertainty.

  20. Avoiding climate change uncertainties in Strategic Environmental Assessment

    International Nuclear Information System (INIS)

    Larsen, Sanne Vammen; Kørnøv, Lone; Driscoll, Patrick

    2013-01-01

    This article is concerned with how Strategic Environmental Assessment (SEA) practice handles climate change uncertainties within the Danish planning system. First, a hypothetical model is set up for how uncertainty is handled and not handled in decision-making. The model incorporates the strategies ‘reduction’ and ‘resilience’, ‘denying’, ‘ignoring’ and ‘postponing’. Second, 151 Danish SEAs are analysed with a focus on the extent to which climate change uncertainties are acknowledged and presented, and the empirical findings are discussed in relation to the model. The findings indicate that despite incentives to do so, climate change uncertainties were systematically avoided or downplayed in all but 5 of the 151 SEAs that were reviewed. Finally, two possible explanatory mechanisms are proposed to explain this: conflict avoidance and a need to quantify uncertainty

  1. 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

  2. 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.

  3. Assessing Groundwater Model Uncertainty for the Central Nevada Test Area

    International Nuclear Information System (INIS)

    Pohll, Greg; Pohlmann, Karl; Hassan, Ahmed; Chapman, Jenny; Mihevc, Todd

    2002-01-01

    The purpose of this study is to quantify the flow and transport model uncertainty for the Central Nevada Test Area (CNTA). Six parameters were identified as uncertain, including the specified head boundary conditions used in the flow model, the spatial distribution of the underlying welded tuff unit, effective porosity, sorption coefficients, matrix diffusion coefficient, and the geochemical release function which describes nuclear glass dissolution. The parameter uncertainty was described by assigning prior statistical distributions for each of these parameters. Standard Monte Carlo techniques were used to sample from the parameter distributions to determine the full prediction uncertainty. Additional analysis is performed to determine the most cost-beneficial characterization activities. The maximum radius of the tritium and strontium-90 contaminant boundary was used as the output metric for evaluation of prediction uncertainty. The results indicate that combining all of the uncertainty in the parameters listed above propagates to a prediction uncertainty in the maximum radius of the contaminant boundary of 234 to 308 m and 234 to 302 m, for tritium and strontium-90, respectively. Although the uncertainty in the input parameters is large, the prediction uncertainty in the contaminant boundary is relatively small. The relatively small prediction uncertainty is primarily due to the small transport velocities such that large changes in the uncertain input parameters causes small changes in the contaminant boundary. This suggests that the model is suitable in terms of predictive capability for the contaminant boundary delineation

  4. Spatial variability and parametric uncertainty in performance assessment models

    International Nuclear Information System (INIS)

    Pensado, Osvaldo; Mancillas, James; Painter, Scott; Tomishima, Yasuo

    2011-01-01

    The problem of defining an appropriate treatment of distribution functions (which could represent spatial variability or parametric uncertainty) is examined based on a generic performance assessment model for a high-level waste repository. The generic model incorporated source term models available in GoldSim ® , the TDRW code for contaminant transport in sparse fracture networks with a complex fracture-matrix interaction process, and a biosphere dose model known as BDOSE TM . Using the GoldSim framework, several Monte Carlo sampling approaches and transport conceptualizations were evaluated to explore the effect of various treatments of spatial variability and parametric uncertainty on dose estimates. Results from a model employing a representative source and ensemble-averaged pathway properties were compared to results from a model allowing for stochastic variation of transport properties along streamline segments (i.e., explicit representation of spatial variability within a Monte Carlo realization). We concluded that the sampling approach and the definition of an ensemble representative do influence consequence estimates. In the examples analyzed in this paper, approaches considering limited variability of a transport resistance parameter along a streamline increased the frequency of fast pathways resulting in relatively high dose estimates, while those allowing for broad variability along streamlines increased the frequency of 'bottlenecks' reducing dose estimates. On this basis, simplified approaches with limited consideration of variability may suffice for intended uses of the performance assessment model, such as evaluation of site safety. (author)

  5. Uncertainty evaluation methods for waste package performance assessment

    International Nuclear Information System (INIS)

    Wu, Y.T.; Nair, P.K.; Journel, A.G.; Abramson, L.R.

    1991-01-01

    This report identifies and investigates methodologies to deal with uncertainties in assessing high-level nuclear waste package performance. Four uncertainty evaluation methods (probability-distribution approach, bounding approach, expert judgment, and sensitivity analysis) are suggested as the elements of a methodology that, without either diminishing or enhancing the input uncertainties, can evaluate performance uncertainty. Such a methodology can also help identify critical inputs as a guide to reducing uncertainty so as to provide reasonable assurance that the risk objectives are met. This report examines the current qualitative waste containment regulation and shows how, in conjunction with the identified uncertainty evaluation methodology, a framework for a quantitative probability-based rule can be developed that takes account of the uncertainties. Current US Nuclear Regulatory Commission (NRC) regulation requires that the waste packages provide ''substantially complete containment'' (SCC) during the containment period. The term ''SCC'' is ambiguous and subject to interpretation. This report, together with an accompanying report that describes the technical considerations that must be addressed to satisfy high-level waste containment requirements, provides a basis for a third report to develop recommendations for regulatory uncertainty reduction in the ''containment''requirement of 10 CFR Part 60. 25 refs., 3 figs., 2 tabs

  6. Qualitative uncertainty analysis in probabilistic safety assessment context

    International Nuclear Information System (INIS)

    Apostol, M.; Constantin, M; Turcu, I.

    2007-01-01

    In Probabilistic Safety Assessment (PSA) context, an uncertainty analysis is performed either to estimate the uncertainty in the final results (the risk to public health and safety) or to estimate the uncertainty in some intermediate quantities (the core damage frequency, the radionuclide release frequency or fatality frequency). The identification and evaluation of uncertainty are important tasks because they afford credit to the results and help in the decision-making process. Uncertainty analysis can be performed qualitatively or quantitatively. This paper performs a preliminary qualitative uncertainty analysis, by identification of major uncertainty in PSA level 1- level 2 interface and in the other two major procedural steps of a level 2 PSA i.e. the analysis of accident progression and of the containment and analysis of source term for severe accidents. One should mention that a level 2 PSA for a Nuclear Power Plant (NPP) involves the evaluation and quantification of the mechanisms, amount and probabilities of subsequent radioactive material releases from the containment. According to NUREG 1150, an important task in source term analysis is fission products transport analysis. The uncertainties related to the isotopes distribution in CANDU NPP primary circuit and isotopes' masses transferred in the containment, using SOPHAEROS module from ASTEC computer code will be also presented. (authors)

  7. Coping with uncertainty in environmental impact assessments: Open techniques

    Energy Technology Data Exchange (ETDEWEB)

    Cardenas, Ibsen C., E-mail: c.cardenas@utwente.nl [IceBridge Research Institutea, Universiteit Twente, P.O. Box 217, 7500 AE Enschede (Netherlands); Halman, Johannes I.M., E-mail: J.I.M.Halman@utwente.nl [Universiteit Twente, P.O. Box 217, 7500 AE Enschede (Netherlands)

    2016-09-15

    Uncertainty is virtually unavoidable in environmental impact assessments (EIAs). From the literature related to treating and managing uncertainty, we have identified specific techniques for coping with uncertainty in EIAs. Here, we have focused on basic steps in the decision-making process that take place within an EIA setting. More specifically, we have identified uncertainties involved in each decision-making step and discussed the extent to which these can be treated and managed in the context of an activity or project that may have environmental impacts. To further demonstrate the relevance of the techniques identified, we have examined the extent to which the EIA guidelines currently used in Colombia consider and provide guidance on managing the uncertainty involved in these assessments. Some points that should be considered in order to provide greater robustness in impact assessments in Colombia have been identified. These include the management of stakeholder values, the systematic generation of project options, and their associated impacts as well as the associated management actions, and the evaluation of uncertainties and assumptions. We believe that the relevant and specific techniques reported here can be a reference for future evaluations of other EIA guidelines in different countries. - Highlights: • uncertainty is unavoidable in environmental impact assessments, EIAs; • we have identified some open techniques to EIAs for treating and managing uncertainty in these assessments; • points for improvement that should be considered in order to provide greater robustness in EIAs in Colombia have been identified; • the paper provides substantiated a reference for possible examinations of EIAs guidelines in other countries.

  8. Coping with uncertainty in environmental impact assessments: Open techniques

    International Nuclear Information System (INIS)

    Cardenas, Ibsen C.; Halman, Johannes I.M.

    2016-01-01

    Uncertainty is virtually unavoidable in environmental impact assessments (EIAs). From the literature related to treating and managing uncertainty, we have identified specific techniques for coping with uncertainty in EIAs. Here, we have focused on basic steps in the decision-making process that take place within an EIA setting. More specifically, we have identified uncertainties involved in each decision-making step and discussed the extent to which these can be treated and managed in the context of an activity or project that may have environmental impacts. To further demonstrate the relevance of the techniques identified, we have examined the extent to which the EIA guidelines currently used in Colombia consider and provide guidance on managing the uncertainty involved in these assessments. Some points that should be considered in order to provide greater robustness in impact assessments in Colombia have been identified. These include the management of stakeholder values, the systematic generation of project options, and their associated impacts as well as the associated management actions, and the evaluation of uncertainties and assumptions. We believe that the relevant and specific techniques reported here can be a reference for future evaluations of other EIA guidelines in different countries. - Highlights: • uncertainty is unavoidable in environmental impact assessments, EIAs; • we have identified some open techniques to EIAs for treating and managing uncertainty in these assessments; • points for improvement that should be considered in order to provide greater robustness in EIAs in Colombia have been identified; • the paper provides substantiated a reference for possible examinations of EIAs guidelines in other countries.

  9. 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.

  10. 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

  11. Vector network analyzer (VNA) measurements and uncertainty assessment

    CERN Document Server

    Shoaib, Nosherwan

    2017-01-01

    This book describes vector network analyzer measurements and uncertainty assessments, particularly in waveguide test-set environments, in order to establish their compatibility to the International System of Units (SI) for accurate and reliable characterization of communication networks. It proposes a fully analytical approach to measurement uncertainty evaluation, while also highlighting the interaction and the linear propagation of different uncertainty sources to compute the final uncertainties associated with the measurements. The book subsequently discusses the dimensional characterization of waveguide standards and the quality of the vector network analyzer (VNA) calibration techniques. The book concludes with an in-depth description of the novel verification artefacts used to assess the performance of the VNAs. It offers a comprehensive reference guide for beginners to experts, in both academia and industry, whose work involves the field of network analysis, instrumentation and measurements.

  12. Sensitivity and uncertainty analyses for performance assessment modeling

    International Nuclear Information System (INIS)

    Doctor, P.G.

    1988-08-01

    Sensitivity and uncertainty analyses methods for computer models are being applied in performance assessment modeling in the geologic high level radioactive waste repository program. The models used in performance assessment tend to be complex physical/chemical models with large numbers of input variables. There are two basic approaches to sensitivity and uncertainty analyses: deterministic and statistical. The deterministic approach to sensitivity analysis involves numerical calculation or employs the adjoint form of a partial differential equation to compute partial derivatives; the uncertainty analysis is based on Taylor series expansions of the input variables propagated through the model to compute means and variances of the output variable. The statistical approach to sensitivity analysis involves a response surface approximation to the model with the sensitivity coefficients calculated from the response surface parameters; the uncertainty analysis is based on simulation. The methods each have strengths and weaknesses. 44 refs

  13. Assessment of dose measurement uncertainty using RisoScan

    International Nuclear Information System (INIS)

    Helt-Hansen, Jakob; Miller, Arne

    2006-01-01

    The dose measurement uncertainty of the dosimeter system RisoScan, office scanner and Riso B3 dosimeters has been assessed by comparison with spectrophotometer measurements of the same dosimeters. The reproducibility and the combined uncertainty were found to be approximately 2% and 4%, respectively, at one standard deviation. The subroutine in RisoScan for electron energy measurement is shown to give results that are equivalent to the measurements with a scanning spectrophotometer

  14. Assessment of dose measurement uncertainty using RisøScan

    DEFF Research Database (Denmark)

    Helt-Hansen, J.; Miller, A.

    2006-01-01

    The dose measurement uncertainty of the dosimeter system RisoScan, office scanner and Riso B3 dosimeters has been assessed by comparison with spectrophotometer measurements of the same dosimeters. The reproducibility and the combined uncertainty were found to be approximately 2% and 4%, respectiv......%, respectively, at one standard deviation. The subroutine in RisoScan for electron energy measurement is shown to give results that are equivalent to the measurements with a scanning spectrophotometer. (c) 2006 Elsevier Ltd. All rights reserved....

  15. Uncertainty in Impact Assessment – EIA in Denmark

    DEFF Research Database (Denmark)

    Larsen, Sanne Vammen

    as problematic, as this is important information for decision makers and public actors. Taking point of departure in these issues, this paper seeks to add to the discussions by presenting the results of a study on the handling of uncertainty in Environmental Impact Assessment (EIA) reports in Denmark. The study...... is based on analysis of 100 EIA reports. The results will shed light on the extent to which uncertainties is addressed in EIA in Denmark and discuss how the practice can be categorised....

  16. 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

  17. Development and comparison of Bayesian modularization method in uncertainty assessment of hydrological models

    Science.gov (United States)

    Li, L.; Xu, C.-Y.; Engeland, K.

    2012-04-01

    With respect to model calibration, parameter estimation and analysis of uncertainty sources, different approaches have been used in hydrological models. Bayesian method is one of the most widely used methods for uncertainty assessment of hydrological models, which incorporates different sources of information into a single analysis through Bayesian theorem. However, none of these applications can well treat the uncertainty in extreme flows of hydrological models' simulations. This study proposes a Bayesian modularization method approach in uncertainty assessment of conceptual hydrological models by considering the extreme flows. It includes a comprehensive comparison and evaluation of uncertainty assessments by a new Bayesian modularization method approach and traditional Bayesian models using the Metropolis Hasting (MH) algorithm with the daily hydrological model WASMOD. Three likelihood functions are used in combination with traditional Bayesian: the AR (1) plus Normal and time period independent model (Model 1), the AR (1) plus Normal and time period dependent model (Model 2) and the AR (1) plus multi-normal model (Model 3). The results reveal that (1) the simulations derived from Bayesian modularization method are more accurate with the highest Nash-Sutcliffe efficiency value, and (2) the Bayesian modularization method performs best in uncertainty estimates of entire flows and in terms of the application and computational efficiency. The study thus introduces a new approach for reducing the extreme flow's effect on the discharge uncertainty assessment of hydrological models via Bayesian. Keywords: extreme flow, uncertainty assessment, Bayesian modularization, hydrological model, WASMOD

  18. Elevation uncertainty in coastal inundation hazard assessments

    Science.gov (United States)

    Gesch, Dean B.; Cheval, Sorin

    2012-01-01

    Coastal inundation has been identified as an important natural hazard that affects densely populated and built-up areas (Subcommittee on Disaster Reduction, 2008). Inundation, or coastal flooding, can result from various physical processes, including storm surges, tsunamis, intense precipitation events, and extreme high tides. Such events cause quickly rising water levels. When rapidly rising water levels overwhelm flood defenses, especially in heavily populated areas, the potential of the hazard is realized and a natural disaster results. Two noteworthy recent examples of such natural disasters resulting from coastal inundation are the Hurricane Katrina storm surge in 2005 along the Gulf of Mexico coast in the United States, and the tsunami in northern Japan in 2011. Longer term, slowly varying processes such as land subsidence (Committee on Floodplain Mapping Technologies, 2007) and sea-level rise also can result in coastal inundation, although such conditions do not have the rapid water level rise associated with other flooding events. Geospatial data are a critical resource for conducting assessments of the potential impacts of coastal inundation, and geospatial representations of the topography in the form of elevation measurements are a primary source of information for identifying the natural and human components of the landscape that are at risk. Recently, the quantity and quality of elevation data available for the coastal zone have increased markedly, and this availability facilitates more detailed and comprehensive hazard impact assessments.

  19. 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

  20. Collaborative framework for PIV uncertainty quantification: comparative assessment of methods

    International Nuclear Information System (INIS)

    Sciacchitano, Andrea; Scarano, Fulvio; Neal, Douglas R; Smith, Barton L; Warner, Scott O; Vlachos, Pavlos P; Wieneke, Bernhard

    2015-01-01

    A posteriori uncertainty quantification of particle image velocimetry (PIV) data is essential to obtain accurate estimates of the uncertainty associated with a given experiment. This is particularly relevant when measurements are used to validate computational models or in design and decision processes. In spite of the importance of the subject, the first PIV uncertainty quantification (PIV-UQ) methods have been developed only in the last three years. The present work is a comparative assessment of four approaches recently proposed in the literature: the uncertainty surface method (Timmins et al 2012), the particle disparity approach (Sciacchitano et al 2013), the peak ratio criterion (Charonko and Vlachos 2013) and the correlation statistics method (Wieneke 2015). The analysis is based upon experiments conducted for this specific purpose, where several measurement techniques are employed simultaneously. The performances of the above approaches are surveyed across different measurement conditions and flow regimes. (paper)

  1. Communicating uncertainty: lessons learned and suggestions for climate change assessment

    International Nuclear Information System (INIS)

    Patt, A.; Dessai, S.

    2005-01-01

    Assessments of climate change face the task of making information about uncertainty accessible and useful to decision-makers. The literature in behavior economics provides many examples of how people make decisions under conditions of uncertainty relying on inappropriate heuristics, leading to inconsistent and counterproductive choices. Modern risk communication practices recommend a number of methods to overcome these hurdles, which have been recommended for the Intergovernmental Panel on Climate Change (IPCC) assessment reports. This paper evaluates the success of the most recent IPCC approach to uncertainty communication, based on a controlled survey of climate change experts. Evaluating the results from the survey, and from a similar survey recently conducted among university students, the paper suggests that the most recent IPCC approach leaves open the possibility for biased and inconsistent responses to the information. The paper concludes by suggesting ways to improve the approach for future IPCC assessment reports. (authors)

  2. The role of sensitivity analysis in assessing uncertainty

    International Nuclear Information System (INIS)

    Crick, M.J.; Hill, M.D.

    1987-01-01

    Outside the specialist world of those carrying out performance assessments considerable confusion has arisen about the meanings of sensitivity analysis and uncertainty analysis. In this paper we attempt to reduce this confusion. We then go on to review approaches to sensitivity analysis within the context of assessing uncertainty, and to outline the types of test available to identify sensitive parameters, together with their advantages and disadvantages. The views expressed in this paper are those of the authors; they have not been formally endorsed by the National Radiological Protection Board and should not be interpreted as Board advice

  3. Assessment of uncertainties in severe accident management strategies

    International Nuclear Information System (INIS)

    Kastenberg, W.E.; Apostolakis, G.; Catton, I.; Dhir, V.K.; Okrent, D.

    1990-01-01

    Recent progress on the development of Probabilistic Risk Assessment (PRA) as a tool for qualifying nuclear reactor safety and on research devoted to severe accident phenomena has made severe accident management an achievable goal. Severe accident management strategies may involve operational changes, modification and/or addition of hardware, and institutional changes. In order to achieve the goal of managing severe accidents, a method for assessment of strategies must be developed which integrates PRA methodology and our current knowledge concerning severe accident phenomena, including uncertainty. The research project presented in this paper is aimed at delineating uncertainties in severe accident progression and their impact on severe accident management strategies

  4. Uncertainty and sensitivity analysis in nuclear accident consequence assessment

    International Nuclear Information System (INIS)

    Karlberg, Olof.

    1989-01-01

    This report contains the results of a four year project in research contracts with the Nordic Cooperation in Nuclear Safety and the National Institute for Radiation Protection. An uncertainty/sensitivity analysis methodology consisting of Latin Hypercube sampling and regression analysis was applied to an accident consequence model. A number of input parameters were selected and the uncertainties related to these parameter were estimated within a Nordic group of experts. Individual doses, collective dose, health effects and their related uncertainties were then calculated for three release scenarios and for a representative sample of meteorological situations. From two of the scenarios the acute phase after an accident were simulated and from one the long time consequences. The most significant parameters were identified. The outer limits of the calculated uncertainty distributions are large and will grow to several order of magnitudes for the low probability consequences. The uncertainty in the expectation values are typical a factor 2-5 (1 Sigma). The variation in the model responses due to the variation of the weather parameters is fairly equal to the parameter uncertainty induced variation. The most important parameters showed out to be different for each pathway of exposure, which could be expected. However, the overall most important parameters are the wet deposition coefficient and the shielding factors. A general discussion of the usefulness of uncertainty analysis in consequence analysis is also given. (au)

  5. Uncertainties in environmental radiological assessment models and their implications

    International Nuclear Information System (INIS)

    Hoffman, F.O.; Miller, C.W.

    1983-01-01

    Environmental radiological assessments rely heavily on the use of mathematical models. The predictions of these models are inherently uncertain because these models are inexact representations of real systems. The major sources of this uncertainty are related to biases in model formulation and parameter estimation. The best approach for estimating the actual extent of over- or underprediction is model validation, a procedure that requires testing over the range of the intended realm of model application. Other approaches discussed are the use of screening procedures, sensitivity and stochastic analyses, and model comparison. The magnitude of uncertainty in model predictions is a function of the questions asked of the model and the specific radionuclides and exposure pathways of dominant importance. Estimates are made of the relative magnitude of uncertainty for situations requiring predictions of individual and collective risks for both chronic and acute releases of radionuclides. It is concluded that models developed as research tools should be distinguished from models developed for assessment applications. Furthermore, increased model complexity does not necessarily guarantee increased accuracy. To improve the realism of assessment modeling, stochastic procedures are recommended that translate uncertain parameter estimates into a distribution of predicted values. These procedures also permit the importance of model parameters to be ranked according to their relative contribution to the overall predicted uncertainty. Although confidence in model predictions can be improved through site-specific parameter estimation and increased model validation, risk factors and internal dosimetry models will probably remain important contributors to the amount of uncertainty that is irreducible

  6. Assessing performance of flaw characterization methods through uncertainty propagation

    Science.gov (United States)

    Miorelli, R.; Le Bourdais, F.; Artusi, X.

    2018-04-01

    In this work, we assess the inversion performance in terms of crack characterization and localization based on synthetic signals associated to ultrasonic and eddy current physics. More precisely, two different standard iterative inversion algorithms are used to minimize the discrepancy between measurements (i.e., the tested data) and simulations. Furthermore, in order to speed up the computational time and get rid of the computational burden often associated to iterative inversion algorithms, we replace the standard forward solver by a suitable metamodel fit on a database built offline. In a second step, we assess the inversion performance by adding uncertainties on a subset of the database parameters and then, through the metamodel, we propagate these uncertainties within the inversion procedure. The fast propagation of uncertainties enables efficiently evaluating the impact due to the lack of knowledge on some parameters employed to describe the inspection scenarios, which is a situation commonly encountered in the industrial NDE context.

  7. 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.

  8. Evaluating variability and uncertainty in radiological impact assessment using SYMBIOSE

    International Nuclear Information System (INIS)

    Simon-Cornu, M.; Beaugelin-Seiller, K.; Boyer, P.; Calmon, P.; Garcia-Sanchez, L.; Mourlon, C.; Nicoulaud, V.; Sy, M.; Gonze, M.A.

    2015-01-01

    SYMBIOSE is a modelling platform that accounts for variability and uncertainty in radiological impact assessments, when simulating the environmental fate of radionuclides and assessing doses to human populations. The default database of SYMBIOSE is partly based on parameter values that are summarized within International Atomic Energy Agency (IAEA) documents. To characterize uncertainty on the transfer parameters, 331 Probability Distribution Functions (PDFs) were defined from the summary statistics provided within the IAEA documents (i.e. sample size, minimal and maximum values, arithmetic and geometric means, standard and geometric standard deviations) and are made available as spreadsheet files. The methods used to derive the PDFs without complete data sets, but merely the summary statistics, are presented. Then, a simple case-study illustrates the use of the database in a second-order Monte Carlo calculation, separating parametric uncertainty and inter-individual variability. - Highlights: • Parametric uncertainty in radioecology was derived from IAEA documents. • 331 Probability Distribution Functions were defined for transfer parameters. • Parametric uncertainty and inter-individual variability were propagated

  9. Comparison of the effect of hazard and response/fragility uncertainties on core melt probability uncertainty

    International Nuclear Information System (INIS)

    Mensing, R.W.

    1985-01-01

    This report proposes a method for comparing the effects of the uncertainty in probabilistic risk analysis (PRA) input parameters on the uncertainty in the predicted risks. The proposed method is applied to compare the effect of uncertainties in the descriptions of (1) the seismic hazard at a nuclear power plant site and (2) random variations in plant subsystem responses and component fragility on the uncertainty in the predicted probability of core melt. The PRA used is that developed by the Seismic Safety Margins Research Program

  10. 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

  11. Analyzing Bullwhip Effect in Supply Networks under Exogenous Uncertainty

    Directory of Open Access Journals (Sweden)

    Mitra Darvish

    2014-05-01

    Full Text Available This paper explains a model for analyzing and measuring the propagation of order amplifications (i.e. bullwhip effect for a single-product supply network topology considering exogenous uncertainty and linear and time-invariant inventory management policies for network entities. The stream of orders placed by each entity of the network is characterized assuming customer demand is ergodic. In fact, we propose an exact formula in order to measure the bullwhip effect in the addressed supply network topology considering the system in Markovian chain framework and presenting a matrix of network member relationships and relevant order sequences. The formula turns out using a mathematical method called frequency domain analysis. The major contribution of this paper is analyzing the bullwhip effect considering exogenous uncertainty in supply networks and using the Fourier transform in order to simplify the relevant calculations. We present a number of numerical examples to assess the analytical results accuracy in quantifying the bullwhip effect.

  12. 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

  13. 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.

  14. Measurement, simulation and uncertainty assessment of implant heating during MRI

    International Nuclear Information System (INIS)

    Neufeld, E; Kuehn, S; Kuster, N; Szekely, G

    2009-01-01

    The heating of tissues around implants during MRI can pose severe health risks, and careful evaluation is required for leads to be labeled as MR conditionally safe. A recent interlaboratory comparison study has shown that different groups can produce widely varying results (sometimes with more than a factor of 5 difference) when performing measurements according to current guidelines. To determine the related difficulties and to derive optimized procedures, two different generic lead structures have been investigated in this study by using state-of-the-art temperature and dosimetric probes, as well as simulations for which detailed uncertainty budgets have been determined. The agreement between simulations and measurements is well within the combined uncertainty. The study revealed that the uncertainty can be kept below 17% if appropriate instrumentation and procedures are applied. Optimized experimental assessment techniques can be derived from the findings presented herein.

  15. Measurement, simulation and uncertainty assessment of implant heating during MRI

    Energy Technology Data Exchange (ETDEWEB)

    Neufeld, E; Kuehn, S; Kuster, N [Foundation for Research on Information Technologies in Society (IT' IS), Zeughausstr. 43, 8004 Zurich (Switzerland); Szekely, G [Computer Vision Laboratory, Swiss Federal Institute of Technology (ETHZ), Sternwartstr 7, ETH Zentrum, 8092 Zurich (Switzerland)], E-mail: neufeld@itis.ethz.ch

    2009-07-07

    The heating of tissues around implants during MRI can pose severe health risks, and careful evaluation is required for leads to be labeled as MR conditionally safe. A recent interlaboratory comparison study has shown that different groups can produce widely varying results (sometimes with more than a factor of 5 difference) when performing measurements according to current guidelines. To determine the related difficulties and to derive optimized procedures, two different generic lead structures have been investigated in this study by using state-of-the-art temperature and dosimetric probes, as well as simulations for which detailed uncertainty budgets have been determined. The agreement between simulations and measurements is well within the combined uncertainty. The study revealed that the uncertainty can be kept below 17% if appropriate instrumentation and procedures are applied. Optimized experimental assessment techniques can be derived from the findings presented herein.

  16. Communicating uncertainties in assessments of future sea level rise

    Science.gov (United States)

    Wikman-Svahn, P.

    2013-12-01

    How uncertainty should be managed and communicated in policy-relevant scientific assessments is directly connected to the role of science and the responsibility of scientists. These fundamentally philosophical issues influence how scientific assessments are made and how scientific findings are communicated to policymakers. It is therefore of high importance to discuss implicit assumptions and value judgments that are made in policy-relevant scientific assessments. The present paper examines these issues for the case of scientific assessments of future sea level rise. The magnitude of future sea level rise is very uncertain, mainly due to poor scientific understanding of all physical mechanisms affecting the great ice sheets of Greenland and Antarctica, which together hold enough land-based ice to raise sea levels more than 60 meters if completely melted. There has been much confusion from policymakers on how different assessments of future sea levels should be interpreted. Much of this confusion is probably due to how uncertainties are characterized and communicated in these assessments. The present paper draws on the recent philosophical debate on the so-called "value-free ideal of science" - the view that science should not be based on social and ethical values. Issues related to how uncertainty is handled in scientific assessments are central to this debate. This literature has much focused on how uncertainty in data, parameters or models implies that choices have to be made, which can have social consequences. However, less emphasis has been on how uncertainty is characterized when communicating the findings of a study, which is the focus of the present paper. The paper argues that there is a tension between on the one hand the value-free ideal of science and on the other hand usefulness for practical applications in society. This means that even if the value-free ideal could be upheld in theory, by carefully constructing and hedging statements characterizing

  17. Uncertainty and sensitivity analysis on probabilistic safety assessment of an experimental facility

    International Nuclear Information System (INIS)

    Burgazzi, L.

    2000-01-01

    The aim of this work is to perform an uncertainty and sensitivity analysis on the probabilistic safety assessment of the International Fusion Materials Irradiation Facility (IFMIF), in order to assess the effect on the final risk values of the uncertainties associated with the generic data used for the initiating events and component reliability and to identify the key quantities contributing to this uncertainty. The analysis is conducted on the expected frequency calculated for the accident sequences, defined through the event tree (ET) modeling. This is in order to increment credit to the ET model quantification, to calculate frequency distributions for the occurrence of events and, consequently, to assess if sequences have been correctly selected on the probability standpoint and finally to verify the fulfillment of the safety conditions. Uncertainty and sensitivity analysis are performed using respectively Monte Carlo sampling and an importance parameter technique. (author)

  18. Uncertainty

    International Nuclear Information System (INIS)

    Silva, T.A. da

    1988-01-01

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

  19. Uncertainty of Energy Consumption Assessment of Domestic Buildings

    DEFF Research Database (Denmark)

    Brohus, Henrik; Heiselberg, Per; Simonsen, A.

    2009-01-01

    In order to assess the influence of energy reduction initiatives, to determine the expected annual cost, to calculate life cycle cost, emission impact, etc. it is crucial to be able to assess the energy consumption reasonably accurate. The present work undertakes a theoretical and empirical study...... of the uncertainty of energy consumption assessment of domestic buildings. The calculated energy consumption of a number of almost identical domestic buildings in Denmark is compared with the measured energy consumption. Furthermore, the uncertainty is determined by means of stochastic modelling based on input...... to correspond reasonably well; however, it is also found that significant differences may occur between calculated and measured energy consumption due to the spread and due to the fact that the result can only be determined with a certain probability. It is found that occupants' behaviour is the major...

  20. Selection of low activation materials for fusion power plants using ACAB system: the effect of computational methods and cross section uncertainties on waste management assessment

    Energy Technology Data Exchange (ETDEWEB)

    Alonso, M.; Sanz, J.; Rodriguez, A.; Falquina, R. [Universidad Nacional de Educacion a Distancia (UNED), Dept. of Power Engineering, Madrid (Spain); Cabellos, O.; Sanz, J. [Universidad Politecnica de Madrid, Instituto de Fusion Nuclear (UPM) (Spain)

    2003-07-01

    The feasibility of nuclear fusion as a realistic option for energy generation depends on its radioactive waste management assessment. In this respect, the production of high level waste is to be avoided and the reduction of low level waste volumes is to be enhanced. Three different waste management options are commonly regarded in fusion plants: Hands-on Recycling, Remote Recycling and Shallow Land Burial (SLB). Therefore, important research work has been undertaken to find low activation structural materials. In performing this task, a major issue is to compute the concentration limits (CLs) for all natural elements, which will be used to select the intended constituent elements of a particular Low Activation Material (LAM) and assess how much the impurities can deteriorate the waste management properties. Nevertheless, the reliable computation of CLs depends on the accuracy of nuclear data (mainly activation cross-sections) and the suitability of the computational method both for inertial and magnetic fusion environments. In this paper the importance of nuclear data uncertainties and mathematical algorithms used in different activation calculations for waste management purposes will be studied. Our work is centred on the study of {sup 186}W activation under first structural wall conditions of Hylife-II inertial fusion reactor design. The importance of the dominant transmutation/decay sequence has been documented in several publications. From a practical point of view, W is used in low activation materials for fusion applications: Cr-W ferritic/martensitic steels, and the need to better compute its activation has been assessed, in particular in relation to the cross-section uncertainties for reactions leading to Ir isotopes. {sup 192n}Ir and {sup 192}Ir reach a secular equilibrium, and {sup 192n}Ir is the critical one for waste management, with a half life of 241 years. From a theoretical point of view, this is one of the most complex chains appearing in

  1. 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.

  2. Uncertainties in Agricultural Impact Assessments of Climate Change

    DEFF Research Database (Denmark)

    Montesino San Martin, Manuel

    Future food security will be challenged by the likely increase in demand, changes in consumption patterns and the effects of climate change. Framing food availability requires adequate agricultural production planning. Decision-making can benefit from improved understanding of the uncertainties...

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

    Directory of Open Access Journals (Sweden)

    A. Chenarani

    2017-10-01

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

  4. Quantifying uncertainty and trade-offs in resilience assessments

    Directory of Open Access Journals (Sweden)

    Craig R. Allen

    2018-03-01

    Full Text Available Several frameworks have been developed to assess the resilience of social-ecological systems, but most require substantial data inputs, time, and technical expertise. Stakeholders and practitioners often lack the resources for such intensive efforts. Furthermore, most end with problem framing and fail to explicitly address trade-offs and uncertainty. To remedy this gap, we developed a rapid survey assessment that compares the relative resilience of social-ecological systems with respect to a number of resilience properties. This approach generates large amounts of information relative to stakeholder inputs. We targeted four stakeholder categories: government (policy, regulation, management, end users (farmers, ranchers, landowners, industry, agency/public science (research, university, extension, and NGOs (environmental, citizen, social justice in four North American watersheds, to assess social-ecological resilience through surveys. Conceptually, social-ecological systems are comprised of components ranging from strictly human to strictly ecological, but that relate directly or indirectly to one another. They have soft boundaries and several important dimensions or axes that together describe the nature of social-ecological interactions, e.g., variability, diversity, modularity, slow variables, feedbacks, capital, innovation, redundancy, and ecosystem services. There is no absolute measure of resilience, so our design takes advantage of cross-watershed comparisons and therefore focuses on relative resilience. Our approach quantifies and compares the relative resilience across watershed systems and potential trade-offs among different aspects of the social-ecological system, e.g., between social, economic, and ecological contributions. This approach permits explicit assessment of several types of uncertainty (e.g., self-assigned uncertainty for stakeholders; uncertainty across respondents, watersheds, and subsystems, and subjectivity in

  5. A Bayesian belief network approach for assessing uncertainty in conceptual site models at contaminated sites

    DEFF Research Database (Denmark)

    Thomsen, Nanna Isbak; Binning, Philip John; McKnight, Ursula S.

    2016-01-01

    the most important site-specific features and processes that may affect the contaminant transport behavior at the site. However, the development of a CSM will always be associated with uncertainties due to limited data and lack of understanding of the site conditions. CSM uncertainty is often found...... to be a major source of model error and it should therefore be accounted for when evaluating uncertainties in risk assessments. We present a Bayesian belief network (BBN) approach for constructing CSMs and assessing their uncertainty at contaminated sites. BBNs are graphical probabilistic models...... that are effective for integrating quantitative and qualitative information, and thus can strengthen decisions when empirical data are lacking. The proposed BBN approach facilitates a systematic construction of multiple CSMs, and then determines the belief in each CSM using a variety of data types and/or expert...

  6. Holistic uncertainty analysis in river basin modeling for climate vulnerability assessment

    Science.gov (United States)

    Taner, M. U.; Wi, S.; Brown, C.

    2017-12-01

    The challenges posed by uncertain future climate are a prominent concern for water resources managers. A number of frameworks exist for assessing the impacts of climate-related uncertainty, including internal climate variability and anthropogenic climate change, such as scenario-based approaches and vulnerability-based approaches. While in many cases climate uncertainty may be dominant, other factors such as future evolution of the river basin, hydrologic response and reservoir operations are potentially significant sources of uncertainty. While uncertainty associated with modeling hydrologic response has received attention, very little attention has focused on the range of uncertainty and possible effects of the water resources infrastructure and management. This work presents a holistic framework that allows analysis of climate, hydrologic and water management uncertainty in water resources systems analysis with the aid of a water system model designed to integrate component models for hydrology processes and water management activities. The uncertainties explored include those associated with climate variability and change, hydrologic model parameters, and water system operation rules. A Bayesian framework is used to quantify and model the uncertainties at each modeling steps in integrated fashion, including prior and the likelihood information about model parameters. The framework is demonstrated in a case study for the St. Croix Basin located at border of United States and Canada.

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

    International Nuclear Information System (INIS)

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

    2013-01-01

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

  8. On economic resolution and uncertainty in hydrocarbon exploration assessment

    International Nuclear Information System (INIS)

    Lerche, I.

    1998-01-01

    When assessment of parameters of a decision tree for a hydrocarbon exploration project can lie within estimated ranges, it is shown that the ensemble average expected value has two sorts of uncertainties: one is due to the expected value of each realization of the decision tree being different than the average; the second is due to intrinsic variance of each decision tree. The total standard error of the average expected value combines both sorts. The use of additional statistical measures, such as standard error, volatility, and cumulative probability of making a profit, provide insight into the selection process leading to a more appropriate decision. In addition, the use of relative contributions and relative importance for the uncertainty measures guides one to a better determination of those parameters that dominantly influence the total ensemble uncertainty. In this way one can concentrate resources on efforts to minimize the uncertainty ranges of such dominant parameters. A numerical illustration is provided to indicate how such calculations can be performed simply with a hand calculator. (author)

  9. Uncertainty Estimate in Resources Assessment: A Geostatistical Contribution

    International Nuclear Information System (INIS)

    Souza, Luis Eduardo de; Costa, Joao Felipe C. L.; Koppe, Jair C.

    2004-01-01

    For many decades the mining industry regarded resources/reserves estimation and classification as a mere calculation requiring basic mathematical and geological knowledge. Most methods were based on geometrical procedures and spatial data distribution. Therefore, uncertainty associated with tonnages and grades either were ignored or mishandled, although various mining codes require a measure of confidence in the values reported. Traditional methods fail in reporting the level of confidence in the quantities and grades. Conversely, kriging is known to provide the best estimate and its associated variance. Among kriging methods, Ordinary Kriging (OK) probably is the most widely used one for mineral resource/reserve estimation, mainly because of its robustness and its facility in uncertainty assessment by using the kriging variance. It also is known that OK variance is unable to recognize local data variability, an important issue when heterogeneous mineral deposits with higher and poorer grade zones are being evaluated. Alternatively, stochastic simulation are used to build local or global uncertainty about a geological attribute respecting its statistical moments. This study investigates methods capable of incorporating uncertainty to the estimates of resources and reserves via OK and sequential gaussian and sequential indicator simulation The results showed that for the type of mineralization studied all methods classified the tonnages similarly. The methods are illustrated using an exploration drill hole data sets from a large Brazilian coal deposit

  10. Accounting for uncertainty factors in biodiversity impact assessment: lessons from a case study

    International Nuclear Information System (INIS)

    Geneletti, D.; Beinat, E.; Chung, C.F.; Fabbri, A.G.; Scholten, H.J.

    2003-01-01

    For an Environmental Impact Statement (EIS) to effectively contribute to decision-making, it must include one crucial step: the estimation of the uncertainty factors affecting the impact evaluation and of their effect on the evaluation results. Knowledge of the uncertainties better orients the strategy of the decision-makers and underlines the most critical data or methodological steps of the procedure. Accounting for uncertainty factors is particularly relevant when dealing with ecological impacts, whose forecasts are typically affected by a high degree of simplification. By means of a case study dealing with the evaluation of road alternatives, this paper explores and discusses the main uncertainties that are related to the typical stages of a biodiversity impact assessment: uncertainty in the data that are used, in the methodologies that are applied, and in the value judgments provided by the experts. Subsequently, the effects of such uncertainty factors are tracked back to the result of the evaluation, i.e., to the relative performance of the project alternatives under consideration. This allows to test the sensitivity of the results, and consequently to provide a more informative ranking of the alternatives. The papers concludes by discussing the added-value for decision-making provided by uncertainty analysis within EIA

  11. Uncertainty analysis on probabilistic fracture mechanics assessment methodology

    International Nuclear Information System (INIS)

    Rastogi, Rohit; Vinod, Gopika; Chandra, Vikas; Bhasin, Vivek; Babar, A.K.; Rao, V.V.S.S.; Vaze, K.K.; Kushwaha, H.S.; Venkat-Raj, V.

    1999-01-01

    Fracture Mechanics has found a profound usage in the area of design of components and assessing fitness for purpose/residual life estimation of an operating component. Since defect size and material properties are statistically distributed, various probabilistic approaches have been employed for the computation of fracture probability. Monte Carlo Simulation is one such procedure towards the analysis of fracture probability. This paper deals with uncertainty analysis using the Monte Carlo Simulation methods. These methods were developed based on the R6 failure assessment procedure, which has been widely used in analysing the integrity of structures. The application of this method is illustrated with a case study. (author)

  12. Probabilistic accident consequence uncertainty analysis: Food chain uncertainty assessment. Volume 2: Appendices

    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 second of a two-volume document that summarizes a joint project by the US Nuclear Regulatory and the Commission of European Communities 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 two-volume report, which examines mechanisms and uncertainties of transfer through the food chain, is the first in a series of five such reports. A panel of sixteen experts was formed to compile credible and traceable uncertainty distributions for food chain transfer that affect calculations of offsite radiological consequences. Seven of the experts reported on transfer into the food chain through soil and plants, nine reported on transfer via food products from animals, and two reported on both. The expert judgment elicitation procedure and its outcomes are described in these volumes. This volume contains seven appendices. Appendix A presents a brief discussion of the MAACS and COSYMA model codes. Appendix B is the structure document and elicitation questionnaire for the expert panel on soils and plants. Appendix C presents the rationales and responses of each of the members of the soils and plants expert panel. Appendix D is the structure document and elicitation questionnaire for the expert panel on animal transfer. The rationales and responses of each of the experts on animal transfer are given in Appendix E. Brief biographies of the food chain expert panel members are provided in Appendix F. Aggregated results of expert responses are presented in graph format in Appendix G.

  13. Probabilistic accident consequence uncertainty analysis: Food chain uncertainty assessment. Volume 2: Appendices

    International Nuclear Information System (INIS)

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

    1997-06-01

    This volume is the second of a two-volume document that summarizes a joint project by the US Nuclear Regulatory and the Commission of European Communities 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 two-volume report, which examines mechanisms and uncertainties of transfer through the food chain, is the first in a series of five such reports. A panel of sixteen experts was formed to compile credible and traceable uncertainty distributions for food chain transfer that affect calculations of offsite radiological consequences. Seven of the experts reported on transfer into the food chain through soil and plants, nine reported on transfer via food products from animals, and two reported on both. The expert judgment elicitation procedure and its outcomes are described in these volumes. This volume contains seven appendices. Appendix A presents a brief discussion of the MAACS and COSYMA model codes. Appendix B is the structure document and elicitation questionnaire for the expert panel on soils and plants. Appendix C presents the rationales and responses of each of the members of the soils and plants expert panel. Appendix D is the structure document and elicitation questionnaire for the expert panel on animal transfer. The rationales and responses of each of the experts on animal transfer are given in Appendix E. Brief biographies of the food chain expert panel members are provided in Appendix F. Aggregated results of expert responses are presented in graph format in Appendix G

  14. 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

  15. Validation and assessment of matrix effect and uncertainty of a gas chromatography coupled to mass spectrometry method for pesticides in papaya and avocado samples

    Directory of Open Access Journals (Sweden)

    Norma Susana Pano-Farias

    2017-07-01

    Full Text Available In this paper a method of using the “quick, easy, cheap, effective, rugged, and safe” (QuEChERS extraction and gas chromatography coupled to mass spectrometry detection (GC–MS was developed for the analysis of five frequently applied pesticides in papaya and avocado. The selected pesticides, ametryn, atrazine, carbaryl, carbofuran, and methyl parathion, represent the most commonly used classes (carbamates, organophosphorous, and triazines. Optimum separation achieved the analysis of all pesticides in 0.99. The limits of detection (LOD and quantification (LOQ in papaya ranged from 0.03 mg/kg to 0.35 mg/kg and from 0.06 mg/kg to 0.75 mg/kg, respectively. Meanwhile for avocado, LOD values varied from 0.14 mg/kg to 0.28 mg/kg and LOQ values ranged from 0.22 mg/kg to 0.40 mg/kg. Recoveries obtained for each pesticide in both matrices ranged between 60.6% and 104.3%. The expanded uncertainty of the method was < 26% for all the pesticides in both fruits. Finally, the method was applied to other fruits.

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

    International Nuclear Information System (INIS)

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

    1992-01-01

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

  17. 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.

  18. Effect of monthly areal rainfall uncertainty on streamflow simulation

    Science.gov (United States)

    Ndiritu, J. G.; Mkhize, N.

    2017-08-01

    Areal rainfall is mostly obtained from point rainfall measurements that are sparsely located and several studies have shown that this results in large areal rainfall uncertainties at the daily time step. However, water resources assessment is often carried out a monthly time step and streamflow simulation is usually an essential component of this assessment. This study set out to quantify monthly areal rainfall uncertainties and assess their effect on streamflow simulation. This was achieved by; i) quantifying areal rainfall uncertainties and using these to generate stochastic monthly areal rainfalls, and ii) finding out how the quality of monthly streamflow simulation and streamflow variability change if stochastic areal rainfalls are used instead of historic areal rainfalls. Tests on monthly rainfall uncertainty were carried out using data from two South African catchments while streamflow simulation was confined to one of them. A non-parametric model that had been applied at a daily time step was used for stochastic areal rainfall generation and the Pitman catchment model calibrated using the SCE-UA optimizer was used for streamflow simulation. 100 randomly-initialised calibration-validation runs using 100 stochastic areal rainfalls were compared with 100 runs obtained using the single historic areal rainfall series. By using 4 rain gauges alternately to obtain areal rainfall, the resulting differences in areal rainfall averaged to 20% of the mean monthly areal rainfall and rainfall uncertainty was therefore highly significant. Pitman model simulations obtained coefficient of efficiencies averaging 0.66 and 0.64 in calibration and validation using historic rainfalls while the respective values using stochastic areal rainfalls were 0.59 and 0.57. Average bias was less than 5% in all cases. The streamflow ranges using historic rainfalls averaged to 29% of the mean naturalised flow in calibration and validation and the respective average ranges using stochastic

  19. On the proper use of Ensembles for Predictive Uncertainty assessment

    Science.gov (United States)

    Todini, Ezio; Coccia, Gabriele; Ortiz, Enrique

    2015-04-01

    uncertainty of the ensemble mean and that of the ensemble spread. The results of this new approach are illustrated by using data and forecasts from an operational real time flood forecasting. Coccia, G. and Todini, E. 2011. Recent developments in predictive uncertainty assessment based on the Model Conditional Processor approach. Hydrology and Earth System Sciences, 15, 3253-3274. doi:10.5194/hess-15-3253-2011. Krzysztofowicz, R. 1999 Bayesian theory of probabilistic forecasting via deterministic hydrologic model, Water Resour. Res., 35, 2739-2750. Raftery, A. E., T. Gneiting, F. Balabdaoui, and M. Polakowski, 2005. Using Bayesian model averaging to calibrate forecast ensembles, Mon. Weather Rev., 133, 1155-1174. Reggiani, P., Renner, M., Weerts, A., and van Gelder, P., 2009. Uncertainty assessment via Bayesian revision of ensemble streamflow predictions in the operational river Rhine forecasting system, Water Resour. Res., 45, W02428, doi:10.1029/2007WR006758. Todini E. 2004. Role and treatment of uncertainty in real-time flood forecasting. Hydrological Processes 18(14), 2743_2746 Todini, E. 2008. A model conditional processor to assess predictive uncertainty in flood forecasting. Intl. J. River Basin Management, 6(2): 123-137.

  20. Joint analysis of epistemic and aleatory uncertainty in stability analysis for geo-hazard assessments

    Science.gov (United States)

    Rohmer, Jeremy; Verdel, Thierry

    2017-04-01

    Uncertainty analysis is an unavoidable task of stability analysis of any geotechnical systems. Such analysis usually relies on the safety factor SF (if SF is below some specified threshold), the failure is possible). The objective of the stability analysis is then to estimate the failure probability P for SF to be below the specified threshold. When dealing with uncertainties, two facets should be considered as outlined by several authors in the domain of geotechnics, namely "aleatoric uncertainty" (also named "randomness" or "intrinsic variability") and "epistemic uncertainty" (i.e. when facing "vague, incomplete or imprecise information" such as limited databases and observations or "imperfect" modelling). The benefits of separating both facets of uncertainty can be seen from a risk management perspective because: - Aleatoric uncertainty, being a property of the system under study, cannot be reduced. However, practical actions can be taken to circumvent the potentially dangerous effects of such variability; - Epistemic uncertainty, being due to the incomplete/imprecise nature of available information, can be reduced by e.g., increasing the number of tests (lab or in site survey), improving the measurement methods or evaluating calculation procedure with model tests, confronting more information sources (expert opinions, data from literature, etc.). Uncertainty treatment in stability analysis usually restricts to the probabilistic framework to represent both facets of uncertainty. Yet, in the domain of geo-hazard assessments (like landslides, mine pillar collapse, rockfalls, etc.), the validity of this approach can be debatable. In the present communication, we propose to review the major criticisms available in the literature against the systematic use of probability in situations of high degree of uncertainty. On this basis, the feasibility of using a more flexible uncertainty representation tool is then investigated, namely Possibility distributions (e

  1. 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

  2. Errors and Uncertainties in Dose Reconstruction for Radiation Effects Research

    Energy Technology Data Exchange (ETDEWEB)

    Strom, Daniel J.

    2008-04-14

    Dose reconstruction for studies of the health effects of ionizing radiation have been carried out for many decades. Major studies have included Japanese bomb survivors, atomic veterans, downwinders of the Nevada Test Site and Hanford, underground uranium miners, and populations of nuclear workers. For such studies to be credible, significant effort must be put into applying the best science to reconstructing unbiased absorbed doses to tissues and organs as a function of time. In many cases, more and more sophisticated dose reconstruction methods have been developed as studies progressed. For the example of the Japanese bomb survivors, the dose surrogate “distance from the hypocenter” was replaced by slant range, and then by TD65 doses, DS86 doses, and more recently DS02 doses. Over the years, it has become increasingly clear that an equal level of effort must be expended on the quantitative assessment of uncertainty in such doses, and to reducing and managing uncertainty. In this context, this paper reviews difficulties in terminology, explores the nature of Berkson and classical uncertainties in dose reconstruction through examples, and proposes a path forward for Joint Coordinating Committee for Radiation Effects Research (JCCRER) Project 2.4 that requires a reasonably small level of effort for DOSES-2008.

  3. Particle Swarm Optimization and Uncertainty Assessment in Inverse Problems

    Directory of Open Access Journals (Sweden)

    José L. G. Pallero

    2018-01-01

    Full Text Available Most inverse problems in the industry (and particularly in geophysical exploration are highly underdetermined because the number of model parameters too high to achieve accurate data predictions and because the sampling of the data space is scarce and incomplete; it is always affected by different kinds of noise. Additionally, the physics of the forward problem is a simplification of the reality. All these facts result in that the inverse problem solution is not unique; that is, there are different inverse solutions (called equivalent, compatible with the prior information that fits the observed data within similar error bounds. In the case of nonlinear inverse problems, these equivalent models are located in disconnected flat curvilinear valleys of the cost-function topography. The uncertainty analysis consists of obtaining a representation of this complex topography via different sampling methodologies. In this paper, we focus on the use of a particle swarm optimization (PSO algorithm to sample the region of equivalence in nonlinear inverse problems. Although this methodology has a general purpose, we show its application for the uncertainty assessment of the solution of a geophysical problem concerning gravity inversion in sedimentary basins, showing that it is possible to efficiently perform this task in a sampling-while-optimizing mode. Particularly, we explain how to use and analyze the geophysical models sampled by exploratory PSO family members to infer different descriptors of nonlinear uncertainty.

  4. 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.

  5. 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

  6. Methods for Assessing Uncertainties in Climate Change, Impacts and Responses (Invited)

    Science.gov (United States)

    Manning, M. R.; Swart, R.

    2009-12-01

    Assessing the scientific uncertainties or confidence levels for the many different aspects of climate change is particularly important because of the seriousness of potential impacts and the magnitude of economic and political responses that are needed to mitigate climate change effectively. This has made the treatment of uncertainty and confidence a key feature in the assessments carried out by the Intergovernmental Panel on Climate Change (IPCC). Because climate change is very much a cross-disciplinary area of science, adequately dealing with uncertainties requires recognition of their wide range and different perspectives on assessing and communicating those uncertainties. The structural differences that exist across disciplines are often embedded deeply in the corresponding literature that is used as the basis for an IPCC assessment. The assessment of climate change science by the IPCC has from its outset tried to report the levels of confidence and uncertainty in the degree of understanding in both the underlying multi-disciplinary science and in projections for future climate. The growing recognition of the seriousness of this led to the formation of a detailed approach for consistent treatment of uncertainties in the IPCC’s Third Assessment Report (TAR) [Moss and Schneider, 2000]. However, in completing the TAR there remained some systematic differences between the disciplines raising concerns about the level of consistency. So further consideration of a systematic approach to uncertainties was undertaken for the Fourth Assessment Report (AR4). The basis for the approach used in the AR4 was developed at an expert meeting of scientists representing many different disciplines. This led to the introduction of a broader way of addressing uncertainties in the AR4 [Manning et al., 2004] which was further refined by lengthy discussions among many IPCC Lead Authors, for over a year, resulting in a short summary of a standard approach to be followed for that

  7. Managing geological uncertainty in CO2-EOR reservoir assessments

    Science.gov (United States)

    Welkenhuysen, Kris; Piessens, Kris

    2014-05-01

    Recently the European Parliament has agreed that an atlas for the storage potential of CO2 is of high importance to have a successful commercial introduction of CCS (CO2 capture and geological storage) technology in Europe. CO2-enhanced oil recovery (CO2-EOR) is often proposed as a promising business case for CCS, and likely has a high potential in the North Sea region. Traditional economic assessments for CO2-EOR largely neglect the geological reality of reservoir uncertainties because these are difficult to introduce realistically in such calculations. There is indeed a gap between the outcome of a reservoir simulation and the input values for e.g. cost-benefit evaluations, especially where it concerns uncertainty. The approach outlined here is to turn the procedure around, and to start from which geological data is typically (or minimally) requested for an economic assessment. Thereafter it is evaluated how this data can realistically be provided by geologists and reservoir engineers. For the storage of CO2 these parameters are total and yearly CO2 injection capacity, and containment or potential on leakage. Specifically for the EOR operation, two additional parameters can be defined: the EOR ratio, or the ratio of recovered oil over injected CO2, and the CO2 recycling ratio of CO2 that is reproduced after breakthrough at the production well. A critical but typically estimated parameter for CO2-EOR projects is the EOR ratio, taken in this brief outline as an example. The EOR ratio depends mainly on local geology (e.g. injection per well), field design (e.g. number of wells), and time. Costs related to engineering can be estimated fairly good, given some uncertainty range. The problem is usually to reliably estimate the geological parameters that define the EOR ratio. Reliable data is only available from (onshore) CO2-EOR projects in the US. Published studies for the North Sea generally refer to these data in a simplified form, without uncertainty ranges, and are

  8. Assessment and visualization of uncertainty for countrywide soil organic matter map of Hungary using local entropy

    Science.gov (United States)

    Szatmári, Gábor; Pásztor, László

    2016-04-01

    Uncertainty is a general term expressing our imperfect knowledge in describing an environmental process and we are aware of it (Bárdossy and Fodor, 2004). Sampling, laboratory measurements, models and so on are subject to uncertainty. Effective quantification and visualization of uncertainty would be indispensable to stakeholders (e.g. policy makers, society). Soil related features and their spatial models should be stressfully targeted to uncertainty assessment because their inferences are further used in modelling and decision making process. The aim of our present study was to assess and effectively visualize the local uncertainty of the countrywide soil organic matter (SOM) spatial distribution model of Hungary using geostatistical tools and concepts. The Hungarian Soil Information and Monitoring System's SOM data (approximately 1,200 observations) and environmental related, spatially exhaustive secondary information (i.e. digital elevation model, climatic maps, MODIS satellite images and geological map) were used to model the countrywide SOM spatial distribution by regression kriging. It would be common to use the calculated estimation (or kriging) variance as a measure of uncertainty, however the normality and homoscedasticity hypotheses have to be refused according to our preliminary analysis on the data. Therefore, a normal score transformation and a sequential stochastic simulation approach was introduced to be able to model and assess the local uncertainty. Five hundred equally probable realizations (i.e. stochastic images) were generated. The number of the stochastic images is fairly enough to provide a model of uncertainty at each location, which is a complete description of uncertainty in geostatistics (Deutsch and Journel, 1998). Furthermore, these models can be applied e.g. to contour the probability of any events, which can be regarded as goal oriented digital soil maps and are of interest for agricultural management and decision making as well. A

  9. Assessment of errors and uncertainty patterns in GIA modeling

    DEFF Research Database (Denmark)

    Barletta, Valentina Roberta; Spada, G.

    2012-01-01

    During the last decade many efforts have been devoted to the assessment of global sea level rise and to the determination of the mass balance of continental ice sheets. In this context, the important role of glacial-isostatic adjustment (GIA) has been clearly recognized. Yet, in many cases only one......, such as time-evolving shorelines and paleo-coastlines. In this study we quantify these uncertainties and their propagation in GIA response using a Monte Carlo approach to obtain spatio-temporal patterns of GIA errors. A direct application is the error estimates in ice mass balance in Antarctica and Greenland...

  10. Dependencies, human interactions and uncertainties in probabilistic safety assessment

    International Nuclear Information System (INIS)

    Hirschberg, S.

    1990-01-01

    In the context of Probabilistic Safety Assessment (PSA), three areas were investigated in a 4-year Nordic programme: dependencies with special emphasis on common cause failures, human interactions and uncertainty aspects. The approach was centered around comparative analyses in form of Benchmark/Reference Studies and retrospective reviews. Weak points in available PSAs were identified and recommendations were made aiming at improving consistency of the PSAs. The sensitivity of PSA-results to basic assumptions was demonstrated and the sensitivity to data assignment and to choices of methods for analysis of selected topics was investigated. (author)

  11. 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.

  12. Uncertainty and sensitivity analysis using probabilistic system assessment code. 1

    International Nuclear Information System (INIS)

    Honma, Toshimitsu; Sasahara, Takashi.

    1993-10-01

    This report presents the results obtained when applying the probabilistic system assessment code under development to the PSACOIN Level 0 intercomparison exercise organized by the Probabilistic System Assessment Code User Group in the Nuclear Energy Agency (NEA) of OECD. This exercise is one of a series designed to compare and verify probabilistic codes in the performance assessment of geological radioactive waste disposal facilities. The computations were performed using the Monte Carlo sampling code PREP and post-processor code USAMO. The submodels in the waste disposal system were described and coded with the specification of the exercise. Besides the results required for the exercise, further additional uncertainty and sensitivity analyses were performed and the details of these are also included. (author)

  13. IAEA CRP on HTGR Uncertainties in Modeling: Assessment of Phase I Lattice to Core Model Uncertainties

    Energy Technology Data Exchange (ETDEWEB)

    Rouxelin, Pascal Nicolas [Idaho National Lab. (INL), Idaho Falls, ID (United States); Strydom, Gerhard [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2016-09-01

    Best-estimate plus uncertainty analysis of reactors is replacing the traditional conservative (stacked uncertainty) method for safety and licensing analysis. To facilitate uncertainty analysis applications, a comprehensive approach and methodology must be developed and applied. High temperature gas cooled reactors (HTGRs) have several features that require techniques not used in light-water reactor analysis (e.g., coated-particle design and large graphite quantities at high temperatures). The International Atomic Energy Agency has therefore launched the Coordinated Research Project on HTGR Uncertainty Analysis in Modeling to study uncertainty propagation in the HTGR analysis chain. The benchmark problem defined for the prismatic design is represented by the General Atomics Modular HTGR 350. The main focus of this report is the compilation and discussion of the results obtained for various permutations of Exercise I 2c and the use of the cross section data in Exercise II 1a of the prismatic benchmark, which is defined as the last and first steps of the lattice and core simulation phases, respectively. The report summarizes the Idaho National Laboratory (INL) best estimate results obtained for Exercise I 2a (fresh single-fuel block), Exercise I 2b (depleted single-fuel block), and Exercise I 2c (super cell) in addition to the first results of an investigation into the cross section generation effects for the super-cell problem. The two dimensional deterministic code known as the New ESC based Weighting Transport (NEWT) included in the Standardized Computer Analyses for Licensing Evaluation (SCALE) 6.1.2 package was used for the cross section evaluation, and the results obtained were compared to the three dimensional stochastic SCALE module KENO VI. The NEWT cross section libraries were generated for several permutations of the current benchmark super-cell geometry and were then provided as input to the Phase II core calculation of the stand alone neutronics Exercise

  14. Using measurement uncertainty in decision-making and conformity assessment

    Science.gov (United States)

    Pendrill, L. R.

    2014-08-01

    Measurements often provide an objective basis for making decisions, perhaps when assessing whether a product conforms to requirements or whether one set of measurements differs significantly from another. There is increasing appreciation of the need to account for the role of measurement uncertainty when making decisions, so that a ‘fit-for-purpose’ level of measurement effort can be set prior to performing a given task. Better mutual understanding between the metrologist and those ordering such tasks about the significance and limitations of the measurements when making decisions of conformance will be especially useful. Decisions of conformity are, however, currently made in many important application areas, such as when addressing the grand challenges (energy, health, etc), without a clear and harmonized basis for sharing the risks that arise from measurement uncertainty between the consumer, supplier and third parties. In reviewing, in this paper, the state of the art of the use of uncertainty evaluation in conformity assessment and decision-making, two aspects in particular—the handling of qualitative observations and of impact—are considered key to bringing more order to the present diverse rules of thumb of more or less arbitrary limits on measurement uncertainty and percentage risk in the field. (i) Decisions of conformity can be made on a more or less quantitative basis—referred in statistical acceptance sampling as by ‘variable’ or by ‘attribute’ (i.e. go/no-go decisions)—depending on the resources available or indeed whether a full quantitative judgment is needed or not. There is, therefore, an intimate relation between decision-making, relating objects to each other in terms of comparative or merely qualitative concepts, and nominal and ordinal properties. (ii) Adding measures of impact, such as the costs of incorrect decisions, can give more objective and more readily appreciated bases for decisions for all parties concerned. Such

  15. A review of occupational dose assessment uncertainties and approaches

    International Nuclear Information System (INIS)

    Anderson, R. W.

    2004-01-01

    The Radiological Protection Practitioner (RPP) will spend a considerable proportion of his time predicting or assessing retrospective radiation exposures to occupational personnel for different purposes. The assessments can be for a variety of purposes, such as to predict doses for occupational dose control, or project design purposes or to make retrospective estimates for the dose record, or account for dosemeters which have been lost or damaged. There are other less frequent occasions when dose assessment will be required such as to support legal cases and compensation claims and to provide the detailed dose information for epidemiological studies. It is important that the level of detail, justification and supporting evidence in the dose assessment is suitable for the requirements. So for instance, day to day operational dose assessments often rely mainly on the knowledge of the RPP in discussion with operators whilst at the other end of the spectrum a historical dose assessment for a legal case will require substantial research and supporting evidence for the estimate to withstand forensic challenge. The robustness of the assessment will depend on many factors including a knowledge of the work activities, the radiation dose uptake and field characteristics; all of which are affected by factors such as the time elapsed, the memory of operators and the dosemeters employed. This paper reviews the various options and uncertainties in dose assessments ranging from use of personal dosimetry results to the development of upper bound assessments. The level of assessment, the extent of research and the evidence adduced should then be appropriate to the end use of the estimate. (Author)

  16. Aiding alternatives assessment with an uncertainty-tolerant hazard scoring method.

    Science.gov (United States)

    Faludi, Jeremy; Hoang, Tina; Gorman, Patrick; Mulvihill, Martin

    2016-11-01

    This research developed a single-score system to simplify and clarify decision-making in chemical alternatives assessment, accounting for uncertainty. Today, assessing alternatives to hazardous constituent chemicals is a difficult task-rather than comparing alternatives by a single definitive score, many independent toxicological variables must be considered at once, and data gaps are rampant. Thus, most hazard assessments are only comprehensible to toxicologists, but business leaders and politicians need simple scores to make decisions. In addition, they must balance hazard against other considerations, such as product functionality, and they must be aware of the high degrees of uncertainty in chemical hazard data. This research proposes a transparent, reproducible method to translate eighteen hazard endpoints into a simple numeric score with quantified uncertainty, alongside a similar product functionality score, to aid decisions between alternative products. The scoring method uses Clean Production Action's GreenScreen as a guide, but with a different method of score aggregation. It provides finer differentiation between scores than GreenScreen's four-point scale, and it displays uncertainty quantitatively in the final score. Displaying uncertainty also illustrates which alternatives are early in product development versus well-defined commercial products. This paper tested the proposed assessment method through a case study in the building industry, assessing alternatives to spray polyurethane foam insulation containing methylene diphenyl diisocyanate (MDI). The new hazard scoring method successfully identified trade-offs between different alternatives, showing finer resolution than GreenScreen Benchmarking. Sensitivity analysis showed that different weighting schemes in hazard scores had almost no effect on alternatives ranking, compared to uncertainty from data gaps. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. Using sequential indicator simulation to assess the uncertainty of delineating heavy-metal contaminated soils

    International Nuclear Information System (INIS)

    Juang, Kai-Wei; Chen, Yue-Shin; Lee, Dar-Yuan

    2004-01-01

    Mapping the spatial distribution of soil pollutants is essential for delineating contaminated areas. Currently, geostatistical interpolation, kriging, is increasingly used to estimate pollutant concentrations in soils. The kriging-based approach, indicator kriging (IK), may be used to model the uncertainty of mapping. However, a smoothing effect is usually produced when using kriging in pollutant mapping. The detailed spatial patterns of pollutants could, therefore, be lost. The local uncertainty of mapping pollutants derived by the IK technique is referred to as the conditional cumulative distribution function (ccdf) for one specific location (i.e. single-location uncertainty). The local uncertainty information obtained by IK is not sufficient as the uncertainty of mapping at several locations simultaneously (i.e. multi-location uncertainty or spatial uncertainty) is required to assess the reliability of the delineation of contaminated areas. The simulation approach, sequential indicator simulation (SIS), which has the ability to model not only single, but also multi-location uncertainties, was used, in this study, to assess the uncertainty of the delineation of heavy metal contaminated soils. To illustrate this, a data set of Cu concentrations in soil from Taiwan was used. The results show that contour maps of Cu concentrations generated by the SIS realizations exhausted all the spatial patterns of Cu concentrations without the smoothing effect found when using the kriging method. Based on the SIS realizations, the local uncertainty of Cu concentrations at a specific location of x', refers to the probability of the Cu concentration z(x') being higher than the defined threshold level of contamination (z c ). This can be written as Prob SIS [z(x')>z c ], representing the probability of contamination. The probability map of Prob SIS [z(x')>z c ] can then be used for delineating contaminated areas. In addition, the multi-location uncertainty of an area A

  18. Ensuring effective supply chain management under uncertainty

    Directory of Open Access Journals (Sweden)

    Lutsenko Iryna Sergiivna

    2016-09-01

    Full Text Available Identified the main sources of uncertainty in supply chains and tools to mitigate them. The necessity of functional, spatial and temporal integration and linkage of decision-making at different management levels. Determined that the optimization of information flow can occur due to the “shrink” in time, volume and direction, this process should be preceded by a thorough analysis and rethinking of the business processes of a complex system of supply chains.

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

    International Nuclear Information System (INIS)

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

    2012-01-01

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

  20. Uncertainty management in radioactive waste repository site assessment

    International Nuclear Information System (INIS)

    Baldwin, J.f.; Martin, T.P.; Tocatlidou

    1994-01-01

    The problem of performance assessment of a site to serve as a repository for the final disposal of radioactive waste involves different types of uncertainties. Their main sources include the large temporal and spatial considerations over which safety of the system has to be ensured, our inability to completely understand and describe a very complex structure such as the repository system, lack of precision in the measured information etc. These issues underlie most of the problems faced when rigid probabilistic approaches are used. Nevertheless a framework is needed, that would allow for an optimal aggregation of the available knowledge and an efficient management of the various types of uncertainty involved. In this work a knowledge-based modelling of the repository selection process is proposed that through a consequence analysis, evaluates the potential impact that hypothetical scenarios will have on a candidate site. The model is organised around a hierarchical structure, relating the scenarios with the possible events and processes that characterise them, and the site parameters. The scheme provides for both crisp and fuzzy parameter values and uses fuzzy semantic unification and evidential support logic reference mechanisms. It is implemented using the artificial intelligence language FRIL and the interaction with the user is performed through a windows interface

  1. 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 ...

  2. effect of uncertainty on the fatigue reliability of reinforced concrete ...

    African Journals Online (AJOL)

    In this paper, a reliability time-variant fatigue analysis and uncertainty effect on the serviceability of reinforced concrete bridge deck was carried out. A simply supported 15m bridge deck was specifically used for the investigation. Mathematical models were developed and the uncertainties in structural resistance, applied ...

  3. Uncertainty Analysis with Considering Resonance Self-shielding Effect

    International Nuclear Information System (INIS)

    Han, Tae Young

    2016-01-01

    If infinitely diluted multi-group cross sections were used for the sensitivity, the covariance data from the evaluated nuclear data library (ENDL) was directly applied. However, in case of using a self-shielded multi-group cross section, the covariance data should be corrected considering self-shielding effect. Usually, implicit uncertainty can be defined as the uncertainty change by the resonance self-shielding effect as described above. MUSAD ( Modules of Uncertainty and Sensitivity Analysis for DeCART ) has been developed for a multiplication factor and cross section uncertainty based on the generalized perturbation theory and it, however, can only quantify the explicit uncertainty by the self-shielded multi-group cross sections without considering the implicit effect. Thus, this paper addresses the implementation of the implicit uncertainty analysis module into the code and the numerical results for the verification are provided. The implicit uncertainty analysis module has been implemented into MUSAD based on infinitely-diluted cross section-based consistent method. The verification calculation was performed on MHTGR 350 Ex.I-1a and the differences with McCARD result decrease from 40% to 1% in CZP case and 3% in HFP case. From this study, it is expected that MUSAD code can reasonably produce the complete uncertainty on VHTR or LWR where the resonance self-shielding effect should be significantly considered

  4. Uncertainty Analysis with Considering Resonance Self-shielding Effect

    Energy Technology Data Exchange (ETDEWEB)

    Han, Tae Young [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2016-10-15

    If infinitely diluted multi-group cross sections were used for the sensitivity, the covariance data from the evaluated nuclear data library (ENDL) was directly applied. However, in case of using a self-shielded multi-group cross section, the covariance data should be corrected considering self-shielding effect. Usually, implicit uncertainty can be defined as the uncertainty change by the resonance self-shielding effect as described above. MUSAD ( Modules of Uncertainty and Sensitivity Analysis for DeCART ) has been developed for a multiplication factor and cross section uncertainty based on the generalized perturbation theory and it, however, can only quantify the explicit uncertainty by the self-shielded multi-group cross sections without considering the implicit effect. Thus, this paper addresses the implementation of the implicit uncertainty analysis module into the code and the numerical results for the verification are provided. The implicit uncertainty analysis module has been implemented into MUSAD based on infinitely-diluted cross section-based consistent method. The verification calculation was performed on MHTGR 350 Ex.I-1a and the differences with McCARD result decrease from 40% to 1% in CZP case and 3% in HFP case. From this study, it is expected that MUSAD code can reasonably produce the complete uncertainty on VHTR or LWR where the resonance self-shielding effect should be significantly considered.

  5. Climate change impact assessment and adaptation under uncertainty

    NARCIS (Netherlands)

    Wardekker, J.A.

    2011-01-01

    Expected impacts of climate change are associated with large uncertainties, particularly at the local level. Adaptation scientists, practitioners, and decision-makers will need to find ways to cope with these uncertainties. Several approaches have been suggested as ‘uncertainty-proof’ to some

  6. Effect of Streamflow Forecast Uncertainty on Real-Time Reservoir Operation

    Science.gov (United States)

    Zhao, T.; Cai, X.; Yang, D.

    2010-12-01

    Various hydrological forecast products have been applied to real-time reservoir operation, including deterministic streamflow forecast (DSF), DSF-based probabilistic streamflow forecast (DPSF), and ensemble streamflow forecast (ESF), which represent forecast uncertainty in the form of deterministic forecast error, deterministic forecast error-based uncertainty distribution, and ensemble forecast errors, respectively. Compared to previous studies that treat these forecast products as ad hoc inputs for reservoir operation models, this paper attempts to model the uncertainties involved in the various forecast products and explores their effect on real-time reservoir operation decisions. In hydrology, there are various indices reflecting the magnitude of streamflow forecast uncertainty; meanwhile, few models illustrate the forecast uncertainty evolution process. This research introduces Martingale Model of Forecast Evolution (MMFE) from supply chain management and justifies its assumptions for quantifying the evolution of uncertainty in streamflow forecast as time progresses. Based on MMFE, this research simulates the evolution of forecast uncertainty in DSF, DPSF, and ESF, and applies the reservoir operation models (dynamic programming, DP; stochastic dynamic programming, SDP; and standard operation policy, SOP) to assess the effect of different forms of forecast uncertainty on real-time reservoir operation. Through a hypothetical single-objective real-time reservoir operation model, the results illustrate that forecast uncertainty exerts significant effects. Reservoir operation efficiency, as measured by a utility function, decreases as the forecast uncertainty increases. Meanwhile, these effects also depend on the type of forecast product being used. In general, the utility of reservoir operation with ESF is nearly as high as the utility obtained with a perfect forecast; the utilities of DSF and DPSF are similar to each other but not as efficient as ESF. Moreover

  7. 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...

  8. 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

  9. Generalized uncertainty principles, effective Newton constant and regular black holes

    OpenAIRE

    Li, Xiang; Ling, Yi; Shen, You-Gen; Liu, Cheng-Zhou; He, Hong-Sheng; Xu, Lan-Fang

    2016-01-01

    In this paper, we explore the quantum spacetimes that are potentially connected with the generalized uncertainty principles. By analyzing the gravity-induced quantum interference pattern and the Gedanken for weighting photon, we find that the generalized uncertainty principles inspire the effective Newton constant as same as our previous proposal. A characteristic momentum associated with the tidal effect is suggested, which incorporates the quantum effect with the geometric nature of gravity...

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

    International Nuclear Information System (INIS)

    Bonnema, B.E.

    2002-01-01

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

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

    International Nuclear Information System (INIS)

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

    2008-01-01

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

  12. 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

  13. Uncertainty assessing of measure result of tungsten in U3O8 by ICP-AES

    International Nuclear Information System (INIS)

    Du Guirong; Nie Jie; Tang Lilei

    2011-01-01

    According as the determining method and the assessing criterion,the uncertainty assessing of measure result of tungsten in U 3 O 8 by ICP-AES is researched. With the assessment of each component in detail, the result shows that u rel (sc)> u rel (c)> u rel (F)> u rel (m) by uncertainty contribution. Other uncertainty is random, calculated by repetition. u rel (sc) is contributed to uncertainty mainly. So the general uncertainty is reduced with strict operation to reduce u rel (sc). (authors)

  14. Assessing uncertainty in high-resolution spatial climate data across the US Northeast.

    Science.gov (United States)

    Bishop, Daniel A; Beier, Colin M

    2013-01-01

    Local and regional-scale knowledge of climate change is needed to model ecosystem responses, assess vulnerabilities and devise effective adaptation strategies. High-resolution gridded historical climate (GHC) products address this need, but come with multiple sources of uncertainty that are typically not well understood by data users. To better understand this uncertainty in a region with a complex climatology, we conducted a ground-truthing analysis of two 4 km GHC temperature products (PRISM and NRCC) for the US Northeast using 51 Cooperative Network (COOP) weather stations utilized by both GHC products. We estimated GHC prediction error for monthly temperature means and trends (1980-2009) across the US Northeast and evaluated any landscape effects (e.g., elevation, distance from coast) on those prediction errors. Results indicated that station-based prediction errors for the two GHC products were similar in magnitude, but on average, the NRCC product predicted cooler than observed temperature means and trends, while PRISM was cooler for means and warmer for trends. We found no evidence for systematic sources of uncertainty across the US Northeast, although errors were largest at high elevations. Errors in the coarse-scale (4 km) digital elevation models used by each product were correlated with temperature prediction errors, more so for NRCC than PRISM. In summary, uncertainty in spatial climate data has many sources and we recommend that data users develop an understanding of uncertainty at the appropriate scales for their purposes. To this end, we demonstrate a simple method for utilizing weather stations to assess local GHC uncertainty and inform decisions among alternative GHC products.

  15. Assessing spatial uncertainties of land allocation using a scenario approach and sensitivity analysis: A study for land use in Europe

    NARCIS (Netherlands)

    Verburg, P.H.; Tabeau, A.A.; Hatna, E.

    2013-01-01

    Land change model outcomes are vulnerable to multiple types of uncertainty, including uncertainty in input data, structural uncertainties in the model and uncertainties in model parameters. In coupled model systems the uncertainties propagate between the models. This paper assesses uncertainty of

  16. Assessing uncertainty in SRTM elevations for global flood modelling

    Science.gov (United States)

    Hawker, L. P.; Rougier, J.; Neal, J. C.; Bates, P. D.

    2017-12-01

    The SRTM DEM is widely used as the topography input to flood models in data-sparse locations. Understanding spatial error in the SRTM product is crucial in constraining uncertainty about elevations and assessing the impact of these upon flood prediction. Assessment of SRTM error was carried out by Rodriguez et al (2006), but this did not explicitly quantify the spatial structure of vertical errors in the DEM, and nor did it distinguish between errors over different types of landscape. As a result, there is a lack of information about spatial structure of vertical errors of the SRTM in the landscape that matters most to flood models - the floodplain. Therefore, this study attempts this task by comparing SRTM, an error corrected SRTM product (The MERIT DEM of Yamazaki et al., 2017) and near truth LIDAR elevations for 3 deltaic floodplains (Mississippi, Po, Wax Lake) and a large lowland region (the Fens, UK). Using the error covariance function, calculated by comparing SRTM elevations to the near truth LIDAR, perturbations of the 90m SRTM DEM were generated, producing a catalogue of plausible DEMs. This allows modellers to simulate a suite of plausible DEMs at any aggregated block size above native SRTM resolution. Finally, the generated DEM's were input into a hydrodynamic model of the Mekong Delta, built using the LISFLOOD-FP hydrodynamic model, to assess how DEM error affects the hydrodynamics and inundation extent across the domain. The end product of this is an inundation map with the probability of each pixel being flooded based on the catalogue of DEMs. In a world of increasing computer power, but a lack of detailed datasets, this powerful approach can be used throughout natural hazard modelling to understand how errors in the SRTM DEM can impact the hazard assessment.

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

    International Nuclear Information System (INIS)

    Laskey, K.B.

    1994-01-01

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

  18. 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.

  19. Advanced Nuclear Fuel Cycle Effects on the Treatment of Uncertainty in the Long-Term Assessment of Geologic Disposal Systems - EBS Input

    International Nuclear Information System (INIS)

    Sutton, M.; Blink, J.A.; Greenberg, H.R.; Sharma, M.

    2012-01-01

    The Used Fuel Disposition (UFD) Campaign within the Department of Energy's Office of Nuclear Energy (DOE-NE) Fuel Cycle Technology (FCT) program has been tasked with investigating the disposal of the nation's spent nuclear fuel (SNF) and high-level nuclear waste (HLW) for a range of potential waste forms and geologic environments. The planning, construction, and operation of a nuclear disposal facility is a long-term process that involves engineered barriers that are tailored to both the geologic environment and the waste forms being emplaced. The UFD Campaign is considering a range of fuel cycles that in turn produce a range of waste forms. The UFD Campaign is also considering a range of geologic media. These ranges could be thought of as adding uncertainty to what the disposal facility design will ultimately be; however, it may be preferable to thinking about the ranges as adding flexibility to design of a disposal facility. For example, as the overall DOE-NE program and industrial actions result in the fuel cycles that will produce waste to be disposed, and the characteristics of those wastes become clear, the disposal program retains flexibility in both the choice of geologic environment and the specific repository design. Of course, other factors also play a major role, including local and State-level acceptance of the specific site that provides the geologic environment. In contrast, the Yucca Mountain Project (YMP) repository license application (LA) is based on waste forms from an open fuel cycle (PWR and BWR assemblies from an open fuel cycle). These waste forms were about 90% of the total waste, and they were the determining waste form in developing the engineered barrier system (EBS) design for the Yucca Mountain Repository design. About 10% of the repository capacity was reserved for waste from a full recycle fuel cycle in which some actinides were extracted for weapons use, and the remaining fission products and some minor actinides were encapsulated

  20. ADVANCED NUCLEAR FUEL CYCLE EFFECTS ON THE TREATMENT OF UNCERTAINTY IN THE LONG-TERM ASSESSMENT OF GEOLOGIC DISPOSAL SYSTEMS - EBS INPUT

    Energy Technology Data Exchange (ETDEWEB)

    Sutton, M; Blink, J A; Greenberg, H R; Sharma, M

    2012-04-25

    The Used Fuel Disposition (UFD) Campaign within the Department of Energy's Office of Nuclear Energy (DOE-NE) Fuel Cycle Technology (FCT) program has been tasked with investigating the disposal of the nation's spent nuclear fuel (SNF) and high-level nuclear waste (HLW) for a range of potential waste forms and geologic environments. The planning, construction, and operation of a nuclear disposal facility is a long-term process that involves engineered barriers that are tailored to both the geologic environment and the waste forms being emplaced. The UFD Campaign is considering a range of fuel cycles that in turn produce a range of waste forms. The UFD Campaign is also considering a range of geologic media. These ranges could be thought of as adding uncertainty to what the disposal facility design will ultimately be; however, it may be preferable to thinking about the ranges as adding flexibility to design of a disposal facility. For example, as the overall DOE-NE program and industrial actions result in the fuel cycles that will produce waste to be disposed, and the characteristics of those wastes become clear, the disposal program retains flexibility in both the choice of geologic environment and the specific repository design. Of course, other factors also play a major role, including local and State-level acceptance of the specific site that provides the geologic environment. In contrast, the Yucca Mountain Project (YMP) repository license application (LA) is based on waste forms from an open fuel cycle (PWR and BWR assemblies from an open fuel cycle). These waste forms were about 90% of the total waste, and they were the determining waste form in developing the engineered barrier system (EBS) design for the Yucca Mountain Repository design. About 10% of the repository capacity was reserved for waste from a full recycle fuel cycle in which some actinides were extracted for weapons use, and the remaining fission products and some minor actinides were

  1. Uncertainty and Sensitivity of Alternative Rn-222 Flux Density Models Used in Performance Assessment

    Energy Technology Data Exchange (ETDEWEB)

    Greg J. Shott, Vefa Yucel, Lloyd Desotell

    2007-06-01

    Performance assessments for the Area 5 Radioactive Waste Management Site on the Nevada Test Site have used three different mathematical models to estimate Rn-222 flux density. This study describes the performance, uncertainty, and sensitivity of the three models which include the U.S. Nuclear Regulatory Commission Regulatory Guide 3.64 analytical method and two numerical methods. The uncertainty of each model was determined by Monte Carlo simulation using Latin hypercube sampling. The global sensitivity was investigated using Morris one-at-time screening method, sample-based correlation and regression methods, the variance-based extended Fourier amplitude sensitivity test, and Sobol's sensitivity indices. The models were found to produce similar estimates of the mean and median flux density, but to have different uncertainties and sensitivities. When the Rn-222 effective diffusion coefficient was estimated using five different published predictive models, the radon flux density models were found to be most sensitive to the effective diffusion coefficient model selected, the emanation coefficient, and the radionuclide inventory. Using a site-specific measured effective diffusion coefficient significantly reduced the output uncertainty. When a site-specific effective-diffusion coefficient was used, the models were most sensitive to the emanation coefficient and the radionuclide inventory.

  2. Uncertainty and Sensitivity of Alternative Rn-222 Flux Density Models Used in Performance Assessment

    International Nuclear Information System (INIS)

    Greg J. Shott, Vefa Yucel, Lloyd Desotell Non-Nstec Authors: G. Pyles and Jon Carilli

    2007-01-01

    Performance assessments for the Area 5 Radioactive Waste Management Site on the Nevada Test Site have used three different mathematical models to estimate Rn-222 flux density. This study describes the performance, uncertainty, and sensitivity of the three models which include the U.S. Nuclear Regulatory Commission Regulatory Guide 3.64 analytical method and two numerical methods. The uncertainty of each model was determined by Monte Carlo simulation using Latin hypercube sampling. The global sensitivity was investigated using Morris one-at-time screening method, sample-based correlation and regression methods, the variance-based extended Fourier amplitude sensitivity test, and Sobol's sensitivity indices. The models were found to produce similar estimates of the mean and median flux density, but to have different uncertainties and sensitivities. When the Rn-222 effective diffusion coefficient was estimated using five different published predictive models, the radon flux density models were found to be most sensitive to the effective diffusion coefficient model selected, the emanation coefficient, and the radionuclide inventory. Using a site-specific measured effective diffusion coefficient significantly reduced the output uncertainty. When a site-specific effective-diffusion coefficient was used, the models were most sensitive to the emanation coefficient and the radionuclide inventory

  3. 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

  4. 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

  5. Sources/treatment of uncertainties in the performance assessment of geologic radioactive waste repositories

    International Nuclear Information System (INIS)

    Cranwell, R.M.

    1987-01-01

    Uncertainties in the performance assessment of geologic radioactive waste repositories have several sources. The more important ones include: 1) uncertainty in the conditions of a disposal system over the temporal scales set forth in regulations, 2) uncertainty in the conceptualization of the geohydrologic system, 3) uncertainty in the theoretical description of a given conceptual model of the system, 4) uncertainty in the development of computer codes to implement the solution of a mathematical model, and 5) uncertainty in the parameters and data required in the models and codes used to assess the long-term performance of the disposal system. This paper discusses each of these uncertainties and outlines methods for addressing these uncertainties

  6. 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...

  7. Assessing concentration uncertainty estimates from passive microwave sea ice products

    Science.gov (United States)

    Meier, W.; Brucker, L.; Miller, J. A.

    2017-12-01

    Sea ice concentration is an essential climate variable and passive microwave derived estimates of concentration are one of the longest satellite-derived climate records. However, until recently uncertainty estimates were not provided. Numerous validation studies provided insight into general error characteristics, but the studies have found that concentration error varied greatly depending on sea ice conditions. Thus, an uncertainty estimate from each observation is desired, particularly for initialization, assimilation, and validation of models. Here we investigate three sea ice products that include an uncertainty for each concentration estimate: the NASA Team 2 algorithm product, the EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI-SAF) product, and the NOAA/NSIDC Climate Data Record (CDR) product. Each product estimates uncertainty with a completely different approach. The NASA Team 2 product derives uncertainty internally from the algorithm method itself. The OSI-SAF uses atmospheric reanalysis fields and a radiative transfer model. The CDR uses spatial variability from two algorithms. Each approach has merits and limitations. Here we evaluate the uncertainty estimates by comparing the passive microwave concentration products with fields derived from the NOAA VIIRS sensor. The results show that the relationship between the product uncertainty estimates and the concentration error (relative to VIIRS) is complex. This may be due to the sea ice conditions, the uncertainty methods, as well as the spatial and temporal variability of the passive microwave and VIIRS products.

  8. Uncertainty propagation and sensitivity analysis in system reliability assessment via unscented transformation

    International Nuclear Information System (INIS)

    Rocco Sanseverino, Claudio M.; Ramirez-Marquez, José Emmanuel

    2014-01-01

    The reliability of a system, notwithstanding it intended function, can be significantly affected by the uncertainty in the reliability estimate of the components that define the system. This paper implements the Unscented Transformation to quantify the effects of the uncertainty of component reliability through two approaches. The first approach is based on the concept of uncertainty propagation, which is the assessment of the effect that the variability of the component reliabilities produces on the variance of the system reliability. This assessment based on UT has been previously considered in the literature but only for system represented through series/parallel configuration. In this paper the assessment is extended to systems whose reliability cannot be represented through analytical expressions and require, for example, Monte Carlo Simulation. The second approach consists on the evaluation of the importance of components, i.e., the evaluation of the components that most contribute to the variance of the system reliability. An extension of the UT is proposed to evaluate the so called “main effects” of each component, as well to assess high order component interaction. Several examples with excellent results illustrate the proposed approach. - Highlights: • Simulation based approach for computing reliability estimates. • Computation of reliability variance via 2n+1 points. • Immediate computation of component importance. • Application to network systems

  9. A Conceptual Methodology for Assessing Acquisition Requirements Robustness against Technology Uncertainties

    Science.gov (United States)

    Chou, Shuo-Ju

    2011-12-01

    In recent years the United States has shifted from a threat-based acquisition policy that developed systems for countering specific threats to a capabilities-based strategy that emphasizes the acquisition of systems that provide critical national defense capabilities. This shift in policy, in theory, allows for the creation of an "optimal force" that is robust against current and future threats regardless of the tactics and scenario involved. In broad terms, robustness can be defined as the insensitivity of an outcome to "noise" or non-controlled variables. Within this context, the outcome is the successful achievement of defense strategies and the noise variables are tactics and scenarios that will be associated with current and future enemies. Unfortunately, a lack of system capability, budget, and schedule robustness against technology performance and development uncertainties has led to major setbacks in recent acquisition programs. This lack of robustness stems from the fact that immature technologies have uncertainties in their expected performance, development cost, and schedule that cause to variations in system effectiveness and program development budget and schedule requirements. Unfortunately, the Technology Readiness Assessment process currently used by acquisition program managers and decision-makers to measure technology uncertainty during critical program decision junctions does not adequately capture the impact of technology performance and development uncertainty on program capability and development metrics. The Technology Readiness Level metric employed by the TRA to describe program technology elements uncertainties can only provide a qualitative and non-descript estimation of the technology uncertainties. In order to assess program robustness, specifically requirements robustness, against technology performance and development uncertainties, a new process is needed. This process should provide acquisition program managers and decision

  10. Assessment of Measurement Uncertainty Values of the Scandium Determination in Marine Sediment

    International Nuclear Information System (INIS)

    Rina-Mulyaningsih, Th.

    2005-01-01

    The result value of testing is meaningless if it isn't completed with uncertainty value. So that with the analysis result Sc in the marine sediment sample. It was assessed the uncertainty measurement of Sc analysis in marine sediment. The experiment was done in AAN Serpong laboratory. The result of calculation uncertainty on Sc analysis showed that the uncertainty components come from: preparation of sample and standard/comparator, purity of standard, counting statistics (sample and standard), repeatability, nuclear data and decay correction. The assessment on uncertainty must be done for the analysis of others elements, because each elements has difference nuclear and physical properties. (author)

  11. Assessment of global phase uncertainty in case-control studies

    Directory of Open Access Journals (Sweden)

    van Houwelingen Hans C

    2009-09-01

    Full Text Available Abstract Background In haplotype-based candidate gene studies a problem is that the genotype data are unphased, which results in haplotype ambiguity. The measure 1 quantifies haplotype predictability from genotype data. It is computed for each individual haplotype, and for a measure of global relative efficiency a minimum value is suggested. Alternatively, we developed methods directly based on the information content of haplotype frequency estimates to obtain global relative efficiency measures: and based on A- and D-optimality, respectively. All three methods are designed for single populations; they can be applied in cases only, controls only or the whole data. Therefore they are not necessarily optimal for haplotype testing in case-control studies. Results A new global relative efficiency measure was derived to maximize power of a simple test statistic that compares haplotype frequencies in cases and controls. Application to real data showed that our proposed method gave a clear and summarizing measure for the case-control study conducted. Additionally this measure might be used for selection of individuals, who have the highest potential for improving power by resolving phase ambiguity. Conclusion Instead of using relative efficiency measure for cases only, controls only or their combined data, we link uncertainty measure to case-control studies directly. Hence, our global efficiency measure might be useful to assess whether data are informative or have enough power for estimation of a specific haplotype risk.

  12. 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.

  13. Effect of Uncertainties in Physical Property Estimates on Process Design - Sensitivity Analysis

    DEFF Research Database (Denmark)

    Hukkerikar, Amol; Jones, Mark Nicholas; Sin, Gürkan

    for performing sensitivity of process design subject to uncertainties in the property estimates. To this end, first uncertainty analysis of the property models of pure components and their mixtures was performed in order to obtain the uncertainties in the estimated property values. As a next step, sensitivity......Chemical process design calculations require accurate and reliable physical and thermodynamic property data and property models of pure components and their mixtures in order to obtain reliable design parameters which help to achieve desired specifications. The uncertainties in the property values...... can arise from the experiments itself or from the property models employed. It is important to consider the effect of these uncertainties on the process design in order to assess the quality and reliability of the final design. The main objective of this work is to develop a systematic methodology...

  14. Sensitivity, uncertainty assessment, and target accuracies related to radiotoxicity evaluation

    International Nuclear Information System (INIS)

    Palmiotti, G.; Salvatores, M.; Hill, R.N.

    1994-01-01

    Time-dependent sensitivity techniques, which have been used in the past for standard reactor applications, are adapted to calculate the impact of data uncertainties and to estimate target data accuracies in radiotoxicity evaluations. The methodology is applied to different strategies of radioactive waste management connected with the European Fast Reactor and the Integral Fast Reactor fuel cycles. Results are provided in terms of sensitivity coefficients of basic data (cross sections and decay constants), uncertainties of global radiotoxicity at different times of storing after discharge, and target data accuracies needed to satisfy maximum uncertainty limits

  15. 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

  16. Probabilistic accident consequence uncertainty analysis: Dispersion and deposition uncertainty assessment, main report

    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, was completed in 1990. These codes 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 ultimate objective of the joint effort was to develop credible and traceable uncertainty distributions for the input variables of the codes. Expert elicitation 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. Experts developed their distributions independently. 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. Resulting distributions closely replicated the aggregated elicited wet deposition distributions. To validate the distributions generated for the dispersion code input variables, samples from the distributions and propagated through the Gaussian plume model (GPM) implemented in the MACCS and COSYMA codes. 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 first of a three-volume document describing the project

  17. 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.

  18. Adult head CT scans: the uncertainties of effective dose estimates

    International Nuclear Information System (INIS)

    Gregory, Kent J.; Bibbo, Giovanni; Pattison, John E.

    2008-01-01

    Full Text: CT scanning is a high dose imaging modality. Effective dose estimates from CT scans can provide important information to patients and medical professionals. For example, medical practitioners can use the dose to estimate the risk to the patient, and judge whether this risk is outweighed by the benefits of the CT examination, while radiographers can gauge the effect of different scanning protocols on the patient effective dose, and take this into consideration when establishing routine scan settings. Dose estimates also form an important part of epidemiological studies examining the health effects of medical radiation exposures on the wider population. Medical physicists have been devoting significant effort towards estimating patient radiation doses from diagnostic CT scans for some years. The question arises: How accurate are these effective dose estimates? The need for a greater understanding and improvement of the uncertainties in CT dose estimates is now gaining recognition as an important issue (BEIR VII 2006). This study is an attempt to analyse and quantify the uncertainty components relating to effective dose estimates from adult head CT examinations that are calculated with four commonly used methods. The dose estimation methods analysed are the Nagel method, the ImpaCT method, the Wellhoefer method and the Dose-Length Product (DLP) method. The analysis of the uncertainties was performed in accordance with the International Standards Organisation's Guide to the Expression of Uncertainty in Measurement as discussed in Gregory et al (Australas. Phys. Eng. Sci. Med., 28: 131-139, 2005). The uncertainty components vary, depending on the method used to derive the effective dose estimate. Uncertainty components in this study include the statistical and other errors from Monte Carlo simulations, uncertainties in the CT settings and positions of patients in the CT gantry, calibration errors from pencil ionization chambers, the variations in the organ

  19. Probabilistic accident consequence uncertainty analysis -- Uncertainty assessment for deposited material and external doses. Volume 2: Appendices

    Energy Technology Data Exchange (ETDEWEB)

    Goossens, L.H.J.; Kraan, B.C.P.; Cooke, R.M. [Delft Univ. of Technology (Netherlands); Boardman, J. [AEA Technology (United Kingdom); Jones, J.A. [National Radiological Protection Board (United Kingdom); Harper, F.T.; Young, M.L. [Sandia National Labs., Albuquerque, NM (United States); Hora, S.C. [Univ. of Hawaii, Hilo, HI (United States)

    1997-12-01

    The development of two new probabilistic accident consequence codes, MACCS and COSYMA, was completed in 1990. These codes estimate the consequence from the accidental releases of radiological material from hypothesized accidents at nuclear installations. In 1991, the US Nuclear Regulatory Commission and the Commission of the European Communities began cosponsoring a joint uncertainty analysis of the two codes. The ultimate objective of this joint effort was to systematically develop credible and traceable uncertainty distributions for the respective code input variables. A formal expert judgment elicitation and evaluation process was identified as the best technology available for developing a library of uncertainty distributions for these consequence parameters. This report focuses on the results of the study to develop distribution for variables related to the MACCS and COSYMA deposited material and external dose models. This volume contains appendices that include (1) a summary of the MACCS and COSYMA consequence codes, (2) the elicitation questionnaires and case structures, (3) the rationales and results for the panel on deposited material and external doses, (4) short biographies of the experts, and (5) the aggregated results of their responses.

  20. Probabilistic accident consequence uncertainty analysis -- Uncertainty assessment for internal dosimetry. Volume 2: Appendices

    Energy Technology Data Exchange (ETDEWEB)

    Goossens, L.H.J.; Kraan, B.C.P.; Cooke, R.M. [Delft Univ. of Technology (Netherlands); Harrison, J.D. [National Radiological Protection Board (United Kingdom); Harper, F.T. [Sandia National Labs., Albuquerque, NM (United States); Hora, S.C. [Univ. of Hawaii, Hilo, HI (United States)

    1998-04-01

    The development of two new probabilistic accident consequence codes, MACCS and COSYMA, was completed in 1990. These codes estimate the consequence from the accidental releases of radiological material from hypothesized accidents at nuclear installations. In 1991, the US Nuclear Regulatory Commission and the Commission of the European Communities began cosponsoring a joint uncertainty analysis of the two codes. The ultimate objective of this joint effort was to systematically develop credible and traceable uncertainty distributions for the respective code input variables. A formal expert judgment elicitation and evaluation process was identified as the best technology available for developing a library of uncertainty distributions for these consequence parameters. This report focuses on the results of the study to develop distribution for variables related to the MACCS and COSYMA internal dosimetry models. This volume contains appendices that include (1) a summary of the MACCS and COSYMA consequence codes, (2) the elicitation questionnaires and case structures, (3) the rationales and results for the panel on internal dosimetry, (4) short biographies of the experts, and (5) the aggregated results of their responses.

  1. On-orbit servicing system assessment and optimization methods based on lifecycle simulation under mixed aleatory and epistemic uncertainties

    Science.gov (United States)

    Yao, Wen; Chen, Xiaoqian; Huang, Yiyong; van Tooren, Michel

    2013-06-01

    To assess the on-orbit servicing (OOS) paradigm and optimize its utilities by taking advantage of its inherent flexibility and responsiveness, the OOS system assessment and optimization methods based on lifecycle simulation under uncertainties are studied. The uncertainty sources considered in this paper include both the aleatory (random launch/OOS operation failure and on-orbit component failure) and the epistemic (the unknown trend of the end-used market price) types. Firstly, the lifecycle simulation under uncertainties is discussed. The chronological flowchart is presented. The cost and benefit models are established, and the uncertainties thereof are modeled. The dynamic programming method to make optimal decision in face of the uncertain events is introduced. Secondly, the method to analyze the propagation effects of the uncertainties on the OOS utilities is studied. With combined probability and evidence theory, a Monte Carlo lifecycle Simulation based Unified Uncertainty Analysis (MCS-UUA) approach is proposed, based on which the OOS utility assessment tool under mixed uncertainties is developed. Thirdly, to further optimize the OOS system under mixed uncertainties, the reliability-based optimization (RBO) method is studied. To alleviate the computational burden of the traditional RBO method which involves nested optimum search and uncertainty analysis, the framework of Sequential Optimization and Mixed Uncertainty Analysis (SOMUA) is employed to integrate MCS-UUA, and the RBO algorithm SOMUA-MCS is developed. Fourthly, a case study on the OOS system for a hypothetical GEO commercial communication satellite is investigated with the proposed assessment tool. Furthermore, the OOS system is optimized with SOMUA-MCS. Lastly, some conclusions are given and future research prospects are highlighted.

  2. A Bayesian belief network approach for assessing uncertainty in conceptual site models at contaminated sites

    Science.gov (United States)

    Thomsen, Nanna I.; Binning, Philip J.; McKnight, Ursula S.; Tuxen, Nina; Bjerg, Poul L.; Troldborg, Mads

    2016-05-01

    A key component in risk assessment of contaminated sites is in the formulation of a conceptual site model (CSM). A CSM is a simplified representation of reality and forms the basis for the mathematical modeling of contaminant fate and transport at the site. The CSM should therefore identify the most important site-specific features and processes that may affect the contaminant transport behavior at the site. However, the development of a CSM will always be associated with uncertainties due to limited data and lack of understanding of the site conditions. CSM uncertainty is often found to be a major source of model error and it should therefore be accounted for when evaluating uncertainties in risk assessments. We present a Bayesian belief network (BBN) approach for constructing CSMs and assessing their uncertainty at contaminated sites. BBNs are graphical probabilistic models that are effective for integrating quantitative and qualitative information, and thus can strengthen decisions when empirical data are lacking. The proposed BBN approach facilitates a systematic construction of multiple CSMs, and then determines the belief in each CSM using a variety of data types and/or expert opinion at different knowledge levels. The developed BBNs combine data from desktop studies and initial site investigations with expert opinion to assess which of the CSMs are more likely to reflect the actual site conditions. The method is demonstrated on a Danish field site, contaminated with chlorinated ethenes. Four different CSMs are developed by combining two contaminant source zone interpretations (presence or absence of a separate phase contamination) and two geological interpretations (fractured or unfractured clay till). The beliefs in each of the CSMs are assessed sequentially based on data from three investigation stages (a screening investigation, a more detailed investigation, and an expert consultation) to demonstrate that the belief can be updated as more information

  3. Cost-effective conservation of an endangered frog under uncertainty.

    Science.gov (United States)

    Rose, Lucy E; Heard, Geoffrey W; Chee, Yung En; Wintle, Brendan A

    2016-04-01

    How should managers choose among conservation options when resources are scarce and there is uncertainty regarding the effectiveness of actions? Well-developed tools exist for prioritizing areas for one-time and binary actions (e.g., protect vs. not protect), but methods for prioritizing incremental or ongoing actions (such as habitat creation and maintenance) remain uncommon. We devised an approach that combines metapopulation viability and cost-effectiveness analyses to select among alternative conservation actions while accounting for uncertainty. In our study, cost-effectiveness is the ratio between the benefit of an action and its economic cost, where benefit is the change in metapopulation viability. We applied the approach to the case of the endangered growling grass frog (Litoria raniformis), which is threatened by urban development. We extended a Bayesian model to predict metapopulation viability under 9 urbanization and management scenarios and incorporated the full probability distribution of possible outcomes for each scenario into the cost-effectiveness analysis. This allowed us to discern between cost-effective alternatives that were robust to uncertainty and those with a relatively high risk of failure. We found a relatively high risk of extinction following urbanization if the only action was reservation of core habitat; habitat creation actions performed better than enhancement actions; and cost-effectiveness ranking changed depending on the consideration of uncertainty. Our results suggest that creation and maintenance of wetlands dedicated to L. raniformis is the only cost-effective action likely to result in a sufficiently low risk of extinction. To our knowledge we are the first study to use Bayesian metapopulation viability analysis to explicitly incorporate parametric and demographic uncertainty into a cost-effective evaluation of conservation actions. The approach offers guidance to decision makers aiming to achieve cost-effective

  4. Area 2: Inexpensive Monitoring and Uncertainty Assessment of CO2 Plume Migration using Injection Data

    Energy Technology Data Exchange (ETDEWEB)

    Srinivasan, Sanjay [Univ. of Texas, Austin, TX (United States)

    2014-09-30

    In-depth understanding of the long-term fate of CO₂ in the subsurface requires study and analysis of the reservoir formation, the overlaying caprock formation, and adjacent faults. Because there is significant uncertainty in predicting the location and extent of geologic heterogeneity that can impact the future migration of CO₂ in the subsurface, there is a need to develop algorithms that can reliably quantify this uncertainty in plume migration. This project is focused on the development of a model selection algorithm that refines an initial suite of subsurface models representing the prior uncertainty to create a posterior set of subsurface models that reflect injection performance consistent with that observed. Such posterior models can be used to represent uncertainty in the future migration of the CO₂ plume. Because only injection data is required, the method provides a very inexpensive method to map the migration of the plume and the associated uncertainty in migration paths. The model selection method developed as part of this project mainly consists of assessing the connectivity/dynamic characteristics of a large prior ensemble of models, grouping the models on the basis of their expected dynamic response, selecting the subgroup of models that most closely yield dynamic response closest to the observed dynamic data, and finally quantifying the uncertainty in plume migration using the selected subset of models. The main accomplishment of the project is the development of a software module within the SGEMS earth modeling software package that implements the model selection methodology. This software module was subsequently applied to analyze CO₂ plume migration in two field projects – the In Salah CO₂ Injection project in Algeria and CO₂ injection into the Utsira formation in Norway. These applications of the software revealed that the proxies developed in this project for quickly assessing the dynamic characteristics of the reservoir were

  5. Particle Dark Matter constraints: the effect of Galactic uncertainties

    Energy Technology Data Exchange (ETDEWEB)

    Benito, Maria; Bernal, Nicolás; Iocco, Fabio [ICTP South American Institute for Fundamental Research Instituto de Física Teórica - Universidade Estadual Paulista (UNESP) Rua Dr. Bento Teobaldo Ferraz 271, 01140-070 São Paulo, SP Brazil (Brazil); Bozorgnia, Nassim; Calore, Francesca, E-mail: mariabenitocst@gmail.com, E-mail: nicolas.bernal@uan.edu.co, E-mail: n.bozorgnia@uva.nl, E-mail: calore@lapth.cnrs.fr, E-mail: fabio.iocco.astro@gmail.com [GRAPPA Institute, Institute for Theoretical Physics Amsterdam and Delta Institute for Theoretical Physics, University of Amsterdam, Science Park 904, 1098 XH Amsterdam (Netherlands)

    2017-02-01

    Collider, space, and Earth based experiments are now able to probe several extensions of the Standard Model of particle physics which provide viable dark matter candidates. Direct and indirect dark matter searches rely on inputs of astrophysical nature, such as the local dark matter density or the shape of the dark matter density profile in the target in object. The determination of these quantities is highly affected by astrophysical uncertainties. The latter, especially those for our own Galaxy, are ill-known, and often not fully accounted for when analyzing the phenomenology of particle physics models. In this paper we present a systematic, quantitative estimate of how astrophysical uncertainties on Galactic quantities (such as the local galactocentric distance, circular velocity, or the morphology of the stellar disk and bulge) propagate to the determination of the phenomenology of particle physics models, thus eventually affecting the determination of new physics parameters. We present results in the context of two specific extensions of the Standard Model (the Singlet Scalar and the Inert Doublet) that we adopt as case studies for their simplicity in illustrating the magnitude and impact of such uncertainties on the parameter space of the particle physics model itself. Our findings point toward very relevant effects of current Galactic uncertainties on the determination of particle physics parameters, and urge a systematic estimate of such uncertainties in more complex scenarios, in order to achieve constraints on the determination of new physics that realistically include all known uncertainties.

  6. Decoherence effect on quantum-memory-assisted entropic uncertainty relations

    Science.gov (United States)

    Ming, Fei; Wang, Dong; Huang, Ai-Jun; Sun, Wen-Yang; Ye, Liu

    2018-01-01

    Uncertainty principle significantly provides a bound to predict precision of measurement with regard to any two incompatible observables, and thereby plays a nontrivial role in quantum precision measurement. In this work, we observe the dynamical features of the quantum-memory-assisted entropic uncertainty relations (EUR) for a pair of incompatible measurements in an open system characterized by local generalized amplitude damping (GAD) noises. Herein, we derive the dynamical evolution of the entropic uncertainty with respect to the measurement affecting by the canonical GAD noises when particle A is initially entangled with quantum memory B. Specifically, we examine the dynamics of EUR in the frame of three realistic scenarios: one case is that particle A is affected by environmental noise (GAD) while particle B as quantum memory is free from any noises, another case is that particle B is affected by the external noise while particle A is not, and the last case is that both of the particles suffer from the noises. By analytical methods, it turns out that the uncertainty is not full dependent of quantum correlation evolution of the composite system consisting of A and B, but the minimal conditional entropy of the measured subsystem. Furthermore, we present a possible physical interpretation for the behavior of the uncertainty evolution by means of the mixedness of the observed system; we argue that the uncertainty might be dramatically correlated with the systematic mixedness. Furthermore, we put forward a simple and effective strategy to reduce the measuring uncertainty of interest upon quantum partially collapsed measurement. Therefore, our explorations might offer an insight into the dynamics of the entropic uncertainty relation in a realistic system, and be of importance to quantum precision measurement during quantum information processing.

  7. Effects of utility demand-side management programs on uncertainty

    International Nuclear Information System (INIS)

    Hirst, E.

    1994-01-01

    Electric utilities face a variety of uncertainties that complicate their long-term resource planning. These uncertainties include future economic and load growths, fuel prices, environmental and economic regulations, performance of existing power plants, cost and availability of purchased power, and the costs and performance of new demand and supply resources. As utilities increasingly turn to demand-side management (DSM) programs to provide resources, it becomes more important to analyze the interactions between these programs and the uncertainties facing utilities. This paper uses a dynamic planning model to quantify the uncertainty effects of supply-only vs DSM + supply resource portfolios. The analysis considers four sets of uncertainties: economic growth, fuel prices, the costs to build new power plants, and the costs to operate DSM programs. The two types of portfolios are tested against these four sets of uncertainties for the period 1990 to 2010. Sensitivity, scenario, and worst-case analysis methods are used. The sensitivity analyses show that the DSM + supply resource portfolio is less sensitive to unanticipated changes in economic growth, fuel prices, and power-plant construction costs than is the supply-only portfolio. The supply-only resource mix is better only with respect to uncertainties about the costs of DSM programs. The base-case analysis shows that including DSM programs in the utility's resource portfolio reduces the net present value of revenue requirements (NPV-RR) by 490 million dollars. The scenario-analysis results show an additional 30 million dollars (6%) in benefits associated with reduction in these uncertainties. In the worst-case analysis, the DSM + supply portfolio again reduces the cost penalty associated with guessing wrong for both cases, when the utility plans for high needs and learns it has low needs and vice versa. 20 refs

  8. Assessing the Expected Value of Research Studies in Reducing Uncertainty and Improving Implementation Dynamics.

    Science.gov (United States)

    Grimm, Sabine E; Dixon, Simon; Stevens, John W

    2017-07-01

    With low implementation of cost-effective health technologies being a problem in many health systems, it is worth considering the potential effects of research on implementation at the time of health technology assessment. Meaningful and realistic implementation estimates must be of dynamic nature. To extend existing methods for assessing the value of research studies in terms of both reduction of uncertainty and improvement in implementation by considering diffusion based on expert beliefs with and without further research conditional on the strength of evidence. We use expected value of sample information and expected value of specific implementation measure concepts accounting for the effects of specific research studies on implementation and the reduction of uncertainty. Diffusion theory and elicitation of expert beliefs about the shape of diffusion curves inform implementation dynamics. We illustrate use of the resulting dynamic expected value of research in a preterm birth screening technology and results are compared with those from a static analysis. Allowing for diffusion based on expert beliefs had a significant impact on the expected value of research in the case study, suggesting that mistakes are made where static implementation levels are assumed. Incorporating the effects of research on implementation resulted in an increase in the expected value of research compared to the expected value of sample information alone. Assessing the expected value of research in reducing uncertainty and improving implementation dynamics has the potential to complement currently used analyses in health technology assessments, especially in recommendations for further research. The combination of expected value of research, diffusion theory, and elicitation described in this article is an important addition to the existing methods of health technology assessment.

  9. Effect of matrix cracking and material uncertainty on composite plates

    International Nuclear Information System (INIS)

    Gayathri, P.; Umesh, K.; Ganguli, R.

    2010-01-01

    A laminated composite plate model based on first order shear deformation theory is implemented using the finite element method. Matrix cracks are introduced into the finite element model by considering changes in the A, B and D matrices of composites. The effects of different boundary conditions, laminate types and ply angles on the behavior of composite plates with matrix cracks are studied. Finally, the effect of material property uncertainty, which is important for composite material on the composite plate, is investigated using Monte Carlo simulations. Probabilistic estimates of damage detection reliability in composite plates are made for static and dynamic measurements. It is found that the effect of uncertainty must be considered for accurate damage detection in composite structures. The estimates of variance obtained for observable system properties due to uncertainty can be used for developing more robust damage detection algorithms.

  10. Analysis of uncertainties caused by the atmospheric dispersion model in accident consequence assessments with UFOMOD

    International Nuclear Information System (INIS)

    Fischer, F.; Ehrhardt, J.

    1988-06-01

    Various techniques available for uncertainty analysis of large computer models are applied, described and selected as most appropriate for analyzing the uncertainty in the predictions of accident consequence assessments. The investigation refers to the atmospheric dispersion and deposition submodel (straight-line Gaussian plume model) of UFOMOD, whose most important input variables and parameters are linked with probability distributions derived from expert judgement. Uncertainty bands show how much variability exists, sensitivity measures determine what causes this variability in consequences. Results are presented as confidence bounds of complementary cumulative frequency distributions (CCFDs) of activity concentrations, organ doses and health effects, partially as a function of distance from the site. In addition the ranked influence of the uncertain parameters on the different consequence types is shown. For the estimation of confidence bounds it was sufficient to choose a model parameter sample size of n (n=59) equal to 1.5 times the number of uncertain model parameters. Different samples or an increase of sample size did not change the 5%-95% - confidence bands. To get statistically stable results of the sensitivity analysis, larger sample sizes are needed (n=100, 200). Random or Latin-hypercube sampling schemes as tools for uncertainty and sensitivity analyses led to comparable results. (orig.) [de

  11. Effect of precipitation spatial distribution uncertainty on the uncertainty bounds of a snowmelt runoff model output

    Science.gov (United States)

    Jacquin, A. P.

    2012-04-01

    This study analyses the effect of precipitation spatial distribution uncertainty on the uncertainty bounds of a snowmelt runoff model's discharge estimates. Prediction uncertainty bounds are derived using the Generalized Likelihood Uncertainty Estimation (GLUE) methodology. The model analysed is a conceptual watershed model operating at a monthly time step. The model divides the catchment into five elevation zones, where the fifth zone corresponds to the catchment glaciers. Precipitation amounts at each elevation zone i are estimated as the product between observed precipitation (at a single station within the catchment) and a precipitation factor FPi. Thus, these factors provide a simplified representation of the spatial variation of precipitation, specifically the shape of the functional relationship between precipitation and height. In the absence of information about appropriate values of the precipitation factors FPi, these are estimated through standard calibration procedures. The catchment case study is Aconcagua River at Chacabuquito, located in the Andean region of Central Chile. Monte Carlo samples of the model output are obtained by randomly varying the model parameters within their feasible ranges. In the first experiment, the precipitation factors FPi are considered unknown and thus included in the sampling process. The total number of unknown parameters in this case is 16. In the second experiment, precipitation factors FPi are estimated a priori, by means of a long term water balance between observed discharge at the catchment outlet, evapotranspiration estimates and observed precipitation. In this case, the number of unknown parameters reduces to 11. The feasible ranges assigned to the precipitation factors in the first experiment are slightly wider than the range of fixed precipitation factors used in the second experiment. The mean squared error of the Box-Cox transformed discharge during the calibration period is used for the evaluation of the

  12. A Bayesian Meta-Analysis of the Effect of Alcohol Use on HCV-Treatment Outcomes with a Comparison of Resampling Methods to Assess Uncertainty in Parameter Estimates.

    Energy Technology Data Exchange (ETDEWEB)

    Cauthen, Katherine Regina [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Lambert, Gregory Joseph [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Finley, Patrick D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Ross, David [US Dept. of Veterans Affairs, Washington, DC (United States); Chartier, Maggie [US Dept. of Veterans Affairs, Washington, DC (United States); Davey, Victoria J. [US Dept. of Veterans Affairs, Washington, DC (United States)

    2015-10-01

    There is mounting evidence that alcohol use is significantly linked to lower HCV treatment response rates in interferon-based therapies, though some of the evidence is conflicting. Furthermore, although health care providers recommend reducing or abstaining from alcohol use prior to treatment, many patients do not succeed in doing so. The goal of this meta-analysis was to systematically review and summarize the Englishlanguage literature up through January 30, 2015 regarding the relationship between alcohol use and HCV treatment outcomes, among patients who were not required to abstain from alcohol use in order to receive treatment. Seven pertinent articles studying 1,751 HCV-infected patients were identified. Log-ORs of HCV treatment response for heavy alcohol use and light alcohol use were calculated and compared. We employed a hierarchical Bayesian meta-analytic model to accommodate the small sample size. The summary estimate for the log-OR of HCV treatment response was -0.775 with a 95% credible interval of (-1.397, -0.236). The results of the Bayesian meta-analysis are slightly more conservative compared to those obtained from a boot-strapped, random effects model. We found evidence of heterogeneity (Q = 14.489, p = 0.025), accounting for 60.28% of the variation among log-ORs. Meta-regression to capture the sources of this heterogeneity did not identify any of the covariates investigated as significant. This meta-analysis confirms that heavy alcohol use is associated with decreased HCV treatment response compared to lighter levels of alcohol use. Further research is required to characterize the mechanism by which alcohol use affects HCV treatment response.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2018-02-09

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

  14. 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

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

    Energy Technology Data Exchange (ETDEWEB)

    Coleou, Thierry

    1998-12-31

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

  16. Status of uncertainty assessment in k0-NAA measurement. Anything still missing?

    International Nuclear Information System (INIS)

    Borut Smodis; Tinkara Bucar

    2014-01-01

    Several approaches to quantifying measurement uncertainty in k 0 -based neutron activation analysis (k 0 -NAA) are reviewed, comprising the original approach, the spreadsheet approach, the dedicated computer program involving analytical calculations and the two k 0 -NAA programs available on the market. Two imperfectness in the dedicated programs are identified, their impact assessed and possible improvements presented for a concrete experimental situation. The status of uncertainty assessment in k 0 -NAA is discussed and steps for improvement are recommended. It is concluded that the present magnitude of measurement uncertainty should further be improved by making additional efforts in reducing uncertainties of the relevant nuclear constants used. (author)

  17. Uncertainty Assessment of Space-Borne Passive Soil Moisture Retrievals

    Science.gov (United States)

    Quets, Jan; De Lannoy, Gabrielle; Reichle, Rolf; Cosh, Michael; van der Schalie, Robin; Wigneron, Jean-Pierre

    2017-01-01

    The uncertainty associated with passive soil moisture retrieval is hard to quantify, and known to be underlain by various, diverse, and complex causes. Factors affecting space-borne retrieved soil moisture estimation include: (i) the optimization or inversion method applied to the radiative transfer model (RTM), such as e.g. the Single Channel Algorithm (SCA), or the Land Parameter Retrieval Model (LPRM), (ii) the selection of the observed brightness temperatures (Tbs), e.g. polarization and incidence angle, (iii) the definition of the cost function and the impact of prior information in it, and (iv) the RTM parameterization (e.g. parameterizations officially used by the SMOS L2 and SMAP L2 retrieval products, ECMWF-based SMOS assimilation product, SMAP L4 assimilation product, and perturbations from those configurations). This study aims at disentangling the relative importance of the above-mentioned sources of uncertainty, by carrying out soil moisture retrieval experiments, using SMOS Tb observations in different settings, of which some are mentioned above. The ensemble uncertainties are evaluated at 11 reference CalVal sites, over a time period of more than 5 years. These experimental retrievals were inter-compared, and further confronted with in situ soil moisture measurements and operational SMOS L2 retrievals, using commonly used skill metrics to quantify the temporal uncertainty in the retrievals.

  18. Uncertainty Assessment of Hydrological Frequency Analysis Using Bootstrap Method

    Directory of Open Access Journals (Sweden)

    Yi-Ming Hu

    2013-01-01

    Full Text Available The hydrological frequency analysis (HFA is the foundation for the hydraulic engineering design and water resources management. Hydrological extreme observations or samples are the basis for HFA; the representativeness of a sample series to the population distribution is extremely important for the estimation reliability of the hydrological design value or quantile. However, for most of hydrological extreme data obtained in practical application, the size of the samples is usually small, for example, in China about 40~50 years. Generally, samples with small size cannot completely display the statistical properties of the population distribution, thus leading to uncertainties in the estimation of hydrological design values. In this paper, a new method based on bootstrap is put forward to analyze the impact of sampling uncertainty on the design value. By bootstrap resampling technique, a large number of bootstrap samples are constructed from the original flood extreme observations; the corresponding design value or quantile is estimated for each bootstrap sample, so that the sampling distribution of design value is constructed; based on the sampling distribution, the uncertainty of quantile estimation can be quantified. Compared with the conventional approach, this method provides not only the point estimation of a design value but also quantitative evaluation on uncertainties of the estimation.

  19. Uncertainty Assessment in Long Term Urban Drainage Modelling

    DEFF Research Database (Denmark)

    Thorndahl, Søren

    the probability of system failures (defined as either flooding or surcharge of manholes or combined sewer overflow); (2) an application of the Generalized Likelihood Uncertainty Estimation methodology in which an event based stochastic calibration is performed; and (3) long term Monte Carlo simulations...

  20. A review of the uncertainties in the assessment of radiological consequences of spent nuclear fuel disposal

    International Nuclear Information System (INIS)

    Wiborgh, M.; Elert, M.; Hoeglund, L.O.; Jones, C.; Grundfelt, B.; Skagius, K.; Bengtsson, A.

    1992-06-01

    Radioactive waste disposal systems for spent nuclear fuel are designed to isolate the radioactive waste from the human environment for long period of time. The isolation is provided by a combination of engineered and natural barriers. Safety assessments are performed to describe and quantify the performance of the individual barriers and the disposal system over long-term periods. These assessments will always be associated with uncertainties. Uncertainties can originate from the variability of natural systems and will also be introduced in the predictive modelling performed to quantitatively evaluate the behaviour of the disposal system as a consequence of the incomplete knowledge about the governing processes. Uncertainties in safety assessments can partly be reduced by additional measurements and research. The aim of this study has been to identify uncertainties in assessments of radiological consequences from the disposal of spent nuclear fuel based on the Swedish KBS-3 concept. The identified uncertainties have been classified with respect to their origin, i.e. in conceptual, modelling and data uncertainties. The possibilities to reduce the uncertainties are also commented upon. In assessments it is important to decrease uncertainties which are of major importance for the performance of the disposal system. These could to some extent be identified by uncertainty analysis. However, conceptual uncertainties and some type of model uncertainties are difficult to evaluate. To be able to decrease uncertainties in conceptual models, it is essential that the processes describing and influencing the radionuclide transport in the engineered and natural barriers are sufficiently understood. In this study a qualitative approach has been used. The importance of different barriers and processes are indicated by their influence on the release of some representative radionuclides. (122 refs.) (au)

  1. A review of the uncertainties in internal radiation dose assessment for inhaled thorium

    International Nuclear Information System (INIS)

    Hewson, G.S.

    1989-01-01

    Present assessments of internal radiation dose to designated radiation workers in the mineral sands industry, calculated using ICRP 26/30 methodology and data, indicate that some workers approach and exceed statutory radiation dose limits. Such exposures are indicative of the need for a critical assessment of work and operational procedures and also of metabolic and dosimetric models used to estimate internal dose. This paper reviews past occupational exposure experience with inhaled thorium compounds, examines uncertainties in the underlying radiation protection models, and indicates the effect of alternative assumptions on the calculation of committed effective dose equivalent. The extremely low recommended inhalation limits for thorium in air do not appear to be well supported by studies on the health status of former thorium refinery workers who were exposed to thorium well in excess of presently accepted limits. The effect of cautious model assumptions is shown to result in internal dose assessments that could be up to an order of magnitude too high. It is concluded that the effect of such uncertainty constrains the usefulness of internal dose estimates as a reliable indicator of actual health risk. 26 refs., 5 figs., 3 tabs

  2. Uncertainty of fast biological radiation dose assessment for emergency response scenarios.

    Science.gov (United States)

    Ainsbury, Elizabeth A; Higueras, Manuel; Puig, Pedro; Einbeck, Jochen; Samaga, Daniel; Barquinero, Joan Francesc; Barrios, Lleonard; Brzozowska, Beata; Fattibene, Paola; Gregoire, Eric; Jaworska, Alicja; Lloyd, David; Oestreicher, Ursula; Romm, Horst; Rothkamm, Kai; Roy, Laurence; Sommer, Sylwester; Terzoudi, Georgia; Thierens, Hubert; Trompier, Francois; Vral, Anne; Woda, Clemens

    2017-01-01

    Reliable dose estimation is an important factor in appropriate dosimetric triage categorization of exposed individuals to support radiation emergency response. Following work done under the EU FP7 MULTIBIODOSE and RENEB projects, formal methods for defining uncertainties on biological dose estimates are compared using simulated and real data from recent exercises. The results demonstrate that a Bayesian method of uncertainty assessment is the most appropriate, even in the absence of detailed prior information. The relative accuracy and relevance of techniques for calculating uncertainty and combining assay results to produce single dose and uncertainty estimates is further discussed. Finally, it is demonstrated that whatever uncertainty estimation method is employed, ignoring the uncertainty on fast dose assessments can have an important impact on rapid biodosimetric categorization.

  3. 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...

  4. Assessing the Feasibility of Managed Aquifer Recharge for Irrigation under Uncertainty

    Directory of Open Access Journals (Sweden)

    Muhammad Arshad

    2014-09-01

    Full Text Available Additional storage of water is a potential option to meet future water supply goals. Financial comparisons are needed to improve decision making about whether to store water in surface reservoirs or below ground, using managed aquifer recharge (MAR. In some places, the results of cost-benefit analysis show that MAR is financially superior to surface storage. However, uncertainty often exists as to whether MAR systems will remain operationally effective and profitable in the future, because the profitability of MAR is dependent on many uncertain technical and financial variables. This paper introduces a method to assess the financial feasibility of MAR under uncertainty. We assess such uncertainties by identification of cross-over points in break-even analysis. Cross-over points are the thresholds where MAR and surface storage have equal financial returns. Such thresholds can be interpreted as a set of minimum requirements beyond which an investment in MAR may no longer be worthwhile. Checking that these thresholds are satisfied can improve confidence in decision making. Our suggested approach can also be used to identify areas that may not be suitable for MAR, thereby avoiding expensive hydrogeological and geophysical investigations.

  5. The Relationship of Cultural Similarity, Communication Effectiveness and Uncertainty Reduction.

    Science.gov (United States)

    Koester, Jolene; Olebe, Margaret

    To investigate the relationship of cultural similarity/dissimilarity, communication effectiveness, and communication variables associated with uncertainty reduction theory, a study examined two groups of students--a multinational group living on an "international floor" in a dormitory at a state university and an unrelated group of U.S.…

  6. The effect of rarity and uncertainty on innovation value

    DEFF Research Database (Denmark)

    Alkærsig, Lars; Beukel, Karin; Lauto, Giancarlo

    This paper addresses the core notions of the Resource Based View, that rarity provides superior performance. We examine the limits of rarity as a driver of performance in the process of innovation. We also claim that uncertainty affects this process, both directly and moderating the effect...

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

    Science.gov (United States)

    2017-12-18

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

  8. Data Quality Assessment of the Uncertainty Analysis Applied to the Greenhouse Gas Emissions of a Dairy Cow System

    Directory of Open Access Journals (Sweden)

    Chun-Youl Baek

    2017-09-01

    Full Text Available The results of an uncertainty analysis are achieved by the statistical information (standard error, type of probability distributions, and range of minimum and maximum of the selected input parameters. However, there are limitations in identifying sufficient data samples for the selected input parameters for statistical information in the field of life cycle assessment (LCA. Therefore, there is a strong need for a consistent screening procedure to identify the input parameters for use in uncertainty analysis in the area of LCA. The conventional procedure for identifying input parameters for the uncertainty analysis method includes assessing the data quality using the pedigree method and the contribution analysis of the LCA results. This paper proposes a simplified procedure for ameliorating the existing data quality assessment method, which can lead to an efficient uncertainly analysis of LCA results. The proposed method has two salient features: (i a simplified procedure based on contribution analysis followed by a data quality assessment for selecting the input parameters for the uncertainty analysis; and (ii a quantitative data quality assessment method is proposed, based on the pedigree method, that adopts the analytic hierarchy process (AHP method and quality function deployment (QFD. The effects of the uncertainty of the selected input parameters on the LCA results were assessed using the Monte Carlo simulation method. A case study of greenhouse gas (GHG emissions from a dairy cow system was used to demonstrate the applicability of the proposed procedure.

  9. Geostatistical modeling of groundwater properties and assessment of their uncertainties

    International Nuclear Information System (INIS)

    Honda, Makoto; Yamamoto, Shinya; Sakurai, Hideyuki; Suzuki, Makoto; Sanada, Hiroyuki; Matsui, Hiroya; Sugita, Yutaka

    2010-01-01

    The distribution of groundwater properties is important for understanding of the deep underground hydrogeological environments. This paper proposes a geostatistical system for modeling the groundwater properties which have a correlation with the ground resistivity data obtained from widespread and exhaustive survey. That is, the methodology for the integration of resistivity data measured by various methods and the methodology for modeling the groundwater properties using the integrated resistivity data has been developed. The proposed system has also been validated using the data obtained in the Horonobe Underground Research Laboratory project. Additionally, the quantification of uncertainties in the estimated model has been tried by numerical simulations based on the data. As a result, the uncertainties of the proposal model have been estimated lower than other traditional model's. (author)

  10. 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

  11. Managing uncertainty in multiple-criteria decision making related to sustainability assessment

    DEFF Research Database (Denmark)

    Dorini, Gianluca Fabio; Kapelan, Zoran; Azapagic, Adisa

    2011-01-01

    In real life, decisions are usually made by comparing different options with respect to several, often conflicting criteria. This requires subjective judgements on the importance of different criteria by DMs and increases uncertainty in decision making. This article demonstrates how uncertainty can......: (1) no uncertainty, (2) uncertainty in data/models and (3) uncertainty in models and decision-makers’ preferences. The results shows how characterising and propagating uncertainty can help increase the effectiveness of multi-criteria decision making processes and lead to more informed decision....... be handled in multi-criteria decision situations using Compromise Programming, one of the Multi-criteria Decision Analysis (MCDA) techniques. Uncertainty is characterised using a probabilistic approach and propagated using a Monte Carlo simulation technique. The methodological approach is illustrated...

  12. Development and evaluation of the feasibility and effects on staff, patients, and families of a new tool, the Psychosocial Assessment and Communication Evaluation (PACE), to improve communication and palliative care in intensive care and during clinical uncertainty.

    Science.gov (United States)

    Higginson, Irene J; Koffman, Jonathan; Hopkins, Philip; Prentice, Wendy; Burman, Rachel; Leonard, Sara; Rumble, Caroline; Noble, Jo; Dampier, Odette; Bernal, William; Hall, Sue; Morgan, Myfanwy; Shipman, Cathy

    2013-10-01

    There are widespread concerns about communication and support for patients and families, especially when they face clinical uncertainty, a situation most marked in intensive care units (ICUs). Therefore, we aimed to develop and evaluate an interventional tool to improve communication and palliative care, using the ICU as an example of where this is difficult. Our design was a phase I-II study following the Medical Research Council Guidance for the Development and Evaluation of Complex Interventions and the (Methods of Researching End-of-life Care (MORECare) statement. In two ICUs, with over 1900 admissions annually, phase I modeled a new intervention comprising implementation training and an assessment tool. We conducted a literature review, qualitative interviews, and focus groups with 40 staff and 13 family members. This resulted in the new tool, the Psychosocial Assessment and Communication Evaluation (PACE). Phase II evaluated the feasibility and effects of PACE, using observation, record audit, and surveys of staff and family members. Qualitative data were analyzed using the framework approach. The statistical tests used on quantitative data were t-tests (for normally distributed characteristics), the χ2 or Fisher's exact test (for non-normally distributed characteristics) and the Mann-Whitney U-test (for experience assessments) to compare the characteristics and experience for cases with and without PACE recorded. PACE provides individualized assessments of all patients entering the ICU. It is completed within 24 to 48 hours of admission, and covers five aspects (key relationships, social details and needs, patient preferences, communication and information status, and other concerns), followed by recording of an ongoing communication evaluation. Implementation is supported by a training program with specialist palliative care. A post-implementation survey of 95 ICU staff found that 89% rated PACE assessment as very or generally useful. Of 213 family members

  13. 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...

  14. Probability and Confidence Trade-space (PACT) Evaluation: Accounting for Uncertainty in Sparing Assessments

    Science.gov (United States)

    Anderson, Leif; Box, Neil; Carter, Katrina; DiFilippo, Denise; Harrington, Sean; Jackson, David; Lutomski, Michael

    2012-01-01

    There are two general shortcomings to the current annual sparing assessment: 1. The vehicle functions are currently assessed according to confidence targets, which can be misleading- overly conservative or optimistic. 2. The current confidence levels are arbitrarily determined and do not account for epistemic uncertainty (lack of knowledge) in the ORU failure rate. There are two major categories of uncertainty that impact Sparing Assessment: (a) Aleatory Uncertainty: Natural variability in distribution of actual failures around an Mean Time Between Failure (MTBF) (b) Epistemic Uncertainty : Lack of knowledge about the true value of an Orbital Replacement Unit's (ORU) MTBF We propose an approach to revise confidence targets and account for both categories of uncertainty, an approach we call Probability and Confidence Trade-space (PACT) evaluation.

  15. Quantified Uncertainties in Comparative Life Cycle Assessment : What Can Be Concluded?

    NARCIS (Netherlands)

    Mendoza Beltran, Angelica; Prado, Valentina; Font Vivanco, David; Henriksson, Patrik J.G.; Guinée, Jeroen B.; Heijungs, Reinout

    2018-01-01

    Interpretation of comparative Life Cycle Assessment (LCA) results can be challenging in the presence of uncertainty. To aid in interpreting such results under the goal of any comparative LCA, we aim to provide guidance to practitioners by gaining insights into uncertainty-statistics methods (USMs).

  16. Coupling Uncertainties with Accuracy Assessment in Object-Based Slum Detections, Case Study: Jakarta, Indonesia

    NARCIS (Netherlands)

    Pratomo, J.; Kuffer, M.; Martinez, Javier; Kohli, D.

    2017-01-01

    Object-Based Image Analysis (OBIA) has been successfully used to map slums. In general, the occurrence of uncertainties in producing geographic data is inevitable. However, most studies concentrated solely on assessing the classification accuracy and neglecting the inherent uncertainties. Our

  17. 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

  18. Uncertainties in different level assessments of domestic ventilation systems

    NARCIS (Netherlands)

    Bokel, R.M.J.; Yang, Z.; Cauberg, J.J.M.

    2013-01-01

    In order to improve the quality of ventilation systems, assessments are widely used. In this paper, 3 main assessment levels are distinguished based on the number of ventilation systems to be assessed and the assessment objective. The main assessment levels distinguished in this paper are global

  19. Perspectives on dosimetric uncertainties and radiological assessments of radioactive waste management

    International Nuclear Information System (INIS)

    Smith, G.M.; Pinedo, P.; Cancio, D.

    1997-01-01

    The purpose of this paper is to raise some issues concerning uncertainties in the estimation of doses of ionizing radiation arising from waste management practices and the contribution to those uncertainties arising from dosimetry modelling. The intentions are: (a) to provide perspective on the relative uncertainties in the different aspects of radiological assessments of waste management; (b) to give pointers as to where resources could best be targeted as regards reduction in overall uncertainties; and (c) to provide regulatory insight to decisions on low dose management as related to waste management practices. (author)

  20. Quantification of Wave Model Uncertainties Used for Probabilistic Reliability Assessments of Wave Energy Converters

    DEFF Research Database (Denmark)

    Ambühl, Simon; Kofoed, Jens Peter; Sørensen, John Dalsgaard

    2015-01-01

    Wave models used for site assessments are subjected to model uncertainties, which need to be quantified when using wave model results for probabilistic reliability assessments. This paper focuses on determination of wave model uncertainties. Four different wave models are considered, and validation...... data are collected from published scientific research. The bias and the root-mean-square error, as well as the scatter index, are considered for the significant wave height as well as the mean zero-crossing wave period. Based on an illustrative generic example, this paper presents how the quantified...... uncertainties can be implemented in probabilistic reliability assessments....

  1. Determination of Wave Model Uncertainties used for Probabilistic Reliability Assessments of Wave Energy Devices

    DEFF Research Database (Denmark)

    Ambühl, Simon; Kofoed, Jens Peter; Sørensen, John Dalsgaard

    2014-01-01

    Wave models used for site assessments are subject to model uncertainties, which need to be quantified when using wave model results for probabilistic reliability assessments. This paper focuses on determination of wave model uncertainties. Considered are four different wave models and validation...... data is collected from published scientific research. The bias, the root-mean-square error as well as the scatter index are considered for the significant wave height as well as the mean zero-crossing wave period. Based on an illustrative generic example it is shown how the estimated uncertainties can...... be implemented in probabilistic reliability assessments....

  2. Quality in environmental science for policy: Assessing uncertainty as a component of policy analysis

    International Nuclear Information System (INIS)

    Maxim, Laura; Sluijs, Jeroen P. van der

    2011-01-01

    The sheer number of attempts to define and classify uncertainty reveals an awareness of its importance in environmental science for policy, though the nature of uncertainty is often misunderstood. The interdisciplinary field of uncertainty analysis is unstable; there are currently several incomplete notions of uncertainty leading to different and incompatible uncertainty classifications. One of the most salient shortcomings of present-day practice is that most of these classifications focus on quantifying uncertainty while ignoring the qualitative aspects that tend to be decisive in the interface between science and policy. Consequently, the current practices of uncertainty analysis contribute to increasing the perceived precision of scientific knowledge, but do not adequately address its lack of socio-political relevance. The 'positivistic' uncertainty analysis models (like those that dominate the fields of climate change modelling and nuclear or chemical risk assessment) have little social relevance, as they do not influence negotiations between stakeholders. From the perspective of the science-policy interface, the current practices of uncertainty analysis are incomplete and incorrectly focused. We argue that although scientific knowledge produced and used in a context of political decision-making embodies traditional scientific characteristics, it also holds additional properties linked to its influence on social, political, and economic relations. Therefore, the significance of uncertainty cannot be assessed based on quality criteria that refer to the scientific content only; uncertainty must also include quality criteria specific to the properties and roles of this scientific knowledge within political, social, and economic contexts and processes. We propose a conceptual framework designed to account for such substantive, contextual, and procedural criteria of knowledge quality. At the same time, the proposed framework includes and synthesizes the various

  3. Probabilistic accident consequence uncertainty analysis: Dispersion and deposition uncertainty assessment. Volume 3, Appendices C, D, E, F, and G

    Energy Technology Data Exchange (ETDEWEB)

    Harper, F.T.; Young, M.L.; Miller, L.A. [Sandia National Labs., Albuquerque, NM (United States)] [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 third of a three-volume document describing the project and contains descriptions of the probability assessment principles; the expert identification and selection process; the weighting methods used; the inverse modeling methods; case structures; and summaries of the consequence codes.

  4. Probabilistic accident consequence uncertainty analysis: Dispersion and deposition uncertainty assessment. Volume 3, Appendices C, D, E, F, and G

    International Nuclear Information System (INIS)

    Harper, F.T.; Young, M.L.; Miller, L.A.

    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 third of a three-volume document describing the project and contains descriptions of the probability assessment principles; the expert identification and selection process; the weighting methods used; the inverse modeling methods; case structures; and summaries of the consequence codes

  5. Ecosystem Services Mapping Uncertainty Assessment: A Case Study in the Fitzroy Basin Mining Region

    Directory of Open Access Journals (Sweden)

    Zhenyu Wang

    2018-01-01

    Full Text Available Ecosystem services mapping is becoming increasingly popular through the use of various readily available mapping tools, however, uncertainties in assessment outputs are commonly ignored. Uncertainties from different sources have the potential to lower the accuracy of mapping outputs and reduce their reliability for decision-making. Using a case study in an Australian mining region, this paper assessed the impact of uncertainties on the modelling of the hydrological ecosystem service, water provision. Three types of uncertainty were modelled using multiple uncertainty scenarios: (1 spatial data sources; (2 modelling scales (temporal and spatial and (3 parameterization and model selection. We found that the mapping scales can induce significant changes to the spatial pattern of outputs and annual totals of water provision. In addition, differences in parameterization using differing sources from the literature also led to obvious differences in base flow. However, the impact of each uncertainty associated with differences in spatial data sources were not so great. The results of this study demonstrate the importance of uncertainty assessment and highlight that any conclusions drawn from ecosystem services mapping, such as the impacts of mining, are likely to also be a property of the uncertainty in ecosystem services mapping methods.

  6. Procedures for uncertainty and sensitivity analysis in repository performance assessment

    International Nuclear Information System (INIS)

    Poern, K.; Aakerlund, O.

    1985-10-01

    The objective of the project was mainly a literature study of available methods for the treatment of parameter uncertainty propagation and sensitivity aspects in complete models such as those concerning geologic disposal of radioactive waste. The study, which has run parallel with the development of a code package (PROPER) for computer assisted analysis of function, also aims at the choice of accurate, cost-affective methods for uncertainty and sensitivity analysis. Such a choice depends on several factors like the number of input parameters, the capacity of the model and the computer reresources required to use the model. Two basic approaches are addressed in the report. In one of these the model of interest is directly simulated by an efficient sampling technique to generate an output distribution. Applying the other basic method the model is replaced by an approximating analytical response surface, which is then used in the sampling phase or in moment matching to generate the output distribution. Both approaches are illustrated by simple examples in the report. (author)

  7. Uncertainties on hydrocarbon exploration assessments in both the absence and presence of optioning

    International Nuclear Information System (INIS)

    Lerche, I.

    1998-01-01

    For hydrocarbon exploration opportunities a decision tree evaluation including variance in expected value leads to an extra uncertainty on the quality and worth of expected values as a decision device, due to both intrinsic uncertainties in success probability, assessed gains and assessed costs, and to the fact that the expected value is not one of the realizable outcomes. This paper shows how these uncertainty factors can be properly taken into account to provide a revised assessment of worth. In addition, a similar sense of logic prevails when options are considered for an opportunity. The uncertainty and success probability for an optional opportunity are also assessed in terms of the volatility of the maximum option worth. (author)

  8. Assessing uncertainties in crop and pasture ensemble model simulations of productivity and N2O emissions

    Science.gov (United States)

    Simulation models are extensively used to predict agricultural productivity and greenhouse gas (GHG) emissions. However, the uncertainties of (reduced) model ensemble simulations have not been assessed systematically for variables affecting food security and climate change mitigation, within multisp...

  9. 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.

  10. Model Uncertainties for Valencia RPA Effect for MINERvA

    Energy Technology Data Exchange (ETDEWEB)

    Gran, Richard [Univ. of Minnesota, Duluth, MN (United States)

    2017-05-08

    This technical note describes the application of the Valencia RPA multi-nucleon effect and its uncertainty to QE reactions from the GENIE neutrino event generator. The analysis of MINERvA neutrino data in Rodrigues et al. PRL 116 071802 (2016) paper makes clear the need for an RPA suppression, especially at very low momentum and energy transfer. That published analysis does not constrain the magnitude of the effect; it only tests models with and without the effect against the data. Other MINERvA analyses need an expression of the model uncertainty in the RPA effect. A well-described uncertainty can be used for systematics for unfolding, for model errors in the analysis of non-QE samples, and as input for fitting exercises for model testing or constraining backgrounds. This prescription takes uncertainties on the parameters in the Valencia RPA model and adds a (not-as-tight) constraint from muon capture data. For MINERvA we apply it as a 2D ($q_0$,$q_3$) weight to GENIE events, in lieu of generating a full beyond-Fermi-gas quasielastic events. Because it is a weight, it can be applied to the generated and fully Geant4 simulated events used in analysis without a special GENIE sample. For some limited uses, it could be cast as a 1D $Q^2$ weight without much trouble. This procedure is a suitable starting point for NOvA and DUNE where the energy dependence is modest, but probably not adequate for T2K or MicroBooNE.

  11. 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

  12. 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)

  13. 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.

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

    International Nuclear Information System (INIS)

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

    1987-01-01

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

  15. Methods to Quantify Uncertainty in Human Health Risk Assessment

    National Research Council Canada - National Science Library

    Aurelius, Lea

    1998-01-01

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

  16. THE UNCERTAINTIES ON THE GIS BASED LAND SUITABILITY ASSESSMENT FOR URBAN AND RURAL PLANNING

    Directory of Open Access Journals (Sweden)

    H. Liu

    2017-09-01

    Full Text Available The majority of the research on the uncertainties of spatial data and spatial analysis focuses on some specific data feature or analysis tool. Few have accomplished the uncertainties of the whole process of an application like planning, making the research of uncertainties detached from practical applications. The paper discusses the uncertainties of the geographical information systems (GIS based land suitability assessment in planning on the basis of literature review. The uncertainties considered range from index system establishment to the classification of the final result. Methods to reduce the uncertainties arise from the discretization of continuous raster data and the index weight determination are summarized. The paper analyzes the merits and demerits of the “Nature Breaks” method which is broadly used by planners. It also explores the other factors which impact the accuracy of the final classification like the selection of class numbers, intervals and the autocorrelation of the spatial data. In the conclusion part, the paper indicates that the adoption of machine learning methods should be modified to integrate the complexity of land suitability assessment. The work contributes to the application of spatial data and spatial analysis uncertainty research on land suitability assessment, and promotes the scientific level of the later planning and decision-making.

  17. Assessment and Reduction of Model Parametric Uncertainties: A Case Study with A Distributed Hydrological Model

    Science.gov (United States)

    Gan, Y.; Liang, X. Z.; Duan, Q.; Xu, J.; Zhao, P.; Hong, Y.

    2017-12-01

    The uncertainties associated with the parameters of a hydrological model need to be quantified and reduced for it to be useful for operational hydrological forecasting and decision support. An uncertainty quantification framework is presented to facilitate practical assessment and reduction of model parametric uncertainties. A case study, using the distributed hydrological model CREST for daily streamflow simulation during the period 2008-2010 over ten watershed, was used to demonstrate the performance of this new framework. Model behaviors across watersheds were analyzed by a two-stage stepwise sensitivity analysis procedure, using LH-OAT method for screening out insensitive parameters, followed by MARS-based Sobol' sensitivity indices for quantifying each parameter's contribution to the response variance due to its first-order and higher-order effects. Pareto optimal sets of the influential parameters were then found by the adaptive surrogate-based multi-objective optimization procedure, using MARS model for approximating the parameter-response relationship and SCE-UA algorithm for searching the optimal parameter sets of the adaptively updated surrogate model. The final optimal parameter sets were validated against the daily streamflow simulation of the same watersheds during the period 2011-2012. The stepwise sensitivity analysis procedure efficiently reduced the number of parameters that need to be calibrated from twelve to seven, which helps to limit the dimensionality of calibration problem and serves to enhance the efficiency of parameter calibration. The adaptive MARS-based multi-objective calibration exercise provided satisfactory solutions to the reproduction of the observed streamflow for all watersheds. The final optimal solutions showed significant improvement when compared to the default solutions, with about 65-90% reduction in 1-NSE and 60-95% reduction in |RB|. The validation exercise indicated a large improvement in model performance with about 40

  18. Characterization of subjective uncertainty in the 1996 performance assessment for the Waste Isolation Pilot Plant

    International Nuclear Information System (INIS)

    HELTON, JON CRAIG; MARTELL, MARY-ALENA; TIERNEY, MARTIN S.

    2000-01-01

    The 1996 performance assessment (PA) for the Waste Isolation Pilot Plant (WIPP) maintains a separation between stochastic (i.e., aleatory) and subjective (i.e., epistemic) uncertainty, with stochastic uncertainty arising from the possible disruptions that could occur at the WIPP over the 10,000 yr regulatory period specified by the US Environmental Protection Agency (40 CFR 191,40 CFR 194) and subjective uncertainty arising from an inability to uniquely characterize many of the inputs required in the 1996 WIPP PA. The characterization of subjective uncertainty is discussed, including assignment of distributions, uncertain variables selected for inclusion in analysis, correlation control, sample size, statistical confidence on mean complementary cumulative distribution functions, generation of Latin hypercube samples, sensitivity analysis techniques, and scenarios involving stochastic and subjective uncertainty

  19. Characterization of subjective uncertainty in the 1996 performance assessment for the Waste Isolation Pilot Plant

    Energy Technology Data Exchange (ETDEWEB)

    HELTON,JON CRAIG; MARTELL,MARY-ALENA; TIERNEY,MARTIN S.

    2000-05-18

    The 1996 performance assessment (PA) for the Waste Isolation Pilot Plant (WIPP) maintains a separation between stochastic (i.e., aleatory) and subjective (i.e., epistemic) uncertainty, with stochastic uncertainty arising from the possible disruptions that could occur at the WIPP over the 10,000 yr regulatory period specified by the US Environmental Protection Agency (40 CFR 191,40 CFR 194) and subjective uncertainty arising from an inability to uniquely characterize many of the inputs required in the 1996 WIPP PA. The characterization of subjective uncertainty is discussed, including assignment of distributions, uncertain variables selected for inclusion in analysis, correlation control, sample size, statistical confidence on mean complementary cumulative distribution functions, generation of Latin hypercube samples, sensitivity analysis techniques, and scenarios involving stochastic and subjective uncertainty.

  20. Assessing the near-term risk of climate uncertainty : interdependencies among the U.S. states.

    Energy Technology Data Exchange (ETDEWEB)

    Loose, Verne W.; Lowry, Thomas Stephen; Malczynski, Leonard A.; Tidwell, Vincent Carroll; Stamber, Kevin Louis; Reinert, Rhonda K.; Backus, George A.; Warren, Drake E.; Zagonel, Aldo A.; Ehlen, Mark Andrew; Klise, Geoffrey T.; Vargas, Vanessa N.

    2010-04-01

    Policy makers will most likely need to make decisions about climate policy before climate scientists have resolved all relevant uncertainties about the impacts of climate change. This study demonstrates a risk-assessment methodology for evaluating uncertain future climatic conditions. We estimate the impacts of climate change on U.S. state- and national-level economic activity from 2010 to 2050. To understand the implications of uncertainty on risk and to provide a near-term rationale for policy interventions to mitigate the course of climate change, we focus on precipitation, one of the most uncertain aspects of future climate change. We use results of the climate-model ensemble from the Intergovernmental Panel on Climate Change's (IPCC) Fourth Assessment Report 4 (AR4) as a proxy for representing climate uncertainty over the next 40 years, map the simulated weather from the climate models hydrologically to the county level to determine the physical consequences on economic activity at the state level, and perform a detailed 70-industry analysis of economic impacts among the interacting lower-48 states. We determine the industry-level contribution to the gross domestic product and employment impacts at the state level, as well as interstate population migration, effects on personal income, and consequences for the U.S. trade balance. We show that the mean or average risk of damage to the U.S. economy from climate change, at the national level, is on the order of $1 trillion over the next 40 years, with losses in employment equivalent to nearly 7 million full-time jobs.

  1. Modeling the effects of uncertainty on fear of nuclear waste: Differences among science, business and environmental group members

    International Nuclear Information System (INIS)

    Bassett, G.; Jenkins-Smith, H.

    1992-10-01

    This paper analyzes the relationships between the subjective assessment of riskiness of managing nuclear waste and the level of certainty regarding the assessment. Uncertainty can be operationalized in two ways. The direct approach asks a person to assess their own subjective beliefs about a potential hazard. The indirect approach assesses how readily an individual will change his or her beliefs when confronted with new information that conflicts with prior beliefs. This paper tests for the relationships between these two distinct operationalizations of uncertainty and overall assessments of the risks posed by radioactive wastes. First we analyze the relationships between stated levels of uncertainty about the effects of radiation on the level of perceived risks from radioactive wastes. Second, we assess the linkage between willingness to alter prior beliefs about the risks of radioactive wastes in response to new information provided by ''a neutral source'' (or responsiveness of beliefs) and uncertainty. Using data taken from random mail surveys of members of scientific, business, and environmental groups in Colorado and New Mexico in the summer of 1990, we test hypotheses that (a) greater uncertainty is associated with greater perceived risks, and (b) greater responsiveness of beliefs to new information is associated with greater uncertainty. The import of these hypotheses concerns the dynamics of uncertainty in controversial technical policy issues, wherein perceived risks are a primary ingredient in policy positions taken by participants in policy disputes

  2. Modeling the effects of uncertainty on fear of nuclear waste: Differences among science, business and environmental group members

    Energy Technology Data Exchange (ETDEWEB)

    Bassett, G. [Illinois Univ., Chicago, IL (United States). Dept. of Economics]|[Argonne National Lab., IL (United States); Jenkins-Smith, H. [New Mexico Univ., Albuquerque, NM (United States). Dept. of Political Science]|[Argonne National Lab., IL (United States)

    1992-10-01

    This paper analyzes the relationships between the subjective assessment of riskiness of managing nuclear waste and the level of certainty regarding the assessment. Uncertainty can be operationalized in two ways. The direct approach asks a person to assess their own subjective beliefs about a potential hazard. The indirect approach assesses how readily an individual will change his or her beliefs when confronted with new information that conflicts with prior beliefs. This paper tests for the relationships between these two distinct operationalizations of uncertainty and overall assessments of the risks posed by radioactive wastes. First we analyze the relationships between stated levels of uncertainty about the effects of radiation on the level of perceived risks from radioactive wastes. Second, we assess the linkage between willingness to alter prior beliefs about the risks of radioactive wastes in response to new information provided by ``a neutral source`` (or responsiveness of beliefs) and uncertainty. Using data taken from random mail surveys of members of scientific, business, and environmental groups in Colorado and New Mexico in the summer of 1990, we test hypotheses that (a) greater uncertainty is associated with greater perceived risks, and (b) greater responsiveness of beliefs to new information is associated with greater uncertainty. The import of these hypotheses concerns the dynamics of uncertainty in controversial technical policy issues, wherein perceived risks are a primary ingredient in policy positions taken by participants in policy disputes.

  3. Modeling the effects of uncertainty on fear of nuclear waste: Differences among science, business and environmental group members

    Energy Technology Data Exchange (ETDEWEB)

    Bassett, G. (Illinois Univ., Chicago, IL (United States). Dept. of Economics Argonne National Lab., IL (United States)); Jenkins-Smith, H. (New Mexico Univ., Albuquerque, NM (United States). Dept. of Political Science Argonne National Lab., IL (United States))

    1992-10-01

    This paper analyzes the relationships between the subjective assessment of riskiness of managing nuclear waste and the level of certainty regarding the assessment. Uncertainty can be operationalized in two ways. The direct approach asks a person to assess their own subjective beliefs about a potential hazard. The indirect approach assesses how readily an individual will change his or her beliefs when confronted with new information that conflicts with prior beliefs. This paper tests for the relationships between these two distinct operationalizations of uncertainty and overall assessments of the risks posed by radioactive wastes. First we analyze the relationships between stated levels of uncertainty about the effects of radiation on the level of perceived risks from radioactive wastes. Second, we assess the linkage between willingness to alter prior beliefs about the risks of radioactive wastes in response to new information provided by a neutral source'' (or responsiveness of beliefs) and uncertainty. Using data taken from random mail surveys of members of scientific, business, and environmental groups in Colorado and New Mexico in the summer of 1990, we test hypotheses that (a) greater uncertainty is associated with greater perceived risks, and (b) greater responsiveness of beliefs to new information is associated with greater uncertainty. The import of these hypotheses concerns the dynamics of uncertainty in controversial technical policy issues, wherein perceived risks are a primary ingredient in policy positions taken by participants in policy disputes.

  4. Performance Assessment Uncertainty Analysis for Japan's HLW Program Feasibility Study (H12)

    International Nuclear Information System (INIS)

    BABA, T.; ISHIGURO, K.; ISHIHARA, Y.; SAWADA, A.; UMEKI, H.; WAKASUGI, K.; WEBB, ERIK K.

    1999-01-01

    Most HLW programs in the world recognize that any estimate of long-term radiological performance must be couched in terms of the uncertainties derived from natural variation, changes through time and lack of knowledge about the essential processes. The Japan Nuclear Cycle Development Institute followed a relatively standard procedure to address two major categories of uncertainty. First, a FEatures, Events and Processes (FEPs) listing, screening and grouping activity was pursued in order to define the range of uncertainty in system processes as well as possible variations in engineering design. A reference and many alternative cases representing various groups of FEPs were defined and individual numerical simulations performed for each to quantify the range of conceptual uncertainty. Second, parameter distributions were developed for the reference case to represent the uncertainty in the strength of these processes, the sequencing of activities and geometric variations. Both point estimates using high and low values for individual parameters as well as a probabilistic analysis were performed to estimate parameter uncertainty. A brief description of the conceptual model uncertainty analysis is presented. This paper focuses on presenting the details of the probabilistic parameter uncertainty assessment

  5. Methodology for quantifying uncertainty in coal assessments with an application to a Texas lignite deposit

    Energy Technology Data Exchange (ETDEWEB)

    Olea, Ricardo A.; Luppens, James A.; Tewalt, Susan J. [U.S. Geological Survey, Reston, VA (United States)

    2011-01-01

    A common practice for characterizing uncertainty in coal resource assessments has been the itemization of tonnage at the mining unit level and the classification of such units according to distance to drilling holes. Distance criteria, such as those used in U.S. Geological Survey Circular 891, are still widely used for public disclosure. A major deficiency of distance methods is that they do not provide a quantitative measure of uncertainty. Additionally, relying on distance between data points alone does not take into consideration other factors known to have an influence on uncertainty, such as spatial correlation, type of probability distribution followed by the data, geological discontinuities, and boundary of the deposit. Several geostatistical methods have been combined to formulate a quantitative characterization for appraising uncertainty. Drill hole datasets ranging from widespread exploration drilling to detailed development drilling from a lignite deposit in Texas were used to illustrate the modeling. The results show that distance to the nearest drill hole is almost completely unrelated to uncertainty, which confirms the inadequacy of characterizing uncertainty based solely on a simple classification of resources by distance classes. The more complex statistical methods used in this study quantify uncertainty and show good agreement between confidence intervals in the uncertainty predictions and data from additional drilling. (author)

  6. Methodology for quantifying uncertainty in coal assessments with an application to a Texas lignite deposit

    Science.gov (United States)

    Olea, R.A.; Luppens, J.A.; Tewalt, S.J.

    2011-01-01

    A common practice for characterizing uncertainty in coal resource assessments has been the itemization of tonnage at the mining unit level and the classification of such units according to distance to drilling holes. Distance criteria, such as those used in U.S. Geological Survey Circular 891, are still widely used for public disclosure. A major deficiency of distance methods is that they do not provide a quantitative measure of uncertainty. Additionally, relying on distance between data points alone does not take into consideration other factors known to have an influence on uncertainty, such as spatial correlation, type of probability distribution followed by the data, geological discontinuities, and boundary of the deposit. Several geostatistical methods have been combined to formulate a quantitative characterization for appraising uncertainty. Drill hole datasets ranging from widespread exploration drilling to detailed development drilling from a lignite deposit in Texas were used to illustrate the modeling. The results show that distance to the nearest drill hole is almost completely unrelated to uncertainty, which confirms the inadequacy of characterizing uncertainty based solely on a simple classification of resources by distance classes. The more complex statistical methods used in this study quantify uncertainty and show good agreement between confidence intervals in the uncertainty predictions and data from additional drilling. ?? 2010.

  7. Taking the uncertainty in climate-change vulnerability assessment seriously

    International Nuclear Information System (INIS)

    Patt, A.; Patt, A.; Klein, R.J.T.; Vega-Leinert, A. de la

    2005-01-01

    Climate-change vulnerability assessment has become a frequently employed tool, with the purpose of informing policy-makers attempting to adapt to global change conditions. However, we suggest that there are three reasons to suspect that vulnerability assessment often promises more certainty, and more useful results, than it can deliver. First, the complexity of the system it purports to describe is greater than that described by other types of assessment. Second, it is difficult, if not impossible, to obtain data to test proposed interactions between different vulnerability drivers. Third, the time scale of analysis is too long to be able to make robust projections about future adaptive capacity. We analyze the results from a stakeholder workshop in a European vulnerability assessment, and find evidence to support these arguments. (authors)

  8. Effect of uncertainty in pore volumes on the uncertainty in amount adsorbed at high-pressures on activated carbon cloth

    International Nuclear Information System (INIS)

    Pendleton, Ph.; Badalyan, A.

    2005-01-01

    Activated carbon cloth (ACC) is a good adsorbent for high rate adsorption of volatile organic carbons [1] and as a storage media for methane [2]. It has been shown [2] that the capacity of ACC to adsorb methane, in the first instance, depends on its micropore volume. One way of increasing this storage capacity is to increase micropore volume [3]. Therefore, the uncertainty in the determination of ACC micropore volume becomes a very important factor, since it affects the uncertainty of amount adsorbed at high-pressures, which usually accompany storage of methane on ACC. Recently, we developed a method for the calculation of experimental uncertainty in micropore volume using low pressure nitrogen adsorption data at 77 K for FM1/250 ACC (ex. Calgon, USA). We tested several cubic equations of state (EOS) and multiple parameter (EOS) to determine the amount of high-pressure nitrogen adsorbed, and compared these data with amounts calculated via interpolated NIST density data. The amount adsorbed calculated from interpolated NIST density data exhibit the lowest propagated combined uncertainty. Values of relative combined standard uncertainty for FM1/250 calculated using a weighted, mean-least-squares method applied to the low-pressure nitrogen adsorption data (Fig. 1) gave 3.52% for the primary micropore volume and 1.63% for the total micropore volume. Our equipment allows the same sample to be exposed to nitrogen (and other gases) at pressures from 10 -4 Pa to 17-MPa in the temperature range from 176 to 252 K. The maximum uptake of nitrogen was 356-mmol/g at 201.92 K and 15.8-MPa (Fig. 2). The delivery capacity of ACC is determined by the amount of adsorbed gas recovered when the pressure is reduced from that for maximum adsorption to 0.1-MPa [2]. In this regard, the total micropore volume becomes an important parameter in determining the amount of gas delivered during desorption. In the present paper we will discuss the effect of uncertainty in micropore volume

  9. Uncertainty assessment in geodetic network adjustment by combining GUM and Monte-Carlo-simulations

    Science.gov (United States)

    Niemeier, Wolfgang; Tengen, Dieter

    2017-06-01

    In this article first ideas are presented to extend the classical concept of geodetic network adjustment by introducing a new method for uncertainty assessment as two-step analysis. In the first step the raw data and possible influencing factors are analyzed using uncertainty modeling according to GUM (Guidelines to the Expression of Uncertainty in Measurements). This approach is well established in metrology, but rarely adapted within Geodesy. The second step consists of Monte-Carlo-Simulations (MC-simulations) for the complete processing chain from raw input data and pre-processing to adjustment computations and quality assessment. To perform these simulations, possible realizations of raw data and the influencing factors are generated, using probability distributions for all variables and the established concept of pseudo-random number generators. Final result is a point cloud which represents the uncertainty of the estimated coordinates; a confidence region can be assigned to these point clouds, as well. This concept may replace the common concept of variance propagation and the quality assessment of adjustment parameters by using their covariance matrix. It allows a new way for uncertainty assessment in accordance with the GUM concept for uncertainty modelling and propagation. As practical example the local tie network in "Metsähovi Fundamental Station", Finland is used, where classical geodetic observations are combined with GNSS data.

  10. Development and comparison in uncertainty assessment based Bayesian modularization method in hydrological modeling

    Science.gov (United States)

    Li, Lu; Xu, Chong-Yu; Engeland, Kolbjørn

    2013-04-01

    SummaryWith respect to model calibration, parameter estimation and analysis of uncertainty sources, various regression and probabilistic approaches are used in hydrological modeling. A family of Bayesian methods, which incorporates different sources of information into a single analysis through Bayes' theorem, is widely used for uncertainty assessment. However, none of these approaches can well treat the impact of high flows in hydrological modeling. This study proposes a Bayesian modularization uncertainty assessment approach in which the highest streamflow observations are treated as suspect information that should not influence the inference of the main bulk of the model parameters. This study includes a comprehensive comparison and evaluation of uncertainty assessments by our new Bayesian modularization method and standard Bayesian methods using the Metropolis-Hastings (MH) algorithm with the daily hydrological model WASMOD. Three likelihood functions were used in combination with standard Bayesian method: the AR(1) plus Normal model independent of time (Model 1), the AR(1) plus Normal model dependent on time (Model 2) and the AR(1) plus Multi-normal model (Model 3). The results reveal that the Bayesian modularization method provides the most accurate streamflow estimates measured by the Nash-Sutcliffe efficiency and provide the best in uncertainty estimates for low, medium and entire flows compared to standard Bayesian methods. The study thus provides a new approach for reducing the impact of high flows on the discharge uncertainty assessment of hydrological models via Bayesian method.

  11. 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

  12. Review of uncertainty estimates associated with models for assessing the impact of breeder reactor radioactivity releases

    International Nuclear Information System (INIS)

    Miller, C.; Little, C.A.

    1982-08-01

    The purpose is to summarize estimates based on currently available data of the uncertainty associated with radiological assessment models. The models being examined herein are those recommended previously for use in breeder reactor assessments. Uncertainty estimates are presented for models of atmospheric and hydrologic transport, terrestrial and aquatic food-chain bioaccumulation, and internal and external dosimetry. Both long-term and short-term release conditions are discussed. The uncertainty estimates presented in this report indicate that, for many sites, generic models and representative parameter values may be used to calculate doses from annual average radionuclide releases when these calculated doses are on the order of one-tenth or less of a relevant dose limit. For short-term, accidental releases, especially those from breeder reactors located in sites dominated by complex terrain and/or coastal meteorology, the uncertainty in the dose calculations may be much larger than an order of magnitude. As a result, it may be necessary to incorporate site-specific information into the dose calculation under these circumstances to reduce this uncertainty. However, even using site-specific information, natural variability and the uncertainties in the dose conversion factor will likely result in an overall uncertainty of greater than an order of magnitude for predictions of dose or concentration in environmental media following shortterm releases

  13. 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

  14. Evaluation of uncertainty associated with parameters for long-term safety assessments of geological disposal

    International Nuclear Information System (INIS)

    Yamaguchi, Tetsuji; Minase, Naofumi; Iida, Yoshihisa; Tanaka, Tadao; Nakayama, Shinichi

    2005-01-01

    This paper describes the current status of our data acquisition on quantifying uncertainties associated with parameters for safety assessment on groundwater scenarios for geological disposal of radioactive wastes. First, sources of uncertainties and the resulting priority in data acquisition were briefed. Then, the current status of data acquisition for quantifying the uncertainties in assessing solubility, diffusivity in bentonite buffer and distribution coefficient on rocks is introduced. The uncertainty with the solubility estimation is quantified from that associated with thermodynamic data and that in estimating groundwater chemistry. The uncertainty associated with the diffusivity in bentonite buffer is composed of variations of relevant factors such as porosity of the bentonite buffer, montmorillonite content, chemical composition of pore water and temperature. The uncertainty of factors such as the specific surface area of the rock, pH, ionic strength, carbonate concentration in groundwater compose uncertainty of the distribution coefficient of radionuclides on rocks. Based on these investigations, problems to be solved in future studies are summarized. (author)

  15. The Impact of Economic Parameter Uncertainty Growth on Regional Energy Demand Assessment

    Directory of Open Access Journals (Sweden)

    Olga Vasilyevna Mazurova

    2017-06-01

    Full Text Available The article deals with the forecasting studies based on the energy demand and prices in the region in terms of the complex interconnections between economy (and energy and the growth of uncertainty of the future development of the country and territories. The authors propose a methodological approach, which combines the assessment of the price elasticity of energy demand with the optimization of energy and fuel regional supply. In this case, the price elasticity of demand is determined taking into account the comparison of cost-effectiveness of using different types of fuel and energy by different consumers. The originality of the proposed approach consists in simulating the behaviour of suppliers’ (energy companies and large customers’ (power plants, boiler rooms, industry, transport, population depending on energy price changes, the existing and new technologies, energy-saving activities and restrictions on fuel supplies. To take into account the uncertainty of future economic and energy conditions, some parameters such as prospective technical and economic parameters, price, technological parameters are set as the intervals of possible values with different probability levels. This approach allows making multivariate studies with different combinations of the expected conditions and receiving as a result the range of the projected values of studied indicators. The multivariate calculations show that the fuel demand has a nonlinear dependence on the consumer characteristics, pricing, projection horizon, and the nature of the future conditions uncertainty. The authors have shown that this effect can be significant and should be considered in the forecasts of the development of fuel and energy sector. The methodological approach and quantitative evaluation can be used to improve the economic and energy development strategies of the country and regions

  16. Sources of uncertainty in hydrological climate impact assessment: a cross-scale study

    Science.gov (United States)

    Hattermann, F. F.; Vetter, T.; Breuer, L.; Su, Buda; Daggupati, P.; Donnelly, C.; Fekete, B.; Flörke, F.; Gosling, S. N.; Hoffmann, P.; Liersch, S.; Masaki, Y.; Motovilov, Y.; Müller, C.; Samaniego, L.; Stacke, T.; Wada, Y.; Yang, T.; Krysnaova, V.

    2018-01-01

    Climate change impacts on water availability and hydrological extremes are major concerns as regards the Sustainable Development Goals. Impacts on hydrology are normally investigated as part of a modelling chain, in which climate projections from multiple climate models are used as inputs to multiple impact models, under different greenhouse gas emissions scenarios, which result in different amounts of global temperature rise. While the goal is generally to investigate the relevance of changes in climate for the water cycle, water resources or hydrological extremes, it is often the case that variations in other components of the model chain obscure the effect of climate scenario variation. This is particularly important when assessing the impacts of relatively lower magnitudes of global warming, such as those associated with the aspirational goals of the Paris Agreement. In our study, we use ANOVA (analyses of variance) to allocate and quantify the main sources of uncertainty in the hydrological impact modelling chain. In turn we determine the statistical significance of different sources of uncertainty. We achieve this by using a set of five climate models and up to 13 hydrological models, for nine large scale river basins across the globe, under four emissions scenarios. The impact variable we consider in our analysis is daily river discharge. We analyze overall water availability and flow regime, including seasonality, high flows and low flows. Scaling effects are investigated by separately looking at discharge generated by global and regional hydrological models respectively. Finally, we compare our results with other recently published studies. We find that small differences in global temperature rise associated with some emissions scenarios have mostly significant impacts on river discharge—however, climate model related uncertainty is so large that it obscures the sensitivity of the hydrological system.

  17. Understanding uncertainty propagation in life cycle assessments of waste management systems

    DEFF Research Database (Denmark)

    Bisinella, Valentina; Conradsen, Knut; Christensen, Thomas Højlund

    2015-01-01

    Uncertainty analysis in Life Cycle Assessments (LCAs) of waste management systems often results obscure and complex, with key parameters rarely determined on a case-by-case basis. The paper shows an application of a simplified approach to uncertainty coupled with a Global Sensitivity Analysis (GSA......) perspective on three alternative waste management systems for Danish single-family household waste. The approach provides a fast and systematic method to select the most important parameters in the LCAs, understand their propagation and contribution to uncertainty....

  18. Assessment of uncertainty in full core reactor physics calculations using statistical methods

    International Nuclear Information System (INIS)

    McEwan, C.

    2012-01-01

    The best estimate method of safety analysis involves choosing a realistic set of input parameters for a proposed safety case and evaluating the uncertainty in the results. Determining the uncertainty in code outputs remains a challenge and is the subject of a benchmarking exercise proposed by the Organization for Economic Cooperation and Development. The work proposed in this paper will contribute to this benchmark by assessing the uncertainty in a depletion calculation of the final nuclide concentrations for an experiment performed in the Fukushima-2 reactor. This will be done using lattice transport code DRAGON and a tool known as DINOSAUR. (author)

  19. 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.

  20. Assessment of uncertainty in full core reactor physics calculations using statistical methods

    Energy Technology Data Exchange (ETDEWEB)

    McEwan, C., E-mail: mcewac2@mcmaster.ca [McMaster Univ., Hamilton, Ontario (Canada)

    2012-07-01

    The best estimate method of safety analysis involves choosing a realistic set of input parameters for a proposed safety case and evaluating the uncertainty in the results. Determining the uncertainty in code outputs remains a challenge and is the subject of a benchmarking exercise proposed by the Organization for Economic Cooperation and Development. The work proposed in this paper will contribute to this benchmark by assessing the uncertainty in a depletion calculation of the final nuclide concentrations for an experiment performed in the Fukushima-2 reactor. This will be done using lattice transport code DRAGON and a tool known as DINOSAUR. (author)

  1. Uncertainty analysis with a view towards applications in accident consequence assessments

    International Nuclear Information System (INIS)

    Fischer, F.; Erhardt, J.

    1985-09-01

    Since the publication of the US-Reactor Safety Study WASH-1400 there has been an increasing interest to develop and apply methods which allow to quantify the uncertainty inherent in probabilistic risk assessments (PRAs) and accident consequence assessments (ACAs) for installations of the nuclear fuel cycle. Research and development in this area is forced by the fact that PRA and ACA are more and more used for comparative, decisive and fact finding studies initiated by industry and regulatory commissions. This report summarizes and reviews some of the main methods and gives some hints to do sensitivity and uncertainty analyses. Some first investigations aiming at the application of the method mentioned above to a submodel of the ACA-code UFOMOD (KfK) are presented. Sensitivity analyses and some uncertainty studies an important submodel of UFOMOD are carried out to identify the relevant parameters for subsequent uncertainty calculations. (orig./HP) [de

  2. High resolution remote sensing for reducing uncertainties in urban forest carbon offset life cycle assessments.

    Science.gov (United States)

    Tigges, Jan; Lakes, Tobia

    2017-10-04

    Urban forests reduce greenhouse gas emissions by storing and sequestering considerable amounts of carbon. However, few studies have considered the local scale of urban forests to effectively evaluate their potential long-term carbon offset. The lack of precise, consistent and up-to-date forest details is challenging for long-term prognoses. Therefore, this review aims to identify uncertainties in urban forest carbon offset assessment and discuss the extent to which such uncertainties can be reduced by recent progress in high resolution remote sensing. We do this by performing an extensive literature review and a case study combining remote sensing and life cycle assessment of urban forest carbon offset in Berlin, Germany. Recent progress in high resolution remote sensing and methods is adequate for delivering more precise details on the urban tree canopy, individual tree metrics, species, and age structures compared to conventional land use/cover class approaches. These area-wide consistent details can update life cycle inventories for more precise future prognoses. Additional improvements in classification accuracy can be achieved by a higher number of features derived from remote sensing data of increasing resolution, but first studies on this subject indicated that a smart selection of features already provides sufficient data that avoids redundancies and enables more efficient data processing. Our case study from Berlin could use remotely sensed individual tree species as consistent inventory of a life cycle assessment. However, a lack of growth, mortality and planting data forced us to make assumptions, therefore creating uncertainty in the long-term prognoses. Regarding temporal changes and reliable long-term estimates, more attention is required to detect changes of gradual growth, pruning and abrupt changes in tree planting and mortality. As such, precise long-term urban ecological monitoring using high resolution remote sensing should be intensified

  3. Comparative and Predictive Multimedia Assessments Using Monte Carlo Uncertainty Analyses

    Science.gov (United States)

    Whelan, G.

    2002-05-01

    Multiple-pathway frameworks (sometimes referred to as multimedia models) provide a platform for combining medium-specific environmental models and databases, such that they can be utilized in a more holistic assessment of contaminant fate and transport in the environment. These frameworks provide a relatively seamless transfer of information from one model to the next and from databases to models. Within these frameworks, multiple models are linked, resulting in models that consume information from upstream models and produce information to be consumed by downstream models. The Framework for Risk Analysis in Multimedia Environmental Systems (FRAMES) is an example, which allows users to link their models to other models and databases. FRAMES is an icon-driven, site-layout platform that is an open-architecture, object-oriented system that interacts with environmental databases; helps the user construct a Conceptual Site Model that is real-world based; allows the user to choose the most appropriate models to solve simulation requirements; solves the standard risk paradigm of release transport and fate; and exposure/risk assessments to people and ecology; and presents graphical packages for analyzing results. FRAMES is specifically designed allow users to link their own models into a system, which contains models developed by others. This paper will present the use of FRAMES to evaluate potential human health exposures using real site data and realistic assumptions from sources, through the vadose and saturated zones, to exposure and risk assessment at three real-world sites, using the Multimedia Environmental Pollutant Assessment System (MEPAS), which is a multimedia model contained within FRAMES. These real-world examples use predictive and comparative approaches coupled with a Monte Carlo analysis. A predictive analysis is where models are calibrated to monitored site data, prior to the assessment, and a comparative analysis is where models are not calibrated but

  4. Treating Uncertainties in A Nuclear Seismic Probabilistic Risk Assessment by Means of the Distemper-Safer Theory of Evidence

    International Nuclear Information System (INIS)

    Lo, Chungkung; Pedroni, N.; Zio, E.

    2014-01-01

    The analyses carried out within the Seismic Probabilistic Risk Assessments (SPRAs) of Nuclear Power Plants (NPPs) are affected by significant aleatory and epistemic uncertainties. These uncertainties have to be represented and quantified coherently with the data, information and knowledge available, to provide reasonable assurance that related decisions can be taken robustly and with confidence. The amount of data, information and knowledge available for seismic risk assessment is typically limited, so that the analysis must strongly rely on expert judgments. In this paper, a Dempster-Shafer Theory (DST) framework for handling uncertainties in NPP SPRAs is proposed and applied to an example case study. The main contributions of this paper are two: (i) applying the complete DST framework to SPRA models, showing how to build the Dempster-Shafer structures of the uncertainty parameters based on industry generic data, and (ii) embedding Bayesian updating based on plant specific data into the framework. The results of the application to a case study show that the approach is feasible and effective in (i) describing and jointly propagating aleatory and epistemic uncertainties in SPRA models and (ii) providing 'conservative' bounds on the safety quantities of interest (i. e. Core Damage Frequency, CDF) that reflect the (limited) state of knowledge of the experts about the system of interest

  5. Treating Uncertainties in A Nuclear Seismic Probabilistic Risk Assessment by Means of the Distemper-Safer Theory of Evidence

    Energy Technology Data Exchange (ETDEWEB)

    Lo, Chungkung [Chair on Systems Science and the Energetic Challenge, Paris (France); Pedroni, N.; Zio, E. [Politecnico di Milano, Milano (Italy)

    2014-02-15

    The analyses carried out within the Seismic Probabilistic Risk Assessments (SPRAs) of Nuclear Power Plants (NPPs) are affected by significant aleatory and epistemic uncertainties. These uncertainties have to be represented and quantified coherently with the data, information and knowledge available, to provide reasonable assurance that related decisions can be taken robustly and with confidence. The amount of data, information and knowledge available for seismic risk assessment is typically limited, so that the analysis must strongly rely on expert judgments. In this paper, a Dempster-Shafer Theory (DST) framework for handling uncertainties in NPP SPRAs is proposed and applied to an example case study. The main contributions of this paper are two: (i) applying the complete DST framework to SPRA models, showing how to build the Dempster-Shafer structures of the uncertainty parameters based on industry generic data, and (ii) embedding Bayesian updating based on plant specific data into the framework. The results of the application to a case study show that the approach is feasible and effective in (i) describing and jointly propagating aleatory and epistemic uncertainties in SPRA models and (ii) providing 'conservative' bounds on the safety quantities of interest (i. e. Core Damage Frequency, CDF) that reflect the (limited) state of knowledge of the experts about the system of interest.

  6. TREATING UNCERTAINTIES IN A NUCLEAR SEISMIC PROBABILISTIC RISK ASSESSMENT BY MEANS OF THE DEMPSTER-SHAFER THEORY OF EVIDENCE

    Directory of Open Access Journals (Sweden)

    CHUNG-KUNG LO

    2014-02-01

    Full Text Available The analyses carried out within the Seismic Probabilistic Risk Assessments (SPRAs of Nuclear Power Plants (NPPs are affected by significant aleatory and epistemic uncertainties. These uncertainties have to be represented and quantified coherently with the data, information and knowledge available, to provide reasonable assurance that related decisions can be taken robustly and with confidence. The amount of data, information and knowledge available for seismic risk assessment is typically limited, so that the analysis must strongly rely on expert judgments. In this paper, a Dempster-Shafer Theory (DST framework for handling uncertainties in NPP SPRAs is proposed and applied to an example case study. The main contributions of this paper are two: (i applying the complete DST framework to SPRA models, showing how to build the Dempster-Shafer structures of the uncertainty parameters based on industry generic data, and (ii embedding Bayesian updating based on plant specific data into the framework. The results of the application to a case study show that the approach is feasible and effective in (i describing and jointly propagating aleatory and epistemic uncertainties in SPRA models and (ii providing ‘conservative’ bounds on the safety quantities of interest (i.e. Core Damage Frequency, CDF that reflect the (limited state of knowledge of the experts about the system of interest.

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

    Science.gov (United States)

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

    2014-05-01

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

  8. Error and Uncertainty in the Accuracy Assessment of Land Cover Maps

    Science.gov (United States)

    Sarmento, Pedro Alexandre Reis

    Traditionally the accuracy assessment of land cover maps is performed through the comparison of these maps with a reference database, which is intended to represent the "real" land cover, being this comparison reported with the thematic accuracy measures through confusion matrixes. Although, these reference databases are also a representation of reality, containing errors due to the human uncertainty in the assignment of the land cover class that best characterizes a certain area, causing bias in the thematic accuracy measures that are reported to the end users of these maps. The main goal of this dissertation is to develop a methodology that allows the integration of human uncertainty present in reference databases in the accuracy assessment of land cover maps, and analyse the impacts that uncertainty may have in the thematic accuracy measures reported to the end users of land cover maps. The utility of the inclusion of human uncertainty in the accuracy assessment of land cover maps is investigated. Specifically we studied the utility of fuzzy sets theory, more precisely of fuzzy arithmetic, for a better understanding of human uncertainty associated to the elaboration of reference databases, and their impacts in the thematic accuracy measures that are derived from confusion matrixes. For this purpose linguistic values transformed in fuzzy intervals that address the uncertainty in the elaboration of reference databases were used to compute fuzzy confusion matrixes. The proposed methodology is illustrated using a case study in which the accuracy assessment of a land cover map for Continental Portugal derived from Medium Resolution Imaging Spectrometer (MERIS) is made. The obtained results demonstrate that the inclusion of human uncertainty in reference databases provides much more information about the quality of land cover maps, when compared with the traditional approach of accuracy assessment of land cover maps. None

  9. Modeling uncertainty in coal resource assessments, with an application to a central area of the Gillette coal field, Wyoming

    Science.gov (United States)

    Olea, Ricardo A.; Luppens, James A.

    2014-01-01

    Standards for the public disclosure of mineral resources and reserves do not require the use of any specific methodology when it comes to estimating the reliability of the resources. Unbeknownst to most intended recipients of resource appraisals, such freedom commonly results in subjective opinions or estimations based on suboptimal approaches, such as use of distance methods. This report presents the results of a study of the third of three coal deposits in which drilling density has been increased one order of magnitude in three stages. Applying geostatistical simulation, the densest dataset was used to check the results obtained by modeling the sparser drillings. We have come up with two summary displays of results based on the same simulations, which individually and combined provide a better assessment of uncertainty than traditional qualitative resource classifications: (a) a display of cell 90 percent confidence interval versus cumulative cell tonnage, and (b) a histogram of total resources. The first graph allows classification of data into any number of bins with dividers to be decided by the assessor on the basis of a discriminating variable that is statistically accepted as a measure of uncertainty, thereby improving the quality and flexibility of the modeling. The second display expands the scope of the modeling by providing a quantitative measure of uncertainty for total tonnage, which is a fundamental concern for stockholders, geologists, and decision makers. Our approach allows us to correctly model uncertainty issues not possible to predict with distance methods, such as (a) different levels of uncertainty for individual beds with the same pattern and density of drill holes, (b) different local degrees of reduction of uncertainty with drilling densification reflecting fluctuation in the complexity of the geology, (c) average reduction in uncertainty at a disproportionately lesser rate than the reduction in area per drill hole, (d) the proportional

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

    International Nuclear Information System (INIS)

    Bogen, K.T.

    1993-01-01

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

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

    International Nuclear Information System (INIS)

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

    2007-01-01

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

  12. 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

  13. Time frames and uncertainty in assessment of geoscientific environment

    International Nuclear Information System (INIS)

    Kusunose, Kinichiro; Koide, Hitoshi

    2001-01-01

    Second Progress Report on Research and Development for the Geological Disposal of high-level radioactive waste (HLW) in Japan was published in 2000 by Japan Nuclear Cycle Development Institute. The issue presents basic technical feasibility of safe HLW disposal on Japan. The issue, however, lacks discussion about realistic time frame for geological stability assessment, and treating of instability in geoscientific models, because candidate repository sites have not yet selected in Japan. This paper present short conceptional discussion of the time frames and instability in geoscientific models and propose some time frames and instability treating process. Methods of geological prediction are classified into seven groups: (1) Prediction by extrapolation, (2) Prediction by analogy, (3) Prediction by probability, (4) Prediction by experiment, (5) Prediction by conceptual model, (6) Prediction by numerical simulation, and (7) Prediction by safety assessment model. Geologic future prediction should be cross-checked by several different methods. However, only geological evidence from the earth's history of nearly five billion years can verify long-range predictions for subterranean containment of waste which are usually based on short-range experiments and numerical modeling. On the geologically unstable Japanese archipelago, Japan is making extensive efforts for prediction of earthquakes and volcanic eruptions to reduce geological hazards. Long-range geological prediction is investigated for safe disposal of nuclear waste and for subterranean sequestration of CO 2 . (author)

  14. A polynomial chaos ensemble hydrologic prediction system for efficient parameter inference and robust uncertainty assessment

    Science.gov (United States)

    Wang, S.; Huang, G. H.; Baetz, B. W.; Huang, W.

    2015-11-01

    This paper presents a polynomial chaos ensemble hydrologic prediction system (PCEHPS) for an efficient and robust uncertainty assessment of model parameters and predictions, in which possibilistic reasoning is infused into probabilistic parameter inference with simultaneous consideration of randomness and fuzziness. The PCEHPS is developed through a two-stage factorial polynomial chaos expansion (PCE) framework, which consists of an ensemble of PCEs to approximate the behavior of the hydrologic model, significantly speeding up the exhaustive sampling of the parameter space. Multiple hypothesis testing is then conducted to construct an ensemble of reduced-dimensionality PCEs with only the most influential terms, which is meaningful for achieving uncertainty reduction and further acceleration of parameter inference. The PCEHPS is applied to the Xiangxi River watershed in China to demonstrate its validity and applicability. A detailed comparison between the HYMOD hydrologic model, the ensemble of PCEs, and the ensemble of reduced PCEs is performed in terms of accuracy and efficiency. Results reveal temporal and spatial variations in parameter sensitivities due to the dynamic behavior of hydrologic systems, and the effects (magnitude and direction) of parametric interactions depending on different hydrological metrics. The case study demonstrates that the PCEHPS is capable not only of capturing both expert knowledge and probabilistic information in the calibration process, but also of implementing an acceleration of more than 10 times faster than the hydrologic model without compromising the predictive accuracy.

  15. The role of the uncertainty in assessing future scenarios of water shortage in alluvial aquifers

    Science.gov (United States)

    Romano, Emanuele; Camici, Stefania; Brocca, Luca; Moramarco, Tommaso; Guyennon, Nicolas; Preziosi, Elisabetta

    2015-04-01

    There are many evidences that the combined effects of variations in precipitation and temperature due to climate change can result in a significant change of the recharge to groundwater at different time scales. A possible reduction of effective infiltration can result in a significant decrease, temporary or permanent, of the availability of the resource and, consequently, the sustainable pumping rate should be reassessed. In addition to this, one should also consider the so called indirect impacts of climate change, resulting from human intervention (e.g. augmentation of abstractions) which are feared to be even more important than the direct ones in the medium term: thus, a possible increase of episodes of shortage (i.e. the inability of the groundwater system to completely supply the water demand) can result both from change in the climate forcing and change in the demand. In order to assess future scenarios of water shortage a modelling chain is often used. It includes: 1) the use of General Circulation Models to estimate changes in temperature and precipitation; 2) downscaling procedures to match modeling scenarios to the observed meteorological time series; 3) soil-atmosphere modelling to estimate the time variation of the recharge to the aquifer; 4) groundwater flow models to simulate the water budget and piezometric head evolution; 5) future scenarios of groundwater quantitative status that include scenarios of demand variation. It is well known that each of these processing steps is affected by an intrinsic uncertainty that propagates through the whole chain leading to a final uncertainty on the piezometric head scenarios. The estimate of such an uncertainty is a key point for a correct management of groundwater resources, in case of water shortage due to prolonged droughts as well as for planning purposes. This study analyzes the uncertainty of the processing chain from GCM scenarios to its impact on an alluvial aquifer in terms of exploitation

  16. Uncertainty & sensitivity analysis of economic assessment of lactic acid production from crude glycerol - impact of price correlations

    DEFF Research Database (Denmark)

    Loureiro da Costa Lira Gargalo, Carina; Carvalho, Ana; Gernaey, Krist V.

    2017-01-01

    In this work, we investigate the impact of the expected price volatility and correlations on the overall economic assessment of lactic acid production from crude glycerol. In particular, the goals of this study are three-fold: (i) to understand how uncertainty in the inputs propagates to the model...... outputs; (ii) to understand the effect of the degree of pairwise correlation between input uncertainties on each other and on the outputs from the economic model (Net Present Value); and lastly, (iii) to estimate the first-order as well as independent sensitivity indices so as to identify which...... of the input uncertainties in the economic analysis affect the estimated NPV the most. To this end, we implemented algorithms in Matlab (R2015a) based on Monte Carlo sampling with permutation using Latin Hypercube Sampling with Iman Conover correlation control (Sin et al., 2009).The results have shown...

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

    Directory of Open Access Journals (Sweden)

    Yuanpu Xia

    2017-10-01

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

  18. Quantifying remarks to the question of uncertainties of the 'general dose assessment fundamentals'

    International Nuclear Information System (INIS)

    Brenk, H.D.; Vogt, K.J.

    1982-12-01

    Dose prediction models are always subject to uncertainties due to a number of factors including deficiencies in the model structure and uncertainties of the model input parameter values. In lieu of validation experiments the evaluation of these uncertainties is restricted to scientific judgement. Several attempts have been made in the literature to evaluate the uncertainties of the current dose assessment models resulting from uncertainties of the model input parameter values using stochastic approaches. Less attention, however, has been paid to potential sources of systematic over- and underestimations of the predicted doses due to deficiencies in the model structure. The present study addresses this aspect with regard to dose assessment models currently used for regulatory purposes. The influence of a number of basic simplifications and conservative assumptions has been investigated. Our systematic approach is exemplified by a comparison of doses evaluated on the basis of the regulatory guide model and a more realistic model respectively. This is done for 3 critical exposure pathways. As a result of this comparison it can be concluded that the currently used regularoty-type models include significant safety factors resulting in a systematic overprediction of dose to man up to two orders of magnitude. For this reason there are some indications that these models usually more than compensate the bulk of the stochastic uncertainties caused by the variability of the input parameter values. (orig.) [de

  19. Radon contents in groundwater and the uncertainty related to risk assessment

    Energy Technology Data Exchange (ETDEWEB)

    Fukui, Masami [Kyoto Univ. (Japan)

    1997-02-01

    The United States has proposed 11 Bq/l (300 pCi/l) as the maximum contaminant levels (MCLs) of radon. Japan has not set up the standards for drinking water. The problems about evaluation of effects of radon on organism and MCLs of radon in groundwater and drinking water in 12 countries were reported. The local area content the high concentrations of radon, but generally it`s low levels were observed in Nigeria, China and Mexico. The countries which content high concentration of radon were Greek, Slovakia, Bornholm Island and Scotland. There are high and low concentration area in US and Japan. I proposed an uncertainty scheme on risk assessment for the exposure by radon. (S.Y.)

  20. Replication quality assessment and uncertainty evaluation of a polymer precision injection moulded component

    DEFF Research Database (Denmark)

    Baruffi, Federico; Calaon, Matteo; Tosello, Guido

    2017-01-01

    Precision injection moulding holds a central role in manufacturing as only replication process currently capable of accurately producing complex shaped polymer parts integrating micrometric features on a mass scale production. In this scenario, a study on the replication quality of a polymer...... injection moulded precision component for telecommunication applications is presented. The effects of the process parameters on the component dimensional variation have been investigated using a statistical approach. Replication fidelity of produced parts has been assessed using a focus variation microscope...... with sub-micrometric resolution. Measurement uncertainty has then been evaluated, according to the GUM considering contributions from different process settings combinations and mould geometries. The analysis showed that the injection moulding manufacturing process and the utilized measurement chain...

  1. 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.

  2. 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

  3. Uncertainty characteristics of EPA's ground-water transport model for low-level waste performance assessment

    International Nuclear Information System (INIS)

    Yim, Man-Sung

    1995-01-01

    Performance assessment is an essential step either in design or in licensing processes to ensure the safety of any proposed radioactive waste disposal facilities. Since performance assessment requires the use of computer codes, understanding the characteristics of computer models used and the uncertainties of the estimated results is important. The PRESTO-EPA code, which was the basis of the Environmental Protection Agency's analysis for low-level-waste rulemaking, is widely used for various performance assessment activities in the country with no adequate information available for the uncertainty characteristics of the results. In this study, the groundwater transport model PRESTO-EPA was examined based on the analysis of 14 C transport along with the investigation of uncertainty characteristics

  4. International survey for good practices in forecasting uncertainty assessment and communication

    Science.gov (United States)

    Berthet, Lionel; Piotte, Olivier

    2014-05-01

    Achieving technically sound flood forecasts is a crucial objective for forecasters but remains of poor use if the users do not understand properly their significance and do not use it properly in decision making. One usual way to precise the forecasts limitations is to communicate some information about their uncertainty. Uncertainty assessment and communication to stakeholders are thus important issues for operational flood forecasting services (FFS) but remain open fields for research. French FFS wants to publish graphical streamflow and level forecasts along with uncertainty assessment in near future on its website (available to the greater public). In order to choose the technical options best adapted to its operational context, it carried out a survey among more than 15 fellow institutions. Most of these are providing forecasts and warnings to civil protection officers while some were mostly working for hydroelectricity suppliers. A questionnaire has been prepared in order to standardize the analysis of the practices of the surveyed institutions. The survey was conducted by gathering information from technical reports or from the scientific literature, as well as 'interviews' driven by phone, email discussions or meetings. The questionnaire helped in the exploration of practices in uncertainty assessment, evaluation and communication. Attention was paid to the particular context within which every insitution works, in the analysis drawn from raw results. Results show that most services interviewed assess their forecasts uncertainty. However, practices can differ significantly from a country to another. Popular techniques are ensemble approaches. They allow to take into account several uncertainty sources. Statistical past forecasts analysis (such as the quantile regressions) are also commonly used. Contrary to what was expected, only few services emphasize the role of the forecaster (subjective assessment). Similar contrasts can be observed in uncertainty

  5. 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.

  6. Assessment of Uncertainty-Based Screening Volumes for NASA Robotic LEO and GEO Conjunction Risk Assessment

    Science.gov (United States)

    Narvet, Steven W.; Frigm, Ryan C.; Hejduk, Matthew D.

    2011-01-01

    Conjunction Assessment operations require screening assets against the space object catalog by placing a pre-determined spatial volume around each asset and predicting when another object will violate that volume. The selection of the screening volume used for each spacecraft is a trade-off between observing all conjunction events that may pose a potential risk to the primary spacecraft and the ability to analyze those predicted events. If the screening volumes are larger, then more conjunctions can be observed and therefore the probability of a missed detection of a high risk conjunction event is small; however, the amount of data which needs to be analyzed increases. This paper characterizes the sensitivity of screening volume size to capturing typical orbit uncertainties and the expected number of conjunction events observed. These sensitivities are quantified in the form of a trade space that allows for selection of appropriate screen-ing volumes to fit the desired concept of operations, system limitations, and tolerable analyst workloads. This analysis will specifically highlight the screening volume determination and selection process for use in the NASA Conjunction Assessment Risk Analysis process but will also provide a general framework for other Owner / Operators faced with similar decisions.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-11-30

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

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

    Energy Technology Data Exchange (ETDEWEB)

    Webster, Mort David [MIT

    2015-03-10

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

  9. Uncertainties in effective dose estimates of adult CT head scans: The effect of head size

    International Nuclear Information System (INIS)

    Gregory, Kent J.; Bibbo, Giovanni; Pattison, John E.

    2009-01-01

    Purpose: This study is an extension of a previous study where the uncertainties in effective dose estimates from adult CT head scans were calculated using four CT effective dose estimation methods, three of which were computer programs (CT-EXPO, CTDOSIMETRY, and IMPACTDOSE) and one that involved the dose length product (DLP). However, that study did not include the uncertainty contribution due to variations in head sizes. Methods: The uncertainties due to head size variations were estimated by first using the computer program data to calculate doses to small and large heads. These doses were then compared with doses calculated for the phantom heads used by the computer programs. An uncertainty was then assigned based on the difference between the small and large head doses and the doses of the phantom heads. Results: The uncertainties due to head size variations alone were found to be between 4% and 26% depending on the method used and the patient gender. When these uncertainties were included with the results of the previous study, the overall uncertainties in effective dose estimates (stated at the 95% confidence interval) were 20%-31% (CT-EXPO), 15%-30% (CTDOSIMETRY), 20%-36% (IMPACTDOSE), and 31%-40% (DLP). Conclusions: For the computer programs, the lower overall uncertainties were still achieved when measured values of CT dose index were used rather than tabulated values. For DLP dose estimates, head size variations made the largest (for males) and second largest (for females) contributions to effective dose uncertainty. An improvement in the uncertainty of the DLP method dose estimates will be achieved if head size variation can be taken into account.

  10. Uncertainties in effective dose estimates of adult CT head scans: The effect of head size

    Energy Technology Data Exchange (ETDEWEB)

    Gregory, Kent J.; Bibbo, Giovanni; Pattison, John E. [Department of Medical Physics, Royal Adelaide Hospital, Adelaide, South Australia 5000 (Australia) and School of Electrical and Information Engineering (Applied Physics), University of South Australia, Mawson Lakes, South Australia 5095 (Australia); Division of Medical Imaging, Women' s and Children' s Hospital, North Adelaide, South Australia 5006 (Australia) and School of Electrical and Information Engineering (Applied Physics), University of South Australia, Mawson Lakes, South Australia 5095 (Australia); School of Electrical and Information Engineering (Applied Physics), University of South Australia, Mawson Lakes, South Australia 5095 (Australia)

    2009-09-15

    Purpose: This study is an extension of a previous study where the uncertainties in effective dose estimates from adult CT head scans were calculated using four CT effective dose estimation methods, three of which were computer programs (CT-EXPO, CTDOSIMETRY, and IMPACTDOSE) and one that involved the dose length product (DLP). However, that study did not include the uncertainty contribution due to variations in head sizes. Methods: The uncertainties due to head size variations were estimated by first using the computer program data to calculate doses to small and large heads. These doses were then compared with doses calculated for the phantom heads used by the computer programs. An uncertainty was then assigned based on the difference between the small and large head doses and the doses of the phantom heads. Results: The uncertainties due to head size variations alone were found to be between 4% and 26% depending on the method used and the patient gender. When these uncertainties were included with the results of the previous study, the overall uncertainties in effective dose estimates (stated at the 95% confidence interval) were 20%-31% (CT-EXPO), 15%-30% (CTDOSIMETRY), 20%-36% (IMPACTDOSE), and 31%-40% (DLP). Conclusions: For the computer programs, the lower overall uncertainties were still achieved when measured values of CT dose index were used rather than tabulated values. For DLP dose estimates, head size variations made the largest (for males) and second largest (for females) contributions to effective dose uncertainty. An improvement in the uncertainty of the DLP method dose estimates will be achieved if head size variation can be taken into account.

  11. Validation of methodology and uncertainty assessment of antimony determination in environmental materials using Neutron Activation Analysis

    International Nuclear Information System (INIS)

    Matsubara, Tassiane C.M.; Saiki, Mitiko; Zahn, Guilherme S.; Moreira, Edson G.

    2013-01-01

    Antimony is an element found in low concentrations in the environment. However, its determination has attracted great interest because of the knowledge of its toxicity and increasing application. Neutron activation analysis (NAA) is a suitable method for the determination of several elements in different types, but in case of Sb, the analysis presents some difficulties due to spectral interferences. The objective of this research was to validate the method of NAA and uncertainty assessment for Sb determination in environmental samples. The experimental procedure consisted of irradiating twelve certified reference samples of different kind of matrices. The samples were irradiated in the nuclear research reactor IEA R1 IPEN/CNEN/SP followed by measurement of induced radioactivity, using a hyperpure germanium detector coupled to a gamma ray spectrometry. The radioisotopes 122 Sb and 124 Sb were measured and the Sb concentrations with their respective uncertainties were obtained by the comparative method. Relative errors and values of Z scores were calculated to evaluate the accuracy of the results for Sb determination in certified reference materials. The evaluation of the components that contribute to uncertainty measurement of the Sb concentration, showed that the major uncertainty contribution is due to statistical counting. The results also indicated that the uncertainty value of the combined standard uncertainty depends on the radioisotope measured and the decay time used for counting. (author)

  12. Applications of Probabilistic Consequence Assessment Uncertainty Analysis for Plant Management (invited paper)

    International Nuclear Information System (INIS)

    Boardman, J.; Pearce, K.I.; Ponting, A.C.

    2000-01-01

    Probabilistic Consequence Assessment (PCA) models describe the dispersion of released radioactive materials and predict the resulting interaction with and influence on the environment and man. Increasing use is being made of PCA tools as an input to the evaluation and improvement of safety for nuclear installations. The nature and extent of the assessment performed varies considerably according to its intended purpose. Nevertheless with the increasing use of such techniques, greater attention has been given to the reliability of the methods used and the inherent uncertainty associated with their predictions. Uncertainty analyses can provide the decision-maker with information to quantify how uncertain the answer is and what drives that uncertainty. They often force a review of the baseline assumptions for any PCA methodology and provide a benchmark against which the impact of further changes in models and recommendations can be compared. This process provides valuable management information to help prioritise further actions or research. (author)

  13. A real-time assessment of measurement uncertainty in the experimental characterization of sprays

    International Nuclear Information System (INIS)

    Panão, M R O; Moreira, A L N

    2008-01-01

    This work addresses the estimation of the measurement uncertainty of discrete probability distributions used in the characterization of sprays. A real-time assessment of this measurement uncertainty is further investigated, particularly concerning the informative quality of the measured distribution and the influence of acquiring additional information on the knowledge retrieved from statistical analysis. The informative quality is associated with the entropy concept as understood in information theory (Shannon entropy), normalized by the entropy of the most informative experiment. A new empirical correlation is derived between the error accuracy of a discrete cumulative probability distribution and the normalized Shannon entropy. The results include case studies using: (i) spray impingement measurements to study the applicability of the real-time assessment of measurement uncertainty, and (ii) the simulation of discrete probability distributions of unknown shape or function to test the applicability of the new correlation

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

    DEFF Research Database (Denmark)

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

    2008-01-01

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

  15. A Framework for Treating Uncertainty to Facilitate Waste Disposal Decision Making - Application of the Approach to GCD Performance Assessment

    International Nuclear Information System (INIS)

    Brown, T.J.; Cochran, J.R.; Gallegos, D.P.

    1999-01-01

    This paper presents an approach for treating uncertainty in the performance assessment process to efficiently address regulatory performance objectives for radioactive waste disposal and discusses the application of the approach at the Greater Confinement Disposal site. In this approach, the performance assessment methodology uses probabilistic risk assessment concepts to guide effective decisions about site characterization activities and provides a path toward reasonable assurance regarding regulatory compliance decisions. Although the approach is particularly amenable to requirements that are probabilistic in nature, the approach is also applicable to deterministic standards such as the dose-based and concentration-based requirements

  16. Characterization uncertainty and its effects on models and performance

    International Nuclear Information System (INIS)

    Rautman, C.A.; Treadway, A.H.

    1991-01-01

    Geostatistical simulation is being used to develop multiple geologic models of rock properties at the proposed Yucca Mountain repository site. Because each replicate model contains the same known information, and is thus essentially indistinguishable statistically from others, the differences between models may be thought of as representing the uncertainty in the site description. The variability among performance measures, such as ground water travel time, calculated using these replicate models therefore quantifies the uncertainty in performance that arises from uncertainty in site characterization

  17. Analyzing the uncertainty of ensemble-based gridded observations in land surface simulations and drought assessment

    Science.gov (United States)

    Ahmadalipour, Ali; Moradkhani, Hamid

    2017-12-01

    Hydrologic modeling is one of the primary tools utilized for drought monitoring and drought early warning systems. Several sources of uncertainty in hydrologic modeling have been addressed in the literature. However, few studies have assessed the uncertainty of gridded observation datasets from a drought monitoring perspective. This study provides a hydrologic modeling oriented analysis of the gridded observation data uncertainties over the Pacific Northwest (PNW) and its implications on drought assessment. We utilized a recently developed 100-member ensemble-based observed forcing data to simulate hydrologic fluxes at 1/8° spatial resolution using Variable Infiltration Capacity (VIC) model, and compared the results with a deterministic observation. Meteorological and hydrological droughts are studied at multiple timescales over the basin, and seasonal long-term trends and variations of drought extent is investigated for each case. Results reveal large uncertainty of observed datasets at monthly timescale, with systematic differences for temperature records, mainly due to different lapse rates. The uncertainty eventuates in large disparities of drought characteristics. In general, an increasing trend is found for winter drought extent across the PNW. Furthermore, a ∼3% decrease per decade is detected for snow water equivalent (SWE) over the PNW, with the region being more susceptible to SWE variations of the northern Rockies than the western Cascades. The agricultural areas of southern Idaho demonstrate decreasing trend of natural soil moisture as a result of precipitation decline, which implies higher appeal for anthropogenic water storage and irrigation systems.

  18. Accounting for multiple sources of uncertainty in impact assessments: The example of the BRACE study

    Science.gov (United States)

    O'Neill, B. C.

    2015-12-01

    Assessing climate change impacts often requires the use of multiple scenarios, types of models, and data sources, leading to a large number of potential sources of uncertainty. For example, a single study might require a choice of a forcing scenario, climate model, bias correction and/or downscaling method, societal development scenario, model (typically several) for quantifying elements of societal development such as economic and population growth, biophysical model (such as for crop yields or hydrology), and societal impact model (e.g. economic or health model). Some sources of uncertainty are reduced or eliminated by the framing of the question. For example, it may be useful to ask what an impact outcome would be conditional on a given societal development pathway, forcing scenario, or policy. However many sources of uncertainty remain, and it is rare for all or even most of these sources to be accounted for. I use the example of a recent integrated project on the Benefits of Reduced Anthropogenic Climate changE (BRACE) to explore useful approaches to uncertainty across multiple components of an impact assessment. BRACE comprises 23 papers that assess the differences in impacts between two alternative climate futures: those associated with Representative Concentration Pathways (RCPs) 4.5 and 8.5. It quantifies difference in impacts in terms of extreme events, health, agriculture, tropical cyclones, and sea level rise. Methodologically, it includes climate modeling, statistical analysis, integrated assessment modeling, and sector-specific impact modeling. It employs alternative scenarios of both radiative forcing and societal development, but generally uses a single climate model (CESM), partially accounting for climate uncertainty by drawing heavily on large initial condition ensembles. Strengths and weaknesses of the approach to uncertainty in BRACE are assessed. Options under consideration for improving the approach include the use of perturbed physics

  19. The effect of uncertainty and cooperative behavior on operational performance: Evidence from Brazilian firms

    Directory of Open Access Journals (Sweden)

    Eliane Pereira Zamith Brito

    2017-12-01

    Full Text Available This study aims to examine the effect of managers’ uncertainty on cooperative behavior in interorganizational relationships, and how this affects operational performance. We conducted a survey with 225 Brazilian managers, and analyzed data using confirmatory factor analysis and structural equation modelling. Results present: a a negative influence of uncertainty of state on operational performance; b a positive influence of uncertainty of effect on uncertainty of response; c a significant influence of uncertainty of response on cooperative behavior; and d a positive influence of cooperative behavior on performance. The results indicated that cooperation and uncertainty accounted for 18.8% of the variability of operational performance. Considering the uncertainty that plagues Latin societies, this study can help to create more efficient ways to deal with the phenomenon. Rather than turning a blind eye to uncertainty, our study underscores it and treats it like another business environment issue.

  20. Assessing the uncertainty of forest carbon estimates using the FVS family of diameter increment equations

    Science.gov (United States)

    Matthew B. Russell; Aaron R. Weiskittel; Anthony W. D’Amato

    2012-01-01

    Serving as a carbon (C) accounting tool, the Forest Vegetation Simulator (FVS) is widely used by forest managers and researchers to forecast future forest C stocks. Assessments of the uncertainty that FVS equations provide in terms of their ability to accurately project forest biomass and C would seemingly differ, depending on the region and scale of interest to the...

  1. Ex-plant consequence assessment for NUREG-1150: models, typical results, uncertainties

    International Nuclear Information System (INIS)

    Sprung, J.L.

    1988-01-01

    The assessment of ex-plant consequences for NUREG-1150 source terms was performed using the MELCOR Accident Consequence Code System (MACCS). This paper briefly discusses the following elements of MACCS consequence calculations: input data, phenomena modeled, computational framework, typical results, controlling phenomena, and uncertainties. Wherever possible, NUREG-1150 results will be used to illustrate the discussion. 28 references

  2. Uncertainty assessment of the breath methane concentration method to determine methane production of dairy cows

    NARCIS (Netherlands)

    Wu, Liansun; Groot Koerkamp, Peter W.G.; Ogink, Nico

    2018-01-01

    The breath methane concentration method uses the methane concentrations in the cow's breath during feed bin visits as a proxy for the methane production rate. The objective of this study was to assess the uncertainty of a breath methane concentration method in a feeder and its capability to measure

  3. Measures of Model Uncertainty in the Assessment of Primary Stresses in Ship Structures

    DEFF Research Database (Denmark)

    Östergaard, Carsten; Dogliani, Mario; Guedes Soares, Carlos

    1996-01-01

    The paper considers various models and methods commonly used for linear elastic stress analysis and assesses the uncertainty involved in their application to the analysis of the distribution of primary stresses in the hull of a containership example, through statistical evaluations of the results...

  4. Effect of the sample matrix on measurement uncertainty in X-ray fluorescence analysis

    International Nuclear Information System (INIS)

    Morgenstern, P.; Brueggemann, L.; Wennrich, R.

    2005-01-01

    The estimation of measurement uncertainty, with reference to univariate calibration functions, is discussed in detail in the Eurachem Guide 'Quantifying Uncertainty in Analytical Measurement'. The adoption of these recommendations to quantitative X-ray fluorescence analysis (XRF) involves basic problems which are above all due to the strong influence of the sample matrix on the analytical response. In XRF-analysis, the proposed recommendations are consequently applicable only to the matrix corrected response. The application is also restricted with regard to both the matrices and analyte concentrations. In this context the present studies are aimed at the problems to predict measurement uncertainty also with reference to more variable sample compositions. The corresponding investigations are focused on the use of the intensity of the Compton scattered tube line as an internal standard to assess the effect of the individual sample matrix on the analytical response relatively to a reference matrix. Based on this concept the estimation of the measurement uncertainty of an analyte presented in an unknown specimen can be predicted in consideration of the data obtained under defined matrix conditions

  5. 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

  6. A Belief Rule Based Expert System to Assess Mental Disorder under Uncertainty

    DEFF Research Database (Denmark)

    Hossain, Mohammad Shahadat; Afif Monrat, Ahmed; Hasan, Mamun

    2016-01-01

    to ignorance, incompleteness, and randomness. So, a belief rule-based expert system (BRBES) has been designed and developed with the capability of handling the uncertainties mentioned. Evidential reasoning works as the inference engine and the belief rule base as the knowledge representation schema......Mental disorder is a change of mental or behavioral pattern that causes sufferings and impairs the ability to function in ordinary life. In psychopathology, the assessment methods of mental disorder contain various types of uncertainties associated with signs and symptoms. This study identifies...

  7. 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

  8. Paradoxical effects of compulsive perseveration : Sentence repetition causes semantic uncertainty

    NARCIS (Netherlands)

    Giele, Catharina L.; van den Hout, Marcel A.; Engelhard, Iris M.; Dek, Eliane C P

    2014-01-01

    Many patients with obsessive compulsive disorder (OCD) perform perseverative checking behavior to reduce uncertainty, but studies have shown that this ironically increases uncertainty. Some patients also tend to perseveratively repeat sentences. The aim of this study was to examine whether sentence

  9. Uncertainty and Sensitivity Analysis Results Obtained in the 1996 Performance Assessment for the Waste Isolation Pilot Plant

    Energy Technology Data Exchange (ETDEWEB)

    Bean, J.E.; Berglund, J.W.; Davis, F.J.; Economy, K.; Garner, J.W.; Helton, J.C.; Johnson, J.D.; MacKinnon, R.J.; Miller, J.; O' Brien, D.G.; Ramsey, J.L.; Schreiber, J.D.; Shinta, A.; Smith, L.N.; Stockman, C.; Stoelzel, D.M.; Vaughn, P.

    1998-09-01

    The Waste Isolation Pilot Plant (WPP) is located in southeastern New Mexico and is being developed by the U.S. Department of Energy (DOE) for the geologic (deep underground) disposal of transuranic (TRU) waste. A detailed performance assessment (PA) for the WIPP was carried out in 1996 and supports an application by the DOE to the U.S. Environmental Protection Agency (EPA) for the certification of the WIPP for the disposal of TRU waste. The 1996 WIPP PA uses a computational structure that maintains a separation between stochastic (i.e., aleatory) and subjective (i.e., epistemic) uncertainty, with stochastic uncertainty arising from the many possible disruptions that could occur over the 10,000 yr regulatory period that applies to the WIPP and subjective uncertainty arising from the imprecision with which many of the quantities required in the PA are known. Important parts of this structure are (1) the use of Latin hypercube sampling to incorporate the effects of subjective uncertainty, (2) the use of Monte Carlo (i.e., random) sampling to incorporate the effects of stochastic uncertainty, and (3) the efficient use of the necessarily limited number of mechanistic calculations that can be performed to support the analysis. The use of Latin hypercube sampling generates a mapping from imprecisely known analysis inputs to analysis outcomes of interest that provides both a display of the uncertainty in analysis outcomes (i.e., uncertainty analysis) and a basis for investigating the effects of individual inputs on these outcomes (i.e., sensitivity analysis). The sensitivity analysis procedures used in the PA include examination of scatterplots, stepwise regression analysis, and partial correlation analysis. Uncertainty and sensitivity analysis results obtained as part of the 1996 WIPP PA are presented and discussed. Specific topics considered include two phase flow in the vicinity of the repository, radionuclide release from the repository, fluid flow and radionuclide

  10. Uncertainty and Sensitivity Analysis Results Obtained in the 1996 Performance Assessment for the Waste Isolation Pilot Plant

    International Nuclear Information System (INIS)

    Bean, J.E.; Berglund, J.W.; Davis, F.J.; Economy, K.; Garner, J.W.; Helton, J.C.; Johnson, J.D.; MacKinnon, R.J.; Miller, J.; O'Brien, D.G.; Ramsey, J.L.; Schreiber, J.D.; Shinta, A.; Smith, L.N.; Stockman, C.; Stoelzel, D.M.; Vaughn, P.

    1998-01-01

    The Waste Isolation Pilot Plant (WPP) is located in southeastern New Mexico and is being developed by the U.S. Department of Energy (DOE) for the geologic (deep underground) disposal of transuranic (TRU) waste. A detailed performance assessment (PA) for the WIPP was carried out in 1996 and supports an application by the DOE to the U.S. Environmental Protection Agency (EPA) for the certification of the WIPP for the disposal of TRU waste. The 1996 WIPP PA uses a computational structure that maintains a separation between stochastic (i.e., aleatory) and subjective (i.e., epistemic) uncertainty, with stochastic uncertainty arising from the many possible disruptions that could occur over the 10,000 yr regulatory period that applies to the WIPP and subjective uncertainty arising from the imprecision with which many of the quantities required in the PA are known. Important parts of this structure are (1) the use of Latin hypercube sampling to incorporate the effects of subjective uncertainty, (2) the use of Monte Carlo (i.e., random) sampling to incorporate the effects of stochastic uncertainty, and (3) the efficient use of the necessarily limited number of mechanistic calculations that can be performed to support the analysis. The use of Latin hypercube sampling generates a mapping from imprecisely known analysis inputs to analysis outcomes of interest that provides both a display of the uncertainty in analysis outcomes (i.e., uncertainty analysis) and a basis for investigating the effects of individual inputs on these outcomes (i.e., sensitivity analysis). The sensitivity analysis procedures used in the PA include examination of scatterplots, stepwise regression analysis, and partial correlation analysis. Uncertainty and sensitivity analysis results obtained as part of the 1996 WIPP PA are presented and discussed. Specific topics considered include two phase flow in the vicinity of the repository, radionuclide release from the repository, fluid flow and radionuclide

  11. Prediction uncertainty and data worth assessment for groundwater transport times in an agricultural catchment

    Science.gov (United States)

    Zell, Wesley O.; Culver, Teresa B.; Sanford, Ward E.

    2018-06-01

    Uncertainties about the age of base-flow discharge can have serious implications for the management of degraded environmental systems where subsurface pathways, and the ongoing release of pollutants that accumulated in the subsurface during past decades, dominate the water quality signal. Numerical groundwater models may be used to estimate groundwater return times and base-flow ages and thus predict the time required for stakeholders to see the results of improved agricultural management practices. However, the uncertainty inherent in the relationship between (i) the observations of atmospherically-derived tracers that are required to calibrate such models and (ii) the predictions of system age that the observations inform have not been investigated. For example, few if any studies have assessed the uncertainty of numerically-simulated system ages or evaluated the uncertainty reductions that may result from the expense of collecting additional subsurface tracer data. In this study we combine numerical flow and transport modeling of atmospherically-derived tracers with prediction uncertainty methods to accomplish four objectives. First, we show the relative importance of head, discharge, and tracer information for characterizing response times in a uniquely data rich catchment that includes 266 age-tracer measurements (SF6, CFCs, and 3H) in addition to long term monitoring of water levels and stream discharge. Second, we calculate uncertainty intervals for model-simulated base-flow ages using both linear and non-linear methods, and find that the prediction sensitivity vector used by linear first-order second-moment methods results in much larger uncertainties than non-linear Monte Carlo methods operating on the same parameter uncertainty. Third, by combining prediction uncertainty analysis with multiple models of the system, we show that data-worth calculations and monitoring network design are sensitive to variations in the amount of water leaving the system via

  12. Calibration of tri-axial MEMS accelerometers in the low-frequency range – Part 2: Uncertainty assessment

    Directory of Open Access Journals (Sweden)

    G. D'Emilia

    2018-05-01

    Full Text Available A comparison among three methods for the calibration of tri-axial accelerometers, in particular MEMS, is presented in this paper, paying attention to the uncertainty assessment of each method. The first method is performed according to the ISO 16063 standards. Two innovative methods are analysed, both suitable for in-field application. The effects on the whole uncertainty of the following aspects have been evaluated: the test bench performances in realizing the reference motion, the vibration reference sensor, the geometrical parameters and the data processing techniques. The uncertainty contributions due to the offset and the transverse sensitivity are also studied, by calibrating two different types of accelerometers, a piezoelectric one and a capacitive one, to check their effect on the accuracy of the methods under comparison. The reproducibility of methods is demonstrated. Relative uncertainty of methods ranges from 3 to 5 %, depending on the complexity of the model and of the requested operations. The results appear promising for low-cost calibration of new tri-axial accelerometers of MEMS type.

  13. Conflict or Caveats? Effects of Media Portrayals of Scientific Uncertainty on Audience Perceptions of New Technologies.

    Science.gov (United States)

    Binder, Andrew R; Hillback, Elliott D; Brossard, Dominique

    2016-04-01

    Research indicates that uncertainty in science news stories affects public assessment of risk and uncertainty. However, the form in which uncertainty is presented may also affect people's risk and uncertainty assessments. For example, a news story that features an expert discussing both what is known and what is unknown about a topic may convey a different form of scientific uncertainty than a story that features two experts who hold conflicting opinions about the status of scientific knowledge of the topic, even when both stories contain the same information about knowledge and its boundaries. This study focuses on audience uncertainty and risk perceptions regarding the emerging science of nanotechnology by manipulating whether uncertainty in a news story about potential risks is attributed to expert sources in the form of caveats (individual uncertainty) or conflicting viewpoints (collective uncertainty). Results suggest that the type of uncertainty portrayed does not impact audience feelings of uncertainty or risk perceptions directly. Rather, the presentation of the story influences risk perceptions only among those who are highly deferent to scientific authority. Implications for risk communication theory and practice are discussed. © 2015 Society for Risk Analysis.

  14. Evaluation and Quantification of Uncertainty in the Modeling of Contaminant Transport and Exposure Assessment at a Radioactive Waste Disposal Site

    Science.gov (United States)

    Tauxe, J.; Black, P.; Carilli, J.; Catlett, K.; Crowe, B.; Hooten, M.; Rawlinson, S.; Schuh, A.; Stockton, T.; Yucel, V.

    2002-12-01

    The disposal of low-level radioactive waste (LLW) in the United States (U.S.) is a highly regulated undertaking. The U.S. Department of Energy (DOE), itself a large generator of such wastes, requires a substantial amount of analysis and assessment before permitting disposal of LLW at its facilities. One of the requirements that must be met in assessing the performance of a disposal site and technology is that a Performance Assessment (PA) demonstrate "reasonable expectation" that certain performance objectives, such as dose to a hypothetical future receptor, not be exceeded. The phrase "reasonable expectation" implies recognition of uncertainty in the assessment process. In order for this uncertainty to be quantified and communicated to decision makers, the PA computer model must accept probabilistic (uncertain) input (parameter values) and produce results which reflect that uncertainty as it is propagated through the model calculations. The GoldSim modeling software was selected for the task due to its unique facility with both probabilistic analysis and radioactive contaminant transport. Probabilistic model parameters range from water content and other physical properties of alluvium to the activity of radionuclides disposed to the amount of time a future resident might be expected to spend tending a garden. Although these parameters govern processes which are defined in isolation as rather simple differential equations, the complex interaction of couple processes makes for a highly nonlinear system with often unanticipated results. The decision maker has the difficult job of evaluating the uncertainty of modeling results in the context of granting permission for LLW disposal. This job also involves the evaluation of alternatives, such as the selection of disposal technologies. Various scenarios can be evaluated in the model, so that the effects of, for example, using a thicker soil cap over the waste cell can be assessed. This ability to evaluate mitigation

  15. Analytical Uncertainty Propagation in Life Cycle Inventory and Impact Assessment: Application to an Automobile Front Panel

    DEFF Research Database (Denmark)

    Hong, Jinglan; Shaked, Shanna; Rosenbaum, Ralph K.

    2010-01-01

    to develop and apply to both inventory and impact assessment an explicit and transparent analytical approach to uncertainty. This approach applies Taylor series expansions to the uncertainty propagation of lognormally distributed parameters. Materials and methods We first apply the Taylor series expansion...... determine a range and a best estimate of a) the squared geometric standard deviation on the ratio of the two scenario scores, "A/B", and b) the degree of confidence in the prediction that the impact of scenario A is lower than B (i.e., the probability that A/B75%). For the aluminum panel, the electricity...... and aluminum primary production, as well as the light oil consumption, are the dominant contributors to the uncertainty. The developed approach for scenario comparisons, differentiating between common and independent parameters, leads to results similar to those of a Monte Carlo analysis; for all tested cases...

  16. Uncertainty propagation in a 3-D thermal code for performance assessment of a nuclear waste disposal

    International Nuclear Information System (INIS)

    Dutfoy, A.; Ritz, J.B.

    2001-01-01

    Given the very large time scale involved, the performance assessment of a nuclear waste repository requires numerical modelling. Because we are uncertain of the exact value of the input parameters, we have to analyse the impact of these uncertainties on the outcome of the physical models. The EDF Division Research and Development has set a reliability method to propagate these uncertainties or variability through models which requires much less physical simulations than the usual simulation methods. We apply the reliability method MEFISTO to a base case modelling the heat transfers in a virtual disposal in the future site of the French underground research laboratory, in the East of France. This study is led in collaboration with ANDRA which is the French Nuclear Waste Management Agency. With this exercise, we want to evaluate the thermal behaviour of a concept related to the variation of physical parameters and their uncertainty. (author)

  17. The French biofuels mandates under cost uncertainty - an assessment based on robust optimization

    International Nuclear Information System (INIS)

    Lorne, Daphne; Tchung-Ming, Stephane

    2012-01-01

    This paper investigates the impact of primary energy and technology cost uncertainty on the achievement of renewable and especially biofuel policies - mandates and norms - in France by 2030. A robust optimization technique that allows to deal with uncertainty sets of high dimensionality is implemented in a TIMES-based long-term planning model of the French energy transport and electricity sectors. The energy system costs and potential benefits (GHG emissions abatements, diversification) of the French renewable mandates are assessed within this framework. The results of this systemic analysis highlight how setting norms and mandates allows to reduce the variability of CO 2 emissions reductions and supply mix diversification when the costs of technological progress and prices are uncertain. Beyond that, we discuss the usefulness of robust optimization in complement of other techniques to integrate uncertainty in large-scale energy models. (authors)

  18. Some concepts of model uncertainty for performance assessments of nuclear waste repositories

    International Nuclear Information System (INIS)

    Eisenberg, N.A.; Sagar, B.; Wittmeyer, G.W.

    1994-01-01

    Models of the performance of nuclear waste repositories will be central to making regulatory decisions regarding the safety of such facilities. The conceptual model of repository performance is represented by mathematical relationships, which are usually implemented as one or more computer codes. A geologic system may allow many conceptual models, which are consistent with the observations. These conceptual models may or may not have the same mathematical representation. Experiences in modeling the performance of a waste repository representation. Experiences in modeling the performance of a waste repository (which is, in part, a geologic system), show that this non-uniqueness of conceptual models is a significant source of model uncertainty. At the same time, each conceptual model has its own set of parameters and usually, it is not be possible to completely separate model uncertainty from parameter uncertainty for the repository system. Issues related to the origin of model uncertainty, its relation to parameter uncertainty, and its incorporation in safety assessments are discussed from a broad regulatory perspective. An extended example in which these issues are explored numerically is also provided

  19. Uncertainty assessment in gamma spectrometric measurements of plutonium isotope ratios and age

    Energy Technology Data Exchange (ETDEWEB)

    Ramebaeck, H., E-mail: henrik.ramebeck@foi.se [Swedish Defence Research Agency, FOI, Division of CBRN Defence and Security, SE-901 82 Umea (Sweden); Chalmers University of Technology, Department of Chemical and Biological Engineering, Nuclear Chemistry, SE-412 96 Goeteborg (Sweden); Nygren, U.; Tovedal, A. [Swedish Defence Research Agency, FOI, Division of CBRN Defence and Security, SE-901 82 Umea (Sweden); Ekberg, C.; Skarnemark, G. [Chalmers University of Technology, Department of Chemical and Biological Engineering, Nuclear Chemistry, SE-412 96 Goeteborg (Sweden)

    2012-09-15

    A method for the assessment of the combined uncertainty in gamma spectrometric measurements of plutonium composition and age was evaluated. Two materials were measured. Isotope dilution inductively coupled plasma sector field mass spectrometry (ID-ICP-SFMS) was used as a reference method for comparing the results obtained with the gamma spectrometric method for one of the materials. For this material (weapons grade plutonium) the measurement results were in agreement between the two methods for all measurands. Moreover, the combined uncertainty in all isotope ratios considered in this material (R{sub Pu238/Pu239}, R{sub Pu240/Pu239}, R{sub Pu241/Pu239}, and R{sub Am241/Pu241} for age determination) were limited by counting statistics. However, the combined uncertainty for the other material (fuel grade plutonium) were limited by the response fit, which shows that the uncertainty in the response function is important to include in the combined measurement uncertainty of gamma spectrometric measurements of plutonium.

  20. Assessment the impact of samplers change on the uncertainty related to geothermalwater sampling

    Science.gov (United States)

    Wątor, Katarzyna; Mika, Anna; Sekuła, Klaudia; Kmiecik, Ewa

    2018-02-01

    The aim of this study is to assess the impact of samplers change on the uncertainty associated with the process of the geothermal water sampling. The study was carried out on geothermal water exploited in Podhale region, southern Poland (Małopolska province). To estimate the uncertainty associated with sampling the results of determinations of metasilicic acid (H2SiO3) in normal and duplicate samples collected in two series were used (in each series the samples were collected by qualified sampler). Chemical analyses were performed using ICP-OES method in the certified Hydrogeochemical Laboratory of the Hydrogeology and Engineering Geology Department at the AGH University of Science and Technology in Krakow (Certificate of Polish Centre for Accreditation No. AB 1050). To evaluate the uncertainty arising from sampling the empirical approach was implemented, based on double analysis of normal and duplicate samples taken from the same well in the series of testing. The analyses of the results were done using ROBAN software based on technique of robust statistics analysis of variance (rANOVA). Conducted research proved that in the case of qualified and experienced samplers uncertainty connected with the sampling can be reduced what results in small measurement uncertainty.

  1. Systematic and non-systematic effects of the uncertainty of the sample position in gamma-ray spectrometry

    International Nuclear Information System (INIS)

    Vidmar, T.; Korun, M.

    2004-01-01

    When cylindrical samples placed coaxially with the detector are measured on a gamma-ray spectrometer, the position of the sample very often deviates from an ideal one with the axes of the sample and the detector less than perfectly aligned. If a calibrated source is used prior to the measurement and is presumed to have been positioned correctly, one might conclude that the misalignment of the measured sample should result in an uncertainty of the reported nuclide activity, since the efficiencies of the sample and the calibrated source are effectively different due to the difference in placement. The efficiency of a displaced cylindrical sample, however, is always lower than the one of a sample that is perfectly aligned. The net effect of misalignment can therefore be not only an increase in the uncertainty of the activity, but also a systematic error in its evaluation. Since the Guide to the Expression of Uncertainty in Measurement requires that all such systematic effects be corrected for, we have developed a method to assess the change in the efficiency resulting from misalignment and to introduce the required correction. The calculation of this correction only requires knowledge of basic sample and detector data. The uncertainty of the reported activity can then also be assessed and is influenced by the uncertainty of the efficiency evaluated around its new, corrected value. An appropriate expression for this uncertainty has been derived

  2. Uncertainty in recharge estimation: impact on groundwater vulnerability assessments for the Pearl Harbor Basin, O'ahu, Hawai'i, U.S.A.

    Science.gov (United States)

    Giambelluca, Thomas W.; Loague, Keith; Green, Richard E.; Nullet, Michael A.

    1996-06-01

    In this paper, uncertainty in recharge estimates is investigated relative to its impact on assessments of groundwater contamination vulnerability using a relatively simple pesticide mobility index, attenuation factor (AF). We employ a combination of first-order uncertainty analysis (FOUA) and sensitivity analysis to investigate recharge uncertainties for agricultural land on the island of O'ahu, Hawai'i, that is currently, or has been in the past, under sugarcane or pineapple cultivation. Uncertainty in recharge due to recharge component uncertainties is 49% of the mean for sugarcane and 58% of the mean for pineapple. The components contributing the largest amounts of uncertainty to the recharge estimate are irrigation in the case of sugarcane and precipitation in the case of pineapple. For a suite of pesticides formerly or currently used in the region, the contribution to AF uncertainty of recharge uncertainty was compared with the contributions of other AF components: retardation factor (RF), a measure of the effects of sorption; soil-water content at field capacity (ΘFC); and pesticide half-life (t1/2). Depending upon the pesticide, the contribution of recharge to uncertainty ranks second or third among the four AF components tested. The natural temporal variability of recharge is another source of uncertainty in AF, because the index is calculated using the time-averaged recharge rate. Relative to the mean, recharge variability is 10%, 44%, and 176% for the annual, monthly, and daily time scales, respectively, under sugarcane, and 31%, 112%, and 344%, respectively, under pineapple. In general, uncertainty in AF associated with temporal variability in recharge at all time scales exceeds AF. For chemicals such as atrazine or diuron under sugarcane, and atrazine or bromacil under pineapple, the range of AF uncertainty due to temporal variability in recharge encompasses significantly higher levels of leaching potential at some locations than that indicated by the

  3. Living with uncertainty: from the precautionary principle to the methodology of ongoing normative assessment

    International Nuclear Information System (INIS)

    Dupuy, J.P.; Grinbaum, A.

    2005-01-01

    The analysis of our epistemic situation regarding singular events, such as abrupt climate change, shows essential limitations in the traditional modes of dealing with uncertainty. Typical cognitive barriers lead to the paralysis of action. What is needed is taking seriously the reality of the future. We argue for the application of the methodology of ongoing normative assessment. We show that it is, paradoxically, a matter of forming a project on the basis of a fixed future which one does not want, and this in a coordinated way at the level of social institutions. Ongoing assessment may be viewed as a prescription to live with uncertainty, in a particular sense of the term, in order for a future catastrophe not to occur. The assessment is necessarily normative in that it must include the anticipation of a retrospective ethical judgment on present choices (notion of moral luck). (authors)

  4. [Uncertainty characterization approaches for ecological risk assessment of polycyclic aromatic hydrocarbon in Taihu Lake].

    Science.gov (United States)

    Guo, Guang-Hui; Wu, Feng-Chang; He, Hong-Ping; Feng, Cheng-Lian; Zhang, Rui-Qing; Li, Hui-Xian

    2012-04-01

    Probabilistic approaches, such as Monte Carlo Sampling (MCS) and Latin Hypercube Sampling (LHS), and non-probabilistic approaches, such as interval analysis, fuzzy set theory and variance propagation, were used to characterize uncertainties associated with risk assessment of sigma PAH8 in surface water of Taihu Lake. The results from MCS and LHS were represented by probability distributions of hazard quotients of sigma PAH8 in surface waters of Taihu Lake. The probabilistic distribution of hazard quotient were obtained from the results of MCS and LHS based on probabilistic theory, which indicated that the confidence intervals of hazard quotient at 90% confidence level were in the range of 0.000 18-0.89 and 0.000 17-0.92, with the mean of 0.37 and 0.35, respectively. In addition, the probabilities that the hazard quotients from MCS and LHS exceed the threshold of 1 were 9.71% and 9.68%, respectively. The sensitivity analysis suggested the toxicity data contributed the most to the resulting distribution of quotients. The hazard quotient of sigma PAH8 to aquatic organisms ranged from 0.000 17 to 0.99 using interval analysis. The confidence interval was (0.001 5, 0.016 3) at the 90% confidence level calculated using fuzzy set theory, and the confidence interval was (0.000 16, 0.88) at the 90% confidence level based on the variance propagation. These results indicated that the ecological risk of sigma PAH8 to aquatic organisms were low. Each method has its own set of advantages and limitations, which was based on different theory; therefore, the appropriate method should be selected on a case-by-case to quantify the effects of uncertainties on the ecological risk assessment. Approach based on the probabilistic theory was selected as the most appropriate method to assess the risk of sigma PAH8 in surface water of Taihu Lake, which provided an important scientific foundation of risk management and control for organic pollutants in water.

  5. Accounting for uncertainty and risk in assessments of impacts for offshore oil and gas leasing proposals

    International Nuclear Information System (INIS)

    Wildermann, R.; Beittel, R.

    1993-01-01

    The Minerals Management Service (MMS) of the US Department of the Interior prepares an environmental impact statement (EIS) for each proposal to lease a portion of the Outer Continental Shelf (OCS) for oil and gas exploration and development. The nature, magnitude, and timing of the activities that would ultimately result from leasing are subject to wide speculation, primarily because of uncertainties about the locations and amounts of petroleum hydrocarbons that exist on most potential leases. These uncertainties create challenges in preparing EIS's that meet National Environmental Policy Act requirements and provide information useful to decision-makers. This paper examines the constraints that uncertainty places on the detail and reliability of assessments of impacts from potential OCS development. It further describes how the MMS accounts for uncertainty in developing reasonable scenarios of future events that can be evaluated in the EIS. A process for incorporating the risk of accidental oil spills into assessments of expected impacts is also presented. Finally, the paper demonstrates through examination of case studies how a balance can be achieved between the need for an EIS to present impacts in sufficient detail to allow a meaningful comparison of alternatives and the tendency to push the analysis beyond credible limits

  6. An end-to-end assessment of range uncertainty in proton therapy using animal tissues

    Science.gov (United States)

    Zheng, Yuanshui; Kang, Yixiu; Zeidan, Omar; Schreuder, Niek

    2016-11-01

    Accurate assessment of range uncertainty is critical in proton therapy. However, there is a lack of data and consensus on how to evaluate the appropriate amount of uncertainty. The purpose of this study is to quantify the range uncertainty in various treatment conditions in proton therapy, using transmission measurements through various animal tissues. Animal tissues, including a pig head, beef steak, and lamb leg, were used in this study. For each tissue, an end-to-end test closely imitating patient treatments was performed. This included CT scan simulation, treatment planning, image-guided alignment, and beam delivery. Radio-chromic films were placed at various depths in the distal dose falloff region to measure depth dose. Comparisons between measured and calculated doses were used to evaluate range differences. The dose difference at the distal falloff between measurement and calculation depends on tissue type and treatment conditions. The estimated range difference was up to 5, 6 and 4 mm for the pig head, beef steak, and lamb leg irradiation, respectively. Our study shows that the TPS was able to calculate proton range within about 1.5% plus 1.5 mm. Accurate assessment of range uncertainty in treatment planning would allow better optimization of proton beam treatment, thus fully achieving proton beams’ superior dose advantage over conventional photon-based radiation therapy.

  7. Seismic Hazard Assessment and Uncertainties Treatment: Discussion on the current French regulation, practices and open issues

    International Nuclear Information System (INIS)

    Berge-Thierry, Catherine

    2014-01-01

    Taking into account the seismic risk in the context of nuclear safety in France is guided by the Fundamental Safety Rule (RFS2001-01) for the assessment of seismic hazard, and by the Guide ASN/2/01 for the design rules of civil engineering structures. These two references have been updated respectively in 2001 and 2006 and validated by the Nuclear Safety Authority. The French approach is anchored on a deterministic approach. We propose to recall the principles of the methodology recommended by the RFS 2001-01, and to illustrate the advantages and limitations highlighted in recent years. Indeed, this regulatory framework is used both in the design stage and for safety reassessment of all nuclear facilities, power reactors and experimental laboratories and factories. We focus on: (i) key parameters of the approach, and their level of knowledge, (ii) key steps and principles that lead to a non-homogeneous approach between various geographic sites, depending on the seismic activity and / or knowledge, (iii) on physical phenomena (such as the geometric extension of the seismic source, the complexity of earthquake rupture on the fault plane) that are not taken into account, or for which (2D and 3D site effects, and non-linear soil behavior under strong motions), the RFS 2001-01 approach does not provide any guidance, (iv) consideration of epistemic and random uncertainties. We discuss also the probabilistic approaches widely implemented both in France as recently to establish the seismic zoning (reference for the regulation of conventional building and classified installations for the environment), used worldwide and strongly supported by the international Atomic Energy Agency references (safety guides and guidelines). The Tohoku earthquake that occurred in Japan on March 11, 2011, triggering the tsunami that itself caused the nuclear accident at Fukushima Daiichi site has resulted in the realization in France of the Complementary Safety Studies as a request of the

  8. Use of screening techniques to reduce uncertainty in risk assessment at a former manufactured gas plant site

    International Nuclear Information System (INIS)

    Logan, C.M.; Walden, R.H.; Baker, S.R.; Pekar, Z.; LaKind, J.S.; MacFarlane, I.D.

    1995-01-01

    Preliminary analysis of risks from a former manufactured gas plant (MGP) site revealed six media associated with potential exposure pathways: soils, air, surface water, groundwater, estuarine sediments, and aquatic biota. Contaminants of concern (COCs) include polycyclic aromatic hydrocarbons, volatile organic hydrocarbons, metals, cyanide, and PCBs. Available chemical data, including site-specific measurements and existing data from other sources (e.g., agency monitoring programs, Chesapeake Bay Program), were evaluated for potential utility in risk assessment. Where sufficient data existed, risk calculations were performed using central tendency and reasonable maximum exposure estimates. Where site-specific data were not available, risks were estimated using conservatively high default assumptions for dose and/or exposure duration. Because of the large number of potential exposure pathways and COCs, a sensitivity analysis was conducted to determine which information most influences risk assessment outcome so that any additional data collection to reduce uncertainty can be cost-effectively targeted. The sensitivity analysis utilized two types of information: (1) the impact that uncertainty in risk input values has on output risk estimates, and (2) the potential improvement in key risk input values, and consequently output values, if better site-specific data were available. A decision matrix using both quantitative and qualitative information was developed to prioritize sampling strategies to minimize uncertainty in the final risk assessment

  9. effect of uncertainty on the fatigue reliability of reinforced concrete

    African Journals Online (AJOL)

    user

    2016-07-03

    Jul 3, 2016 ... Keywords: Fatigue, cracks, structural reliability, uncertainties, high stress loads. 1. INTRODUCTION ... infrastructure system, are extremely vulnerable to this action of fatigue. .... Shear in the deck beam, G(x3) is the equation for.

  10. Incorporating the effects of socioeconomic uncertainty into priority setting for conservation investment.

    Science.gov (United States)

    McBride, Marissa F; Wilson, Kerrie A; Bode, Michael; Possingham, Hugh P

    2007-12-01

    Uncertainty in the implementation and outcomes of conservation actions that is not accounted for leaves conservation plans vulnerable to potential changes in future conditions. We used a decision-theoretic approach to investigate the effects of two types of investment uncertainty on the optimal allocation of global conservation resources for land acquisition in the Mediterranean Basin. We considered uncertainty about (1) whether investment will continue and (2) whether the acquired biodiversity assets are secure, which we termed transaction uncertainty and performance uncertainty, respectively. We also developed and tested the robustness of different rules of thumb for guiding the allocation of conservation resources when these sources of uncertainty exist. In the presence of uncertainty in future investment ability (transaction uncertainty), the optimal strategy was opportunistic, meaning the investment priority should be to act where uncertainty is highest while investment remains possible. When there was a probability that investments would fail (performance uncertainty), the optimal solution became a complex trade-off between the immediate biodiversity benefits of acting in a region and the perceived longevity of the investment. In general, regions were prioritized for investment when they had the greatest performance certainty, even if an alternative region was highly threatened or had higher biodiversity value. The improved performance of rules of thumb when accounting for uncertainty highlights the importance of explicitly incorporating sources of investment uncertainty and evaluating potential conservation investments in the context of their likely long-term success.

  11. Parameter uncertainty effects on variance-based sensitivity analysis

    International Nuclear Information System (INIS)

    Yu, W.; Harris, T.J.

    2009-01-01

    In the past several years there has been considerable commercial and academic interest in methods for variance-based sensitivity analysis. The industrial focus is motivated by the importance of attributing variance contributions to input factors. A more complete understanding of these relationships enables companies to achieve goals related to quality, safety and asset utilization. In a number of applications, it is possible to distinguish between two types of input variables-regressive variables and model parameters. Regressive variables are those that can be influenced by process design or by a control strategy. With model parameters, there are typically no opportunities to directly influence their variability. In this paper, we propose a new method to perform sensitivity analysis through a partitioning of the input variables into these two groupings: regressive variables and model parameters. A sequential analysis is proposed, where first an sensitivity analysis is performed with respect to the regressive variables. In the second step, the uncertainty effects arising from the model parameters are included. This strategy can be quite useful in understanding process variability and in developing strategies to reduce overall variability. When this method is used for nonlinear models which are linear in the parameters, analytical solutions can be utilized. In the more general case of models that are nonlinear in both the regressive variables and the parameters, either first order approximations can be used, or numerically intensive methods must be used

  12. Effectively Communicating the Uncertainties Surrounding Ebola Virus Transmission.

    Directory of Open Access Journals (Sweden)

    Andy Kilianski

    2015-10-01

    Full Text Available The current Ebola virus outbreak has highlighted the uncertainties surrounding many aspects of Ebola virus virology, including routes of transmission. The scientific community played a leading role during the outbreak-potentially, the largest of its kind-as many of the questions surrounding ebolaviruses have only been interrogated in the laboratory. Scientists provided an invaluable resource for clinicians, public health officials, policy makers, and the lay public in understanding the progress of Ebola virus disease and the continuing outbreak. Not all of the scientific communication, however, was accurate or effective. There were multiple instances of published articles during the height of the outbreak containing potentially misleading scientific language that spurred media overreaction and potentially jeopardized preparedness and policy decisions at critical points. Here, we use articles declaring the potential for airborne transmission of Ebola virus as a case study in the inaccurate reporting of basic science, and we provide recommendations for improving the communication about unknown aspects of disease during public health crises.

  13. Effectively Communicating the Uncertainties Surrounding Ebola Virus Transmission.

    Science.gov (United States)

    Kilianski, Andy; Evans, Nicholas G

    2015-10-01

    The current Ebola virus outbreak has highlighted the uncertainties surrounding many aspects of Ebola virus virology, including routes of transmission. The scientific community played a leading role during the outbreak-potentially, the largest of its kind-as many of the questions surrounding ebolaviruses have only been interrogated in the laboratory. Scientists provided an invaluable resource for clinicians, public health officials, policy makers, and the lay public in understanding the progress of Ebola virus disease and the continuing outbreak. Not all of the scientific communication, however, was accurate or effective. There were multiple instances of published articles during the height of the outbreak containing potentially misleading scientific language that spurred media overreaction and potentially jeopardized preparedness and policy decisions at critical points. Here, we use articles declaring the potential for airborne transmission of Ebola virus as a case study in the inaccurate reporting of basic science, and we provide recommendations for improving the communication about unknown aspects of disease during public health crises.

  14. Data related uncertainty in near-surface vulnerability assessments for agrochemicals in the San Joaquin Valley.

    Science.gov (United States)

    Loague, Keith; Blanke, James S; Mills, Melissa B; Diaz-Diaz, Ricardo; Corwin, Dennis L

    2012-01-01

    Precious groundwater resources across the United States have been contaminated due to decades-long nonpoint-source applications of agricultural chemicals. Assessing the impact of past, ongoing, and future chemical applications for large-scale agriculture operations is timely for designing best-management practices to prevent subsurface pollution. Presented here are the results from a series of regional-scale vulnerability assessments for the San Joaquin Valley (SJV). Two relatively simple indices, the retardation and attenuation factors, are used to estimate near-surface vulnerabilities based on the chemical properties of 32 pesticides and the variability of both soil characteristics and recharge rates across the SJV. The uncertainties inherit to these assessments, derived from the uncertainties within the chemical and soil data bases, are estimated using first-order analyses. The results are used to screen and rank the chemicals based on mobility and leaching potential, without and with consideration of data-related uncertainties. Chemicals of historic high visibility in the SJV (e.g., atrazine, DBCP [dibromochloropropane], ethylene dibromide, and simazine) are ranked in the top half of those considered. Vulnerability maps generated for atrazine and DBCP, featured for their legacy status in the study area, clearly illustrate variations within and across the assessments. For example, the leaching potential is greater for DBCP than for atrazine, the leaching potential for DBCP is greater for the spatially variable recharge values than for the average recharge rate, and the leaching potentials for both DBCP and atrazine are greater for the annual recharge estimates than for the monthly recharge estimates. The data-related uncertainties identified in this study can be significant, targeting opportunities for improving future vulnerability assessments. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America

  15. Variability and uncertainty in Swedish exposure factors for use in quantitative exposure assessments.

    Science.gov (United States)

    Filipsson, Monika; Öberg, Tomas; Bergbäck, Bo

    2011-01-01

    Information of exposure factors used in quantitative risk assessments has previously been compiled and reported for U.S. and European populations. However, due to the advancement of science and knowledge, these reports are in continuous need of updating with new data. Equally important is the change over time of many exposure factors related to both physiological characteristics and human behavior. Body weight, skin surface, time use, and dietary habits are some of the most obvious examples covered here. A wealth of data is available from literature not primarily gathered for the purpose of risk assessment. Here we review a number of key exposure factors and compare these factors between northern Europe--here represented by Sweden--and the United States. Many previous compilations of exposure factor data focus on interindividual variability and variability between sexes and age groups, while uncertainty is mainly dealt with in a qualitative way. In this article variability is assessed along with uncertainty. As estimates of central tendency and interindividual variability, mean, standard deviation, skewness, kurtosis, and multiple percentiles were calculated, while uncertainty was characterized using 95% confidence intervals for these parameters. The presented statistics are appropriate for use in deterministic analyses using point estimates for each input parameter as well as in probabilistic assessments. © 2010 Society for Risk Analysis.

  16. Transforming Medical Assessment: Integrating Uncertainty Into the Evaluation of Clinical Reasoning in Medical Education.

    Science.gov (United States)

    Cooke, Suzette; Lemay, Jean-Francois

    2017-06-01

    In an age where practicing physicians have access to an overwhelming volume of clinical information and are faced with increasingly complex medical decisions, the ability to execute sound clinical reasoning is essential to optimal patient care. The authors propose two concepts that are philosophically paramount to the future assessment of clinical reasoning in medicine: assessment in the context of "uncertainty" (when, despite all of the information that is available, there is still significant doubt as to the best diagnosis, investigation, or treatment), and acknowledging that it is entirely possible (and reasonable) to have more than "one correct answer." The purpose of this article is to highlight key elements related to these two core concepts and discuss genuine barriers that currently exist on the pathway to creating such assessments. These include acknowledging situations of uncertainty, creating clear frameworks that define progressive levels of clinical reasoning skills, providing validity evidence to increase the defensibility of such assessments, considering the comparative feasibility with other forms of assessment, and developing strategies to evaluate the impact of these assessment methods on future learning and practice. The authors recommend that concerted efforts be directed toward these key areas to help advance the field of clinical reasoning assessment, improve the clinical care decisions made by current and future physicians, and have positive outcomes for patients. It is anticipated that these and subsequent efforts will aid in reaching the goal of making future assessment in medical education more representative of current-day clinical reasoning and decision making.

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

    International Nuclear Information System (INIS)

    Fathauer, P.M.

    1995-08-01

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

  18. Bayesian uncertainty assessment of flood predictions in ungauged urban basins for conceptual rainfall-runoff models

    Directory of Open Access Journals (Sweden)

    A. E. Sikorska

    2012-04-01

    Full Text Available Urbanization and the resulting land-use change strongly affect the water cycle and runoff-processes in watersheds. Unfortunately, small urban watersheds, which are most affected by urban sprawl, are mostly ungauged. This makes it intrinsically difficult to assess the consequences of urbanization. Most of all, it is unclear how to reliably assess the predictive uncertainty given the structural deficits of the applied models. In this study, we therefore investigate the uncertainty of flood predictions in ungauged urban basins from structurally uncertain rainfall-runoff models. To this end, we suggest a procedure to explicitly account for input uncertainty and model structure deficits using Bayesian statistics with a continuous-time autoregressive error model. In addition, we propose a concise procedure to derive prior parameter distributions from base data and successfully apply the methodology to an urban catchment in Warsaw, Poland. Based on our results, we are able to demonstrate that the autoregressive error model greatly helps to meet the statistical assumptions and to compute reliable prediction intervals. In our study, we found that predicted peak flows were up to 7 times higher than observations. This was reduced to 5 times with Bayesian updating, using only few discharge measurements. In addition, our analysis suggests that imprecise rainfall information and model structure deficits contribute mostly to the total prediction uncertainty. In the future, flood predictions in ungauged basins will become more important due to ongoing urbanization as well as anthropogenic and climatic changes. Thus, providing reliable measures of uncertainty is crucial to support decision making.

  19. Integrating uncertainties to the combined environmental and economic assessment of algal biorefineries: A Monte Carlo approach.

    Science.gov (United States)

    Pérez-López, Paula; Montazeri, Mahdokht; Feijoo, Gumersindo; Moreira, María Teresa; Eckelman, Matthew J

    2018-06-01

    The economic and environmental performance of microalgal processes has been widely analyzed in recent years. However, few studies propose an integrated process-based approach to evaluate economic and environmental indicators simultaneously. Biodiesel is usually the single product and the effect of environmental benefits of co-products obtained in the process is rarely discussed. In addition, there is wide variation of the results due to inherent variability of some parameters as well as different assumptions in the models and limited knowledge about the processes. In this study, two standardized models were combined to provide an integrated simulation tool allowing the simultaneous estimation of economic and environmental indicators from a unique set of input parameters. First, a harmonized scenario was assessed to validate the joint environmental and techno-economic model. The findings were consistent with previous assessments. In a second stage, a Monte Carlo simulation was applied to evaluate the influence of variable and uncertain parameters in the model output, as well as the correlations between the different outputs. The simulation showed a high probability of achieving favorable environmental performance for the evaluated categories and a minimum selling price ranging from $11gal -1 to $106gal -1 . Greenhouse gas emissions and minimum selling price were found to have the strongest positive linear relationship, whereas eutrophication showed weak correlations with the other indicators (namely greenhouse gas emissions, cumulative energy demand and minimum selling price). Process parameters (especially biomass productivity and lipid content) were the main source of variation, whereas uncertainties linked to the characterization methods and economic parameters had limited effect on the results. Copyright © 2018 Elsevier B.V. All rights reserved.

  20. Uncertainty and sensitivity analysis methodology in a level-I PSA (Probabilistic Safety Assessment)

    International Nuclear Information System (INIS)

    Nunez McLeod, J.E.; Rivera, S.S.

    1997-01-01

    This work presents a methodology for sensitivity and uncertainty analysis, applicable to a probabilistic safety assessment level I. The work contents are: correct association of distributions to parameters, importance and qualification of expert opinions, generations of samples according to sample sizes, and study of the relationships among system variables and system response. A series of statistical-mathematical techniques are recommended along the development of the analysis methodology, as well different graphical visualization for the control of the study. (author) [es

  1. UpWind D1. Uncertainties in wind assessment with LIDAR

    Energy Technology Data Exchange (ETDEWEB)

    Lindeloew-Marsden, P.

    2009-01-15

    In this report sources influencing wind assessments with lidars are listed and discussed. Comparisons with mast mounted cup anemometers are presented and the magnitudes of the errors from the listed error sources are estimated. Finally an attempt to define uncertainty windows for the current state of the two commercial wind sensing lidars is presented. The results in this report give important feedback on system improvements to manufacturers and an estimation of the current ability for wind farm developers which are potential users. (author)

  2. Real Options Effect of Uncertainty and Labor Demand Shocks on the Housing Market

    OpenAIRE

    Lee, Gabriel; Nguyen Thanh, Binh; Strobel, Johannes

    2016-01-01

    This paper shows that uncertainty affects the housing market in two significant ways. First, uncertainty shocks adversely affect housing prices but not the quantities that are traded. Controlling for a broad set of variables in fixed-effects regressions, we find that uncertainty shocks reduce housing prices and median sales prices in the amount of 1.4% and 1.8%, respectively, but the effect is not statistically significant for the percentage changes of all homes sold. Second, when...

  3. Damage assessment of composite plate structures with material and measurement uncertainty

    Science.gov (United States)

    Chandrashekhar, M.; Ganguli, Ranjan

    2016-06-01

    Composite materials are very useful in structural engineering particularly in weight sensitive applications. Two different test models of the same structure made from composite materials can display very different dynamic behavior due to large uncertainties associated with composite material properties. Also, composite structures can suffer from pre-existing imperfections like delaminations, voids or cracks during fabrication. In this paper, we show that modeling and material uncertainties in composite structures can cause considerable problem in damage assessment. A recently developed C0 shear deformable locking free refined composite plate element is employed in the numerical simulations to alleviate modeling uncertainty. A qualitative estimate of the impact of modeling uncertainty on the damage detection problem is made. A robust Fuzzy Logic System (FLS) with sliding window defuzzifier is used for delamination damage detection in composite plate type structures. The FLS is designed using variations in modal frequencies due to randomness in material properties. Probabilistic analysis is performed using Monte Carlo Simulation (MCS) on a composite plate finite element model. It is demonstrated that the FLS shows excellent robustness in delamination detection at very high levels of randomness in input data.

  4. Uncertainty Assessment: Reservoir Inflow Forecasting with Ensemble Precipitation Forecasts and HEC-HMS

    Directory of Open Access Journals (Sweden)

    Sheng-Chi Yang

    2014-01-01

    Full Text Available During an extreme event, having accurate inflow forecasting with enough lead time helps reservoir operators decrease the impact of floods downstream. Furthermore, being able to efficiently operate reservoirs could help maximize flood protection while saving water for drier times of the year. This study combines ensemble quantitative precipitation forecasts and a hydrological model to provide a 3-day reservoir inflow in the Shihmen Reservoir, Taiwan. A total of six historical typhoons were used for model calibration, validation, and application. An understanding of cascaded uncertainties from the numerical weather model through the hydrological model is necessary for a better use for forecasting. This study thus conducted an assessment of forecast uncertainty on magnitude and timing of peak and cumulative inflows. It found that using the ensemble-mean had less uncertainty than randomly selecting individual member. The inflow forecasts with shorter length of cumulative time had a higher uncertainty. The results showed that using the ensemble precipitation forecasts with the hydrological model would have the advantage of extra lead time and serve as a valuable reference for operating reservoirs.

  5. Characterization of stochastic uncertainty in the 1996 performance assessment for the Waste Isolation Pilot Plant

    International Nuclear Information System (INIS)

    Helton, Jon Craig; Davis, Freddie J.; Johnson, J.D.

    2000-01-01

    The 1996 performance assessment (PA) for the Waste Isolation Pilot Plant (WIPP) maintains a separation between stochastic (i.e., aleatory) and subjective (i.e., epistemic) uncertainty, with stochastic uncertainty arising from the possible disruptions that could occur at the WIPP over the 10,000 yr regulatory period specified by the US Environmental Protection Agency (40 CFR 191, 40 CFR 194) and subjective uncertainty arising from an inability to uniquely characterize many of the inputs required in the 1996 WIPP PA. The characterization of stochastic uncertainty is discussed including drilling intrusion time, drilling location penetration of excavated/nonexcavated areas of the repository, penetration of pressurized brine beneath the repository, borehole plugging patterns, activity level of waste, and occurrence of potash mining. Additional topics discussed include sampling procedures, generation of individual 10,000 yr futures for the WIPP, construction of complementary cumulative distribution functions (CCDFs), mechanistic calculations carried out to support CCDF construction the Kaplan/Garrick ordered triple representation for risk and determination of scenarios and scenario probabilities

  6. Uncertainties in environmental impact assessments due to expert opinion. Case study. Radioactive waste in Slovenia

    International Nuclear Information System (INIS)

    Kontic, B.; Ravnik, M.

    1998-01-01

    A comprehensive study was done at the J. Stefan Institute in Ljubljana and the School of Environmental Sciences in Nova Gorica in relation to sources of uncertainties in long-term environmental impact assessment (EIA). Under the research two main components were examined: first, methodology of the preparation of an EIA, and second validity of an expert opinion. Following the findings of the research a survey was performed in relation to assessing acceptability of radioactive waste repository by the regulatory. The components of dose evaluation in different time frames were examined in terms of susceptibility to uncertainty. Uncertainty associated to human exposure in the far future is so large that dose and risk, as individual numerical indicators of safety, by our opinion, should not be used in compliance assessment for radioactive waste repository. On the other hand, results of the calculations on the amount and activity of low and intermediate level waste and the spent fuel from the Krsko NPP show that expert's understanding of the treated questions can be expressed in transparent way giving credible output of the models used.(author)

  7. Effect of uncertainties on probabilistic-based design capacity of hydrosystems

    Science.gov (United States)

    Tung, Yeou-Koung

    2018-02-01

    Hydrosystems engineering designs involve analysis of hydrometric data (e.g., rainfall, floods) and use of hydrologic/hydraulic models, all of which contribute various degrees of uncertainty to the design process. Uncertainties in hydrosystem designs can be generally categorized into aleatory and epistemic types. The former arises from the natural randomness of hydrologic processes whereas the latter are due to knowledge deficiency in model formulation and model parameter specification. This study shows that the presence of epistemic uncertainties induces uncertainty in determining the design capacity. Hence, the designer needs to quantify the uncertainty features of design capacity to determine the capacity with a stipulated performance reliability under the design condition. Using detention basin design as an example, the study illustrates a methodological framework by considering aleatory uncertainty from rainfall and epistemic uncertainties from the runoff coefficient, curve number, and sampling error in design rainfall magnitude. The effects of including different items of uncertainty and performance reliability on the design detention capacity are examined. A numerical example shows that the mean value of the design capacity of the detention basin increases with the design return period and this relation is found to be practically the same regardless of the uncertainty types considered. The standard deviation associated with the design capacity, when subject to epistemic uncertainty, increases with both design frequency and items of epistemic uncertainty involved. It is found that the epistemic uncertainty due to sampling error in rainfall quantiles should not be ignored. Even with a sample size of 80 (relatively large for a hydrologic application) the inclusion of sampling error in rainfall quantiles resulted in a standard deviation about 2.5 times higher than that considering only the uncertainty of the runoff coefficient and curve number. Furthermore, the

  8. Assessing the uncertainty of soil moisture impacts on convective precipitation using a new ensemble approach

    Directory of Open Access Journals (Sweden)

    O. Henneberg

    2018-05-01

    Full Text Available Soil moisture amount and distribution control evapotranspiration and thus impact the occurrence of convective precipitation. Many recent model studies demonstrate that changes in initial soil moisture content result in modified convective precipitation. However, to quantify the resulting precipitation changes, the chaotic behavior of the atmospheric system needs to be considered. Slight changes in the simulation setup, such as the chosen model domain, also result in modifications to the simulated precipitation field. This causes an uncertainty due to stochastic variability, which can be large compared to effects caused by soil moisture variations. By shifting the model domain, we estimate the uncertainty of the model results. Our novel uncertainty estimate includes 10 simulations with shifted model boundaries and is compared to the effects on precipitation caused by variations in soil moisture amount and local distribution. With this approach, the influence of soil moisture amount and distribution on convective precipitation is quantified. Deviations in simulated precipitation can only be attributed to soil moisture impacts if the systematic effects of soil moisture modifications are larger than the inherent simulation uncertainty at the convection-resolving scale.We performed seven experiments with modified soil moisture amount or distribution to address the effect of soil moisture on precipitation. Each of the experiments consists of 10 ensemble members using the deep convection-resolving COSMO model with a grid spacing of 2.8 km. Only in experiments with very strong modification in soil moisture do precipitation changes exceed the model spread in amplitude, location or structure. These changes are caused by a 50 % soil moisture increase in either the whole or part of the model domain or by drying the whole model domain. Increasing or decreasing soil moisture both predominantly results in reduced precipitation rates. Replacing the soil

  9. Quantifying the Effects of Historical Land Cover Conversion Uncertainty on Global Carbon and Climate Estimates

    Science.gov (United States)

    Di Vittorio, A. V.; Mao, J.; Shi, X.; Chini, L.; Hurtt, G.; Collins, W. D.

    2018-01-01

    Previous studies have examined land use change as a driver of global change, but the translation of land use change into land cover conversion has been largely unconstrained. Here we quantify the effects of land cover conversion uncertainty on the global carbon and climate system using the integrated Earth System Model. Our experiments use identical land use change data and vary land cover conversions to quantify associated uncertainty in carbon and climate estimates. Land cover conversion uncertainty is large, constitutes a 5 ppmv range in estimated atmospheric CO2 in 2004, and generates carbon uncertainty that is equivalent to 80% of the net effects of CO2 and climate and 124% of the effects of nitrogen deposition during 1850-2004. Additionally, land cover uncertainty generates differences in local surface temperature of over 1°C. We conclude that future studies addressing land use, carbon, and climate need to constrain and reduce land cover conversion uncertainties.

  10. Effect of uncertainty parameters on graphene sheets Young's modulus prediction

    International Nuclear Information System (INIS)

    Sahlaoui, Habib; Sidhom Habib; Guedri, Mohamed

    2013-01-01

    Software based on molecular structural mechanics approach (MSMA) and using finite element method (FEM) has been developed to predict the Young's modulus of graphene sheets. Obtained results have been compared to results available in the literature and good agreement has been shown when the same values of uncertainty parameters are used. A sensibility of the models to their uncertainty parameters has been investigated using a stochastic finite element method (SFEM). The different values of the used uncertainty parameters, such as molecular mechanics force field constants k_r and k_θ, thickness (t) of a graphene sheet and length ( L_B) of a carbon carbon bonds, have been collected from the literature. Strong sensibilities of 91% to the thickness and of 21% to the stretching force (k_r) have been shown. The results justify the great difference between Young's modulus predicted values of the graphene sheets and their large disagreement with experimental results.

  11. Assessing the relative importance of parameter and forcing uncertainty and their interactions in conceptual hydrological model simulations

    Science.gov (United States)

    Mockler, E. M.; Chun, K. P.; Sapriza-Azuri, G.; Bruen, M.; Wheater, H. S.

    2016-11-01

    Predictions of river flow dynamics provide vital information for many aspects of water management including water resource planning, climate adaptation, and flood and drought assessments. Many of the subjective choices that modellers make including model and criteria selection can have a significant impact on the magnitude and distribution of the output uncertainty. Hydrological modellers are tasked with understanding and minimising the uncertainty surrounding streamflow predictions before communicating the overall uncertainty to decision makers. Parameter uncertainty in conceptual rainfall-runoff models has been widely investigated, and model structural uncertainty and forcing data have been receiving increasing attention. This study aimed to assess uncertainties in streamflow predictions due to forcing data and the identification of behavioural parameter sets in 31 Irish catchments. By combining stochastic rainfall ensembles and multiple parameter sets for three conceptual rainfall-runoff models, an analysis of variance model was used to decompose the total uncertainty in streamflow simulations into contributions from (i) forcing data, (ii) identification of model parameters and (iii) interactions between the two. The analysis illustrates that, for our subjective choices, hydrological model selection had a greater contribution to overall uncertainty, while performance criteria selection influenced the relative intra-annual uncertainties in streamflow predictions. Uncertainties in streamflow predictions due to the method of determining parameters were relatively lower for wetter catchments, and more evenly distributed throughout the year when the Nash-Sutcliffe Efficiency of logarithmic values of flow (lnNSE) was the evaluation criterion.

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

    Directory of Open Access Journals (Sweden)

    S. Lari

    2012-11-01

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

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

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

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

  13. [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.

  14. Assessing the performance and benefits of customer distributed generation developers under uncertainties

    International Nuclear Information System (INIS)

    Zangiabadi, Mansoureh; Feuillet, Rene; Lesani, Hamid; Hadj-Said, Nouredine; Kvaloy, Jan T.

    2011-01-01

    In this paper, the performance of customer-owned distributed generation (DG) units is quantified from different perspectives through an uncertainty study. A Monte Carlo-based method is applied to assess the stochastic operation of the customer-owned DG units in the power distribution system. Several cases are studied to analyze the impact on system performance of using such generators, with the emphasis on benefits. The results of the studied cases show that proper operation of customer-owned DG units placed close to significant consumption centers offers several benefits which lead to significant energy savings and improvement in the performance indices while maintaining the cost-effectiveness. Furthermore, based on the energy demand, different electricity price scenarios considering a cost sensitivity analysis are performed to indicate how the variations in electricity price influence each scenario's feasibility. It is concluded that implementation of a proper energy purchase policy, and allocating the benefits of DG units to the owners, improves the economic performance of their investments and encourages customer DG developers to connect DG to the distribution network. -- Research highlights: → Focusing on the main drives for customers and utilities to adopt DG solutions. → Assessing the stochastic operation of the customer-owned DG units in the power distribution system using Monte Carlo method. → Studying the technical and economic impacts of customer-owned DG units in a distribution system. → Implementing the proper power purchase policy by the utility to encourage DG owners to operate at peak load periods. → Performing different electricity price scenarios to indicate the ability of customer-owned DG units to reduce the volatility in prices.

  15. Effect of minimal length uncertainty on the mass-radius relation of white dwarfs

    Science.gov (United States)

    Mathew, Arun; Nandy, Malay K.

    2018-06-01

    Generalized uncertainty relation that carries the imprint of quantum gravity introduces a minimal length scale into the description of space-time. It effectively changes the invariant measure of the phase space through a factor (1 + βp2) - 3 so that the equation of state for an electron gas undergoes a significant modification from the ideal case. It has been shown in the literature (Rashidi 2016) that the ideal Chandrasekhar limit ceases to exist when the modified equation of state due to the generalized uncertainty is taken into account. To assess the situation in a more complete fashion, we analyze in detail the mass-radius relation of Newtonian white dwarfs whose hydrostatic equilibria are governed by the equation of state of the degenerate relativistic electron gas subjected to the generalized uncertainty principle. As the constraint of minimal length imposes a severe restriction on the availability of high momentum states, it is speculated that the central Fermi momentum cannot have values arbitrarily higher than pmax ∼β - 1 / 2. When this restriction is imposed, it is found that the system approaches limiting mass values higher than the Chandrasekhar mass upon decreasing the parameter β to a value given by a legitimate upper bound. Instead, when the more realistic restriction due to inverse β-decay is considered, it is found that the mass and radius approach the values 1.4518 M⊙ and 601.18 km near the legitimate upper bound for the parameter β.

  16. Assessment and characterization of the total geometric uncertainty in Gamma Knife radiosurgery using polymer gels

    International Nuclear Information System (INIS)

    Moutsatsos, A.; Karaiskos, P.; Pantelis, E.; Georgiou, E.; Petrokokkinos, L.; Sakelliou, L.; Torrens, M.; Seimenis, I.

    2013-01-01

    Purpose: This work proposes and implements an experimental methodology, based on polymer gels, for assessing the total geometric uncertainty and characterizing its contributors in Gamma Knife (GK) radiosurgery. Methods: A treatment plan consisting of 26, 4-mm GK single shot dose distributions, covering an extended region of the Leksell stereotactic space, was prepared and delivered to a polymer gel filled polymethyl methacrylate (PMMA) head phantom (16 cm diameter) used to accurately reproduce every link in the GK treatment chain. The center of each shot served as a “control point” in the assessment of the GK total geometric uncertainty, which depends on (a) the spatial dose delivery uncertainty of the PERFEXION GK unit used in this work, (b) the spatial distortions inherent in MR images commonly used for target delineation, and (c) the geometric uncertainty contributor associated with the image registration procedure performed by the Leksell GammaPlan (LGP) treatment planning system (TPS), in the case that registration is directly based on the apparent fiducial locations depicted in each MR image by the N-shaped rods on the Leksell localization box. The irradiated phantom was MR imaged at 1.5 T employing a T2-weighted pulse sequence. Four image series were acquired by alternating the frequency encoding axis and reversing the read gradient polarity, thus allowing the characterization of the MR-related spatial distortions. Results: MR spatial distortions stemming from main field (B 0 ) inhomogeneity as well as from susceptibility and chemical shift phenomena (also known as sequence dependent distortions) were found to be of the order of 0.5 mm, while those owing to gradient nonlinearities (also known as sequence independent distortions) were found to increase with distance from the MR scanner isocenter extending up to 0.47 mm at an Euclidean distance of 69.6 mm. Regarding the LGP image registration procedure, the corresponding average contribution to the total

  17. Assessment and characterization of the total geometric uncertainty in Gamma Knife radiosurgery using polymer gels.

    Science.gov (United States)

    Moutsatsos, A; Karaiskos, P; Petrokokkinos, L; Sakelliou, L; Pantelis, E; Georgiou, E; Torrens, M; Seimenis, I

    2013-03-01

    This work proposes and implements an experimental methodology, based on polymer gels, for assessing the total geometric uncertainty and characterizing its contributors in Gamma Knife (GK) radiosurgery. A treatment plan consisting of 26, 4-mm GK single shot dose distributions, covering an extended region of the Leksell stereotactic space, was prepared and delivered to a polymer gel filled polymethyl methacrylate (PMMA) head phantom (16 cm diameter) used to accurately reproduce every link in the GK treatment chain. The center of each shot served as a "control point" in the assessment of the GK total geometric uncertainty, which depends on (a) the spatial dose delivery uncertainty of the PERFEXION GK unit used in this work, (b) the spatial distortions inherent in MR images commonly used for target delineation, and (c) the geometric uncertainty contributor associated with the image registration procedure performed by the Leksell GammaPlan (LGP) treatment planning system (TPS), in the case that registration is directly based on the apparent fiducial locations depicted in each MR image by the N-shaped rods on the Leksell localization box. The irradiated phantom was MR imaged at 1.5 T employing a T2-weighted pulse sequence. Four image series were acquired by alternating the frequency encoding axis and reversing the read gradient polarity, thus allowing the characterization of the MR-related spatial distortions. MR spatial distortions stemming from main field (B0) inhomogeneity as well as from susceptibility and chemical shift phenomena (also known as sequence dependent distortions) were found to be of the order of 0.5 mm, while those owing to gradient nonlinearities (also known as sequence independent distortions) were found to increase with distance from the MR scanner isocenter extending up to 0.47 mm at an Euclidean distance of 69.6 mm. Regarding the LGP image registration procedure, the corresponding average contribution to the total geometric uncertainty ranged from

  18. Effect of Discontinuities and Uncertainties on the Response and Failure of Composite Structures

    Science.gov (United States)

    Noor, Ahmed K.; Perry, Ferman W.; Poteat, Marcia M. (Technical Monitor)

    2000-01-01

    The overall goal of this research was to assess the effect of discontinuities and uncertainties on the nonlinear response and failure of composite structures subjected to combined mechanical and thermal loads. The four key elements of the study were: (1) development of simple and efficient procedures for the accurate determination of transverse shear and transverse normal stresses in structural sandwiches as well as in unstiffened and stiffened composite panels and shells; (2) study the effects of transverse stresses on the response, damage initiation and propagation in composite and sandwich structures; (3) use of hierarchical sensitivity coefficients to identify the major parameters that affect the response and damage in each of the different levels in the hierarchy (micro-mechanical, layer, panel, subcomponent and component levels); and (4) application of fuzzy set techniques to identify the range and variation of possible responses. The computational models developed were used in conjunction with experiments, to understand the physical phenomena associated with the nonlinear response and failure of composite and sandwich structures. A toolkit was developed for use in conjunction with deterministic analysis programs to help the designer in assessing the effect of uncertainties in the different computational model parameters on the variability of the response quantities.

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

    Directory of Open Access Journals (Sweden)

    Alex G. Stewart

    2018-01-01

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

  20. 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

  1. Can agent based models effectively reduce fisheries management implementation uncertainty?

    Science.gov (United States)

    Drexler, M.

    2016-02-01

    Uncertainty is an inherent feature of fisheries management. Implementation uncertainty remains a challenge to quantify often due to unintended responses of users to management interventions. This problem will continue to plague both single species and ecosystem based fisheries management advice unless the mechanisms driving these behaviors are properly understood. Equilibrium models, where each actor in the system is treated as uniform and predictable, are not well suited to forecast the unintended behaviors of individual fishers. Alternatively, agent based models (AMBs) can simulate the behaviors of each individual actor driven by differing incentives and constraints. This study evaluated the feasibility of using AMBs to capture macro scale behaviors of the US West Coast Groundfish fleet. Agent behavior was specified at the vessel level. Agents made daily fishing decisions using knowledge of their own cost structure, catch history, and the histories of catch and quota markets. By adding only a relatively small number of incentives, the model was able to reproduce highly realistic macro patterns of expected outcomes in response to management policies (catch restrictions, MPAs, ITQs) while preserving vessel heterogeneity. These simulations indicate that agent based modeling approaches hold much promise for simulating fisher behaviors and reducing implementation uncertainty. Additional processes affecting behavior, informed by surveys, are continually being added to the fisher behavior model. Further coupling of the fisher behavior model to a spatial ecosystem model will provide a fully integrated social, ecological, and economic model capable of performing management strategy evaluations to properly consider implementation uncertainty in fisheries management.

  2. Assessing 5 years of GOSAT Proxy XCH4 data and associated uncertainties

    Directory of Open Access Journals (Sweden)

    R. J. Parker

    2015-11-01

    Full Text Available We present 5 years of GOSAT XCH4 retrieved using the "proxy" approach. The Proxy XCH4 data are validated against ground-based TCCON observations and are found to be of high quality with a small bias of 4.8 ppb (∼ 0.27 % and a single-sounding precision of 13.4 ppb (∼ 0.74 %. The station-to-station bias (ameasure of the relative accuracy is found to be 4.2 ppb. For the first time the XCH4 / XCO2 ratio component of the Proxy retrieval is validated (bias of 0.014 ppb ppm−1 (∼ 0.30 %, single-sounding precision of 0.033 ppb ppm−1 (∼ 0.72 %. The uncertainty relating to the model XCO2 component of the Proxy XCH4 is assessed through the use of an ensemble of XCO2 models. While each individual XCO2 model is found to agree well with the TCCON validation data (r = 0.94–0.97, it is not possible to select one model as the best from our comparisons. The median XCO2 value of the ensemble has a smaller scatter against TCCON (a standard deviation of 0.92 ppm than any of the individual models whilst maintaining a small bias (0.15 ppm. This model median XCO2 is used to calculate the Proxy XCH4 with the maximum deviation of the ensemble from the median used as an estimate of the uncertainty. We compare this uncertainty to the a posteriori retrieval error (which is assumed to reduce with sqrt(N and find typically that the model XCO2 uncertainty becomes significant during summer months when the a posteriori error is at its lowest due to the increase in signal related to increased summertime reflected sunlight. We assess the significance of these model and retrieval uncertainties on flux inversion by comparing the GOSAT XCH4 against modelled XCH4 from TM5-4DVAR constrained by NOAA surface observations (MACC reanalysis scenario S1-NOAA. We find that for the majority of regions the differences are much larger than the estimated uncertainties. Our findings show that useful information will be provided to the inversions for the majority of regions in addition

  3. Assessing the Uncertainty of Tropical Cyclone Simulations in NCAR's Community Atmosphere Model

    Directory of Open Access Journals (Sweden)

    Kevin A Reed

    2011-08-01

    Full Text Available The paper explores the impact of the initial-data, parameter and structural model uncertainty on the simulation of a tropical cyclone-like vortex in the National Center for Atmospheric Research's (NCAR Community Atmosphere Model (CAM. An analytic technique is used to initialize the model with an idealized weak vortex that develops into a tropical cyclone over ten simulation days. A total of 78 ensemble simulations are performed at horizontal grid spacings of 1.0°, 0.5° and 0.25° using two recently released versions of the model, CAM 4 and CAM 5. The ensemble members represent simulations with random small-amplitude perturbations of the initial conditions, small shifts in the longitudinal position of the initial vortex and runs with slightly altered model parameters. The main distinction between CAM 4 and CAM 5 lies within the physical parameterization suite, and the simulations with both CAM versions at the varying resolutions assess the structural model uncertainty. At all resolutions storms are produced with many tropical cyclone-like characteristics. The CAM 5 simulations exhibit more intense storms than CAM 4 by day 10 at the 0.5° and 0.25° grid spacings, while the CAM 4 storm at 1.0° is stronger. There are also distinct differences in the shapes and vertical profiles of the storms in the two variants of CAM. The ensemble members show no distinction between the initial-data and parameter uncertainty simulations. At day 10 they produce ensemble root-mean-square deviations from an unperturbed control simulation on the order of 1--5 m s-1 for the maximum low-level wind speed and 2--10 hPa for the minimum surface pressure. However, there are large differences between the two CAM versions at identical horizontal resolutions. It suggests that the structural uncertainty is more dominant than the initial-data and parameter uncertainties in this study. The uncertainty among the ensemble members is assessed and quantified.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-05-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-05-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-04-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-06-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-05-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-04-01

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

  10. Assessing uncertainty in extreme events: Applications to risk-based decision making in interdependent infrastructure sectors

    International Nuclear Information System (INIS)

    Barker, Kash; Haimes, Yacov Y.

    2009-01-01

    Risk-based decision making often relies upon expert probability assessments, particularly in the consequences of disruptive events and when such events are extreme or catastrophic in nature. Naturally, such expert-elicited probability distributions can be fraught with errors, as they describe events which occur very infrequently and for which only sparse data exist. This paper presents a quantitative framework, the extreme event uncertainty sensitivity impact method (EE-USIM), for measuring the sensitivity of extreme event consequences to uncertainties in the parameters of the underlying probability distribution. The EE-USIM is demonstrated with the Inoperability input-output model (IIM), a model with which to evaluate the propagation of inoperability throughout an interdependent set of economic and infrastructure sectors. The EE-USIM also makes use of a two-sided power distribution function generated by expert elicitation of extreme event consequences

  11. County-Level Climate Uncertainty for Risk Assessments: Volume 15 Appendix N - Forecast Surface Runoff.

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-05-01

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

  12. County-Level Climate Uncertainty for Risk Assessments: Volume 10 Appendix I - Historical Evaporation.

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-06-01

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

  13. County-Level Climate Uncertainty for Risk Assessments: Volume 14 Appendix M - Historical Surface Runoff.

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-06-01

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

  14. County-Level Climate Uncertainty for Risk Assessments: Volume 8 Appendix G - Historical Precipitation.

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-06-01

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

  15. County-Level Climate Uncertainty for Risk Assessments: Volume 12 Appendix K - Historical Rel. Humidity.

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-06-01

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

  16. County-Level Climate Uncertainty for Risk Assessments: Volume 16 Appendix O - Historical Soil Moisture.

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-06-01

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

  17. County-Level Climate Uncertainty for Risk Assessments: Volume 22 Appendix U - Historical Sea Ice Thickness

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-06-01

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

  18. Assessing Fatigue and Ultimate Load Uncertainty in Floating Offshore Wind Turbines Due to Varying Simulation Length

    Energy Technology Data Exchange (ETDEWEB)

    Stewart, G.; Lackner, M.; Haid, L.; Matha, D.; Jonkman, J.; Robertson, A.

    2013-07-01

    With the push towards siting wind turbines farther offshore due to higher wind quality and less visibility, floating offshore wind turbines, which can be located in deep water, are becoming an economically attractive option. The International Electrotechnical Commission's (IEC) 61400-3 design standard covers fixed-bottom offshore wind turbines, but there are a number of new research questions that need to be answered to modify these standards so that they are applicable to floating wind turbines. One issue is the appropriate simulation length needed for floating turbines. This paper will discuss the results from a study assessing the impact of simulation length on the ultimate and fatigue loads of the structure, and will address uncertainties associated with changing the simulation length for the analyzed floating platform. Recommendations of required simulation length based on load uncertainty will be made and compared to current simulation length requirements.

  19. Approach to uncertainty assessment for fluid flow and contaminant transport modeling in heterogeneous groundwater systems

    International Nuclear Information System (INIS)

    Nelson, R.W.; Jacobson, E.A.; Conbere, W.

    1985-06-01

    There is a growing awareness of the need to quantify uncertainty in groundwater flow and transport model results. Regulatory organizations are beginning to request the statistical distributions of predicted contaminant arrival to the biosphere, so that realistic confidence intervals can be obtained for the modeling results. To meet these needs, methods are being developed to quantify uncertainty in the subsurface flow and transport analysis sequence. A method for evaluating this uncertainty, described in this paper, considers uncertainty in material properties and was applied to an example field problem. Our analysis begins by using field measurements of transmissivity and hydraulic head in a regional, parameter estimation method to obtain a calibrated fluid flow model and a covariance matrix of the parameter estimation errors. The calibrated model and the covariance matrix are next used in a conditional simulation mode to generate a large number of 'head realizations.' The specific pore water velocity distribution for each realization is calculated from the effective porosity, the aquifer parameter realization, and the associated head values. Each velocity distribution is used to obtain a transport solution for a contaminant originating from the same source for all realizations. The results are the statistical distributions for the outflow arrival times. The confidence intervals for contamination reaching the biosphere are obtained from the outflow statistical distributions. 20 refs., 12 figs

  20. Introduction to special section on Uncertainty Assessment in Surface and Subsurface Hydrology : An overview of issues and challenges

    NARCIS (Netherlands)

    Montanari, A.; Shoemaker, C.A.; Van de Giesen, N.C.

    This paper introduces the Water Resources Research special section on Uncertainty Assessment in Surface and Subsurface Hydrology. Over the past years, hydrological literature has seen a large increase in the number of papers dealing with uncertainty. In this article, we present an overview of the

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

    DEFF Research Database (Denmark)

    Thomsen, Nanna Isbak

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

  2. Qualification and application of nuclear reactor accident analysis code with the capability of internal assessment of uncertainty

    International Nuclear Information System (INIS)

    Borges, Ronaldo Celem

    2001-10-01

    This thesis presents an independent qualification of the CIAU code ('Code with the capability of - Internal Assessment of Uncertainty') which is part of the internal uncertainty evaluation process with a thermal hydraulic system code on a realistic basis. This is done by combining the uncertainty methodology UMAE ('Uncertainty Methodology based on Accuracy Extrapolation') with the RELAP5/Mod3.2 code. This allows associating uncertainty band estimates with the results obtained by the realistic calculation of the code, meeting licensing requirements of safety analysis. The independent qualification is supported by simulations with RELAP5/Mod3.2 related to accident condition tests of LOBI experimental facility and to an event which has occurred in Angra 1 nuclear power plant, by comparison with measured results and by establishing uncertainty bands on safety parameter calculated time trends. These bands have indeed enveloped the measured trends. Results from this independent qualification of CIAU have allowed to ascertain the adequate application of a systematic realistic code procedure to analyse accidents with uncertainties incorporated in the results, although there is an evident need of extending the uncertainty data base. It has been verified that use of the code with this internal assessment of uncertainty is feasible in the design and license stages of a NPP. (author)

  3. Assessing Uncertainties of Water Footprints Using an Ensemble of Crop Growth Models on Winter Wheat

    Directory of Open Access Journals (Sweden)

    Kurt Christian Kersebaum

    2016-12-01

    Full Text Available Crop productivity and water consumption form the basis to calculate the water footprint (WF of a specific crop. Under current climate conditions, calculated evapotranspiration is related to observed crop yields to calculate WF. The assessment of WF under future climate conditions requires the simulation of crop yields adding further uncertainty. To assess the uncertainty of model based assessments of WF, an ensemble of crop models was applied to data from five field experiments across Europe. Only limited data were provided for a rough calibration, which corresponds to a typical situation for regional assessments, where data availability is limited. Up to eight models were applied for wheat. The coefficient of variation for the simulated actual evapotranspiration between models was in the range of 13%–19%, which was higher than the inter-annual variability. Simulated yields showed a higher variability between models in the range of 17%–39%. Models responded differently to elevated CO2 in a FACE (Free-Air Carbon Dioxide Enrichment experiment, especially regarding the reduction of water consumption. The variability of calculated WF between models was in the range of 15%–49%. Yield predictions contributed more to this variance than the estimation of water consumption. Transpiration accounts on average for 51%–68% of the total actual evapotranspiration.

  4. Measurement Uncertainty

    Science.gov (United States)

    Koch, Michael

    Measurement uncertainty is one of the key issues in quality assurance. It became increasingly important for analytical chemistry laboratories with the accreditation to ISO/IEC 17025. The uncertainty of a measurement is the most important criterion for the decision whether a measurement result is fit for purpose. It also delivers help for the decision whether a specification limit is exceeded or not. Estimation of measurement uncertainty often is not trivial. Several strategies have been developed for this purpose that will shortly be described in this chapter. In addition the different possibilities to take into account the uncertainty in compliance assessment are explained.

  5. The Generic Containment SB-LOCA accident simulation: Comparison of the parameter uncertainties and user-effect

    International Nuclear Information System (INIS)

    Povilaitis, Mantas; Kelm, Stephan; Urbonavičius, Egidijus

    2017-01-01

    Highlights: • Uncertainty and sensitivity analysis for the Generic Containment severe accident. • Comparison of the analysis results with the uncertainties based in the user effect. • Demonstration of the similar importance of both the reducing the user effect and input uncertainties. - Abstract: Uncertainties in safety assessment of the nuclear power plants using computer codes come from several sources: choice of computer code, user effect (a strong impact of user choices on the simulation’s outcome) and uncertainty of various physical parameters. The “Generic Containment” activity was performed in the frames of the EU-FP7 project SARNET2 to investigate the influence of user effect and computer code choice on the results on the nuclear power plant scale. During this activity, a Generic Containment nodalisation was developed and used for exercise by the participants applying various computer codes. Even though the model of the Generic Containment and the transient scenario were precisely and uniquely defined, considerably different results were obtained not only among different codes but also among participants using the same code, showing significant influence of the user effect. This paper present analysis, which is an extension of the “Generic Containment” benchmark and investigates the effect of input parameter’s uncertainties in comparison to the user effect. Calculations were performed using the computer code ASTEC, the uncertainty and sensitivity of the results were estimated using GRS method and tool SUSA. The results of the present analysis show, that while there are differences between the uncertainty bands of the parameters, in general the deviation bands caused by parameters’ uncertainty and the user effect are comparable and of the same order. The properties of concrete and the surface areas may have more influence on containment pressure than the user effect and choice of computer code as identified in the SARNET2 Generic

  6. Assessment of Uncertainty in the Determination of Activation Energy for Polymeric Materials

    Science.gov (United States)

    Darby, Stephania P.; Landrum, D. Brian; Coleman, Hugh W.

    1998-01-01

    An assessment of the experimental uncertainty in obtaining the kinetic activation energy from thermogravimetric analysis (TGA) data is presented. A neat phenolic resin, Borden SC1O08, was heated at three heating rates to obtain weight loss vs temperature data. Activation energy was calculated by two methods: the traditional Flynn and Wall method based on the slope of log(q) versus 1/T, and a modification of this method where the ordinate and abscissa are reversed in the linear regression. The modified method produced a more accurate curve fit of the data, was more sensitive to data nonlinearity, and gave a value of activation energy 75 percent greater than the original method. An uncertainty analysis using the modified method yielded a 60 percent uncertainty in the average activation energy. Based on this result, the activation energy for a carbon-phenolic material was doubled and used to calculate the ablation rate In a typical solid rocket environment. Doubling the activation energy increased surface recession by 3 percent. Current TGA data reduction techniques that use the traditional Flynn and Wall approach to calculate activation energy should be changed to the modified method.

  7. Effects of input uncertainty on cross-scale crop modeling

    Science.gov (United States)

    Waha, Katharina; Huth, Neil; Carberry, Peter

    2014-05-01

    The quality of data on climate, soils and agricultural management in the tropics is in general low or data is scarce leading to uncertainty in process-based modeling of cropping systems. Process-based crop models are common tools for simulating crop yields and crop production in climate change impact studies, studies on mitigation and adaptation options or food security studies. Crop modelers are concerned about input data accuracy as this, together with an adequate representation of plant physiology processes and choice of model parameters, are the key factors for a reliable simulation. For example, assuming an error in measurements of air temperature, radiation and precipitation of ± 0.2°C, ± 2 % and ± 3 % respectively, Fodor & Kovacs (2005) estimate that this translates into an uncertainty of 5-7 % in yield and biomass simulations. In our study we seek to answer the following questions: (1) are there important uncertainties in the spatial variability of simulated crop yields on the grid-cell level displayed on maps, (2) are there important uncertainties in the temporal variability of simulated crop yields on the aggregated, national level displayed in time-series, and (3) how does the accuracy of different soil, climate and management information influence the simulated crop yields in two crop models designed for use at different spatial scales? The study will help to determine whether more detailed information improves the simulations and to advise model users on the uncertainty related to input data. We analyse the performance of the point-scale crop model APSIM (Keating et al., 2003) and the global scale crop model LPJmL (Bondeau et al., 2007) with different climate information (monthly and daily) and soil conditions (global soil map and African soil map) under different agricultural management (uniform and variable sowing dates) for the low-input maize-growing areas in Burkina Faso/West Africa. We test the models' response to different levels of input

  8. Procedural justice effects on self-esteem under certainty versus uncertainty emotions

    NARCIS (Netherlands)

    D. de Cremer (David); A. van Hiel (Alain)

    2008-01-01

    textabstractBuilding upon the idea that procedural justice effects are more pronounced when uncertainty is high, we proposed that recall of an uncertainty-eliciting emotion (fear) will render people more responsive to variations in procedural justice than will recall of a certainty-eliciting emotion

  9. 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

  10. Uncertainties in radioecological assessment models-Their nature and approaches to reduce them

    International Nuclear Information System (INIS)

    Kirchner, G.; Steiner, M.

    2008-01-01

    Radioecological assessment models are necessary tools for estimating the radiation exposure of humans and non-human biota. This paper focuses on factors affecting their predictive accuracy, discusses the origin and nature of the different contributions to uncertainty and variability and presents approaches to separate and quantify them. The key role of the conceptual model, notably in relation to its structure and complexity, as well as the influence of the number and type of input parameters, are highlighted. Guidelines are provided to improve the degree of reliability of radioecological models

  11. Uncertainty assessment of climate change adaptation options in urban flash floods

    DEFF Research Database (Denmark)

    Zhou, Qianqian; Arnbjerg-Nielsen, Karsten

    Adaptation is necessary to cope with the increasing flood risk in cities due to anthropogenic climate change in many regions of the world. The choice of adaptation strategies can and should be based on a comprehensive risk-based economic analysis to indicate the net benefits of proposed options...... presented is based on a flood risk framework that is in accordance with the EU flood directive, but adapted and extended to incorporate anticipated future changes due to city development and hydrologic extremes. The framework is used to study the importance of inherent uncertainties in order to find robust......-effective regardless of the uncertainties from climate change impacts and /or damage estimation procedure when considering the ability to reduce the risk of flooding. The description of the correlation structure between the key inputs proved to be important in order to obtain a correct description of the resulting...

  12. The greenhouse effect: Its causes, possible impacts, and associated uncertainties

    International Nuclear Information System (INIS)

    Schneider, S.H.; Rosenberg, N.J.

    1991-01-01

    The Earth's climate changes. The climatic effects of having polluted the atmosphere with gases such as carbon dioxide (CO2) may already be felt. There is no doubt that the concentration of CO2 in the atmosphere has been rising. CO2 tends to trap heat near the Earth's surface. This is known as the greenhouse effect, and its existence and basic mechanisms are not questioned by atmospheric scientists. What is questioned is the precise amount of warming and the regional pattern of climatic change that can be expected on the Earth from the anthropogenic increase in the atmospheric concentration of CO2 and other greenhouse gases. It is the regional patterns of changes in temperature, precipitation, and soil moisture that will determine what impact the greenhouse effect will have on natural ecosystems, agriculture, and water supplies. These possible effects are discussed in detail. It is concluded, however, that a detailed assessment of the climatic, biological, and societal changes that are evolving and should continue to occur into the next century cannot reliably be made with available scientific capabilities. Nevertheless, enough is known to suggest a range of plausible futures with attendant impacts, both positive and negative, on natural resources and human well being

  13. Regulatory risk assessments: Is there a need to reduce uncertainty and enhance robustness?

    Science.gov (United States)

    Snodin, D J

    2015-12-01

    A critical evaluation of several recent regulatory risk assessments has been undertaken. These relate to propyl paraben (as a food additive, cosmetic ingredient or pharmaceutical excipient), cobalt (in terms of a safety-based limit for pharmaceuticals) and the cancer Threshold of Toxicological Concern as applied to food contaminants and pharmaceutical impurities. In all cases, a number of concerns can be raised regarding the reliability of the current assessments, some examples being absence of data audits, use of single-dose and/or non-good laboratory practice studies to determine safety metrics, use of a biased data set and questionable methodology and lack of consistency with precedents and regulatory guidance. Drawing on these findings, a set of recommendations is provided to reduce uncertainty and improve the quality and robustness of future regulatory risk assessments. © The Author(s) 2015.

  14. On the uncertainties in effective dose estimates of adult CT head scans

    International Nuclear Information System (INIS)

    Gregory, Kent J.; Bibbo, Giovanni; Pattison, John E.

    2008-01-01

    Estimates of the effective dose to adult patients from computed tomography (CT) head scanning can be calculated using a number of different methods. These estimates can be used for a variety of purposes, such as improving scanning protocols, comparing different CT imaging centers, and weighing the benefits of the scan against the risk of radiation-induced cancer. The question arises: What is the uncertainty in these effective dose estimates? This study calculates the uncertainty of effective dose estimates produced by three computer programs (CT-EXPO, CTDosimetry, and ImpactDose) and one method that makes use of dose-length product (DLP) values. Uncertainties were calculated in accordance with an internationally recognized uncertainty analysis guide. For each of the four methods, the smallest and largest overall uncertainties (stated at the 95% confidence interval) were: 20%-31% (CT-EXPO), 15%-28% (CTDosimetry), 20%-36% (ImpactDose), and 22%-32% (DLP), respectively. The overall uncertainties for each method vary due to differences in the uncertainties of factors used in each method. The smallest uncertainties apply when the CT dose index for the scanner has been measured using a calibrated pencil ionization chamber

  15. Uncertainty and sensitivity assessments of an agricultural-hydrological model (RZWQM2) using the GLUE method

    Science.gov (United States)

    Sun, Mei; Zhang, Xiaolin; Huo, Zailin; Feng, Shaoyuan; Huang, Guanhua; Mao, Xiaomin

    2016-03-01

    Quantitatively ascertaining and analyzing the effects of model uncertainty on model reliability is a focal point for agricultural-hydrological models due to more uncertainties of inputs and processes. In this study, the generalized likelihood uncertainty estimation (GLUE) method with Latin hypercube sampling (LHS) was used to evaluate the uncertainty of the RZWQM-DSSAT (RZWQM2) model outputs responses and the sensitivity of 25 parameters related to soil properties, nutrient transport and crop genetics. To avoid the one-sided risk of model prediction caused by using a single calibration criterion, the combined likelihood (CL) function integrated information concerning water, nitrogen, and crop production was introduced in GLUE analysis for the predictions of the following four model output responses: the total amount of water content (T-SWC) and the nitrate nitrogen (T-NIT) within the 1-m soil profile, the seed yields of waxy maize (Y-Maize) and winter wheat (Y-Wheat). In the process of evaluating RZWQM2, measurements and meteorological data were obtained from a field experiment that involved a winter wheat and waxy maize crop rotation system conducted from 2003 to 2004 in southern Beijing. The calibration and validation results indicated that RZWQM2 model can be used to simulate the crop growth and water-nitrogen migration and transformation in wheat-maize crop rotation planting system. The results of uncertainty analysis using of GLUE method showed T-NIT was sensitive to parameters relative to nitrification coefficient, maize growth characteristics on seedling period, wheat vernalization period, and wheat photoperiod. Parameters on soil saturated hydraulic conductivity, nitrogen nitrification and denitrification, and urea hydrolysis played an important role in crop yield component. The prediction errors for RZWQM2 outputs with CL function were relatively lower and uniform compared with other likelihood functions composed of individual calibration criterion. This

  16. Input Uncertainty and its Implications on Parameter Assessment in Hydrologic and Hydroclimatic Modelling Studies

    Science.gov (United States)

    Chowdhury, S.; Sharma, A.

    2005-12-01

    present. SIMEX is based on theory that the trend in alternate parameters can be extrapolated back to the notional error free zone. We illustrate the utility of SIMEX in a synthetic rainfall-runoff modelling scenario and an application to study the dependence of uncertain distributed sea surface temperature anomalies with an indicator of the El Nino Southern Oscillation, the Southern Oscillation Index (SOI). The errors in rainfall data and its affect is explored using Sacramento rainfall runoff model. The rainfall uncertainty is assumed to be multiplicative and temporally invariant. The model used to relate the sea surface temperature anomalies (SSTA) to the SOI is assumed to be of a linear form. The nature of uncertainty in the SSTA is additive and varies with time. The SIMEX framework allows assessment of the relationship between the error free inputs and response. Cook, J.R., Stefanski, L. A., Simulation-Extrapolation Estimation in Parametric Measurement Error Models, Journal of the American Statistical Association, 89 (428), 1314-1328, 1994.

  17. Assessment of uncertainties of external dose estimation after the Chernobyl accident

    International Nuclear Information System (INIS)

    Kruk, Julianna

    2008-01-01

    Full text: In the remote period of time after the Chernobyl accident the estimation of an external exposure with using of direct dose rate measurements or individual monitoring of inhabitants is rationally only for settlements where the preliminary estimation makes the range equal or greater 1.0 mSv per year. For inhabitancies of settlements where the preliminary estimation makes the range less 1.0 mSv per year the external dose is correctly to estimate by calculation. For the last cases the uncertainty should be assessed. The most accessible initial parameter for calculation of a dose of an external exposure is the average ground deposition of Cs-137 for the settlements. The character of density distribution of Cs-137 deposition in an area of one settlement is well enough studied. The best agreement of distribution of this parameter is reached with log-normal distribution practically for all settlements of the investigated territories with factor of a variation 0.3-0.6 and the standard geometrical deviation lying within the limits of 1.4-1.7. The dose factors which correspond to the structure of an available housing of settlement (type of apartment houses: wooden, stone, multi-storey) and age structure of the population are bring the main contribution into uncertainty of the external dose estimation. The situations with a different level of known information have been considered for the estimation of influence of those parameters on the general uncertainty. Thus the estimation of the uncertainty of the external dose was done for two variant: optimistic and pessimistic. In the optimistic case the estimation of external doses will be spent for specific settlement with known structure of housing and according to a known share of the living population in houses of the certain type. In that case, variability value dose factor will be limited to the chosen type of a residential building (for example - the one-storied wooden house), and a share of the living population

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

    Directory of Open Access Journals (Sweden)

    Kelly C. Chang

    2017-11-01

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

  19. Uncertainty on shallow landslide hazard assessment: from field data to hazard mapping

    Science.gov (United States)

    Trefolini, Emanuele; Tolo, Silvia; Patelli, Eduardo; Broggi, Matteo; Disperati, Leonardo; Le Tuan, Hai

    2015-04-01

    Shallow landsliding that involve Hillslope Deposits (HD), the surficial soil that cover the bedrock, is an important process of erosion, transport and deposition of sediment along hillslopes. Despite Shallow landslides generally mobilize relatively small volume of material, they represent the most hazardous factor in mountain regions due to their high velocity and the common absence of warning signs. Moreover, increasing urbanization and likely climate change make shallow landslides a source of widespread risk, therefore the interest of scientific community about this process grown in the last three decades. One of the main aims of research projects involved on this topic, is to perform robust shallow landslides hazard assessment for wide areas (regional assessment), in order to support sustainable spatial planning. Currently, three main methodologies may be implemented to assess regional shallow landslides hazard: expert evaluation, probabilistic (or data mining) methods and physical models based methods. The aim of this work is evaluate the uncertainty of shallow landslides hazard assessment based on physical models taking into account spatial variables such as: geotechnical and hydrogeologic parameters as well as hillslope morphometry. To achieve this goal a wide dataset of geotechnical properties (shear strength, permeability, depth and unit weight) of HD was gathered by integrating field survey, in situ and laboratory tests. This spatial database was collected from a study area of about 350 km2 including different bedrock lithotypes and geomorphological features. The uncertainty associated to each step of the hazard assessment process (e.g. field data collection, regionalization of site specific information and numerical modelling of hillslope stability) was carefully characterized. The most appropriate probability density function (PDF) was chosen for each numerical variable and we assessed the uncertainty propagation on HD strength parameters obtained by

  20. Effects of uncertainty, transmission type, driver age and gender on brake reaction and movement time.

    Science.gov (United States)

    Warshawsky-Livne, Lora; Shinar, David

    2002-01-01

    Braking time (BT) is a critical component in safe driving, and various approaches have been applied to minimize it. This study analyzed the components of BT in order to assess the effects of age, gender, vehicle transmission type, and event uncertainty, on its two primary components, perception-reaction time and brake-movement time. Perception-reaction time and brake-movement time were measured at the onset of lights for 72 subjects in a simulator. The six experimental conditions were three levels of uncertainty conditions (none, some, and some + false alarms) and two types of transmission (manual and automatic). The 72 subjects, half male and half female, were further divided into three age groups (mean of 23, 30, and 62 years). Each subject had 10 trials in each of the three levels of uncertainty conditions. Transmission type did not significantly affect either perception-reaction time or brake-movement time. Perception-reaction time increased significantly from 0.32 to 0.42 s (P brake-movement time did not change. Perception-reaction time increased (from 0.35 to 0.43 s) with age but brake-movement time did not change with age. Gender did not affect perception-reaction time but did affect brake-movement time (males 0.19 s vs. females 0.16 s). At 90 km/h, a car travels 0.25 m in 0.01 s. Consequently, even such small effects multiplied by millions of vehicle-kilometers can contribute to significant savings in lives and damages.

  1. Uncertainty in wave energy resource assessment. Part 2: Variability and predictability

    International Nuclear Information System (INIS)

    Mackay, Edward B.L.; Bahaj, AbuBakr S.; Challenor, Peter G.

    2010-01-01

    The uncertainty in estimates of the energy yield from a wave energy converter (WEC) is considered. The study is presented in two articles. The first article considered the accuracy of the historic data and the second article, presented here, considers the uncertainty which arises from variability in the wave climate. Mean wave conditions exhibit high levels of interannual variability. Moreover, many previous studies have demonstrated longer-term decadal changes in wave climate. The effect of interannual and climatic changes in wave climate on the predictability of long-term mean WEC power is examined for an area off the north coast of Scotland. In this location anomalies in mean WEC power are strongly correlated with the North Atlantic Oscillation (NAO) index. This link enables the results of many previous studies on the variability of the NAO and its sensitivity to climate change to be applied to WEC power levels. It is shown that the variability in 5, 10 and 20 year mean power levels is greater than if annual power anomalies were uncorrelated noise. It is also shown that the change in wave climate from anthropogenic climate change over the life time of a wave farm is likely to be small in comparison to the natural level of variability. Finally, it is shown that despite the uncertainty related to variability in the wave climate, improvements in the accuracy of historic data will improve the accuracy of predictions of future WEC yield. (author)

  2. Energy assessment of peri-urban horticulture and its uncertainty: Case study for Bogota, Colombia

    Energy Technology Data Exchange (ETDEWEB)

    Bojaca, C.R. [Centro de Investigaciones y Asesorias Agroindustriales, Facultad de Ciencias Naturales, Universidad de Bogota Jorge Tadeo Lozano, P.O. Box: 140196, Chia (Colombia); Schrevens, E. [Department of Biosystems, Faculty of Applied Bioscience Engineering, Katholieke Universiteit Leuven, Geo-Institute, Celestijnenlaan 200 E, 3001 Heverlee (Belgium)

    2010-05-15

    Scarce information is available about the energy use pattern of horticultural commodities in general and more specifically for peri-urban horticulture. Peri-urban horticulture in the outskirts of Bogota is an important source of vegetables for Colombia's capital city. Based on detailed follow-ups and periodic field measurements an output-input energy balance was performed with the main objective to study the energy use efficiency of those systems. An uncertainty analysis on the input factors and on the energy equivalents was then applied. Over a measurement period of 18-month, the energy use for coriander, lettuce, radish and spinach was investigated, respectively 12.1, 18.8, 6.6 and 10.7 GJ ha{sup -1} were consumed in these cropping systems. Negative balances were observed for all species exception made for spinach where an output:input ratio of 1.16 was found. The two-way uncertainty analysis showed the highest uncertainty for N-based fertilization while no significant effect was observed for seeds in direct sowing crops. Sustainability of peri-urban horticulture around Bogota is compromised not only because of the city expansion but also due to its inefficient energy use. Technical improvements are required to ensure the environmental subsistence of this important sector for the metropolitan area of the city. (author)

  3. Severe Accident Research Network (SARNET). Level 2 PSA work package: comparison of partners methods for uncertainties assessment

    International Nuclear Information System (INIS)

    Chaumont, B.; Haesendonck, M.; Vidal, S.; Eyink, J.; Loeffler, H.; Radu, G.; Kopustinskas, V.; Ming, A.; Guntay, S.; Gustavsson, V.; Ivanov, I.; Dienstbier, J.; Bareith, A.; Hollo, E.; Lajtha, G.

    2007-01-01

    The PSA2 work package (PSA2 WP) is a part of the Joined Programme Activity of the European Severe Accident Network (SARNET) related to level 2 PSA methodologies. The general objectives of this work package is to provide a comparison of the different methodologies used or under development for level 2 PSA application by the partners involved in the work package and to promote their harmonization. The PSA2 WP is organized into three main topics: methodologies in general, methodologies for uncertainties assessment, and dynamic reliability methods. The different tasks initially defined for these three topics are shortly described and the partners involved identified. Attention is then paid on the methodologies used so far by the different partners to assess the uncertainties in their level 2 PSA. A review of partners approaches to assess - as far as possible - the different sources of possible uncertainties is done for the different following topics: - uncertainties propagated from the level 1 PSA, - uncertainties (in sense of approximation) due to the binning of the level 1 sequences in Plant Damage, - uncertainties related to the structure of the Accident Progression Event Tree, - uncertainties related to the probabilities of stochastic events (system failure or recovery, human actions, some physical phenomena such as ignition of hydrogen combustion or triggering of steam explosion), - uncertainties elated to the modelling of the different physical phenomena, - uncertainties related to the cut-off frequency used in the probabilistic quantification of the Accident Progression Event Tree; - uncertainties related to the binning of level 2 sequences in Release Categories (variables not considered, values of eventual continuous variables). First conclusions of the comparison are given in terms of improvement needs and then of perspectives of the work for the following period of work. (authors)

  4. Multi-model ensembles for assessment of flood losses and associated uncertainty

    Science.gov (United States)

    Figueiredo, Rui; Schröter, Kai; Weiss-Motz, Alexander; Martina, Mario L. V.; Kreibich, Heidi

    2018-05-01

    Flood loss modelling is a crucial part of risk assessments. However, it is subject to large uncertainty that is often neglected. Most models available in the literature are deterministic, providing only single point estimates of flood loss, and large disparities tend to exist among them. Adopting any one such model in a risk assessment context is likely to lead to inaccurate loss estimates and sub-optimal decision-making. In this paper, we propose the use of multi-model ensembles to address these issues. This approach, which has been applied successfully in other scientific fields, is based on the combination of different model outputs with the aim of improving the skill and usefulness of predictions. We first propose a model rating framework to support ensemble construction, based on a probability tree of model properties, which establishes relative degrees of belief between candidate models. Using 20 flood loss models in two test cases, we then construct numerous multi-model ensembles, based both on the rating framework and on a stochastic method, differing in terms of participating members, ensemble size and model weights. We evaluate the performance of ensemble means, as well as their probabilistic skill and reliability. Our results demonstrate that well-designed multi-model ensembles represent a pragmatic approach to consistently obtain more accurate flood loss estimates and reliable probability distributions of model uncertainty.

  5. The treatment of climate-driven environmental change and associated uncertainty in post-closure assessments

    International Nuclear Information System (INIS)

    Wilmot, R.D.

    1993-01-01

    The post-closure performance of radioactive waste repositories is influenced by a range of processes such as groundwater flow and fracture movement which are in turn affected by conditions in the surface environment. For deep repositories the period for which an assessment must be performed is in the order of 10 6 years. The geological record of the last 10 6 years shows that surface environmental conditions have varied considerably over such time-scales. A model of surface environmental change, known as TIME4, has been developed on behalf of the UK Department of the Environment for use with the probabilistic risk assessment code VANDAL. This paper describes the extent of surface environmental change, discusses possible driving mechanisms for such changes and summarises the processes which have been incorporated within the TIME4 model. The underlying cause of change in surface environment sub-systems is inferred to be climate change but considerable uncertainty remains over the mechanisms of such change. Methods for treating these uncertainties are described. (author)

  6. Intelligent Aircraft Damage Assessment, Trajectory Planning, and Decision-Making under Uncertainty

    Science.gov (United States)

    Lopez, Israel; Sarigul-Klijn, Nesrin

    Situational awareness and learning are necessary to identify and select the optimal set of mutually non-exclusive hypothesis in order to maximize mission performance and adapt system behavior accordingly. This paper presents a hierarchical and decentralized approach for integrated damage assessment and trajectory planning in aircraft with uncertain navigational decision-making. Aircraft navigation can be safely accomplished by properly addressing the following: decision-making, obstacle perception, aircraft state estimation, and aircraft control. When in-flight failures or damage occur, rapid and precise decision-making under imprecise information is required in order to regain and maintain control of the aircraft. To achieve planned aircraft trajectory and complete safe landing, the uncertainties in system dynamics of the damaged aircraft need to be learned and incorporated at the level of motion planning. The damaged aircraft is simulated via a simplified kinematic model. The different sources and perspectives of uncertainties in the damage assessment process and post-failure trajectory planning are presented and classified. The decision-making process for an emergency motion planning and landing is developed via the Dempster-Shafer evidence theory. The objective of the trajectory planning is to arrive at a target position while maximizing the safety of the aircraft given uncertain conditions. Simulations are presented for an emergency motion planning and landing that takes into account aircraft dynamics, path complexity, distance to landing site, runway characteristics, and subjective human decision.

  7. Changes of heart: the switch-value method for assessing value uncertainty.

    Science.gov (United States)

    John, Leslie K; Fischhoff, Baruch

    2010-01-01

    Medical choices often evoke great value uncertainty, as patients face difficult, unfamiliar tradeoffs. Those seeking to aid such choices must be able to assess patients' ability to reduce that uncertainty, to reach stable, informed choices. The authors demonstrate a new method for evaluating how well people have articulated their preferences for difficult health decisions. The method uses 2 evaluative criteria. One is internal consistency, across formally equivalent ways of posing a choice. The 2nd is compliance with principles of prospect theory, indicating sufficient task mastery to respond in predictable ways. Subjects considered a hypothetical choice between noncurative surgery and palliative care, posed by a brain tumor. The choice options were characterized on 6 outcomes (e.g., pain, life expectancy, treatment risk), using a drug facts box display. After making an initial choice, subjects indicated their willingness to switch, given plausible changes in the outcomes. These changes involved either gains (improvements) in the unchosen option or losses (worsening) in the chosen one. A 2 x 2 mixed design manipulated focal change (gains v. losses) within subjects and change order between subjects. In this demonstration, subjects' preferences were generally consistent 1) with one another: with similar percentages willing to switch for gains and losses, and 2) with prospect theory, requiring larger gains than losses, to make those switches. Informed consent requires understanding decisions well enough to articulate coherent references. The authors' method allows assessing individuals' success in doing so.

  8. Enquiring into the roots of bioenergy - epistemic uncertainties in life cycle assessments

    DEFF Research Database (Denmark)

    Saez de Bikuna Salinas, Koldo

    global warming impacts than the respective fossil fuels they replace unless planted on abandoned lands. With Papers I-II, the selection of the land-use references and time horizons involved in LCA of biofuels was demonstrated to be crucial for the characterization of the resulting environmental impacts......The research for this Thesis was originally framed around the “sustainability assessment of full chain bioenergy”. However, it is known for some years that the critical impacts of dedicated bioenergy relate to induced land use changes (LUC). Their criticality derives from their potential...... to dominate environmental impacts from a life-cycle perspective and from the uncertainty that accompanies them. On the other hand, continued land use may be a concern for soil’s long-term sustainability (understood as fertility), which has recently received attention in environmental life-cycle assessments...

  9. Uncertainty assessment of PM2.5 contamination mapping using spatiotemporal sequential indicator simulations and multi-temporal monitoring data

    Science.gov (United States)

    Yang, Yong; Christakos, George; Huang, Wei; Lin, Chengda; Fu, Peihong; Mei, Yang

    2016-04-01

    Because of the rapid economic growth in China, many regions are subjected to severe particulate matter pollution. Thus, improving the methods of determining the spatiotemporal distribution and uncertainty of air pollution can provide considerable benefits when developing risk assessments and environmental policies. The uncertainty assessment methods currently in use include the sequential indicator simulation (SIS) and indicator kriging techniques. However, these methods cannot be employed to assess multi-temporal data. In this work, a spatiotemporal sequential indicator simulation (STSIS) based on a non-separable spatiotemporal semivariogram model was used to assimilate multi-temporal data in the mapping and uncertainty assessment of PM2.5 distributions in a contaminated atmosphere. PM2.5 concentrations recorded throughout 2014 in Shandong Province, China were used as the experimental dataset. Based on the number of STSIS procedures, we assessed various types of mapping uncertainties, including single-location uncertainties over one day and multiple days and multi-location uncertainties over one day and multiple days. A comparison of the STSIS technique with the SIS technique indicate that a better performance was obtained with the STSIS method.

  10. Selected examples of practical approaches for the assessment of model reliability - parameter uncertainty analysis

    International Nuclear Information System (INIS)

    Hofer, E.; Hoffman, F.O.

    1987-02-01

    The uncertainty analysis of model predictions has to discriminate between two fundamentally different types of uncertainty. The presence of stochastic variability (Type 1 uncertainty) necessitates the use of a probabilistic model instead of the much simpler deterministic one. Lack of knowledge (Type 2 uncertainty), however, applies to deterministic as well as to probabilistic model predictions and often dominates over uncertainties of Type 1. The term ''probability'' is interpreted differently in the probabilistic analysis of either type of uncertainty. After these discriminations have been explained the discussion centers on the propagation of parameter uncertainties through the model, the derivation of quantitative uncertainty statements for model predictions and the presentation and interpretation of the results of a Type 2 uncertainty analysis. Various alternative approaches are compared for a very simple deterministic model

  11. Effects of input data information content on the uncertainty of simulating water resources

    Science.gov (United States)

    Camargos, Carla; Julich, Stefan; Bach, Martin; Breuer, Lutz

    2017-04-01

    Hydrological models like the Soil and Water Assessment Tool (SWAT) demand a large variety of spatial input data. These are commonly available in different resolutions and result from different preprocessing methodologies. Effort is made to apply the most specific data as possible for the study area, which features heterogeneous landscape elements. Most often, modelers prefer to use regional data, especially with fine resolution, which is not always available. Instead, global datasets are considered that are more general. This study investigates how the use of global and regional input datasets may affect the simulation performance and uncertainty of the model. We analyzed eight different setups for the SWAT model, combining two of each Digital Elevation Models (DEM), soil and land use maps of diverse spatial resolution and information content. The models were calibrated to discharge at two stations across the mesoscale Haute-Sûre catchment, which is partly located in the north of Luxembourg and partly in the southeast of Belgium. The region is a rural area of about 743 km2 and mainly covered by forests and complex agricultural system and arable lands. As part of the catchment, the Upper-Sûre Lake is an important source of drinking water for Luxembourgish population, satisfying 30% of the country's demand. The Metropolis Markov Chain Monte Carlo algorithm implemented in the SPOTPY python package was used to infer posterior parameter distributions and assess parameter uncertainty. We are optimizing the mean of the Nash-Sutcliffe Efficiency (NSE) and the logarithm of NSE. We focused on soil physical, groundwater, main channel, land cover management and basin physical process parameters. Preliminary results indicate that the model has the best performance when using the regional DEM and land use map and the global soil map, indicating that SWAT cannot necessarily make use of additional soil information if they are not substantially effecting soil hydrological fluxes

  12. Advanced probabilistic methods for quantifying the effects of various uncertainties in structural response

    Science.gov (United States)

    Nagpal, Vinod K.

    1988-01-01

    The effects of actual variations, also called uncertainties, in geometry and material properties on the structural response of a space shuttle main engine turbopump blade are evaluated. A normal distribution was assumed to represent the uncertainties statistically. Uncertainties were assumed to be totally random, partially correlated, and fully correlated. The magnitude of these uncertainties were represented in terms of mean and variance. Blade responses, recorded in terms of displacements, natural frequencies, and maximum stress, was evaluated and plotted in the form of probabilistic distributions under combined uncertainties. These distributions provide an estimate of the range of magnitudes of the response and probability of occurrence of a given response. Most importantly, these distributions provide the information needed to estimate quantitatively the risk in a structural design.

  13. Reducing Multisensor Satellite Monthly Mean Aerosol Optical Depth Uncertainty: 1. Objective Assessment of Current AERONET Locations

    Science.gov (United States)

    Li, Jing; Li, Xichen; Carlson, Barbara E.; Kahn, Ralph A.; Lacis, Andrew A.; Dubovik, Oleg; Nakajima, Teruyuki

    2016-01-01

    Various space-based sensors have been designed and corresponding algorithms developed to retrieve aerosol optical depth (AOD), the very basic aerosol optical property, yet considerable disagreement still exists across these different satellite data sets. Surface-based observations aim to provide ground truth for validating satellite data; hence, their deployment locations should preferably contain as much spatial information as possible, i.e., high spatial representativeness. Using a novel Ensemble Kalman Filter (EnKF)- based approach, we objectively evaluate the spatial representativeness of current Aerosol Robotic Network (AERONET) sites. Multisensor monthly mean AOD data sets from Moderate Resolution Imaging Spectroradiometer, Multiangle Imaging Spectroradiometer, Sea-viewing Wide Field-of-view Sensor, Ozone Monitoring Instrument, and Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar are combined into a 605-member ensemble, and AERONET data are considered as the observations to be assimilated into this ensemble using the EnKF. The assessment is made by comparing the analysis error variance (that has been constrained by ground-based measurements), with the background error variance (based on satellite data alone). Results show that the total uncertainty is reduced by approximately 27% on average and could reach above 50% over certain places. The uncertainty reduction pattern also has distinct seasonal patterns, corresponding to the spatial distribution of seasonally varying aerosol types, such as dust in the spring for Northern Hemisphere and biomass burning in the fall for Southern Hemisphere. Dust and biomass burning sites have the highest spatial representativeness, rural and oceanic sites can also represent moderate spatial information, whereas the representativeness of urban sites is relatively localized. A spatial score ranging from 1 to 3 is assigned to each AERONET site based on the uncertainty

  14. Assessment of uncertainties associated with characterization of geological environment in the Tono area. Japanese fiscal year, 2006 (Contract research)

    International Nuclear Information System (INIS)

    Toida, Masaru; Suyama, Yasuhiro; Seno, Shoji; Atsumi, Hiroyuki; Ogata, Nobuhisa

    2008-03-01

    'Geoscientific research' performed at the Tono Geoscience Center is developing site investigation, characterization and assessment techniques for understanding of geological environment. Their important themes are to establish a methodology for analyzing uncertainties in heterogeneous geological environment, and to develop investigation techniques for reducing the uncertainties efficiently. This study proposes a new approach where all the possible options in the models and data-sets that cannot be excluded in the light of the evidence available, are identified. This approach enables uncertainties associated with the understanding at a given stage of the site characterization to be made explicitly using an uncertainty analysis technique based on Fuzzy geostatistics. This, in turn, supports the design of the following investigation stage to reduce the uncertainties efficiently. In the study, current knowledge had been compiled, and the technique had been advanced through geological modeling and groundwater analyses in the Tono area. This report systematized the uncertainty analysis methodology associated with the characterization of the geological environment, and organized the procedure of the methodology with the application examples in the study. This report also dealt with investigation techniques for reducing the uncertainties efficiently, and underground facility design options for handling geological uncertainties based on the characterization of the geological environment. (author)

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

    International Nuclear Information System (INIS)

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

    2017-01-01

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

  16. Leverage effect, economic policy uncertainty and realized volatility with regime switching

    Science.gov (United States)

    Duan, Yinying; Chen, Wang; Zeng, Qing; Liu, Zhicao

    2018-03-01

    In this study, we first investigate the impacts of leverage effect and economic policy uncertainty (EPU) on future volatility in the framework of regime switching. Out-of-sample results show that the HAR-RV including the leverage effect and economic policy uncertainty with regimes can achieve higher forecast accuracy than RV-type and GARCH-class models. Our robustness results further imply that these factors in the framework of regime switching can substantially improve the HAR-RV's forecast performance.

  17. Facts and feelings: Framing effects in responses to uncertainties about high-voltage power lines

    OpenAIRE

    de Vries, G.; de Bruijn, J.A.

    2017-01-01

    To ensure power supply security, electricity transmission system operators (TSOs) have to upscale high-voltage overhead power lines. However, upscaling frequently meets opposition. Opposition can be caused by uncertainties about risks and benefits and might lead to costly delays (Linder, 1995; Wiedemann, Boerner,& Claus, 2016). To minimize opposition, TSOs and related public services need to respond to these uncertainties in a credible and convincing (effective) way. Effective risk commun...

  18. [Application of robustness test for assessment of the measurement uncertainty at the end of development phase of a chromatographic method for quantification of water-soluble vitamins].

    Science.gov (United States)

    Ihssane, B; Bouchafra, H; El Karbane, M; Azougagh, M; Saffaj, T

    2016-05-01

    We propose in this work an efficient way to evaluate the measurement of uncertainty at the end of the development step of an analytical method, since this assessment provides an indication of the performance of the optimization process. The estimation of the uncertainty is done through a robustness test by applying a Placquett-Burman design, investigating six parameters influencing the simultaneous chromatographic assay of five water-soluble vitamins. The estimated effects of the variation of each parameter are translated into standard uncertainty value at each concentration level. The values obtained of the relative uncertainty do not exceed the acceptance limit of 5%, showing that the procedure development was well done. In addition, a statistical comparison conducted to compare standard uncertainty after the development stage and those of the validation step indicates that the estimated uncertainty are equivalent. The results obtained show clearly the performance and capacity of the chromatographic method to simultaneously assay the five vitamins and suitability for use in routine application. Copyright © 2015 Académie Nationale de Pharmacie. Published by Elsevier Masson SAS. All rights reserved.

  19. Consideration of vertical uncertainty in elevation-based sea-level rise assessments: Mobile Bay, Alabama case study

    Science.gov (United States)

    Gesch, Dean B.

    2013-01-01

    The accuracy with which coastal topography has been mapped directly affects the reliability and usefulness of elevationbased sea-level rise vulnerability assessments. Recent research has shown that the qualities of the elevation data must be well understood to properly model potential impacts. The cumulative vertical uncertainty has contributions from elevation data error, water level data uncertainties, and vertical datum and transformation uncertainties. The concepts of minimum sealevel rise increment and minimum planning timeline, important parameters for an elevation-based sea-level rise assessment, are used in recognition of the inherent vertical uncertainty of the underlying data. These concepts were applied to conduct a sea-level rise vulnerability assessment of the Mobile Bay, Alabama, region based on high-quality lidar-derived elevation data. The results that detail the area and associated resources (land cover, population, and infrastructure) vulnerable to a 1.18-m sea-level rise by the year 2100 are reported as a range of values (at the 95% confidence level) to account for the vertical uncertainty in the base data. Examination of the tabulated statistics about land cover, population, and infrastructure in the minimum and maximum vulnerable areas shows that these resources are not uniformly distributed throughout the overall vulnerable zone. The methods demonstrated in the Mobile Bay analysis provide an example of how to consider and properly account for vertical uncertainty in elevation-based sea-level rise vulnerability assessments, and the advantages of doing so.

  20. Flexible investment under uncertainty in smart distribution networks with demand side response: Assessment framework and practical implementation

    International Nuclear Information System (INIS)

    Schachter, Jonathan A.; Mancarella, Pierluigi; Moriarty, John; Shaw, Rita

    2016-01-01

    Classical deterministic models applied to investment valuation in distribution networks may not be adequate for a range of real-world decision-making scenarios as they effectively ignore the uncertainty found in the most important variables driving network planning (e.g., load growth). As greater uncertainty is expected from growing distributed energy resources in distribution networks, there is an increasing risk of investing in too much or too little network capacity and hence causing the stranding and inefficient use of network assets; these costs are then passed on to the end-user. An alternative emerging solution in the context of smart grid development is to release untapped network capacity through Demand-Side Response (DSR). However, to date there is no approach able to quantify the value of ‘smart’ DSR solutions against ‘conventional’ asset-heavy investments. On these premises, this paper presents a general real options framework and a novel probabilistic tool for the economic assessment of DSR for smart distribution network planning under uncertainty, which allows the modeling and comparison of multiple investment strategies, including DSR and capacity reinforcements, based on different cost and risk metrics. In particular the model provides an explicit quantification of the economic value of DSR against alternative investment strategies. Through sensitivity analysis it is able to indicate the maximum price payable for DSR service such that DSR remains economically optimal against these alternatives. The proposed model thus provides Regulators with clear insights for overseeing DSR contractual arrangements. Further it highlights that differences exist in the economic perspective of the regulated DNO business and of customers. Our proposed model is therefore capable of highlighting instances where a particular investment strategy is favorable to the DNO but not to its customers, or vice-versa, and thus aspects of the regulatory framework which may

  1. Health technology assessment and primary data collection for reducing uncertainty in decision making.

    Science.gov (United States)

    Goeree, Ron; Levin, Les; Chandra, Kiran; Bowen, James M; Blackhouse, Gord; Tarride, Jean-Eric; Burke, Natasha; Bischof, Matthias; Xie, Feng; O'Reilly, Daria

    2009-05-01

    Health care expenditures continue to escalate, and pressures for increased spending will continue. Health care decision makers from publicly financed systems, private insurance companies, or even from individual health care institutions, will continue to be faced with making difficult purchasing, access, and reimbursement decisions. As a result, decision makers are increasingly turning to evidence-based platforms to help control costs and make the most efficient use of existing resources. Most tools used to assist with evidence-based decision making focus on clinical outcomes. Health technology assessment (HTA) is increasing in popularity because it also considers other factors important for decision making, such as cost, social and ethical values, legal issues, and factors such as the feasibility of implementation. In some jurisdictions, HTAs have also been supplemented with primary data collection to help address uncertainty that may still exist after conducting a traditional HTA. The HTA process adopted in Ontario, Canada, is unique in that assessments are also made to determine what primary data research should be conducted and what should be collected in these studies. In this article, concerns with the traditional HTA process are discussed, followed by a description of the HTA process that has been established in Ontario, with a particular focus on the data collection program followed by the Programs for Assessment of Technology in Health Research Institute. An illustrative example is used to show how the Ontario HTA process works and the role value of information analyses plays in addressing decision uncertainty, determining research feasibility, and determining study data collection needs.

  2. Application of probability distributions for quantifying uncertainty in radionuclide source terms for Seabrook risk assessment

    International Nuclear Information System (INIS)

    Walker, D.H.; Savin, N.L.

    1985-01-01

    The calculational models developed for the Reactor Safety Study (RSS) have traditionally been used to generate 'point estimate values' for radionuclide release to the environment for nuclear power plant risk assessments. The point estimate values so calculated are acknowledged by most knowledgeable individuals to be conservatively high. Further, recent evaluations of the overall uncertainties in the various components that make up risk estimates for nuclear electric generating stations show that one of the large uncertainties is associated with the magnitude of the radionuclide release to the environment. In the approach developed for the RSS, values for fission product release from the fuel are derived from data obtained from small experiments. A reappraisal of the RSS release fractions was published in 1981 in NUREG-0772. Estimates of fractional releases from fuel are similar to those of the RSS. In the RSS approach, depletion during transport from the core (where the fission products are released) to the containment is assumed to be zero for calculation purposes. In the containment, the CORRAL code is applied to calculate radioactivity depletion by containment processes and to calculate the quantity and timing of release to the environment

  3. Generalized uncertainty principle as a consequence of the effective field theory

    Energy Technology Data Exchange (ETDEWEB)

    Faizal, Mir, E-mail: mirfaizalmir@gmail.com [Irving K. Barber School of Arts and Sciences, University of British Columbia – Okanagan, Kelowna, British Columbia V1V 1V7 (Canada); Department of Physics and Astronomy, University of Lethbridge, Lethbridge, Alberta T1K 3M4 (Canada); Ali, Ahmed Farag, E-mail: ahmed.ali@fsc.bu.edu.eg [Department of Physics, Faculty of Science, Benha University, Benha, 13518 (Egypt); Netherlands Institute for Advanced Study, Korte Spinhuissteeg 3, 1012 CG Amsterdam (Netherlands); Nassar, Ali, E-mail: anassar@zewailcity.edu.eg [Department of Physics, Zewail City of Science and Technology, 12588, Giza (Egypt)

    2017-02-10

    We will demonstrate that the generalized uncertainty principle exists because of the derivative expansion in the effective field theories. This is because in the framework of the effective field theories, the minimum measurable length scale has to be integrated away to obtain the low energy effective action. We will analyze the deformation of a massive free scalar field theory by the generalized uncertainty principle, and demonstrate that the minimum measurable length scale corresponds to a second more massive scale in the theory, which has been integrated away. We will also analyze CFT operators dual to this deformed scalar field theory, and observe that scaling of the new CFT operators indicates that they are dual to this more massive scale in the theory. We will use holographic renormalization to explicitly calculate the renormalized boundary action with counter terms for this scalar field theory deformed by generalized uncertainty principle, and show that the generalized uncertainty principle contributes to the matter conformal anomaly.

  4. Generalized uncertainty principle as a consequence of the effective field theory

    Directory of Open Access Journals (Sweden)

    Mir Faizal

    2017-02-01

    Full Text Available We will demonstrate that the generalized uncertainty principle exists because of the derivative expansion in the effective field theories. This is because in the framework of the effective field theories, the minimum measurable length scale has to be integrated away to obtain the low energy effective action. We will analyze the deformation of a massive free scalar field theory by the generalized uncertainty principle, and demonstrate that the minimum measurable length scale corresponds to a second more massive scale in the theory, which has been integrated away. We will also analyze CFT operators dual to this deformed scalar field theory, and observe that scaling of the new CFT operators indicates that they are dual to this more massive scale in the theory. We will use holographic renormalization to explicitly calculate the renormalized boundary action with counter terms for this scalar field theory deformed by generalized uncertainty principle, and show that the generalized uncertainty principle contributes to the matter conformal anomaly.

  5. Oil price uncertainty in Canada

    Energy Technology Data Exchange (ETDEWEB)

    Elder, John [Department of Finance and Real Estate, 1272 Campus Delivery, Colorado State University, Fort Collins, CO 80523 (United States); Serletis, Apostolos [Department of Economics, University of Calgary, Calgary, Alberta (Canada)

    2009-11-15

    Bernanke [Bernanke, Ben S. Irreversibility, uncertainty, and cyclical investment. Quarterly Journal of Economics 98 (1983), 85-106.] shows how uncertainty about energy prices may induce optimizing firms to postpone investment decisions, thereby leading to a decline in aggregate output. Elder and Serletis [Elder, John and Serletis, Apostolos. Oil price uncertainty.] find empirical evidence that uncertainty about oil prices has tended to depress investment in the United States. In this paper we assess the robustness of these results by investigating the effects of oil price uncertainty in Canada. Our results are remarkably similar to existing results for the United States, providing additional evidence that uncertainty about oil prices may provide another explanation for why the sharp oil price declines of 1985 failed to produce rapid output growth. Impulse-response analysis suggests that uncertainty about oil prices may tend to reinforce the negative response of output to positive oil shocks. (author)

  6. Recent developments in predictive uncertainty assessment based on the model conditional processor approach

    Directory of Open Access Journals (Sweden)

    G. Coccia

    2011-10-01

    Full Text Available The work aims at discussing the role of predictive uncertainty in flood forecasting and flood emergency management, its relevance to improve the decision making process and the techniques to be used for its assessment.

    Real time flood forecasting requires taking into account predictive uncertainty for a number of reasons. Deterministic hydrological/hydraulic forecasts give useful information about real future events, but their predictions, as usually done in practice, cannot be taken and used as real future occurrences but rather used as pseudo-measurements of future occurrences in order to reduce the uncertainty of decision makers. Predictive Uncertainty (PU is in fact defined as the probability of occurrence of a future value of a predictand (such as water level, discharge or water volume conditional upon prior observations and knowledge as well as on all the information we can obtain on that specific future value from model forecasts. When dealing with commensurable quantities, as in the case of floods, PU must be quantified in terms of a probability distribution function which will be used by the emergency managers in their decision process in order to improve the quality and reliability of their decisions.

    After introducing the concept of PU, the presently available processors are introduced and discussed in terms of their benefits and limitations. In this work the Model Conditional Processor (MCP has been extended to the possibility of using two joint Truncated Normal Distributions (TNDs, in order to improve adaptation to low and high flows.

    The paper concludes by showing the results of the application of the MCP on two case studies, the Po river in Italy and the Baron Fork river, OK, USA. In the Po river case the data provided by the Civil Protection of the Emilia Romagna region have been used to implement an operational example, where the predicted variable is the observed water level. In the Baron Fork River

  7. Uncertainty analysis comes to integrated assessment models for climate change…and conversely

    NARCIS (Netherlands)

    Cooke, R.M.

    2012-01-01

    This article traces the development of uncertainty analysis through three generations punctuated by large methodology investments in the nuclear sector. Driven by a very high perceived legitimation burden, these investments aimed at strengthening the scientific basis of uncertainty quantification.

  8. An Empirical Assessment of the Impact of Requirements Uncertainty on Development Quality Performance

    National Research Council Canada - National Science Library

    Aldaijy, Ayad Y

    2004-01-01

    .... The main purpose of this research is to examine the impact of requirements uncertainty and task uncertainty on outcomes in software development projects, limiting the attention to process and product quality...

  9. Effect of Uncertainty Parameters in Blowdown and Reflood Models for OPR1000 LBLOCA Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Huh, Byung Gil; Jin, Chang Yong; Seul, Kwangwon; Hwang, Taesuk [Korea Institute of Nuclear Safety, Daejeon (Korea, Republic of)

    2014-05-15

    KINS(Korea Institute of Nuclear Safety) has also performed the audit calculation with the KINS Realistic Evaluation Methodology(KINS-REM) to confirm the validity of licensee's calculation. In the BEPU method, it is very important to quantify the code and model uncertainty. It is referred in the following requirement: BE calculations in Regulatory Guide 1.157 - 'the code and models used are acceptable and applicable to the specific facility over the intended operating range and must quantify the uncertainty in the specific application'. In general, the uncertainty of model/code should be obtained through the data comparison with relevant integral- and separate-effect tests at different scales. However, it is not easy to determine these kinds of uncertainty because of the difficulty for evaluating accurately various experiments. Therefore, the expert judgment has been used in many cases even with the limitation that the uncertainty range of important parameters can be wide and inaccurate. In the KINS-REM, six heat transfer parameters in the blowdown phase have been used to consider the uncertainty of models. Recently, MARS-KS code was modified to consider the uncertainty of the five heat transfer parameters in the reflood phase. Accordingly, it is required that the uncertainty range for parameters of reflood models is determined and the effect of these ranges is evaluated. In this study, the large break LOCA (LBLOCA) analysis for OPR1000 was performed to identify the effect of uncertainty parameters in blowdown and reflood models.

  10. Effect of visuomotor-map uncertainty on visuomotor adaptation.

    Science.gov (United States)

    Saijo, Naoki; Gomi, Hiroaki

    2012-03-01

    Vision and proprioception contribute to generating hand movement. If a conflict between the visual and proprioceptive feedback of hand position is given, reaching movement is disturbed initially but recovers after training. Although previous studies have predominantly investigated the adaptive change in the motor output, it is unclear whether the contributions of visual and proprioceptive feedback controls to the reaching movement are modified by visuomotor adaptation. To investigate this, we focused on the change in proprioceptive feedback control associated with visuomotor adaptation. After the adaptation to gradually introduce visuomotor rotation, the hand reached the shifted position of the visual target to move the cursor to the visual target correctly. When the cursor feedback was occasionally eliminated (probe trial), the end point of the hand movement was biased in the visual-target direction, while the movement was initiated in the adapted direction, suggesting the incomplete adaptation of proprioceptive feedback control. Moreover, after the learning of uncertain visuomotor rotation, in which the rotation angle was randomly fluctuated on a trial-by-trial basis, the end-point bias in the probe trial increased, but the initial movement direction was not affected, suggesting a reduction in the adaptation level of proprioceptive feedback control. These results suggest that the change in the relative contribution of visual and proprioceptive feedback controls to the reaching movement in response to the visuomotor-map uncertainty is involved in visuomotor adaptation, whereas feedforward control might adapt in a manner different from that of the feedback control.

  11. TREATING UNCERTAINTIES IN A NUCLEAR SEISMIC PROBABILISTIC RISK ASSESSMENT BY MEANS OF THE DEMPSTER-SHAFER THEORY OF EVIDENCE

    OpenAIRE

    Lo , Chung-Kung; Pedroni , N.; Zio , Enrico

    2014-01-01

    International audience; The analyses carried out within the Seismic Probabilistic Risk Assessments (SPRAs) of Nuclear Power Plants (NPPs) are affected by significant aleatory and epistemic uncertainties. These uncertainties have to be represented and quantified coherently with the data, information and knowledge available, to provide reasonable assurance that related decisions can be taken robustly and with confidence. The amount of data, information and knowledge available for seismic risk a...

  12. Quality in environmental science for policy: assessing uncertainty as a component of policy analysis

    NARCIS (Netherlands)

    Maxim, L.; van der Sluijs, J.P.

    2011-01-01

    The sheer number of attempts to define and classify uncertainty reveals an awareness of its importance in environmental science for policy, though the nature of uncertainty is often misunderstood. The interdisciplinary field of uncertainty analysis is unstable; there are currently several incomplete

  13. Radial core expansion reactivity feedback in advanced LMRs: uncertainties and their effects on inherent safety

    International Nuclear Information System (INIS)

    Wigeland, R.A.; Moran, T.J.

    1988-01-01

    An analytical model for calculating radial core expansion, based on the thermal and elastic bowing of a single subassembly at the core periphery, is used to quantify the effect of uncertainties on this reactivity feedback mechanism. This model has been verified and validated with experimental and numerical results. The impact of these uncertainties on the safety margins in unprotected transients is investigated with SASSYS/SAS4A, which includes this model for calculating the reactivity feedback from radial core expansion. The magnitudes of these uncertainties are not sufficient to preclude the use of radial core expansion reactivity feedback in transient analysis

  14. Urban-rural migration: uncertainty and the effect of a change in the minimum wage.

    Science.gov (United States)

    Ingene, C A; Yu, E S

    1989-01-01

    "This paper extends the neoclassical, Harris-Todaro model of urban-rural migration to the case of production uncertainty in the agricultural sector. A unique feature of the Harris-Todaro model is an exogenously determined minimum wage in the urban sector that exceeds the rural wage. M