Summary of existing uncertainty methods
International Nuclear Information System (INIS)
Glaeser, Horst
2013-01-01
A summary of existing and most used uncertainty methods is presented, and the main features are compared. One of these methods is the order statistics method based on Wilks' formula. It is applied in safety research as well as in licensing. This method has been first proposed by GRS for use in deterministic safety analysis, and is now used by many organisations world-wide. Its advantage is that the number of potential uncertain input and output parameters is not limited to a small number. Such a limitation was necessary for the first demonstration of the Code Scaling Applicability Uncertainty Method (CSAU) by the United States Regulatory Commission (USNRC). They did not apply Wilks' formula in their statistical method propagating input uncertainties to obtain the uncertainty of a single output variable, like peak cladding temperature. A Phenomena Identification and Ranking Table (PIRT) was set up in order to limit the number of uncertain input parameters, and consequently, the number of calculations to be performed. Another purpose of such a PIRT process is to identify the most important physical phenomena which a computer code should be suitable to calculate. The validation of the code should be focused on the identified phenomena. Response surfaces are used in some applications replacing the computer code for performing a high number of calculations. The second well known uncertainty method is the Uncertainty Methodology Based on Accuracy Extrapolation (UMAE) and the follow-up method 'Code with the Capability of Internal Assessment of Uncertainty (CIAU)' developed by the University Pisa. Unlike the statistical approaches, the CIAU does compare experimental data with calculation results. It does not consider uncertain input parameters. Therefore, the CIAU is highly dependent on the experimental database. The accuracy gained from the comparison between experimental data and calculated results are extrapolated to obtain the uncertainty of the system code predictions
Survey of Existing Uncertainty Quantification Capabilities for Army Relevant Problems
2017-11-27
first of these introductory sections is an overview of UQ and its various methods. The second of these discusses issues pertaining to the use of UQ...can be readily assessed, as well as the variance or other statistical measures of the distribu- tion of parameters. The uncertainty in the parameters is... statistics of the outputs of these methods, such as the moments of the probability distributions of model outputs. The module does not explicitly support
Large-uncertainty intelligent states for angular momentum and angle
International Nuclear Information System (INIS)
Goette, Joerg B; Zambrini, Roberta; Franke-Arnold, Sonja; Barnett, Stephen M
2005-01-01
The equality in the uncertainty principle for linear momentum and position is obtained for states which also minimize the uncertainty product. However, in the uncertainty relation for angular momentum and angular position both sides of the inequality are state dependent and therefore the intelligent states, which satisfy the equality, do not necessarily give a minimum for the uncertainty product. In this paper, we highlight the difference between intelligent states and minimum uncertainty states by investigating a class of intelligent states which obey the equality in the angular uncertainty relation while having an arbitrarily large uncertainty product. To develop an understanding for the uncertainties of angle and angular momentum for the large-uncertainty intelligent states we compare exact solutions with analytical approximations in two limiting cases
Large break LOCA uncertainty evaluation and comparison with conservative calculation
International Nuclear Information System (INIS)
Glaeser, H.G.
2004-01-01
The first formulation of the USA Code of Federal Regulations (CFR) 10CFR50 with applicable sections specific to NPP licensing requirements was released 1976. Over a decade later 10CFR 50.46 allowed the use of BE codes instead of conservative code models but uncertainties have to be identified and quantified. Guidelines were released that described interpretations developed over the intervening years that are applicable. Other countries established similar conservative procedures and acceptance criteria. Because conservative methods were used to calculate the peak values of key parameters, such as peak clad temperature (PCT), it was always acknowledged that a large margin, between the 'conservative' calculated value and the 'true' value, existed. Beside USA, regulation in other countries, like Germany, for example, allowed that the state of science and technology is applied in licensing. I.e. the increase of experimental evidence and progress in code development during time could be used. There was no requirement to apply a pure evaluation methodology with licensed assumptions and frozen codes. The thermal-hydraulic system codes became more and more best-estimate codes based on comprehensive validation. This development was and is possible because the rules and guidelines provide the necessary latitude to consider further development of safety technology. Best estimate codes are allowed to be used in licensing in combination with conservative initial and boundary conditions. However, uncertainty quantification is not required. Since some of the initial and boundary conditions are more conservative compared with those internationally used (e.g. 106% reactor power instead 102%, a single failure plus a non-availability due to preventive maintenance is assumed, etc.) it is claimed that the uncertainties of code models are covered. Since many utilities apply for power increase, calculation results come closer to some licensing criteria. The situation in German licensing
Alignment measurements uncertainties for large assemblies using probabilistic analysis techniques
AUTHOR|(CDS)2090816; Almond, Heather
Big science and ambitious industrial projects continually push forward with technical requirements beyond the grasp of conventional engineering techniques. Example of those are ultra-high precision requirements in the field of celestial telescopes, particle accelerators and aerospace industry. Such extreme requirements are limited largely by the capability of the metrology used, namely, it’s uncertainty in relation to the alignment tolerance required. The current work was initiated as part of Maria Curie European research project held at CERN, Geneva aiming to answer those challenges as related to future accelerators requiring alignment of 2 m large assemblies to tolerances in the 10 µm range. The thesis has found several gaps in current knowledge limiting such capability. Among those was the lack of application of state of the art uncertainty propagation methods in alignment measurements metrology. Another major limiting factor found was the lack of uncertainty statements in the thermal errors compensatio...
How uncertainty in socio-economic variables affects large-scale transport model forecasts
DEFF Research Database (Denmark)
Manzo, Stefano; Nielsen, Otto Anker; Prato, Carlo Giacomo
2015-01-01
A strategic task assigned to large-scale transport models is to forecast the demand for transport over long periods of time to assess transport projects. However, by modelling complex systems transport models have an inherent uncertainty which increases over time. As a consequence, the longer...... the period forecasted the less reliable is the forecasted model output. Describing uncertainty propagation patterns over time is therefore important in order to provide complete information to the decision makers. Among the existing literature only few studies analyze uncertainty propagation patterns over...
Evaluating Sources of Risks in Large Engineering Projects: The Roles of Equivocality and Uncertainty
Directory of Open Access Journals (Sweden)
Leena Pekkinen
2015-11-01
Full Text Available Contemporary project risk management literature introduces uncertainty, i.e., the lack of information, as a fundamental basis of project risks. In this study the authors assert that equivocality, i.e., the existence of multiple and conflicting interpretations, can also serve as a basis of risks. With an in-depth empirical investigation of a large complex engineering project the authors identified risk sources having their bases in the situations where uncertainty or equivocality was the predominant attribute. The information processing theory proposes different managerial practices for risk management based on the sources of risks in uncertainty or equivocality.
Risk Management and Uncertainty in Large Complex Public Projects
DEFF Research Database (Denmark)
Neerup Themsen, Tim; Harty, Chris; Tryggestad, Kjell
Governmental actors worldwide are promoting risk management as a rational approach to man-age uncertainty and improve the abilities to deliver large complex projects according to budget, time plans, and pre-set project specifications: But what do we know about the effects of risk management...... on the abilities to meet such objectives? Using Callon’s (1998) twin notions of framing and overflowing we examine the implementation of risk management within the Dan-ish public sector and the effects this generated for the management of two large complex pro-jects. We show how the rational framing of risk...... management have generated unexpected costly outcomes such as: the undermining of the longer-term value and societal relevance of the built asset, the negligence of the wider range of uncertainties emerging during project processes, and constraining forms of knowledge. We also show how expert accountants play...
International Nuclear Information System (INIS)
Muelaner, J E; Wang, Z; Keogh, P S; Brownell, J; Fisher, D
2016-01-01
Understanding the uncertainty of dimensional measurements for large products such as aircraft, spacecraft and wind turbines is fundamental to improving efficiency in these products. Much work has been done to ascertain the uncertainty associated with the main types of instruments used, based on laser tracking and photogrammetry, and the propagation of this uncertainty through networked measurements. Unfortunately this is not sufficient to understand the combined uncertainty of industrial measurements, which include secondary tooling and datum structures used to locate the coordinate frame. This paper presents for the first time a complete evaluation of the uncertainty of large scale industrial measurement processes. Generic analysis and design rules are proven through uncertainty evaluation and optimization for the measurement of a large aero gas turbine engine. This shows how the instrument uncertainty can be considered to be negligible. Before optimization the dominant source of uncertainty was the tooling design, after optimization the dominant source was thermal expansion of the engine; meaning that no further improvement can be made without measurement in a temperature controlled environment. These results will have a significant impact on the ability of aircraft and wind turbines to improve efficiency and therefore reduce carbon emissions, as well as the improved reliability of these products. (paper)
Managing the continuum certainty, uncertainty, unpredictability in large engineering projects
Caron, Franco
2013-01-01
The brief will describe how to develop a risk analysis applied to a project , through a sequence of steps: risk management planning, risk identification, risk classification, risk assessment, risk quantification, risk response planning, risk monitoring and control, process close out and lessons learning. The project risk analysis and management process will be applied to large engineering projects, in particular related to the oil and gas industry. The brief will address the overall range of possible events affecting the project moving from certainty (project issues) through uncertainty (project risks) to unpredictability (unforeseeable events), considering both negative and positive events. Some quantitative techniques (simulation, event tree, Bayesian inference, etc.) will be used to develop risk quantification. The brief addresses a typical subject in the area of project management, with reference to large engineering projects concerning the realization of large plants and infrastructures. These projects a...
Value of Uncertainty: The Lost Opportunities in Large Projects
Directory of Open Access Journals (Sweden)
Agnar Johansen
2016-08-01
Full Text Available The uncertainty management theory has become well established over the last 20–30 years. However, the authors suggest that it does not fully address why opportunities often remain unexploited. Empirical studies show a stronger focus on mitigating risks than exploiting opportunities. This paper therefore addresses why so few opportunities are explored in large projects. The theory claims that risks and opportunities should be equally managed in the same process. In two surveys, conducted in six (private and public companies over a four-year period, project managers stated that uncertainty management is about managing risk and opportunities. However, two case studies from 12 projects from the same companies revealed that all of them had their main focus on risks, and most of the opportunities were left unexploited. We have developed a theoretical explanation model to shed light on this phenomena. The concept is a reflection based on findings from our empirical data up against current project management, uncertainty, risk and stakeholder literature. Our model shows that the threshold for pursuing a potential opportunity is high. If a potential opportunity should be considered, it must be extremely interesting, since it may require contract changes, and the project must abandon an earlier-accepted best solution.
Directory of Open Access Journals (Sweden)
Mathieu Lepot
2017-10-01
Full Text Available A thorough review has been performed on interpolation methods to fill gaps in time-series, efficiency criteria, and uncertainty quantifications. On one hand, there are numerous available methods: interpolation, regression, autoregressive, machine learning methods, etc. On the other hand, there are many methods and criteria to estimate efficiencies of these methods, but uncertainties on the interpolated values are rarely calculated. Furthermore, while they are estimated according to standard methods, the prediction uncertainty is not taken into account: a discussion is thus presented on the uncertainty estimation of interpolated/extrapolated data. Finally, some suggestions for further research and a new method are proposed.
Large contribution of natural aerosols to uncertainty in indirect forcing
Carslaw, K. S.; Lee, L. A.; Reddington, C. L.; Pringle, K. J.; Rap, A.; Forster, P. M.; Mann, G. W.; Spracklen, D. V.; Woodhouse, M. T.; Regayre, L. A.; Pierce, J. R.
2013-11-01
The effect of anthropogenic aerosols on cloud droplet concentrations and radiative properties is the source of one of the largest uncertainties in the radiative forcing of climate over the industrial period. This uncertainty affects our ability to estimate how sensitive the climate is to greenhouse gas emissions. Here we perform a sensitivity analysis on a global model to quantify the uncertainty in cloud radiative forcing over the industrial period caused by uncertainties in aerosol emissions and processes. Our results show that 45 per cent of the variance of aerosol forcing since about 1750 arises from uncertainties in natural emissions of volcanic sulphur dioxide, marine dimethylsulphide, biogenic volatile organic carbon, biomass burning and sea spray. Only 34 per cent of the variance is associated with anthropogenic emissions. The results point to the importance of understanding pristine pre-industrial-like environments, with natural aerosols only, and suggest that improved measurements and evaluation of simulated aerosols in polluted present-day conditions will not necessarily result in commensurate reductions in the uncertainty of forcing estimates.
Large contribution of natural aerosols to uncertainty in indirect forcing.
Carslaw, K S; Lee, L A; Reddington, C L; Pringle, K J; Rap, A; Forster, P M; Mann, G W; Spracklen, D V; Woodhouse, M T; Regayre, L A; Pierce, J R
2013-11-07
The effect of anthropogenic aerosols on cloud droplet concentrations and radiative properties is the source of one of the largest uncertainties in the radiative forcing of climate over the industrial period. This uncertainty affects our ability to estimate how sensitive the climate is to greenhouse gas emissions. Here we perform a sensitivity analysis on a global model to quantify the uncertainty in cloud radiative forcing over the industrial period caused by uncertainties in aerosol emissions and processes. Our results show that 45 per cent of the variance of aerosol forcing since about 1750 arises from uncertainties in natural emissions of volcanic sulphur dioxide, marine dimethylsulphide, biogenic volatile organic carbon, biomass burning and sea spray. Only 34 per cent of the variance is associated with anthropogenic emissions. The results point to the importance of understanding pristine pre-industrial-like environments, with natural aerosols only, and suggest that improved measurements and evaluation of simulated aerosols in polluted present-day conditions will not necessarily result in commensurate reductions in the uncertainty of forcing estimates.
Uncertainty Quantification for Large-Scale Ice Sheet Modeling
Energy Technology Data Exchange (ETDEWEB)
Ghattas, Omar [Univ. of Texas, Austin, TX (United States)
2016-02-05
This report summarizes our work to develop advanced forward and inverse solvers and uncertainty quantification capabilities for a nonlinear 3D full Stokes continental-scale ice sheet flow model. The components include: (1) forward solver: a new state-of-the-art parallel adaptive scalable high-order-accurate mass-conservative Newton-based 3D nonlinear full Stokes ice sheet flow simulator; (2) inverse solver: a new adjoint-based inexact Newton method for solution of deterministic inverse problems governed by the above 3D nonlinear full Stokes ice flow model; and (3) uncertainty quantification: a novel Hessian-based Bayesian method for quantifying uncertainties in the inverse ice sheet flow solution and propagating them forward into predictions of quantities of interest such as ice mass flux to the ocean.
Lepot, M.J.; Aubin, Jean Baptiste; Clemens, F.H.L.R.
2017-01-01
A thorough review has been performed on interpolation methods to fill gaps in time-series, efficiency criteria, and uncertainty quantifications. On one hand, there are numerous available methods: interpolation, regression, autoregressive, machine learning methods, etc. On the other hand, there are
Large storage operations under climate change: expanding uncertainties and evolving tradeoffs
Giuliani, Matteo; Anghileri, Daniela; Castelletti, Andrea; Vu, Phuong Nam; Soncini-Sessa, Rodolfo
2016-03-01
In a changing climate and society, large storage systems can play a key role for securing water, energy, and food, and rebalancing their cross-dependencies. In this letter, we study the role of large storage operations as flexible means of adaptation to climate change. In particular, we explore the impacts of different climate projections for different future time horizons on the multi-purpose operations of the existing system of large dams in the Red River basin (China-Laos-Vietnam). We identify the main vulnerabilities of current system operations, understand the risk of failure across sectors by exploring the evolution of the system tradeoffs, quantify how the uncertainty associated to climate scenarios is expanded by the storage operations, and assess the expected costs if no adaptation is implemented. Results show that, depending on the climate scenario and the time horizon considered, the existing operations are predicted to change on average from -7 to +5% in hydropower production, +35 to +520% in flood damages, and +15 to +160% in water supply deficit. These negative impacts can be partially mitigated by adapting the existing operations to future climate, reducing the loss of hydropower to 5%, potentially saving around 34.4 million US year-1 at the national scale. Since the Red River is paradigmatic of many river basins across south east Asia, where new large dams are under construction or are planned to support fast growing economies, our results can support policy makers in prioritizing responses and adaptation strategies to the changing climate.
Uncertainty budget in internal monostandard NAA for small and large size samples analysis
International Nuclear Information System (INIS)
Dasari, K.B.; Acharya, R.
2014-01-01
Total uncertainty budget evaluation on determined concentration value is important under quality assurance programme. Concentration calculation in NAA or carried out by relative NAA and k0 based internal monostandard NAA (IM-NAA) method. IM-NAA method has been used for small and large sample analysis of clay potteries. An attempt was made to identify the uncertainty components in IM-NAA and uncertainty budget for La in both small and large size samples has been evaluated and compared. (author)
Uncertainty analysis methods for quantification of source terms using a large computer code
International Nuclear Information System (INIS)
Han, Seok Jung
1997-02-01
Quantification of uncertainties in the source term estimations by a large computer code, such as MELCOR and MAAP, is an essential process of the current probabilistic safety assessments (PSAs). The main objectives of the present study are (1) to investigate the applicability of a combined procedure of the response surface method (RSM) based on input determined from a statistical design and the Latin hypercube sampling (LHS) technique for the uncertainty analysis of CsI release fractions under a hypothetical severe accident sequence of a station blackout at Young-Gwang nuclear power plant using MAAP3.0B code as a benchmark problem; and (2) to propose a new measure of uncertainty importance based on the distributional sensitivity analysis. On the basis of the results obtained in the present work, the RSM is recommended to be used as a principal tool for an overall uncertainty analysis in source term quantifications, while using the LHS in the calculations of standardized regression coefficients (SRC) and standardized rank regression coefficients (SRRC) to determine the subset of the most important input parameters in the final screening step and to check the cumulative distribution functions (cdfs) obtained by RSM. Verification of the response surface model for its sufficient accuracy is a prerequisite for the reliability of the final results obtained by the combined procedure proposed in the present work. In the present study a new measure has been developed to utilize the metric distance obtained from cumulative distribution functions (cdfs). The measure has been evaluated for three different cases of distributions in order to assess the characteristics of the measure: The first case and the second are when the distribution is known as analytical distributions and the other case is when the distribution is unknown. The first case is given by symmetry analytical distributions. The second case consists of two asymmetry distributions of which the skewness is non zero
Deterministic methods for sensitivity and uncertainty analysis in large-scale computer models
International Nuclear Information System (INIS)
Worley, B.A.; Oblow, E.M.; Pin, F.G.; Maerker, R.E.; Horwedel, J.E.; Wright, R.Q.; Lucius, J.L.
1987-01-01
The fields of sensitivity and uncertainty analysis are dominated by statistical techniques when large-scale modeling codes are being analyzed. This paper reports on the development and availability of two systems, GRESS and ADGEN, that make use of computer calculus compilers to automate the implementation of deterministic sensitivity analysis capability into existing computer models. This automation removes the traditional limitation of deterministic sensitivity methods. The paper describes a deterministic uncertainty analysis method (DUA) that uses derivative information as a basis to propagate parameter probability distributions to obtain result probability distributions. The paper demonstrates the deterministic approach to sensitivity and uncertainty analysis as applied to a sample problem that models the flow of water through a borehole. The sample problem is used as a basis to compare the cumulative distribution function of the flow rate as calculated by the standard statistical methods and the DUA method. The DUA method gives a more accurate result based upon only two model executions compared to fifty executions in the statistical case
Deterministic sensitivity and uncertainty analysis for large-scale computer models
International Nuclear Information System (INIS)
Worley, B.A.; Pin, F.G.; Oblow, E.M.; Maerker, R.E.; Horwedel, J.E.; Wright, R.Q.
1988-01-01
The fields of sensitivity and uncertainty analysis have traditionally been dominated by statistical techniques when large-scale modeling codes are being analyzed. These methods are able to estimate sensitivities, generate response surfaces, and estimate response probability distributions given the input parameter probability distributions. Because the statistical methods are computationally costly, they are usually applied only to problems with relatively small parameter sets. Deterministic methods, on the other hand, are very efficient and can handle large data sets, but generally require simpler models because of the considerable programming effort required for their implementation. The first part of this paper reports on the development and availability of two systems, GRESS and ADGEN, that make use of computer calculus compilers to automate the implementation of deterministic sensitivity analysis capability into existing computer models. This automation removes the traditional limitation of deterministic sensitivity methods. This second part of the paper describes a deterministic uncertainty analysis method (DUA) that uses derivative information as a basis to propagate parameter probability distributions to obtain result probability distributions. This paper is applicable to low-level radioactive waste disposal system performance assessment
Planning under uncertainty solving large-scale stochastic linear programs
Energy Technology Data Exchange (ETDEWEB)
Infanger, G. [Stanford Univ., CA (United States). Dept. of Operations Research]|[Technische Univ., Vienna (Austria). Inst. fuer Energiewirtschaft
1992-12-01
For many practical problems, solutions obtained from deterministic models are unsatisfactory because they fail to hedge against certain contingencies that may occur in the future. Stochastic models address this shortcoming, but up to recently seemed to be intractable due to their size. Recent advances both in solution algorithms and in computer technology now allow us to solve important and general classes of practical stochastic problems. We show how large-scale stochastic linear programs can be efficiently solved by combining classical decomposition and Monte Carlo (importance) sampling techniques. We discuss the methodology for solving two-stage stochastic linear programs with recourse, present numerical results of large problems with numerous stochastic parameters, show how to efficiently implement the methodology on a parallel multi-computer and derive the theory for solving a general class of multi-stage problems with dependency of the stochastic parameters within a stage and between different stages.
[Dual process in large number estimation under uncertainty].
Matsumuro, Miki; Miwa, Kazuhisa; Terai, Hitoshi; Yamada, Kento
2016-08-01
According to dual process theory, there are two systems in the mind: an intuitive and automatic System 1 and a logical and effortful System 2. While many previous studies about number estimation have focused on simple heuristics and automatic processes, the deliberative System 2 process has not been sufficiently studied. This study focused on the System 2 process for large number estimation. First, we described an estimation process based on participants’ verbal reports. The task, corresponding to the problem-solving process, consisted of creating subgoals, retrieving values, and applying operations. Second, we investigated the influence of such deliberative process by System 2 on intuitive estimation by System 1, using anchoring effects. The results of the experiment showed that the System 2 process could mitigate anchoring effects.
Social Discounting of Large Dams with Climate Change Uncertainty
Directory of Open Access Journals (Sweden)
Marc Jeuland
2010-06-01
This paper reviews the recent discounting controversy and examines its implications for the appraisal of an illustrative hydropower project in Ethiopia. The analysis uses an integrated hydro-economic model that accounts for how the dam’s transboundary impacts vary with climate change. The real value of the dam is found to be highly sensitive to assumptions about future economic growth. The argument for investment is weakest under conditions of robust global economic growth, particularly if these coincide with unfavourable hydrological or development factors related to the project. If however long-term growth is reduced, the value of the dam tends to increase. There may also be distributional or local arguments favouring investment, if growth in the investment region lags behind that of the rest of the globe. In such circumstances, a large dam can be seen as a form of insurance that protects future vulnerable generations against the possibility of macroeconomic instability or climate shocks.
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 ...
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
Sampling based uncertainty analysis of 10% hot leg break LOCA in large scale test facility
International Nuclear Information System (INIS)
Sengupta, Samiran; Kraina, V.; Dubey, S. K.; Rao, R. S.; Gupta, S. K.
2010-01-01
Sampling based uncertainty analysis was carried out to quantify uncertainty in predictions of best estimate code RELAP5/MOD3.2 for a thermal hydraulic test (10% hot leg break LOCA) performed in the Large Scale Test Facility (LSTF) as a part of an IAEA coordinated research project. The nodalisation of the test facility was qualified for both steady state and transient level by systematically applying the procedures led by uncertainty methodology based on accuracy extrapolation (UMAE); uncertainty analysis was carried out using the Latin hypercube sampling (LHS) method to evaluate uncertainty for ten input parameters. Sixteen output parameters were selected for uncertainty evaluation and uncertainty band between 5 th and 95 th percentile of the output parameters were evaluated. It was observed that the uncertainty band for the primary pressure during two phase blowdown is larger than that of the remaining period. Similarly, a larger uncertainty band is observed relating to accumulator injection flow during reflood phase. Importance analysis was also carried out and standard rank regression coefficients were computed to quantify the effect of each individual input parameter on output parameters. It was observed that the break discharge coefficient is the most important uncertain parameter relating to the prediction of all the primary side parameters and that the steam generator (SG) relief pressure setting is the most important parameter in predicting the SG secondary pressure
Directory of Open Access Journals (Sweden)
Peter E. Land
2018-05-01
Full Text Available Uncertainty estimation is crucial to establishing confidence in any data analysis, and this is especially true for Essential Climate Variables, including ocean colour. Methods for deriving uncertainty vary greatly across data types, so a generic statistics-based approach applicable to multiple data types is an advantage to simplify the use and understanding of uncertainty data. Progress towards rigorous uncertainty analysis of ocean colour has been slow, in part because of the complexity of ocean colour processing. Here, we present a general approach to uncertainty characterisation, using a database of satellite-in situ matchups to generate a statistical model of satellite uncertainty as a function of its contributing variables. With an example NASA MODIS-Aqua chlorophyll-a matchups database mostly covering the north Atlantic, we demonstrate a model that explains 67% of the squared error in log(chlorophyll-a as a potentially correctable bias, with the remaining uncertainty being characterised as standard deviation and standard error at each pixel. The method is quite general, depending only on the existence of a suitable database of matchups or reference values, and can be applied to other sensors and data types such as other satellite observed Essential Climate Variables, empirical algorithms derived from in situ data, or even model data.
International Nuclear Information System (INIS)
Luxat, J.C.; Huget, R.G.
2001-01-01
Development of a methodology to perform best estimate and uncertainty nuclear safety analysis has been underway at Ontario Power Generation for the past two and one half years. A key driver for the methodology development, and one of the major challenges faced, is the need to re-establish demonstrated safety margins that have progressively been undermined through excessive and compounding conservatism in deterministic analyses. The major focus of the prototyping applications was to quantify the safety margins that exist at the probable range of high power operating conditions, rather than the highly improbable operating states associated with Limit of the Envelope (LOE) assumptions. In LOE, all parameters of significance to the consequences of a postulated accident are assumed to simultaneously deviate to their limiting values. Another equally important objective of the prototyping was to demonstrate the feasibility of conducting safety analysis as an incremental analysis activity, as opposed to a major re-analysis activity. The prototype analysis solely employed prior analyses of Bruce B large break LOCA events - no new computer simulations were undertaken. This is a significant and novel feature of the prototyping work. This methodology framework has been applied to a postulated large break LOCA in a Bruce generating unit on a prototype basis. This paper presents results of the application. (author)
Effects of uncertainty in model predictions of individual tree volume on large area volume estimates
Ronald E. McRoberts; James A. Westfall
2014-01-01
Forest inventory estimates of tree volume for large areas are typically calculated by adding model predictions of volumes for individual trees. However, the uncertainty in the model predictions is generally ignored with the result that the precision of the large area volume estimates is overestimated. The primary study objective was to estimate the effects of model...
Interpretation of the peak areas in gamma-ray spectra that have a large relative uncertainty
International Nuclear Information System (INIS)
Korun, M.; Maver Modec, P.; Vodenik, B.
2012-01-01
Empirical evidence is provided that the areas of peaks having a relative uncertainty in excess of 30% are overestimated. This systematic influence is of a statistical nature and originates in way the peak-analyzing routine recognizes the small peaks. It is not easy to detect this influence since it is smaller than the peak-area uncertainty. However, the systematic influence can be revealed in repeated measurements under the same experimental conditions, e.g., in background measurements. To evaluate the systematic influence, background measurements were analyzed with the peak-analyzing procedure described by Korun et al. (2008). The magnitude of the influence depends on the relative uncertainty of the peak area and may amount, in the conditions used in the peak analysis, to a factor of 5 at relative uncertainties exceeding 60%. From the measurements, the probability for type-II errors, as a function of the relative uncertainty of the peak area, was extracted. This probability is near zero below an uncertainty of 30% and rises to 90% at uncertainties exceeding 50%. - Highlights: ► A systematic influence affecting small peak areas in gamma-ray spectra is described. ► The influence originates in the peak locating procedure, using a pre-determined sensitivity. ► The predetermined sensitivity makes peak areas with large uncertainties to be overestimated. ► The influence depends on the relative uncertainty of the number of counts in the peak. ► Corrections exceeding a factor of 3 are attained at peak area uncertainties exceeding 60%.
Hughes, J. D.; Metz, P. A.
2014-12-01
Most watershed studies include observation-based water budget analyses to develop first-order estimates of significant flow terms. Surface-water/groundwater (SWGW) exchange is typically assumed to be equal to the residual of the sum of inflows and outflows in a watershed. These estimates of SWGW exchange, however, are highly uncertain as a result of the propagation of uncertainty inherent in the calculation or processing of the other terms of the water budget, such as stage-area-volume relations, and uncertainties associated with land-cover based evapotranspiration (ET) rate estimates. Furthermore, the uncertainty of estimated SWGW exchanges can be magnified in large wetland systems that transition from dry to wet during wet periods. Although it is well understood that observation-based estimates of SWGW exchange are uncertain it is uncommon for the uncertainty of these estimates to be directly quantified. High-level programming languages like Python can greatly reduce the effort required to (1) quantify the uncertainty of estimated SWGW exchange in large wetland systems and (2) evaluate how different approaches for partitioning land-cover data in a watershed may affect the water-budget uncertainty. We have used Python with the Numpy, Scipy.stats, and pyDOE packages to implement an unconstrained Monte Carlo approach with Latin Hypercube sampling to quantify the uncertainty of monthly estimates of SWGW exchange in the Floral City watershed of the Tsala Apopka wetland system in west-central Florida, USA. Possible sources of uncertainty in the water budget analysis include rainfall, ET, canal discharge, and land/bathymetric surface elevations. Each of these input variables was assigned a probability distribution based on observation error or spanning the range of probable values. The Monte Carlo integration process exposes the uncertainties in land-cover based ET rate estimates as the dominant contributor to the uncertainty in SWGW exchange estimates. We will discuss
Doytchinov, I.; Tonnellier, X.; Shore, P.; Nicquevert, B.; Modena, M.; Mainaud Durand, H.
2018-05-01
Micrometric assembly and alignment requirements for future particle accelerators, and especially large assemblies, create the need for accurate uncertainty budgeting of alignment measurements. Measurements and uncertainties have to be accurately stated and traceable, to international standards, for metre-long sized assemblies, in the range of tens of µm. Indeed, these hundreds of assemblies will be produced and measured by several suppliers around the world, and will have to be integrated into a single machine. As part of the PACMAN project at CERN, we proposed and studied a practical application of probabilistic modelling of task-specific alignment uncertainty by applying a simulation by constraints calibration method. Using this method, we calibrated our measurement model using available data from ISO standardised tests (10360 series) for the metrology equipment. We combined this model with reference measurements and analysis of the measured data to quantify the actual specific uncertainty of each alignment measurement procedure. Our methodology was successfully validated against a calibrated and traceable 3D artefact as part of an international inter-laboratory study. The validated models were used to study the expected alignment uncertainty and important sensitivity factors in measuring the shortest and longest of the compact linear collider study assemblies, 0.54 m and 2.1 m respectively. In both cases, the laboratory alignment uncertainty was within the targeted uncertainty budget of 12 µm (68% confidence level). It was found that the remaining uncertainty budget for any additional alignment error compensations, such as the thermal drift error due to variation in machine operation heat load conditions, must be within 8.9 µm and 9.8 µm (68% confidence level) respectively.
International Nuclear Information System (INIS)
Sig Drellack, Lance Prothro
2007-01-01
The Underground Test Area (UGTA) Project of the U.S. Department of Energy, National Nuclear Security Administration Nevada Site Office is in the process of assessing and developing regulatory decision options based on modeling predictions of contaminant transport from underground testing of nuclear weapons at the Nevada Test Site (NTS). The UGTA Project is attempting to develop an effective modeling strategy that addresses and quantifies multiple components of uncertainty including natural variability, parameter uncertainty, conceptual/model uncertainty, and decision uncertainty in translating model results into regulatory requirements. The modeling task presents multiple unique challenges to the hydrological sciences as a result of the complex fractured and faulted hydrostratigraphy, the distributed locations of sources, the suite of reactive and non-reactive radionuclides, and uncertainty in conceptual models. Characterization of the hydrogeologic system is difficult and expensive because of deep groundwater in the arid desert setting and the large spatial setting of the NTS. Therefore, conceptual model uncertainty is partially addressed through the development of multiple alternative conceptual models of the hydrostratigraphic framework and multiple alternative models of recharge and discharge. Uncertainty in boundary conditions is assessed through development of alternative groundwater fluxes through multiple simulations using the regional groundwater flow model. Calibration of alternative models to heads and measured or inferred fluxes has not proven to provide clear measures of model quality. Therefore, model screening by comparison to independently-derived natural geochemical mixing targets through cluster analysis has also been invoked to evaluate differences between alternative conceptual models. Advancing multiple alternative flow models, sensitivity of transport predictions to parameter uncertainty is assessed through Monte Carlo simulations. The
International Nuclear Information System (INIS)
Fakhari, Vahid; Choi, Seung-Bok; Cho, Chang-Hyun
2015-01-01
This work presents a new robust model reference adaptive control (MRAC) for vibration control caused from vehicle engine using an electromagnetic type of active engine mount. Vibration isolation performances of the active mount associated with the robust controller are evaluated in the presence of large uncertainties. As a first step, an active mount with linear solenoid actuator is prepared and its dynamic model is identified via experimental test. Subsequently, a new robust MRAC based on the gradient method with σ-modification is designed by selecting a proper reference model. In designing the robust adaptive control, structured (parametric) uncertainties in the stiffness of the passive part of the mount and in damping ratio of the active part of the mount are considered to investigate the robustness of the proposed controller. Experimental and simulation results are presented to evaluate performance focusing on the robustness behavior of the controller in the face of large uncertainties. The obtained results show that the proposed controller can sufficiently provide the robust vibration control performance even in the presence of large uncertainties showing an effective vibration isolation. (paper)
Deterministic sensitivity and uncertainty analysis for large-scale computer models
International Nuclear Information System (INIS)
Worley, B.A.; Pin, F.G.; Oblow, E.M.; Maerker, R.E.; Horwedel, J.E.; Wright, R.Q.
1988-01-01
This paper presents a comprehensive approach to sensitivity and uncertainty analysis of large-scale computer models that is analytic (deterministic) in principle and that is firmly based on the model equations. The theory and application of two systems based upon computer calculus, GRESS and ADGEN, are discussed relative to their role in calculating model derivatives and sensitivities without a prohibitive initial manpower investment. Storage and computational requirements for these two systems are compared for a gradient-enhanced version of the PRESTO-II computer model. A Deterministic Uncertainty Analysis (DUA) method that retains the characteristics of analytically computing result uncertainties based upon parameter probability distributions is then introduced and results from recent studies are shown. 29 refs., 4 figs., 1 tab
Uncertainty Evaluation of Reactivity Coefficients for a large advanced SFR Core Design
International Nuclear Information System (INIS)
Khamakhem, Wassim; Rimpault, Gerald
2008-01-01
Sodium Cooled Fast Reactors are currently being reshaped in order to meet Generation IV goals on economics, safety and reliability, sustainability and proliferation resistance. Recent studies have led to large SFR cores for a 3600 MWth power plants, cores which exhibit interesting features. The designs have had to balance between competing aspects such as sustainability and safety characteristics. Sustainability in neutronic terms is translated into positive breeding gain and safety into rather low Na void reactivity effects. The studies have been done on two SFR concepts using oxide and carbide fuels. The use of the sensitivity theory in the ERANOS determinist code system has been used. Calculations have been performed with different sodium evaluations: JEF2.2, ERALIB-1 and the most recent JEFF3.1 and ENDF/B-VII in order to make a broad comparison. Values for the Na void reactivity effect exhibit differences as large as 14% when using the different sodium libraries. Uncertainties due to nuclear data on the reactivity coefficients were performed with BOLNA variances-covariances data, the Na Void Effect uncertainties are near to 12% at 1σ. Since, the uncertainties are far beyond the target accuracy for a design achieving high performance, two directions are envisaged: the first one is to perform new differential measurements or in a second attempt use integral experiments to improve effectively the nuclear data set and its uncertainties such as performed in the past with ERALIB1. (authors)
Effectiveness of a large mimic panel in an existing nuclear power plant central control board
International Nuclear Information System (INIS)
Kubota, Ryuji; Satoh, Hiroyuki; Sasajima, Katsuhiro; Kawano, Ryutaro; Shibuya Shinya
1999-01-01
We conducted the analysis of the nuclear power plant (NPP) operators' behaviors under emergency conditions by using training simulators as a joint research project by Japanese BWR groups for twelve years. In the phase-IV of this project we executed two kinds of experiments to evaluate the effectiveness of the interfaces. One was for evaluations of the interfaces such as CRTs with touch screen, a large mimic panel, and a hierarchical annunciator system introduced in the newly developed ABWR type central control board. The other was that we analyzed the operators' behaviors in emergency conditions by using the first generation BWR type central control board which was added new interfaces such as a large display screen and demarcation on the board to help operators to understand the plant. The demarcation is one of the visual interface improvements and its technique is that a line enclosing several components causes them to be perceived as a group.The result showed that both the large display panel Introduced in ABWR central control board and the large display screen in the existing BWR type central control board improved the performance of the NPP operators in the experiments. It was expected that introduction of the large mimic panel into the existing BWR type central control boards would improve operators' performance. However, in the case of actual installation of the large display board into the existing central control boards, there are spatial and hardware constraints. Therefore the size of lamps, lines connecting from symbols of the pumps or valves to the others' will have to be modified under these constraints. It is important to evaluate the displayed information on the large display board before actual installation. We made experiments to solve these problems by using TEPCO's research simulator which is added a large mimic panel. (author)
Systematic uncertainties in long-baseline neutrino oscillations for large θ₁₃
Energy Technology Data Exchange (ETDEWEB)
Coloma, Pilar; Huber, Patrick; Kopp, Joachim; Winter, Walter
2013-02-01
We study the physics potential of future long-baseline neutrino oscillation experiments at large θ₁₃, focusing especially on systematic uncertainties. We discuss superbeams, \\bbeams, and neutrino factories, and for the first time compare these experiments on an equal footing with respect to systematic errors. We explicitly simulate near detectors for all experiments, we use the same implementation of systematic uncertainties for all experiments, and we fully correlate the uncertainties among detectors, oscillation channels, and beam polarizations as appropriate. As our primary performance indicator, we use the achievable precision in the measurement of the CP violating phase $\\deltacp$. We find that a neutrino factory is the only instrument that can measure $\\deltacp$ with a precision similar to that of its quark sector counterpart. All neutrino beams operating at peak energies ≳2 GeV are quite robust with respect to systematic uncertainties, whereas especially \\bbeams and \\thk suffer from large cross section uncertainties in the quasi-elastic regime, combined with their inability to measure the appearance signal cross sections at the near detector. A noteworthy exception is the combination of a γ =100 \\bbeam with an \\spl-based superbeam, in which all relevant cross sections can be measured in a self-consistent way. This provides a performance, second only to the neutrino factory. For other superbeam experiments such as \\lbno and the setups studied in the context of the \\lbne reconfiguration effort, statistics turns out to be the bottleneck. In almost all cases, the near detector is not critical to control systematics since the combined fit of appearance and disappearance data already constrains the impact of systematics to be small provided that the three active flavor oscillation framework is valid.
Zheng, Xiao-Tong; Hui, Chang; Yeh, Sang-Wook
2018-06-01
El Niño-Southern Oscillation (ENSO) is the dominant mode of variability in the coupled ocean-atmospheric system. Future projections of ENSO change under global warming are highly uncertain among models. In this study, the effect of internal variability on ENSO amplitude change in future climate projections is investigated based on a 40-member ensemble from the Community Earth System Model Large Ensemble (CESM-LE) project. A large uncertainty is identified among ensemble members due to internal variability. The inter-member diversity is associated with a zonal dipole pattern of sea surface temperature (SST) change in the mean along the equator, which is similar to the second empirical orthogonal function (EOF) mode of tropical Pacific decadal variability (TPDV) in the unforced control simulation. The uncertainty in CESM-LE is comparable in magnitude to that among models of the Coupled Model Intercomparison Project phase 5 (CMIP5), suggesting the contribution of internal variability to the intermodel uncertainty in ENSO amplitude change. However, the causations between changes in ENSO amplitude and the mean state are distinct between CESM-LE and CMIP5 ensemble. The CESM-LE results indicate that a large ensemble of 15 members is needed to separate the relative contributions to ENSO amplitude change over the twenty-first century between forced response and internal variability.
MageComet—web application for harmonizing existing large-scale experiment descriptions
Xue, Vincent; Burdett, Tony; Lukk, Margus; Taylor, Julie; Brazma, Alvis; Parkinson, Helen
2012-01-01
Motivation: Meta-analysis of large gene expression datasets obtained from public repositories requires consistently annotated data. Curation of such experiments, however, is an expert activity which involves repetitive manipulation of text. Existing tools for automated curation are few, which bottleneck the analysis pipeline. Results: We present MageComet, a web application for biologists and annotators that facilitates the re-annotation of gene expression experiments in MAGE-TAB format. It i...
Sustainability Risk Evaluation for Large-Scale Hydropower Projects with Hybrid Uncertainty
Directory of Open Access Journals (Sweden)
Weiyao Tang
2018-01-01
Full Text Available As large-scale hydropower projects are influenced by many factors, risk evaluations are complex. This paper considers a hydropower project as a complex system from the perspective of sustainability risk, and divides it into three subsystems: the natural environment subsystem, the eco-environment subsystem and the socioeconomic subsystem. Risk-related factors and quantitative dimensions of each subsystem are comprehensively analyzed considering uncertainty of some quantitative dimensions solved by hybrid uncertainty methods, including fuzzy (e.g., the national health degree, the national happiness degree, the protection of cultural heritage, random (e.g., underground water levels, river width, and fuzzy random uncertainty (e.g., runoff volumes, precipitation. By calculating the sustainability risk-related degree in each of the risk-related factors, a sustainable risk-evaluation model is built. Based on the calculation results, the critical sustainability risk-related factors are identified and targeted to reduce the losses caused by sustainability risk factors of the hydropower project. A case study at the under-construction Baihetan hydropower station is presented to demonstrate the viability of the risk-evaluation model and to provide a reference for the sustainable risk evaluation of other large-scale hydropower projects.
Härer, Stefan; Bernhardt, Matthias; Siebers, Matthias; Schulz, Karsten
2018-05-01
Knowledge of current snow cover extent is essential for characterizing energy and moisture fluxes at the Earth's surface. The snow-covered area (SCA) is often estimated by using optical satellite information in combination with the normalized-difference snow index (NDSI). The NDSI thereby uses a threshold for the definition if a satellite pixel is assumed to be snow covered or snow free. The spatiotemporal representativeness of the standard threshold of 0.4 is however questionable at the local scale. Here, we use local snow cover maps derived from ground-based photography to continuously calibrate the NDSI threshold values (NDSIthr) of Landsat satellite images at two European mountain sites of the period from 2010 to 2015. The Research Catchment Zugspitzplatt (RCZ, Germany) and Vernagtferner area (VF, Austria) are both located within a single Landsat scene. Nevertheless, the long-term analysis of the NDSIthr demonstrated that the NDSIthr at these sites are not correlated (r = 0.17) and different than the standard threshold of 0.4. For further comparison, a dynamic and locally optimized NDSI threshold was used as well as another locally optimized literature threshold value (0.7). It was shown that large uncertainties in the prediction of the SCA of up to 24.1 % exist in satellite snow cover maps in cases where the standard threshold of 0.4 is used, but a newly developed calibrated quadratic polynomial model which accounts for seasonal threshold dynamics can reduce this error. The model minimizes the SCA uncertainties at the calibration site VF by 50 % in the evaluation period and was also able to improve the results at RCZ in a significant way. Additionally, a scaling experiment shows that the positive effect of a locally adapted threshold diminishes using a pixel size of 500 m or larger, underlining the general applicability of the standard threshold at larger scales.
International Nuclear Information System (INIS)
Varlamov, V.V.; Efimkin, N.G.; Ishkhanov, B.S.; Sapunenko, V.V.
1994-12-01
The authors describe a method based on the reduction method for the evaluation of photonuclear reaction cross-sections obtained under conditions where there are large systematic uncertainties (different instrumental functions, calibration and normalization errors). The evaluation method involves using the actual instrumental function (photon spectrum) of each individual experiment to reduce the data to a representation generated by an instrumental function of better quality. The objective is to find the most reasonably achievable monoenergetic representation of the information on the reaction cross-section derived from the results of various experiments and to take into account the calibration and normalization errors in these experiments. The method was used to obtain the evaluated total photoneutron reaction cross-section (γ,xn) for a large number of nuclei. Data obtained for 16 O and 208 Pb are presented. (author). 36 refs, 6 figs, 4 tabs
The existence of very large-scale structures in the universe
Energy Technology Data Exchange (ETDEWEB)
Goicoechea, L J; Martin-Mirones, J M [Universidad de Cantabria Santander, (ES)
1989-09-01
Assuming that the dipole moment observed in the cosmic background radiation (microwaves and X-rays) can be interpreted as a consequence of the motion of the observer toward a non-local and very large-scale structure in our universe, we study the perturbation of the m-z relation by this inhomogeneity, the dynamical contribution of sources to the dipole anisotropy in the X-ray background and the imprint that several structures with such characteristics would have had on the microwave background at the decoupling. We conclude that in this model the observed anisotropy in the microwave background on intermediate angular scales ({approx}10{sup 0}) may be in conflict with the existence of superstructures.
Directory of Open Access Journals (Sweden)
Min Chen
2014-01-01
Full Text Available We study the one-dimensional bipolar nonisentropic Euler-Poisson equations which can model various physical phenomena, such as the propagation of electron and hole in submicron semiconductor devices, the propagation of positive ion and negative ion in plasmas, and the biological transport of ions for channel proteins. We show the existence and large time behavior of global smooth solutions for the initial value problem, when the difference of two particles’ initial mass is nonzero, and the far field of two particles’ initial temperatures is not the ambient device temperature. This result improves that of Y.-P. Li, for the case that the difference of two particles’ initial mass is zero, and the far field of the initial temperature is the ambient device temperature.
Shearer, Christine; West, Mick; Caldeira, Ken; Davis, Steven J.
2016-08-01
Nearly 17% of people in an international survey said they believed the existence of a secret large-scale atmospheric program (SLAP) to be true or partly true. SLAP is commonly referred to as ‘chemtrails’ or ‘covert geoengineering’, and has led to a number of websites purported to show evidence of widespread chemical spraying linked to negative impacts on human health and the environment. To address these claims, we surveyed two groups of experts—atmospheric chemists with expertize in condensation trails and geochemists working on atmospheric deposition of dust and pollution—to scientifically evaluate for the first time the claims of SLAP theorists. Results show that 76 of the 77 scientists (98.7%) that took part in this study said they had not encountered evidence of a SLAP, and that the data cited as evidence could be explained through other factors, including well-understood physics and chemistry associated with aircraft contrails and atmospheric aerosols. Our goal is not to sway those already convinced that there is a secret, large-scale spraying program—who often reject counter-evidence as further proof of their theories—but rather to establish a source of objective science that can inform public discourse.
Multi-fidelity uncertainty quantification in large-scale predictive simulations of turbulent flow
Geraci, Gianluca; Jofre-Cruanyes, Lluis; Iaccarino, Gianluca
2017-11-01
The performance characterization of complex engineering systems often relies on accurate, but computationally intensive numerical simulations. It is also well recognized that in order to obtain a reliable numerical prediction the propagation of uncertainties needs to be included. Therefore, Uncertainty Quantification (UQ) plays a fundamental role in building confidence in predictive science. Despite the great improvement in recent years, even the more advanced UQ algorithms are still limited to fairly simplified applications and only moderate parameter dimensionality. Moreover, in the case of extremely large dimensionality, sampling methods, i.e. Monte Carlo (MC) based approaches, appear to be the only viable alternative. In this talk we describe and compare a family of approaches which aim to accelerate the convergence of standard MC simulations. These methods are based on hierarchies of generalized numerical resolutions (multi-level) or model fidelities (multi-fidelity), and attempt to leverage the correlation between Low- and High-Fidelity (HF) models to obtain a more accurate statistical estimator without introducing additional HF realizations. The performance of these methods are assessed on an irradiated particle laden turbulent flow (PSAAP II solar energy receiver). This investigation was funded by the United States Department of Energy's (DoE) National Nuclear Security Administration (NNSA) under the Predicitive Science Academic Alliance Program (PSAAP) II at Stanford University.
Scalable multi-objective control for large scale water resources systems under uncertainty
Giuliani, Matteo; Quinn, Julianne; Herman, Jonathan; Castelletti, Andrea; Reed, Patrick
2016-04-01
The use of mathematical models to support the optimal management of environmental systems is rapidly expanding over the last years due to advances in scientific knowledge of the natural processes, efficiency of the optimization techniques, and availability of computational resources. However, undergoing changes in climate and society introduce additional challenges for controlling these systems, ultimately motivating the emergence of complex models to explore key causal relationships and dependencies on uncontrolled sources of variability. In this work, we contribute a novel implementation of the evolutionary multi-objective direct policy search (EMODPS) method for controlling environmental systems under uncertainty. The proposed approach combines direct policy search (DPS) with hierarchical parallelization of multi-objective evolutionary algorithms (MOEAs) and offers a threefold advantage: the DPS simulation-based optimization can be combined with any simulation model and does not add any constraint on modeled information, allowing the use of exogenous information in conditioning the decisions. Moreover, the combination of DPS and MOEAs prompts the generation or Pareto approximate set of solutions for up to 10 objectives, thus overcoming the decision biases produced by cognitive myopia, where narrow or restrictive definitions of optimality strongly limit the discovery of decision relevant alternatives. Finally, the use of large-scale MOEAs parallelization improves the ability of the designed solutions in handling the uncertainty due to severe natural variability. The proposed approach is demonstrated on a challenging water resources management problem represented by the optimal control of a network of four multipurpose water reservoirs in the Red River basin (Vietnam). As part of the medium-long term energy and food security national strategy, four large reservoirs have been constructed on the Red River tributaries, which are mainly operated for hydropower
Familiality of co-existing ADHD and tic disorders: evidence from a large sibling study
Directory of Open Access Journals (Sweden)
Veit Roessner
2016-07-01
Full Text Available AbstractBackground: The association of attention-deficit/hyperactivity disorder (ADHD and tic disorder (TD is frequent and clinically important. Very few and inconclusive attempts have been made to clarify if and how the combination of ADHD+TD runs in families. Aim: To determine the first time in a large-scale ADHD sample whether ADHD+TD increases the risk of ADHD+TD in siblings and, also the first time, if this is independent of their psychopathological vulnerability in general. Methods: The study is based on the International Multicenter ADHD Genetics (IMAGE study. The present sub-sample of 2815 individuals included ADHD-index patients with co-existing TD (ADHD+TD, n=262 and without TD (ADHD-TD, n=947 as well as their 1606 full siblings (n=358 of the ADHD+TD index patients and n=1248 of the ADHD-TD index patients. We assessed psychopathological symptoms in index patients and siblings by using the strength and difficulties questionnaire (SDQ and the parent and teacher Conners’ long version Rating Scales (CRS. For disorder classification the Parental Account of Childhood Symptoms (PACS-Interview was applied in n = 271 children. Odds ratio with the GENMOD procedure (PROCGENMOD was used to test if the risk for ADHD, TD and ADHD+TD in siblings was associated with the related index patients’ diagnoses. In order to get an estimate for specificity we compared the four groups for general psychopathological symptoms.Results: Co-existing ADHD+TD in index patients increased the risk of both comorbid ADHD+TD and TD in the siblings of these index patients. These effects did not extend to general psychopathology. Interpretation: Co-existence of ADHD+TD may segregate in families. The same holds true for TD (without ADHD. Hence, the segregation of TD (included in both groups seems to be the determining factor, independent of further behavioral problems. This close relationship between ADHD and TD supports the clinical approach to carefully assess ADHD in
Uncertainty of SWAT model at different DEM resolutions in a large mountainous watershed.
Zhang, Peipei; Liu, Ruimin; Bao, Yimeng; Wang, Jiawei; Yu, Wenwen; Shen, Zhenyao
2014-04-15
The objective of this study was to enhance understanding of the sensitivity of the SWAT model to the resolutions of Digital Elevation Models (DEMs) based on the analysis of multiple evaluation indicators. The Xiangxi River, a large tributary of Three Gorges Reservoir in China, was selected as the study area. A range of 17 DEM spatial resolutions, from 30 to 1000 m, was examined, and the annual and monthly model outputs based on each resolution were compared. The following results were obtained: (i) sediment yield was greatly affected by DEM resolution; (ii) the prediction of dissolved oxygen load was significantly affected by DEM resolutions coarser than 500 m; (iii) Total Nitrogen (TN) load was not greatly affected by the DEM resolution; (iv) Nitrate Nitrogen (NO₃-N) and Total Phosphorus (TP) loads were slightly affected by the DEM resolution; and (v) flow and Ammonia Nitrogen (NH₄-N) load were essentially unaffected by the DEM resolution. The flow and dissolved oxygen load decreased more significantly in the dry season than in the wet and normal seasons. Excluding flow and dissolved oxygen, the uncertainties of the other Hydrology/Non-point Source (H/NPS) pollution indicators were greater in the wet season than in the dry and normal seasons. Considering the temporal distribution uncertainties, the optimal DEM resolutions for flow was 30-200 m, for sediment and TP was 30-100 m, for dissolved oxygen and NO₃-N was 30-300 m, for NH₄-N was 30 to 70 m and for TN was 30-150 m. Copyright © 2014 Elsevier Ltd. All rights reserved.
Mannina, Giorgio; Cosenza, Alida; Viviani, Gaspare
In the last few years, the use of mathematical models in WasteWater Treatment Plant (WWTP) processes has become a common way to predict WWTP behaviour. However, mathematical models generally demand advanced input for their implementation that must be evaluated by an extensive data-gathering campaign, which cannot always be carried out. This fact, together with the intrinsic complexity of the model structure, leads to model results that may be very uncertain. Quantification of the uncertainty is imperative. However, despite the importance of uncertainty quantification, only few studies have been carried out in the wastewater treatment field, and those studies only included a few of the sources of model uncertainty. Seeking the development of the area, the paper presents the uncertainty assessment of a mathematical model simulating biological nitrogen and phosphorus removal. The uncertainty assessment was conducted according to the Generalised Likelihood Uncertainty Estimation (GLUE) methodology that has been scarcely applied in wastewater field. The model was based on activated-sludge models 1 (ASM) and 2 (ASM2). Different approaches can be used for uncertainty analysis. The GLUE methodology requires a large number of Monte Carlo simulations in which a random sampling of individual parameters drawn from probability distributions is used to determine a set of parameter values. Using this approach, model reliability was evaluated based on its capacity to globally limit the uncertainty. The method was applied to a large full-scale WWTP for which quantity and quality data was gathered. The analysis enabled to gain useful insights for WWTP modelling identifying the crucial aspects where higher uncertainty rely and where therefore, more efforts should be provided in terms of both data gathering and modelling practises.
International Nuclear Information System (INIS)
Townsend, Lawrence W.; Zapp, E. Neal
1999-01-01
The true uncertainties in estimates of body organ absorbed dose and dose equivalent, from exposures of interplanetary astronauts to large solar particle events (SPEs), are essentially unknown. Variations in models used to parameterize SPE proton spectra for input into space radiation transport and shielding computer codes can result in uncertainty about the reliability of dose predictions for these events. Also, different radiation transport codes and their input databases can yield significant differences in dose predictions, even for the same input spectra. Different results may also be obtained for the same input spectra and transport codes if different spacecraft and body self-shielding distributions are assumed. Heretofore there have been no systematic investigations of the variations in dose and dose equivalent resulting from these assumptions and models. In this work we present a study of the variability in predictions of organ dose and dose equivalent arising from the use of different parameters to represent the same incident SPE proton data and from the use of equivalent sphere approximations to represent human body geometry. The study uses the BRYNTRN space radiation transport code to calculate dose and dose equivalent for the skin, ocular lens and bone marrow using the October 1989 SPE as a model event. Comparisons of organ dose and dose equivalent, obtained with a realistic human geometry model and with the oft-used equivalent sphere approximation, are also made. It is demonstrated that variations of 30-40% in organ dose and dose equivalent are obtained for slight variations in spectral fitting parameters obtained when various data points are included or excluded from the fitting procedure. It is further demonstrated that extrapolating spectra from low energy (≤30 MeV) proton fluence measurements, rather than using fluence data extending out to 100 MeV results in dose and dose equivalent predictions that are underestimated by factors as large as 2
Large uncertainty in carbon uptake potential of land-based climate-change mitigation efforts.
Krause, Andreas; Pugh, Thomas A M; Bayer, Anita D; Li, Wei; Leung, Felix; Bondeau, Alberte; Doelman, Jonathan C; Humpenöder, Florian; Anthoni, Peter; Bodirsky, Benjamin L; Ciais, Philippe; Müller, Christoph; Murray-Tortarolo, Guillermo; Olin, Stefan; Popp, Alexander; Sitch, Stephen; Stehfest, Elke; Arneth, Almut
2018-07-01
Most climate mitigation scenarios involve negative emissions, especially those that aim to limit global temperature increase to 2°C or less. However, the carbon uptake potential in land-based climate change mitigation efforts is highly uncertain. Here, we address this uncertainty by using two land-based mitigation scenarios from two land-use models (IMAGE and MAgPIE) as input to four dynamic global vegetation models (DGVMs; LPJ-GUESS, ORCHIDEE, JULES, LPJmL). Each of the four combinations of land-use models and mitigation scenarios aimed for a cumulative carbon uptake of ~130 GtC by the end of the century, achieved either via the cultivation of bioenergy crops combined with carbon capture and storage (BECCS) or avoided deforestation and afforestation (ADAFF). Results suggest large uncertainty in simulated future land demand and carbon uptake rates, depending on the assumptions related to land use and land management in the models. Total cumulative carbon uptake in the DGVMs is highly variable across mitigation scenarios, ranging between 19 and 130 GtC by year 2099. Only one out of the 16 combinations of mitigation scenarios and DGVMs achieves an equivalent or higher carbon uptake than achieved in the land-use models. The large differences in carbon uptake between the DGVMs and their discrepancy against the carbon uptake in IMAGE and MAgPIE are mainly due to different model assumptions regarding bioenergy crop yields and due to the simulation of soil carbon response to land-use change. Differences between land-use models and DGVMs regarding forest biomass and the rate of forest regrowth also have an impact, albeit smaller, on the results. Given the low confidence in simulated carbon uptake for a given land-based mitigation scenario, and that negative emissions simulated by the DGVMs are typically lower than assumed in scenarios consistent with the 2°C target, relying on negative emissions to mitigate climate change is a highly uncertain strategy. © 2018 John
Dexter, Franklin; Epstein, Richard H; Thenuwara, Kokila; Lubarsky, David A
2017-11-22
Multiple previous studies have shown that having a large diversity of procedures has a substantial impact on quality management of hospital surgical suites. At hospitals with substantial diversity, unless sophisticated statistical methods suitable for rare events are used, anesthesiologists working in surgical suites will have inaccurate predictions of surgical blood usage, case durations, cost accounting and price transparency, times remaining in late running cases, and use of intraoperative equipment. What is unknown is whether large diversity is a feature of only a few very unique set of hospitals nationwide (eg, the largest hospitals in each state or province). The 2013 United States Nationwide Readmissions Database was used to study heterogeneity among 1981 hospitals in their diversities of physiologically complex surgical procedures (ie, the procedure codes). The diversity of surgical procedures performed at each hospital was quantified using a summary measure, the number of different physiologically complex surgical procedures commonly performed at the hospital (ie, 1/Herfindahl). A total of 53.9% of all hospitals commonly performed 3-fold larger diversity (ie, >30 commonly performed physiologically complex procedures). Larger hospitals had greater diversity than the small- and medium-sized hospitals (P 30 procedures (lower 99% CL, 71.9% of hospitals). However, there was considerable variability among the large teaching hospitals in their diversity (interquartile range of the numbers of commonly performed physiologically complex procedures = 19.3; lower 99% CL, 12.8 procedures). The diversity of procedures represents a substantive differentiator among hospitals. Thus, the usefulness of statistical methods for operating room management should be expected to be heterogeneous among hospitals. Our results also show that "large teaching hospital" alone is an insufficient description for accurate prediction of the extent to which a hospital sustains the
Large-scale integration of wind power into the existing Chinese energy system
DEFF Research Database (Denmark)
Liu, Wen; Lund, Henrik; Mathiesen, Brian Vad
2011-01-01
stability, the maximum feasible wind power penetration in the existing Chinese energy system is approximately 26% from both technical and economic points of view. A fuel efficiency decrease occurred when increasing wind power penetration in the system, due to its rigid power supply structure and the task......This paper presents the ability of the existing Chinese energy system to integrate wind power and explores how the Chinese energy system needs to prepare itself in order to integrate more fluctuating renewable energy in the future. With this purpose in mind, a model of the Chinese energy system has...... been constructed by using EnergyPLAN based on the year 2007, which has then been used for investigating three issues. Firstly, the accuracy of the model itself has been examined and then the maximum feasible wind power penetration in the existing energy system has been identified. Finally, barriers...
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.
Transportation of Large Wind Components: A Review of Existing Geospatial Data
Energy Technology Data Exchange (ETDEWEB)
Mooney, Meghan [National Renewable Energy Lab. (NREL), Golden, CO (United States); Maclaurin, Galen [National Renewable Energy Lab. (NREL), Golden, CO (United States)
2016-09-01
This report features the geospatial data component of a larger project evaluating logistical and infrastructure requirements for transporting oversized and overweight (OSOW) wind components. The goal of the larger project was to assess the status and opportunities for improving the infrastructure and regulatory practices necessary to transport wind turbine towers, blades, and nacelles from current and potential manufacturing facilities to end-use markets. The purpose of this report is to summarize existing geospatial data on wind component transportation infrastructure and to provide a data gap analysis, identifying areas for further analysis and data collection.
Large-scale straw supplies to existing coal-fired power stations
International Nuclear Information System (INIS)
Gylling, M.; Parsby, M.; Thellesen, H.Z.; Keller, P.
1992-08-01
It is considered that large-scale supply of straw to power stations and decentral cogeneration plants could open up new economical systems and methods of organization of straw supply in Denmark. This thesis is elucidated and involved constraints are pointed out. The aim is to describe to what extent large-scale straw supply is interesting with regard to monetary savings and available resources. Analyses of models, systems and techniques described in a foregoing project are carried out. It is reckoned that the annual total amount of surplus straw in Denmark is 3.6 million tons. At present, use of straw which is not agricultural is limited to district heating plants with an annual consumption of 2-12 thousand tons. A prerequisite for a significant increase in the use of straw is an annual consumption by power and cogeneration plants of more than 100.000 tons. All aspects of straw management are examined in detail, also in relation to two actual Danish coal-fired plants. The reliability of straw supply is considered. It is concluded that very significant resources of straw are available in Denmark but there remain a number of constraints. Price competitiveness must be considered in relation to other fuels. It is suggested that the use of corn harvests, with whole stems attached (handled as large bales or in the same way as sliced straw alone) as fuel, would result in significant monetary savings in transport and storage especially. An equal status for whole-harvested corn with other forms of biomass fuels, with following changes in taxes and subsidies could possibly reduce constraints on large scale straw fuel supply. (AB) (13 refs.)
The Effects of Uncertainty in Speed-Flow Curve Parameters on a Large-Scale Model
DEFF Research Database (Denmark)
Manzo, Stefano; Nielsen, Otto Anker; Prato, Carlo Giacomo
2014-01-01
-delay functions express travel time as a function of traffic flows and the theoretical capacity of the modeled facility. The U.S. Bureau of Public Roads (BPR) formula is one of the most extensively applied volume delay functions in practice. This study investigated uncertainty in the BPR parameters. Initially......-stage Danish national transport model. The results clearly highlight the importance to modeling purposes of taking into account BPR formula parameter uncertainty, expressed as a distribution of values rather than assumed point values. Indeed, the model output demonstrates a noticeable sensitivity to parameter...
Calibration and Forward Uncertainty Propagation for Large-eddy Simulations of Engineering Flows
Energy Technology Data Exchange (ETDEWEB)
Templeton, Jeremy Alan [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Blaylock, Myra L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Domino, Stefan P. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hewson, John C. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Kumar, Pritvi Raj [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Ling, Julia [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Najm, Habib N. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Ruiz, Anthony [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Safta, Cosmin [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Sargsyan, Khachik [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Stewart, Alessia [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Wagner, Gregory [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2015-09-01
The objective of this work is to investigate the efficacy of using calibration strategies from Uncertainty Quantification (UQ) to determine model coefficients for LES. As the target methods are for engineering LES, uncertainty from numerical aspects of the model must also be quantified. 15 The ultimate goal of this research thread is to generate a cost versus accuracy curve for LES such that the cost could be minimized given an accuracy prescribed by an engineering need. Realization of this goal would enable LES to serve as a predictive simulation tool within the engineering design process.
DEFF Research Database (Denmark)
Zhukovsky, Sergei; Andryieuski, Andrei; Lavrinenko, Andrei
2014-01-01
We theoretically investigate general existence conditions for broadband bulk large-wavevector (high-k) propagating waves (such as volume plasmon polaritons in hyperbolic metamaterials) in arbitrary subwavelength periodic multilayers structures. Treating the elementary excitation in the unit cell...... of the structure as a generalized resonance pole of reflection coefficient and using Bloch's theorem, we derive analytical expressions for the band of large-wavevector propagating solutions. We apply our formalism to determine the high-k band existence in two important cases: the well-known metal-dielectric...
The Kembs project: environmental integration of a large existing hydropower scheme
International Nuclear Information System (INIS)
Garnier, Alain; Barillier, Agnes
2015-01-01
The environment was a major issue for the Kembs re-licensing process on the upper Rhine River. Since 1932, Kembs dam derives water from the Rhine River to the 'Grand Canal d'Alsace' (GCA) which is equipped with four hydropower plants (max. diverted flow: 1400 m 3 /s, 630 MW, 3760 GWh/y). The Old Rhine River downstream of the dam is 50 km long and has been strongly affected by works (dikes) since the 19. century for flood protection and navigation, and then by the construction of the dam. Successive engineering works induced morphological simplification and stabilization of the channel pattern from a formerly braided form to a single incised channel, generating ecological alterations. As the Kembs hydroelectric scheme concerns three countries (France, Germany and Switzerland) with various regulations and views on how to manage with environment, EDF undertook an integrated environmental approach instead of a strict 'impact/mitigation' balance that took 10 years to develop. Therefore, the project simultaneously acts on complementary compartments of the aquatic, riparian and terrestrial environment, to benefit from the synergies that exist between them; a new power plant (8,5 MW, 28 GWh/y) is built to limit the energetic losses and to ensure various functions thereby increasing the overall environmental gain. (authors)
Energy Technology Data Exchange (ETDEWEB)
Arkoma, Asko, E-mail: asko.arkoma@vtt.fi; Ikonen, Timo
2016-08-15
Highlights: • A sensitivity analysis using the data from EPR LB-LOCA simulations is done. • A procedure to analyze such complex data is outlined. • Both visual and quantitative methods are used. • Input factors related to core design are identified as most significant. - Abstract: In this paper, a sensitivity analysis for the data originating from a large break loss-of-coolant accident (LB-LOCA) analysis of an EPR-type nuclear power plant is presented. In the preceding LOCA analysis, the number of failing fuel rods in the accident was established (Arkoma et al., 2015). However, the underlying causes for rod failures were not addressed. It is essential to bring out which input parameters and boundary conditions have significance to the outcome of the analysis, i.e. the ballooning and burst of the rods. Due to complexity of the existing data, the first part of the analysis consists of defining the relevant input parameters for the sensitivity analysis. Then, selected sensitivity measures are calculated between the chosen input and output parameters. The ultimate goal is to develop a systematic procedure for the sensitivity analysis of statistical LOCA simulation that takes into account the various sources of uncertainties in the calculation chain. In the current analysis, the most relevant parameters with respect to the cladding integrity are the decay heat power during the transient, the thermal hydraulic conditions in the rod’s location in reactor, and the steady-state irradiation history of the rod. Meanwhile, the tolerances in fuel manufacturing parameters were found to have negligible effect on cladding deformation.
2015-12-02
of completely new nonlinear Malliavin calculus . This type of calculus is important for the analysis and simulation of stationary and/or “causal...been limited by the fact that it requires the solution of an optimization problem with noisy gradients . When using deterministic optimization schemes...under uncertainty. We tested new developments on nonlinear Malliavin calculus , combining reduced basis methods with ANOVA, model validation, on
International Nuclear Information System (INIS)
Young, M.Y.; Bajorek, S.M.; Nissley, M.E.
1998-01-01
In the late 1980s, after completion of an extensive research program, the United States Nuclear Regulatory Commission (USNRC) amended its regulations (10CFR50.46) to allow the use of realistic physical models to analyze the loss of coolant accident (LOCA) in a light water reactors. Prior to this time, the evaluation of this accident was subject to a prescriptive set of rules (appendix K of the regulations) requiring conservative models and assumptions to be applied simultaneously, leading to very pessimistic estimates of the impact of this accident on the reactor core. The rule change therefore promised to provide significant benefits to owners of power reactors, allowing them to increase output. In response to the rule change, a method called code scaling, applicability and uncertainty (CSAU) was developed to apply realistic methods, while properly taking into account data uncertainty, uncertainty in physical modeling and plant variability. The method was claimed to be structured, traceable, and practical, but was met with some criticism when first demonstrated. In 1996, the USNRC approved a methodology, based on CSAU, developed by a group led by Westinghouse. The lessons learned in this application of CSAU will be summarized. Some of the issues raised concerning the validity and completeness of the CSAU methodology will also be discussed. (orig.)
Modeling and solving a large-scale generation expansion planning problem under uncertainty
Energy Technology Data Exchange (ETDEWEB)
Jin, Shan; Ryan, Sarah M. [Iowa State University, Department of Industrial and Manufacturing Systems Engineering, Ames (United States); Watson, Jean-Paul [Sandia National Laboratories, Discrete Math and Complex Systems Department, Albuquerque (United States); Woodruff, David L. [University of California Davis, Graduate School of Management, Davis (United States)
2011-11-15
We formulate a generation expansion planning problem to determine the type and quantity of power plants to be constructed over each year of an extended planning horizon, considering uncertainty regarding future demand and fuel prices. Our model is expressed as a two-stage stochastic mixed-integer program, which we use to compute solutions independently minimizing the expected cost and the Conditional Value-at-Risk; i.e., the risk of significantly larger-than-expected operational costs. We introduce stochastic process models to capture demand and fuel price uncertainty, which are in turn used to generate trees that accurately represent the uncertainty space. Using a realistic problem instance based on the Midwest US, we explore two fundamental, unexplored issues that arise when solving any stochastic generation expansion model. First, we introduce and discuss the use of an algorithm for computing confidence intervals on obtained solution costs, to account for the fact that a finite sample of scenarios was used to obtain a particular solution. Second, we analyze the nature of solutions obtained under different parameterizations of this method, to assess whether the recommended solutions themselves are invariant to changes in costs. The issues are critical for decision makers who seek truly robust recommendations for generation expansion planning. (orig.)
Uncertainty analysis of multiple canister repository model by large-scale calculation
International Nuclear Information System (INIS)
Tsujimoto, K.; Okuda, H.; Ahn, J.
2007-01-01
A prototype uncertainty analysis has been made by using the multiple-canister radionuclide transport code, VR, for performance assessment for the high-level radioactive waste repository. Fractures in the host rock determine main conduit of groundwater, and thus significantly affect the magnitude of radionuclide release rates from the repository. In this study, the probability distribution function (PDF) for the number of connected canisters in the same fracture cluster that bears water flow has been determined in a Monte-Carlo fashion by running the FFDF code with assumed PDFs for fracture geometry. The uncertainty for the release rate of 237 Np from a hypothetical repository containing 100 canisters has been quantitatively evaluated by using the VR code with PDFs for the number of connected canisters and the near field rock porosity. The calculation results show that the mass transport is greatly affected by (1) the magnitude of the radionuclide source determined by the number of connected canisters by the fracture cluster, and (2) the canister concentration effect in the same fracture network. The results also show the two conflicting tendencies that the more fractures in the repository model space, the greater average value but the smaller uncertainty of the peak fractional release rate is. To perform a vast amount of calculation, we have utilized the Earth Simulator and SR8000. The multi-level hybrid programming method is applied in the optimization to exploit high performance of the Earth Simulator. The Latin Hypercube Sampling has been utilized to reduce the number of samplings in Monte-Carlo calculation. (authors)
Tinti, Stefano; Armigliato, Alberto; Pagnoni, Gianluca; Zaniboni, Filippo
2013-04-01
Geoscientists deal often with hazardous processes like earthquakes, volcanic eruptions, tsunamis, hurricanes, etc., and their research is aimed not only to a better understanding of the physical processes, but also to provide assessment of the space and temporal evolution of a given individual event (i.e. to provide short-term prediction) and of the expected evolution of a group of events (i.e. to provide statistical estimates referred to a given return period, and a given geographical area). One of the main issues of any scientific method is how to cope with measurement errors, a topic which in case of forecast of ongoing or of future events translates into how to deal with forecast uncertainties. In general, the more data are available and processed to make a prediction, the more accurate the prediction is expected to be if the scientific approach is sound, and the smaller the associated uncertainties are. However, there are several important cases where assessment is to be made with insufficient data or insufficient time for processing, which leads to large uncertainties. Two examples can be given taken from tsunami science, since tsunamis are rare events that may have destructive power and very large impact. One example is the case of warning for a tsunami generated by a near-coast earthquake, which is an issue at the focus of the European funded project NearToWarn. Warning has to be launched before tsunami hits the coast, that is in a few minutes after its generation. This may imply that data collected in such a short time are not yet enough for an accurate evaluation, also because the implemented monitoring system (if any) could be inadequate (f.i. one reason of inadequacy could be that implementing a dense instrumental network could be judged too expensive for rare events) The second case is the long term prevention from tsunami strikes. Tsunami infrequency may imply that the historical record for a given piece of coast is too short to capture a statistical
International Nuclear Information System (INIS)
Baron, Jorge H.; Nunez Mac Leod, J.E.
2000-01-01
The present paper deals with the utilization of advanced sampling statistical methods to perform uncertainty and sensitivity analysis on numerical models. Such models may represent physical phenomena, logical structures (such as boolean expressions) or other systems, and various of their intrinsic parameters and/or input variables are usually treated as random variables simultaneously. In the present paper a simple method to scale-up Latin Hypercube Sampling (LHS) samples is presented, starting with a small sample and duplicating its size at each step, making it possible to use the already run numerical model results with the smaller sample. The method does not distort the statistical properties of the random variables and does not add any bias to the samples. The results is a significant reduction in numerical models running time can be achieved (by re-using the previously run samples), keeping all the advantages of LHS, until an acceptable representation level is achieved in the output variables. (author)
Jaxa-Rozen, M.; Rostampour, V.; Kwakkel, J. H.; Bloemendal, M.
2017-12-01
Seasonal Aquifer Thermal Energy Storage (ATES) technology can help reduce the demand of energy for heating and cooling in buildings, and has become a popular option for larger buildings in northern Europe. However, the larger-scale deployment of this technology has evidenced some issues of concern for policymakers; in particular, recent research shows that operational uncertainties contribute to inefficient outcomes under current planning methods for ATES. For instance, systems in the Netherlands typically use less than half of their permitted pumping volume on an annual basis. This overcapacity gives users more flexibility to operate their systems in response to the uncertainties which drive building energy demand; these include short-term operational factors such as weather and occupancy, and longer-term, deeply uncertain factors such as changes in climate and aquifer conditions over the lifespan of the buildings. However, as allocated subsurface volume remains unused, this situation limits the adoption of the technology in dense areas. Previous work using coupled agent-based/geohydrological simulation has shown that the cooperative operation of neighbouring ATES systems can support more efficient spatial planning, by dynamically managing thermal interactions in response to uncertain operating conditions. An idealized case study with centralized ATES control thus showed significant improvements in the energy savings which could obtained per unit of allocated subsurface volume, without degrading the recovery performance of systems. This work will extend this cooperative approach for a realistic case study of ATES planning in the city of Utrecht, in the Netherlands. This case was previously simulated under different scenarios for individual ATES operation. The poster will compare these results with a cooperative case under which neighbouring systems can coordinate their operation to manage interactions. Furthermore, a cooperative game-theoretical framework will be
Managing Risk and Uncertainty in Large-Scale University Research Projects
Moore, Sharlissa; Shangraw, R. F., Jr.
2011-01-01
Both publicly and privately funded research projects managed by universities are growing in size and scope. Complex, large-scale projects (over $50 million) pose new management challenges and risks for universities. This paper explores the relationship between project success and a variety of factors in large-scale university projects. First, we…
Directory of Open Access Journals (Sweden)
Pescari S.
2015-05-01
Full Text Available One of the targets of EU Directives on the energy performance of buildings is to reduce the energy consumption of the existing buildings by finding efficient solutions for thermal rehabilitation. In order to find the adequate solutions, the first step is to establish the current state of the buildings and to determine their actual energy consumption. The current paper aims to present the energy demands of the existing buildings with bearing structure of large precast concrete panels in the city of Timisoara. Timisoara is one of the most important cities in the west side of Romania, being on the third place in terms of size and economic development. The Census of Population and Housing of 2011 states that Timisoara has about 127841 private dwellings and 60 percent of them are collective buildings. Energy demand values of the existing buildings with bearing structure of large precast concrete panels in Timisoara, in their current condition, are higher than the accepted values provided in the Romanian normative, C107. The difference between these two values can reach up to 300 percent.
International Nuclear Information System (INIS)
Gabadadze, Gregory; Shifman, Mikhail
2000-01-01
A number of arguments exists that the ''minimal'' Bogomol'nyi-Prasad-Sommerfeld (BPS) wall width in large-N supersymmetric gluodynamics vanishes as 1/N. There is a certain tension between this assertion and the fact that the mesons coupled to λλ have masses O(N 0 ). To reconcile these facts we argue that there should exist additional solitonlike states with masses scaling as N. The BPS walls must be ''made'' predominantly of these heavy states which are coupled to λλ stronger than the conventional mesons. The tension of the BPS wall junction scales as N 2 , which serves as an additional argument in favor of the 1/N scaling of the wall width. The heavy states can be thought of as solitons of the corresponding closed string theory. They are related to certain fivebranes in the M-theory construction. We study the issue of the wall width in toy models which capture some features of supersymmetric gluodynamics. We speculate that the special hadrons with mass scaling as N should also exist in the large-N limit of nonsupersymmetric gluodynamics. (c) 2000 The American Physical Society
International Nuclear Information System (INIS)
Abdul-Razzak, A.; Zhang, J.; Sills, H.E.; Flatt, L.; Jenkins, D.; Wallace, D.J.; Popov, N.
2002-01-01
The paper describes briefly a best estimate plus uncertainty analysis (BE+UA) methodology and presents its proto-typing application to the power pulse phase of a limiting large Loss-of-Coolant Accident (LOCA) for a CANDU 6 reactor fuelled with CANFLEX R fuel. The methodology is consistent with and builds on world practice. The analysis is divided into two phases to focus on the dominant parameters for each phase and to allow for the consideration of all identified highly ranked parameters in the statistical analysis and response surface fits for margin parameters. The objective of this analysis is to quantify improvements in predicted safety margins under best estimate conditions. (authors)
Energy Technology Data Exchange (ETDEWEB)
Awad Nuñez, S.; Camarero Orive, A.; Romero Sanchez-Brunete, M.; Camarero Orive, A.; Gonzalez Cancelas, N.
2016-07-01
This research discusses the challenges involved in the treatment of uncertainties in the existence of free berths during the arrival of cruise ships at seaports. Pursuing this goal, a three-step methodology is adopted: 1) Identifying risk sources and critical risk variables and how they are related; 2) Fitting the Probability Distribution Functions that best represent the behaviour of each critical risk variable; and 3) Simulating the probability of a ship having to wait because there are no free berths using a technique that combines statistical concepts (random sampling) with the ability of computers to generate pseudo-random numbers and automate estimations of the values of the set of critical risk variables. The innovative use of risk analysis techniques in this field allows the establishment of policies to improve the planning and management of port infrastructure, for example, deciding when it is necessary to work to increase the number of berths. As a case of study, we applied this methodology to study whether the enlargement of the wharf in the port of Cadiz (Spain) is necessary right now considering the number of cruise ships that have arrived at the port in the past three years, their date and hour of arrival, their length and draught, the duration of their stay in port and their waiting time before being able to enter the port. This action would require moving logistics activities to a new terminal, but would bring to the city the opportunity to rethink the seafront, introducing new cruiser links with the city centre and developing a better seaport-city integration. (Author)
Directory of Open Access Journals (Sweden)
D. Bachmann
2004-01-01
Full Text Available Using a new 3-D physical modelling technique we investigated the initiation and evolution of large scale landslides in presence of pre-existing large scale fractures and taking into account the slope material weakening due to the alteration/weathering. The modelling technique is based on the specially developed properly scaled analogue materials, as well as on the original vertical accelerator device enabling increases in the 'gravity acceleration' up to a factor 50. The weathering primarily affects the uppermost layers through the water circulation. We simulated the effect of this process by making models of two parts. The shallower one represents the zone subject to homogeneous weathering and is made of low strength material of compressive strength σl. The deeper (core part of the model is stronger and simulates intact rocks. Deformation of such a model subjected to the gravity force occurred only in its upper (low strength layer. In another set of experiments, low strength (σw narrow planar zones sub-parallel to the slope surface (σwl were introduced into the model's superficial low strength layer to simulate localized highly weathered zones. In this configuration landslides were initiated much easier (at lower 'gravity force', were shallower and had smaller horizontal size largely defined by the weak zone size. Pre-existing fractures were introduced into the model by cutting it along a given plan. They have proved to be of small influence on the slope stability, except when they were associated to highly weathered zones. In this latter case the fractures laterally limited the slides. Deep seated rockslides initiation is thus directly defined by the mechanical structure of the hillslope's uppermost levels and especially by the presence of the weak zones due to the weathering. The large scale fractures play a more passive role and can only influence the shape and the volume of the sliding units.
Energy Technology Data Exchange (ETDEWEB)
Alonso, Juan J. [Stanford University; Iaccarino, Gianluca [Stanford University
2013-08-25
The following is the final report covering the entire period of this aforementioned grant, June 1, 2011 - May 31, 2013 for the portion of the effort corresponding to Stanford University (SU). SU has partnered with Sandia National Laboratories (PI: Mike S. Eldred) and Purdue University (PI: Dongbin Xiu) to complete this research project and this final report includes those contributions made by the members of the team at Stanford. Dr. Eldred is continuing his contributions to this project under a no-cost extension and his contributions to the overall effort will be detailed at a later time (once his effort has concluded) on a separate project submitted by Sandia National Laboratories. At Stanford, the team is made up of Profs. Alonso, Iaccarino, and Duraisamy, post-doctoral researcher Vinod Lakshminarayan, and graduate student Santiago Padron. At Sandia National Laboratories, the team includes Michael Eldred, Matt Barone, John Jakeman, and Stefan Domino, and at Purdue University, we have Prof. Dongbin Xiu as our main collaborator. The overall objective of this project was to develop a novel, comprehensive methodology for uncertainty quantification by combining stochastic expansions (nonintrusive polynomial chaos and stochastic collocation), the adjoint approach, and fusion with experimental data to account for aleatory and epistemic uncertainties from random variable, random field, and model form sources. The expected outcomes of this activity were detailed in the proposal and are repeated here to set the stage for the results that we have generated during the time period of execution of this project: 1. The rigorous determination of an error budget comprising numerical errors in physical space and statistical errors in stochastic space and its use for optimal allocation of resources; 2. A considerable increase in efficiency when performing uncertainty quantification with a large number of uncertain variables in complex non-linear multi-physics problems; 3. A
Xiao, Mengli; Zhang, Yongbo; Fu, Huimin; Wang, Zhihua
2018-05-01
High-precision navigation algorithm is essential for the future Mars pinpoint landing mission. The unknown inputs caused by large uncertainties of atmospheric density and aerodynamic coefficients as well as unknown measurement biases may cause large estimation errors of conventional Kalman filters. This paper proposes a derivative-free version of nonlinear unbiased minimum variance filter for Mars entry navigation. This filter has been designed to solve this problem by estimating the state and unknown measurement biases simultaneously with derivative-free character, leading to a high-precision algorithm for the Mars entry navigation. IMU/radio beacons integrated navigation is introduced in the simulation, and the result shows that with or without radio blackout, our proposed filter could achieve an accurate state estimation, much better than the conventional unscented Kalman filter, showing the ability of high-precision Mars entry navigation algorithm. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.
Flemming, Burghard W.; Kudrass, Hermann-Rudolf
2018-02-01
The existence of a continuously flowing Mozambique Current, i.e. a western geostrophic boundary current flowing southwards along the shelf break of Mozambique, was until recently accepted by oceanographers studying ocean circulation in the south-western Indian Ocean. This concept was then cast into doubt based on long-term current measurements obtained from current-meter moorings deployed across the northern Mozambique Channel, which suggested that southward flow through the Mozambique Channel took place in the form of successive, southward migrating and counter-clockwise rotating eddies. Indeed, numerical modelling found that, if at all, strong currents on the outer shelf occurred for not more than 9 days per year. In the present study, the negation of the existence of a Mozambique Current is challenged by the discovery of a large (50 km long, 12 km wide) subaqueous dune field (with up to 10 m high dunes) on the outer shelf east of the modern Zambezi River delta at water depths between 50 and 100 m. Being interpreted as representing the current-modified, early Holocene Zambezi palaeo-delta, the dune field would have migrated southwards by at least 50 km from its former location since sea level recovered to its present-day position some 7 ka ago and after the former delta had been remoulded into a migrating dune field. Because a large dune field composed of actively migrating bedforms cannot be generated and maintained by currents restricted to a period of only 9 days per year, the validity of those earlier modelling results is questioned for the western margin of the flow field. Indeed, satellite images extracted from the Perpetual Ocean display of NASA, which show monthly time-integrated surface currents in the Mozambique Channel for the 5 month period from June-October 2006, support the proposition that strong flow on the outer Mozambican shelf occurs much more frequently than postulated by those modelling results. This is consistent with more recent modelling
Uncertainty, joint uncertainty, and the quantum uncertainty principle
International Nuclear Information System (INIS)
Narasimhachar, Varun; Poostindouz, Alireza; Gour, Gilad
2016-01-01
Historically, the element of uncertainty in quantum mechanics has been expressed through mathematical identities called uncertainty relations, a great many of which continue to be discovered. These relations use diverse measures to quantify uncertainty (and joint uncertainty). In this paper we use operational information-theoretic principles to identify the common essence of all such measures, thereby defining measure-independent notions of uncertainty and joint uncertainty. We find that most existing entropic uncertainty relations use measures of joint uncertainty that yield themselves to a small class of operational interpretations. Our notion relaxes this restriction, revealing previously unexplored joint uncertainty measures. To illustrate the utility of our formalism, we derive an uncertainty relation based on one such new measure. We also use our formalism to gain insight into the conditions under which measure-independent uncertainty relations can be found. (paper)
International Nuclear Information System (INIS)
Perkó, Zoltán; Lathouwers, Danny; Kloosterman, Jan Leen; Hagen, Tim van der
2014-01-01
Highlights: • Grid and basis adaptive Polynomial Chaos techniques are presented for S and U analysis. • Dimensionality reduction and incremental polynomial order reduce computational costs. • An unprotected loss of flow transient is investigated in a Gas Cooled Fast Reactor. • S and U analysis is performed with MC and adaptive PC methods, for 42 input parameters. • PC accurately estimates means, variances, PDFs, sensitivities and uncertainties. - Abstract: Since the early years of reactor physics the most prominent sensitivity and uncertainty (S and U) analysis methods in the nuclear community have been adjoint based techniques. While these are very effective for pure neutronics problems due to the linearity of the transport equation, they become complicated when coupled non-linear systems are involved. With the continuous increase in computational power such complicated multi-physics problems are becoming progressively tractable, hence affordable and easily applicable S and U analysis tools also have to be developed in parallel. For reactor physics problems for which adjoint methods are prohibitive Polynomial Chaos (PC) techniques offer an attractive alternative to traditional random sampling based approaches. At TU Delft such PC methods have been studied for a number of years and this paper presents a large scale application of our Fully Adaptive Non-Intrusive Spectral Projection (FANISP) algorithm for performing the sensitivity and uncertainty analysis of a Gas Cooled Fast Reactor (GFR) Unprotected Loss Of Flow (ULOF) transient. The transient was simulated using the Cathare 2 code system and a fully detailed model of the GFR2400 reactor design that was investigated in the European FP7 GoFastR project. Several sources of uncertainty were taken into account amounting to an unusually high number of stochastic input parameters (42) and numerous output quantities were investigated. The results show consistently good performance of the applied adaptive PC
Directory of Open Access Journals (Sweden)
Julie Vercelloni
Full Text Available Recently, attempts to improve decision making in species management have focussed on uncertainties associated with modelling temporal fluctuations in populations. Reducing model uncertainty is challenging; while larger samples improve estimation of species trajectories and reduce statistical errors, they typically amplify variability in observed trajectories. In particular, traditional modelling approaches aimed at estimating population trajectories usually do not account well for nonlinearities and uncertainties associated with multi-scale observations characteristic of large spatio-temporal surveys. We present a Bayesian semi-parametric hierarchical model for simultaneously quantifying uncertainties associated with model structure and parameters, and scale-specific variability over time. We estimate uncertainty across a four-tiered spatial hierarchy of coral cover from the Great Barrier Reef. Coral variability is well described; however, our results show that, in the absence of additional model specifications, conclusions regarding coral trajectories become highly uncertain when considering multiple reefs, suggesting that management should focus more at the scale of individual reefs. The approach presented facilitates the description and estimation of population trajectories and associated uncertainties when variability cannot be attributed to specific causes and origins. We argue that our model can unlock value contained in large-scale datasets, provide guidance for understanding sources of uncertainty, and support better informed decision making.
Energy Technology Data Exchange (ETDEWEB)
Martin-Quller, E.; Torras, O.; Alberdi, I.; Solana, J.; Saura, S.
2011-07-01
An integral understanding of forest biodiversity requires the exploration of the many aspects it comprises and of the numerous potential determinants of their distribution. The landscape ecological approach provides a necessary complement to conventional local studies that focus on individual plots or forest ownerships. However, most previous landscape studies used equally-sized cells as units of analysis to identify the factors affecting forest biodiversity distribution. Stratification of the analysis by habitats with a relatively homogeneous forest composition might be more adequate to capture the underlying patterns associated to the formation and development of a particular ensemble of interacting forest species. Here we used a landscape perspective in order to improve our understanding on the influence of large-scale explanatory factors on forest biodiversity indicators in Spanish habitats, covering a wide latitudinal and attitudinal range. We considered six forest biodiversity indicators estimated from more than 30,000 field plots in the Spanish national forest inventory, distributed in 213 forest habitats over 16 Spanish provinces. We explored biodiversity response to various environmental (climate and topography) and landscape configuration (fragmentation and shape complexity) variables through multiple linear regression models (built and assessed through the Akaike Information Criterion). In particular, we took into account the inherent model uncertainty when dealing with a complex and large set of variables, and considered different plausible models and their probability of being the best candidate for the observed data. Our results showed that compositional indicators (species richness and diversity) were mostly explained by environmental factors. Models for structural indicators (standing deadwood and stand complexity) had the worst fits and selection uncertainties, but did show significant associations with some configuration metrics. In general
Directory of Open Access Journals (Sweden)
Nezir Aydin
2016-03-01
Full Text Available In this study, we consider field hospital location decisions for emergency treatment points in response to large scale disasters. Specifically, we developed a two-stage stochastic model that determines the number and locations of field hospitals and the allocation of injured victims to these field hospitals. Our model considers the locations as well as the failings of the existing public hospitals while deciding on the location of field hospitals that are anticipated to be opened. The model that we developed is a variant of the P-median location model and it integrates capacity restrictions both on field hospitals that are planned to be opened and the disruptions that occur in existing public hospitals. We conducted experiments to demonstrate how the proposed model can be utilized in practice in a real life problem case scenario. Results show the effects of the failings of existing hospitals, the level of failure probability and the capacity of projected field hospitals to deal with the assessment of any given emergency treatment system’s performance. Crucially, it also specifically provides an assessment on the average distance within which a victim needs to be transferred in order to be treated properly and then from this assessment, the proportion of total satisfied demand is then calculated.
International Nuclear Information System (INIS)
Jocelyn, Sabrina; Baudoin, James; Chinniah, Yuvin; Charpentier, Philippe
2014-01-01
In industry, machine users and people who modify or integrate equipment often have to evaluate the safety level of a safety-related control circuit that they have not necessarily designed. The modifications or integrations may involve work to make an existing machine that does not comply with normative or regulatory specifications safe. However, how can a circuit performing a safety function be validated a posteriori? Is the validation exercise feasible? What are the difficulties and limitations of such a procedure? The aim of this article is to answer these questions by presenting a validation study of a safety function of an existing machine. A plastic injection molding machine is used for this study, as well as standard ISO 13849-1:2006. Validation consists of performing an a posteriori (post-design) estimation of the performance level of the safety function. The procedure is studied for two contexts of use of the machine: in industry, and in laboratory. The calculations required by the ISO standard were done using Excel, followed by SIStema software. It is shown that, based on the context of use, the estimated performance level was different for the same safety-related circuit. The variability in the results is explained by the assumptions made by the person undertaking the validation without the involvement of the machine designer. - Highlights: • Validation of the performance level of a safety function is undertaken. • An injection molding machine and ISO 13849-1:2006 standard are used for the procedure. • The procedure is undertaken for two contexts of use of the machine. • In this study, the performance level depends on the context of use. • The assumptions made throughout the study partially explain this difference
Tang, S.; Xie, S.; Tang, Q.; Zhang, Y.
2017-12-01
Two types of instruments, the eddy correlation flux measurement system (ECOR) and the energy balance Bowen ratio system (EBBR), are used at the Atmospheric Radiation Measurement (ARM) program Southern Great Plains (SGP) site to measure surface latent and sensible fluxes. ECOR and EBBR typically sample different land surface types, and the domain-mean surface fluxes derived from ECOR and EBBR are not always consistent. The uncertainties of the surface fluxes will have impacts on the derived large-scale forcing data and further affect the simulations of single-column models (SCM), cloud-resolving models (CRM) and large-eddy simulation models (LES), especially for the shallow-cumulus clouds which are mainly driven by surface forcing. This study aims to quantify the uncertainties of the large-scale forcing caused by surface turbulence flux measurements and investigate the impacts on cloud simulations using long-term observations from the ARM SGP site.
Lau, William K. M. (Technical Monitor); Bell, Thomas L.; Steiner, Matthias; Zhang, Yu; Wood, Eric F.
2002-01-01
The uncertainty of rainfall estimated from averages of discrete samples collected by a satellite is assessed using a multi-year radar data set covering a large portion of the United States. The sampling-related uncertainty of rainfall estimates is evaluated for all combinations of 100 km, 200 km, and 500 km space domains, 1 day, 5 day, and 30 day rainfall accumulations, and regular sampling time intervals of 1 h, 3 h, 6 h, 8 h, and 12 h. These extensive analyses are combined to characterize the sampling uncertainty as a function of space and time domain, sampling frequency, and rainfall characteristics by means of a simple scaling law. Moreover, it is shown that both parametric and non-parametric statistical techniques of estimating the sampling uncertainty produce comparable results. Sampling uncertainty estimates, however, do depend on the choice of technique for obtaining them. They can also vary considerably from case to case, reflecting the great variability of natural rainfall, and should therefore be expressed in probabilistic terms. Rainfall calibration errors are shown to affect comparison of results obtained by studies based on data from different climate regions and/or observation platforms.
International Nuclear Information System (INIS)
Jones-Lee, M.; Aven, T.
2009-01-01
Social cost-benefit analysis is a well-established method for guiding decisions about safety investments, particularly in situations in which it is possible to make accurate predictions of future performance. However, its direct applicability to situations involving large degrees of uncertainty is less obvious and this raises the question of the extent to which social cost-benefit analysis can provide a useful input to the decision framework that has been explicitly developed to deal with safety decisions in which uncertainty is a major factor, namely risk analysis. This is the main focus of the arguments developed in this paper. In particular, we provide new insights by examining the fundamentals of both approaches and our principal conclusion is that social cost-benefit analysis and risk analysis represent complementary input bases to the decision-making process, and even in the case of large uncertainties social cost-benefit analysis may provide very useful decision support. What is required is the establishment of a proper contextual framework which structures and gives adequate weight to the uncertainties. An application to the possibility of a robbery at a cash depot is examined as a practical example.
Energy Technology Data Exchange (ETDEWEB)
Ligon, C.; Kirby, G.; Jordan, D.; Lawrence, J.H.; Wiesner, W.; Kosovec, A.; Swanson, R.K.; Smith, R.T.; Johnson, C.C.; Hodson, H.O.
1976-04-01
Detailed wind energy assessment from the available wind records, and evaluation of the application of wind energy systems to an existing electric utility were performed in an area known as the Texas Panhandle, on the Great Plains. The study area includes parts of Texas, eastern New Mexico, the Oklahoma Panhandle and southern Kansas. The region is shown to have uniformly distributed winds of relatively high velocity, with average wind power density of 0.53 kW/m/sup 2/ at 30 m height at Amarillo, Texas, a representative location. The annual period of calm is extremely low. Three separate compressed air storage systems with good potential were analyzed in detail, and two potential pumped-hydro facilities were identified and given preliminary consideration. Aquifer storage of compressed air is a promising possibility in the region.
Directory of Open Access Journals (Sweden)
Christopher J Topping
Full Text Available Pattern-oriented modeling (POM is a general strategy for modeling complex systems. In POM, multiple patterns observed at different scales and hierarchical levels are used to optimize model structure, to test and select sub-models of key processes, and for calibration. So far, POM has been used for developing new models and for models of low to moderate complexity. It remains unclear, though, whether the basic idea of POM to utilize multiple patterns, could also be used to test and possibly develop existing and established models of high complexity. Here, we use POM to test, calibrate, and further develop an existing agent-based model of the field vole (Microtus agrestis, which was developed and tested within the ALMaSS framework. This framework is complex because it includes a high-resolution representation of the landscape and its dynamics, of the individual's behavior, and of the interaction between landscape and individual behavior. Results of fitting to the range of patterns chosen were generally very good, but the procedure required to achieve this was long and complicated. To obtain good correspondence between model and the real world it was often necessary to model the real world environment closely. We therefore conclude that post-hoc POM is a useful and viable way to test a highly complex simulation model, but also warn against the dangers of over-fitting to real world patterns that lack details in their explanatory driving factors. To overcome some of these obstacles we suggest the adoption of open-science and open-source approaches to ecological simulation modeling.
International Nuclear Information System (INIS)
Okamoto, Toshiro
1987-01-01
In our laboratory a study of siting on quarternary ground is followed to make possible to construct a nuclear power plant on soil ground in Japan, a important subject is to understand bearing capacity, settlement and seismic responce of foundation. So measured data are collected about relation between ground and type of foundation, total settlement and differential settlement of already constructed large structures, and it is done to investigate the real condition and to examine allowable settlement. Investigated structures are mainly foreign nuclear power plant and domestic and foreign high buildings. The higher buildings are, the more raft foundation are for type of foundation and the higher contact pressure are to similar to a nuclear power plant. So discussion is done about mainly raft foundation. It is found that some measured maximum total settlements are larger than already proposed allowable values. So empirical allowable settlement is derived from measured values considering the effect of the width of base slab, contact pressure and foundation ground. Differential settlement is investigated about relation to maximum total settlement, and is formulated considering the width and the rigidity of base slab. Beside the limit of differential settlement is obtained as foundation is damaged, and the limit of maximum total settlement is obtained by combining this and above mentioned relation. Obtained allowable value is largely influenced by the width of base slab, and becomes less severe than some already proposed values. So it is expected that deformation of foundation is rationaly investigated when large structure as nuclear power plant is constructed on soft ground. (author)
Sankey, J. B.; Kreitler, J.; McVay, J.; Hawbaker, T. J.; Vaillant, N.; Lowe, S. E.
2014-12-01
Wildland fire is a primary threat to watersheds that can impact water supply through increased sedimentation, water quality decline, and change the timing and amount of runoff leading to increased risk from flood and sediment natural hazards. It is of great societal importance in the western USA and throughout the world to improve understanding of how changing fire frequency, extent, and location, in conjunction with fuel treatments will affect watersheds and the ecosystem services they supply to communities. In this work we assess the utility of the InVEST Sediment Retention Model to accurately characterize vulnerability of burned watersheds to erosion and sedimentation. The InVEST tools are GIS-based implementations of common process models, engineered for high-end computing to allow the faster simulation of larger landscapes and incorporation into decision-making. The InVEST Sediment Retention Model is based on common soil erosion models (e.g., RUSLE -Revised Universal Soil Loss Equation) and determines which areas of the landscape contribute the greatest sediment loads to a hydrological network and conversely evaluate the ecosystem service of sediment retention on a watershed basis. We evaluate the accuracy and uncertainties for InVEST predictions of increased sedimentation after fire, using measured post-fire sedimentation rates available for many watersheds in different rainfall regimes throughout the western USA from an existing, large USGS database of post-fire sediment yield [synthesized in Moody J, Martin D (2009) Synthesis of sediment yields after wildland fire in different rainfall regimes in the western United States. International Journal of Wildland Fire 18: 96-115]. The ultimate goal of this work is to calibrate and implement the model to accurately predict variability in post-fire sediment yield as a function of future landscape heterogeneity predicted by wildfire simulations, and future landscape fuel treatment scenarios, within watersheds.
Energy Technology Data Exchange (ETDEWEB)
Benyoucef, Abderrezak; Lantz, Frederic
2010-09-15
The objective of this article is to analyze the development of Algeria refinery industry when uncertainty exists, from a dynamic linear programming model. Because of the different market conditions volatility, many parameters must be able to be considered as uncertain. In our study, we treat mainly uncertainties of petroleum products demand. The model gives production levels, the units market rate and the exterior exchange of products at horizons 2030. It allows to appreciate the impact of volatility on this industry's development. [French] L'objectif de cet article est d'analyser le developpement de l'industrie algerienne du raffinage en presence d'incertitudes, a partir d'un modele de programmation lineaire dynamique. En raison de la volatilite des differentes conditions du marche, de nombreux parametres doivent pouvoir etre consideres comme incertains. Dans notre etude, nous traitons en particulier des incertitudes sur la demande des produits petroliers. Le modele fournit les niveaux de production, le taux de marche des unites et les echanges exterieurs de produits a l'horizon 2030. Il permet ainsi d'apprecier l'impact de la volatilite sur le developpement de cette industrie.
International Nuclear Information System (INIS)
Mavko, B.; Stritar, A.; Prosek, A.
1993-01-01
In NED 119, No. 1 (May 1990) a series of six papers published by a Technical Program Group presented a new methodology for the safety evaluation of emergency core cooling systems in nuclear power plants. This paper describes the application of that new methodology to the LB LOCA analysis of the two loop Westinghouse power plant. Results of the original work were used wherever possible, so that the analysis was finished in less than one man year of work. Steam generator plugging level and safety injection flow rate were used as additional uncertainty parameters, which had not been used in the original work. The computer code RELAP5/MOD2 was used. Response surface was generated by the regression analysis and by the artificial neural network like Optimal Statistical Estimator method. Results were compared also to the analytical calculation. (orig.)
Sze, Sing-Hoi; Parrott, Jonathan J; Tarone, Aaron M
2017-12-06
While the continued development of high-throughput sequencing has facilitated studies of entire transcriptomes in non-model organisms, the incorporation of an increasing amount of RNA-Seq libraries has made de novo transcriptome assembly difficult. Although algorithms that can assemble a large amount of RNA-Seq data are available, they are generally very memory-intensive and can only be used to construct small assemblies. We develop a divide-and-conquer strategy that allows these algorithms to be utilized, by subdividing a large RNA-Seq data set into small libraries. Each individual library is assembled independently by an existing algorithm, and a merging algorithm is developed to combine these assemblies by picking a subset of high quality transcripts to form a large transcriptome. When compared to existing algorithms that return a single assembly directly, this strategy achieves comparable or increased accuracy as memory-efficient algorithms that can be used to process a large amount of RNA-Seq data, and comparable or decreased accuracy as memory-intensive algorithms that can only be used to construct small assemblies. Our divide-and-conquer strategy allows memory-intensive de novo transcriptome assembly algorithms to be utilized to construct large assemblies.
Neustupa, Tomáš
2017-07-01
The paper presents the mathematical model of a steady 2-dimensional viscous incompressible flow through a radial blade machine. The corresponding boundary value problem is studied in the rotating frame. We provide the classical and weak formulation of the problem. Using a special form of the so called "artificial" or "natural" boundary condition on the outflow, we prove the existence of a weak solution for an arbitrarily large inflow.
Schlosser, C. A.; Strzepek, K. M.; Gao, X.; Fant, C. W.; Blanc, E.; Monier, E.; Sokolov, A. P.; Paltsev, S.; Arndt, C.; Prinn, R. G.; Reilly, J. M.; Jacoby, H.
2013-12-01
The fate of natural and managed water resources is controlled to varying degrees by interlinked energy, agricultural, and environmental systems, as well as the hydro-climate cycles. The need for risk-based assessments of impacts and adaptation to regional change calls for likelihood quantification of outcomes via the representation of uncertainty - to the fullest extent possible. A hybrid approach of the MIT Integrated Global System Model (IGSM) framework provides probabilistic projections of regional climate change - generated in tandem with consistent socio-economic projections. A Water Resources System (WRS) then tracks water allocation and availability across these competing demands. As such, the IGSM-WRS is an integrated tool that provides quantitative insights on the risks and sustainability of water resources over large river basins. This pilot project focuses the IGSM-WRS on Southeast Asia (Figure 1). This region presents exceptional challenges toward sustainable water resources given its texture of basins that traverse and interconnect developing nations as well as large, ascending economies and populations - such as China and India. We employ the IGSM-WRS in a large ensemble of outcomes spanning hydro-climatic, economic, and policy uncertainties. For computational efficiency, a Gaussian Quadrature procedure sub-samples these outcomes (Figure 2). The IGSM-WRS impacts are quantified through frequency distributions of water stress changes. The results allow for interpretation of: the effects of policy measures; impacts on food production; and the value of design flexibility of infrastructure/institutions. An area of model development and exploration is the feedback of water-stress shocks to economic activity (i.e. GDP and land use). We discuss these further results (where possible) as well as other efforts to refine: uncertainty methods, greater basin-level and climate detail, and process-level representation glacial melt-water sources. Figure 1 Figure 2
Abbaspour, K. C.; Rouholahnejad, E.; Vaghefi, S.; Srinivasan, R.; Yang, H.; Kløve, B.
2015-05-01
A combination of driving forces are increasing pressure on local, national, and regional water supplies needed for irrigation, energy production, industrial uses, domestic purposes, and the environment. In many parts of Europe groundwater quantity, and in particular quality, have come under sever degradation and water levels have decreased resulting in negative environmental impacts. Rapid improvements in the economy of the eastern European block of countries and uncertainties with regard to freshwater availability create challenges for water managers. At the same time, climate change adds a new level of uncertainty with regard to freshwater supplies. In this research we build and calibrate an integrated hydrological model of Europe using the Soil and Water Assessment Tool (SWAT) program. Different components of water resources are simulated and crop yield and water quality are considered at the Hydrological Response Unit (HRU) level. The water resources are quantified at subbasin level with monthly time intervals. Leaching of nitrate into groundwater is also simulated at a finer spatial level (HRU). The use of large-scale, high-resolution water resources models enables consistent and comprehensive examination of integrated system behavior through physically-based, data-driven simulation. In this article we discuss issues with data availability, calibration of large-scale distributed models, and outline procedures for model calibration and uncertainty analysis. The calibrated model and results provide information support to the European Water Framework Directive and lay the basis for further assessment of the impact of climate change on water availability and quality. The approach and methods developed are general and can be applied to any large region around the world.
Uncertainties in Safety Analysis. A literature review
International Nuclear Information System (INIS)
Ekberg, C.
1995-05-01
The purpose of the presented work has been to give a short summary of the origins of many uncertainties arising in the designing and performance assessment of a repository for spent nuclear fuel. Some different methods to treat these uncertainties is also included. The methods and conclusions are in many cases general in the sense that they are applicable to many other disciplines where simulations are used. As a conclusion it may be noted that uncertainties of different origin have been discussed and debated, but one large group, e.g. computer simulations, where the methods to make a more explicit investigation exists, have not been investigated in a satisfying way. 50 refs
Uncertainties in Safety Analysis. A literature review
Energy Technology Data Exchange (ETDEWEB)
Ekberg, C [Chalmers Univ. of Technology, Goeteborg (Sweden). Dept. of Nuclear Chemistry
1995-05-01
The purpose of the presented work has been to give a short summary of the origins of many uncertainties arising in the designing and performance assessment of a repository for spent nuclear fuel. Some different methods to treat these uncertainties is also included. The methods and conclusions are in many cases general in the sense that they are applicable to many other disciplines where simulations are used. As a conclusion it may be noted that uncertainties of different origin have been discussed and debated, but one large group, e.g. computer simulations, where the methods to make a more explicit investigation exists, have not been investigated in a satisfying way. 50 refs.
Fuzzy Uncertainty Evaluation for Fault Tree Analysis
Energy Technology Data Exchange (ETDEWEB)
Kim, Ki Beom; Shim, Hyung Jin [Seoul National University, Seoul (Korea, Republic of); Jae, Moo Sung [Hanyang University, Seoul (Korea, Republic of)
2015-05-15
This traditional probabilistic approach can calculate relatively accurate results. However it requires a long time because of repetitive computation due to the MC method. In addition, when informative data for statistical analysis are not sufficient or some events are mainly caused by human error, the probabilistic approach may not be possible because uncertainties of these events are difficult to be expressed by probabilistic distributions. In order to reduce the computation time and quantify uncertainties of top events when basic events whose uncertainties are difficult to be expressed by probabilistic distributions exist, the fuzzy uncertainty propagation based on fuzzy set theory can be applied. In this paper, we develop a fuzzy uncertainty propagation code and apply the fault tree of the core damage accident after the large loss of coolant accident (LLOCA). The fuzzy uncertainty propagation code is implemented and tested for the fault tree of the radiation release accident. We apply this code to the fault tree of the core damage accident after the LLOCA in three cases and compare the results with those computed by the probabilistic uncertainty propagation using the MC method. The results obtained by the fuzzy uncertainty propagation can be calculated in relatively short time, covering the results obtained by the probabilistic uncertainty propagation.
Nasonova, Olga N.; Gusev, Yeugeniy M.; Kovalev, Evgeny E.; Ayzel, Georgy V.
2018-06-01
Climate change impact on river runoff was investigated within the framework of the second phase of the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP2) using a physically-based land surface model Soil Water - Atmosphere - Plants (SWAP) (developed in the Institute of Water Problems of the Russian Academy of Sciences) and meteorological projections (for 2006-2099) simulated by five General Circulation Models (GCMs) (including GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, MIROC-ESM-CHEM, and NorESM1-M) for each of four Representative Concentration Pathway (RCP) scenarios (RCP2.6, RCP4.5, RCP6.0, and RCP8.5). Eleven large-scale river basins were used in this study. First of all, SWAP was calibrated and validated against monthly values of measured river runoff with making use of forcing data from the WATCH data set and all GCMs' projections were bias-corrected to the WATCH. Then, for each basin, 20 projections of possible changes in river runoff during the 21st century were simulated by SWAP. Analysis of the obtained hydrological projections allowed us to estimate their uncertainties resulted from application of different GCMs and RCP scenarios. On the average, the contribution of different GCMs to the uncertainty of the projected river runoff is nearly twice larger than the contribution of RCP scenarios. At the same time the contribution of GCMs slightly decreases with time.
Energy Technology Data Exchange (ETDEWEB)
Smith, P.J.; Eddings, E.G.; Ring, T.; Thornock, J.; Draper, T.; Isaac, B.; Rezeai, D.; Toth, P.; Wu, Y.; Kelly, K.
2014-08-01
The objective of this task is to produce predictive capability with quantified uncertainty bounds for the heat flux in commercial-scale, tangentially fired, oxy-coal boilers. Validation data came from the Alstom Boiler Simulation Facility (BSF) for tangentially fired, oxy-coal operation. This task brings together experimental data collected under Alstom’s DOE project for measuring oxy-firing performance parameters in the BSF with this University of Utah project for large eddy simulation (LES) and validation/uncertainty quantification (V/UQ). The Utah work includes V/UQ with measurements in the single-burner facility where advanced strategies for O2 injection can be more easily controlled and data more easily obtained. Highlights of the work include: • Simulations of Alstom’s 15 megawatt (MW) BSF, exploring the uncertainty in thermal boundary conditions. A V/UQ analysis showed consistency between experimental results and simulation results, identifying uncertainty bounds on the quantities of interest for this system (Subtask 9.1) • A simulation study of the University of Utah’s oxy-fuel combustor (OFC) focused on heat flux (Subtask 9.2). A V/UQ analysis was used to show consistency between experimental and simulation results. • Measurement of heat flux and temperature with new optical diagnostic techniques and comparison with conventional measurements (Subtask 9.3). Various optical diagnostics systems were created to provide experimental data to the simulation team. The final configuration utilized a mid-wave infrared (MWIR) camera to measure heat flux and temperature, which was synchronized with a high-speed, visible camera to utilize two-color pyrometry to measure temperature and soot concentration. • Collection of heat flux and temperature measurements in the University of Utah’s OFC for use is subtasks 9.2 and 9.3 (Subtask 9.4). Several replicates were carried to better assess the experimental error. Experiments were specifically designed for the
International Nuclear Information System (INIS)
Thomas, R.E.
1982-03-01
An evaluation is made of the suitability of analytical and statistical sampling methods for making uncertainty analyses. The adjoint method is found to be well-suited for obtaining sensitivity coefficients for computer programs involving large numbers of equations and input parameters. For this purpose the Latin Hypercube Sampling method is found to be inferior to conventional experimental designs. The Latin hypercube method can be used to estimate output probability density functions, but requires supplementary rank transformations followed by stepwise regression to obtain uncertainty information on individual input parameters. A simple Cork and Bottle problem is used to illustrate the efficiency of the adjoint method relative to certain statistical sampling methods. For linear models of the form Ax=b it is shown that a complete adjoint sensitivity analysis can be made without formulating and solving the adjoint problem. This can be done either by using a special type of statistical sampling or by reformulating the primal problem and using suitable linear programming software
BEPU methods and combining of uncertainties
International Nuclear Information System (INIS)
Prosek, A.; Mavko, B.
2004-01-01
After approval of the revised rule on the acceptance of emergency core cooling system (ECCS) performance in 1988 there has been significant interest in the development of codes and methodologies for best-estimate loss-of-coolant accident (LOCAs) analyses. The Code Scaling, Applicability and Uncertainty (CSAU) evaluation method was developed and demonstrated for large-break (LB) LOCA in a pressurized water reactor. Later several new best estimate plus uncertainty methods (BEPUs) were developed in the world. The purpose of the paper is to identify and compare the statistical approaches of BEPU methods and present their important plant and licensing applications. The study showed that uncertainty analysis with random sampling of input parameters and the use of order statistics for desired tolerance limits of output parameters is today commonly accepted approach. The existing BEPU methods seems mature enough while the future research may be focused on the codes with internal assessment of uncertainty. (author)
Welter, David E.; White, Jeremy T.; Hunt, Randall J.; Doherty, John E.
2015-09-18
The PEST++ Version 1 object-oriented parameter estimation code is here extended to Version 3 to incorporate additional algorithms and tools to further improve support for large and complex environmental modeling problems. PEST++ Version 3 includes the Gauss-Marquardt-Levenberg (GML) algorithm for nonlinear parameter estimation, Tikhonov regularization, integrated linear-based uncertainty quantification, options of integrated TCP/IP based parallel run management or external independent run management by use of a Version 2 update of the GENIE Version 1 software code, and utilities for global sensitivity analyses. The Version 3 code design is consistent with PEST++ Version 1 and continues to be designed to lower the barriers of entry for users as well as developers while providing efficient and optimized algorithms capable of accommodating large, highly parameterized inverse problems. As such, this effort continues the original focus of (1) implementing the most popular and powerful features of the PEST software suite in a fashion that is easy for novice or experienced modelers to use and (2) developing a software framework that is easy to extend.
Lindley, Dennis V
2013-01-01
Praise for the First Edition ""...a reference for everyone who is interested in knowing and handling uncertainty.""-Journal of Applied Statistics The critically acclaimed First Edition of Understanding Uncertainty provided a study of uncertainty addressed to scholars in all fields, showing that uncertainty could be measured by probability, and that probability obeyed three basic rules that enabled uncertainty to be handled sensibly in everyday life. These ideas were extended to embrace the scientific method and to show how decisions, containing an uncertain element, could be rationally made.
Conditional uncertainty principle
Gour, Gilad; Grudka, Andrzej; Horodecki, Michał; Kłobus, Waldemar; Łodyga, Justyna; Narasimhachar, Varun
2018-04-01
We develop a general operational framework that formalizes the concept of conditional uncertainty in a measure-independent fashion. Our formalism is built upon a mathematical relation which we call conditional majorization. We define conditional majorization and, for the case of classical memory, we provide its thorough characterization in terms of monotones, i.e., functions that preserve the partial order under conditional majorization. We demonstrate the application of this framework by deriving two types of memory-assisted uncertainty relations, (1) a monotone-based conditional uncertainty relation and (2) a universal measure-independent conditional uncertainty relation, both of which set a lower bound on the minimal uncertainty that Bob has about Alice's pair of incompatible measurements, conditioned on arbitrary measurement that Bob makes on his own system. We next compare the obtained relations with their existing entropic counterparts and find that they are at least independent.
Measurement uncertainty and probability
Willink, Robin
2013-01-01
A measurement result is incomplete without a statement of its 'uncertainty' or 'margin of error'. But what does this statement actually tell us? By examining the practical meaning of probability, this book discusses what is meant by a '95 percent interval of measurement uncertainty', and how such an interval can be calculated. The book argues that the concept of an unknown 'target value' is essential if probability is to be used as a tool for evaluating measurement uncertainty. It uses statistical concepts, such as a conditional confidence interval, to present 'extended' classical methods for evaluating measurement uncertainty. The use of the Monte Carlo principle for the simulation of experiments is described. Useful for researchers and graduate students, the book also discusses other philosophies relating to the evaluation of measurement uncertainty. It employs clear notation and language to avoid the confusion that exists in this controversial field of science.
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.
Uncertainty in the inelastic resonant scattering assisted by phonons
International Nuclear Information System (INIS)
Garcia, N.; Garcia-Sanz, J.; Solana, J.
1977-01-01
We have analyzed the inelastic minima observed in new results of He atoms scattered from LiF(001) surfaces. This is done considering bound state resonance processes assisted by phonons. The analysis presents large uncertainties. In the range of uncertainty, we find two ''possible'' bands associated with the vibrations of F - and Li + , respectively. Many more experimental data are necessary to confirm the existence of these processes
Uncertainty in hydrological signatures
McMillan, Hilary; Westerberg, Ida
2015-04-01
magnitude and bias, and to test how uncertainty depended on the density of the raingauge network and flow gauging station characteristics. The uncertainties were sometimes large (i.e. typical intervals of ±10-40% relative uncertainty) and highly variable between signatures. Uncertainty in the mean discharge was around ±10% for both catchments, while signatures describing the flow variability had much higher uncertainties in the Mahurangi where there was a fast rainfall-runoff response and greater high-flow rating uncertainty. Event and total runoff ratios had uncertainties from ±10% to ±15% depending on the number of rain gauges used; precipitation uncertainty was related to interpolation rather than point uncertainty. Uncertainty distributions in these signatures were skewed, and meant that differences in signature values between these catchments were often not significant. We hope that this study encourages others to use signatures in a way that is robust to data uncertainty.
International Nuclear Information System (INIS)
Boyack, B.; Duffey, R.; Wilson, G.; Griffith, P.; Lellouche, G.; Levy, S.; Rohatgi, U.; Wulff, W.; Zuber, N.
1989-12-01
The US Nuclear Regulatory Commission (NRC) has issued a revised rule for loss-of-coolant accident/emergency core cooling system (ECCS) analysis of light water reactors to allow the use of best-estimate computer codes in safety analysis as an option. A key feature of this option requires the licensee to quantify the uncertainty of the calculations and include that uncertainty when comparing the calculated results with acceptance limits provided in 10 CFR Part 50. To support the revised ECCS rule and illustrate its application, the NRC and its contractors and consultants have developed and demonstrated an uncertainty evaluation methodology called code scaling, applicability, and uncertainty (CSAU). The CSAU methodology and an example application described in this report demonstrate that uncertainties in complex phenomena can be quantified. The methodology is structured, traceable, and practical, as is needed in the regulatory arena. The methodology is systematic and comprehensive as it addresses and integrates the scenario, experiments, code, and plant to resolve questions concerned with: (a) code capability to scale-up processes from test facility to full-scale nuclear power plants; (b) code applicability to safety studies of a postulated accident scenario in a specified nuclear power plant; and (c) quantifying uncertainties of calculated results. 127 refs., 55 figs., 40 tabs
Uncertainties as Barriers for Knowledge Sharing with Enterprise Social Media
DEFF Research Database (Denmark)
Trier, Matthias; Fung, Magdalene; Hansen, Abigail
2017-01-01
become a barrier for the participants’ adoption. There is only limited existing research studying the types of uncertainties that employees perceive and their impact on knowledge transfer via social media. To address this gap, this article presents a qualitative interview-based study of the adoption...... of the Enterprise Social Media tool Yammer for knowledge sharing in a large global organization. We identify and categorize nine uncertainties that were perceived as barriers by the respondents. The study revealed that the uncertainty types play an important role in affecting employees’ participation...
Liu, Baoding
2015-01-01
When no samples are available to estimate a probability distribution, we have to invite some domain experts to evaluate the belief degree that each event will happen. Perhaps some people think that the belief degree should be modeled by subjective probability or fuzzy set theory. However, it is usually inappropriate because both of them may lead to counterintuitive results in this case. In order to rationally deal with belief degrees, uncertainty theory was founded in 2007 and subsequently studied by many researchers. Nowadays, uncertainty theory has become a branch of axiomatic mathematics for modeling belief degrees. This is an introductory textbook on uncertainty theory, uncertain programming, uncertain statistics, uncertain risk analysis, uncertain reliability analysis, uncertain set, uncertain logic, uncertain inference, uncertain process, uncertain calculus, and uncertain differential equation. This textbook also shows applications of uncertainty theory to scheduling, logistics, networks, data mining, c...
Uncertainty in Seismic Capacity of Masonry Buildings
Directory of Open Access Journals (Sweden)
Nicola Augenti
2012-07-01
Full Text Available Seismic assessment of masonry structures is plagued by both inherent randomness and model uncertainty. The former is referred to as aleatory uncertainty, the latter as epistemic uncertainty because it depends on the knowledge level. Pioneering studies on reinforced concrete buildings have revealed a significant influence of modeling parameters on seismic vulnerability. However, confidence in mechanical properties of existing masonry buildings is much lower than in the case of reinforcing steel and concrete. This paper is aimed at assessing whether and how uncertainty propagates from material properties to seismic capacity of an entire masonry structure. A typical two-story unreinforced masonry building is analyzed. Based on previous statistical characterization of mechanical properties of existing masonry types, the following random variables have been considered in this study: unit weight, uniaxial compressive strength, shear strength at zero confining stress, Young’s modulus, shear modulus, and available ductility in shear. Probability density functions were implemented to generate a significant number of realizations and static pushover analysis of the case-study building was performed for each vector of realizations, load combination and lateral load pattern. Analysis results show a large dispersion in displacement capacity and lower dispersion in spectral acceleration capacity. This can directly affect decision-making because both design and retrofit solutions depend on seismic capacity predictions. Therefore, engineering judgment should always be used when assessing structural safety of existing masonry constructions against design earthquakes, based on a series of seismic analyses under uncertain parameters.
DEFF Research Database (Denmark)
Schwämmle, Veit; Aspalter, Claudia-Maria; Sidoli, Simone
2014-01-01
Mass spectrometry (MS) is a powerful analytical method for the identification and quantification of co-existing post-translational modifications in histone proteins. One of the most important challenges in current chromatin biology is to characterize the relationships between co-existing histone...... sample-specific patterns for the co-frequency of histone post-translational modifications. We implemented a new method to identify positive and negative interplay between pairs of methylation and acetylation marks in proteins. Many of the detected features were conserved between different cell types...... sites but negative cross-talk for distant ones, and for discrete methylation states at Lys-9, Lys-27, and Lys-36 of histone H3, suggesting a more differentiated functional role of methylation beyond the general expectation of enhanced activity at higher methylation states....
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)
Chemical model reduction under uncertainty
Najm, Habib; Galassi, R. Malpica; Valorani, M.
2016-01-01
We outline a strategy for chemical kinetic model reduction under uncertainty. We present highlights of our existing deterministic model reduction strategy, and describe the extension of the formulation to include parametric uncertainty in the detailed mechanism. We discuss the utility of this construction, as applied to hydrocarbon fuel-air kinetics, and the associated use of uncertainty-aware measures of error between predictions from detailed and simplified models.
Chemical model reduction under uncertainty
Najm, Habib
2016-01-05
We outline a strategy for chemical kinetic model reduction under uncertainty. We present highlights of our existing deterministic model reduction strategy, and describe the extension of the formulation to include parametric uncertainty in the detailed mechanism. We discuss the utility of this construction, as applied to hydrocarbon fuel-air kinetics, and the associated use of uncertainty-aware measures of error between predictions from detailed and simplified models.
Directory of Open Access Journals (Sweden)
Marcus Ulrich
2012-11-01
Full Text Available Abstract Background Country level comparisons of HIV prevalence among men having sex with men (MSM is challenging for a variety of reasons, including differences in the definition and measurement of the denominator group, recruitment strategies and the HIV detection methods. To assess their comparability, self-reported data on HIV diagnoses in a 2010 pan-European MSM internet survey (EMIS were compared with pre-existing estimates of HIV prevalence in MSM from a variety of European countries. Methods The first pan-European survey of MSM recruited more than 180,000 men from 38 countries across Europe and included questions on the year and result of last HIV test. HIV prevalence as measured in EMIS was compared with national estimates of HIV prevalence based on studies using biological measurements or modelling approaches to explore the degree of agreement between different methods. Existing estimates were taken from Dublin Declaration Monitoring Reports or UNAIDS country fact sheets, and were verified by contacting the nominated contact points for HIV surveillance in EU/EEA countries. Results The EMIS self-reported measurements of HIV prevalence were strongly correlated with existing estimates based on biological measurement and modelling studies using surveillance data (R2=0.70 resp. 0.72. In most countries HIV positive MSM appeared disproportionately likely to participate in EMIS, and prevalences as measured in EMIS are approximately twice the estimates based on existing estimates. Conclusions Comparison of diagnosed HIV prevalence as measured in EMIS with pre-existing estimates based on biological measurements using varied sampling frames (e.g. Respondent Driven Sampling, Time and Location Sampling demonstrates a high correlation and suggests similar selection biases from both types of studies. For comparison with modelled estimates the self-selection bias of the Internet survey with increased participation of men diagnosed with HIV has to be
Lü, Boqiang; Shi, Xiaoding; Zhong, Xin
2018-06-01
We are concerned with the Cauchy problem of the two-dimensional (2D) nonhomogeneous incompressible Navier–Stokes equations with vacuum as far-field density. It is proved that if the initial density decays not too slow at infinity, the 2D Cauchy problem of the density-dependent Navier–Stokes equations on the whole space admits a unique global strong solution. Note that the initial data can be arbitrarily large and the initial density can contain vacuum states and even have compact support. Furthermore, we also obtain the large time decay rates of the spatial gradients of the velocity and the pressure, which are the same as those of the homogeneous case.
Duerdoth, Ian
2009-01-01
The subject of uncertainties (sometimes called errors) is traditionally taught (to first-year science undergraduates) towards the end of a course on statistics that defines probability as the limit of many trials, and discusses probability distribution functions and the Gaussian distribution. We show how to introduce students to the concepts of…
DEFF Research Database (Denmark)
Heydorn, Kaj; Anglov, Thomas
2002-01-01
Methods recommended by the International Standardization Organisation and Eurachem are not satisfactory for the correct estimation of calibration uncertainty. A novel approach is introduced and tested on actual calibration data for the determination of Pb by ICP-AES. The improved calibration...
Uncertainty calculations made easier
International Nuclear Information System (INIS)
Hogenbirk, A.
1994-07-01
The results are presented of a neutron cross section sensitivity/uncertainty analysis performed in a complicated 2D model of the NET shielding blanket design inside the ITER torus design, surrounded by the cryostat/biological shield as planned for ITER. The calculations were performed with a code system developed at ECN Petten, with which sensitivity/uncertainty calculations become relatively simple. In order to check the deterministic neutron transport calculations (performed with DORT), calculations were also performed with the Monte Carlo code MCNP. Care was taken to model the 2.0 cm wide gaps between two blanket segments, as the neutron flux behind the vacuum vessel is largely determined by neutrons streaming through these gaps. The resulting neutron flux spectra are in excellent agreement up to the end of the cryostat. It is noted, that at this position the attenuation of the neutron flux is about 1 l orders of magnitude. The uncertainty in the energy integrated flux at the beginning of the vacuum vessel and at the beginning of the cryostat was determined in the calculations. The uncertainty appears to be strongly dependent on the exact geometry: if the gaps are filled with stainless steel, the neutron spectrum changes strongly, which results in an uncertainty of 70% in the energy integrated flux at the beginning of the cryostat in the no-gap-geometry, compared to an uncertainty of only 5% in the gap-geometry. Therefore, it is essential to take into account the exact geometry in sensitivity/uncertainty calculations. Furthermore, this study shows that an improvement of the covariance data is urgently needed in order to obtain reliable estimates of the uncertainties in response parameters in neutron transport calculations. (orig./GL)
DEFF Research Database (Denmark)
Nguyen, Daniel Xuyen
This paper presents a model of trade that explains why firms wait to export and why many exporters fail. Firms face uncertain demands that are only realized after the firm enters the destination. The model retools the timing of uncertainty resolution found in productivity heterogeneity models....... This retooling addresses several shortcomings. First, the imperfect correlation of demands reconciles the sales variation observed in and across destinations. Second, since demands for the firm's output are correlated across destinations, a firm can use previously realized demands to forecast unknown demands...... in untested destinations. The option to forecast demands causes firms to delay exporting in order to gather more information about foreign demand. Third, since uncertainty is resolved after entry, many firms enter a destination and then exit after learning that they cannot profit. This prediction reconciles...
Citizen Candidates Under Uncertainty
Eguia, Jon X.
2005-01-01
In this paper we make two contributions to the growing literature on "citizen-candidate" models of representative democracy. First, we add uncertainty about the total vote count. We show that in a society with a large electorate, where the outcome of the election is uncertain and where winning candidates receive a large reward from holding office, there will be a two-candidate equilibrium and no equilibria with a single candidate. Second, we introduce a new concept of equilibrium, which we te...
Justification for recommended uncertainties
International Nuclear Information System (INIS)
Pronyaev, V.G.; Badikov, S.A.; Carlson, A.D.
2007-01-01
The uncertainties obtained in an earlier standards evaluation were considered to be unrealistically low by experts of the US Cross Section Evaluation Working Group (CSEWG). Therefore, the CSEWG Standards Subcommittee replaced the covariance matrices of evaluated uncertainties by expanded percentage errors that were assigned to the data over wide energy groups. There are a number of reasons that might lead to low uncertainties of the evaluated data: Underestimation of the correlations existing between the results of different measurements; The presence of unrecognized systematic uncertainties in the experimental data can lead to biases in the evaluated data as well as to underestimations of the resulting uncertainties; Uncertainties for correlated data cannot only be characterized by percentage uncertainties or variances. Covariances between evaluated value at 0.2 MeV and other points obtained in model (RAC R matrix and PADE2 analytical expansion) and non-model (GMA) fits of the 6 Li(n,t) TEST1 data and the correlation coefficients are presented and covariances between the evaluated value at 0.045 MeV and other points (along the line or column of the matrix) as obtained in EDA and RAC R matrix fits of the data available for reactions that pass through the formation of the 7 Li system are discussed. The GMA fit with the GMA database is shown for comparison. The following diagrams are discussed: Percentage uncertainties of the evaluated cross section for the 6 Li(n,t) reaction and the for the 235 U(n,f) reaction; estimation given by CSEWG experts; GMA result with full GMA database, including experimental data for the 6 Li(n,t), 6 Li(n,n) and 6 Li(n,total) reactions; uncertainties in the GMA combined fit for the standards; EDA and RAC R matrix results, respectively. Uncertainties of absolute and 252 Cf fission spectrum averaged cross section measurements, and deviations between measured and evaluated values for 235 U(n,f) cross-sections in the neutron energy range 1
Uncertainty enabled Sensor Observation Services
Cornford, Dan; Williams, Matthew; Bastin, Lucy
2010-05-01
Almost all observations of reality are contaminated with errors, which introduce uncertainties into the actual observation result. Such uncertainty is often held to be a data quality issue, and quantification of this uncertainty is essential for the principled exploitation of the observations. Many existing systems treat data quality in a relatively ad-hoc manner, however if the observation uncertainty is a reliable estimate of the error on the observation with respect to reality then knowledge of this uncertainty enables optimal exploitation of the observations in further processes, or decision making. We would argue that the most natural formalism for expressing uncertainty is Bayesian probability theory. In this work we show how the Open Geospatial Consortium Sensor Observation Service can be implemented to enable the support of explicit uncertainty about observations. We show how the UncertML candidate standard is used to provide a rich and flexible representation of uncertainty in this context. We illustrate this on a data set of user contributed weather data where the INTAMAP interpolation Web Processing Service is used to help estimate the uncertainty on the observations of unknown quality, using observations with known uncertainty properties. We then go on to discuss the implications of uncertainty for a range of existing Open Geospatial Consortium standards including SWE common and Observations and Measurements. We discuss the difficult decisions in the design of the UncertML schema and its relation and usage within existing standards and show various options. We conclude with some indications of the likely future directions for UncertML in the context of Open Geospatial Consortium services.
Sensitivity and uncertainty analysis
Cacuci, Dan G; Navon, Ionel Michael
2005-01-01
As computer-assisted modeling and analysis of physical processes have continued to grow and diversify, sensitivity and uncertainty analyses have become indispensable scientific tools. Sensitivity and Uncertainty Analysis. Volume I: Theory focused on the mathematical underpinnings of two important methods for such analyses: the Adjoint Sensitivity Analysis Procedure and the Global Adjoint Sensitivity Analysis Procedure. This volume concentrates on the practical aspects of performing these analyses for large-scale systems. The applications addressed include two-phase flow problems, a radiative c
Dealing with exploration uncertainties
International Nuclear Information System (INIS)
Capen, E.
1992-01-01
Exploration for oil and gas should fulfill the most adventurous in their quest for excitement and surprise. This paper tries to cover that tall order. The authors will touch on the magnitude of the uncertainty (which is far greater than in most other businesses), the effects of not knowing target sizes very well, how to build uncertainty into analyses naturally, how to tie reserves and chance estimates to economics, and how to look at the portfolio effect of an exploration program. With no apologies, the authors will be using a different language for some readers - the language of uncertainty, which means probability and statistics. These tools allow one to combine largely subjective exploration information with the more analytical data from the engineering and economic side
Zou, Xiao-Duan; Li, Jian-Yang; Clark, Beth Ellen; Golish, Dathon
2018-01-01
The OSIRIS-REx spacecraft, launched in September, 2016, will study the asteroid Bennu and return a sample from its surface to Earth in 2023. Bennu is a near-Earth carbonaceous asteroid which will provide insight into the formation and evolution of the solar system. OSIRIS-REx will first approach Bennu in August 2018 and will study the asteroid for approximately two years before sampling. OSIRIS-REx will develop its photometric model (including Lommel-Seelinger, ROLO, McEwen, Minnaert and Akimov) of Bennu with OCAM and OVIRS during the Detailed Survey mission phase. The model developed during this phase will be used to photometrically correct the OCAM and OVIRS data.Here we present the analysis of the error for the photometric corrections. Based on our testing data sets, we find:1. The model uncertainties is only correct when we use the covariance matrix to calculate, because the parameters are highly correlated.2. No evidence of domination of any parameter in each model.3. And both model error and the data error contribute to the final correction error comparably.4. We tested the uncertainty module on fake and real data sets, and find that model performance depends on the data coverage and data quality. These tests gave us a better understanding of how different model behave in different case.5. L-S model is more reliable than others. Maybe because the simulated data are based on L-S model. However, the test on real data (SPDIF) does show slight advantage of L-S, too. ROLO is not reliable to use when calculating bond albedo. The uncertainty of McEwen model is big in most cases. Akimov performs unphysical on SOPIE 1 data.6. Better use L-S as our default choice, this conclusion is based mainly on our test on SOPIE data and IPDIF.
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
A novel dose uncertainty model and its application for dose verification
International Nuclear Information System (INIS)
Jin Hosang; Chung Heetaek; Liu Chihray; Palta, Jatinder; Suh, Tae-Suk; Kim, Siyong
2005-01-01
Based on statistical approach, a novel dose uncertainty model was introduced considering both nonspatial and spatial dose deviations. Non-space-oriented uncertainty is mainly caused by dosimetric uncertainties, and space-oriented dose uncertainty is the uncertainty caused by all spatial displacements. Assuming these two parts are independent, dose difference between measurement and calculation is a linear combination of nonspatial and spatial dose uncertainties. Two assumptions were made: (1) the relative standard deviation of nonspatial dose uncertainty is inversely proportional to the dose standard deviation σ, and (2) the spatial dose uncertainty is proportional to the gradient of dose. The total dose uncertainty is a quadratic sum of the nonspatial and spatial uncertainties. The uncertainty model provides the tolerance dose bound for comparison between calculation and measurement. In the statistical uncertainty model based on a Gaussian distribution, a confidence level of 3σ theoretically confines 99.74% of measurements within the bound. By setting the confidence limit, the tolerance bound for dose comparison can be made analogous to that of existing dose comparison methods (e.g., a composite distribution analysis, a γ test, a χ evaluation, and a normalized agreement test method). However, the model considers the inherent dose uncertainty characteristics of the test points by taking into account the space-specific history of dose accumulation, while the previous methods apply a single tolerance criterion to the points, although dose uncertainty at each point is significantly different from others. Three types of one-dimensional test dose distributions (a single large field, a composite flat field made by two identical beams, and three-beam intensity-modulated fields) were made to verify the robustness of the model. For each test distribution, the dose bound predicted by the uncertainty model was compared with simulated measurements. The simulated
Robustness of dynamic systems with parameter uncertainties
Balemi, S; Truöl, W
1992-01-01
Robust Control is one of the fastest growing and promising areas of research today. In many practical systems there exist uncertainties which have to be considered in the analysis and design of control systems. In the last decade methods were developed for dealing with dynamic systems with unstructured uncertainties such as HOO_ and £I-optimal control. For systems with parameter uncertainties, the seminal paper of V. L. Kharitonov has triggered a large amount of very promising research. An international workshop dealing with all aspects of robust control was successfully organized by S. P. Bhattacharyya and L. H. Keel in San Antonio, Texas, USA in March 1991. We organized the second international workshop in this area in Ascona, Switzer land in April 1992. However, this second workshop was restricted to robust control of dynamic systems with parameter uncertainties with the objective to concentrate on some aspects of robust control. This book contains a collection of papers presented at the International W...
Stereo-particle image velocimetry uncertainty quantification
International Nuclear Information System (INIS)
Bhattacharya, Sayantan; Vlachos, Pavlos P; Charonko, John J
2017-01-01
Particle image velocimetry (PIV) measurements are subject to multiple elemental error sources and thus estimating overall measurement uncertainty is challenging. Recent advances have led to a posteriori uncertainty estimation methods for planar two-component PIV. However, no complete methodology exists for uncertainty quantification in stereo PIV. In the current work, a comprehensive framework is presented to quantify the uncertainty stemming from stereo registration error and combine it with the underlying planar velocity uncertainties. The disparity in particle locations of the dewarped images is used to estimate the positional uncertainty of the world coordinate system, which is then propagated to the uncertainty in the calibration mapping function coefficients. Next, the calibration uncertainty is combined with the planar uncertainty fields of the individual cameras through an uncertainty propagation equation and uncertainty estimates are obtained for all three velocity components. The methodology was tested with synthetic stereo PIV data for different light sheet thicknesses, with and without registration error, and also validated with an experimental vortex ring case from 2014 PIV challenge. Thorough sensitivity analysis was performed to assess the relative impact of the various parameters to the overall uncertainty. The results suggest that in absence of any disparity, the stereo PIV uncertainty prediction method is more sensitive to the planar uncertainty estimates than to the angle uncertainty, although the latter is not negligible for non-zero disparity. Overall the presented uncertainty quantification framework showed excellent agreement between the error and uncertainty RMS values for both the synthetic and the experimental data and demonstrated reliable uncertainty prediction coverage. This stereo PIV uncertainty quantification framework provides the first comprehensive treatment on the subject and potentially lays foundations applicable to volumetric
Uncertainties on lung doses from inhaled plutonium.
Puncher, Matthew; Birchall, Alan; Bull, Richard K
2011-10-01
In a recent epidemiological study, Bayesian uncertainties on lung doses have been calculated to determine lung cancer risk from occupational exposures to plutonium. These calculations used a revised version of the Human Respiratory Tract Model (HRTM) published by the ICRP. In addition to the Bayesian analyses, which give probability distributions of doses, point estimates of doses (single estimates without uncertainty) were also provided for that study using the existing HRTM as it is described in ICRP Publication 66; these are to be used in a preliminary analysis of risk. To infer the differences between the point estimates and Bayesian uncertainty analyses, this paper applies the methodology to former workers of the United Kingdom Atomic Energy Authority (UKAEA), who constituted a subset of the study cohort. The resulting probability distributions of lung doses are compared with the point estimates obtained for each worker. It is shown that mean posterior lung doses are around two- to fourfold higher than point estimates and that uncertainties on doses vary over a wide range, greater than two orders of magnitude for some lung tissues. In addition, we demonstrate that uncertainties on the parameter values, rather than the model structure, are largely responsible for these effects. Of these it appears to be the parameters describing absorption from the lungs to blood that have the greatest impact on estimates of lung doses from urine bioassay. Therefore, accurate determination of the chemical form of inhaled plutonium and the absorption parameter values for these materials is important for obtaining reliable estimates of lung doses and hence risk from occupational exposures to plutonium.
Uncertainty analysis techniques
International Nuclear Information System (INIS)
Marivoet, J.; Saltelli, A.; Cadelli, N.
1987-01-01
The origin of the uncertainty affecting Performance Assessments, as well as their propagation to dose and risk results is discussed. The analysis is focused essentially on the uncertainties introduced by the input parameters, the values of which may range over some orders of magnitude and may be given as probability distribution function. The paper briefly reviews the existing sampling techniques used for Monte Carlo simulations and the methods for characterizing the output curves, determining their convergence and confidence limits. Annual doses, expectation values of the doses and risks are computed for a particular case of a possible repository in clay, in order to illustrate the significance of such output characteristics as the mean, the logarithmic mean and the median as well as their ratios. The report concludes that provisionally, due to its better robustness, such estimation as the 90th percentile may be substituted to the arithmetic mean for comparison of the estimated doses with acceptance criteria. In any case, the results obtained through Uncertainty Analyses must be interpreted with caution as long as input data distribution functions are not derived from experiments reasonably reproducing the situation in a well characterized repository and site
Risk uncertainty analysis methods for NUREG-1150
International Nuclear Information System (INIS)
Benjamin, A.S.; Boyd, G.J.
1987-01-01
Evaluation and display of risk uncertainties for NUREG-1150 constitute a principal focus of the Severe Accident Risk Rebaselining/Risk Reduction Program (SARRP). Some of the principal objectives of the uncertainty evaluation are: (1) to provide a quantitative estimate that reflects, for those areas considered, a credible and realistic range of uncertainty in risk; (2) to rank the various sources of uncertainty with respect to their importance for various measures of risk; and (3) to characterize the state of understanding of each aspect of the risk assessment for which major uncertainties exist. This paper describes the methods developed to fulfill these objectives
Scherer, Laura; Venkatesh, Aranya; Karuppiah, Ramkumar; Pfister, Stephan
2015-04-21
Physical water scarcities can be described by water stress indices. These are often determined at an annual scale and a watershed level; however, such scales mask seasonal fluctuations and spatial heterogeneity within a watershed. In order to account for this level of detail, first and foremost, water availability estimates must be improved and refined. State-of-the-art global hydrological models such as WaterGAP and UNH/GRDC have previously been unable to reliably reflect water availability at the subbasin scale. In this study, the Soil and Water Assessment Tool (SWAT) was tested as an alternative to global models, using the case study of the Mississippi watershed. While SWAT clearly outperformed the global models at the scale of a large watershed, it was judged to be unsuitable for global scale simulations due to the high calibration efforts required. The results obtained in this study show that global assessments miss out on key aspects related to upstream/downstream relations and monthly fluctuations, which are important both for the characterization of water scarcity in the Mississippi watershed and for water footprints. Especially in arid regions, where scarcity is high, these models provide unsatisfying results.
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
Investment, regulation, and uncertainty
Smyth, Stuart J; McDonald, Jillian; Falck-Zepeda, Jose
2014-01-01
As with any technological innovation, time refines the technology, improving upon the original version of the innovative product. The initial GM crops had single traits for either herbicide tolerance or insect resistance. Current varieties have both of these traits stacked together and in many cases other abiotic and biotic traits have also been stacked. This innovation requires investment. While this is relatively straight forward, certain conditions need to exist such that investments can be facilitated. The principle requirement for investment is that regulatory frameworks render consistent and timely decisions. If the certainty of regulatory outcomes weakens, the potential for changes in investment patterns increases. This article provides a summary background to the leading plant breeding technologies that are either currently being used to develop new crop varieties or are in the pipeline to be applied to plant breeding within the next few years. Challenges for existing regulatory systems are highlighted. Utilizing an option value approach from investment literature, an assessment of uncertainty regarding the regulatory approval for these varying techniques is undertaken. This research highlights which technology development options have the greatest degree of uncertainty and hence, which ones might be expected to see an investment decline. PMID:24499745
International Nuclear Information System (INIS)
Landsberg, P.T.
1990-01-01
This paper explores how the quantum mechanics uncertainty relation can be considered to result from measurements. A distinction is drawn between the uncertainties obtained by scrutinising experiments and the standard deviation type of uncertainty definition used in quantum formalism. (UK)
Added Value of uncertainty Estimates of SOurce term and Meteorology (AVESOME)
DEFF Research Database (Denmark)
Sørensen, Jens Havskov; Schönfeldt, Fredrik; Sigg, Robert
In the early phase of a nuclear accident, two large sources of uncertainty exist: one related to the source term and one associated with the meteorological data. Operational methods are being developed in AVESOME for quantitative estimation of uncertainties in atmospheric dispersion prediction.......g. at national meteorological services, the proposed methodology is feasible for real-time use, thereby adding value to decision support. In the recent NKS-B projects MUD, FAUNA and MESO, the implications of meteorological uncertainties for nuclear emergency preparedness and management have been studied...... uncertainty in atmospheric dispersion model forecasting stemming from both the source term and the meteorological data is examined. Ways to implement the uncertainties of forecasting in DSSs, and the impacts on real-time emergency management are described. The proposed methodology allows for efficient real...
International Nuclear Information System (INIS)
Horton, S.G.
1984-01-01
The author presents a system planning perspective on how Ontario Hydro is viewing the future, and where nuclear power fits into that future. Before the 1980s Ontario experienced a steady seven percent per year growth in power demand. Shifting patterns of energy demand have made planning much more difficult. In the early 80s growth in demand fell short of predictions. It is hard to tell what level of demand to plan for in the future. With respect to any energy option, a utility planner or board of directors would want to know when it will be delivered, what it will cost when it is delivered, what it will cost to operate, how long it will last as an economic energy producer, and how all of these factors will be affected by future changes. Ontario Hydro's studies show that nuclear power continues to be the preferred option for large blocks of base load capacity. By 1996 Ontario Hydro will have saved about 10 billion 1983 dollars by using nuclear power. The utility continues to study both sides of the supply-demand equation, looking at conservation as an alternative to constructing new generating facilities and attempting to become aware of shifts in demand trends as soon as they happen
Uncertainties in Nuclear Proliferation Modeling
International Nuclear Information System (INIS)
Kim, Chul Min; Yim, Man-Sung; Park, Hyeon Seok
2015-01-01
There have been various efforts in the research community to understand the determinants of nuclear proliferation and develop quantitative tools to predict nuclear proliferation events. Such systematic approaches have shown the possibility to provide warning for the international community to prevent nuclear proliferation activities. However, there are still large debates for the robustness of the actual effect of determinants and projection results. Some studies have shown that several factors can cause uncertainties in previous quantitative nuclear proliferation modeling works. This paper analyzes the uncertainties in the past approaches and suggests future works in the view of proliferation history, analysis methods, and variable selection. The research community still lacks the knowledge for the source of uncertainty in current models. Fundamental problems in modeling will remain even other advanced modeling method is developed. Before starting to develop fancy model based on the time dependent proliferation determinants' hypothesis, using graph theory, etc., it is important to analyze the uncertainty of current model to solve the fundamental problems of nuclear proliferation modeling. The uncertainty from different proliferation history coding is small. Serious problems are from limited analysis methods and correlation among the variables. Problems in regression analysis and survival analysis cause huge uncertainties when using the same dataset, which decreases the robustness of the result. Inaccurate variables for nuclear proliferation also increase the uncertainty. To overcome these problems, further quantitative research should focus on analyzing the knowledge suggested on the qualitative nuclear proliferation studies
Model uncertainties in top-quark physics
Seidel, Markus
2014-01-01
The ATLAS and CMS collaborations at the Large Hadron Collider (LHC) are studying the top quark in pp collisions at 7 and 8 TeV. Due to the large integrated luminosity, precision measurements of production cross-sections and properties are often limited by systematic uncertainties. An overview of the modeling uncertainties for simulated events is given in this report.
The uncertainties in estimating measurement uncertainties
International Nuclear Information System (INIS)
Clark, J.P.; Shull, A.H.
1994-01-01
All measurements include some error. Whether measurements are used for accountability, environmental programs or process support, they are of little value unless accompanied by an estimate of the measurements uncertainty. This fact is often overlooked by the individuals who need measurements to make decisions. This paper will discuss the concepts of measurement, measurements errors (accuracy or bias and precision or random error), physical and error models, measurement control programs, examples of measurement uncertainty, and uncertainty as related to measurement quality. Measurements are comparisons of unknowns to knowns, estimates of some true value plus uncertainty; and are no better than the standards to which they are compared. Direct comparisons of unknowns that match the composition of known standards will normally have small uncertainties. In the real world, measurements usually involve indirect comparisons of significantly different materials (e.g., measuring a physical property of a chemical element in a sample having a matrix that is significantly different from calibration standards matrix). Consequently, there are many sources of error involved in measurement processes that can affect the quality of a measurement and its associated uncertainty. How the uncertainty estimates are determined and what they mean is as important as the measurement. The process of calculating the uncertainty of a measurement itself has uncertainties that must be handled correctly. Examples of chemistry laboratory measurement will be reviewed in this report and recommendations made for improving measurement uncertainties
Dong, Zhaomin; Liu, Yanju; Duan, Luchun; Bekele, Dawit; Naidu, Ravi
2015-12-01
Addressing uncertainties in human health risk assessment is a critical issue when evaluating the effects of contaminants on public health. A range of uncertainties exist through the source-to-outcome continuum, including exposure assessment, hazard and risk characterisation. While various strategies have been applied to characterising uncertainty, classical approaches largely rely on how to maximise the available resources. Expert judgement, defaults and tools for characterising quantitative uncertainty attempt to fill the gap between data and regulation requirements. The experiences of researching 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) illustrated uncertainty sources and how to maximise available information to determine uncertainties, and thereby provide an 'adequate' protection to contaminant exposure. As regulatory requirements and recurring issues increase, the assessment of complex scenarios involving a large number of chemicals requires more sophisticated tools. Recent advances in exposure and toxicology science provide a large data set for environmental contaminants and public health. In particular, biomonitoring information, in vitro data streams and computational toxicology are the crucial factors in the NexGen risk assessment, as well as uncertainties minimisation. Although in this review we cannot yet predict how the exposure science and modern toxicology will develop in the long-term, current techniques from emerging science can be integrated to improve decision-making. Copyright © 2015 Elsevier Ltd. All rights reserved.
Uncertainty Quantification for a Sailing Yacht Hull, Using Multi-Fidelity Kriging
de Baar, J.H.S.; Roberts, S; Dwight, R.P.; Mallol, B.
2015-01-01
Uncertainty Quantication (UQ) for CFD-based ship design can require a large number of simulations, resulting in signicant overall computational cost. Presently, we use an existing method, multi-delity Kriging, to reduce the number of simulations required for the UQ analysis of the performance of a
Geological-structural models used in SR 97. Uncertainty analysis
Energy Technology Data Exchange (ETDEWEB)
Saksa, P.; Nummela, J. [FINTACT Oy (Finland)
1998-10-01
The uncertainty of geological-structural models was studied for the three sites in SR 97, called Aberg, Beberg and Ceberg. The evaluation covered both regional and site scale models, the emphasis being placed on fracture zones in the site scale. Uncertainty is a natural feature of all geoscientific investigations. It originates from measurements (errors in data, sampling limitations, scale variation) and conceptualisation (structural geometries and properties, ambiguous geometric or parametric solutions) to name the major ones. The structures of A-, B- and Ceberg are fracture zones of varying types. No major differences in the conceptualisation between the sites were noted. One source of uncertainty in the site models is the non-existence of fracture and zone information in the scale from 10 to 300 - 1000 m. At Aberg the development of the regional model has been performed very thoroughly. At the site scale one major source of uncertainty is that a clear definition of the target area is missing. Structures encountered in the boreholes are well explained and an interdisciplinary approach in interpretation have taken place. Beberg and Ceberg regional models contain relatively large uncertainties due to the investigation methodology and experience available at that time. In site scale six additional structures were proposed both to Beberg and Ceberg to variant analysis of these sites. Both sites include uncertainty in the form of many non-interpreted fractured sections along the boreholes. Statistical analysis gives high occurrences of structures for all three sites: typically 20 - 30 structures/km{sup 3}. Aberg has highest structural frequency, Beberg comes next and Ceberg has the lowest. The borehole configuration, orientations and surveying goals were inspected to find whether preferences or factors causing bias were present. Data from Aberg supports the conclusion that Aespoe sub volume would be an anomalously fractured, tectonised unit of its own. This means that
Geological-structural models used in SR 97. Uncertainty analysis
International Nuclear Information System (INIS)
Saksa, P.; Nummela, J.
1998-10-01
The uncertainty of geological-structural models was studied for the three sites in SR 97, called Aberg, Beberg and Ceberg. The evaluation covered both regional and site scale models, the emphasis being placed on fracture zones in the site scale. Uncertainty is a natural feature of all geoscientific investigations. It originates from measurements (errors in data, sampling limitations, scale variation) and conceptualisation (structural geometries and properties, ambiguous geometric or parametric solutions) to name the major ones. The structures of A-, B- and Ceberg are fracture zones of varying types. No major differences in the conceptualisation between the sites were noted. One source of uncertainty in the site models is the non-existence of fracture and zone information in the scale from 10 to 300 - 1000 m. At Aberg the development of the regional model has been performed very thoroughly. At the site scale one major source of uncertainty is that a clear definition of the target area is missing. Structures encountered in the boreholes are well explained and an interdisciplinary approach in interpretation have taken place. Beberg and Ceberg regional models contain relatively large uncertainties due to the investigation methodology and experience available at that time. In site scale six additional structures were proposed both to Beberg and Ceberg to variant analysis of these sites. Both sites include uncertainty in the form of many non-interpreted fractured sections along the boreholes. Statistical analysis gives high occurrences of structures for all three sites: typically 20 - 30 structures/km 3 . Aberg has highest structural frequency, Beberg comes next and Ceberg has the lowest. The borehole configuration, orientations and surveying goals were inspected to find whether preferences or factors causing bias were present. Data from Aberg supports the conclusion that Aespoe sub volume would be an anomalously fractured, tectonised unit of its own. This means that the
Energy Technology Data Exchange (ETDEWEB)
Kitanidis, Peter [Stanford Univ., CA (United States)
2016-04-30
As large-scale, commercial storage projects become operational, the problem of utilizing information from diverse sources becomes more critically important. In this project, we developed, tested, and applied an advanced joint data inversion system for CO_{2} storage modeling with large data sets for use in site characterization and real-time monitoring. Emphasis was on the development of advanced and efficient computational algorithms for joint inversion of hydro-geophysical data, coupled with state-of-the-art forward process simulations. The developed system consists of (1) inversion tools using characterization data, such as 3D seismic survey (amplitude images), borehole log and core data, as well as hydraulic, tracer and thermal tests before CO_{2} injection, (2) joint inversion tools for updating the geologic model with the distribution of rock properties, thus reducing uncertainty, using hydro-geophysical monitoring data, and (3) highly efficient algorithms for directly solving the dense or sparse linear algebra systems derived from the joint inversion. The system combines methods from stochastic analysis, fast linear algebra, and high performance computing. The developed joint inversion tools have been tested through synthetic CO_{2} storage examples.
Framework for managing uncertainty in property projects
Reymen, I.M.M.J.; Dewulf, G.P.M.R.; Blokpoel, S.B.
2008-01-01
A primary task of property development (or real estate development, RED) is making assessments and managing risks and uncertainties. Property managers cope with a wide range of uncertainties, particularly in the early project phases. Although the existing literature addresses the management of
Predictive uncertainty in auditory sequence processing
DEFF Research Database (Denmark)
Hansen, Niels Chr.; Pearce, Marcus T
2014-01-01
in a melodic sequence (inferred uncertainty). Finally, we simulate listeners' perception of expectedness and uncertainty using computational models of auditory expectation. A detailed model comparison indicates which model parameters maximize fit to the data and how they compare to existing models...
Uncertainty in social dilemmas
Kwaadsteniet, Erik Willem de
2007-01-01
This dissertation focuses on social dilemmas, and more specifically, on environmental uncertainty in these dilemmas. Real-life social dilemma situations are often characterized by uncertainty. For example, fishermen mostly do not know the exact size of the fish population (i.e., resource size uncertainty). Several researchers have therefore asked themselves the question as to how such uncertainty influences people’s choice behavior. These researchers have repeatedly concluded that uncertainty...
Lebesgue Sets Immeasurable Existence
Directory of Open Access Journals (Sweden)
Diana Marginean Petrovai
2012-12-01
Full Text Available It is well known that the notion of measure and integral were released early enough in close connection with practical problems of measuring of geometric ﬁgures. Notion of measure was outlined in the early 20th century through H. Lebesgue’s research, founder of the modern theory of measure and integral. It was developed concurrently a technique of integration of functions. Gradually it was formed a speciﬁc area todaycalled the measure and integral theory. Essential contributions to building this theory was made by a large number of mathematicians: C. Carathodory, J. Radon, O. Nikodym, S. Bochner, J. Pettis, P. Halmos and many others. In the following we present several abstract sets, classes of sets. There exists the sets which are not Lebesgue measurable and the sets which are Lebesgue measurable but are not Borel measurable. Hence B ⊂ L ⊂ P(X.
Ubertini, Pietro; Sidoli, L.; Sguera, V.; Bazzano, A.
2009-12-01
Supergiant Fast X-ray Transients (SFXTs) are one of the most interesting (and unexpected) results of the INTEGRAL mission. They are a new class of HMXBs displaying short hard X-ray outbursts (duration less tha a day) characterized by fast flares (few hours timescale) and large dinamic range (10E3-10E4). The physical mechanism driving their peculiar behaviour is still unclear and highly debated: some models involve the structure of the supergiant companion donor wind (likely clumpy, in a spherical or non spherical geometry) and the orbital properties (wide separation with eccentric or circular orbit), while others involve the properties of the neutron star compact object and invoke very low magnetic field values (B 1E14 G, magnetars). The picture is still highly unclear from the observational point of view as well: no cyclotron lines have been detected in the spectra, thus the strength of the neutron star magnetic field is unknown. Orbital periods have been measured in only 4 systems, spanning from 3.3 days to 165 days. Even the duty cycle seems to be quite different from source to source. The Energetic X-ray Imaging Survey Telescope (EXIST), with its hard X-ray all-sky survey and large improved limiting sensitivity, will allow us to get a clearer picture of SFXTs. A complete census of their number is essential to enlarge the sample. A long term and continuous as possible X-ray monitoring is crucial to -(1) obtain the duty cycle, -(2 )investigate their unknown orbital properties (separation, orbital period, eccentricity),- (3) to completely cover the whole outburst activity, (4)-to search for cyclotron lines in the high energy spectra. EXIST observations will provide crucial informations to test the different models and shed light on the peculiar behaviour of SFXTs.
International Nuclear Information System (INIS)
Ghione, Alberto; Noel, Brigitte; Vinai, Paolo; Demazière, Christophe
2017-01-01
Highlights: • A station blackout scenario in the Jules Horowitz Reactor is analyzed using CATHARE. • Input and model uncertainties relevant to the transient, are considered. • A statistical methodology for the propagation of the uncertainties is applied. • No safety criteria are exceeded and sufficiently large safety margins are estimated. • The most influential uncertainties are determined with a sensitivity analysis. - Abstract: An uncertainty and sensitivity analysis for the simulation of a station blackout scenario in the Jules Horowitz Reactor (JHR) is presented. The JHR is a new material testing reactor under construction at CEA on the Cadarache site, France. The thermal-hydraulic system code CATHARE is applied to investigate the response of the reactor system to the scenario. The uncertainty and sensitivity study was based on a statistical methodology for code uncertainty propagation, and the ‘Uncertainty and Sensitivity’ platform URANIE was used. Accordingly, the input uncertainties relevant to the transient, were identified, quantified, and propagated to the code output. The results show that the safety criteria are not exceeded and sufficiently large safety margins exist. In addition, the most influential input uncertainties on the safety parameters were found by making use of a sensitivity analysis.
Propagation of dynamic measurement uncertainty
International Nuclear Information System (INIS)
Hessling, J P
2011-01-01
The time-dependent measurement uncertainty has been evaluated in a number of recent publications, starting from a known uncertain dynamic model. This could be defined as the 'downward' propagation of uncertainty from the model to the targeted measurement. The propagation of uncertainty 'upward' from the calibration experiment to a dynamic model traditionally belongs to system identification. The use of different representations (time, frequency, etc) is ubiquitous in dynamic measurement analyses. An expression of uncertainty in dynamic measurements is formulated for the first time in this paper independent of representation, joining upward as well as downward propagation. For applications in metrology, the high quality of the characterization may be prohibitive for any reasonably large and robust model to pass the whiteness test. This test is therefore relaxed by not directly requiring small systematic model errors in comparison to the randomness of the characterization. Instead, the systematic error of the dynamic model is propagated to the uncertainty of the measurand, analogously but differently to how stochastic contributions are propagated. The pass criterion of the model is thereby transferred from the identification to acceptance of the total accumulated uncertainty of the measurand. This increases the relevance of the test of the model as it relates to its final use rather than the quality of the calibration. The propagation of uncertainty hence includes the propagation of systematic model errors. For illustration, the 'upward' propagation of uncertainty is applied to determine if an appliance box is damaged in an earthquake experiment. In this case, relaxation of the whiteness test was required to reach a conclusive result
On the uncertainty principle. V
International Nuclear Information System (INIS)
Halpern, O.
1976-01-01
The treatment of ideal experiments connected with the uncertainty principle is continued. The author analyzes successively measurements of momentum and position, and discusses the common reason why the results in all cases differ from the conventional ones. A similar difference exists for the measurement of field strengths. The interpretation given by Weizsaecker, who tried to interpret Bohr's complementarity principle by introducing a multi-valued logic is analyzed. The treatment of the uncertainty principle ΔE Δt is deferred to a later paper as is the interpretation of the method of variation of constants. Every ideal experiment discussed shows various lower limits for the value of the uncertainty product which limits depend on the experimental arrangement and are always (considerably) larger than h. (Auth.)
Inventories and sales uncertainty\\ud
Caglayan, M.; Maioli, S.; Mateut, S.
2011-01-01
We investigate the empirical linkages between sales uncertainty and firms´ inventory investment behavior while controlling for firms´ financial strength. Using large panels of manufacturing firms from several European countries we find that higher sales uncertainty leads to larger stocks of inventories. We also identify an indirect effect of sales uncertainty on inventory accumulation through the financial strength of firms. Our results provide evidence that financial strength mitigates the a...
Estimation of sampling error uncertainties in observed surface air temperature change in China
Hua, Wei; Shen, Samuel S. P.; Weithmann, Alexander; Wang, Huijun
2017-08-01
This study examines the sampling error uncertainties in the monthly surface air temperature (SAT) change in China over recent decades, focusing on the uncertainties of gridded data, national averages, and linear trends. Results indicate that large sampling error variances appear at the station-sparse area of northern and western China with the maximum value exceeding 2.0 K2 while small sampling error variances are found at the station-dense area of southern and eastern China with most grid values being less than 0.05 K2. In general, the negative temperature existed in each month prior to the 1980s, and a warming in temperature began thereafter, which accelerated in the early and mid-1990s. The increasing trend in the SAT series was observed for each month of the year with the largest temperature increase and highest uncertainty of 0.51 ± 0.29 K (10 year)-1 occurring in February and the weakest trend and smallest uncertainty of 0.13 ± 0.07 K (10 year)-1 in August. The sampling error uncertainties in the national average annual mean SAT series are not sufficiently large to alter the conclusion of the persistent warming in China. In addition, the sampling error uncertainties in the SAT series show a clear variation compared with other uncertainty estimation methods, which is a plausible reason for the inconsistent variations between our estimate and other studies during this period.
Uncertainty analysis of LBLOCA for Advanced Heavy Water Reactor
International Nuclear Information System (INIS)
Srivastava, A.; Lele, H.G.; Ghosh, A.K.; Kushwaha, H.S.
2008-01-01
The main objective of safety analysis is to demonstrate in a robust way that all safety requirements are met, i.e. sufficient margins exist between real values of important parameters and their threshold values at which damage of the barriers against release of radioactivity would occur. As stated in the IAEA Safety Requirements for Design of NPPs 'a safety analysis of the plant design shall be conducted in which methods of both deterministic and probabilistic analysis shall be applied'. It is required that 'the computer programs, analytical methods and plant models used in the safety analysis shall be verified and validated, and adequate consideration shall be given to uncertainties'. Uncertainties are present in calculations due to the computer codes, initial and boundary conditions, plant state, fuel parameters, scaling and numerical solution algorithm. All conservative approaches, still widely used, were introduced to cover uncertainties due to limited capability for modelling and understanding of physical phenomena at the early stages of safety analysis. The results obtained by this approach are quite unrealistic and the level of conservatism is not fully known. Another approach is the use of Best Estimate (BE) codes with realistic initial and boundary conditions. If this approach is selected, it should be based on statistically combined uncertainties for plant initial and boundary conditions, assumptions and code models. The current trends are going into direction of the best estimate code with some conservative assumptions of the system with realistic input data with uncertainty analysis. The BE analysis with evaluation of uncertainties offers, in addition, a way to quantify the existing plant safety margins. Its broader use in the future is therefore envisaged, even though it is not always feasible because of the difficulty of quantifying code uncertainties with sufficiently narrow range for every phenomenon and for each accident sequence. In this paper
Incorporating Forecast Uncertainty in Utility Control Center
Energy Technology Data Exchange (ETDEWEB)
Makarov, Yuri V.; Etingov, Pavel V.; Ma, Jian
2014-07-09
Uncertainties in forecasting the output of intermittent resources such as wind and solar generation, as well as system loads are not adequately reflected in existing industry-grade tools used for transmission system management, generation commitment, dispatch and market operation. There are other sources of uncertainty such as uninstructed deviations of conventional generators from their dispatch set points, generator forced outages and failures to start up, load drops, losses of major transmission facilities and frequency variation. These uncertainties can cause deviations from the system balance, which sometimes require inefficient and costly last minute solutions in the near real-time timeframe. This Chapter considers sources of uncertainty and variability, overall system uncertainty model, a possible plan for transition from deterministic to probabilistic methods in planning and operations, and two examples of uncertainty-based fools for grid operations.This chapter is based on work conducted at the Pacific Northwest National Laboratory (PNNL)
Uncertainty in spatial planning proceedings
Directory of Open Access Journals (Sweden)
Aleš Mlakar
2009-01-01
Full Text Available Uncertainty is distinctive of spatial planning as it arises from the necessity to co-ordinate the various interests within the area, from the urgency of adopting spatial planning decisions, the complexity of the environment, physical space and society, addressing the uncertainty of the future and from the uncertainty of actually making the right decision. Response to uncertainty is a series of measures that mitigate the effects of uncertainty itself. These measures are based on two fundamental principles – standardization and optimization. The measures are related to knowledge enhancement and spatial planning comprehension, in the legal regulation of changes, in the existence of spatial planning as a means of different interests co-ordination, in the active planning and the constructive resolution of current spatial problems, in the integration of spatial planning and the environmental protection process, in the implementation of the analysis as the foundation of spatial planners activities, in the methods of thinking outside the parameters, in forming clear spatial concepts and in creating a transparent management spatial system and also in the enforcement the participatory processes.
Reporting and analyzing statistical uncertainties in Monte Carlo-based treatment planning
International Nuclear Information System (INIS)
Chetty, Indrin J.; Rosu, Mihaela; Kessler, Marc L.; Fraass, Benedick A.; Haken, Randall K. ten; Kong, Feng-Ming; McShan, Daniel L.
2006-01-01
Purpose: To investigate methods of reporting and analyzing statistical uncertainties in doses to targets and normal tissues in Monte Carlo (MC)-based treatment planning. Methods and Materials: Methods for quantifying statistical uncertainties in dose, such as uncertainty specification to specific dose points, or to volume-based regions, were analyzed in MC-based treatment planning for 5 lung cancer patients. The effect of statistical uncertainties on target and normal tissue dose indices was evaluated. The concept of uncertainty volume histograms for targets and organs at risk was examined, along with its utility, in conjunction with dose volume histograms, in assessing the acceptability of the statistical precision in dose distributions. The uncertainty evaluation tools were extended to four-dimensional planning for application on multiple instances of the patient geometry. All calculations were performed using the Dose Planning Method MC code. Results: For targets, generalized equivalent uniform doses and mean target doses converged at 150 million simulated histories, corresponding to relative uncertainties of less than 2% in the mean target doses. For the normal lung tissue (a volume-effect organ), mean lung dose and normal tissue complication probability converged at 150 million histories despite the large range in the relative organ uncertainty volume histograms. For 'serial' normal tissues such as the spinal cord, large fluctuations exist in point dose relative uncertainties. Conclusions: The tools presented here provide useful means for evaluating statistical precision in MC-based dose distributions. Tradeoffs between uncertainties in doses to targets, volume-effect organs, and 'serial' normal tissues must be considered carefully in determining acceptable levels of statistical precision in MC-computed dose distributions
International Nuclear Information System (INIS)
Peters, H.P.; Hennen, L.
1990-01-01
The authors report on the results of three representative surveys that made a closer inquiry into perceptions and valuations of information and information sources concering Chernobyl. If turns out that the information sources are generally considered little trustworthy. This was generally attributable to the interpretation of the events being tied to attitudes in the atmonic energy issue. The greatest credit was given to television broadcasting. The authors summarize their discourse as follows: There is good reason to interpret the widespread uncertainty after Chernobyl as proof of the fact that large parts of the population are prepared and willing to assume a critical stance towards information and prefer to draw their information from various sources representing different positions. (orig.) [de
Instrument uncertainty predictions
International Nuclear Information System (INIS)
Coutts, D.A.
1991-07-01
The accuracy of measurements and correlations should normally be provided for most experimental activities. The uncertainty is a measure of the accuracy of a stated value or equation. The uncertainty term reflects a combination of instrument errors, modeling limitations, and phenomena understanding deficiencies. This report provides several methodologies to estimate an instrument's uncertainty when used in experimental work. Methods are shown to predict both the pretest and post-test uncertainty
The state of the art of the impact of sampling uncertainty on measurement uncertainty
Leite, V. J.; Oliveira, E. C.
2018-03-01
The measurement uncertainty is a parameter that marks the reliability and can be divided into two large groups: sampling and analytical variations. Analytical uncertainty is a controlled process, performed in the laboratory. The same does not occur with the sampling uncertainty, which, because it faces several obstacles and there is no clarity on how to perform the procedures, has been neglected, although it is admittedly indispensable to the measurement process. This paper aims at describing the state of the art of sampling uncertainty and at assessing its relevance to measurement uncertainty.
Correlated uncertainties in integral data
International Nuclear Information System (INIS)
McCracken, A.K.
1978-01-01
The use of correlated uncertainties in calculational data is shown in cases investigated to lead to a reduction in the uncertainty of calculated quantities of importance to reactor design. It is stressed however that such reductions are likely to be important in a minority of cases of practical interest. The effect of uncertainties in detector cross-sections is considered and is seen to be, in some cases, of equal importance to that in the data used in calculations. Numerical investigations have been limited by the sparse information available on data correlations; some comparisons made of these data reveal quite large inconsistencies for both detector cross-sections and cross-section of interest for reactor calculations
Uncertainty Quantification in Numerical Aerodynamics
Litvinenko, Alexander
2017-05-16
We consider uncertainty quantification problem in aerodynamic simulations. We identify input uncertainties, classify them, suggest an appropriate statistical model and, finally, estimate propagation of these uncertainties into the solution (pressure, velocity and density fields as well as the lift and drag coefficients). The deterministic problem under consideration is a compressible transonic Reynolds-averaged Navier-Strokes flow around an airfoil with random/uncertain data. Input uncertainties include: uncertain angle of attack, the Mach number, random perturbations in the airfoil geometry, mesh, shock location, turbulence model and parameters of this turbulence model. This problem requires efficient numerical/statistical methods since it is computationally expensive, especially for the uncertainties caused by random geometry variations which involve a large number of variables. In numerical section we compares five methods, including quasi-Monte Carlo quadrature, polynomial chaos with coefficients determined by sparse quadrature and gradient-enhanced version of Kriging, radial basis functions and point collocation polynomial chaos, in their efficiency in estimating statistics of aerodynamic performance upon random perturbation to the airfoil geometry [D.Liu et al \\'17]. For modeling we used the TAU code, developed in DLR, Germany.
Uncertainty quantification theory, implementation, and applications
Smith, Ralph C
2014-01-01
The field of uncertainty quantification is evolving rapidly because of increasing emphasis on models that require quantified uncertainties for large-scale applications, novel algorithm development, and new computational architectures that facilitate implementation of these algorithms. Uncertainty Quantification: Theory, Implementation, and Applications provides readers with the basic concepts, theory, and algorithms necessary to quantify input and response uncertainties for simulation models arising in a broad range of disciplines. The book begins with a detailed discussion of applications where uncertainty quantification is critical for both scientific understanding and policy. It then covers concepts from probability and statistics, parameter selection techniques, frequentist and Bayesian model calibration, propagation of uncertainties, quantification of model discrepancy, surrogate model construction, and local and global sensitivity analysis. The author maintains a complementary web page where readers ca...
Report on the uncertainty methods study
International Nuclear Information System (INIS)
1998-06-01
The Uncertainty Methods Study (UMS) Group, following a mandate from CSNI, has compared five methods for calculating the uncertainty in the predictions of advanced 'best estimate' thermal-hydraulic codes: the Pisa method (based on extrapolation from integral experiments) and four methods identifying and combining input uncertainties. Three of these, the GRS, IPSN and ENUSA methods, use subjective probability distributions, and one, the AEAT method, performs a bounding analysis. Each method has been used to calculate the uncertainty in specified parameters for the LSTF SB-CL-18 5% cold leg small break LOCA experiment in the ROSA-IV Large Scale Test Facility (LSTF). The uncertainty analysis was conducted essentially blind and the participants did not use experimental measurements from the test as input apart from initial and boundary conditions. Participants calculated uncertainty ranges for experimental parameters including pressurizer pressure, primary circuit inventory and clad temperature (at a specified position) as functions of time
Uncertainty Quantification of Multi-Phase Closures
Energy Technology Data Exchange (ETDEWEB)
Nadiga, Balasubramanya T. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Baglietto, Emilio [Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
2017-10-27
In the ensemble-averaged dispersed phase formulation used for CFD of multiphase ows in nuclear reactor thermohydraulics, closures of interphase transfer of mass, momentum, and energy constitute, by far, the biggest source of error and uncertainty. Reliable estimators of this source of error and uncertainty are currently non-existent. Here, we report on how modern Validation and Uncertainty Quanti cation (VUQ) techniques can be leveraged to not only quantify such errors and uncertainties, but also to uncover (unintended) interactions between closures of di erent phenomena. As such this approach serves as a valuable aide in the research and development of multiphase closures. The joint modeling of lift, drag, wall lubrication, and turbulent dispersion|forces that lead to tranfer of momentum between the liquid and gas phases|is examined in the frame- work of validation of the adiabatic but turbulent experiments of Liu and Banko , 1993. An extensive calibration study is undertaken with a popular combination of closure relations and the popular k-ϵ turbulence model in a Bayesian framework. When a wide range of super cial liquid and gas velocities and void fractions is considered, it is found that this set of closures can be validated against the experimental data only by allowing large variations in the coe cients associated with the closures. We argue that such an extent of variation is a measure of uncertainty induced by the chosen set of closures. We also nd that while mean uid velocity and void fraction pro les are properly t, uctuating uid velocity may or may not be properly t. This aspect needs to be investigated further. The popular set of closures considered contains ad-hoc components and are undesirable from a predictive modeling point of view. Consequently, we next consider improvements that are being developed by the MIT group under CASL and which remove the ad-hoc elements. We use non-intrusive methodologies for sensitivity analysis and calibration (using
Requirements for existing buildings
DEFF Research Database (Denmark)
Thomsen, Kirsten Engelund; Wittchen, Kim Bjarne
This report collects energy performance requirements for existing buildings in European member states by June 2012.......This report collects energy performance requirements for existing buildings in European member states by June 2012....
Greening Existing Tribal Buildings
Guidance about improving sustainability in existing tribal casinos and manufactured homes. Many steps can be taken to make existing buildings greener and healthier. They may also reduce utility and medical costs.
Reusable launch vehicle model uncertainties impact analysis
Chen, Jiaye; Mu, Rongjun; Zhang, Xin; Deng, Yanpeng
2018-03-01
Reusable launch vehicle(RLV) has the typical characteristics of complex aerodynamic shape and propulsion system coupling, and the flight environment is highly complicated and intensely changeable. So its model has large uncertainty, which makes the nominal system quite different from the real system. Therefore, studying the influences caused by the uncertainties on the stability of the control system is of great significance for the controller design. In order to improve the performance of RLV, this paper proposes the approach of analyzing the influence of the model uncertainties. According to the typical RLV, the coupling dynamic and kinematics models are built. Then different factors that cause uncertainties during building the model are analyzed and summed up. After that, the model uncertainties are expressed according to the additive uncertainty model. Choosing the uncertainties matrix's maximum singular values as the boundary model, and selecting the uncertainties matrix's norm to show t how much the uncertainty factors influence is on the stability of the control system . The simulation results illustrate that the inertial factors have the largest influence on the stability of the system, and it is necessary and important to take the model uncertainties into consideration before the designing the controller of this kind of aircraft( like RLV, etc).
Using a Meniscus to Teach Uncertainty in Measurement
Backman, Philip
2008-01-01
I have found that students easily understand that a measurement cannot be exact, but they often seem to lack an understanding of why it is important to know "something" about the magnitude of the uncertainty. This tends to promote an attitude that almost any uncertainty value will do. Such indifference may exist because once an uncertainty is…
International Nuclear Information System (INIS)
Andres, T.H.
2002-05-01
This guide applies to the estimation of uncertainty in quantities calculated by scientific, analysis and design computer programs that fall within the scope of AECL's software quality assurance (SQA) manual. The guide weaves together rational approaches from the SQA manual and three other diverse sources: (a) the CSAU (Code Scaling, Applicability, and Uncertainty) evaluation methodology; (b) the ISO Guide,for the Expression of Uncertainty in Measurement; and (c) the SVA (Systems Variability Analysis) method of risk analysis. This report describes the manner by which random and systematic uncertainties in calculated quantities can be estimated and expressed. Random uncertainty in model output can be attributed to uncertainties of inputs. The propagation of these uncertainties through a computer model can be represented in a variety of ways, including exact calculations, series approximations and Monte Carlo methods. Systematic uncertainties emerge from the development of the computer model itself, through simplifications and conservatisms, for example. These must be estimated and combined with random uncertainties to determine the combined uncertainty in a model output. This report also addresses the method by which uncertainties should be employed in code validation, in order to determine whether experiments and simulations agree, and whether or not a code satisfies the required tolerance for its application. (author)
Energy Technology Data Exchange (ETDEWEB)
Andres, T.H
2002-05-01
This guide applies to the estimation of uncertainty in quantities calculated by scientific, analysis and design computer programs that fall within the scope of AECL's software quality assurance (SQA) manual. The guide weaves together rational approaches from the SQA manual and three other diverse sources: (a) the CSAU (Code Scaling, Applicability, and Uncertainty) evaluation methodology; (b) the ISO Guide,for the Expression of Uncertainty in Measurement; and (c) the SVA (Systems Variability Analysis) method of risk analysis. This report describes the manner by which random and systematic uncertainties in calculated quantities can be estimated and expressed. Random uncertainty in model output can be attributed to uncertainties of inputs. The propagation of these uncertainties through a computer model can be represented in a variety of ways, including exact calculations, series approximations and Monte Carlo methods. Systematic uncertainties emerge from the development of the computer model itself, through simplifications and conservatisms, for example. These must be estimated and combined with random uncertainties to determine the combined uncertainty in a model output. This report also addresses the method by which uncertainties should be employed in code validation, in order to determine whether experiments and simulations agree, and whether or not a code satisfies the required tolerance for its application. (author)
Do Orthopaedic Surgeons Acknowledge Uncertainty?
Teunis, Teun; Janssen, Stein; Guitton, Thierry G; Ring, David; Parisien, Robert
2016-06-01
R(2), 0.29). The relatively low levels of uncertainty among orthopaedic surgeons and confidence bias seem inconsistent with the paucity of definitive evidence. If patients want to be informed of the areas of uncertainty and surgeon-to-surgeon variation relevant to their care, it seems possible that a low recognition of uncertainty and surgeon confidence bias might hinder adequately informing patients, informed decisions, and consent. Moreover, limited recognition of uncertainty is associated with modifiable factors such as confidence bias, trust in orthopaedic evidence base, and statistical understanding. Perhaps improved statistical teaching in residency, journal clubs to improve the critique of evidence and awareness of bias, and acknowledgment of knowledge gaps at courses and conferences might create awareness about existing uncertainties. Level 1, prognostic study.
Uncertainty and Cognitive Control
Directory of Open Access Journals (Sweden)
Faisal eMushtaq
2011-10-01
Full Text Available A growing trend of neuroimaging, behavioural and computational research has investigated the topic of outcome uncertainty in decision-making. Although evidence to date indicates that humans are very effective in learning to adapt to uncertain situations, the nature of the specific cognitive processes involved in the adaptation to uncertainty are still a matter of debate. In this article, we reviewed evidence suggesting that cognitive control processes are at the heart of uncertainty in decision-making contexts. Available evidence suggests that: (1 There is a strong conceptual overlap between the constructs of uncertainty and cognitive control; (2 There is a remarkable overlap between the neural networks associated with uncertainty and the brain networks subserving cognitive control; (3 The perception and estimation of uncertainty might play a key role in monitoring processes and the evaluation of the need for control; (4 Potential interactions between uncertainty and cognitive control might play a significant role in several affective disorders.
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.
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
Limitations of existing web services
Indian Academy of Sciences (India)
First page Back Continue Last page Overview Graphics. Limitations of existing web services. Uploading or downloading large data. Serving too many user from single source. Difficult to provide computer intensive job. Depend on internet and its bandwidth. Security of data in transition. Maintain confidentiality of data ...
Habitable zone dependence on stellar parameter uncertainties
International Nuclear Information System (INIS)
Kane, Stephen R.
2014-01-01
An important property of exoplanetary systems is the extent of the Habitable Zone (HZ), defined as that region where water can exist in a liquid state on the surface of a planet with sufficient atmospheric pressure. Both ground- and space-based observations have revealed a plethora of confirmed exoplanets and exoplanetary candidates, most notably from the Kepler mission using the transit detection technique. Many of these detected planets lie within the predicted HZ of their host star. However, as is the case with the derived properties of the planets themselves, the HZ boundaries depend on how well we understand the host star. Here we quantify the uncertainties of HZ boundaries on the parameter uncertainties of the host star. We examine the distribution of stellar parameter uncertainties from confirmed exoplanet hosts and Kepler candidate hosts and translate these into HZ boundary uncertainties. We apply this to several known systems with an HZ planet to determine the uncertainty in their HZ status.
Habitable zone dependence on stellar parameter uncertainties
Energy Technology Data Exchange (ETDEWEB)
Kane, Stephen R., E-mail: skane@sfsu.edu [Department of Physics and Astronomy, San Francisco State University, 1600 Holloway Avenue, San Francisco, CA 94132 (United States)
2014-02-20
An important property of exoplanetary systems is the extent of the Habitable Zone (HZ), defined as that region where water can exist in a liquid state on the surface of a planet with sufficient atmospheric pressure. Both ground- and space-based observations have revealed a plethora of confirmed exoplanets and exoplanetary candidates, most notably from the Kepler mission using the transit detection technique. Many of these detected planets lie within the predicted HZ of their host star. However, as is the case with the derived properties of the planets themselves, the HZ boundaries depend on how well we understand the host star. Here we quantify the uncertainties of HZ boundaries on the parameter uncertainties of the host star. We examine the distribution of stellar parameter uncertainties from confirmed exoplanet hosts and Kepler candidate hosts and translate these into HZ boundary uncertainties. We apply this to several known systems with an HZ planet to determine the uncertainty in their HZ status.
Quantifying the uncertainty in heritability.
Furlotte, Nicholas A; Heckerman, David; Lippert, Christoph
2014-05-01
The use of mixed models to determine narrow-sense heritability and related quantities such as SNP heritability has received much recent attention. Less attention has been paid to the inherent variability in these estimates. One approach for quantifying variability in estimates of heritability is a frequentist approach, in which heritability is estimated using maximum likelihood and its variance is quantified through an asymptotic normal approximation. An alternative approach is to quantify the uncertainty in heritability through its Bayesian posterior distribution. In this paper, we develop the latter approach, make it computationally efficient and compare it to the frequentist approach. We show theoretically that, for a sufficiently large sample size and intermediate values of heritability, the two approaches provide similar results. Using the Atherosclerosis Risk in Communities cohort, we show empirically that the two approaches can give different results and that the variance/uncertainty can remain large.
International Nuclear Information System (INIS)
Kaul, Dean C.; Egbert, Stephen D.; Woolson, William A.
2005-01-01
In order to avoid the pitfalls that so discredited DS86 and its uncertainty estimates, and to provide DS02 uncertainties that are both defensible and credible, this report not only presents the ensemble uncertainties assembled from uncertainties in individual computational elements and radiation dose components but also describes how these relate to comparisons between observed and computed quantities at critical intervals in the computational process. These comparisons include those between observed and calculated radiation free-field components, where observations include thermal- and fast-neutron activation and gamma-ray thermoluminescence, which are relevant to the estimated systematic uncertainty for DS02. The comparisons also include those between calculated and observed survivor shielding, where the observations consist of biodosimetric measurements for individual survivors, which are relevant to the estimated random uncertainty for DS02. (J.P.N.)
Preliminary Results on Uncertainty Quantification for Pattern Analytics
Energy Technology Data Exchange (ETDEWEB)
Stracuzzi, David John [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Brost, Randolph [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Chen, Maximillian Gene [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Malinas, Rebecca [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Peterson, Matthew Gregor [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Phillips, Cynthia A. [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Robinson, David G. [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Woodbridge, Diane [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
2015-09-01
This report summarizes preliminary research into uncertainty quantification for pattern ana- lytics within the context of the Pattern Analytics to Support High-Performance Exploitation and Reasoning (PANTHER) project. The primary focus of PANTHER was to make large quantities of remote sensing data searchable by analysts. The work described in this re- port adds nuance to both the initial data preparation steps and the search process. Search queries are transformed from does the specified pattern exist in the data? to how certain is the system that the returned results match the query? We show example results for both data processing and search, and discuss a number of possible improvements for each.
Model uncertainty and probability
International Nuclear Information System (INIS)
Parry, G.W.
1994-01-01
This paper discusses the issue of model uncertainty. The use of probability as a measure of an analyst's uncertainty as well as a means of describing random processes has caused some confusion, even though the two uses are representing different types of uncertainty with respect to modeling a system. The importance of maintaining the distinction between the two types is illustrated with a simple example
Uncertainty in artificial intelligence
Kanal, LN
1986-01-01
How to deal with uncertainty is a subject of much controversy in Artificial Intelligence. This volume brings together a wide range of perspectives on uncertainty, many of the contributors being the principal proponents in the controversy.Some of the notable issues which emerge from these papers revolve around an interval-based calculus of uncertainty, the Dempster-Shafer Theory, and probability as the best numeric model for uncertainty. There remain strong dissenting opinions not only about probability but even about the utility of any numeric method in this context.
Uncertainties in hydrogen combustion
International Nuclear Information System (INIS)
Stamps, D.W.; Wong, C.C.; Nelson, L.S.
1988-01-01
Three important areas of hydrogen combustion with uncertainties are identified: high-temperature combustion, flame acceleration and deflagration-to-detonation transition, and aerosol resuspension during hydrogen combustion. The uncertainties associated with high-temperature combustion may affect at least three different accident scenarios: the in-cavity oxidation of combustible gases produced by core-concrete interactions, the direct containment heating hydrogen problem, and the possibility of local detonations. How these uncertainties may affect the sequence of various accident scenarios is discussed and recommendations are made to reduce these uncertainties. 40 references
On treatment of uncertainty in system planning
International Nuclear Information System (INIS)
Flage, R.; Aven, T.
2009-01-01
In system planning and operation considerable efforts and resources are spent to reduce uncertainties, as a part of project management, uncertainty management and safety management. The basic idea seems to be that uncertainties are purely negative and should be reduced. In this paper we challenge this way of thinking, using a common industry practice as an example. In accordance with this industry practice, three uncertainty interval categories are used: ±40% intervals for the feasibility phase, ±30% intervals for the concept development phase and ±20% intervals for the engineering phase. The problem is that such a regime could easily lead to a conservative management regime encouraging the use of existing methods and tools, as new activities and novel solutions and arrangements necessarily mean increased uncertainties. In the paper we suggest an alternative approach based on uncertainty and risk descriptions, but having no predefined uncertainty reduction structures. The approach makes use of risk assessments and economic optimisation tools such as the expected net present value, but acknowledges the need for broad risk management processes which extend beyond the analyses. Different concerns need to be balanced, including economic aspects, uncertainties and risk, and practicability
Sensitivity/uncertainty analysis for the Hiroshima dosimetry reevaluation effort
International Nuclear Information System (INIS)
Broadhead, B.L.; Lillie, R.A.; Pace, J.V. III; Cacuci, D.G.
1987-01-01
Uncertainty estimates and cross correlations by range/survivor location have been obtained for the free-in-air (FIA) tissue kerma for the Hiroshima atomic event. These uncertainties in the FIA kerma include contributions due to various modeling parameters and the basic cross section data and are given at three ground ranges, 700, 1000 and 1500 m. The estimated uncertainties are nearly constant over the given ground ranges and are approximately 27% for the prompt neutron kerma and secondary gamma kerma and 35% for the prompt gamma kerma. The total kerma uncertainty is dominated by the secondary gamma kerma uncertainties which are in turn largely due to the modeling parameter uncertainties
Climate change impact assessment and adaptation under uncertainty
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
Uncertainty propagation in urban hydrology water quality modelling
Torres Matallana, Arturo; Leopold, U.; Heuvelink, G.B.M.
2016-01-01
Uncertainty is often ignored in urban hydrology modelling. Engineering practice typically ignores uncertainties and uncertainty propagation. This can have large impacts, such as the wrong dimensioning of urban drainage systems and the inaccurate estimation of pollution in the environment caused
Uncertainty in social dilemmas
Kwaadsteniet, Erik Willem de
2007-01-01
This dissertation focuses on social dilemmas, and more specifically, on environmental uncertainty in these dilemmas. Real-life social dilemma situations are often characterized by uncertainty. For example, fishermen mostly do not know the exact size of the fish population (i.e., resource size
Uncertainty and Climate Change
Berliner, L. Mark
2003-01-01
Anthropogenic, or human-induced, climate change is a critical issue in science and in the affairs of humankind. Though the target of substantial research, the conclusions of climate change studies remain subject to numerous uncertainties. This article presents a very brief review of the basic arguments regarding anthropogenic climate change with particular emphasis on uncertainty.
Deterministic uncertainty analysis
International Nuclear Information System (INIS)
Worley, B.A.
1987-01-01
Uncertainties of computer results are of primary interest in applications such as high-level waste (HLW) repository performance assessment in which experimental validation is not possible or practical. This work presents an alternate deterministic approach for calculating uncertainties that has the potential to significantly reduce the number of computer runs required for conventional statistical analysis. 7 refs., 1 fig
International Nuclear Information System (INIS)
Depres, B.; Dossantos-Uzarralde, P.
2009-01-01
More than 150 researchers and engineers from universities and the industrial world met to discuss on the new methodologies developed around assessing uncertainty. About 20 papers were presented and the main topics were: methods to study the propagation of uncertainties, sensitivity analysis, nuclear data covariances or multi-parameter optimisation. This report gathers the contributions of CEA researchers and engineers
Physical Uncertainty Bounds (PUB)
Energy Technology Data Exchange (ETDEWEB)
Vaughan, Diane Elizabeth [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Preston, Dean L. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2015-03-19
This paper introduces and motivates the need for a new methodology for determining upper bounds on the uncertainties in simulations of engineered systems due to limited fidelity in the composite continuum-level physics models needed to simulate the systems. We show that traditional uncertainty quantification methods provide, at best, a lower bound on this uncertainty. We propose to obtain bounds on the simulation uncertainties by first determining bounds on the physical quantities or processes relevant to system performance. By bounding these physics processes, as opposed to carrying out statistical analyses of the parameter sets of specific physics models or simply switching out the available physics models, one can obtain upper bounds on the uncertainties in simulated quantities of interest.
Climate Certainties and Uncertainties
International Nuclear Information System (INIS)
Morel, Pierre
2012-01-01
In issue 380 of Futuribles in December 2011, Antonin Pottier analysed in detail the workings of what is today termed 'climate scepticism' - namely the propensity of certain individuals to contest the reality of climate change on the basis of pseudo-scientific arguments. He emphasized particularly that what fuels the debate on climate change is, largely, the degree of uncertainty inherent in the consequences to be anticipated from observation of the facts, not the description of the facts itself. In his view, the main aim of climate sceptics is to block the political measures for combating climate change. However, since they do not admit to this political posture, they choose instead to deny the scientific reality. This month, Futuribles complements this socio-psychological analysis of climate-sceptical discourse with an - in this case, wholly scientific - analysis of what we know (or do not know) about climate change on our planet. Pierre Morel gives a detailed account of the state of our knowledge in the climate field and what we are able to predict in the medium/long-term. After reminding us of the influence of atmospheric meteorological processes on the climate, he specifies the extent of global warming observed since 1850 and the main origin of that warming, as revealed by the current state of knowledge: the increase in the concentration of greenhouse gases. He then describes the changes in meteorological regimes (showing also the limits of climate simulation models), the modifications of hydrological regimes, and also the prospects for rises in sea levels. He also specifies the mechanisms that may potentially amplify all these phenomena and the climate disasters that might ensue. Lastly, he shows what are the scientific data that cannot be disregarded, the consequences of which are now inescapable (melting of the ice-caps, rises in sea level etc.), the only remaining uncertainty in this connection being the date at which these things will happen. 'In this
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.)
Computational chemical product design problems under property uncertainties
DEFF Research Database (Denmark)
Frutiger, Jerome; Cignitti, Stefano; Abildskov, Jens
2017-01-01
Three different strategies of how to combine computational chemical product design with Monte Carlo based methods for uncertainty analysis of chemical properties are outlined. One method consists of a computer-aided molecular design (CAMD) solution and a post-processing property uncertainty...... fluid design. While the higher end of the uncertainty range of the process model output is similar for the best performing fluids, the lower end of the uncertainty range differs largely....
Quantification of water resources uncertainties in the Luvuvhu sub-basin of the Limpopo river basin
Oosthuizen, N.; Hughes, D.; Kapangaziwiri, E.; Mwenge Kahinda, J.; Mvandaba, V.
2018-06-01
In the absence of historical observed data, models are generally used to describe the different hydrological processes and generate data and information that will inform management and policy decision making. Ideally, any hydrological model should be based on a sound conceptual understanding of the processes in the basin and be backed by quantitative information for the parameterization of the model. However, these data are often inadequate in many sub-basins, necessitating the incorporation of the uncertainty related to the estimation process. This paper reports on the impact of the uncertainty related to the parameterization of the Pitman monthly model and water use data on the estimates of the water resources of the Luvuvhu, a sub-basin of the Limpopo river basin. The study reviews existing information sources associated with the quantification of water balance components and gives an update of water resources of the sub-basin. The flows generated by the model at the outlet of the basin were between 44.03 Mm3 and 45.48 Mm3 per month when incorporating +20% uncertainty to the main physical runoff generating parameters. The total predictive uncertainty of the model increased when water use data such as small farm and large reservoirs and irrigation were included. The dam capacity data was considered at an average of 62% uncertainty mainly as a result of the large differences between the available information in the national water resources database and that digitised from satellite imagery. Water used by irrigated crops was estimated with an average of about 50% uncertainty. The mean simulated monthly flows were between 38.57 Mm3 and 54.83 Mm3 after the water use uncertainty was added. However, it is expected that the uncertainty could be reduced by using higher resolution remote sensing imagery.
International Nuclear Information System (INIS)
Zwermann, W.; Krzykacz-Hausmann, B.; Gallner, L.; Klein, M.; Pautz, A.; Velkov, K.
2012-01-01
Sampling based uncertainty and sensitivity analyses due to epistemic input uncertainties, i.e. to an incomplete knowledge of uncertain input parameters, can be performed with arbitrary application programs to solve the physical problem under consideration. For the description of steady-state particle transport, direct simulations of the microscopic processes with Monte Carlo codes are often used. This introduces an additional source of uncertainty, the aleatoric sampling uncertainty, which is due to the randomness of the simulation process performed by sampling, and which adds to the total combined output sampling uncertainty. So far, this aleatoric part of uncertainty is minimized by running a sufficiently large number of Monte Carlo histories for each sample calculation, thus making its impact negligible as compared to the impact from sampling the epistemic uncertainties. Obviously, this process may cause high computational costs. The present paper shows that in many applications reliable epistemic uncertainty results can also be obtained with substantially lower computational effort by performing and analyzing two appropriately generated series of samples with much smaller number of Monte Carlo histories each. The method is applied along with the nuclear data uncertainty and sensitivity code package XSUSA in combination with the Monte Carlo transport code KENO-Va to various critical assemblies and a full scale reactor calculation. It is shown that the proposed method yields output uncertainties and sensitivities equivalent to the traditional approach, with a high reduction of computing time by factors of the magnitude of 100. (authors)
Interactions between perceived uncertainty types in service dyads
DEFF Research Database (Denmark)
Kreye, Melanie
2018-01-01
to avoid business failure. A conceptual framework of four uncertainty types is investigated: environmental, technological, organisational, and relational uncertainty. We present insights from four empirical cases of service dyads collected via multiple sources of evidence including 54 semi-structured...... interviews, observations, and secondary data. The cases show seven interaction paths with direct knock-on effects between two uncertainty types and indirect knock-on effects between three or four uncertainty types. The findings suggest a causal chain from environmental, technological, organisational......, to relational uncertainty. This research contributes to the servitization literature by (i) con-firming the existence of uncertainty types, (ii) providing an in-depth characterisation of technological uncertainty, and (iii) showing the interaction paths between four uncertainty types in the form of a causal...
Uncertainty Propagation in OMFIT
Smith, Sterling; Meneghini, Orso; Sung, Choongki
2017-10-01
A rigorous comparison of power balance fluxes and turbulent model fluxes requires the propagation of uncertainties in the kinetic profiles and their derivatives. Making extensive use of the python uncertainties package, the OMFIT framework has been used to propagate covariant uncertainties to provide an uncertainty in the power balance calculation from the ONETWO code, as well as through the turbulent fluxes calculated by the TGLF code. The covariant uncertainties arise from fitting 1D (constant on flux surface) density and temperature profiles and associated random errors with parameterized functions such as a modified tanh. The power balance and model fluxes can then be compared with quantification of the uncertainties. No effort is made at propagating systematic errors. A case study will be shown for the effects of resonant magnetic perturbations on the kinetic profiles and fluxes at the top of the pedestal. A separate attempt at modeling the random errors with Monte Carlo sampling will be compared to the method of propagating the fitting function parameter covariant uncertainties. Work supported by US DOE under DE-FC02-04ER54698, DE-FG2-95ER-54309, DE-SC 0012656.
Verification of uncertainty budgets
DEFF Research Database (Denmark)
Heydorn, Kaj; Madsen, B.S.
2005-01-01
, and therefore it is essential that the applicability of the overall uncertainty budget to actual measurement results be verified on the basis of current experimental data. This should be carried out by replicate analysis of samples taken in accordance with the definition of the measurand, but representing...... the full range of matrices and concentrations for which the budget is assumed to be valid. In this way the assumptions made in the uncertainty budget can be experimentally verified, both as regards sources of variability that are assumed negligible, and dominant uncertainty components. Agreement between...
Evaluation of uncertainty of adaptive radiation therapy
International Nuclear Information System (INIS)
Garcia Molla, R.; Gomez Martin, C.; Vidueira, L.; Juan-Senabre, X.; Garcia Gomez, R.
2013-01-01
This work is part of tests to perform to its acceptance in the clinical practice. The uncertainties of adaptive radiation, and which will separate the study, can be divided into two large parts: dosimetry in the CBCT and RDI. At each stage, their uncertainties are quantified and a level of action from which it would be reasonable to adapt the plan may be obtained with the total. (Author)
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
Information-theoretic approach to uncertainty importance
International Nuclear Information System (INIS)
Park, C.K.; Bari, R.A.
1985-01-01
A method is presented for importance analysis in probabilistic risk assessments (PRA) for which the results of interest are characterized by full uncertainty distributions and not just point estimates. The method is based on information theory in which entropy is a measure of uncertainty of a probability density function. We define the relative uncertainty importance between two events as the ratio of the two exponents of the entropies. For the log-normal and log-uniform distributions the importance measure is comprised of the median (central tendency) and of the logarithm of the error factor (uncertainty). Thus, if accident sequences are ranked this way, and the error factors are not all equal, then a different rank order would result than if the sequences were ranked by the central tendency measure alone. As an illustration, the relative importance of internal events and in-plant fires was computed on the basis of existing PRA results
Evaluating prediction uncertainty
International Nuclear Information System (INIS)
McKay, M.D.
1995-03-01
The probability distribution of a model prediction is presented as a proper basis for evaluating the uncertainty in a model prediction that arises from uncertainty in input values. Determination of important model inputs and subsets of inputs is made through comparison of the prediction distribution with conditional prediction probability distributions. Replicated Latin hypercube sampling and variance ratios are used in estimation of the distributions and in construction of importance indicators. The assumption of a linear relation between model output and inputs is not necessary for the indicators to be effective. A sequential methodology which includes an independent validation step is applied in two analysis applications to select subsets of input variables which are the dominant causes of uncertainty in the model predictions. Comparison with results from methods which assume linearity shows how those methods may fail. Finally, suggestions for treating structural uncertainty for submodels are presented
International Nuclear Information System (INIS)
Limperopoulos, G.J.
1995-01-01
This report presents an oil project valuation under uncertainty by means of two well-known financial techniques: The Capital Asset Pricing Model (CAPM) and The Black-Scholes Option Pricing Formula. CAPM gives a linear positive relationship between expected rate of return and risk but does not take into consideration the aspect of flexibility which is crucial for an irreversible investment as an oil price is. Introduction of investment decision flexibility by using real options can increase the oil project value substantially. Some simple tests for the importance of uncertainty in stock market for oil investments are performed. Uncertainty in stock returns is correlated with aggregate product market uncertainty according to Pindyck (1991). The results of the tests are not satisfactory due to the short data series but introducing two other explanatory variables the interest rate and Gross Domestic Product make the situation better. 36 refs., 18 figs., 6 tabs
Uncertainties and climatic change
International Nuclear Information System (INIS)
De Gier, A.M.; Opschoor, J.B.; Van de Donk, W.B.H.J.; Hooimeijer, P.; Jepma, J.; Lelieveld, J.; Oerlemans, J.; Petersen, A.
2008-01-01
Which processes in the climate system are misunderstood? How are scientists dealing with uncertainty about climate change? What will be done with the conclusions of the recently published synthesis report of the IPCC? These and other questions were answered during the meeting 'Uncertainties and climate change' that was held on Monday 26 November 2007 at the KNAW in Amsterdam. This report is a compilation of all the presentations and provides some conclusions resulting from the discussions during this meeting. [mk] [nl
Lemaire, Maurice
2014-01-01
Science is a quest for certainty, but lack of certainty is the driving force behind all of its endeavors. This book, specifically, examines the uncertainty of technological and industrial science. Uncertainty and Mechanics studies the concepts of mechanical design in an uncertain setting and explains engineering techniques for inventing cost-effective products. Though it references practical applications, this is a book about ideas and potential advances in mechanical science.
Uncertainty: lotteries and risk
Ávalos, Eloy
2011-01-01
In this paper we develop the theory of uncertainty in a context where the risks assumed by the individual are measurable and manageable. We primarily use the definition of lottery to formulate the axioms of the individual's preferences, and its representation through the utility function von Neumann - Morgenstern. We study the expected utility theorem and its properties, the paradoxes of choice under uncertainty and finally the measures of risk aversion with monetary lotteries.
Planning ATES systems under uncertainty
Jaxa-Rozen, Marc; Kwakkel, Jan; Bloemendal, Martin
2015-04-01
Aquifer Thermal Energy Storage (ATES) can contribute to significant reductions in energy use within the built environment, by providing seasonal energy storage in aquifers for the heating and cooling of buildings. ATES systems have experienced a rapid uptake over the last two decades; however, despite successful experiments at the individual level, the overall performance of ATES systems remains below expectations - largely due to suboptimal practices for the planning and operation of systems in urban areas. The interaction between ATES systems and underground aquifers can be interpreted as a common-pool resource problem, in which thermal imbalances or interference could eventually degrade the storage potential of the subsurface. Current planning approaches for ATES systems thus typically follow the precautionary principle. For instance, the permitting process in the Netherlands is intended to minimize thermal interference between ATES systems. However, as shown in recent studies (Sommer et al., 2015; Bakr et al., 2013), a controlled amount of interference may benefit the collective performance of ATES systems. An overly restrictive approach to permitting is instead likely to create an artificial scarcity of available space, limiting the potential of the technology in urban areas. In response, master plans - which take into account the collective arrangement of multiple systems - have emerged as an increasingly popular alternative. However, permits and master plans both take a static, ex ante view of ATES governance, making it difficult to predict the effect of evolving ATES use or climactic conditions on overall performance. In particular, the adoption of new systems by building operators is likely to be driven by the available subsurface space and by the performance of existing systems; these outcomes are themselves a function of planning parameters. From this perspective, the interactions between planning authorities, ATES operators, and subsurface conditions
Religion in the face of uncertainty: an uncertainty-identity theory account of religiousness.
Hogg, Michael A; Adelman, Janice R; Blagg, Robert D
2010-02-01
The authors characterize religions as social groups and religiosity as the extent to which a person identifies with a religion, subscribes to its ideology or worldview, and conforms to its normative practices. They argue that religions have attributes that make them well suited to reduce feelings of self-uncertainty. According to uncertainty-identity theory, people are motivated to reduce feelings of uncertainty about or reflecting on self; and identification with groups, particularly highly entitative groups, is a very effective way to reduce uncertainty. All groups provide belief systems and normative prescriptions related to everyday life. However, religions also address the nature of existence, invoking sacred entities and associated rituals and ceremonies. They are entitative groups that provide a moral compass and rules for living that pervade a person's life, making them particularly attractive in times of uncertainty. The authors document data supporting their analysis and discuss conditions that transform religiosity into religious zealotry and extremism.
Uncertainties in the proton lifetime
International Nuclear Information System (INIS)
Ellis, J.; Nanopoulos, D.V.; Rudaz, S.; Gaillard, M.K.
1980-04-01
We discuss the masses of the leptoquark bosons m(x) and the proton lifetime in Grand Unified Theories based principally on SU(5). It is emphasized that estimates of m(x) based on the QCD coupling and the fine structure constant are probably more reliable than those using the experimental value of sin 2 theta(w). Uncertainties in the QCD Λ parameter and the correct value of α are discussed. We estimate higher order effects on the evolution of coupling constants in a momentum space renormalization scheme. It is shown that increasing the number of generations of fermions beyond the minimal three increases m(X) by almost a factor of 2 per generation. Additional uncertainties exist for each generation of technifermions that may exist. We discuss and discount the possibility that proton decay could be 'Cabibbo-rotated' away, and a speculation that Lorentz invariance may be violated in proton decay at a detectable level. We estimate that in the absence of any substantial new physics beyond that in the minimal SU(5) model the proton lifetimes is 8 x 10 30+-2 years
International Nuclear Information System (INIS)
Wilson, Brandon M; Smith, Barton L
2013-01-01
Uncertainties are typically assumed to be constant or a linear function of the measured value; however, this is generally not true. Particle image velocimetry (PIV) is one example of a measurement technique that has highly nonlinear, time varying local uncertainties. Traditional uncertainty methods are not adequate for the estimation of the uncertainty of measurement statistics (mean and variance) in the presence of nonlinear, time varying errors. Propagation of instantaneous uncertainty estimates into measured statistics is performed allowing accurate uncertainty quantification of time-mean and statistics of measurements such as PIV. It is shown that random errors will always elevate the measured variance, and thus turbulent statistics such as u'u'-bar. Within this paper, nonlinear, time varying errors are propagated from instantaneous measurements into the measured mean and variance using the Taylor-series method. With these results and knowledge of the systematic and random uncertainty of each measurement, the uncertainty of the time-mean, the variance and covariance can be found. Applicability of the Taylor-series uncertainty equations to time varying systematic and random errors and asymmetric error distributions are demonstrated with Monte-Carlo simulations. The Taylor-series uncertainty estimates are always accurate for uncertainties on the mean quantity. The Taylor-series variance uncertainty is similar to the Monte-Carlo results for cases in which asymmetric random errors exist or the magnitude of the instantaneous variations in the random and systematic errors is near the ‘true’ variance. However, the Taylor-series method overpredicts the uncertainty in the variance as the instantaneous variations of systematic errors are large or are on the same order of magnitude as the ‘true’ variance. (paper)
Why preeclampsia still exists?
Chelbi, Sonia T; Veitia, Reiner A; Vaiman, Daniel
2013-08-01
Preeclampsia (PE) is a deadly gestational disease affecting up to 10% of women and specific of the human species. Preeclampsia is clearly multifactorial, but the existence of a genetic basis for this disease is now clearly established by the existence of familial cases, epidemiological studies and known predisposing gene polymorphisms. PE is very common despite the fact that Darwinian pressure should have rapidly eliminated or strongly minimized the frequency of predisposing alleles. Consecutive pregnancies with the same partner decrease the risk and severity of PE. Here, we show that, due to this peculiar feature, preeclampsia predisposing-alleles can be differentially maintained according to the familial structure. Thus, we suggest that an optimal frequency of PE-predisposing alleles in human populations can be achieved as a result of a trade-off between benefits of exogamy, importance for maintaining genetic diversity and increase of the fitness owing to a stable paternal investment. Copyright © 2013 Elsevier Ltd. All rights reserved.
Model Uncertainty Quantification Methods In Data Assimilation
Pathiraja, S. D.; Marshall, L. A.; Sharma, A.; Moradkhani, H.
2017-12-01
Data Assimilation involves utilising observations to improve model predictions in a seamless and statistically optimal fashion. Its applications are wide-ranging; from improving weather forecasts to tracking targets such as in the Apollo 11 mission. The use of Data Assimilation methods in high dimensional complex geophysical systems is an active area of research, where there exists many opportunities to enhance existing methodologies. One of the central challenges is in model uncertainty quantification; the outcome of any Data Assimilation study is strongly dependent on the uncertainties assigned to both observations and models. I focus on developing improved model uncertainty quantification methods that are applicable to challenging real world scenarios. These include developing methods for cases where the system states are only partially observed, where there is little prior knowledge of the model errors, and where the model error statistics are likely to be highly non-Gaussian.
Existence of Projective Planes
Perrott, Xander
2016-01-01
This report gives an overview of the history of finite projective planes and their properties before going on to outline the proof that no projective plane of order 10 exists. The report also investigates the search carried out by MacWilliams, Sloane and Thompson in 1970 [12] and confirms their result by providing independent verification that there is no vector of weight 15 in the code generated by the projective plane of order 10.
Turner, L
2009-12-01
Bioethicists disagree over methods, theories, decision-making guides, case analyses and public policies. Thirty years ago, the thinking of many scholars coalesced around a principlist approach to bioethics. That mid-level mode of moral reasoning is now one of many approaches to moral deliberation. Significant variation in contemporary approaches to the study of ethical issues related to medicine, biotechnology and health care raises the question of whether bioethics exists as widely shared method, theory, normative framework or mode of moral reasoning.
Predictive uncertainty in auditory sequence processing
Directory of Open Access Journals (Sweden)
Niels Chr. eHansen
2014-09-01
Full Text Available Previous studies of auditory expectation have focused on the expectedness perceived by listeners retrospectively in response to events. In contrast, this research examines predictive uncertainty - a property of listeners’ prospective state of expectation prior to the onset of an event. We examine the information-theoretic concept of Shannon entropy as a model of predictive uncertainty in music cognition. This is motivated by the Statistical Learning Hypothesis, which proposes that schematic expectations reflect probabilistic relationships between sensory events learned implicitly through exposure.Using probability estimates from an unsupervised, variable-order Markov model, 12 melodic contexts high in entropy and 12 melodic contexts low in entropy were selected from two musical repertoires differing in structural complexity (simple and complex. Musicians and non-musicians listened to the stimuli and provided explicit judgments of perceived uncertainty (explicit uncertainty. We also examined an indirect measure of uncertainty computed as the entropy of expectedness distributions obtained using a classical probe-tone paradigm where listeners rated the perceived expectedness of the final note in a melodic sequence (inferred uncertainty. Finally, we simulate listeners’ perception of expectedness and uncertainty using computational models of auditory expectation. A detailed model comparison indicates which model parameters maximize fit to the data and how they compare to existing models in the literature.The results show that listeners experience greater uncertainty in high-entropy musical contexts than low-entropy contexts. This effect is particularly apparent for inferred uncertainty and is stronger in musicians than non-musicians. Consistent with the Statistical Learning Hypothesis, the results suggest that increased domain-relevant training is associated with an increasingly accurate cognitive model of probabilistic structure in music.
Predictive uncertainty in auditory sequence processing.
Hansen, Niels Chr; Pearce, Marcus T
2014-01-01
Previous studies of auditory expectation have focused on the expectedness perceived by listeners retrospectively in response to events. In contrast, this research examines predictive uncertainty-a property of listeners' prospective state of expectation prior to the onset of an event. We examine the information-theoretic concept of Shannon entropy as a model of predictive uncertainty in music cognition. This is motivated by the Statistical Learning Hypothesis, which proposes that schematic expectations reflect probabilistic relationships between sensory events learned implicitly through exposure. Using probability estimates from an unsupervised, variable-order Markov model, 12 melodic contexts high in entropy and 12 melodic contexts low in entropy were selected from two musical repertoires differing in structural complexity (simple and complex). Musicians and non-musicians listened to the stimuli and provided explicit judgments of perceived uncertainty (explicit uncertainty). We also examined an indirect measure of uncertainty computed as the entropy of expectedness distributions obtained using a classical probe-tone paradigm where listeners rated the perceived expectedness of the final note in a melodic sequence (inferred uncertainty). Finally, we simulate listeners' perception of expectedness and uncertainty using computational models of auditory expectation. A detailed model comparison indicates which model parameters maximize fit to the data and how they compare to existing models in the literature. The results show that listeners experience greater uncertainty in high-entropy musical contexts than low-entropy contexts. This effect is particularly apparent for inferred uncertainty and is stronger in musicians than non-musicians. Consistent with the Statistical Learning Hypothesis, the results suggest that increased domain-relevant training is associated with an increasingly accurate cognitive model of probabilistic structure in music.
Quantifying uncertainty in NDSHA estimates due to earthquake catalogue
Magrin, Andrea; Peresan, Antonella; Vaccari, Franco; Panza, Giuliano
2014-05-01
The procedure for the neo-deterministic seismic zoning, NDSHA, is based on the calculation of synthetic seismograms by the modal summation technique. This approach makes use of information about the space distribution of large magnitude earthquakes, which can be defined based on seismic history and seismotectonics, as well as incorporating information from a wide set of geological and geophysical data (e.g., morphostructural features and ongoing deformation processes identified by earth observations). Hence the method does not make use of attenuation models (GMPE), which may be unable to account for the complexity of the product between seismic source tensor and medium Green function and are often poorly constrained by the available observations. NDSHA defines the hazard from the envelope of the values of ground motion parameters determined considering a wide set of scenario earthquakes; accordingly, the simplest outcome of this method is a map where the maximum of a given seismic parameter is associated to each site. In NDSHA uncertainties are not statistically treated as in PSHA, where aleatory uncertainty is traditionally handled with probability density functions (e.g., for magnitude and distance random variables) and epistemic uncertainty is considered by applying logic trees that allow the use of alternative models and alternative parameter values of each model, but the treatment of uncertainties is performed by sensitivity analyses for key modelling parameters. To fix the uncertainty related to a particular input parameter is an important component of the procedure. The input parameters must account for the uncertainty in the prediction of fault radiation and in the use of Green functions for a given medium. A key parameter is the magnitude of sources used in the simulation that is based on catalogue informations, seismogenic zones and seismogenic nodes. Because the largest part of the existing catalogues is based on macroseismic intensity, a rough estimate
International Nuclear Information System (INIS)
Jin Hosang; Palta, Jatinder R.; Kim, You-Hyun; Kim, Siyong
2010-01-01
Purpose: To analyze dose uncertainty using a previously published dose-uncertainty model, and to assess potential dosimetric risks existing in prostate intensity-modulated radiotherapy (IMRT). Methods and Materials: The dose-uncertainty model provides a three-dimensional (3D) dose-uncertainty distribution in a given confidence level. For 8 retrospectively selected patients, dose-uncertainty maps were constructed using the dose-uncertainty model at the 95% CL. In addition to uncertainties inherent to the radiation treatment planning system, four scenarios of spatial errors were considered: machine only (S1), S1 + intrafraction, S1 + interfraction, and S1 + both intrafraction and interfraction errors. To evaluate the potential risks of the IMRT plans, three dose-uncertainty-based plan evaluation tools were introduced: confidence-weighted dose-volume histogram, confidence-weighted dose distribution, and dose-uncertainty-volume histogram. Results: Dose uncertainty caused by interfraction setup error was more significant than that of intrafraction motion error. The maximum dose uncertainty (95% confidence) of the clinical target volume (CTV) was smaller than 5% of the prescribed dose in all but two cases (13.9% and 10.2%). The dose uncertainty for 95% of the CTV volume ranged from 1.3% to 2.9% of the prescribed dose. Conclusions: The dose uncertainty in prostate IMRT could be evaluated using the dose-uncertainty model. Prostate IMRT plans satisfying the same plan objectives could generate a significantly different dose uncertainty because a complex interplay of many uncertainty sources. The uncertainty-based plan evaluation contributes to generating reliable and error-resistant treatment plans.
Strategic Capital Budgeting : Asset Replacement Under Uncertainty
Pawlina, G.; Kort, P.M.
2001-01-01
We consider a firm's decision to replace an existing production technology with a new, more cost-efficient one.Kulatilaka and Perotti [1998, Management Science] nd that, in a two-period model, increased product market uncertainty could encourage the firm to invest strategically in the new
Illustrative uncertainty visualization of DTI fiber pathways
Brecheisen, R.; Platel, B.; Haar Romeny, B.M. Ter; Vilanova, A.
2013-01-01
Diffusion Tensor Imaging (DTI) and fiber tracking provide unique insight into the 3D structure of fibrous tissues in the brain. However, the output of fiber tracking contains a significant amount of uncertainty accumulated in the various steps of the processing pipeline. Existing DTI visualization
Uncertainties in Forecasting Streamflow using Entropy Theory
Cui, H.; Singh, V. P.
2017-12-01
Streamflow forecasting is essential in river restoration, reservoir operation, power generation, irrigation, navigation, and water management. However, there is always uncertainties accompanied in forecast, which may affect the forecasting results and lead to large variations. Therefore, uncertainties must be considered and be assessed properly when forecasting streamflow for water management. The aim of our work is to quantify the uncertainties involved in forecasting streamflow and provide reliable streamflow forecast. Despite that streamflow time series are stochastic, they exhibit seasonal and periodic patterns. Therefore, streamflow forecasting entails modeling seasonality, periodicity, and its correlation structure, and assessing uncertainties. This study applies entropy theory to forecast streamflow and measure uncertainties during the forecasting process. To apply entropy theory for streamflow forecasting, spectral analysis is combined to time series analysis, as spectral analysis can be employed to characterize patterns of streamflow variation and identify the periodicity of streamflow. That is, it permits to extract significant information for understanding the streamflow process and prediction thereof. Application of entropy theory for streamflow forecasting involves determination of spectral density, determination of parameters, and extension of autocorrelation function. The uncertainties brought by precipitation input, forecasting model and forecasted results are measured separately using entropy. With information theory, how these uncertainties transported and aggregated during these processes will be described.
Resolving uncertainty in chemical speciation determinations
Smith, D. Scott; Adams, Nicholas W. H.; Kramer, James R.
1999-10-01
Speciation determinations involve uncertainty in system definition and experimentation. Identification of appropriate metals and ligands from basic chemical principles, analytical window considerations, types of species and checking for consistency in equilibrium calculations are considered in system definition uncertainty. A systematic approach to system definition limits uncertainty in speciation investigations. Experimental uncertainty is discussed with an example of proton interactions with Suwannee River fulvic acid (SRFA). A Monte Carlo approach was used to estimate uncertainty in experimental data, resulting from the propagation of uncertainties in electrode calibration parameters and experimental data points. Monte Carlo simulations revealed large uncertainties present at high (>9-10) and low (monoprotic ligands. Least-squares fit the data with 21 sites, whereas linear programming fit the data equally well with 9 sites. Multiresponse fitting, involving simultaneous fluorescence and pH measurements, improved model discrimination. Deconvolution of the excitation versus emission fluorescence surface for SRFA establishes a minimum of five sites. Diprotic sites are also required for the five fluorescent sites, and one non-fluorescent monoprotic site was added to accommodate the pH data. Consistent with greater complexity, the multiresponse method had broader confidence limits than the uniresponse methods, but corresponded better with the accepted total carboxylic content for SRFA. Overall there was a 40% standard deviation in total carboxylic content for the multiresponse fitting, versus 10% and 1% for least-squares and linear programming, respectively.
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
Revisiting organizational interpretation and three types of uncertainty
DEFF Research Database (Denmark)
Sund, Kristian J.
2015-01-01
that might help explain and untangle some of the conflicting empirical results found in the extant literature. The paper illustrates how the literature could benefit from re-conceptualizing the perceived environmental uncertainty construct to take into account different types of uncertainty. Practical....... Design/methodology/approach – This conceptual paper extends existing conceptual work by distinguishing between general and issue-specific scanning and linking the interpretation process to three different types of perceived uncertainty: state, effect and response uncertainty. Findings – It is proposed...... on existing work by linking the interpretation process to three different types of uncertainty (state, effect and response uncertainty) with several novel and testable propositions. The paper also differentiates clearly general (regular) scanning from issue-specific (irregular) scanning. Finally, the paper...
Roadmap toward addressing and communicating uncertainty in LCA
DEFF Research Database (Denmark)
Laurin, Lise; Vigon, Bruce; Fantke, Peter
2017-01-01
-characterized uncertainty. The group has investigated current best LCA practices, such as refinements to the pedigree matrix used to assess LCI data quality. In parallel, in the frame of UNEP-SETAC Life Cycle Initiative flagship project on providing Harmonization and Global Guidance for Environmental Life Cycle Impact...... uncertainty is further related to input data, model selection and choices, amongst other aspects. Currently, methods exist to assess and assign uncertainty and variability on LCI data as well as LCIA characterization results. However, often uncertainty is only assessed and reported qualitatively......, is not comparable across impact categories and not consistently assessed and reported across levels of detail. Furthermore, many existing methods and models do not report uncertainty at all or limit their uncertainty assessment to a sensitivity analysis of selected input parameters, while ignoring variability...
Directory of Open Access Journals (Sweden)
R. H. Moore
2013-04-01
Full Text Available We use the Global Modelling Initiative (GMI chemical transport model with a cloud droplet parameterisation adjoint to quantify the sensitivity of cloud droplet number concentration to uncertainties in predicting CCN concentrations. Published CCN closure uncertainties for six different sets of simplifying compositional and mixing state assumptions are used as proxies for modelled CCN uncertainty arising from application of those scenarios. It is found that cloud droplet number concentrations (Nd are fairly insensitive to the number concentration (Na of aerosol which act as CCN over the continents (∂lnNd/∂lnNa ~10–30%, but the sensitivities exceed 70% in pristine regions such as the Alaskan Arctic and remote oceans. This means that CCN concentration uncertainties of 4–71% translate into only 1–23% uncertainty in cloud droplet number, on average. Since most of the anthropogenic indirect forcing is concentrated over the continents, this work shows that the application of Köhler theory and attendant simplifying assumptions in models is not a major source of uncertainty in predicting cloud droplet number or anthropogenic aerosol indirect forcing for the liquid, stratiform clouds simulated in these models. However, it does highlight the sensitivity of some remote areas to pollution brought into the region via long-range transport (e.g., biomass burning or from seasonal biogenic sources (e.g., phytoplankton as a source of dimethylsulfide in the southern oceans. Since these transient processes are not captured well by the climatological emissions inventories employed by current large-scale models, the uncertainties in aerosol-cloud interactions during these events could be much larger than those uncovered here. This finding motivates additional measurements in these pristine regions, for which few observations exist, to quantify the impact (and associated uncertainty of transient aerosol processes on cloud properties.
ICYESS 2013: Understanding and Interpreting Uncertainty
Rauser, F.; Niederdrenk, L.; Schemann, V.; Schmidt, A.; Suesser, D.; Sonntag, S.
2013-12-01
We will report the outcomes and highlights of the Interdisciplinary Conference of Young Earth System Scientists (ICYESS) on Understanding and Interpreting Uncertainty in September 2013, Hamburg, Germany. This conference is aimed at early career scientists (Masters to Postdocs) from a large variety of scientific disciplines and backgrounds (natural, social and political sciences) and will enable 3 days of discussions on a variety of uncertainty-related aspects: 1) How do we deal with implicit and explicit uncertainty in our daily scientific work? What is uncertain for us, and for which reasons? 2) How can we communicate these uncertainties to other disciplines? E.g., is uncertainty in cloud parameterization and respectively equilibrium climate sensitivity a concept that is understood equally well in natural and social sciences that deal with Earth System questions? Or vice versa, is, e.g., normative uncertainty as in choosing a discount rate relevant for natural scientists? How can those uncertainties be reconciled? 3) How can science communicate this uncertainty to the public? Is it useful at all? How are the different possible measures of uncertainty understood in different realms of public discourse? Basically, we want to learn from all disciplines that work together in the broad Earth System Science community how to understand and interpret uncertainty - and then transfer this understanding to the problem of how to communicate with the public, or its different layers / agents. ICYESS is structured in a way that participation is only possible via presentation, so every participant will give their own professional input into how the respective disciplines deal with uncertainty. Additionally, a large focus is put onto communication techniques; there are no 'standard presentations' in ICYESS. Keynote lectures by renowned scientists and discussions will lead to a deeper interdisciplinary understanding of what we do not really know, and how to deal with it. Many
Fischer, Andreas
2016-11-01
Optical flow velocity measurements are important for understanding the complex behavior of flows. Although a huge variety of methods exist, they are either based on a Doppler or a time-of-flight measurement principle. Doppler velocimetry evaluates the velocity-dependent frequency shift of light scattered at a moving particle, whereas time-of-flight velocimetry evaluates the traveled distance of a scattering particle per time interval. Regarding the aim of achieving a minimal measurement uncertainty, it is unclear if one principle allows to achieve lower uncertainties or if both principles can achieve equal uncertainties. For this reason, the natural, fundamental uncertainty limit according to Heisenberg's uncertainty principle is derived for Doppler and time-of-flight measurement principles, respectively. The obtained limits of the velocity uncertainty are qualitatively identical showing, e.g., a direct proportionality for the absolute value of the velocity to the power of 32 and an indirect proportionality to the square root of the scattered light power. Hence, both measurement principles have identical potentials regarding the fundamental uncertainty limit due to the quantum mechanical behavior of photons. This fundamental limit can be attained (at least asymptotically) in reality either with Doppler or time-of-flight methods, because the respective Cramér-Rao bounds for dominating photon shot noise, which is modeled as white Poissonian noise, are identical with the conclusions from Heisenberg's uncertainty principle.
Uncertainty as Knowledge: Constraints on Policy Choices Provided by Analysis of Uncertainty
Lewandowsky, S.; Risbey, J.; Smithson, M.; Newell, B. R.
2012-12-01
Uncertainty forms an integral part of climate science, and it is often cited in connection with arguments against mitigative action. We argue that an analysis of uncertainty must consider existing knowledge as well as uncertainty, and the two must be evaluated with respect to the outcomes and risks associated with possible policy options. Although risk judgments are inherently subjective, an analysis of the role of uncertainty within the climate system yields two constraints that are robust to a broad range of assumptions. Those constraints are that (a) greater uncertainty about the climate system is necessarily associated with greater expected damages from warming, and (b) greater uncertainty translates into a greater risk of the failure of mitigation efforts. These ordinal constraints are unaffected by subjective or cultural risk-perception factors, they are independent of the discount rate, and they are independent of the magnitude of the estimate for climate sensitivity. The constraints mean that any appeal to uncertainty must imply a stronger, rather than weaker, need to cut greenhouse gas emissions than in the absence of uncertainty.
Policy Uncertainty and the US Ethanol Industry
Directory of Open Access Journals (Sweden)
Jason P. H. Jones
2017-11-01
Full Text Available The Renewable Fuel Standard (RFS2, as implemented, has introduced uncertainty into US ethanol producers and the supporting commodity market. First, the fixed mandate for what is mainly cornstarch-based ethanol has increased feedstock price volatility and exerts a general effect across the agricultural sector. Second, the large discrepancy between the original Energy Independence and Security Act (EISA intentions and the actual RFS2 implementation for some fuel classes has increased the investment uncertainty facing investors in biofuel production, distribution, and consumption. Here we discuss and analyze the sources of uncertainty and evaluate the effect of potential RFS2 adjustments as they influence these uncertainties. This includes the use of a flexible, production dependent mandate on corn starch ethanol. We find that a flexible mandate on cornstarch ethanol relaxed during drought could significantly reduce commodity price spikes and alleviate the decline of livestock production in cases of feedstock production shortfalls, but it would increase the risk for ethanol investors.
Uncertainty in project phases: A framework for organisational change management
DEFF Research Database (Denmark)
Kreye, Melanie; Balangalibun, Sarah
2015-01-01
in the early stage of the change project but was delayed until later phases. Furthermore, the sources of uncertainty were found to be predominantly within the organisation that initiated the change project and connected to the project scope. Based on these findings, propositions for future research are defined......Uncertainty is an integral challenge when managing organisational change projects (OCPs). Current literature highlights the importance of uncertainty; however, falls short of giving insights into the nature of uncertainty and suggestions for managing it. Specifically, no insights exist on how...... uncertainty develops over the different phases of OCPs. This paper presents case-based evidence on different sources of uncertainty in OCPs and how these develop over the different project phases. The results showed some surprising findings as the majority of the uncertainty did not manifest itself...
Some sources of the underestimation of evaluated cross section uncertainties
International Nuclear Information System (INIS)
Badikov, S.A.; Gai, E.V.
2003-01-01
The problem of the underestimation of evaluated cross-section uncertainties is addressed. Two basic sources of the underestimation of evaluated cross-section uncertainties - a) inconsistency between declared and observable experimental uncertainties and b) inadequacy between applied statistical models and processed experimental data - are considered. Both the sources of the underestimation are mainly a consequence of existence of the uncertainties unrecognized by experimenters. A model of a 'constant shift' is proposed for taking unrecognised experimental uncertainties into account. The model is applied for statistical analysis of the 238 U(n,f)/ 235 U(n,f) reaction cross-section ratio measurements. It is demonstrated that multiplication by sqrt(χ 2 ) as instrument for correction of underestimated evaluated cross-section uncertainties fails in case of correlated measurements. It is shown that arbitrary assignment of uncertainties and correlation in a simple least squares fit of two correlated measurements of unknown mean leads to physically incorrect evaluated results. (author)
Uncertainty representation of grey numbers and grey sets.
Yang, Yingjie; Liu, Sifeng; John, Robert
2014-09-01
In the literature, there is a presumption that a grey set and an interval-valued fuzzy set are equivalent. This presumption ignores the existence of discrete components in a grey number. In this paper, new measurements of uncertainties of grey numbers and grey sets, consisting of both absolute and relative uncertainties, are defined to give a comprehensive representation of uncertainties in a grey number and a grey set. Some simple examples are provided to illustrate that the proposed uncertainty measurement can give an effective representation of both absolute and relative uncertainties in a grey number and a grey set. The relationships between grey sets and interval-valued fuzzy sets are also analyzed from the point of view of the proposed uncertainty representation. The analysis demonstrates that grey sets and interval-valued fuzzy sets provide different but overlapping models for uncertainty representation in sets.
Some Implications of Two Forms of the Generalized Uncertainty Principle
Directory of Open Access Journals (Sweden)
Mohammed M. Khalil
2014-01-01
Full Text Available Various theories of quantum gravity predict the existence of a minimum length scale, which leads to the modification of the standard uncertainty principle to the Generalized Uncertainty Principle (GUP. In this paper, we study two forms of the GUP and calculate their implications on the energy of the harmonic oscillator and the hydrogen atom more accurately than previous studies. In addition, we show how the GUP modifies the Lorentz force law and the time-energy uncertainty principle.
Research of Uncertainty Reasoning in Pineapple Disease Identification System
Liu, Liqun; Fan, Haifeng
In order to deal with the uncertainty of evidences mostly existing in pineapple disease identification system, a reasoning model based on evidence credibility factor was established. The uncertainty reasoning method is discussed,including: uncertain representation of knowledge, uncertain representation of rules, uncertain representation of multi-evidences and update of reasoning rules. The reasoning can fully reflect the uncertainty in disease identification and reduce the influence of subjective factors on the accuracy of the system.
Concrete structures. Contribution to the safety assessment of existing structures
Directory of Open Access Journals (Sweden)
D. COUTO
Full Text Available The safety evaluation of an existing concrete structure differs from the design of new structures. The partial safety factors for actions and resistances adopted in the design phase consider uncertainties and inaccuracies related to the building processes of structures, variability of materials strength and numerical approximations of the calculation and design processes. However, when analyzing a finished structure, a large number of unknown factors during the design stage are already defined and can be measured, which justifies a change in the increasing factors of the actions or reduction factors of resistances. Therefore, it is understood that safety assessment in existing structures is more complex than introducing security when designing a new structure, because it requires inspection, testing, analysis and careful diagnose. Strong knowledge and security concepts in structural engineering are needed, as well as knowledge about the materials of construction employed, in order to identify, control and properly consider the variability of actions and resistances in the structure. With the intention of discussing this topic considered complex and diffuse, this paper presents an introduction to the safety of concrete structures, a synthesis of the recommended procedures by Brazilian standards and another codes, associated with the topic, as well a realistic example of the safety assessment of an existing structure.
Uncertainties and severe-accident management
International Nuclear Information System (INIS)
Kastenberg, W.E.
1991-01-01
Severe-accident management can be defined as the use of existing and or alternative resources, systems, and actions to prevent or mitigate a core-melt accident. Together with risk management (e.g., changes in plant operation and/or addition of equipment) and emergency planning (off-site actions), accident management provides an extension of the defense-indepth safety philosophy for severe accidents. A significant number of probabilistic safety assessments have been completed, which yield the principal plant vulnerabilities, and can be categorized as (a) dominant sequences with respect to core-melt frequency, (b) dominant sequences with respect to various risk measures, (c) dominant threats that challenge safety functions, and (d) dominant threats with respect to failure of safety systems. Severe-accident management strategies can be generically classified as (a) use of alternative resources, (b) use of alternative equipment, and (c) use of alternative actions. For each sequence/threat and each combination of strategy, there may be several options available to the operator. Each strategy/option involves phenomenological and operational considerations regarding uncertainty. These include (a) uncertainty in key phenomena, (b) uncertainty in operator behavior, (c) uncertainty in system availability and behavior, and (d) uncertainty in information availability (i.e., instrumentation). This paper focuses on phenomenological uncertainties associated with severe-accident management strategies
Directory of Open Access Journals (Sweden)
Carlos Alexandre Molina Noccioli
2016-07-01
Full Text Available Este trabalho busca analisar o tratamento linguístico-discursivo das informações acerca de um tópicotemático tradicionalmente visto como tabu, relacionado a questões sexuais, na notícia O ponto G existe?, publicada em 2008, na revista brasileira Superinteressante, destacando-se como o conhecimento em questão é representado socialmente ao se considerar a linha editorial da revista. A notícia caracteriza-se como um campo fértil para a análise das estratégias divulgativas, já que atrai, inclusive pelas escolhas temáticas, a curiosidade dos leitores. Imbuído de um tema excêntrico, o texto consegue angariar um público jovem interessado em discussões polêmicas relacionadas ao seu universo.
Uncertainty in artificial intelligence
Levitt, TS; Lemmer, JF; Shachter, RD
1990-01-01
Clearly illustrated in this volume is the current relationship between Uncertainty and AI.It has been said that research in AI revolves around five basic questions asked relative to some particular domain: What knowledge is required? How can this knowledge be acquired? How can it be represented in a system? How should this knowledge be manipulated in order to provide intelligent behavior? How can the behavior be explained? In this volume, all of these questions are addressed. From the perspective of the relationship of uncertainty to the basic questions of AI, the book divides naturally i
Directory of Open Access Journals (Sweden)
Silvia Novaes Zilber
2013-06-01
sustainable and incremental innovations linked to the adequacy of existing products.
Directory of Open Access Journals (Sweden)
Silvia Novaes Zilber
2012-01-01
sustainable and incremental innovations linked to the adequacy of existing products.
Uncertainty Analyses and Strategy
International Nuclear Information System (INIS)
Kevin Coppersmith
2001-01-01
The DOE identified a variety of uncertainties, arising from different sources, during its assessment of the performance of a potential geologic repository at the Yucca Mountain site. In general, the number and detail of process models developed for the Yucca Mountain site, and the complex coupling among those models, make the direct incorporation of all uncertainties difficult. The DOE has addressed these issues in a number of ways using an approach to uncertainties that is focused on producing a defensible evaluation of the performance of a potential repository. The treatment of uncertainties oriented toward defensible assessments has led to analyses and models with so-called ''conservative'' assumptions and parameter bounds, where conservative implies lower performance than might be demonstrated with a more realistic representation. The varying maturity of the analyses and models, and uneven level of data availability, result in total system level analyses with a mix of realistic and conservative estimates (for both probabilistic representations and single values). That is, some inputs have realistically represented uncertainties, and others are conservatively estimated or bounded. However, this approach is consistent with the ''reasonable assurance'' approach to compliance demonstration, which was called for in the U.S. Nuclear Regulatory Commission's (NRC) proposed 10 CFR Part 63 regulation (64 FR 8640 [DIRS 101680]). A risk analysis that includes conservatism in the inputs will result in conservative risk estimates. Therefore, the approach taken for the Total System Performance Assessment for the Site Recommendation (TSPA-SR) provides a reasonable representation of processes and conservatism for purposes of site recommendation. However, mixing unknown degrees of conservatism in models and parameter representations reduces the transparency of the analysis and makes the development of coherent and consistent probability statements about projected repository
Appropriatie spatial scales to achieve model output uncertainty goals
Booij, Martijn J.; Melching, Charles S.; Chen, Xiaohong; Chen, Yongqin; Xia, Jun; Zhang, Hailun
2008-01-01
Appropriate spatial scales of hydrological variables were determined using an existing methodology based on a balance in uncertainties from model inputs and parameters extended with a criterion based on a maximum model output uncertainty. The original methodology uses different relationships between
Conquering complexity - Dealing with uncertainty and ambiguity in water management
Hommes, Saskia
2008-01-01
Water management problems are embedded in a natural and social system that is characterized by complexity. Knowledge uncertainty and the existence of divergent actors’ perceptions contribute to this complexity. Consequently, dealing with water management issues is not just a knowledge uncertainty
Uncertainties in repository modeling
Energy Technology Data Exchange (ETDEWEB)
Wilson, J.R.
1996-12-31
The distant future is ver difficult to predict. Unfortunately, our regulators are being enchouraged to extend ther regulatory period form the standard 10,000 years to 1 million years. Such overconfidence is not justified due to uncertainties in dating, calibration, and modeling.
Uncertainties in repository modeling
International Nuclear Information System (INIS)
Wilson, J.R.
1996-01-01
The distant future is ver difficult to predict. Unfortunately, our regulators are being enchouraged to extend ther regulatory period form the standard 10,000 years to 1 million years. Such overconfidence is not justified due to uncertainties in dating, calibration, and modeling
International Nuclear Information System (INIS)
Haefele, W.; Renn, O.; Erdmann, G.
1990-01-01
The notion of 'risk' is discussed in its social and technological contexts, leading to an investigation of the terms factuality, hypotheticality, uncertainty, and vagueness, and to the problems of acceptance and acceptability especially in the context of political decision finding. (DG) [de
Do `negative' temperatures exist?
Lavenda, B. H.
1999-06-01
A modification of the second law is required for a system with a bounded density of states and not the introduction of a `negative' temperature scale. The ascending and descending branches of the entropy versus energy curve describe particle and hole states, having thermal equations of state that are given by the Fermi and logistic distributions, respectively. Conservation of energy requires isentropic states to be isothermal. The effect of adiabatically reversing the field is entirely mechanical because the only difference between the two states is their energies. The laws of large and small numbers, leading to the normal and Poisson approximations, characterize statistically the states of infinite and zero temperatures, respectively. Since the heat capacity also vanishes in the state of maximum disorder, the third law can be generalized in systems with a bounded density of states: the entropy tends to a constant as the temperature tends to either zero or infinity.
Courtney, H; Kirkland, J; Viguerie, P
1997-01-01
At the heart of the traditional approach to strategy lies the assumption that by applying a set of powerful analytic tools, executives can predict the future of any business accurately enough to allow them to choose a clear strategic direction. But what happens when the environment is so uncertain that no amount of analysis will allow us to predict the future? What makes for a good strategy in highly uncertain business environments? The authors, consultants at McKinsey & Company, argue that uncertainty requires a new way of thinking about strategy. All too often, they say, executives take a binary view: either they underestimate uncertainty to come up with the forecasts required by their companies' planning or capital-budging processes, or they overestimate it, abandon all analysis, and go with their gut instinct. The authors outline a new approach that begins by making a crucial distinction among four discrete levels of uncertainty that any company might face. They then explain how a set of generic strategies--shaping the market, adapting to it, or reserving the right to play at a later time--can be used in each of the four levels. And they illustrate how these strategies can be implemented through a combination of three basic types of actions: big bets, options, and no-regrets moves. The framework can help managers determine which analytic tools can inform decision making under uncertainty--and which cannot. At a broader level, it offers executives a discipline for thinking rigorously and systematically about uncertainty and its implications for strategy.
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
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
Uncertainty quantification for environmental models
Hill, Mary C.; Lu, Dan; Kavetski, Dmitri; Clark, Martyn P.; Ye, Ming
2012-01-01
Environmental models are used to evaluate the fate of fertilizers in agricultural settings (including soil denitrification), the degradation of hydrocarbons at spill sites, and water supply for people and ecosystems in small to large basins and cities—to mention but a few applications of these models. They also play a role in understanding and diagnosing potential environmental impacts of global climate change. The models are typically mildly to extremely nonlinear. The persistent demand for enhanced dynamics and resolution to improve model realism [17] means that lengthy individual model execution times will remain common, notwithstanding continued enhancements in computer power. In addition, high-dimensional parameter spaces are often defined, which increases the number of model runs required to quantify uncertainty [2]. Some environmental modeling projects have access to extensive funding and computational resources; many do not. The many recent studies of uncertainty quantification in environmental model predictions have focused on uncertainties related to data error and sparsity of data, expert judgment expressed mathematically through prior information, poorly known parameter values, and model structure (see, for example, [1,7,9,10,13,18]). Approaches for quantifying uncertainty include frequentist (potentially with prior information [7,9]), Bayesian [13,18,19], and likelihood-based. A few of the numerous methods, including some sensitivity and inverse methods with consequences for understanding and quantifying uncertainty, are as follows: Bayesian hierarchical modeling and Bayesian model averaging; single-objective optimization with error-based weighting [7] and multi-objective optimization [3]; methods based on local derivatives [2,7,10]; screening methods like OAT (one at a time) and the method of Morris [14]; FAST (Fourier amplitude sensitivity testing) [14]; the Sobol' method [14]; randomized maximum likelihood [10]; Markov chain Monte Carlo (MCMC) [10
Adaptively Addressing Uncertainty in Estuarine and Near Coastal Restoration Projects
Energy Technology Data Exchange (ETDEWEB)
Thom, Ronald M.; Williams, Greg D.; Borde, Amy B.; Southard, John A.; Sargeant, Susan L.; Woodruff, Dana L.; Laufle, Jeffrey C.; Glasoe, Stuart
2005-03-01
Restoration projects have an uncertain outcome because of a lack of information about current site conditions, historical disturbance levels, effects of landscape alterations on site development, unpredictable trajectories or patterns of ecosystem structural development, and many other factors. A poor understanding of the factors that control the development and dynamics of a system, such as hydrology, salinity, wave energies, can also lead to an unintended outcome. Finally, lack of experience in restoring certain types of systems (e.g., rare or very fragile habitats) or systems in highly modified situations (e.g., highly urbanized estuaries) makes project outcomes uncertain. Because of these uncertainties, project costs can rise dramatically in an attempt to come closer to project goals. All of the potential sources of error can be addressed to a certain degree through adaptive management. The first step is admitting that these uncertainties can exist, and addressing as many of the uncertainties with planning and directed research prior to implementing the project. The second step is to evaluate uncertainties through hypothesis-driven experiments during project implementation. The third step is to use the monitoring program to evaluate and adjust the project as needed to improve the probability of the project to reach is goal. The fourth and final step is to use the information gained in the project to improve future projects. A framework that includes a clear goal statement, a conceptual model, and an evaluation framework can help in this adaptive restoration process. Projects and programs vary in their application of adaptive management in restoration, and it is very difficult to be highly prescriptive in applying adaptive management to projects that necessarily vary widely in scope, goal, ecosystem characteristics, and uncertainties. Very large ecosystem restoration programs in the Mississippi River delta (Coastal Wetlands Planning, Protection, and Restoration
Quantifying measurement uncertainty and spatial variability in the context of model evaluation
Choukulkar, A.; Brewer, A.; Pichugina, Y. L.; Bonin, T.; Banta, R. M.; Sandberg, S.; Weickmann, A. M.; Djalalova, I.; McCaffrey, K.; Bianco, L.; Wilczak, J. M.; Newman, J. F.; Draxl, C.; Lundquist, J. K.; Wharton, S.; Olson, J.; Kenyon, J.; Marquis, M.
2017-12-01
In an effort to improve wind forecasts for the wind energy sector, the Department of Energy and the NOAA funded the second Wind Forecast Improvement Project (WFIP2). As part of the WFIP2 field campaign, a large suite of in-situ and remote sensing instrumentation was deployed to the Columbia River Gorge in Oregon and Washington from October 2015 - March 2017. The array of instrumentation deployed included 915-MHz wind profiling radars, sodars, wind- profiling lidars, and scanning lidars. The role of these instruments was to provide wind measurements at high spatial and temporal resolution for model evaluation and improvement of model physics. To properly determine model errors, the uncertainties in instrument-model comparisons need to be quantified accurately. These uncertainties arise from several factors such as measurement uncertainty, spatial variability, and interpolation of model output to instrument locations, to name a few. In this presentation, we will introduce a formalism to quantify measurement uncertainty and spatial variability. The accuracy of this formalism will be tested using existing datasets such as the eXperimental Planetary boundary layer Instrumentation Assessment (XPIA) campaign. Finally, the uncertainties in wind measurement and the spatial variability estimates from the WFIP2 field campaign will be discussed to understand the challenges involved in model evaluation.
Optimization Under Uncertainty for Wake Steering Strategies
Energy Technology Data Exchange (ETDEWEB)
Quick, Julian [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Annoni, Jennifer [National Renewable Energy Laboratory (NREL), Golden, CO (United States); King, Ryan N [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Dykes, Katherine L [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Fleming, Paul A [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Ning, Andrew [Brigham Young University
2017-08-03
Offsetting turbines' yaw orientations from incoming wind is a powerful tool that may be leveraged to reduce undesirable wake effects on downstream turbines. First, we examine a simple two-turbine case to gain intuition as to how inflow direction uncertainty affects the optimal solution. The turbines are modeled with unidirectional inflow such that one turbine directly wakes the other, using ten rotor diameter spacing. We perform optimization under uncertainty (OUU) via a parameter sweep of the front turbine. The OUU solution generally prefers less steering. We then do this optimization for a 60-turbine wind farm with unidirectional inflow, varying the degree of inflow uncertainty and approaching this OUU problem by nesting a polynomial chaos expansion uncertainty quantification routine within an outer optimization. We examined how different levels of uncertainty in the inflow direction effect the ratio of the expected values of deterministic and OUU solutions for steering strategies in the large wind farm, assuming the directional uncertainty used to reach said OUU solution (this ratio is defined as the value of the stochastic solution or VSS).
Uncertainties affecting fund collection, management and final utilisation
International Nuclear Information System (INIS)
Soederberg, Olof
2006-01-01
The paper presents, on a general level, major uncertainties in financing systems aiming at providing secure funding for future costs for decommissioning. The perspective chosen is that of a fund collector/manager. The paper also contains a description of how these uncertainties are dealt within the Swedish financing system and particularly from the perspective of the Board of the Swedish Nuclear Waste Fund. It is concluded that existing uncertainties are a good reason not to postpone decommissioning activities to a distant future. This aspect is important also when countries have in place financing systems that have been constructed in order to be robust against identified uncertainties. (author)
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
Failure probability under parameter uncertainty.
Gerrard, R; Tsanakas, A
2011-05-01
In many problems of risk analysis, failure is equivalent to the event of a random risk factor exceeding a given threshold. Failure probabilities can be controlled if a decisionmaker is able to set the threshold at an appropriate level. This abstract situation applies, for example, to environmental risks with infrastructure controls; to supply chain risks with inventory controls; and to insurance solvency risks with capital controls. However, uncertainty around the distribution of the risk factor implies that parameter error will be present and the measures taken to control failure probabilities may not be effective. We show that parameter uncertainty increases the probability (understood as expected frequency) of failures. For a large class of loss distributions, arising from increasing transformations of location-scale families (including the log-normal, Weibull, and Pareto distributions), the article shows that failure probabilities can be exactly calculated, as they are independent of the true (but unknown) parameters. Hence it is possible to obtain an explicit measure of the effect of parameter uncertainty on failure probability. Failure probability can be controlled in two different ways: (1) by reducing the nominal required failure probability, depending on the size of the available data set, and (2) by modifying of the distribution itself that is used to calculate the risk control. Approach (1) corresponds to a frequentist/regulatory view of probability, while approach (2) is consistent with a Bayesian/personalistic view. We furthermore show that the two approaches are consistent in achieving the required failure probability. Finally, we briefly discuss the effects of data pooling and its systemic risk implications. © 2010 Society for Risk Analysis.
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
Uncertainty visualisation in the Model Web
Gerharz, L. E.; Autermann, C.; Hopmann, H.; Stasch, C.; Pebesma, E.
2012-04-01
Visualisation of geospatial data as maps is a common way to communicate spatially distributed information. If temporal and furthermore uncertainty information are included in the data, efficient visualisation methods are required. For uncertain spatial and spatio-temporal data, numerous visualisation methods have been developed and proposed, but only few tools for visualisation of data in a standardised way exist. Furthermore, usually they are realised as thick clients, and lack functionality of handling data coming from web services as it is envisaged in the Model Web. We present an interactive web tool for visualisation of uncertain spatio-temporal data developed in the UncertWeb project. The client is based on the OpenLayers JavaScript library. OpenLayers provides standard map windows and navigation tools, i.e. pan, zoom in/out, to allow interactive control for the user. Further interactive methods are implemented using jStat, a JavaScript library for statistics plots developed in UncertWeb, and flot. To integrate the uncertainty information into existing standards for geospatial data, the Uncertainty Markup Language (UncertML) was applied in combination with OGC Observations&Measurements 2.0 and JavaScript Object Notation (JSON) encodings for vector and NetCDF for raster data. The client offers methods to visualise uncertain vector and raster data with temporal information. Uncertainty information considered for the tool are probabilistic and quantified attribute uncertainties which can be provided as realisations or samples, full probability distributions functions and statistics. Visualisation is supported for uncertain continuous and categorical data. In the client, the visualisation is realised using a combination of different methods. Based on previously conducted usability studies, a differentiation between expert (in statistics or mapping) and non-expert users has been indicated as useful. Therefore, two different modes are realised together in the tool
Using finite mixture models in thermal-hydraulics system code uncertainty analysis
Energy Technology Data Exchange (ETDEWEB)
Carlos, S., E-mail: scarlos@iqn.upv.es [Department d’Enginyeria Química i Nuclear, Universitat Politècnica de València, Camí de Vera s.n, 46022 València (Spain); Sánchez, A. [Department d’Estadística Aplicada i Qualitat, Universitat Politècnica de València, Camí de Vera s.n, 46022 València (Spain); Ginestar, D. [Department de Matemàtica Aplicada, Universitat Politècnica de València, Camí de Vera s.n, 46022 València (Spain); Martorell, S. [Department d’Enginyeria Química i Nuclear, Universitat Politècnica de València, Camí de Vera s.n, 46022 València (Spain)
2013-09-15
Highlights: • Best estimate codes simulation needs uncertainty quantification. • The output variables can present multimodal probability distributions. • The analysis of multimodal distribution is performed using finite mixture models. • Two methods to reconstruct output variable probability distribution are used. -- Abstract: Nuclear Power Plant safety analysis is mainly based on the use of best estimate (BE) codes that predict the plant behavior under normal or accidental conditions. As the BE codes introduce uncertainties due to uncertainty in input parameters and modeling, it is necessary to perform uncertainty assessment (UA), and eventually sensitivity analysis (SA), of the results obtained. These analyses are part of the appropriate treatment of uncertainties imposed by current regulation based on the adoption of the best estimate plus uncertainty (BEPU) approach. The most popular approach for uncertainty assessment, based on Wilks’ method, obtains a tolerance/confidence interval, but it does not completely characterize the output variable behavior, which is required for an extended UA and SA. However, the development of standard UA and SA impose high computational cost due to the large number of simulations needed. In order to obtain more information about the output variable and, at the same time, to keep computational cost as low as possible, there has been a recent shift toward developing metamodels (model of model), or surrogate models, that approximate or emulate complex computer codes. In this way, there exist different techniques to reconstruct the probability distribution using the information provided by a sample of values as, for example, the finite mixture models. In this paper, the Expectation Maximization and the k-means algorithms are used to obtain a finite mixture model that reconstructs the output variable probability distribution from data obtained with RELAP-5 simulations. Both methodologies have been applied to a separated
Gething, Peter W; Patil, Anand P; Hay, Simon I
2010-04-01
Risk maps estimating the spatial distribution of infectious diseases are required to guide public health policy from local to global scales. The advent of model-based geostatistics (MBG) has allowed these maps to be generated in a formal statistical framework, providing robust metrics of map uncertainty that enhances their utility for decision-makers. In many settings, decision-makers require spatially aggregated measures over large regions such as the mean prevalence within a country or administrative region, or national populations living under different levels of risk. Existing MBG mapping approaches provide suitable metrics of local uncertainty--the fidelity of predictions at each mapped pixel--but have not been adapted for measuring uncertainty over large areas, due largely to a series of fundamental computational constraints. Here the authors present a new efficient approximating algorithm that can generate for the first time the necessary joint simulation of prevalence values across the very large prediction spaces needed for global scale mapping. This new approach is implemented in conjunction with an established model for P. falciparum allowing robust estimates of mean prevalence at any specified level of spatial aggregation. The model is used to provide estimates of national populations at risk under three policy-relevant prevalence thresholds, along with accompanying model-based measures of uncertainty. By overcoming previously unchallenged computational barriers, this study illustrates how MBG approaches, already at the forefront of infectious disease mapping, can be extended to provide large-scale aggregate measures appropriate for decision-makers.
The EXIST Mission Concept Study
Fishman, Gerald J.; Grindlay, J.; Hong, J.
2008-01-01
scanning mode, interrupted for several orbits per day by GRB follow-ups, followed by a combined pointing-scanning mission phase for optical/IR spectroscopy and redshifts for the large AGN sample found in the survey as well as GRBs and LSST transients. A Team of university, NASA, and industry investigators will conduct the study to determine the full sensitivity and capabilities of this new configuration for EXIST. It will build on the extensive studies of the prior design for the mission and the HET and will incorporate the optical/IR telescope (hereafter IRT) now fully developed by our ITT partner for the NextView Commercial Remote Sensing mission (early 2008 launch) with a focal plane to be developed at GSFC based in part on JWST/NIRSPEC designs. No new technology is needed for either the IRT or HET instruments. The study will pay close attention to full mission cost and present a design for the Decadal Survey Workshop to ensure this even more capable EXIST mission is once again part of the next Decadal Survey.
Uncertainty in adaptive capacity
International Nuclear Information System (INIS)
Neil Adger, W.; Vincent, K.
2005-01-01
The capacity to adapt is a critical element of the process of adaptation: it is the vector of resources that represent the asset base from which adaptation actions can be made. Adaptive capacity can in theory be identified and measured at various scales, from the individual to the nation. The assessment of uncertainty within such measures comes from the contested knowledge domain and theories surrounding the nature of the determinants of adaptive capacity and the human action of adaptation. While generic adaptive capacity at the national level, for example, is often postulated as being dependent on health, governance and political rights, and literacy, and economic well-being, the determinants of these variables at national levels are not widely understood. We outline the nature of this uncertainty for the major elements of adaptive capacity and illustrate these issues with the example of a social vulnerability index for countries in Africa. (authors)
International Nuclear Information System (INIS)
Laval, Katia; Laval, Guy
2013-01-01
Like meteorology, climatology is not an exact science: climate change forecasts necessarily include a share of uncertainty. It is precisely this uncertainty which is brandished and exploited by the opponents to the global warming theory to put into question the estimations of its future consequences. Is it legitimate to predict the future using the past climate data (well documented up to 100000 years BP) or the climates of other planets, taking into account the impreciseness of the measurements and the intrinsic complexity of the Earth's machinery? How is it possible to model a so huge and interwoven system for which any exact description has become impossible? Why water and precipitations play such an important role in local and global forecasts, and how should they be treated? This book written by two physicists answers with simpleness these delicate questions in order to give anyone the possibility to build his own opinion about global warming and the need to act rapidly
International Nuclear Information System (INIS)
Martens, Hans.
1991-01-01
The subject of this thesis is the uncertainty principle (UP). The UP is one of the most characteristic points of differences between quantum and classical mechanics. The starting point of this thesis is the work of Niels Bohr. Besides the discussion the work is also analyzed. For the discussion of the different aspects of the UP the formalism of Davies and Ludwig is used instead of the more commonly used formalism of Neumann and Dirac. (author). 214 refs.; 23 figs
Uncertainty in artificial intelligence
Shachter, RD; Henrion, M; Lemmer, JF
1990-01-01
This volume, like its predecessors, reflects the cutting edge of research on the automation of reasoning under uncertainty.A more pragmatic emphasis is evident, for although some papers address fundamental issues, the majority address practical issues. Topics include the relations between alternative formalisms (including possibilistic reasoning), Dempster-Shafer belief functions, non-monotonic reasoning, Bayesian and decision theoretic schemes, and new inference techniques for belief nets. New techniques are applied to important problems in medicine, vision, robotics, and natural language und
Decision Making Under Uncertainty
2010-11-01
A sound approach to rational decision making requires a decision maker to establish decision objectives, identify alternatives, and evaluate those...often violate the axioms of rationality when making decisions under uncertainty. The systematic description of such observations may lead to the...which leads to “anchoring” on the initial value. The fact that individuals have been shown to deviate from rationality when making decisions
Economic uncertainty principle?
Alexander Harin
2006-01-01
The economic principle of (hidden) uncertainty is presented. New probability formulas are offered. Examples of solutions of three types of fundamental problems are reviewed.; Principe d'incertitude économique? Le principe économique d'incertitude (cachée) est présenté. De nouvelles formules de chances sont offertes. Les exemples de solutions des trois types de problèmes fondamentaux sont reconsidérés.
Straightening: existence, uniqueness and stability
Destrade, M.; Ogden, R. W.; Sgura, I.; Vergori, L.
2014-01-01
One of the least studied universal deformations of incompressible nonlinear elasticity, namely the straightening of a sector of a circular cylinder into a rectangular block, is revisited here and, in particular, issues of existence and stability are addressed. Particular attention is paid to the system of forces required to sustain the large static deformation, including by the application of end couples. The influence of geometric parameters and constitutive models on the appearance of wrinkles on the compressed face of the block is also studied. Different numerical methods for solving the incremental stability problem are compared and it is found that the impedance matrix method, based on the resolution of a matrix Riccati differential equation, is the more precise. PMID:24711723
Calibration Under Uncertainty.
Energy Technology Data Exchange (ETDEWEB)
Swiler, Laura Painton; Trucano, Timothy Guy
2005-03-01
This report is a white paper summarizing the literature and different approaches to the problem of calibrating computer model parameters in the face of model uncertainty. Model calibration is often formulated as finding the parameters that minimize the squared difference between the model-computed data (the predicted data) and the actual experimental data. This approach does not allow for explicit treatment of uncertainty or error in the model itself: the model is considered the %22true%22 deterministic representation of reality. While this approach does have utility, it is far from an accurate mathematical treatment of the true model calibration problem in which both the computed data and experimental data have error bars. This year, we examined methods to perform calibration accounting for the error in both the computer model and the data, as well as improving our understanding of its meaning for model predictability. We call this approach Calibration under Uncertainty (CUU). This talk presents our current thinking on CUU. We outline some current approaches in the literature, and discuss the Bayesian approach to CUU in detail.
Participation under Uncertainty
International Nuclear Information System (INIS)
Boudourides, Moses A.
2003-01-01
This essay reviews a number of theoretical perspectives about uncertainty and participation in the present-day knowledge-based society. After discussing the on-going reconfigurations of science, technology and society, we examine how appropriate for policy studies are various theories of social complexity. Post-normal science is such an example of a complexity-motivated approach, which justifies civic participation as a policy response to an increasing uncertainty. But there are different categories and models of uncertainties implying a variety of configurations of policy processes. A particular role in all of them is played by expertise whose democratization is an often-claimed imperative nowadays. Moreover, we discuss how different participatory arrangements are shaped into instruments of policy-making and framing regulatory processes. As participation necessitates and triggers deliberation, we proceed to examine the role and the barriers of deliberativeness. Finally, we conclude by referring to some critical views about the ultimate assumptions of recent European policy frameworks and the conceptions of civic participation and politicization that they invoke
Deterministic uncertainty analysis
International Nuclear Information System (INIS)
Worley, B.A.
1987-12-01
This paper presents a deterministic uncertainty analysis (DUA) method for calculating uncertainties that has the potential to significantly reduce the number of computer runs compared to conventional statistical analysis. The method is based upon the availability of derivative and sensitivity data such as that calculated using the well known direct or adjoint sensitivity analysis techniques. Formation of response surfaces using derivative data and the propagation of input probability distributions are discussed relative to their role in the DUA method. A sample problem that models the flow of water through a borehole is used as a basis to compare the cumulative distribution function of the flow rate as calculated by the standard statistical methods and the DUA method. Propogation of uncertainties by the DUA method is compared for ten cases in which the number of reference model runs was varied from one to ten. The DUA method gives a more accurate representation of the true cumulative distribution of the flow rate based upon as few as two model executions compared to fifty model executions using a statistical approach. 16 refs., 4 figs., 5 tabs
Systematic Evaluation of Uncertainty in Material Flow Analysis
DEFF Research Database (Denmark)
Laner, David; Rechberger, Helmut; Astrup, Thomas Fruergaard
2014-01-01
Material flow analysis (MFA) is a tool to investigate material flows and stocks in defined systems as a basis for resource management or environmental pollution control. Because of the diverse nature of sources and the varying quality and availability of data, MFA results are inherently uncertain....... Uncertainty analyses have received increasing attention in recent MFA studies, but systematic approaches for selection of appropriate uncertainty tools are missing. This article reviews existing literature related to handling of uncertainty in MFA studies and evaluates current practice of uncertainty analysis......) and exploratory MFA (identification of critical parameters and system behavior). Whereas mathematically simpler concepts focusing on data uncertainty characterization are appropriate for descriptive MFAs, statistical approaches enabling more-rigorous evaluation of uncertainty and model sensitivity are needed...
Uncertainty quantification in flood risk assessment
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.
Uncertainty and sampling issues in tank characterization
International Nuclear Information System (INIS)
Liebetrau, A.M.; Pulsipher, B.A.; Kashporenko, D.M.
1997-06-01
A defensible characterization strategy must recognize that uncertainties are inherent in any measurement or estimate of interest and must employ statistical methods for quantifying and managing those uncertainties. Estimates of risk and therefore key decisions must incorporate knowledge about uncertainty. This report focuses statistical methods that should be employed to ensure confident decision making and appropriate management of uncertainty. Sampling is a major source of uncertainty that deserves special consideration in the tank characterization strategy. The question of whether sampling will ever provide the reliable information needed to resolve safety issues is explored. The issue of sample representativeness must be resolved before sample information is reliable. Representativeness is a relative term but can be defined in terms of bias and precision. Currently, precision can be quantified and managed through an effective sampling and statistical analysis program. Quantifying bias is more difficult and is not being addressed under the current sampling strategies. Bias could be bounded by (1) employing new sampling methods that can obtain samples from other areas in the tanks, (2) putting in new risers on some worst case tanks and comparing the results from existing risers with new risers, or (3) sampling tanks through risers under which no disturbance or activity has previously occurred. With some bound on bias and estimates of precision, various sampling strategies could be determined and shown to be either cost-effective or infeasible
Existence and construction of large stable food webs
Haerter, Jan O.; Mitarai, Namiko; Sneppen, Kim
2017-09-01
Ecological diversity is ubiquitous despite the restrictions imposed by competitive exclusion and apparent competition. To explain the observed richness of species in a given habitat, food-web theory has explored nonlinear functional responses, self-interaction, or spatial structure and dispersal—model ingredients that have proven to promote stability and diversity. We return instead here to classical Lotka-Volterra equations, where species-species interaction is characterized by a simple product and spatial restrictions are ignored. We quantify how this idealization imposes constraints on coexistence and diversity for many species. To this end, we introduce the concept of free and controlled species and use this to demonstrate how stable food webs can be constructed by the sequential addition of species. The resulting food webs can reach dozens of species and generally yield nonrandom degree distributions in accordance with the constraints imposed through the assembly process. Our model thus serves as a formal starting point for the study of sustainable interaction patterns between species.
Analysis of uncertainty in modeling perceived risks
International Nuclear Information System (INIS)
Melnyk, R.; Sandquist, G.M.
2005-01-01
Expanding on a mathematical model developed for quantifying and assessing perceived risks, the distribution functions, variances, and uncertainties associated with estimating the model parameters are quantified. The analytical model permits the identification and assignment of any number of quantifiable risk perception factors that can be incorporated within standard risk methodology. Those risk perception factors associated with major technical issues are modeled using lognormal probability density functions to span the potentially large uncertainty variations associated with these risk perceptions. The model quantifies the logic of public risk perception and provides an effective means for measuring and responding to perceived risks. (authors)
Uncertainty quantification and stochastic modeling with Matlab
Souza de Cursi, Eduardo
2015-01-01
Uncertainty Quantification (UQ) is a relatively new research area which describes the methods and approaches used to supply quantitative descriptions of the effects of uncertainty, variability and errors in simulation problems and models. It is rapidly becoming a field of increasing importance, with many real-world applications within statistics, mathematics, probability and engineering, but also within the natural sciences. Literature on the topic has up until now been largely based on polynomial chaos, which raises difficulties when considering different types of approximation and does no
On the relationship between aerosol model uncertainty and radiative forcing uncertainty.
Lee, Lindsay A; Reddington, Carly L; Carslaw, Kenneth S
2016-05-24
The largest uncertainty in the historical radiative forcing of climate is caused by the interaction of aerosols with clouds. Historical forcing is not a directly measurable quantity, so reliable assessments depend on the development of global models of aerosols and clouds that are well constrained by observations. However, there has been no systematic assessment of how reduction in the uncertainty of global aerosol models will feed through to the uncertainty in the predicted forcing. We use a global model perturbed parameter ensemble to show that tight observational constraint of aerosol concentrations in the model has a relatively small effect on the aerosol-related uncertainty in the calculated forcing between preindustrial and present-day periods. One factor is the low sensitivity of present-day aerosol to natural emissions that determine the preindustrial aerosol state. However, the major cause of the weak constraint is that the full uncertainty space of the model generates a large number of model variants that are equally acceptable compared to present-day aerosol observations. The narrow range of aerosol concentrations in the observationally constrained model gives the impression of low aerosol model uncertainty. However, these multiple "equifinal" models predict a wide range of forcings. To make progress, we need to develop a much deeper understanding of model uncertainty and ways to use observations to constrain it. Equifinality in the aerosol model means that tuning of a small number of model processes to achieve model-observation agreement could give a misleading impression of model robustness.
Methodologies of Uncertainty Propagation Calculation
International Nuclear Information System (INIS)
Chojnacki, Eric
2002-01-01
After recalling the theoretical principle and the practical difficulties of the methodologies of uncertainty propagation calculation, the author discussed how to propagate input uncertainties. He said there were two kinds of input uncertainty: - variability: uncertainty due to heterogeneity, - lack of knowledge: uncertainty due to ignorance. It was therefore necessary to use two different propagation methods. He demonstrated this in a simple example which he generalised, treating the variability uncertainty by the probability theory and the lack of knowledge uncertainty by the fuzzy theory. He cautioned, however, against the systematic use of probability theory which may lead to unjustifiable and illegitimate precise answers. Mr Chojnacki's conclusions were that the importance of distinguishing variability and lack of knowledge increased as the problem was getting more and more complex in terms of number of parameters or time steps, and that it was necessary to develop uncertainty propagation methodologies combining probability theory and fuzzy theory
LOFT uncertainty-analysis methodology
International Nuclear Information System (INIS)
Lassahn, G.D.
1983-01-01
The methodology used for uncertainty analyses of measurements in the Loss-of-Fluid Test (LOFT) nuclear-reactor-safety research program is described and compared with other methodologies established for performing uncertainty analyses
LOFT uncertainty-analysis methodology
International Nuclear Information System (INIS)
Lassahn, G.D.
1983-01-01
The methodology used for uncertainty analyses of measurements in the Loss-of-Fluid Test (LOFT) nuclear reactor safety research program is described and compared with other methodologies established for performing uncertainty analyses
International Nuclear Information System (INIS)
Gigase, Yves
2007-01-01
Available in abstract form only. Full text of publication follows: The uncertainty on characteristics of radioactive LILW waste packages is difficult to determine and often very large. This results from a lack of knowledge of the constitution of the waste package and of the composition of the radioactive sources inside. To calculate a quantitative estimate of the uncertainty on a characteristic of a waste package one has to combine these various uncertainties. This paper discusses an approach to this problem, based on the use of the log-normal distribution, which is both elegant and easy to use. It can provide as example quantitative estimates of uncertainty intervals that 'make sense'. The purpose is to develop a pragmatic approach that can be integrated into existing characterization methods. In this paper we show how our method can be applied to the scaling factor method. We also explain how it can be used when estimating other more complex characteristics such as the total uncertainty of a collection of waste packages. This method could have applications in radioactive waste management, more in particular in those decision processes where the uncertainty on the amount of activity is considered to be important such as in probability risk assessment or the definition of criteria for acceptance or categorization. (author)
International Nuclear Information System (INIS)
Ortiz, M.G.; Ghan, L.S.; Vogl, J.
1991-01-01
The Nuclear Regulatory Commission (NRC) revised the Emergency Core Cooling System (ECCS) licensing rule to allow the use of Best Estimate (BE) computer codes, provided the uncertainty of the calculations are quantified and used in the licensing and regulation process. The NRC developed a generic methodology called Code Scaling, Applicability and Uncertainty (CSAU) to evaluate BE code uncertainties. The CSAU methodology was demonstrated with a specific application to a pressurized water reactor (PWR), experiencing a postulated large break loss-of-coolant accident (LBLOCA). The current work is part of an effort to adapt and demonstrate the CSAU methodology to a small break (SB) LOCA in a PWR of B and W design using RELAP5/MOD3 as the simulation tool. The subject of this paper is the Assessment and Ranging of Parameters (Element 2 of the CSAU methodology), which determines the contribution to uncertainty of specific models in the code
Do Orthopaedic Surgeons Acknowledge Uncertainty?
Teunis, Teun; Janssen, Stein; Guitton, Thierry G.; Ring, David; Parisien, Robert
2016-01-01
Much of the decision-making in orthopaedics rests on uncertain evidence. Uncertainty is therefore part of our normal daily practice, and yet physician uncertainty regarding treatment could diminish patients' health. It is not known if physician uncertainty is a function of the evidence alone or if
Assignment of uncertainties to scientific data
International Nuclear Information System (INIS)
Froehner, F.H.
1994-01-01
Long-standing problems of uncertainty assignment to scientific data came into a sharp focus in recent years when uncertainty information ('covariance files') had to be added to application-oriented large libraries of evaluated nuclear data such as ENDF and JEF. Question arouse about the best way to express uncertainties, the meaning of statistical and systematic errors, the origin of correlation and construction of covariance matrices, the combination of uncertain data from different sources, the general usefulness of results that are strictly valid only for Gaussian or only for linear statistical models, etc. Conventional statistical theory is often unable to give unambiguous answers, and tends to fail when statistics is bad so that prior information becomes crucial. Modern probability theory, on the other hand, incorporating decision information becomes group-theoretic results, is shown to provide straight and unique answers to such questions, and to deal easily with prior information and small samples. (author). 10 refs
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
On uncertainty relations in quantum mechanics
International Nuclear Information System (INIS)
Ignatovich, V.K.
2004-01-01
Uncertainty relations (UR) are shown to have nothing specific for quantum mechanics (QM), being the general property valid for the arbitrary function. A wave function of a particle simultaneously having a precisely defined position and momentum in QM is demonstrated. Interference on two slits in a screen is shown to exist in classical mechanics. A nonlinear classical system of equations replacing the QM Schroedinger equation is suggested. This approach is shown to have nothing in common with the Bohm mechanics
Quantum Action Principle with Generalized Uncertainty Principle
Gu, Jie
2013-01-01
One of the common features in all promising candidates of quantum gravity is the existence of a minimal length scale, which naturally emerges with a generalized uncertainty principle, or equivalently a modified commutation relation. Schwinger's quantum action principle was modified to incorporate this modification, and was applied to the calculation of the kernel of a free particle, partly recovering the result previously studied using path integral.
Uncertainty in reactive transport geochemical modelling
International Nuclear Information System (INIS)
Oedegaard-Jensen, A.; Ekberg, C.
2005-01-01
Full text of publication follows: Geochemical modelling is one way of predicting the transport of i.e. radionuclides in a rock formation. In a rock formation there will be fractures in which water and dissolved species can be transported. The composition of the water and the rock can either increase or decrease the mobility of the transported entities. When doing simulations on the mobility or transport of different species one has to know the exact water composition, the exact flow rates in the fracture and in the surrounding rock, the porosity and which minerals the rock is composed of. The problem with simulations on rocks is that the rock itself it not uniform i.e. larger fractures in some areas and smaller in other areas which can give different water flows. The rock composition can be different in different areas. In additions to this variance in the rock there are also problems with measuring the physical parameters used in a simulation. All measurements will perturb the rock and this perturbation will results in more or less correct values of the interesting parameters. The analytical methods used are also encumbered with uncertainties which in this case are added to the uncertainty from the perturbation of the analysed parameters. When doing simulation the effect of the uncertainties must be taken into account. As the computers are getting faster and faster the complexity of simulated systems are increased which also increase the uncertainty in the results from the simulations. In this paper we will show how the uncertainty in the different parameters will effect the solubility and mobility of different species. Small uncertainties in the input parameters can result in large uncertainties in the end. (authors)
Climate change impacts on extreme events in the United States: an uncertainty analysis
Extreme weather and climate events, such as heat waves, droughts and severe precipitation events, have substantial impacts on ecosystems and the economy. However, future climate simulations display large uncertainty in mean changes. As a result, the uncertainty in future changes ...
Uncertainty analysis comes to integrated assessment models for climate change and conversely
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.
DEFF Research Database (Denmark)
Greasley, David; Madsen, Jakob B.
2006-01-01
A severe collapse of fixed capital formation distinguished the onset of the Great Depression from other investment downturns between the world wars. Using a model estimated for the years 1890-2000, we show that the expected profitability of capital measured by Tobin's q, and the uncertainty...... surrounding expected profits indicated by share price volatility, were the chief influences on investment levels, and that heightened share price volatility played the dominant role in the crucial investment collapse in 1930. Investment did not simply follow the downward course of income at the onset...
Optimization under Uncertainty
Lopez, Rafael H.
2016-01-06
The goal of this poster is to present the main approaches to optimization of engineering systems in the presence of uncertainties. We begin by giving an insight about robust optimization. Next, we detail how to deal with probabilistic constraints in optimization, the so called the reliability based design. Subsequently, we present the risk optimization approach, which includes the expected costs of failure in the objective function. After that the basic description of each approach is given, the projects developed by CORE are presented. Finally, the main current topic of research of CORE is described.
Optimizing production under uncertainty
DEFF Research Database (Denmark)
Rasmussen, Svend
This Working Paper derives criteria for optimal production under uncertainty based on the state-contingent approach (Chambers and Quiggin, 2000), and discusses po-tential problems involved in applying the state-contingent approach in a normative context. The analytical approach uses the concept...... of state-contingent production functions and a definition of inputs including both sort of input, activity and alloca-tion technology. It also analyses production decisions where production is combined with trading in state-contingent claims such as insurance contracts. The final part discusses...
Commonplaces and social uncertainty
DEFF Research Database (Denmark)
Lassen, Inger
2008-01-01
This article explores the concept of uncertainty in four focus group discussions about genetically modified food. In the discussions, members of the general public interact with food biotechnology scientists while negotiating their attitudes towards genetic engineering. Their discussions offer...... an example of risk discourse in which the use of commonplaces seems to be a central feature (Myers 2004: 81). My analyses support earlier findings that commonplaces serve important interactional purposes (Barton 1999) and that they are used for mitigating disagreement, for closing topics and for facilitating...
Kadane, Joseph B
2011-01-01
An intuitive and mathematical introduction to subjective probability and Bayesian statistics. An accessible, comprehensive guide to the theory of Bayesian statistics, Principles of Uncertainty presents the subjective Bayesian approach, which has played a pivotal role in game theory, economics, and the recent boom in Markov Chain Monte Carlo methods. Both rigorous and friendly, the book contains: Introductory chapters examining each new concept or assumption Just-in-time mathematics -- the presentation of ideas just before they are applied Summary and exercises at the end of each chapter Discus
Mathematical Analysis of Uncertainty
Directory of Open Access Journals (Sweden)
Angel GARRIDO
2016-01-01
Full Text Available Classical Logic showed early its insufficiencies for solving AI problems. The introduction of Fuzzy Logic aims at this problem. There have been research in the conventional Rough direction alone or in the Fuzzy direction alone, and more recently, attempts to combine both into Fuzzy Rough Sets or Rough Fuzzy Sets. We analyse some new and powerful tools in the study of Uncertainty, as the Probabilistic Graphical Models, Chain Graphs, Bayesian Networks, and Markov Networks, integrating our knowledge of graphs and probability.
Uncertainty Quantification in High Throughput Screening ...
Using uncertainty quantification, we aim to improve the quality of modeling data from high throughput screening assays for use in risk assessment. ToxCast is a large-scale screening program that analyzes thousands of chemicals using over 800 assays representing hundreds of biochemical and cellular processes, including endocrine disruption, cytotoxicity, and zebrafish development. Over 2.6 million concentration response curves are fit to models to extract parameters related to potency and efficacy. Models built on ToxCast results are being used to rank and prioritize the toxicological risk of tested chemicals and to predict the toxicity of tens of thousands of chemicals not yet tested in vivo. However, the data size also presents challenges. When fitting the data, the choice of models, model selection strategy, and hit call criteria must reflect the need for computational efficiency and robustness, requiring hard and somewhat arbitrary cutoffs. When coupled with unavoidable noise in the experimental concentration response data, these hard cutoffs cause uncertainty in model parameters and the hit call itself. The uncertainty will then propagate through all of the models built on the data. Left unquantified, this uncertainty makes it difficult to fully interpret the data for risk assessment. We used bootstrap resampling methods to quantify the uncertainty in fitting models to the concentration response data. Bootstrap resampling determines confidence intervals for
Uncertainties in Organ Burdens Estimated from PAS
International Nuclear Information System (INIS)
La Bone, T.R.
2004-01-01
To calculate committed effective dose equivalent, one needs to know the quantity of the radionuclide in all significantly irradiated organs (the organ burden) as a function of time following the intake. There are two major sources of uncertainty in an organ burden estimated from personal air sampling (PAS) data: (1) The uncertainty in going from the exposure measured with the PAS to the quantity of aerosol inhaled by the individual, and (2) The uncertainty in going from the intake to the organ burdens at any given time, taking into consideration the biological variability of the biokinetic models from person to person (interperson variability) and in one person over time (intra-person variability). We have been using biokinetic modeling methods developed by researchers at the University of Florida to explore the impact of inter-person variability on the uncertainty of organ burdens estimated from PAS data. These initial studies suggest that the uncertainties are so large that PAS might be considered to be a qualitative (rather than quantitative) technique. These results indicate that more studies should be performed to properly classify the reliability and usefulness of using PAS monitoring data to estimate organ burdens, organ dose, and ultimately CEDE
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
Propagation of nuclear data uncertainties for fusion power measurements
Directory of Open Access Journals (Sweden)
Sjöstrand Henrik
2017-01-01
Full Text Available Neutron measurements using neutron activation systems are an essential part of the diagnostic system at large fusion machines such as JET and ITER. Nuclear data is used to infer the neutron yield. Consequently, high-quality nuclear data is essential for the proper determination of the neutron yield and fusion power. However, uncertainties due to nuclear data are not fully taken into account in uncertainty analysis for neutron yield calibrations using activation foils. This paper investigates the neutron yield uncertainty due to nuclear data using the so-called Total Monte Carlo Method. The work is performed using a detailed MCNP model of the JET fusion machine; the uncertainties due to the cross-sections and angular distributions in JET structural materials, as well as the activation cross-sections in the activation foils, are analysed. It is found that a significant contribution to the neutron yield uncertainty can come from uncertainties in the nuclear data.
Uncertainty information in climate data records from Earth observation
Merchant, Christopher J.; Paul, Frank; Popp, Thomas; Ablain, Michael; Bontemps, Sophie; Defourny, Pierre; Hollmann, Rainer; Lavergne, Thomas; Laeng, Alexandra; de Leeuw, Gerrit; Mittaz, Jonathan; Poulsen, Caroline; Povey, Adam C.; Reuter, Max; Sathyendranath, Shubha; Sandven, Stein; Sofieva, Viktoria F.; Wagner, Wolfgang
2017-07-01
The question of how to derive and present uncertainty information in climate data records (CDRs) has received sustained attention within the European Space Agency Climate Change Initiative (CCI), a programme to generate CDRs addressing a range of essential climate variables (ECVs) from satellite data. Here, we review the nature, mathematics, practicalities, and communication of uncertainty information in CDRs from Earth observations. This review paper argues that CDRs derived from satellite-based Earth observation (EO) should include rigorous uncertainty information to support the application of the data in contexts such as policy, climate modelling, and numerical weather prediction reanalysis. Uncertainty, error, and quality are distinct concepts, and the case is made that CDR products should follow international metrological norms for presenting quantified uncertainty. As a baseline for good practice, total standard uncertainty should be quantified per datum in a CDR, meaning that uncertainty estimates should clearly discriminate more and less certain data. In this case, flags for data quality should not duplicate uncertainty information, but instead describe complementary information (such as the confidence in the uncertainty estimate provided or indicators of conditions violating the retrieval assumptions). The paper discusses the many sources of error in CDRs, noting that different errors may be correlated across a wide range of timescales and space scales. Error effects that contribute negligibly to the total uncertainty in a single-satellite measurement can be the dominant sources of uncertainty in a CDR on the large space scales and long timescales that are highly relevant for some climate applications. For this reason, identifying and characterizing the relevant sources of uncertainty for CDRs is particularly challenging. The characterization of uncertainty caused by a given error effect involves assessing the magnitude of the effect, the shape of the
International Nuclear Information System (INIS)
Hogenbirk, A.
1994-07-01
The use is demonstrated of the newly developed ECN-SUSD sensitivity/uncertainty code system. With ECN-SUSD it is possible to calculate uncertainties in response parameters in fixed source calculations due to cross section uncertainties (using MF33) as well as to uncertainties in angular distributions (using MF34). It is shown that the latter contribution, which is generally neglected because of the lack of MF34-data in modern evaluations (except for EFF), is large in fusion reactor shielding calculations. (orig.)
Probabilistic Mass Growth Uncertainties
Plumer, Eric; Elliott, Darren
2013-01-01
Mass has been widely used as a variable input parameter for Cost Estimating Relationships (CER) for space systems. As these space systems progress from early concept studies and drawing boards to the launch pad, their masses tend to grow substantially, hence adversely affecting a primary input to most modeling CERs. Modeling and predicting mass uncertainty, based on historical and analogous data, is therefore critical and is an integral part of modeling cost risk. This paper presents the results of a NASA on-going effort to publish mass growth datasheet for adjusting single-point Technical Baseline Estimates (TBE) of masses of space instruments as well as spacecraft, for both earth orbiting and deep space missions at various stages of a project's lifecycle. This paper will also discusses the long term strategy of NASA Headquarters in publishing similar results, using a variety of cost driving metrics, on an annual basis. This paper provides quantitative results that show decreasing mass growth uncertainties as mass estimate maturity increases. This paper's analysis is based on historical data obtained from the NASA Cost Analysis Data Requirements (CADRe) database.
Uncertainty Propagation in Hypersonic Vehicle Aerothermoelastic Analysis
Lamorte, Nicolas Etienne
Hypersonic vehicles face a challenging flight environment. The aerothermoelastic analysis of its components requires numerous simplifying approximations. Identifying and quantifying the effect of uncertainties pushes the limits of the existing deterministic models, and is pursued in this work. An uncertainty quantification framework is used to propagate the effects of identified uncertainties on the stability margins and performance of the different systems considered. First, the aeroelastic stability of a typical section representative of a control surface on a hypersonic vehicle is examined. Variability in the uncoupled natural frequencies of the system is modeled to mimic the effect of aerodynamic heating. Next, the stability of an aerodynamically heated panel representing a component of the skin of a generic hypersonic vehicle is considered. Uncertainty in the location of transition from laminar to turbulent flow and the heat flux prediction is quantified using CFD. In both cases significant reductions of the stability margins are observed. A loosely coupled airframe--integrated scramjet engine is considered next. The elongated body and cowl of the engine flow path are subject to harsh aerothermodynamic loading which causes it to deform. Uncertainty associated with deformation prediction is propagated to the engine performance analysis. The cowl deformation is the main contributor to the sensitivity of the propulsion system performance. Finally, a framework for aerothermoelastic stability boundary calculation for hypersonic vehicles using CFD is developed. The usage of CFD enables one to consider different turbulence conditions, laminar or turbulent, and different models of the air mixture, in particular real gas model which accounts for dissociation of molecules at high temperature. The system is found to be sensitive to turbulence modeling as well as the location of the transition from laminar to turbulent flow. Real gas effects play a minor role in the
Embracing uncertainty in applied ecology.
Milner-Gulland, E J; Shea, K
2017-12-01
Applied ecologists often face uncertainty that hinders effective decision-making.Common traps that may catch the unwary are: ignoring uncertainty, acknowledging uncertainty but ploughing on, focussing on trivial uncertainties, believing your models, and unclear objectives.We integrate research insights and examples from a wide range of applied ecological fields to illustrate advances that are generally underused, but could facilitate ecologists' ability to plan and execute research to support management.Recommended approaches to avoid uncertainty traps are: embracing models, using decision theory, using models more effectively, thinking experimentally, and being realistic about uncertainty. Synthesis and applications . Applied ecologists can become more effective at informing management by using approaches that explicitly take account of uncertainty.
Quantification of margins and uncertainties: Alternative representations of epistemic uncertainty
International Nuclear Information System (INIS)
Helton, Jon C.; Johnson, Jay D.
2011-01-01
In 2001, the National Nuclear Security Administration of the U.S. Department of Energy in conjunction with the national security laboratories (i.e., Los Alamos National Laboratory, Lawrence Livermore National Laboratory and Sandia National Laboratories) initiated development of a process designated Quantification of Margins and Uncertainties (QMU) for the use of risk assessment methodologies in the certification of the reliability and safety of the nation's nuclear weapons stockpile. A previous presentation, 'Quantification of Margins and Uncertainties: Conceptual and Computational Basis,' describes the basic ideas that underlie QMU and illustrates these ideas with two notional examples that employ probability for the representation of aleatory and epistemic uncertainty. The current presentation introduces and illustrates the use of interval analysis, possibility theory and evidence theory as alternatives to the use of probability theory for the representation of epistemic uncertainty in QMU-type analyses. The following topics are considered: the mathematical structure of alternative representations of uncertainty, alternative representations of epistemic uncertainty in QMU analyses involving only epistemic uncertainty, and alternative representations of epistemic uncertainty in QMU analyses involving a separation of aleatory and epistemic uncertainty. Analyses involving interval analysis, possibility theory and evidence theory are illustrated with the same two notional examples used in the presentation indicated above to illustrate the use of probability to represent aleatory and epistemic uncertainty in QMU analyses.
Solar Panel Installations on Existing Structures
Tim D. Sass; Pe; Leed
2013-01-01
The rising price of fossil fuels, government incentives and growing public aware-ness for the need to implement sustainable energy supplies has resulted in a large in-crease in solar panel installations across the country. For many sites the most eco-nomical solar panel installation uses existing, southerly facing rooftops. Adding solar panels to an existing roof typically means increased loads that must be borne by the building-s structural elements. The structural desig...
Huang, Hening
2018-01-01
This paper is the second (Part II) in a series of two papers (Part I and Part II). Part I has quantitatively discussed the fundamental limitations of the t-interval method for uncertainty estimation with a small number of measurements. This paper (Part II) reveals that the t-interval is an ‘exact’ answer to a wrong question; it is actually misused in uncertainty estimation. This paper proposes a redefinition of uncertainty, based on the classical theory of errors and the theory of point estimation, and a modification of the conventional approach to estimating measurement uncertainty. It also presents an asymptotic procedure for estimating the z-interval. The proposed modification is to replace the t-based uncertainty with an uncertainty estimator (mean- or median-unbiased). The uncertainty estimator method is an approximate answer to the right question to uncertainty estimation. The modified approach provides realistic estimates of uncertainty, regardless of whether the population standard deviation is known or unknown, or if the sample size is small or large. As an application example of the modified approach, this paper presents a resolution to the Du-Yang paradox (i.e. Paradox 2), one of the three paradoxes caused by the misuse of the t-interval in uncertainty estimation.
Saikawa, E.; Trail, M.; Young, C. L.; Zhong, M.; Avramov, A.; Kim, H.; Wu, Q.; Janssens-Maenhout, G. G. A.; Kurokawa, J. I.; Klimont, Z.; Wagner, F.; Naik, V.; Horowitz, L. W.; Zhao, Y.; Nagpure, A.; Gurjar, B.; Zhang, Q.
2017-12-01
Greenhouse gas and air pollutant precursor emissions have been increasing rapidly in both China and India, resulting in local to regional scale effects on air quality. Modelers use emission inventories to represent the temporal and spatial distribution of impacts of air pollutant emissions on regional and global air quality. However, large uncertainties exist in emission inventories. Quantification of uncertainties in emission estimates is essential to better understand the linkages among emissions, air quality, climate, and health. We use Monte Carlo methods to assess the uncertainties of the existing carbon dioxide (CO2), carbon monoxide (CO), sulfur dioxide (SO2), nitrogen oxides (NOx), and particulate matter (PM) emission estimates for both China and India. We focus on the period between 2000 and 2008. In addition to national totals, we also analyze emissions from four source sectors, including industry, transport, power, and residential. We also assess differences in the existing emission estimates within each of the subnational regions. We find large disagreements among the existing inventories at disaggregated levels. We further assess the impact of these differences in emissions on air quality using a chemical transport model. More efforts are needed to constrain emissions, especially in the Indo-Gangetic Plains and in the East and Central regions of China, where large differences across emission inventories result in concomitant large differences in the simulated concentrations of PM and ozone. Our study also highlights the importance of constraining SO2, NOx, and NH3 emissions for secondary PM concentrations over China and India.
Probabilistic risk assessment for new and existing chemicals: Example calculations
Jager T; Hollander HA den; Janssen GB; Poel P van der; Rikken MGJ; Vermeire TG; ECO; CSR; LAE; CSR
2000-01-01
In the risk assessment methods for new and existing chemicals in the EU, "risk" is characterised by means of the deterministic quotient of exposure and effects (PEC/PNEC or Margin of Safety). From a scientific viewpoint, the uncertainty in the risk quotient should be accounted for explicitly in the
Data-Driven Model Uncertainty Estimation in Hydrologic Data Assimilation
Pathiraja, S.; Moradkhani, H.; Marshall, L.; Sharma, A.; Geenens, G.
2018-02-01
The increasing availability of earth observations necessitates mathematical methods to optimally combine such data with hydrologic models. Several algorithms exist for such purposes, under the umbrella of data assimilation (DA). However, DA methods are often applied in a suboptimal fashion for complex real-world problems, due largely to several practical implementation issues. One such issue is error characterization, which is known to be critical for a successful assimilation. Mischaracterized errors lead to suboptimal forecasts, and in the worst case, to degraded estimates even compared to the no assimilation case. Model uncertainty characterization has received little attention relative to other aspects of DA science. Traditional methods rely on subjective, ad hoc tuning factors or parametric distribution assumptions that may not always be applicable. We propose a novel data-driven approach (named SDMU) to model uncertainty characterization for DA studies where (1) the system states are partially observed and (2) minimal prior knowledge of the model error processes is available, except that the errors display state dependence. It includes an approach for estimating the uncertainty in hidden model states, with the end goal of improving predictions of observed variables. The SDMU is therefore suited to DA studies where the observed variables are of primary interest. Its efficacy is demonstrated through a synthetic case study with low-dimensional chaotic dynamics and a real hydrologic experiment for one-day-ahead streamflow forecasting. In both experiments, the proposed method leads to substantial improvements in the hidden states and observed system outputs over a standard method involving perturbation with Gaussian noise.
Uncertainty, robustness, and the value of information in managing a population of northern bobwhites
Johnson, Fred A.; Hagan, Greg; Palmer, William E.; Kemmerer, Michael
2014-01-01
The abundance of northern bobwhites (Colinus virginianus) has decreased throughout their range. Managers often respond by considering improvements in harvest and habitat management practices, but this can be challenging if substantial uncertainty exists concerning the cause(s) of the decline. We were interested in how application of decision science could be used to help managers on a large, public management area in southwestern Florida where the bobwhite is a featured species and where abundance has severely declined. We conducted a workshop with managers and scientists to elicit management objectives, alternative hypotheses concerning population limitation in bobwhites, potential management actions, and predicted management outcomes. Using standard and robust approaches to decision making, we determined that improved water management and perhaps some changes in hunting practices would be expected to produce the best management outcomes in the face of uncertainty about what is limiting bobwhite abundance. We used a criterion called the expected value of perfect information to determine that a robust management strategy may perform nearly as well as an optimal management strategy (i.e., a strategy that is expected to perform best, given the relative importance of different management objectives) with all uncertainty resolved. We used the expected value of partial information to determine that management performance could be increased most by eliminating uncertainty over excessive-harvest and human-disturbance hypotheses. Beyond learning about the factors limiting bobwhites, adoption of a dynamic management strategy, which recognizes temporal changes in resource and environmental conditions, might produce the greatest management benefit. Our research demonstrates that robust approaches to decision making, combined with estimates of the value of information, can offer considerable insight into preferred management approaches when great uncertainty exists about
UNCERTAINTY IN THE DEVELOPMENT AND USE OF EQUATION OF STATE MODELS
Weirs, V. Gregory; Fabian, Nathan; Potter, Kristin; McNamara, Laura; Otahal, Thomas
2013-01-01
In this paper we present the results from a series of focus groups on the visualization of uncertainty in equation-of-state (EOS) models. The initial goal was to identify the most effective ways to present EOS uncertainty to analysts, code developers, and material modelers. Four prototype visualizations were developed to present EOS surfaces in a three-dimensional, thermodynamic space. Focus group participants, primarily from Sandia National Laboratories, evaluated particular features of the various techniques for different use cases and discussed their individual workflow processes, experiences with other visualization tools, and the impact of uncertainty on their work. Related to our prototypes, we found the 3D presentations to be helpful for seeing a large amount of information at once and for a big-picture view; however, participants also desired relatively simple, two-dimensional graphics for better quantitative understanding and because these plots are part of the existing visual language for material models. In addition to feedback on the prototypes, several themes and issues emerged that are as compelling as the original goal and will eventually serve as a starting point for further development of visualization and analysis tools. In particular, a distributed workflow centered around material models was identified. Material model stakeholders contribute and extract information at different points in this workflow depending on their role, but encounter various institutional and technical barriers which restrict the flow of information. An effective software tool for this community must be cognizant of this workflow and alleviate the bottlenecks and barriers within it. Uncertainty in EOS models is defined and interpreted differently at the various stages of the workflow. In this context, uncertainty propagation is difficult to reduce to the mathematical problem of estimating the uncertainty of an output from uncertain inputs.
Heisenberg's principle of uncertainty and the uncertainty relations
International Nuclear Information System (INIS)
Redei, Miklos
1987-01-01
The usual verbal form of the Heisenberg uncertainty principle and the usual mathematical formulation (the so-called uncertainty theorem) are not equivalent. The meaning of the concept 'uncertainty' is not unambiguous and different interpretations are used in the literature. Recently a renewed interest has appeared to reinterpret and reformulate the precise meaning of Heisenberg's principle and to find adequate mathematical form. The suggested new theorems are surveyed and critically analyzed. (D.Gy.) 20 refs
Petzinger, Tom
I am trying to make money in the biotech industry from complexity science. And I am doing it with inspiration that I picked up on the edge of Appalachia spending time with June Holley and ACEnet when I was a Wall Street Journal reporter. I took some of those ideas to Pittsburgh, in biotechnology, in a completely private setting with an economic development focus, but also with a mission t o return profit to private capital. And we are doing that. I submit as a hypothesis, something we are figuring out in the post- industrial era, that business evolves. It is not the definition of business, but business critically involves the design of systems in which uncertainty is treated as a certainty. That is what I have seen and what I have tried to put into practice.
2012-03-01
ISO / IEC 17025 Inspection Bodies – ISO / IEC 17020 RMPs – ISO Guide 34 (Reference...certify to : ISO 9001 (QMS), ISO 14001 (EMS), TS 16949 (US Automotive) etc. 2 3 DoD QSM 4.2 standard ISO / IEC 17025 :2005 Each has uncertainty...IPV6, NLLAP, NEFAP TRAINING Programs Certification Bodies – ISO / IEC 17021 Accreditation for Management System
Traceability and Measurement Uncertainty
DEFF Research Database (Denmark)
Tosello, Guido; De Chiffre, Leonardo
2004-01-01
. The project partnership aims (composed by 7 partners in 5 countries, thus covering a real European spread in high tech production technology) to develop and implement an advanced e-learning system that integrates contributions from quite different disciplines into a user-centred approach that strictly....... Machine tool testing 9. The role of manufacturing metrology for QM 10. Inspection planning 11. Quality management of measurements incl. Documentation 12. Advanced manufacturing measurement technology The present report (which represents the section 2 - Traceability and Measurement Uncertainty – of the e-learning......This report is made as a part of the project ‘Metro-E-Learn: European e-Learning in Manufacturing Metrology’, an EU project under the program SOCRATES MINERVA (ODL and ICT in Education), Contract No: 101434-CP-1-2002-1-DE-MINERVA, coordinated by Friedrich-Alexander-University Erlangen...
Decision making under uncertainty
International Nuclear Information System (INIS)
Cyert, R.M.
1989-01-01
This paper reports on ways of improving the reliability of products and systems in this country if we are to survive as a first-rate industrial power. The use of statistical techniques have, since the 1920s, been viewed as one of the methods for testing quality and estimating the level of quality in a universe of output. Statistical quality control is not relevant, generally, to improving systems in an industry like yours, but certainly the use of probability concepts is of significance. In addition, when it is recognized that part of the problem involves making decisions under uncertainty, it becomes clear that techniques such as sequential decision making and Bayesian analysis become major methodological approaches that must be utilized
Sustainability and uncertainty
DEFF Research Database (Denmark)
Jensen, Karsten Klint
2007-01-01
The widely used concept of sustainability is seldom precisely defined, and its clarification involves making up one's mind about a range of difficult questions. One line of research (bottom-up) takes sustaining a system over time as its starting point and then infers prescriptions from...... this requirement. Another line (top-down) takes an economical interpretation of the Brundtland Commission's suggestion that the present generation's needsatisfaction should not compromise the need-satisfaction of future generations as its starting point. It then measures sustainability at the level of society...... a clarified ethical goal, disagreements can arise. At present we do not know what substitutions will be possible in the future. This uncertainty clearly affects the prescriptions that follow from the measure of sustainability. Consequently, decisions about how to make future agriculture sustainable...
Observational uncertainty and regional climate model evaluation: A pan-European perspective
Kotlarski, Sven; Szabó, Péter; Herrera, Sixto; Räty, Olle; Keuler, Klaus; Soares, Pedro M.; Cardoso, Rita M.; Bosshard, Thomas; Pagé, Christian; Boberg, Fredrik; Gutiérrez, José M.; Jaczewski, Adam; Kreienkamp, Frank; Liniger, Mark. A.; Lussana, Cristian; Szepszo, Gabriella
2017-04-01
Local and regional climate change assessments based on downscaling methods crucially depend on the existence of accurate and reliable observational reference data. In dynamical downscaling via regional climate models (RCMs) observational data can influence model development itself and, later on, model evaluation, parameter calibration and added value assessment. In empirical-statistical downscaling, observations serve as predictand data and directly influence model calibration with corresponding effects on downscaled climate change projections. Focusing on the evaluation of RCMs, we here analyze the influence of uncertainties in observational reference data on evaluation results in a well-defined performance assessment framework and on a European scale. For this purpose we employ three different gridded observational reference grids, namely (1) the well-established EOBS dataset (2) the recently developed EURO4M-MESAN regional re-analysis, and (3) several national high-resolution and quality-controlled gridded datasets that recently became available. In terms of climate models five reanalysis-driven experiments carried out by five different RCMs within the EURO-CORDEX framework are used. Two variables (temperature and precipitation) and a range of evaluation metrics that reflect different aspects of RCM performance are considered. We furthermore include an illustrative model ranking exercise and relate observational spread to RCM spread. The results obtained indicate a varying influence of observational uncertainty on model evaluation depending on the variable, the season, the region and the specific performance metric considered. Over most parts of the continent, the influence of the choice of the reference dataset for temperature is rather small for seasonal mean values and inter-annual variability. Here, model uncertainty (as measured by the spread between the five RCM simulations considered) is typically much larger than reference data uncertainty. For
International Nuclear Information System (INIS)
Kančev, Duško; Čepin, Marko
2012-01-01
Highlights: ► Application of analytical unavailability model integrating T and M, ageing, and test strategy. ► Ageing data uncertainty propagation on system level assessed via Monte Carlo simulation. ► Uncertainty impact is growing with the extension of the surveillance test interval. ► Calculated system unavailability dependence on two different sensitivity study ageing databases. ► System unavailability sensitivity insights regarding specific groups of BEs as test intervals extend. - Abstract: The interest in operational lifetime extension of the existing nuclear power plants is growing. Consequently, plants life management programs, considering safety components ageing, are being developed and employed. Ageing represents a gradual degradation of the physical properties and functional performance of different components consequently implying their reduced availability. Analyses, which are being made in the direction of nuclear power plants lifetime extension are based upon components ageing management programs. On the other side, the large uncertainties of the ageing parameters as well as the uncertainties associated with most of the reliability data collections are widely acknowledged. This paper addresses the uncertainty and sensitivity analyses conducted utilizing a previously developed age-dependent unavailability model, integrating effects of test and maintenance activities, for a selected stand-by safety system in a nuclear power plant. The most important problem is the lack of data concerning the effects of ageing as well as the relatively high uncertainty associated to these data, which would correspond to more detailed modelling of ageing. A standard Monte Carlo simulation was coded for the purpose of this paper and utilized in the process of assessment of the component ageing parameters uncertainty propagation on system level. The obtained results from the uncertainty analysis indicate the extent to which the uncertainty of the selected
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.
An uncertainty inventory demonstration - a primary step in uncertainty quantification
Energy Technology Data Exchange (ETDEWEB)
Langenbrunner, James R. [Los Alamos National Laboratory; Booker, Jane M [Los Alamos National Laboratory; Hemez, Francois M [Los Alamos National Laboratory; Salazar, Issac F [Los Alamos National Laboratory; Ross, Timothy J [UNM
2009-01-01
Tools, methods, and theories for assessing and quantifying uncertainties vary by application. Uncertainty quantification tasks have unique desiderata and circumstances. To realistically assess uncertainty requires the engineer/scientist to specify mathematical models, the physical phenomena of interest, and the theory or framework for assessments. For example, Probabilistic Risk Assessment (PRA) specifically identifies uncertainties using probability theory, and therefore, PRA's lack formal procedures for quantifying uncertainties that are not probabilistic. The Phenomena Identification and Ranking Technique (PIRT) proceeds by ranking phenomena using scoring criteria that results in linguistic descriptors, such as importance ranked with words, 'High/Medium/Low.' The use of words allows PIRT to be flexible, but the analysis may then be difficult to combine with other uncertainty theories. We propose that a necessary step for the development of a procedure or protocol for uncertainty quantification (UQ) is the application of an Uncertainty Inventory. An Uncertainty Inventory should be considered and performed in the earliest stages of UQ.
Contribution to uncertainties computing: application to aerosol nanoparticles metrology
International Nuclear Information System (INIS)
Coquelin, Loic
2013-01-01
This thesis aims to provide SMPS users with a methodology to compute uncertainties associated with the estimation of aerosol size distributions. SMPS selects and detects airborne particles with a Differential Mobility Analyser (DMA) and a Condensation Particle Counter (CPC), respectively. The on-line measurement provides particle counting over a large measuring range. Then, recovering aerosol size distribution from CPC measurements yields to consider an inverse problem under uncertainty. A review of models to represent CPC measurements as a function of the aerosol size distribution is presented in the first chapter showing that competitive theories exist to model the physic involved in the measurement. It shows in the meantime the necessity of modelling parameters and other functions as uncertain. The physical model we established was first created to accurately represent the physic and second to be low time consuming. The first requirement is obvious as it characterizes the performance of the model. On the other hand, the time constraint is common to every large-scale problems for which an evaluation of the uncertainty is sought. To perform the estimation of the size distribution, a new criterion that couples regularization techniques and decomposition on a wavelet basis is described. Regularization is largely used to solve ill-posed problems. The regularized solution is computed as a trade-off between fidelity to the data and prior on the solution to be rebuilt, the trade-off being represented by a scalar known as the regularization parameter. Nevertheless, when dealing with size distributions showing broad and sharp profiles, an homogeneous prior is no longer suitable. Main improvement of this work is brought when such situations occur. The multi-scale approach we propose for the definition of the new prior is an alternative that enables to adjust the weights of the regularization on each scale of the signal. The method is tested against common regularization
Damage assessment of composite plate structures with material and measurement uncertainty
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.
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
Illness uncertainty and treatment motivation in type 2 diabetes patients.
Apóstolo, João Luís Alves; Viveiros, Catarina Sofia Castro; Nunes, Helena Isabel Ribeiro; Domingues, Helena Raquel Faustino
2007-01-01
To characterize the uncertainty in illness and the motivation for treatment and to evaluate the existing relation between these variables in individuals with type 2 diabetes. Descriptive, correlational study, using a sample of 62 individuals in diabetes consultation sessions. The Uncertainty Stress Scale and the Treatment Self-Regulation Questionnaire were used. The individuals with type 2 diabetes present low levels of uncertainty in illness and a high motivation for treatment, with a stronger intrinsic than extrinsic motivation. A negative correlation was verified between the uncertainty in the face of the prognosis and treatment and the intrinsic motivation. These individuals are already adapted, acting according to the meanings they attribute to illness. Uncertainty can function as a threat, intervening negatively in the attribution of meaning to the events related to illness and in the process of adaptation and motivation to adhere to treatment. Intrinsic motivation seems to be essential to adhere to treatment.
On Commitments and Other Uncertainty Reduction Tools in Joint Action
Directory of Open Access Journals (Sweden)
Michael John
2015-01-01
Full Text Available In this paper, we evaluate the proposal that a central function of commitments within joint action is to reduce various kinds of uncertainty, and that this accounts for the prevalence of commitments in joint action. While this idea is prima facie attractive, we argue that it faces two serious problems. First, commitments can only reduce uncertainty if they are credible, and accounting for the credibility of commitments proves not to be straightforward. Second, there are many other ways in which uncertainty is commonly reduced within joint actions, which raises the possibility that commitments may be superfluous. Nevertheless, we argue that the existence of these alternative uncertainty reduction processes does not make commitments superfluous after all but, rather, helps to explain how commitments may contribute in various ways to uncertainty reduction.
Risk Management and Uncertainty in Infrastructure Projects
DEFF Research Database (Denmark)
Harty, Chris; Neerup Themsen, Tim; Tryggestad, Kjell
2014-01-01
The assumption that large complex projects should be managed in order to reduce uncertainty and increase predictability is not new. What is relatively new, however, is that uncertainty reduction can and should be obtained through formal risk management approaches. We question both assumptions...... by addressing a more fundamental question about the role of knowledge in current risk management practices. Inquiries into the predominant approaches to risk management in large infrastructure and construction projects reveal their assumptions about knowledge and we discuss the ramifications these have...... for project and construction management. Our argument and claim is that predominant risk management approaches tends to reinforce conventional ideas of project control whilst undermining other notions of value and relevance of built assets and project management process. These approaches fail to consider...
Essays on model uncertainty in financial models
Li, Jing
2018-01-01
This dissertation studies model uncertainty, particularly in financial models. It consists of two empirical chapters and one theoretical chapter. The first empirical chapter (Chapter 2) classifies model uncertainty into parameter uncertainty and misspecification uncertainty. It investigates the
A new uncertainty importance measure
International Nuclear Information System (INIS)
Borgonovo, E.
2007-01-01
Uncertainty in parameters is present in many risk assessment problems and leads to uncertainty in model predictions. In this work, we introduce a global sensitivity indicator which looks at the influence of input uncertainty on the entire output distribution without reference to a specific moment of the output (moment independence) and which can be defined also in the presence of correlations among the parameters. We discuss its mathematical properties and highlight the differences between the present indicator, variance-based uncertainty importance measures and a moment independent sensitivity indicator previously introduced in the literature. Numerical results are discussed with application to the probabilistic risk assessment model on which Iman [A matrix-based approach to uncertainty and sensitivity analysis for fault trees. Risk Anal 1987;7(1):22-33] first introduced uncertainty importance measures
Uncertainty Management and Sensitivity Analysis
DEFF Research Database (Denmark)
Rosenbaum, Ralph K.; Georgiadis, Stylianos; Fantke, Peter
2018-01-01
Uncertainty is always there and LCA is no exception to that. The presence of uncertainties of different types and from numerous sources in LCA results is a fact, but managing them allows to quantify and improve the precision of a study and the robustness of its conclusions. LCA practice sometimes...... suffers from an imbalanced perception of uncertainties, justifying modelling choices and omissions. Identifying prevalent misconceptions around uncertainties in LCA is a central goal of this chapter, aiming to establish a positive approach focusing on the advantages of uncertainty management. The main...... objectives of this chapter are to learn how to deal with uncertainty in the context of LCA, how to quantify it, interpret and use it, and how to communicate it. The subject is approached more holistically than just focusing on relevant statistical methods or purely mathematical aspects. This chapter...
Additivity of entropic uncertainty relations
Directory of Open Access Journals (Sweden)
René Schwonnek
2018-03-01
Full Text Available We consider the uncertainty between two pairs of local projective measurements performed on a multipartite system. We show that the optimal bound in any linear uncertainty relation, formulated in terms of the Shannon entropy, is additive. This directly implies, against naive intuition, that the minimal entropic uncertainty can always be realized by fully separable states. Hence, in contradiction to proposals by other authors, no entanglement witness can be constructed solely by comparing the attainable uncertainties of entangled and separable states. However, our result gives rise to a huge simplification for computing global uncertainty bounds as they now can be deduced from local ones. Furthermore, we provide the natural generalization of the Maassen and Uffink inequality for linear uncertainty relations with arbitrary positive coefficients.
Validity of WTP measures under preference uncertainty
Kniebes, Carola; Rehdanz, Katrin; Schmidt, Ulrich
2014-01-01
This paper establishes a new method for eliciting Willingness to Pay (WTP) in contingent valuation (CV) studies with an open-ended elicitation format: the Range-WTP method. In contrast to the traditional approach for eliciting Point-WTP, Range-WTP explicitly allows for preference uncertainty in responses. Using data from two novel large-scale surveys on the perception of solar radiation management (SRM), a little-known technique for counteracting climate change, we compare the performance of ...
Calibration and Propagation of Uncertainty for Independence
Energy Technology Data Exchange (ETDEWEB)
Holland, Troy Michael [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Kress, Joel David [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Bhat, Kabekode Ghanasham [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2017-06-30
This document reports on progress and methods for the calibration and uncertainty quantification of the Independence model developed at UT Austin. The Independence model is an advanced thermodynamic and process model framework for piperazine solutions as a high-performance CO_{2} capture solvent. Progress is presented in the framework of the CCSI standard basic data model inference framework. Recent work has largely focused on the thermodynamic submodels of Independence.
Decisions under uncertainty using Bayesian analysis
Directory of Open Access Journals (Sweden)
Stelian STANCU
2006-01-01
Full Text Available The present paper makes a short presentation of the Bayesian decions method, where extrainformation brings a great support to decision making process, but also attract new costs. In this situation, getting new information, generally experimentaly based, contributes to diminushing the uncertainty degree that influences decision making process. As a conclusion, in a large number of decision problems, there is the possibility that the decision makers will renew some decisions already taken because of the facilities offered by obtainig extrainformation.
Decommissioning funding: ethics, implementation, uncertainties
International Nuclear Information System (INIS)
2006-01-01
This status report on Decommissioning Funding: Ethics, Implementation, Uncertainties also draws on the experience of the NEA Working Party on Decommissioning and Dismantling (WPDD). The report offers, in a concise form, an overview of relevant considerations on decommissioning funding mechanisms with regard to ethics, implementation and uncertainties. Underlying ethical principles found in international agreements are identified, and factors influencing the accumulation and management of funds for decommissioning nuclear facilities are discussed together with the main sources of uncertainties of funding systems. (authors)
The Uncertainty of Measurement Results
Energy Technology Data Exchange (ETDEWEB)
Ambrus, A. [Hungarian Food Safety Office, Budapest (Hungary)
2009-07-15
Factors affecting the uncertainty of measurement are explained, basic statistical formulae given, and the theoretical concept explained in the context of pesticide formulation analysis. Practical guidance is provided on how to determine individual uncertainty components within an analytical procedure. An extended and comprehensive table containing the relevant mathematical/statistical expressions elucidates the relevant underlying principles. Appendix I provides a practical elaborated example on measurement uncertainty estimation, above all utilizing experimental repeatability and reproducibility laboratory data. (author)
Uncertainty analysis of environmental models
International Nuclear Information System (INIS)
Monte, L.
1990-01-01
In the present paper an evaluation of the output uncertainty of an environmental model for assessing the transfer of 137 Cs and 131 I in the human food chain are carried out on the basis of a statistical analysis of data reported by the literature. The uncertainty analysis offers the oppotunity of obtaining some remarkable information about the uncertainty of models predicting the migration of non radioactive substances in the environment mainly in relation to the dry and wet deposition
Multi-scenario modelling of uncertainty in stochastic chemical systems
International Nuclear Information System (INIS)
Evans, R. David; Ricardez-Sandoval, Luis A.
2014-01-01
Uncertainty analysis has not been well studied at the molecular scale, despite extensive knowledge of uncertainty in macroscale systems. The ability to predict the effect of uncertainty allows for robust control of small scale systems such as nanoreactors, surface reactions, and gene toggle switches. However, it is difficult to model uncertainty in such chemical systems as they are stochastic in nature, and require a large computational cost. To address this issue, a new model of uncertainty propagation in stochastic chemical systems, based on the Chemical Master Equation, is proposed in the present study. The uncertain solution is approximated by a composite state comprised of the averaged effect of samples from the uncertain parameter distributions. This model is then used to study the effect of uncertainty on an isomerization system and a two gene regulation network called a repressilator. The results of this model show that uncertainty in stochastic systems is dependent on both the uncertain distribution, and the system under investigation. -- Highlights: •A method to model uncertainty on stochastic systems was developed. •The method is based on the Chemical Master Equation. •Uncertainty in an isomerization reaction and a gene regulation network was modelled. •Effects were significant and dependent on the uncertain input and reaction system. •The model was computationally more efficient than Kinetic Monte Carlo
Uncertainty quantification in resonance absorption
International Nuclear Information System (INIS)
Williams, M.M.R.
2012-01-01
We assess the uncertainty in the resonance escape probability due to uncertainty in the neutron and radiation line widths for the first 21 resonances in 232 Th as given by . Simulation, quadrature and polynomial chaos methods are used and the resonance data are assumed to obey a beta distribution. We find the uncertainty in the total resonance escape probability to be the equivalent, in reactivity, of 75–130 pcm. Also shown are pdfs of the resonance escape probability for each resonance and the variation of the uncertainty with temperature. The viability of the polynomial chaos expansion method is clearly demonstrated.
Reliability analysis under epistemic uncertainty
International Nuclear Information System (INIS)
Nannapaneni, Saideep; Mahadevan, Sankaran
2016-01-01
This paper proposes a probabilistic framework to include both aleatory and epistemic uncertainty within model-based reliability estimation of engineering systems for individual limit states. Epistemic uncertainty is considered due to both data and model sources. Sparse point and/or interval data regarding the input random variables leads to uncertainty regarding their distribution types, distribution parameters, and correlations; this statistical uncertainty is included in the reliability analysis through a combination of likelihood-based representation, Bayesian hypothesis testing, and Bayesian model averaging techniques. Model errors, which include numerical solution errors and model form errors, are quantified through Gaussian process models and included in the reliability analysis. The probability integral transform is used to develop an auxiliary variable approach that facilitates a single-level representation of both aleatory and epistemic uncertainty. This strategy results in an efficient single-loop implementation of Monte Carlo simulation (MCS) and FORM/SORM techniques for reliability estimation under both aleatory and epistemic uncertainty. Two engineering examples are used to demonstrate the proposed methodology. - Highlights: • Epistemic uncertainty due to data and model included in reliability analysis. • A novel FORM-based approach proposed to include aleatory and epistemic uncertainty. • A single-loop Monte Carlo approach proposed to include both types of uncertainties. • Two engineering examples used for illustration.
Simplified propagation of standard uncertainties
International Nuclear Information System (INIS)
Shull, A.H.
1997-01-01
An essential part of any measurement control program is adequate knowledge of the uncertainties of the measurement system standards. Only with an estimate of the standards'' uncertainties can one determine if the standard is adequate for its intended use or can one calculate the total uncertainty of the measurement process. Purchased standards usually have estimates of uncertainty on their certificates. However, when standards are prepared and characterized by a laboratory, variance propagation is required to estimate the uncertainty of the standard. Traditional variance propagation typically involves tedious use of partial derivatives, unfriendly software and the availability of statistical expertise. As a result, the uncertainty of prepared standards is often not determined or determined incorrectly. For situations meeting stated assumptions, easier shortcut methods of estimation are now available which eliminate the need for partial derivatives and require only a spreadsheet or calculator. A system of simplifying the calculations by dividing into subgroups of absolute and relative uncertainties is utilized. These methods also incorporate the International Standards Organization (ISO) concepts for combining systematic and random uncertainties as published in their Guide to the Expression of Measurement Uncertainty. Details of the simplified methods and examples of their use are included in the paper
International Nuclear Information System (INIS)
Chapman, J. B.; Pohlmann, K.; Pohll, G.; Hassan, A.; Sanders, P.; Sanchez, M.; Jaunarajs, S.
2002-01-01
parameter values and the additive effects of multiple sources of uncertainty. Ultimately, the question was whether new data collection would substantially reduce uncertainty in the model. A Data Decision Analysis (DDA) was performed to quantify uncertainty in the existing model and determine the most cost-beneficial activities for reducing uncertainty, if reduction was needed. The DDA indicated that though there is large uncertainty present in some model parameters, the overall uncertainty in the calculated contaminant boundary during the 1,000-year regulatory timeframe is relatively small. As a result, limited uncertainty reduction can be expected from expensive characterization activities. With these results, DOE and NDEP have determined that the site model is suitable for moving forward in the corrective action process. Key to this acceptance is acknowledgment that the model requires independent validation data and the site requires long-term monitoring. Developing the validation and monitoring plans, and calculating contaminant boundaries are the tasks now being pursued for the site. The significant progress made for the site is due to the close cooperation and communication of the parties involved and an acceptance and understanding of the role of uncertainty
The role of general relativity in the uncertainty principle
International Nuclear Information System (INIS)
Padmanabhan, T.
1986-01-01
The role played by general relativity in quantum mechanics (especially as regards the uncertainty principle) is investigated. It is confirmed that the validity of time-energy uncertainty does depend on gravitational time dilation. It is also shown that there exists an intrinsic lower bound to the accuracy with which acceleration due to gravity can be measured. The motion of equivalence principle in quantum mechanics is clarified. (author)
Uncertainty information in climate data records from Earth observation
Merchant, C. J.
2017-12-01
How to derive and present uncertainty in climate data records (CDRs) has been debated within the European Space Agency Climate Change Initiative, in search of common principles applicable across a range of essential climate variables. Various points of consensus have been reached, including the importance of improving provision of uncertainty information and the benefit of adopting international norms of metrology for language around the distinct concepts of uncertainty and error. Providing an estimate of standard uncertainty per datum (or the means to readily calculate it) emerged as baseline good practice, and should be highly relevant to users of CDRs when the uncertainty in data is variable (the usual case). Given this baseline, the role of quality flags is clarified as being complementary to and not repetitive of uncertainty information. Data with high uncertainty are not poor quality if a valid estimate of the uncertainty is available. For CDRs and their applications, the error correlation properties across spatio-temporal scales present important challenges that are not fully solved. Error effects that are negligible in the uncertainty of a single pixel may dominate uncertainty in the large-scale and long-term. A further principle is that uncertainty estimates should themselves be validated. The concepts of estimating and propagating uncertainty are generally acknowledged in geophysical sciences, but less widely practised in Earth observation and development of CDRs. Uncertainty in a CDR depends in part (and usually significantly) on the error covariance of the radiances and auxiliary data used in the retrieval. Typically, error covariance information is not available in the fundamental CDR (FCDR) (i.e., with the level-1 radiances), since provision of adequate level-1 uncertainty information is not yet standard practice. Those deriving CDRs thus cannot propagate the radiance uncertainty to their geophysical products. The FIDUCEO project (www.fiduceo.eu) is
Some target assay uncertainties for passive neutron coincidence counting
International Nuclear Information System (INIS)
Ensslin, N.; Langner, D.G.; Menlove, H.O.; Miller, M.C.; Russo, P.A.
1990-01-01
This paper provides some target assay uncertainties for passive neutron coincidence counting of plutonium metal, oxide, mixed oxide, and scrap and waste. The target values are based in part on past user experience and in part on the estimated results from new coincidence counting techniques that are under development. The paper summarizes assay error sources and the new coincidence techniques, and recommends the technique that is likely to yield the lowest assay uncertainty for a given material type. These target assay uncertainties are intended to be useful for NDA instrument selection and assay variance propagation studies for both new and existing facilities. 14 refs., 3 tabs
Implicit knowledge of visual uncertainty guides decisions with asymmetric outcomes
DEFF Research Database (Denmark)
Whiteley, Louise Emma; Sahani, Maneesh
2008-01-01
under conditions of uncertainty. Here we show that human observers performing a simple visual choice task under an externally imposed loss function approach the optimal strategy, as defined by Bayesian probability and decision theory (Berger, 1985; Cox, 1961). In concert with earlier work, this suggests...... are pre-existing, widespread, and can be propagated to decision-making areas of the brain....... that observers possess a model of their internal uncertainty and can utilize this model in the neural computations that underlie their behavior (Knill & Pouget, 2004). In our experiment, optimal behavior requires that observers integrate the loss function with an estimate of their internal uncertainty rather...
CSAU (Code Scaling, Applicability and Uncertainty)
International Nuclear Information System (INIS)
Wilson, G.E.; Boyack, B.E.
1989-01-01
Best Estimate computer codes have been accepted by the U.S. Nuclear Regulatory Commission as an optional tool for performing safety analysis related to the licensing and regulation of current nuclear reactors producing commercial electrical power, providing their uncertainty is quantified. In support of this policy change, the NRC and its contractors and consultants have developed and demonstrated an uncertainty quantification methodology called CSAU. The primary use of the CSAU methodology is to quantify safety margins for existing designs; however, the methodology can also serve an equally important role in advanced reactor research for plants not yet built. This paper describes the CSAU methodology, at the generic process level, and provides the general principles whereby it may be applied to evaluations of advanced reactor designs
Investment choice under uncertainty: A review essay
Directory of Open Access Journals (Sweden)
Trifunović Dejan
2005-01-01
Full Text Available An investment opportunity whose return is perfectly predictable, hardly exists at all. Instead, investor makes his decisions under conditions of uncertainty. Theory of expected utility is the main analytical tool for description of choice under uncertainty. Critics of the theory contend that individuals have bounded rationality and that the theory of expected utility is not correct. When agents are faced with risky decisions they behave differently, conditional on their attitude towards risk. They can be risk loving, risk averse or risk neutral. In order to make an investment decision it is necessary to compare probability distribution functions of returns. Investment decision making is much simpler if one uses expected values and variances instead of probability distribution functions.
Uncertainties of Molecular Structural Parameters
International Nuclear Information System (INIS)
Császár, Attila G.
2014-01-01
performed. Simply, there are significant disagreements between the same bond lengths measured by different techniques. These disagreements are, however, systematic and can be computed via techniques of quantum chemistry which deal not only with the motions of the electrons (electronic structure theory) but also with the often large amplitude motions of the nuclei. As to the relevant quantum chemical computations, since about 1970 electronic structure theory has become able to make quantitative predictions and thus challenge (or even overrule) many experiments. Nevertheless, quantitative agreement of quantum chemical results with experiment can only be expected when the motions of the atoms are also considered. In the fourth age of quantum chemistry we are living in an era where one can bridge quantitatively the gap between ‘effective’, experimental and ‘equilibrium’, computed structures at even elevated temperatures of interest thus minimizing any real uncertainties of structural parameters. The connections mentioned are extremely important as they help to understand the true uncertainty of measured structural parameters. Traditionally it is microwave (MW) and millimeterwave (MMW) spectroscopy, as well as gas-phase electron diffraction (GED), which yielded the most accurate structural parameters of molecules. The accuracy of the MW and GED experiments approached about 0.001Å and 0.1º under ideal circumstances, worse, sometimes considerably worse, in less than ideal and much more often encountered situations. Quantum chemistry can define both highly accurate equilibrium (so-called Born-Oppenheimer, r_e"B"O, and semiexperimental, r_e"S"E) structures and, via detailed investigation of molecular motions, accurate temperature-dependent rovibrationally averaged structures. Determining structures is still a rich field for research, understanding the measured or computed uncertainties of structures and structural parameters is still a challenge but there are firm and well
Ontological Proofs of Existence and Non-Existence
Czech Academy of Sciences Publication Activity Database
Hájek, Petr
2008-01-01
Roč. 90, č. 2 (2008), s. 257-262 ISSN 0039-3215 R&D Projects: GA AV ČR IAA100300503 Institutional research plan: CEZ:AV0Z10300504 Keywords : ontological proofs * existence * non-existence * Gödel * Caramuel Subject RIV: BA - General Mathematics
Uncertainty of Doppler reactivity worth due to uncertainties of JENDL-3.2 resonance parameters
Energy Technology Data Exchange (ETDEWEB)
Zukeran, Atsushi [Hitachi Ltd., Hitachi, Ibaraki (Japan). Power and Industrial System R and D Div.; Hanaki, Hiroshi; Nakagawa, Tuneo; Shibata, Keiichi; Ishikawa, Makoto
1998-03-01
Analytical formula of Resonance Self-shielding Factor (f-factor) is derived from the resonance integral (J-function) based on NR approximation and the analytical expression for Doppler reactivity worth ({rho}) is also obtained by using the result. Uncertainties of the f-factor and Doppler reactivity worth are evaluated on the basis of sensitivity coefficients to the resonance parameters. The uncertainty of the Doppler reactivity worth at 487{sup 0}K is about 4 % for the PNC Large Fast Breeder Reactor. (author)
Probabilistic numerics and uncertainty in computations.
Hennig, Philipp; Osborne, Michael A; Girolami, Mark
2015-07-08
We deliver a call to arms for probabilistic numerical methods : algorithms for numerical tasks, including linear algebra, integration, optimization and solving differential equations, that return uncertainties in their calculations. Such uncertainties, arising from the loss of precision induced by numerical calculation with limited time or hardware, are important for much contemporary science and industry. Within applications such as climate science and astrophysics, the need to make decisions on the basis of computations with large and complex data have led to a renewed focus on the management of numerical uncertainty. We describe how several seminal classic numerical methods can be interpreted naturally as probabilistic inference. We then show that the probabilistic view suggests new algorithms that can flexibly be adapted to suit application specifics, while delivering improved empirical performance. We provide concrete illustrations of the benefits of probabilistic numeric algorithms on real scientific problems from astrometry and astronomical imaging, while highlighting open problems with these new algorithms. Finally, we describe how probabilistic numerical methods provide a coherent framework for identifying the uncertainty in calculations performed with a combination of numerical algorithms (e.g. both numerical optimizers and differential equation solvers), potentially allowing the diagnosis (and control) of error sources in computations.
Despax, Aurélien; Perret, Christian; Garçon, Rémy; Hauet, Alexandre; Belleville, Arnaud; Le Coz, Jérôme; Favre, Anne-Catherine
2016-02-01
Streamflow time series provide baseline data for many hydrological investigations. Errors in the data mainly occur through uncertainty in gauging (measurement uncertainty) and uncertainty in the determination of the stage-discharge relationship based on gaugings (rating curve uncertainty). As the velocity-area method is the measurement technique typically used for gaugings, it is fundamental to estimate its level of uncertainty. Different methods are available in the literature (ISO 748, Q + , IVE), all with their own limitations and drawbacks. Among the terms forming the combined relative uncertainty in measured discharge, the uncertainty component relating to the limited number of verticals often includes a large part of the relative uncertainty. It should therefore be estimated carefully. In ISO 748 standard, proposed values of this uncertainty component only depend on the number of verticals without considering their distribution with respect to the depth and velocity cross-sectional profiles. The Q + method is sensitive to a user-defined parameter while it is questionable whether the IVE method is applicable to stream-gaugings performed with a limited number of verticals. To address the limitations of existing methods, this paper presents a new methodology, called FLow Analog UnceRtainty Estimation (FLAURE), to estimate the uncertainty component relating to the limited number of verticals. High-resolution reference gaugings (with 31 and more verticals) are used to assess the uncertainty component through a statistical analysis. Instead of subsampling purely randomly the verticals of these reference stream-gaugings, a subsampling method is developed in a way that mimicks the behavior of a hydrometric technician. A sampling quality index (SQI) is suggested and appears to be a more explanatory variable than the number of verticals. This index takes into account the spacing between verticals and the variation of unit flow between two verticals. To compute the
Sketching Uncertainty into Simulations.
Ribicic, H; Waser, J; Gurbat, R; Sadransky, B; Groller, M E
2012-12-01
In a variety of application areas, the use of simulation steering in decision making is limited at best. Research focusing on this problem suggests that most user interfaces are too complex for the end user. Our goal is to let users create and investigate multiple, alternative scenarios without the need for special simulation expertise. To simplify the specification of parameters, we move from a traditional manipulation of numbers to a sketch-based input approach. Users steer both numeric parameters and parameters with a spatial correspondence by sketching a change onto the rendering. Special visualizations provide immediate visual feedback on how the sketches are transformed into boundary conditions of the simulation models. Since uncertainty with respect to many intertwined parameters plays an important role in planning, we also allow the user to intuitively setup complete value ranges, which are then automatically transformed into ensemble simulations. The interface and the underlying system were developed in collaboration with experts in the field of flood management. The real-world data they have provided has allowed us to construct scenarios used to evaluate the system. These were presented to a variety of flood response personnel, and their feedback is discussed in detail in the paper. The interface was found to be intuitive and relevant, although a certain amount of training might be necessary.
Uncertainty vs. Information (Invited)
Nearing, Grey
2017-04-01
Information theory is the branch of logic that describes how rational epistemic states evolve in the presence of empirical data (Knuth, 2005), and any logic of science is incomplete without such a theory. Developing a formal philosophy of science that recognizes this fact results in essentially trivial solutions to several longstanding problems are generally considered intractable, including: • Alleviating the need for any likelihood function or error model. • Derivation of purely logical falsification criteria for hypothesis testing. • Specification of a general quantitative method for process-level model diagnostics. More generally, I make the following arguments: 1. Model evaluation should not proceed by quantifying and/or reducing error or uncertainty, and instead should be approached as a problem of ensuring that our models contain as much information as our experimental data. I propose that the latter is the only question a scientist actually has the ability to ask. 2. Instead of building geophysical models as solutions to differential equations that represent conservation laws, we should build models as maximum entropy distributions constrained by conservation symmetries. This will allow us to derive predictive probabilities directly from first principles. Knuth, K. H. (2005) 'Lattice duality: The origin of probability and entropy', Neurocomputing, 67, pp. 245-274.
Pandemic influenza: certain uncertainties
Morens, David M.; Taubenberger, Jeffery K.
2011-01-01
SUMMARY For at least five centuries, major epidemics and pandemics of influenza have occurred unexpectedly and at irregular intervals. Despite the modern notion that pandemic influenza is a distinct phenomenon obeying such constant (if incompletely understood) rules such as dramatic genetic change, cyclicity, “wave” patterning, virus replacement, and predictable epidemic behavior, much evidence suggests the opposite. Although there is much that we know about pandemic influenza, there appears to be much more that we do not know. Pandemics arise as a result of various genetic mechanisms, have no predictable patterns of mortality among different age groups, and vary greatly in how and when they arise and recur. Some are followed by new pandemics, whereas others fade gradually or abruptly into long-term endemicity. Human influenza pandemics have been caused by viruses that evolved singly or in co-circulation with other pandemic virus descendants and often have involved significant transmission between, or establishment of, viral reservoirs within other animal hosts. In recent decades, pandemic influenza has continued to produce numerous unanticipated events that expose fundamental gaps in scientific knowledge. Influenza pandemics appear to be not a single phenomenon but a heterogeneous collection of viral evolutionary events whose similarities are overshadowed by important differences, the determinants of which remain poorly understood. These uncertainties make it difficult to predict influenza pandemics and, therefore, to adequately plan to prevent them. PMID:21706672
Maugis, Pierre-André G
2018-07-01
Big data-the idea that an always-larger volume of information is being constantly recorded-suggests that new problems can now be subjected to scientific scrutiny. However, can classical statistical methods be used directly on big data? We analyze the problem by looking at two known pitfalls of big datasets. First, that they are biased, in the sense that they do not offer a complete view of the populations under consideration. Second, that they present a weak but pervasive level of dependence between all their components. In both cases we observe that the uncertainty of the conclusion obtained by statistical methods is increased when used on big data, either because of a systematic error (bias), or because of a larger degree of randomness (increased variance). We argue that the key challenge raised by big data is not only how to use big data to tackle new problems, but to develop tools and methods able to rigorously articulate the new risks therein. Copyright © 2016. Published by Elsevier Ltd.
Uncertainty during breast diagnostic evaluation: state of the science.
Montgomery, Mariann
2010-01-01
To present the state of the science on uncertainty in relationship to the experiences of women undergoing diagnostic evaluation for suspected breast cancer. Published articles from Medline, CINAHL, PubMED, and PsycINFO from 1983-2008 using the following key words: breast biopsy, mammography, uncertainty, reframing, inner strength, and disruption. Fifty research studies were examined with all reporting the presence of anxiety persisting throughout the diagnostic evaluation until certitude is achieved through the establishment of a definitive diagnosis. Indirect determinants of uncertainty for women undergoing breast diagnostic evaluation include measures of anxiety, depression, social support, emotional responses, defense mechanisms, and the psychological impact of events. Understanding and influencing the uncertainty experience have been suggested to be key in relieving psychosocial distress and positively influencing future screening behaviors. Several studies examine correlational relationships among anxiety, selection of coping methods, and demographic factors that influence uncertainty. A gap exists in the literature with regard to the relationship of inner strength and uncertainty. Nurses can be invaluable in assisting women in coping with the uncertainty experience by providing positive communication and support. Nursing interventions should be designed and tested for their effects on uncertainty experienced by women undergoing a breast diagnostic evaluation.
Calculation of uncertainties; Calculo de incertidumbres
Energy Technology Data Exchange (ETDEWEB)
Diaz-Asencio, Misael [Centro de Estudios Ambientales de Cienfuegos (Cuba)
2012-07-01
One of the most important aspects in relation to the quality assurance in any analytical activity is the estimation of measurement uncertainty. There is general agreement that 'the expression of the result of a measurement is not complete without specifying its associated uncertainty'. An analytical process is the mechanism for obtaining methodological information (measurand) of a material system (population). This implies the need for the definition of the problem, the choice of methods for sampling and measurement and proper execution of these activities for obtaining information. The result of a measurement is only an approximation or estimate of the value of the measurand, which is complete only when accompanied by an estimate of the uncertainty of the analytical process. According to the 'Vocabulary of Basic and General Terms in Metrology' measurement uncertainty' is the parameter associated with the result of a measurement that characterizes the dispersion of the values that could reasonably be attributed to the measurand (or magnitude). This parameter could be a standard deviation or a confidence interval. The uncertainty evaluation requires detailed look at all possible sources, but not disproportionately. We can make a good estimate of the uncertainty concentrating efforts on the largest contributions. The key steps of the process of determining the uncertainty in the measurements are: - the specification of the measurand; - identification of the sources of uncertainty - the quantification of individual components of uncertainty, - calculate the combined standard uncertainty; - report of uncertainty. [Spanish] Uno de los aspectos mas importantes en relacion con el aseguramiento de la calidad en cualquier actividad analitica es la estimacion de la incertidumbre de la medicion. Existe el acuerdo general que 'la expresion del resultado de una medicion no esta completa sin especificar su incertidumbre asociada'. Un proceso analitico es el mecanismo
Existence theory in optimal control
International Nuclear Information System (INIS)
Olech, C.
1976-01-01
This paper treats the existence problem in two main cases. One case is that of linear systems when existence is based on closedness or compactness of the reachable set and the other, non-linear case refers to a situation where for the existence of optimal solutions closedness of the set of admissible solutions is needed. Some results from convex analysis are included in the paper. (author)
International Nuclear Information System (INIS)
Brown, J.; Jones, J.A.
2000-01-01
This paper describes the uncertainty analysis of the food chain module of COSYMA and the uncertainty distributions on the input parameter values for the food chain model provided by the expert panels that were used for the analysis. Two expert panels were convened, covering the areas of soil and plant transfer processes and transfer to and through animals. The aggregated uncertainty distributions from the experts for the elicited variables were used in an uncertainty analysis of the food chain module of COSYMA. The main aim of the module analysis was to identify those parameters whose uncertainty makes large contributions to the overall uncertainty and so should be included in the overall analysis. (author)
ESFR core optimization and uncertainty studies
International Nuclear Information System (INIS)
Rineiski, A.; Vezzoni, B.; Zhang, D.; Marchetti, M.; Gabrielli, F.; Maschek, W.; Chen, X.-N.; Buiron, L.; Krepel, J.; Sun, K.; Mikityuk, K.; Polidoro, F.; Rochman, D.; Koning, A.J.; DaCruz, D.F.; Tsige-Tamirat, H.; Sunderland, R.
2015-01-01
In the European Sodium Fast Reactor (ESFR) project supported by EURATOM in 2008-2012, a concept for a large 3600 MWth sodium-cooled fast reactor design was investigated. In particular, reference core designs with oxide and carbide fuel were optimized to improve their safety parameters. Uncertainties in these parameters were evaluated for the oxide option. Core modifications were performed first to reduce the sodium void reactivity effect. Introduction of a large sodium plenum with an absorber layer above the core and a lower axial fertile blanket improve the total sodium void effect appreciably, bringing it close to zero for a core with fresh fuel, in line with results obtained worldwide, while not influencing substantially other core physics parameters. Therefore an optimized configuration, CONF2, with a sodium plenum and a lower blanket was established first and used as a basis for further studies in view of deterioration of safety parameters during reactor operation. Further options to study were an inner fertile blanket, introduction of moderator pins, a smaller core height, special designs for pins, such as 'empty' pins, and subassemblies. These special designs were proposed to facilitate melted fuel relocation in order to avoid core re-criticality under severe accident conditions. In the paper further CONF2 modifications are compared in terms of safety and fuel balance. They may bring further improvements in safety, but their accurate assessment requires additional studies, including transient analyses. Uncertainty studies were performed by employing a so-called Total Monte-Carlo method, for which a large number of nuclear data files is produced for single isotopes and then used in Monte-Carlo calculations. The uncertainties for the criticality, sodium void and Doppler effects, effective delayed neutron fraction due to uncertainties in basic nuclear data were assessed for an ESFR core. They prove applicability of the available nuclear data for ESFR
A commentary on model uncertainty
International Nuclear Information System (INIS)
Apostolakis, G.
1994-01-01
A framework is proposed for the identification of model and parameter uncertainties in risk assessment models. Two cases are distinguished; in the first case, a set of mutually exclusive and exhaustive hypotheses (models) can be formulated, while, in the second, only one reference model is available. The relevance of this formulation to decision making and the communication of uncertainties is discussed
Mama Software Features: Uncertainty Testing
Energy Technology Data Exchange (ETDEWEB)
Ruggiero, Christy E. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Porter, Reid B. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2014-05-30
This document reviews how the uncertainty in the calculations is being determined with test image data. The results of this testing give an ‘initial uncertainty’ number than can be used to estimate the ‘back end’ uncertainty in digital image quantification in images. Statisticians are refining these numbers as part of a UQ effort.
Designing for Uncertainty: Three Approaches
Bennett, Scott
2007-01-01
Higher education wishes to get long life and good returns on its investment in learning spaces. Doing this has become difficult because rapid changes in information technology have created fundamental uncertainties about the future in which capital investments must deliver value. Three approaches to designing for this uncertainty are described…
International Nuclear Information System (INIS)
Zhang, W.; Zaehringer, M.; Ungar, K.; Hoffman, I.
2008-01-01
In this paper, the uncertainties of gamma-ray small peak analysis have been examined. As the intensity of a gamma-ray peak approaches its detection decision limit, derived parameters such as centroid channel energy, peak area, peak area uncertainty, baseline determination, and peak significance are statistically sensitive. The intercomparison exercise organized by the CTBTO provided an excellent opportunity for this to be studied. Near background levels, the false-positive and false-negative peak identification frequencies in artificial test spectra have been compared to statistically predictable limiting values. In addition, naturally occurring radon progeny were used to compare observed variance against nominal uncertainties. The results infer that the applied fit algorithms do not always represent the best estimator. Understanding the statistically predicted peak-finding limit is important for data evaluation and analysis assessment. Furthermore, these results are useful to optimize analytical procedures to achieve the best results
Structural interpretation of seismic data and inherent uncertainties
Bond, Clare
2013-04-01
Geoscience is perhaps unique in its reliance on incomplete datasets and building knowledge from their interpretation. This interpretation basis for the science is fundamental at all levels; from creation of a geological map to interpretation of remotely sensed data. To teach and understand better the uncertainties in dealing with incomplete data we need to understand the strategies individual practitioners deploy that make them effective interpreters. The nature of interpretation is such that the interpreter needs to use their cognitive ability in the analysis of the data to propose a sensible solution in their final output that is both consistent not only with the original data but also with other knowledge and understanding. In a series of experiments Bond et al. (2007, 2008, 2011, 2012) investigated the strategies and pitfalls of expert and non-expert interpretation of seismic images. These studies focused on large numbers of participants to provide a statistically sound basis for analysis of the results. The outcome of these experiments showed that a wide variety of conceptual models were applied to single seismic datasets. Highlighting not only spatial variations in fault placements, but whether interpreters thought they existed at all, or had the same sense of movement. Further, statistical analysis suggests that the strategies an interpreter employs are more important than expert knowledge per se in developing successful interpretations. Experts are successful because of their application of these techniques. In a new set of experiments a small number of experts are focused on to determine how they use their cognitive and reasoning skills, in the interpretation of 2D seismic profiles. Live video and practitioner commentary were used to track the evolving interpretation and to gain insight on their decision processes. The outputs of the study allow us to create an educational resource of expert interpretation through online video footage and commentary with
Troldborg, M.; Nowak, W.; Binning, P. J.; Bjerg, P. L.
2012-12-01
Estimates of mass discharge (mass/time) are increasingly being used when assessing risks of groundwater contamination and designing remedial systems at contaminated sites. Mass discharge estimates are, however, prone to rather large uncertainties as they integrate uncertain spatial distributions of both concentration and groundwater flow velocities. For risk assessments or any other decisions that are being based on mass discharge estimates, it is essential to address these uncertainties. We present a novel Bayesian geostatistical approach for quantifying the uncertainty of the mass discharge across a multilevel control plane. The method decouples the flow and transport simulation and has the advantage of avoiding the heavy computational burden of three-dimensional numerical flow and transport simulation coupled with geostatistical inversion. It may therefore be of practical relevance to practitioners compared to existing methods that are either too simple or computationally demanding. The method is based on conditional geostatistical simulation and accounts for i) heterogeneity of both the flow field and the concentration distribution through Bayesian geostatistics (including the uncertainty in covariance functions), ii) measurement uncertainty, and iii) uncertain source zone geometry and transport parameters. The method generates multiple equally likely realizations of the spatial flow and concentration distribution, which all honour the measured data at the control plane. The flow realizations are generated by analytical co-simulation of the hydraulic conductivity and the hydraulic gradient across the control plane. These realizations are made consistent with measurements of both hydraulic conductivity and head at the site. An analytical macro-dispersive transport solution is employed to simulate the mean concentration distribution across the control plane, and a geostatistical model of the Box-Cox transformed concentration data is used to simulate observed
Energy Technology Data Exchange (ETDEWEB)
Gubik, A. [RAG-AG Wien (Austria); Baffoe, J.; Schulze-Riegert, R. [SPT Group GmbH, Hamburg (Germany)
2013-08-01
Gas storages define a key contribution for building a reliable gas supply chain from production to consumers. In a competitive gas market with short reaction times to seasonal and other gas injection and extraction requirements, gas storages also receive a strong focus on availability and precise prediction estimates for future operation scenarios. Reservoir management workflows are increasingly built on reservoir simulation support for optimizing production schemes and estimating the impact of subsurface uncertainties on field development scenarios. Simulation models for gas storages are calibrated to geological data and accurate reproduction of historical production data are defined as a prerequisite for reliable production and performance forecasts. The underlying model validation process is called history matching, which potentially generates alternative simulation models due to prevailing geological uncertainties. In the past, a single basecase reference model was used to predict production capacities of a gas storage. The working gas volume was precisely defined over a contracted plateau delivery and the required cushion gas volume maintains the reservoir pressure during the operation. Cushion and working gas Volume are strongly dependent on reservoir parameters. In this work an existing depleted gas reservoir and the operation target as a gas storage is described. Key input data to the reservoir model description and simulation is reviewed including production history and geological uncertainties based on large well spacing, limited core and well data and a limited seismic resolution. Target delivery scenarios of the prospected gas storage are evaluated under uncertainty. As one key objective, optimal working gas and cushion gas volumes are described in a probabilistic context reflecting geological uncertainties. Several work steps are defined and included in an integrated workflow design. Equiprobable geological models are generated and evaluated based on
Efficient Quantification of Uncertainties in Complex Computer Code Results, Phase I
National Aeronautics and Space Administration — This proposal addresses methods for efficient quantification of margins and uncertainties (QMU) for models that couple multiple, large-scale commercial or...
Xu, Zhuocan; Mace, Jay; Avalone, Linnea; Wang, Zhien
2015-04-01
The extreme variability of ice particle habits in precipitating clouds affects our understanding of these cloud systems in every aspect (i.e. radiation transfer, dynamics, precipitation rate, etc) and largely contributes to the uncertainties in the model representation of related processes. Ice particle mass-dimensional power law relationships, M=a*(D ^ b), are commonly assumed in models and retrieval algorithms, while very little knowledge exists regarding the uncertainties of these M-D parameters in real-world situations. In this study, we apply Optimal Estimation (OE) methodology to infer ice particle mass-dimensional relationship from ice particle size distributions and bulk water contents independently measured on board the University of Wyoming King Air during the Colorado Airborne Multi-Phase Cloud Study (CAMPS). We also utilize W-band radar reflectivity obtained on the same platform (King Air) offering a further constraint to this ill-posed problem (Heymsfield et al. 2010). In addition to the values of retrieved M-D parameters, the associated uncertainties are conveniently acquired in the OE framework, within the limitations of assumed Gaussian statistics. We find, given the constraints provided by the bulk water measurement and in situ radar reflectivity, that the relative uncertainty of mass-dimensional power law prefactor (a) is approximately 80% and the relative uncertainty of exponent (b) is 10-15%. With this level of uncertainty, the forward model uncertainty in radar reflectivity would be on the order of 4 dB or a factor of approximately 2.5 in ice water content. The implications of this finding are that inferences of bulk water from either remote or in situ measurements of particle spectra cannot be more certain than this when the mass-dimensional relationships are not known a priori which is almost never the case.
Extensive neutronic sensitivity-uncertainty analysis of a fusion reactor shielding blanket
International Nuclear Information System (INIS)
Hogenbirk, A.
1994-01-01
In this paper the results are presented of an extensive neutronic sensitivity-uncertainty study performed for the design of a shielding blanket for a next-step fusion reactor, such as ITER. A code system was used, which was developed at ECN Petten. The uncertainty in an important response parameter, the neutron heating in the inboard superconducting coils, was evaluated. Neutron transport calculations in the 100 neutron group GAM-II structure were performed using the code ANISN. For the sensitivity and uncertainty calculations the code SUSD was used. Uncertainties due to cross-section uncertainties were taken into account as well as uncertainties due to uncertainties in energy and angular distributions of scattered neutrons (SED and SAD uncertainties, respectively). The subject of direct-term uncertainties (i.e. uncertainties due to uncertainties in the kerma factors of the superconducting coils) is briefly touched upon. It is shown that SAD uncertainties, which have been largely neglected until now, contribute significantly to the total uncertainty. Moreover, the contribution of direct-term uncertainties may be large. The total uncertainty in the neutron heating, only due to Fe cross-sections, amounts to approximately 25%, which is rather large. However, uncertainty data are scarce and the data may very well be conservative. It is shown in this paper that with the code system used, sensitivity and uncertainty calculations can be performed in a straightforward way. Therefore, it is suggested that emphasis is now put on the generation of realistic, reliable covariance data for cross-sections as well as for angular and energy distributions. ((orig.))
Surrogate-based optimization of hydraulic fracturing in pre-existing fracture networks
Chen, Mingjie; Sun, Yunwei; Fu, Pengcheng; Carrigan, Charles R.; Lu, Zhiming; Tong, Charles H.; Buscheck, Thomas A.
2013-08-01
Hydraulic fracturing has been used widely to stimulate production of oil, natural gas, and geothermal energy in formations with low natural permeability. Numerical optimization of fracture stimulation often requires a large number of evaluations of objective functions and constraints from forward hydraulic fracturing models, which are computationally expensive and even prohibitive in some situations. Moreover, there are a variety of uncertainties associated with the pre-existing fracture distributions and rock mechanical properties, which affect the optimized decisions for hydraulic fracturing. In this study, a surrogate-based approach is developed for efficient optimization of hydraulic fracturing well design in the presence of natural-system uncertainties. The fractal dimension is derived from the simulated fracturing network as the objective for maximizing energy recovery sweep efficiency. The surrogate model, which is constructed using training data from high-fidelity fracturing models for mapping the relationship between uncertain input parameters and the fractal dimension, provides fast approximation of the objective functions and constraints. A suite of surrogate models constructed using different fitting methods is evaluated and validated for fast predictions. Global sensitivity analysis is conducted to gain insights into the impact of the input variables on the output of interest, and further used for parameter screening. The high efficiency of the surrogate-based approach is demonstrated for three optimization scenarios with different and uncertain ambient conditions. Our results suggest the critical importance of considering uncertain pre-existing fracture networks in optimization studies of hydraulic fracturing.
Uncertainty Evaluation of Best Estimate Calculation Results
International Nuclear Information System (INIS)
Glaeser, H.
2006-01-01
Efforts are underway in Germany to perform analysis using best estimate computer codes and to include uncertainty evaluation in licensing. The German Reactor Safety Commission (RSK) issued a recommendation to perform uncertainty analysis in loss of coolant accident safety analyses (LOCA), recently. A more general requirement is included in a draft revision of the German Nuclear Regulation which is an activity of the German Ministry of Environment and Reactor Safety (BMU). According to the recommendation of the German RSK to perform safety analyses for LOCA in licensing the following deterministic requirements have still to be applied: Most unfavourable single failure, Unavailability due to preventive maintenance, Break location, Break size and break type, Double ended break, 100 percent through 200 percent, Large, medium and small break, Loss of off-site power, Core power (at accident initiation the most unfavourable conditions and values have to be assumed which may occur under normal operation taking into account the set-points of integral power and power density control. Measurement and calibration errors can be considered statistically), Time of fuel cycle. Analysis using best estimate codes with evaluation of uncertainties is the only way to quantify conservatisms with regard to code models and uncertainties of plant, fuel parameters and decay heat. This is especially the case for approaching licensing limits, e.g. due to power up-rates, higher burn-up and higher enrichment. Broader use of best estimate analysis is therefore envisaged in the future. Since some deterministic unfavourable assumptions regarding availability of NPP systems are still used, some conservatism in best-estimate analyses remains. Methods of uncertainty analyses have been developed and applied by the vendor Framatome ANP as well as by GRS in Germany. The GRS development was sponsored by the German Ministry of Economy and Labour (BMWA). (author)
Managing uncertainty in flood protection planning with climate projections
Dittes, Beatrice; Špačková, Olga; Schoppa, Lukas; Straub, Daniel
2018-04-01
Technical flood protection is a necessary part of integrated strategies to protect riverine settlements from extreme floods. Many technical flood protection measures, such as dikes and protection walls, are costly to adapt after their initial construction. This poses a challenge to decision makers as there is large uncertainty in how the required protection level will change during the measure lifetime, which is typically many decades long. Flood protection requirements should account for multiple future uncertain factors: socioeconomic, e.g., whether the population and with it the damage potential grows or falls; technological, e.g., possible advancements in flood protection; and climatic, e.g., whether extreme discharge will become more frequent or not. This paper focuses on climatic uncertainty. Specifically, we devise methodology to account for uncertainty associated with the use of discharge projections, ultimately leading to planning implications. For planning purposes, we categorize uncertainties as either visible, if they can be quantified from available catchment data, or hidden, if they cannot be quantified from catchment data and must be estimated, e.g., from the literature. It is vital to consider the hidden uncertainty, since in practical applications only a limited amount of information (e.g., a finite projection ensemble) is available. We use a Bayesian approach to quantify the visible uncertainties and combine them with an estimate of the hidden uncertainties to learn a joint probability distribution of the parameters of extreme discharge. The methodology is integrated into an optimization framework and applied to a pre-alpine case study to give a quantitative, cost-optimal recommendation on the required amount of flood protection. The results show that hidden uncertainty ought to be considered in planning, but the larger the uncertainty already present, the smaller the impact of adding more. The recommended planning is robust to moderate changes in
Dittes, Beatrice; Kaiser, Maria; Špačková, Olga; Rieger, Wolfgang; Disse, Markus; Straub, Daniel
2018-05-01
Planning authorities are faced with a range of questions when planning flood protection measures: is the existing protection adequate for current and future demands or should it be extended? How will flood patterns change in the future? How should the uncertainty pertaining to this influence the planning decision, e.g., for delaying planning or including a safety margin? Is it sufficient to follow a protection criterion (e.g., to protect from the 100-year flood) or should the planning be conducted in a risk-based way? How important is it for flood protection planning to accurately estimate flood frequency (changes), costs and damage? These are questions that we address for a medium-sized pre-alpine catchment in southern Germany, using a sequential Bayesian decision making framework that quantitatively addresses the full spectrum of uncertainty. We evaluate different flood protection systems considered by local agencies in a test study catchment. Despite large uncertainties in damage, cost and climate, the recommendation is robust for the most conservative approach. This demonstrates the feasibility of making robust decisions under large uncertainty. Furthermore, by comparison to a previous study, it highlights the benefits of risk-based planning over the planning of flood protection to a prescribed return period.
Directory of Open Access Journals (Sweden)
B. Dittes
2018-05-01
Full Text Available Planning authorities are faced with a range of questions when planning flood protection measures: is the existing protection adequate for current and future demands or should it be extended? How will flood patterns change in the future? How should the uncertainty pertaining to this influence the planning decision, e.g., for delaying planning or including a safety margin? Is it sufficient to follow a protection criterion (e.g., to protect from the 100-year flood or should the planning be conducted in a risk-based way? How important is it for flood protection planning to accurately estimate flood frequency (changes, costs and damage? These are questions that we address for a medium-sized pre-alpine catchment in southern Germany, using a sequential Bayesian decision making framework that quantitatively addresses the full spectrum of uncertainty. We evaluate different flood protection systems considered by local agencies in a test study catchment. Despite large uncertainties in damage, cost and climate, the recommendation is robust for the most conservative approach. This demonstrates the feasibility of making robust decisions under large uncertainty. Furthermore, by comparison to a previous study, it highlights the benefits of risk-based planning over the planning of flood protection to a prescribed return period.
The neurobiology of uncertainty: implications for statistical learning.
Hasson, Uri
2017-01-05
The capacity for assessing the degree of uncertainty in the environment relies on estimating statistics of temporally unfolding inputs. This, in turn, allows calibration of predictive and bottom-up processing, and signalling changes in temporally unfolding environmental features. In the last decade, several studies have examined how the brain codes for and responds to input uncertainty. Initial neurobiological experiments implicated frontoparietal and hippocampal systems, based largely on paradigms that manipulated distributional features of visual stimuli. However, later work in the auditory domain pointed to different systems, whose activation profiles have interesting implications for computational and neurobiological models of statistical learning (SL). This review begins by briefly recapping the historical development of ideas pertaining to the sensitivity to uncertainty in temporally unfolding inputs. It then discusses several issues at the interface of studies of uncertainty and SL. Following, it presents several current treatments of the neurobiology of uncertainty and reviews recent findings that point to principles that serve as important constraints on future neurobiological theories of uncertainty, and relatedly, SL. This review suggests it may be useful to establish closer links between neurobiological research on uncertainty and SL, considering particularly mechanisms sensitive to local and global structure in inputs, the degree of input uncertainty, the complexity of the system generating the input, learning mechanisms that operate on different temporal scales and the use of learnt information for online prediction.This article is part of the themed issue 'New frontiers for statistical learning in the cognitive sciences'. © 2016 The Author(s).
Uncertainty quantification using evidence theory in multidisciplinary design optimization
International Nuclear Information System (INIS)
Agarwal, Harish; Renaud, John E.; Preston, Evan L.; Padmanabhan, Dhanesh
2004-01-01
Advances in computational performance have led to the development of large-scale simulation tools for design. Systems generated using such simulation tools can fail in service if the uncertainty of the simulation tool's performance predictions is not accounted for. In this research an investigation of how uncertainty can be quantified in multidisciplinary systems analysis subject to epistemic uncertainty associated with the disciplinary design tools and input parameters is undertaken. Evidence theory is used to quantify uncertainty in terms of the uncertain measures of belief and plausibility. To illustrate the methodology, multidisciplinary analysis problems are introduced as an extension to the epistemic uncertainty challenge problems identified by Sandia National Laboratories. After uncertainty has been characterized mathematically the designer seeks the optimum design under uncertainty. The measures of uncertainty provided by evidence theory are discontinuous functions. Such non-smooth functions cannot be used in traditional gradient-based optimizers because the sensitivities of the uncertain measures are not properly defined. In this research surrogate models are used to represent the uncertain measures as continuous functions. A sequential approximate optimization approach is used to drive the optimization process. The methodology is illustrated in application to multidisciplinary example problems
Discussion of OECD LWR Uncertainty Analysis in Modelling Benchmark
International Nuclear Information System (INIS)
Ivanov, K.; Avramova, M.; Royer, E.; Gillford, J.
2013-01-01
The demand for best estimate calculations in nuclear reactor design and safety evaluations has increased in recent years. Uncertainty quantification has been highlighted as part of the best estimate calculations. The modelling aspects of uncertainty and sensitivity analysis are to be further developed and validated on scientific grounds in support of their performance and application to multi-physics reactor simulations. The Organization for Economic Co-operation and Development (OECD) / Nuclear Energy Agency (NEA) Nuclear Science Committee (NSC) has endorsed the creation of an Expert Group on Uncertainty Analysis in Modelling (EGUAM). Within the framework of activities of EGUAM/NSC the OECD/NEA initiated the Benchmark for Uncertainty Analysis in Modelling for Design, Operation, and Safety Analysis of Light Water Reactor (OECD LWR UAM benchmark). The general objective of the benchmark is to propagate the predictive uncertainties of code results through complex coupled multi-physics and multi-scale simulations. The benchmark is divided into three phases with Phase I highlighting the uncertainty propagation in stand-alone neutronics calculations, while Phase II and III are focused on uncertainty analysis of reactor core and system respectively. This paper discusses the progress made in Phase I calculations, the Specifications for Phase II and the incoming challenges in defining Phase 3 exercises. The challenges of applying uncertainty quantification to complex code systems, in particular the time-dependent coupled physics models are the large computational burden and the utilization of non-linear models (expected due to the physics coupling). (authors)
Confronting the Uncertainty in Aerosol Forcing Using Comprehensive Observational Data
Johnson, J. S.; Regayre, L. A.; Yoshioka, M.; Pringle, K.; Sexton, D.; Lee, L.; Carslaw, K. S.
2017-12-01
The effect of aerosols on cloud droplet concentrations and radiative properties is the largest uncertainty in the overall radiative forcing of climate over the industrial period. In this study, we take advantage of a large perturbed parameter ensemble of simulations from the UK Met Office HadGEM-UKCA model (the aerosol component of the UK Earth System Model) to comprehensively sample uncertainty in aerosol forcing. Uncertain aerosol and atmospheric parameters cause substantial aerosol forcing uncertainty in climatically important regions. As the aerosol radiative forcing itself is unobservable, we investigate the potential for observations of aerosol and radiative properties to act as constraints on the large forcing uncertainty. We test how eight different theoretically perfect aerosol and radiation observations can constrain the forcing uncertainty over Europe. We find that the achievable constraint is weak unless many diverse observations are used simultaneously. This is due to the complex relationships between model output responses and the multiple interacting parameter uncertainties: compensating model errors mean there are many ways to produce the same model output (known as model equifinality) which impacts on the achievable constraint. However, using all eight observable quantities together we show that the aerosol forcing uncertainty can potentially be reduced by around 50%. This reduction occurs as we reduce a large sample of model variants (over 1 million) that cover the full parametric uncertainty to around 1% that are observationally plausible.Constraining the forcing uncertainty using real observations is a more complex undertaking, in which we must account for multiple further uncertainties including measurement uncertainties, structural model uncertainties and the model discrepancy from reality. Here, we make a first attempt to determine the true potential constraint on the forcing uncertainty from our model that is achievable using a comprehensive
Energy Technology Data Exchange (ETDEWEB)
Van Dril, A.W.N. [ECN Beleidsstudies, Petten (Netherlands); Verdonk, M. [Planbureau voor de Leefomgeving PBL, Bilthoven (Netherlands)
2008-09-15
In view of recent social and political discussions on nuclear energy, ECN and PBL have gathered and updated information on the cost of options for reducing CO2 emissions in large scale electricity generation. This memo compares the cost of nuclear energy with other large scale options for electricity generation. Special attention is paid to the uncertainties of the cost of nuclear energy. In addition, some external costs and benefits are examined. This memo does not provide a complete framework for comparing the options for generation of electricity, though. Aspects such as public support, various aspects of sustainability and risks are not addressed in this memo. [mk]. [Dutch] Naar aanleiding van de actuele maatschappelijke en politieke discussie over kernenergie hebben ECN en PBL kosteninformatie over opties om CO2-emissies te beperken bij grootschalige opwekking van elektriciteit verzameld en geactualiseerd. In deze notitie worden de kosten van kernenergie vergeleken met andere grootschalige opties van elektriciteitsopwekking. Daarbij wordt speciale aandacht besteed aan de onzekerheden over de kosten van kernenergie. Aanvullend zijn enkele externe kosten en baten beschouwd. Deze notitie geeft echter geen volledig kader om de opties voor de opwekking van elektriciteit met elkaar te vergelijken. Aspecten als draagvlak, diverse duurzaamheidaspecten en risico's zijn in deze notitie namelijk buiten beschouwing gelaten.
Uncertainty Quantification in Alchemical Free Energy Methods.
Bhati, Agastya P; Wan, Shunzhou; Hu, Yuan; Sherborne, Brad; Coveney, Peter V
2018-05-02
Alchemical free energy methods have gained much importance recently from several reports of improved ligand-protein binding affinity predictions based on their implementation using molecular dynamics simulations. A large number of variants of such methods implementing different accelerated sampling techniques and free energy estimators are available, each claimed to be better than the others in its own way. However, the key features of reproducibility and quantification of associated uncertainties in such methods have barely been discussed. Here, we apply a systematic protocol for uncertainty quantification to a number of popular alchemical free energy methods, covering both absolute and relative free energy predictions. We show that a reliable measure of error estimation is provided by ensemble simulation-an ensemble of independent MD simulations-which applies irrespective of the free energy method. The need to use ensemble methods is fundamental and holds regardless of the duration of time of the molecular dynamics simulations performed.
Measurement uncertainty: Friend or foe?
Infusino, Ilenia; Panteghini, Mauro
2018-02-02
The definition and enforcement of a reference measurement system, based on the implementation of metrological traceability of patients' results to higher order reference methods and materials, together with a clinically acceptable level of measurement uncertainty, are fundamental requirements to produce accurate and equivalent laboratory results. The uncertainty associated with each step of the traceability chain should be governed to obtain a final combined uncertainty on clinical samples fulfilling the requested performance specifications. It is important that end-users (i.e., clinical laboratory) may know and verify how in vitro diagnostics (IVD) manufacturers have implemented the traceability of their calibrators and estimated the corresponding uncertainty. However, full information about traceability and combined uncertainty of calibrators is currently very difficult to obtain. Laboratory professionals should investigate the need to reduce the uncertainty of the higher order metrological references and/or to increase the precision of commercial measuring systems. Accordingly, the measurement uncertainty should not be considered a parameter to be calculated by clinical laboratories just to fulfil the accreditation standards, but it must become a key quality indicator to describe both the performance of an IVD measuring system and the laboratory itself. Copyright © 2018 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.
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.)
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.).
Calibration and Measurement Uncertainty Estimation of Radiometric Data: Preprint
Energy Technology Data Exchange (ETDEWEB)
Habte, A.; Sengupta, M.; Reda, I.; Andreas, A.; Konings, J.
2014-11-01
Evaluating the performance of photovoltaic cells, modules, and arrays that form large solar deployments relies on accurate measurements of the available solar resource. Therefore, determining the accuracy of these solar radiation measurements provides a better understanding of investment risks. This paper provides guidelines and recommended procedures for estimating the uncertainty in calibrations and measurements by radiometers using methods that follow the International Bureau of Weights and Measures Guide to the Expression of Uncertainty (GUM). Standardized analysis based on these procedures ensures that the uncertainty quoted is well documented.
Model uncertainty: Probabilities for models?
International Nuclear Information System (INIS)
Winkler, R.L.
1994-01-01
Like any other type of uncertainty, model uncertainty should be treated in terms of probabilities. The question is how to do this. The most commonly-used approach has a drawback related to the interpretation of the probabilities assigned to the models. If we step back and look at the big picture, asking what the appropriate focus of the model uncertainty question should be in the context of risk and decision analysis, we see that a different probabilistic approach makes more sense, although it raise some implementation questions. Current work that is underway to address these questions looks very promising
African anthropogenic combustion emission inventory: specificities and uncertainties
Sekou, K.; Liousse, C.; Eric-michel, A.; Veronique, Y.; Thierno, D.; Roblou, L.; Toure, E. N.; Julien, B.
2015-12-01
Fossil fuel and biofuel emissions of gases and particles in Africa are expected to significantly increase in the near future, particularly due to the growth of African cities. In addition, African large savannah fires occur each year during the dry season, mainly for socio-economical purposes. In this study, we will present the most recent developments of African anthropogenic combustion emission inventories, stressing African specificities. (1)A regional fossil fuel and biofuel inventory for gases and particulates will be presented for Africa at a resolution of 0.25° x 0.25° from 1990 to 2012. For this purpose, the original database of Liousse et al. (2014) has been used after modification for emission factors and for updated regional fuel consumption including new emitter categories (waste burning, flaring) and new activity sectors (i.e. disaggregation of transport into sub-sectors including two wheel ). In terms of emission factors, new measured values will be presented and compared to litterature with a focus on aerosols. They result from measurement campaigns organized in the frame of DACCIWA European program for each kind of African specific anthropogenic sources in 2015, in Abidjan (Ivory Coast), Cotonou (Benin) and in Laboratoire d'Aérologie combustion chamber. Finally, a more detailed spatial distribution of emissions will be proposed at a country level to better take into account road distributions and population densities. (2) Large uncertainties still remain in biomass burning emission inventories estimates, especially over Africa between different datasets such as GFED and AMMABB. Sensitivity tests will be presented to investigate uncertainties in the emission inventories, applying methodologies used for AMMABB and GFED inventories respectively. Then, the relative importance of each sources (fossil fuel, biofuel and biomass burning inventories) on the budgets of carbon monoxide, nitrogen oxides, sulfur dioxide, black and organic carbon, and volatile
Uncertainty modelling and code calibration for composite materials
DEFF Research Database (Denmark)
Toft, Henrik Stensgaard; Branner, Kim; Mishnaevsky, Leon, Jr
2013-01-01
and measurement uncertainties which are introduced on the different scales. Typically, these uncertainties are taken into account in the design process using characteristic values and partial safety factors specified in a design standard. The value of the partial safety factors should reflect a reasonable balance...... to wind turbine blades are calibrated for two typical lay-ups using a large number of load cases and ratios between the aerodynamic forces and the inertia forces....
Decision-making under great uncertainty
International Nuclear Information System (INIS)
Hansson, S.O.
1992-01-01
Five types of decision-uncertainty are distinguished: uncertainty of consequences, of values, of demarcation, of reliance, and of co-ordination. Strategies are proposed for each type of uncertainty. The general conclusion is that it is meaningful for decision theory to treat cases with greater uncertainty than the textbook case of 'decision-making under uncertainty'. (au)
Quantification of Safety-Critical Software Test Uncertainty
International Nuclear Information System (INIS)
Khalaquzzaman, M.; Cho, Jaehyun; Lee, Seung Jun; Jung, Wondea
2015-01-01
The method, conservatively assumes that the failure probability of a software for the untested inputs is 1, and the failure probability turns in 0 for successful testing of all test cases. However, in reality the chance of failure exists due to the test uncertainty. Some studies have been carried out to identify the test attributes that affect the test quality. Cao discussed the testing effort, testing coverage, and testing environment. Management of the test uncertainties was discussed in. In this study, the test uncertainty has been considered to estimate the software failure probability because the software testing process is considered to be inherently uncertain. A reliability estimation of software is very important for a probabilistic safety analysis of a digital safety critical system of NPPs. This study focused on the estimation of the probability of a software failure that considers the uncertainty in software testing. In our study, BBN has been employed as an example model for software test uncertainty quantification. Although it can be argued that the direct expert elicitation of test uncertainty is much simpler than BBN estimation, however the BBN approach provides more insights and a basis for uncertainty estimation
A Framework for Understanding Uncertainty in Seismic Risk Assessment.
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.
Overview of Existing Wind Energy Ordinances
Energy Technology Data Exchange (ETDEWEB)
Oteri, F.
2008-12-01
Due to increased energy demand in the United States, rural communities with limited or no experience with wind energy now have the opportunity to become involved in this industry. Communities with good wind resources may be approached by entities with plans to develop the resource. Although these opportunities can create new revenue in the form of construction jobs and land lease payments, they also create a new responsibility on the part of local governments to ensure that ordinances will be established to aid the development of safe facilities that will be embraced by the community. The purpose of this report is to educate and engage state and local governments, as well as policymakers, about existing large wind energy ordinances. These groups will have a collection of examples to utilize when they attempt to draft a new large wind energy ordinance in a town or county without existing ordinances.
Uncertainties in fission-product decay-heat calculations
Energy Technology Data Exchange (ETDEWEB)
Oyamatsu, K.; Ohta, H.; Miyazono, T.; Tasaka, K. [Nagoya Univ. (Japan)
1997-03-01
The present precision of the aggregate decay heat calculations is studied quantitatively for 50 fissioning systems. In this evaluation, nuclear data and their uncertainty data are taken from ENDF/B-VI nuclear data library and those which are not available in this library are supplemented by a theoretical consideration. An approximate method is proposed to simplify the evaluation of the uncertainties in the aggregate decay heat calculations so that we can point out easily nuclei which cause large uncertainties in the calculated decay heat values. In this paper, we attempt to clarify the justification of the approximation which was not very clear at the early stage of the study. We find that the aggregate decay heat uncertainties for minor actinides such as Am and Cm isotopes are 3-5 times as large as those for {sup 235}U and {sup 239}Pu. The recommended values by Atomic Energy Society of Japan (AESJ) were given for 3 major fissioning systems, {sup 235}U(t), {sup 239}Pu(t) and {sup 238}U(f). The present results are consistent with the AESJ values for these systems although the two evaluations used different nuclear data libraries and approximations. Therefore, the present results can also be considered to supplement the uncertainty values for the remaining 17 fissioning systems in JNDC2, which were not treated in the AESJ evaluation. Furthermore, we attempt to list nuclear data which cause large uncertainties in decay heat calculations for the future revision of decay and yield data libraries. (author)
Uncertainty Analysis and Expert Judgment in Seismic Hazard Analysis
Klügel, Jens-Uwe
2011-01-01
The large uncertainty associated with the prediction of future earthquakes is usually regarded as the main reason for increased hazard estimates which have resulted from some recent large scale probabilistic seismic hazard analysis studies (e.g. the PEGASOS study in Switzerland and the Yucca Mountain study in the USA). It is frequently overlooked that such increased hazard estimates are characteristic for a single specific method of probabilistic seismic hazard analysis (PSHA): the traditional (Cornell-McGuire) PSHA method which has found its highest level of sophistication in the SSHAC probability method. Based on a review of the SSHAC probability model and its application in the PEGASOS project, it is shown that the surprising results of recent PSHA studies can be explained to a large extent by the uncertainty model used in traditional PSHA, which deviates from the state of the art in mathematics and risk analysis. This uncertainty model, the Ang-Tang uncertainty model, mixes concepts of decision theory with probabilistic hazard assessment methods leading to an overestimation of uncertainty in comparison to empirical evidence. Although expert knowledge can be a valuable source of scientific information, its incorporation into the SSHAC probability method does not resolve the issue of inflating uncertainties in PSHA results. Other, more data driven, PSHA approaches in use in some European countries are less vulnerable to this effect. The most valuable alternative to traditional PSHA is the direct probabilistic scenario-based approach, which is closely linked with emerging neo-deterministic methods based on waveform modelling.
Brown, G.
2017-12-01
Sediment diversions have been proposed as a crucial component of the restoration of Coastal Louisiana. They are generally characterized as a means of creating land by mimicking natural crevasse-splay sub-delta processes. However, the criteria that are often promoted to optimize the performance of these diversions (i.e. large, sand-rich diversions into existing, degraded wetlands) are at odds with the natural processes that govern the development of crevasse-splay sub-deltas (typically sand-lean or sand-neutral diversions into open water). This is due in large part to the fact that these optimization criteria have been developed in the absence of consideration for the natural constraints associated with fundamental hydraulics: specifically, the conservation of mechanical energy. Although the implementation of the aforementioned optimization criteria have the potential to greatly increase the land-building capacity of a given diversion, the concomitant widespread inundation of the existing wetlands (an unavoidable consequence of diverting into a shallow, vegetated embayment), and the resultant stresses on existing wetland vegetation, have the potential to dramatically accelerate the loss of these existing wetlands. Hence, there are inherent uncertainties in the forecasted performance of sediment diversions that are designed according to the criteria mentioned above. This talk details the reasons for these uncertainties, using analytic and numerical model results, together with evidence from field observations and experiments. The likelihood that, in the foreseeable future, these uncertainties can be reduced, or even rationally bounded, is discussed.
Improved Monte Carlo Method for PSA Uncertainty Analysis
International Nuclear Information System (INIS)
Choi, Jongsoo
2016-01-01
The treatment of uncertainty is an important issue for regulatory decisions. Uncertainties exist from knowledge limitations. A probabilistic approach has exposed some of these limitations and provided a framework to assess their significance and assist in developing a strategy to accommodate them in the regulatory process. The uncertainty analysis (UA) is usually based on the Monte Carlo method. This paper proposes a Monte Carlo UA approach to calculate the mean risk metrics accounting for the SOKC between basic events (including CCFs) using efficient random number generators and to meet Capability Category III of the ASME/ANS PRA standard. Audit calculation is needed in PSA regulatory reviews of uncertainty analysis results submitted for licensing. The proposed Monte Carlo UA approach provides a high degree of confidence in PSA reviews. All PSA needs accounting for the SOKC between event probabilities to meet the ASME/ANS PRA standard
Improved Monte Carlo Method for PSA Uncertainty Analysis
Energy Technology Data Exchange (ETDEWEB)
Choi, Jongsoo [Korea Institute of Nuclear Safety, Daejeon (Korea, Republic of)
2016-10-15
The treatment of uncertainty is an important issue for regulatory decisions. Uncertainties exist from knowledge limitations. A probabilistic approach has exposed some of these limitations and provided a framework to assess their significance and assist in developing a strategy to accommodate them in the regulatory process. The uncertainty analysis (UA) is usually based on the Monte Carlo method. This paper proposes a Monte Carlo UA approach to calculate the mean risk metrics accounting for the SOKC between basic events (including CCFs) using efficient random number generators and to meet Capability Category III of the ASME/ANS PRA standard. Audit calculation is needed in PSA regulatory reviews of uncertainty analysis results submitted for licensing. The proposed Monte Carlo UA approach provides a high degree of confidence in PSA reviews. All PSA needs accounting for the SOKC between event probabilities to meet the ASME/ANS PRA standard.
Realising the Uncertainty Enabled Model Web
Cornford, D.; Bastin, L.; Pebesma, E. J.; Williams, M.; Stasch, C.; Jones, R.; Gerharz, L.
2012-12-01
The FP7 funded UncertWeb project aims to create the "uncertainty enabled model web". The central concept here is that geospatial models and data resources are exposed via standard web service interfaces, such as the Open Geospatial Consortium (OGC) suite of encodings and interface standards, allowing the creation of complex workflows combining both data and models. The focus of UncertWeb is on the issue of managing uncertainty in such workflows, and providing the standards, architecture, tools and software support necessary to realise the "uncertainty enabled model web". In this paper we summarise the developments in the first two years of UncertWeb, illustrating several key points with examples taken from the use case requirements that motivate the project. Firstly we address the issue of encoding specifications. We explain the usage of UncertML 2.0, a flexible encoding for representing uncertainty based on a probabilistic approach. This is designed to be used within existing standards such as Observations and Measurements (O&M) and data quality elements of ISO19115 / 19139 (geographic information metadata and encoding specifications) as well as more broadly outside the OGC domain. We show profiles of O&M that have been developed within UncertWeb and how UncertML 2.0 is used within these. We also show encodings based on NetCDF and discuss possible future directions for encodings in JSON. We then discuss the issues of workflow construction, considering discovery of resources (both data and models). We discuss why a brokering approach to service composition is necessary in a world where the web service interfaces remain relatively heterogeneous, including many non-OGC approaches, in particular the more mainstream SOAP and WSDL approaches. We discuss the trade-offs between delegating uncertainty management functions to the service interfaces themselves and integrating the functions in the workflow management system. We describe two utility services to address
The Uncertainties of Risk Management
DEFF Research Database (Denmark)
Vinnari, Eija; Skærbæk, Peter
2014-01-01
for expanding risk management. More generally, such uncertainties relate to the professional identities and responsibilities of operational managers as defined by the framing devices. Originality/value – The paper offers three contributions to the extant literature: first, it shows how risk management itself......Purpose – The purpose of this paper is to analyse the implementation of risk management as a tool for internal audit activities, focusing on unexpected effects or uncertainties generated during its application. Design/methodology/approach – Public and confidential documents as well as semi......-structured interviews are analysed through the lens of actor-network theory to identify the effects of risk management devices in a Finnish municipality. Findings – The authors found that risk management, rather than reducing uncertainty, itself created unexpected uncertainties that would otherwise not have emerged...
Climate Projections and Uncertainty Communication.
Joslyn, Susan L; LeClerc, Jared E
2016-01-01
Lingering skepticism about climate change might be due in part to the way climate projections are perceived by members of the public. Variability between scientists' estimates might give the impression that scientists disagree about the fact of climate change rather than about details concerning the extent or timing. Providing uncertainty estimates might clarify that the variability is due in part to quantifiable uncertainty inherent in the prediction process, thereby increasing people's trust in climate projections. This hypothesis was tested in two experiments. Results suggest that including uncertainty estimates along with climate projections leads to an increase in participants' trust in the information. Analyses explored the roles of time, place, demographic differences (e.g., age, gender, education level, political party affiliation), and initial belief in climate change. Implications are discussed in terms of the potential benefit of adding uncertainty estimates to public climate projections. Copyright © 2015 Cognitive Science Society, Inc.
Relational uncertainty in service dyads
DEFF Research Database (Denmark)
Kreye, Melanie
2017-01-01
in service dyads and how they resolve it through suitable organisational responses to increase the level of service quality. Design/methodology/approach: We apply the overall logic of Organisational Information-Processing Theory (OIPT) and present empirical insights from two industrial case studies collected...... the relational uncertainty increased the functional quality while resolving the partner’s organisational uncertainty increased the technical quality of the delivered service. Originality: We make two contributions. First, we introduce relational uncertainty to the OM literature as the inability to predict...... and explain the actions of a partnering organisation due to a lack of knowledge about their abilities and intentions. Second, we present suitable organisational responses to relational uncertainty and their effect on service quality....
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)
How to live with uncertainties?
International Nuclear Information System (INIS)
Michel, R.
2012-01-01
In a short introduction, the problem of uncertainty as a general consequence of incomplete information as well as the approach to quantify uncertainty in metrology are addressed. A little history of the more than 30 years of the working group AK SIGMA is followed by an appraisal of its up-to-now achievements. Then, the potential future of the AK SIGMA is discussed based on its actual tasks and on open scientific questions and future topics. (orig.)
Some remarks on modeling uncertainties
International Nuclear Information System (INIS)
Ronen, Y.
1983-01-01
Several topics related to the question of modeling uncertainties are considered. The first topic is related to the use of the generalized bias operator method for modeling uncertainties. The method is expanded to a more general form of operators. The generalized bias operator is also used in the inverse problem and applied to determine the anisotropic scattering law. The last topic discussed is related to the question of the limit to accuracy and how to establish its value. (orig.) [de
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)
Optimal Taxation under Income Uncertainty
Xianhua Dai
2011-01-01
Optimal taxation under income uncertainty has been extensively developed in expected utility theory, but it is still open for inseparable utility function between income and effort. As an alternative of decision-making under uncertainty, prospect theory (Kahneman and Tversky (1979), Tversky and Kahneman (1992)) has been obtained empirical support, for example, Kahneman and Tversky (1979), and Camerer and Lowenstein (2003). It is beginning to explore optimal taxation in the context of prospect...
New Perspectives on Policy Uncertainty
Hlatshwayo, Sandile
2017-01-01
In recent years, the ubiquitous and intensifying nature of economic policy uncertainty has made it a popular explanation for weak economic performance in developed and developing markets alike. The primary channel for this effect is decreased and delayed investment as firms adopt a ``wait and see'' approach to irreversible investments (Bernanke, 1983; Dixit and Pindyck, 1994). Deep empirical examination of policy uncertainty's impact is rare because of the difficulty associated in measuring i...
Pharmacological Fingerprints of Contextual Uncertainty.
Directory of Open Access Journals (Sweden)
Louise Marshall
2016-11-01
Full Text Available Successful interaction with the environment requires flexible updating of our beliefs about the world. By estimating the likelihood of future events, it is possible to prepare appropriate actions in advance and execute fast, accurate motor responses. According to theoretical proposals, agents track the variability arising from changing environments by computing various forms of uncertainty. Several neuromodulators have been linked to uncertainty signalling, but comprehensive empirical characterisation of their relative contributions to perceptual belief updating, and to the selection of motor responses, is lacking. Here we assess the roles of noradrenaline, acetylcholine, and dopamine within a single, unified computational framework of uncertainty. Using pharmacological interventions in a sample of 128 healthy human volunteers and a hierarchical Bayesian learning model, we characterise the influences of noradrenergic, cholinergic, and dopaminergic receptor antagonism on individual computations of uncertainty during a probabilistic serial reaction time task. We propose that noradrenaline influences learning of uncertain events arising from unexpected changes in the environment. In contrast, acetylcholine balances attribution of uncertainty to chance fluctuations within an environmental context, defined by a stable set of probabilistic associations, or to gross environmental violations following a contextual switch. Dopamine supports the use of uncertainty representations to engender fast, adaptive responses.
Existing Steel Railway Bridges Evaluation
Vičan, Josef; Gocál, Jozef; Odrobiňák, Jaroslav; Koteš, Peter
2016-12-01
The article describes general principles and basis of evaluation of existing railway bridges based on the concept of load-carrying capacity determination. Compared to the design of a new bridge, the modified reliability level for existing bridges evaluation should be considered due to implementation of the additional data related to bridge condition and behaviour obtained from regular inspections. Based on those data respecting the bridge remaining lifetime, a modification of partial safety factors for actions and materials could be respected in the bridge evaluation process. A great attention is also paid to the specific problems of determination of load-caring capacity of steel railway bridges in service. Recommendation for global analysis and methodology for existing steel bridge superstructure load-carrying capacity determination are described too.
Existing Steel Railway Bridges Evaluation
Directory of Open Access Journals (Sweden)
Vičan Josef
2016-12-01
Full Text Available The article describes general principles and basis of evaluation of existing railway bridges based on the concept of load-carrying capacity determination. Compared to the design of a new bridge, the modified reliability level for existing bridges evaluation should be considered due to implementation of the additional data related to bridge condition and behaviour obtained from regular inspections. Based on those data respecting the bridge remaining lifetime, a modification of partial safety factors for actions and materials could be respected in the bridge evaluation process. A great attention is also paid to the specific problems of determination of load-caring capacity of steel railway bridges in service. Recommendation for global analysis and methodology for existing steel bridge superstructure load-carrying capacity determination are described too.
A Bayesian approach to model uncertainty
International Nuclear Information System (INIS)
Buslik, A.
1994-01-01
A Bayesian approach to model uncertainty is taken. For the case of a finite number of alternative models, the model uncertainty is equivalent to parameter uncertainty. A derivation based on Savage's partition problem is given
The NASA Langley Multidisciplinary Uncertainty Quantification Challenge
Crespo, Luis G.; Kenny, Sean P.; Giesy, Daniel P.
2014-01-01
This paper presents the formulation of an uncertainty quantification challenge problem consisting of five subproblems. These problems focus on key aspects of uncertainty characterization, sensitivity analysis, uncertainty propagation, extreme-case analysis, and robust design.
Communicating spatial uncertainty to non-experts using R
Luzzi, Damiano; Sawicka, Kasia; Heuvelink, Gerard; de Bruin, Sytze
2016-04-01
Effective visualisation methods are important for the efficient use of uncertainty information for various groups of users. Uncertainty propagation analysis is often used with spatial environmental models to quantify the uncertainty within the information. A challenge arises when trying to effectively communicate the uncertainty information to non-experts (not statisticians) in a wide range of cases. Due to the growing popularity and applicability of the open source programming language R, we undertook a project to develop an R package that facilitates uncertainty propagation analysis in spatial environmental modelling. The package has implemented Monte Carlo algorithms for uncertainty propagation, the output of which is represented by an ensemble of model outputs (i.e. a sample from a probability distribution). Numerous visualisation methods exist that aim to present such spatial uncertainty information both statically, dynamically and interactively. To provide the most universal visualisation tools for non-experts, we conducted a survey on a group of 20 university students and assessed the effectiveness of selected static and interactive methods for visualising uncertainty in spatial variables such as DEM and land cover. The static methods included adjacent maps and glyphs for continuous variables. Both allow for displaying maps with information about the ensemble mean, variance/standard deviation and prediction intervals. Adjacent maps were also used for categorical data, displaying maps of the most probable class, as well as its associated probability. The interactive methods included a graphical user interface, which in addition to displaying the previously mentioned variables also allowed for comparison of joint uncertainties at multiple locations. The survey indicated that users could understand the basics of the uncertainty information displayed in the static maps, with the interactive interface allowing for more in-depth information. Subsequently, the R
Uncertainties in risk assessment at USDOE facilities
Energy Technology Data Exchange (ETDEWEB)
Hamilton, L.D.; Holtzman, S.; Meinhold, A.F.; Morris, S.C.; Rowe, M.D.
1994-01-01
The United States Department of Energy (USDOE) has embarked on an ambitious program to remediate environmental contamination at its facilities. Decisions concerning cleanup goals, choices among cleanup technologies, and funding prioritization should be largely risk-based. Risk assessments will be used more extensively by the USDOE in the future. USDOE needs to develop and refine risk assessment methods and fund research to reduce major sources of uncertainty in risk assessments at USDOE facilities. The terms{open_quote} risk assessment{close_quote} and{open_quote} risk management{close_quote} are frequently confused. The National Research Council (1983) and the United States Environmental Protection Agency (USEPA, 1991a) described risk assessment as a scientific process that contributes to risk management. Risk assessment is the process of collecting, analyzing and integrating data and information to identify hazards, assess exposures and dose responses, and characterize risks. Risk characterization must include a clear presentation of {open_quotes}... the most significant data and uncertainties...{close_quotes} in an assessment. Significant data and uncertainties are {open_quotes}...those that define and explain the main risk conclusions{close_quotes}. Risk management integrates risk assessment information with other considerations, such as risk perceptions, socioeconomic and political factors, and statutes, to make and justify decisions. Risk assessments, as scientific processes, should be made independently of the other aspects of risk management (USEPA, 1991a), but current methods for assessing health risks are based on conservative regulatory principles, causing unnecessary public concern and misallocation of funds for remediation.
Uncertainties in risk assessment at USDOE facilities
International Nuclear Information System (INIS)
Hamilton, L.D.; Holtzman, S.; Meinhold, A.F.; Morris, S.C.; Rowe, M.D.
1994-01-01
The United States Department of Energy (USDOE) has embarked on an ambitious program to remediate environmental contamination at its facilities. Decisions concerning cleanup goals, choices among cleanup technologies, and funding prioritization should be largely risk-based. Risk assessments will be used more extensively by the USDOE in the future. USDOE needs to develop and refine risk assessment methods and fund research to reduce major sources of uncertainty in risk assessments at USDOE facilities. The terms open-quote risk assessment close-quote and open-quote risk management close-quote are frequently confused. The National Research Council (1983) and the United States Environmental Protection Agency (USEPA, 1991a) described risk assessment as a scientific process that contributes to risk management. Risk assessment is the process of collecting, analyzing and integrating data and information to identify hazards, assess exposures and dose responses, and characterize risks. Risk characterization must include a clear presentation of open-quotes... the most significant data and uncertainties...close quotes in an assessment. Significant data and uncertainties are open-quotes...those that define and explain the main risk conclusionsclose quotes. Risk management integrates risk assessment information with other considerations, such as risk perceptions, socioeconomic and political factors, and statutes, to make and justify decisions. Risk assessments, as scientific processes, should be made independently of the other aspects of risk management (USEPA, 1991a), but current methods for assessing health risks are based on conservative regulatory principles, causing unnecessary public concern and misallocation of funds for remediation
Improvement of Statistical Decisions under Parametric Uncertainty
Nechval, Nicholas A.; Nechval, Konstantin N.; Purgailis, Maris; Berzins, Gundars; Rozevskis, Uldis
2011-10-01
A large number of problems in production planning and scheduling, location, transportation, finance, and engineering design require that decisions be made in the presence of uncertainty. Decision-making under uncertainty is a central problem in statistical inference, and has been formally studied in virtually all approaches to inference. The aim of the present paper is to show how the invariant embedding technique, the idea of which belongs to the authors, may be employed in the particular case of finding the improved statistical decisions under parametric uncertainty. This technique represents a simple and computationally attractive statistical method based on the constructive use of the invariance principle in mathematical statistics. Unlike the Bayesian approach, an invariant embedding technique is independent of the choice of priors. It allows one to eliminate unknown parameters from the problem and to find the best invariant decision rule, which has smaller risk than any of the well-known decision rules. To illustrate the proposed technique, application examples are given.
Liu, Jianbo; Kummerow, Christian D.; Elsaesser, Gregory S.
2016-01-01
Despite continuous improvements in microwave sensors and retrieval algorithms, our understanding of precipitation uncertainty is quite limited, due primarily to inconsistent findings in studies that compare satellite estimates to in situ observations over different parts of the world. This study seeks to characterize the temporal and spatial properties of uncertainty in the Tropical Rainfall Measuring Mission Microwave Imager surface rainfall product over tropical ocean basins. Two uncertainty analysis frameworks are introduced to qualitatively evaluate the properties of uncertainty under a hierarchy of spatiotemporal data resolutions. The first framework (i.e. 'climate method') demonstrates that, apart from random errors and regionally dependent biases, a large component of the overall precipitation uncertainty is manifested in cyclical patterns that are closely related to large-scale atmospheric modes of variability. By estimating the magnitudes of major uncertainty sources independently, the climate method is able to explain 45-88% of the monthly uncertainty variability. The percentage is largely resolution dependent (with the lowest percentage explained associated with a 1 deg x 1 deg spatial/1 month temporal resolution, and highest associated with a 3 deg x 3 deg spatial/3 month temporal resolution). The second framework (i.e. 'weather method') explains regional mean precipitation uncertainty as a summation of uncertainties associated with individual precipitation systems. By further assuming that self-similar recurring precipitation systems yield qualitatively comparable precipitation uncertainties, the weather method can consistently resolve about 50 % of the daily uncertainty variability, with only limited dependence on the regions of interest.
Performance of Existing Hydrogen Stations
Energy Technology Data Exchange (ETDEWEB)
Sprik, Samuel [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Kurtz, Jennifer M [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Ainscough, Christopher D [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Saur, Genevieve [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Peters, Michael C [National Renewable Energy Laboratory (NREL), Golden, CO (United States)
2017-12-01
In this presentation, the National Renewable Energy Laboratory presented aggregated analysis results on the performance of existing hydrogen stations, including performance, operation, utilization, maintenance, safety, hydrogen quality, and cost. The U.S. Department of Energy funds technology validation work at NREL through its National Fuel Cell Technology Evaluation Center (NFCTEC).
Knowledge, consensus and uncertainty.
Cavell, M
1999-12-01
Some months ago the editors of this journal asked me if I would undertake a series of short entries of a general sort on philosophical topics germane to current discussions in psychoanalysis. Both authors and topics were left to my discretion. I thought the series was a good idea and gladly agreed to do it. To my surprise and pleasure, all the philosophers I invited accepted I am only sorry that the series could not be longer as there are other philosophers as well who would have been splendid participants, and other topics I would like to have addressed. The essays that will follow in subsequent issues represent by and large the tradition of analytic philosophy, though this has come in the last few decades to comprise many of the themes we used to associate with the Continental tradition. Future entries, by James Conant, Donald Davison, Pascal Engel, Dagfinn Føllesdal, James Hopkins, Ernest Le Pore, Jeffrey Malpas, Jerome Neu, Brian O'Shaughnessy, Richard Rorty and Richard Wollheim, will address the following topics: intersubjectivity, meaning and language, consciousness and perception, pragmatism, knowledge and belief, norms and nature, metaphor, hermeneutics, truth, self-deception, the emotions. The essay below on knowledge, which will also be the topic of another entry by a different author later on, is the only one in the series that I will write.
Essential information: Uncertainty and optimal control of Ebola outbreaks.
Li, Shou-Li; Bjørnstad, Ottar N; Ferrari, Matthew J; Mummah, Riley; Runge, Michael C; Fonnesbeck, Christopher J; Tildesley, Michael J; Probert, William J M; Shea, Katriona
2017-05-30
Early resolution of uncertainty during an epidemic outbreak can lead to rapid and efficient decision making, provided that the uncertainty affects prioritization of actions. The wide range in caseload projections for the 2014 Ebola outbreak caused great concern and debate about the utility of models. By coding and running 37 published Ebola models with five candidate interventions, we found that, despite this large variation in caseload projection, the ranking of management options was relatively consistent. Reducing funeral transmission and reducing community transmission were generally ranked as the two best options. Value of information (VoI) analyses show that caseloads could be reduced by 11% by resolving all model-specific uncertainties, with information about model structure accounting for 82% of this reduction and uncertainty about caseload only accounting for 12%. Our study shows that the uncertainty that is of most interest epidemiologically may not be the same as the uncertainty that is most relevant for management. If the goal is to improve management outcomes, then the focus of study should be to identify and resolve those uncertainties that most hinder the choice of an optimal intervention. Our study further shows that simplifying multiple alternative models into a smaller number of relevant groups (here, with shared structure) could streamline the decision-making process and may allow for a better integration of epidemiological modeling and decision making for policy.
Essential information: Uncertainty and optimal control of Ebola outbreaks
Li, Shou-Li; Bjornstad, Ottar; Ferrari, Matthew J.; Mummah, Riley; Runge, Michael C.; Fonnesbeck, Christopher J.; Tildesley, Michael J.; Probert, William J. M.; Shea, Katriona
2017-01-01
Early resolution of uncertainty during an epidemic outbreak can lead to rapid and efficient decision making, provided that the uncertainty affects prioritization of actions. The wide range in caseload projections for the 2014 Ebola outbreak caused great concern and debate about the utility of models. By coding and running 37 published Ebola models with five candidate interventions, we found that, despite this large variation in caseload projection, the ranking of management options was relatively consistent. Reducing funeral transmission and reducing community transmission were generally ranked as the two best options. Value of information (VoI) analyses show that caseloads could be reduced by 11% by resolving all model-specific uncertainties, with information about model structure accounting for 82% of this reduction and uncertainty about caseload only accounting for 12%. Our study shows that the uncertainty that is of most interest epidemiologically may not be the same as the uncertainty that is most relevant for management. If the goal is to improve management outcomes, then the focus of study should be to identify and resolve those uncertainties that most hinder the choice of an optimal intervention. Our study further shows that simplifying multiple alternative models into a smaller number of relevant groups (here, with shared structure) could streamline the decision-making process and may allow for a better integration of epidemiological modeling and decision making for policy.
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)
Automated uncertainty analysis methods in the FRAP computer codes
International Nuclear Information System (INIS)
Peck, S.O.
1980-01-01
A user oriented, automated uncertainty analysis capability has been incorporated in the Fuel Rod Analysis Program (FRAP) computer codes. The FRAP codes have been developed for the analysis of Light Water Reactor fuel rod behavior during steady state (FRAPCON) and transient (FRAP-T) conditions as part of the United States Nuclear Regulatory Commission's Water Reactor Safety Research Program. The objective of uncertainty analysis of these codes is to obtain estimates of the uncertainty in computed outputs of the codes is to obtain estimates of the uncertainty in computed outputs of the codes as a function of known uncertainties in input variables. This paper presents the methods used to generate an uncertainty analysis of a large computer code, discusses the assumptions that are made, and shows techniques for testing them. An uncertainty analysis of FRAP-T calculated fuel rod behavior during a hypothetical loss-of-coolant transient is presented as an example and carried through the discussion to illustrate the various concepts
Rational consensus under uncertainty: Expert judgment in the EC-USNRC uncertainty study
International Nuclear Information System (INIS)
Cooke, R.; Kraan, B.; Goossens, L.
1999-01-01
Governmental bodies are confronted with the problem of achieving rational consensus in the face of substantial uncertainties. The area of accident consequence management for nuclear power plants affords a good example. Decisions with regard to evacuation, decontamination, and food bans must be taken on the basis of predictions of environmental transport of radioactive material, contamination through the food chain, cancer induction, and the like. These predictions use mathematical models containing scores of uncertain parameters. Decision makers want to take, and want to be perceived to take, these decisions in a rational manner. The question is, how can this be accomplished in the face of large uncertainties? Indeed, the very presence of uncertainty poses a threat to rational consensus. Decision makers will necessarily base their actions on the judgments of experts. The experts, however, will not agree among themselves, as otherwise we would not speak of large uncertainties. Any given expert's viewpoint will be favorable to the interests of some stakeholders, and hostile to the interests of others. If a decision maker bases his/her actions on the views of one single expert, then (s)he is invariably open to charges of partiality toward the interests favored by this viewpoint. An appeal to 'impartial' or 'disinterested' experts will fail for two reasons. First, experts have interests; they have jobs, mortgages and professional reputations. Second, even if expert interests could somehow be quarantined, even then the experts would disagree. Expert disagreement is not explained by diverging interests, and consensus cannot be reached by shielding the decision process from expert interests. If rational consensus requires expert agreement, then rational consensus is simply not possible in the face of uncertainty. If rational consensus under uncertainty is to be achieved, then evidently the views of a diverse set of experts must be taken into account. The question is how
RUMINATIONS ON NDA MEASUREMENT UNCERTAINTY COMPARED TO DA UNCERTAINTY
Energy Technology Data Exchange (ETDEWEB)
Salaymeh, S.; Ashley, W.; Jeffcoat, R.
2010-06-17
It is difficult to overestimate the importance that physical measurements performed with nondestructive assay instruments play throughout the nuclear fuel cycle. They underpin decision making in many areas and support: criticality safety, radiation protection, process control, safeguards, facility compliance, and waste measurements. No physical measurement is complete or indeed meaningful, without a defensible and appropriate accompanying statement of uncertainties and how they combine to define the confidence in the results. The uncertainty budget should also be broken down in sufficient detail suitable for subsequent uses to which the nondestructive assay (NDA) results will be applied. Creating an uncertainty budget and estimating the total measurement uncertainty can often be an involved process, especially for non routine situations. This is because data interpretation often involves complex algorithms and logic combined in a highly intertwined way. The methods often call on a multitude of input data subject to human oversight. These characteristics can be confusing and pose a barrier to developing and understanding between experts and data consumers. ASTM subcommittee C26-10 recognized this problem in the context of how to summarize and express precision and bias performance across the range of standards and guides it maintains. In order to create a unified approach consistent with modern practice and embracing the continuous improvement philosophy a consensus arose to prepare a procedure covering the estimation and reporting of uncertainties in non destructive assay of nuclear materials. This paper outlines the needs analysis, objectives and on-going development efforts. In addition to emphasizing some of the unique challenges and opportunities facing the NDA community we hope this article will encourage dialog and sharing of best practice and furthermore motivate developers to revisit the treatment of measurement uncertainty.
Ruminations On NDA Measurement Uncertainty Compared TO DA Uncertainty
International Nuclear Information System (INIS)
Salaymeh, S.; Ashley, W.; Jeffcoat, R.
2010-01-01
It is difficult to overestimate the importance that physical measurements performed with nondestructive assay instruments play throughout the nuclear fuel cycle. They underpin decision making in many areas and support: criticality safety, radiation protection, process control, safeguards, facility compliance, and waste measurements. No physical measurement is complete or indeed meaningful, without a defensible and appropriate accompanying statement of uncertainties and how they combine to define the confidence in the results. The uncertainty budget should also be broken down in sufficient detail suitable for subsequent uses to which the nondestructive assay (NDA) results will be applied. Creating an uncertainty budget and estimating the total measurement uncertainty can often be an involved process, especially for non routine situations. This is because data interpretation often involves complex algorithms and logic combined in a highly intertwined way. The methods often call on a multitude of input data subject to human oversight. These characteristics can be confusing and pose a barrier to developing and understanding between experts and data consumers. ASTM subcommittee C26-10 recognized this problem in the context of how to summarize and express precision and bias performance across the range of standards and guides it maintains. In order to create a unified approach consistent with modern practice and embracing the continuous improvement philosophy a consensus arose to prepare a procedure covering the estimation and reporting of uncertainties in non destructive assay of nuclear materials. This paper outlines the needs analysis, objectives and on-going development efforts. In addition to emphasizing some of the unique challenges and opportunities facing the NDA community we hope this article will encourage dialog and sharing of best practice and furthermore motivate developers to revisit the treatment of measurement uncertainty.
Can you put too much on your plate? Uncertainty exposure in servitized triads
DEFF Research Database (Denmark)
Kreye, Melanie E.
2017-01-01
-national servitized triad in a European-North African set-up which was collected through 29 semi-structured interviews and secondary data. Findings: The empirical study identified the existence of the three uncertainty types and directional knock-on effects between them. Specifically, environmental uncertainty...... relational governance reduced relational uncertainty. The knock-on effects were reduced through organisational and relational responses. Originality: This paper makes two contributions. First, a structured analysis of the uncertainty exposure in servitized triads is presented which shows the existence...... of three individual uncertainty types and the knock-on effects between them. Second, organisational responses to reduce the three uncertainty types individually and the knock-on effects between them are presented....
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.
OpenTURNS, an open source uncertainty engineering software
International Nuclear Information System (INIS)
Popelin, A.L.; Dufoy, A.
2013-01-01
The needs to assess robust performances for complex systems have lead to the emergence of a new industrial simulation challenge: to take into account uncertainties when dealing with complex numerical simulation frameworks. EDF has taken part in the development of an Open Source software platform dedicated to uncertainty propagation by probabilistic methods, named OpenTURNS for Open source Treatment of Uncertainty, Risk and Statistics. OpenTURNS includes a large variety of qualified algorithms in order to manage uncertainties in industrial studies, from the uncertainty quantification step (with possibilities to model stochastic dependence thanks to the copula theory and stochastic processes), to the uncertainty propagation step (with some innovative simulation algorithms as the ziggurat method for normal variables) and the sensitivity analysis one (with some sensitivity index based on the evaluation of means conditioned to the realization of a particular event). It also enables to build some response surfaces that can include the stochastic modeling (with the chaos polynomial method for example). Generic wrappers to link OpenTURNS to the modeling software are proposed. At last, OpenTURNS is largely documented to provide rules to help use and contribution
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
Uncertainty modeling and decision support
International Nuclear Information System (INIS)
Yager, Ronald R.
2004-01-01
We first formulate the problem of decision making under uncertainty. The importance of the representation of our knowledge about the uncertainty in formulating a decision process is pointed out. We begin with a brief discussion of the case of probabilistic uncertainty. Next, in considerable detail, we discuss the case of decision making under ignorance. For this case the fundamental role of the attitude of the decision maker is noted and its subjective nature is emphasized. Next the case in which a Dempster-Shafer belief structure is used to model our knowledge of the uncertainty is considered. Here we also emphasize the subjective choices the decision maker must make in formulating a decision function. The case in which the uncertainty is represented by a fuzzy measure (monotonic set function) is then investigated. We then return to the Dempster-Shafer belief structure and show its relationship to the fuzzy measure. This relationship allows us to get a deeper understanding of the formulation the decision function used Dempster- Shafer framework. We discuss how this deeper understanding allows a decision analyst to better make the subjective choices needed in the formulation of the decision function
Quantifying phenomenological importance in best-estimate plus uncertainty analyses
International Nuclear Information System (INIS)
Martin, Robert P.
2009-01-01
This paper describes a general methodology for quantifying the importance of specific phenomenological elements to analysis measures evaluated from non-parametric best-estimate plus uncertainty evaluation methodologies. The principal objective of an importance analysis is to reveal those uncertainty contributors having the greatest influence on key analysis measures. This characterization supports the credibility of the uncertainty analysis, the applicability of the analytical tools, and even the generic evaluation methodology through the validation of the engineering judgments that guided the evaluation methodology development. A demonstration of the importance analysis is provided using data from a sample problem considered in the development of AREVA's Realistic LBLOCA methodology. The results are presented against the original large-break LOCA Phenomena Identification and Ranking Table developed by the Technical Program Group responsible for authoring the Code Scaling, Applicability and Uncertainty methodology. (author)
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
Regime-dependent forecast uncertainty of convective precipitation
Energy Technology Data Exchange (ETDEWEB)
Keil, Christian; Craig, George C. [Muenchen Univ. (Germany). Meteorologisches Inst.
2011-04-15
Forecast uncertainty of convective precipitation is influenced by all scales, but in different ways in different meteorological situations. Forecasts of the high resolution ensemble prediction system COSMO-DE-EPS of Deutscher Wetterdienst (DWD) are used to examine the dominant sources of uncertainty of convective precipitation. A validation with radar data using traditional as well as spatial verification measures highlights differences in precipitation forecast performance in differing weather regimes. When the forecast uncertainty can primarily be associated with local, small-scale processes individual members run with the same variation of the physical parameterisation driven by different global models outperform all other ensemble members. In contrast when the precipitation is governed by the large-scale flow all ensemble members perform similarly. Application of the convective adjustment time scale confirms this separation and shows a regime-dependent forecast uncertainty of convective precipitation. (orig.)
The Greenhouse Effect Does Exist!
Ebel, Jochen
2009-01-01
In particular, without the greenhouse effect, essential features of the atmospheric temperature profile as a function of height cannot be described, i.e., the existence of the tropopause above which we see an almost isothermal temperature curve, whereas beneath it the temperature curve is nearly adiabatic. The relationship between the greenhouse effect and observed temperature curve is explained and the paper by Gerlich and Tscheuschner [arXiv:0707.1161] critically analyzed. Gerlich and Tsche...
Europe - space for transcultural existence?
Tamcke, Martin; Janny, de Jong; Klein, Lars; Waal, Margriet
2013-01-01
Europe - Space for Transcultural Existence? is the first volume of the new series, Studies in Euroculture, published by Göttingen University Press. The series derives its name from the Erasmus Mundus Master of Excellence Euroculture: Europe in the Wider World, a two year programme offered by a consortium of eight European universities in collaboration with four partner universities outside Europe. This master highlights regional, national and supranational dimensions of the European democrati...
Existence of undiscovered Uranian satellites
International Nuclear Information System (INIS)
Boice, D.C.
1986-04-01
Structure in the Uranian ring system as observed in recent occultations may contain indirect evidence for the existence of undiscovered satellites. Using the Alfven and Arrhenius (1975, 1976) scenario for the formation of planetary systems, the orbital radii of up to nine hypothetical satellites interior to Miranda are computed. These calculations should provide interesting comparisons when the results from the Voyager 2 encounter with Uranus are made public. 15 refs., 1 fig., 1 tab
UNCITRAL: Changes to existing law
Andersson, Joakim
2008-01-01
The UNCITRAL Convention on Contracts for the International Carriage of Goods [wholly or partly] by Sea has an ambition of replacing current maritime regimes and expands the application of the Convention to include also multimodal transport. This thesis questions what changes to existing law, in certain areas, the new Convention will bring compared to the current regimes. In the initial part, the thesis provides for a brief background and history of international maritime regulations and focus...
Existence Results for Incompressible Magnetoelasticity
Czech Academy of Sciences Publication Activity Database
Kružík, Martin; Stefanelli, U.; Zeman, J.
2015-01-01
Roč. 35, č. 6 (2015), s. 2615-2623 ISSN 1078-0947 R&D Projects: GA ČR GA13-18652S Institutional support: RVO:67985556 Keywords : magnetoelasticity * magnetostrictive solids * incompressibility * existence of minimizers * quasistatic evolution * energetic solution Subject RIV: BA - General Mathematics Impact factor: 1.127, year: 2015 http://library.utia.cas.cz/separaty/2015/MTR/kruzik-0443017.pdf
Risk communication for existing exposure situation after the nuclear disaster
International Nuclear Information System (INIS)
Yamaguchi, Ichiro
2011-01-01
The title subject is explained for its better understanding and recognition. The present state (Oct. 2011) where crisis of Fukushima Nuclear Accident has reached a settlement with release of 0.1 GBq/hr from the reactor container, is called the existing exposure situation. Radiation risk must be reduced under such a situation as people have to live in. Risk is defined to be a probability of matters undesirable, its size is assessed by various conditions and assumptions, it is manageable on its assessment, but its realization largely depends on subjectivity. Measures for lessening the risk usually accompany a load and disadvantage, leading to an antinomy structure (trade-off), of which problem is ultimately an ethical task of public health and cannot be solved in the form everybody agrees with. Therefore, a mutual consent among concerned people is required for deciding the principle of the risk management, for which the risk communication is essential. Risk communication about radiation is an unavoidable task of medical staffs as guided by International Commission of Radiological Protection (ICRP) (2001), International Atomic Energy Agency (IAEA) (2008) reports, World Health Organization (WHO), etc. However, the communication about radiation has now become also a task of the ordinary public under the present situation. For this, medical staffs are expected to play their role by acquiring the statistical literacy as well as with the radiological concept because the risk assessment accompanies the uncertainty. The author concludes that the risk communication is a problem of resolution to act, not of coping with. (T.T.)
LIU Jinquan; ZHENG Tingguo; SUI Jianli
2008-01-01
This paper uses the ARFIMA-FIGARCH model to investigate the China¡¯s monthly inflation rate from January 1983 to October 2005. It is found that both first moment and second moment of inflation have remarkable long memory, indicating the existence of long memory properties in both inflation level and inflation uncertainty. By the Granger-causality test on inflation rate and inflation uncertainty, it is shown that the inflation level affects the inflation uncertainty and so supports Friedman hy...
Insurance Applications of Active Fault Maps Showing Epistemic Uncertainty
Woo, G.
2005-12-01
high deductible is in force, this requires estimation of the epistemic uncertainty on fault geometry and activity. Transport infrastructure insurance is of practical interest in seismic countries. On the North Anatolian Fault in Turkey, there is uncertainty over an unbroken segment between the eastern end of the Dazce Fault and Bolu. This may have ruptured during the 1944 earthquake. Existing hazard maps may simply use a question mark to flag uncertainty. However, a far more informative type of hazard map might express spatial variations in the confidence level associated with a fault map. Through such visual guidance, an insurance risk analyst would be better placed to price earthquake cover, allowing for epistemic uncertainty.
International Nuclear Information System (INIS)
Davis, C.B.
1987-08-01
The uncertainties of calculations of loss-of-feedwater transients at Davis-Besse Unit 1 were determined to address concerns of the US Nuclear Regulatory Commission relative to the effectiveness of feed and bleed cooling. Davis-Besse Unit 1 is a pressurized water reactor of the raised-loop Babcock and Wilcox design. A detailed, quality-assured RELAP5/MOD2 model of Davis-Besse was developed at the Idaho National Engineering Laboratory. The model was used to perform an analysis of the loss-of-feedwater transient that occurred at Davis-Besse on June 9, 1985. A loss-of-feedwater transient followed by feed and bleed cooling was also calculated. The evaluation of uncertainty was based on the comparisons of calculations and data, comparisons of different calculations of the same transient, sensitivity calculations, and the propagation of the estimated uncertainty in initial and boundary conditions to the final calculated results
Decommissioning Funding: Ethics, Implementation, Uncertainties
International Nuclear Information System (INIS)
2007-01-01
This status report on decommissioning funding: ethics, implementation, uncertainties is based on a review of recent literature and materials presented at NEA meetings in 2003 and 2004, and particularly at a topical session organised in November 2004 on funding issues associated with the decommissioning of nuclear power facilities. The report also draws on the experience of the NEA Working Party on Decommissioning and Dismantling (WPDD). This report offers, in a concise form, an overview of relevant considerations on decommissioning funding mechanisms with regard to ethics, implementation and uncertainties. Underlying ethical principles found in international agreements are identified, and factors influencing the accumulation and management of funds for decommissioning nuclear facilities are discussed together with the main sources of uncertainties of funding systems
Uncertainty and Sensitivity Analyses Plan
International Nuclear Information System (INIS)
Simpson, J.C.; Ramsdell, J.V. Jr.
1993-04-01
Hanford Environmental Dose Reconstruction (HEDR) Project staff are developing mathematical models to be used to estimate the radiation dose that individuals may have received as a result of emissions since 1944 from the US Department of Energy's (DOE) Hanford Site near Richland, Washington. An uncertainty and sensitivity analyses plan is essential to understand and interpret the predictions from these mathematical models. This is especially true in the case of the HEDR models where the values of many parameters are unknown. This plan gives a thorough documentation of the uncertainty and hierarchical sensitivity analysis methods recommended for use on all HEDR mathematical models. The documentation includes both technical definitions and examples. In addition, an extensive demonstration of the uncertainty and sensitivity analysis process is provided using actual results from the Hanford Environmental Dose Reconstruction Integrated Codes (HEDRIC). This demonstration shows how the approaches used in the recommended plan can be adapted for all dose predictions in the HEDR Project
Sources of uncertainty in future changes in local precipitation
Energy Technology Data Exchange (ETDEWEB)
Rowell, David P. [Met Office Hadley Centre, Exeter (United Kingdom)
2012-10-15
This study considers the large uncertainty in projected changes in local precipitation. It aims to map, and begin to understand, the relative roles of uncertain modelling and natural variability, using 20-year mean data from four perturbed physics or multi-model ensembles. The largest - 280-member - ensemble illustrates a rich pattern in the varying contribution of modelling uncertainty, with similar features found using a CMIP3 ensemble (despite its limited sample size, which restricts it value in this context). The contribution of modelling uncertainty to the total uncertainty in local precipitation change is found to be highest in the deep tropics, particularly over South America, Africa, the east and central Pacific, and the Atlantic. In the moist maritime tropics, the highly uncertain modelling of sea-surface temperature changes is transmitted to a large uncertain modelling of local rainfall changes. Over tropical land and summer mid-latitude continents (and to a lesser extent, the tropical oceans), uncertain modelling of atmospheric processes, land surface processes and the terrestrial carbon cycle all appear to play an additional substantial role in driving the uncertainty of local rainfall changes. In polar regions, inter-model variability of anomalous sea ice drives an uncertain precipitation response, particularly in winter. In all these regions, there is therefore the potential to reduce the uncertainty of local precipitation changes through targeted model improvements and observational constraints. In contrast, over much of the arid subtropical and mid-latitude oceans, over Australia, and over the Sahara in winter, internal atmospheric variability dominates the uncertainty in projected precipitation changes. Here, model improvements and observational constraints will have little impact on the uncertainty of time means shorter than at least 20 years. Last, a supplementary application of the metric developed here is that it can be interpreted as a measure
Implications of nuclear data uncertainties to reactor design
International Nuclear Information System (INIS)
Greebler, P.; Hutchins, B.A.; Cowan, C.L.
1970-01-01
Uncertainties in nuclear data require significant allowances to be made in the design and the operating conditions of reactor cores and of shielded-reactor-plant and fuel-processing systems. These allowances result in direct cost increases due to overdesign of components and equipment and reduced core and fuel operating performance. Compromising the allowances for data uncertainties has indirect cost implications due to increased risks of failure to meet plant and fuel performance objectives, with warrantees involved in some cases, and to satisfy licensed safety requirements. Fast breeders are the most sensitive power reactors to the uncertainties in nuclear data over the neutron energy range of interest for fission reactors, and this paper focuses on the implications of the data uncertainties to design and operation of fast breeder reactors and fuel-processing systems. The current status of uncertainty in predicted physics parameters due to data uncertainties is reviewed and compared with the situation in 1966 and that projected for within the next two years due to anticipated data improvements. Implications of the uncertainties in the predicted physics parameters to design and operation are discussed for both a near-term prototype or demonstration breeder plant (∼300 MW(e)) and a longer-term large (∼1000 MW(e)) plant. Significant improvements in the nuclear data have been made during the past three years, the most important of these to fast power reactors being the 239 Pu alpha below 15 keV. The most important remaining specific data uncertainties are illustrated by their individual contributions to the computational uncertainty of selected physics parameters, and recommended priorities and accuracy requirements for improved data are presented
GENERAL RISKS AND UNCERTAINTIES OF REPORTING AND MANAGEMENT REPORTING RISKS
Directory of Open Access Journals (Sweden)
CAMELIA I. LUNGU
2011-04-01
Full Text Available Purpose: Highlighting risks and uncertainties reporting based on a literature review research. Objectives: The delimitation of risk management models and uncertainties in fundamental research. Research method: Fundamental research study directed to identify the relevant risks’ models presented in entities’ financial statements. Uncertainty is one of the fundamental coordinates of our world. As showed J.K. Galbraith (1978, the world now lives under the age of uncertainty. Moreover, we can say that contemporary society development could be achieved by taking decisions under uncertainty, though, risks. Growing concern for the study of uncertainty, its effects and precautions led to the rather recent emergence of a new science, science of hazards (les cindyniques - l.fr. (Kenvern, 1991. Current analysis of risk are dominated by Beck’s (1992 notion that a risk society now exists whereby we have become more concerned about our impact upon nature than the impact of nature upon us. Clearly, risk permeates most aspects of corporate but also of regular life decision-making and few can predict with any precision the future. The risk is almost always a major variable in real-world corporate decision-making, and managers that ignore it are in a real peril. In these circumstances, a possible answer is assuming financial discipline with an appropriate system of incentives.
Compilation of information on uncertainties involved in deposition modeling
International Nuclear Information System (INIS)
Lewellen, W.S.; Varma, A.K.; Sheng, Y.P.
1985-04-01
The current generation of dispersion models contains very simple parameterizations of deposition processes. The analysis here looks at the physical mechanisms governing these processes in an attempt to see if more valid parameterizations are available and what level of uncertainty is involved in either these simple parameterizations or any more advanced parameterization. The report is composed of three parts. The first, on dry deposition model sensitivity, provides an estimate of the uncertainty existing in current estimates of the deposition velocity due to uncertainties in independent variables such as meteorological stability, particle size, surface chemical reactivity and canopy structure. The range of uncertainty estimated for an appropriate dry deposition velocity for a plume generated by a nuclear power plant accident is three orders of magnitude. The second part discusses the uncertainties involved in precipitation scavenging rates for effluents resulting from a nuclear reactor accident. The conclusion is that major uncertainties are involved both as a result of the natural variability of the atmospheric precipitation process and due to our incomplete understanding of the underlying process. The third part involves a review of the important problems associated with modeling the interaction between the atmosphere and a forest. It gives an indication of the magnitude of the problem involved in modeling dry deposition in such environments. Separate analytics have been done for each section and are contained in the EDB
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
Tadini, A.; Bisson, M.; Neri, A.; Cioni, R.; Bevilacqua, A.; Aspinall, W. P.
2017-06-01
This study presents new and revised data sets about the spatial distribution of past volcanic vents, eruptive fissures, and regional/local structures of the Somma-Vesuvio volcanic system (Italy). The innovative features of the study are the identification and quantification of important sources of uncertainty affecting interpretations of the data sets. In this regard, the spatial uncertainty of each feature is modeled by an uncertainty area, i.e., a geometric element typically represented by a polygon drawn around points or lines. The new data sets have been assembled as an updatable geodatabase that integrates and complements existing databases for Somma-Vesuvio. The data are organized into 4 data sets and stored as 11 feature classes (points and lines for feature locations and polygons for the associated uncertainty areas), totaling more than 1700 elements. More specifically, volcanic vent and eruptive fissure elements are subdivided into feature classes according to their associated eruptive styles: (i) Plinian and sub-Plinian eruptions (i.e., large- or medium-scale explosive activity); (ii) violent Strombolian and continuous ash emission eruptions (i.e., small-scale explosive activity); and (iii) effusive eruptions (including eruptions from both parasitic vents and eruptive fissures). Regional and local structures (i.e., deep faults) are represented as linear feature classes. To support interpretation of the eruption data, additional data sets are provided for Somma-Vesuvio geological units and caldera morphological features. In the companion paper, the data presented here, and the associated uncertainties, are used to develop a first vent opening probability map for the Somma-Vesuvio caldera, with specific attention focused on large or medium explosive events.
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
Awe, uncertainty, and agency detection.
Valdesolo, Piercarlo; Graham, Jesse
2014-01-01
Across five studies, we found that awe increases both supernatural belief (Studies 1, 2, and 5) and intentional-pattern perception (Studies 3 and 4)-two phenomena that have been linked to agency detection, or the tendency to interpret events as the consequence of intentional and purpose-driven agents. Effects were both directly and conceptually replicated, and mediational analyses revealed that these effects were driven by the influence of awe on tolerance for uncertainty. Experiences of awe decreased tolerance for uncertainty, which, in turn, increased the tendency to believe in nonhuman agents and to perceive human agency in random events.
Linear Programming Problems for Generalized Uncertainty
Thipwiwatpotjana, Phantipa
2010-01-01
Uncertainty occurs when there is more than one realization that can represent an information. This dissertation concerns merely discrete realizations of an uncertainty. Different interpretations of an uncertainty and their relationships are addressed when the uncertainty is not a probability of each realization. A well known model that can handle…
Quantum logics with existence property
International Nuclear Information System (INIS)
Schindler, C.
1991-01-01
A quantum logic (σ-orthocomplete orthomodular poset L with a convex, unital, and separating set Δ of states) is said to have the existence property if the expectation functionals on lin(Δ) associated with the bounded observables of L form a vector space. Classical quantum logics as well as the Hilbert space logics of traditional quantum mechanics have this property. The author shows that, if a quantum logic satisfies certain conditions in addition to having property E, then the number of its blocks (maximal classical subsystems) must either be one (classical logics) or uncountable (as in Hilbert space logics)
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
Mendoza Beltran, A.; Heijungs, R.; Guinée, J.; Tukker, A.
2016-01-01
Purpose: Despite efforts to treat uncertainty due to methodological choices in life cycle assessment (LCA) such as standardization, one-at-a-time (OAT) sensitivity analysis, and analytical and statistical methods, no method exists that propagate this source of uncertainty for all relevant processes
Thibodeau, Michel A; Carleton, R Nicholas; McEvoy, Peter M; Zvolensky, Michael J; Brandt, Charles P; Boelen, Paul A; Mahoney, Alison E J; Deacon, Brett J; Asmundson, Gordon J G
Intolerance of uncertainty (IU) is a construct of growing prominence in literature on anxiety disorders and major depressive disorder. Existing measures of IU do not define the uncertainty that respondents perceive as distressing. To address this limitation, we developed eight scales measuring
Uncertainty, probability and information-gaps
International Nuclear Information System (INIS)
Ben-Haim, Yakov
2004-01-01
This paper discusses two main ideas. First, we focus on info-gap uncertainty, as distinct from probability. Info-gap theory is especially suited for modelling and managing uncertainty in system models: we invest all our knowledge in formulating the best possible model; this leaves the modeller with very faulty and fragmentary information about the variation of reality around that optimal model. Second, we examine the interdependence between uncertainty modelling and decision-making. Good uncertainty modelling requires contact with the end-use, namely, with the decision-making application of the uncertainty model. The most important avenue of uncertainty-propagation is from initial data- and model-uncertainties into uncertainty in the decision-domain. Two questions arise. Is the decision robust to the initial uncertainties? Is the decision prone to opportune windfall success? We apply info-gap robustness and opportunity functions to the analysis of representation and propagation of uncertainty in several of the Sandia Challenge Problems
Entropy Evolution and Uncertainty Estimation with Dynamical Systems
Directory of Open Access Journals (Sweden)
X. San Liang
2014-06-01
Full Text Available This paper presents a comprehensive introduction and systematic derivation of the evolutionary equations for absolute entropy H and relative entropy D, some of which exist sporadically in the literature in different forms under different subjects, within the framework of dynamical systems. In general, both H and D are dissipated, and the dissipation bears a form reminiscent of the Fisher information; in the absence of stochasticity, dH/dt is connected to the rate of phase space expansion, and D stays invariant, i.e., the separation of two probability density functions is always conserved. These formulas are validated with linear systems, and put to application with the Lorenz system and a large-dimensional stochastic quasi-geostrophic flow problem. In the Lorenz case, H falls at a constant rate with time, implying that H will eventually become negative, a situation beyond the capability of the commonly used computational technique like coarse-graining and bin counting. For the stochastic flow problem, it is first reduced to a computationally tractable low-dimensional system, using a reduced model approach, and then handled through ensemble prediction. Both the Lorenz system and the stochastic flow system are examples of self-organization in the light of uncertainty reduction. The latter particularly shows that, sometimes stochasticity may actually enhance the self-organization process.
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
Morton, Douglas C.; Sales, Marcio H.; Souza, Carlos M., Jr.; Griscom, Bronson
2011-01-01
Historic carbon emissions are an important foundation for proposed efforts to Reduce Emissions from Deforestation and forest Degradation and enhance forest carbon stocks through conservation and sustainable forest management (REDD+). The level of uncertainty in historic carbon emissions estimates is also critical for REDD+, since high uncertainties could limit climate benefits from mitigation actions. Here, we analyzed source data uncertainties based on the range of available deforestation, forest degradation, and forest carbon stock estimates for the Brazilian state of Mato Grosso during 1990-2008. Results: Deforestation estimates showed good agreement for multi-year trends of increasing and decreasing deforestation during the study period. However, annual deforestation rates differed by >20% in more than half of the years between 1997-2008, even for products based on similar input data. Tier 2 estimates of average forest carbon stocks varied between 99-192 Mg C/ha, with greatest differences in northwest Mato Grosso. Carbon stocks in deforested areas increased over the study period, yet this increasing trend in deforested biomass was smaller than the difference among carbon stock datasets for these areas. Conclusions: Patterns of spatial and temporal disagreement among available data products provide a roadmap for future efforts to reduce source data uncertainties for estimates of historic forest carbon emissions. Specifically, regions with large discrepancies in available estimates of both deforestation and forest carbon stocks are priority areas for evaluating and improving existing estimates. Full carbon accounting for REDD+ will also require filling data gaps, including forest degradation and secondary forest, with annual data on all forest transitions.
Evaluation of the uncertainty of environmental measurements of radioactivity
International Nuclear Information System (INIS)
Heydorn, K.
2003-01-01
Full text: The almost universal acceptance of the concept of uncertainty has led to its introduction into the ISO 17025 standard for general requirements to testing and calibration laboratories. This means that not only scientists, but also legislators, politicians, the general population - and perhaps even the press - expect to see all future results associated with an expression of their uncertainty. Results obtained by measurement of radioactivity have routinely been associated with an expression of their uncertainty, based on the so-called counting statistics. This is calculated together with the actual result on the assumption that the number of counts observed has a Poisson distribution with equal mean and variance. Most of the nuclear scientific community has therefore assumed that it already complied with the latest ISO 17025 requirements. Counting statistics, however, express only the variability observed among repeated measurements of the same sample under the same counting conditions, which is equivalent to the term repeatability used in quantitative analysis. Many other sources of uncertainty need to be taken into account before a statement of the uncertainty of the actual result can be made. As the first link in the traceability chain calibration is always an important uncertainty component in any kind of measurement. For radioactivity measurements in particular we find that counting geometry assumes the greatest importance, because it is often not possible to measure a standard and a control sample under exactly the same conditions. In the case of large samples we have additional uncertainty components associated with sample heterogeneity and its influence on self-absorption and counting efficiency. In low-level environmental measurements we have an additional risk of sample contamination, but the most important contribution to uncertainty is usually the representativity of the sample being analysed. For uniform materials this can be expressed by the
Uncertainty analysis of light water reactor unit fuel pin cells
Energy Technology Data Exchange (ETDEWEB)
Kamerow, S.; Ivanov, K., E-mail: sln107@PSU.EDU, E-mail: kni1@PSU.EDU [Department of Mechanical and Nuclear Engineering, The Pennsylvania State University, PA (United States); Moreno, C. Arenas, E-mail: cristina.arenas@UPC.EDU [Department of Physics and Nuclear Engineering, Technical University of Catalonia, Barcelona (Spain)
2011-07-01
The study explored the calculation of uncertainty based on available covariance data and computational tools. Uncertainty due to temperature changes and different fuel compositions are the main focus of this analysis. Selected unit fuel pin cells were analyzed according to the OECD LWR UAM benchmark specifications. Criticality and uncertainty analyses were performed using TSUNAMI-1D sequence in SCALE 6.0. It was found that uncertainties increase with increasing temperature while k{sub eff} decreases. This increase in the uncertainty is due to the increase in sensitivity of the largest contributor of uncertainty, namely nuclide reaction {sup 238}U (n, gamma). The sensitivity grew larger as the capture cross-section of {sup 238}U expanded due to Doppler broadening. In addition, three different compositions (UOx, MOx, and UOxGd{sub 2}O{sub 3}) of fuel cells were analyzed. It showed a remarkable increase in uncertainty in k{sub eff} for the case of the MOx fuel cell and UOxGd{sub 2}O{sub 3} fuel cell. The increase in the uncertainty of k{sub eff} in UOxGd{sub 2}O{sub 3} fuel was nearly twice of that in MOx fuel and almost four times the amount in UOx fuel. The components of the uncertainties in k{sub eff} in each case were examined and it was found that the neutron-nuclide reaction of {sup 238}U, mainly (n,n'), contributed the most to the uncertainties in the cases of MOx and UOxGd{sub 2}O{sub 3}. At higher energy, the covariance coefficient matrix of {sup 238}U (n,n') to {sup 238}U (n,n') and {sup 238}U (n,n') cross-section showed very large values. Further, examination of the UOxGd{sub 2}O{sub 3} case found that the {sup 238}U (n,n') became the dominant contributor to the uncertainty because most of the thermal neutrons in the cell were absorbed by Gadolinium in UOxGd{sub 2}O{sub 3} case and thus shifting the neutron spectrum to higher energy. For the MOx case on other hand, {sup 239}Pu has a very strong absorption cross-section at low energy
Water supply infrastructure planning under multiple uncertainties: A differentiated approach
Fletcher, S.; Strzepek, K.
2017-12-01
Many water planners face increased pressure on water supply systems from increasing demands from population and economic growth in combination with uncertain water supply. Supply uncertainty arises from short-term climate variability and long-term climate change as well as uncertainty in groundwater availability. Social and economic uncertainties - such as sectoral competition for water, food and energy security, urbanization, and environmental protection - compound physical uncertainty. Further, the varying risk aversion of stakeholders and water managers makes it difficult to assess the necessity of expensive infrastructure investments to reduce risk. We categorize these uncertainties on two dimensions: whether they can be updated over time by collecting additional information, and whether the uncertainties can be described probabilistically or are "deep" uncertainties whose likelihood is unknown. Based on this, we apply a decision framework that combines simulation for probabilistic uncertainty, scenario analysis for deep uncertainty, and multi-stage decision analysis for uncertainties that are reduced over time with additional information. In light of these uncertainties and the investment costs of large infrastructure, we propose the assessment of staged, modular infrastructure and information updating as a hedge against risk. We apply this framework to cases in Melbourne, Australia and Riyadh, Saudi Arabia. Melbourne is a surface water system facing uncertain population growth and variable rainfall and runoff. A severe drought from 1997 to 2009 prompted investment in a 150 MCM/y reverse osmosis desalination plan with a capital cost of 3.5 billion. Our analysis shows that flexible design in which a smaller portion of capacity is developed initially with the option to add modular capacity in the future can mitigate uncertainty and reduce the expected lifetime costs by up to 1 billion. In Riyadh, urban water use relies on fossil groundwater aquifers and
Chapter 3: Traceability and uncertainty
International Nuclear Information System (INIS)
McEwen, Malcolm
2014-01-01
Chapter 3 presents: an introduction; Traceability (measurement standard, role of the Bureau International des Poids et Mesures, Secondary Standards Laboratories, documentary standards and traceability as process review); Uncertainty (Example 1 - Measurement, M raw (SSD), Example 2 - Calibration data, N D.w 60 Co, kQ, Example 3 - Correction factor, P TP ) and Conclusion
Competitive Capacity Investment under Uncertainty
X. Li (Xishu); R.A. Zuidwijk (Rob); M.B.M. de Koster (René); R. Dekker (Rommert)
2016-01-01
textabstractWe consider a long-term capacity investment problem in a competitive market under demand uncertainty. Two firms move sequentially in the competition and a firm’s capacity decision interacts with the other firm’s current and future capacity. Throughout the investment race, a firm can
Uncertainty quantification and error analysis
Energy Technology Data Exchange (ETDEWEB)
Higdon, Dave M [Los Alamos National Laboratory; Anderson, Mark C [Los Alamos National Laboratory; Habib, Salman [Los Alamos National Laboratory; Klein, Richard [Los Alamos National Laboratory; Berliner, Mark [OHIO STATE UNIV.; Covey, Curt [LLNL; Ghattas, Omar [UNIV OF TEXAS; Graziani, Carlo [UNIV OF CHICAGO; Seager, Mark [LLNL; Sefcik, Joseph [LLNL; Stark, Philip [UC/BERKELEY; Stewart, James [SNL
2010-01-01
UQ studies all sources of error and uncertainty, including: systematic and stochastic measurement error; ignorance; limitations of theoretical models; limitations of numerical representations of those models; limitations on the accuracy and reliability of computations, approximations, and algorithms; and human error. A more precise definition for UQ is suggested below.
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
Numerical modeling of economic uncertainty
DEFF Research Database (Denmark)
Schjær-Jacobsen, Hans
2007-01-01
Representation and modeling of economic uncertainty is addressed by different modeling methods, namely stochastic variables and probabilities, interval analysis, and fuzzy numbers, in particular triple estimates. Focusing on discounted cash flow analysis numerical results are presented, comparisons...... are made between alternative modeling methods, and characteristics of the methods are discussed....
Uncertainty covariances in robotics applications
International Nuclear Information System (INIS)
Smith, D.L.
1984-01-01
The application of uncertainty covariance matrices in the analysis of robot trajectory errors is explored. First, relevant statistical concepts are reviewed briefly. Then, a simple, hypothetical robot model is considered to illustrate methods for error propagation and performance test data evaluation. The importance of including error correlations is emphasized
Regulating renewable resources under uncertainty
DEFF Research Database (Denmark)
Hansen, Lars Gårn
) that a pro-quota result under uncertainty about prices and marginal costs is unlikely, requiring that the resource growth function is highly concave locally around the optimum and, 3) that quotas are always preferred if uncertainly about underlying structural economic parameters dominates. These results...... showing that quotas are preferred in a number of situations qualify the pro fee message dominating prior studies....
Indian Academy of Sciences (India)
Home; Journals; Resonance – Journal of Science Education; Volume 4; Issue 2. Uncertainty in the Real World - Fuzzy Sets. Satish Kumar. General Article Volume 4 Issue 2 February 1999 pp 37-47. Fulltext. Click here to view fulltext PDF. Permanent link: https://www.ias.ac.in/article/fulltext/reso/004/02/0037-0047 ...
Uncertainty of dustfall monitoring results
Directory of Open Access Journals (Sweden)
Martin A. van Nierop
2017-06-01
Full Text Available Fugitive dust has the ability to cause a nuisance and pollute the ambient environment, particularly from human activities including construction and industrial sites and mining operations. As such, dustfall monitoring has occurred for many decades in South Africa; little has been published on the repeatability, uncertainty, accuracy and precision of dustfall monitoring. Repeatability assesses the consistency associated with the results of a particular measurement under the same conditions; the consistency of the laboratory is assessed to determine the uncertainty associated with dustfall monitoring conducted by the laboratory. The aim of this study was to improve the understanding of the uncertainty in dustfall monitoring; thereby improving the confidence in dustfall monitoring. Uncertainty of dustfall monitoring was assessed through a 12-month study of 12 sites that were located on the boundary of the study area. Each site contained a directional dustfall sampler, which was modified by removing the rotating lid, with four buckets (A, B, C and D installed. Having four buckets on one stand allows for each bucket to be exposed to the same conditions, for the same period of time; therefore, should have equal amounts of dust deposited in these buckets. The difference in the weight (mg of the dust recorded from each bucket at each respective site was determined using the American Society for Testing and Materials method D1739 (ASTM D1739. The variability of the dust would provide the confidence level of dustfall monitoring when reporting to clients.
Knowledge Uncertainty and Composed Classifier
Czech Academy of Sciences Publication Activity Database
Klimešová, Dana; Ocelíková, E.
2007-01-01
Roč. 1, č. 2 (2007), s. 101-105 ISSN 1998-0140 Institutional research plan: CEZ:AV0Z10750506 Keywords : Boosting architecture * contextual modelling * composed classifier * knowledge management, * knowledge * uncertainty Subject RIV: IN - Informatics, Computer Science
Uncertainty propagation in nuclear forensics
International Nuclear Information System (INIS)
Pommé, S.; Jerome, S.M.; Venchiarutti, C.
2014-01-01
Uncertainty propagation formulae are presented for age dating in support of nuclear forensics. The age of radioactive material in this context refers to the time elapsed since a particular radionuclide was chemically separated from its decay product(s). The decay of the parent radionuclide and ingrowth of the daughter nuclide are governed by statistical decay laws. Mathematical equations allow calculation of the age of specific nuclear material through the atom ratio between parent and daughter nuclides, or through the activity ratio provided that the daughter nuclide is also unstable. The derivation of the uncertainty formulae of the age may present some difficulty to the user community and so the exact solutions, some approximations, a graphical representation and their interpretation are presented in this work. Typical nuclides of interest are actinides in the context of non-proliferation commitments. The uncertainty analysis is applied to a set of important parent–daughter pairs and the need for more precise half-life data is examined. - Highlights: • Uncertainty propagation formulae for age dating with nuclear chronometers. • Applied to parent–daughter pairs used in nuclear forensics. • Investigated need for better half-life data
WASH-1400: quantifying the uncertainties
International Nuclear Information System (INIS)
Erdmann, R.C.; Leverenz, F.L. Jr.; Lellouche, G.S.
1981-01-01
The purpose of this paper is to focus on the limitations of the WASH-1400 analysis in estimating the risk from light water reactors (LWRs). This assessment attempts to modify the quantification of the uncertainty in and estimate of risk as presented by the RSS (reactor safety study). 8 refs
Model uncertainty in growth empirics
Prüfer, P.
2008-01-01
This thesis applies so-called Bayesian model averaging (BMA) to three different economic questions substantially exposed to model uncertainty. Chapter 2 addresses a major issue of modern development economics: the analysis of the determinants of pro-poor growth (PPG), which seeks to combine high
Charm quark mass with calibrated uncertainty
Energy Technology Data Exchange (ETDEWEB)
Erler, Jens [Universidad Nacional Autonoma de Mexico, Instituto de Fisica, Mexico, DF (Mexico); Masjuan, Pere [Universitat Autonoma de Barcelona, Grup de Fisica Teorica, Departament de Fisica, Barcelona (Spain); Institut de Fisica d' Altes Energies (IFAE), The Barcelona Institute of Science and Technology (BIST), Barcelona (Spain); Spiesberger, Hubert [Johannes Gutenberg-Universitaet, PRISMA Cluster of Excellence, Institut fuer Physik, Mainz (Germany); University of Cape Town, Centre for Theoretical and Mathematical Physics and Department of Physics, Rondebosch (South Africa)
2017-02-15
We determine the charm quark mass m{sub c} from QCD sum rules of the moments of the vector current correlator calculated in perturbative QCD at O(α{sub s}{sup 3}). Only experimental data for the charm resonances below the continuum threshold are needed in our approach, while the continuum contribution is determined by requiring self-consistency between various sum rules, including the one for the zeroth moment. Existing data from the continuum region can then be used to bound the theoretic uncertainty. Our result is m{sub c}(m{sub c}) = 1272 ± 8 MeV for α{sub s}(M{sub Z}) = 0.1182, where the central value is in very good agreement with other recent determinations based on the relativistic sum rule approach. On the other hand, there is considerably less agreement regarding the theory dominated uncertainty and we pay special attention to the question how to quantify and justify it. (orig.)