Benefits of using an optimization methodology for identifying robust process integration investments under uncertainty-A pulp mill example

Energy Technology Data Exchange (ETDEWEB)

Svensson, Elin [Department of Energy and Environment, Division of Heat and Power Technology, Chalmers University of Technology, SE-412 96 Goeteborg (Sweden)], E-mail: elin.svensson@chalmers.se; Berntsson, Thore [Department of Energy and Environment, Division of Heat and Power Technology, Chalmers University of Technology, SE-412 96 Goeteborg (Sweden); Stroemberg, Ann-Brith [Fraunhofer-Chalmers Research Centre for Industrial Mathematics, Chalmers Science Park, SE-412 88 Gothenburg (Sweden)

2009-03-15

This paper presents a case study on the optimization of process integration investments in a pulp mill considering uncertainties in future electricity and biofuel prices and CO{sub 2} emissions charges. The work follows the methodology described in Svensson et al. [Svensson, E., Berntsson, T., Stroemberg, A.-B., Patriksson, M., 2008b. An optimization methodology for identifying robust process integration investments under uncertainty. Energy Policy, in press, (doi:10.1016/j.enpol.2008.10.023)] where a scenario-based approach is proposed for the modelling of uncertainties. The results show that the proposed methodology provides a way to handle the time dependence and the uncertainties of the parameters. For the analyzed case, a robust solution is found which turns out to be a combination of two opposing investment strategies. The difference between short-term and strategic views for the investment decision is analyzed and it is found that uncertainties are increasingly important to account for as a more strategic view is employed. Furthermore, the results imply that the obvious effect of policy instruments aimed at decreasing CO{sub 2} emissions is, in applications like this, an increased profitability for all energy efficiency investments, and not as much a shift between different alternatives.

Benefits of using an optimization methodology for identifying robust process integration investments under uncertainty. A pulp mill example

Energy Technology Data Exchange (ETDEWEB)

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

2009-03-15

This paper presents a case study on the optimization of process integration investments in a pulp mill considering uncertainties in future electricity and biofuel prices and CO{sub 2} emissions charges. The work follows the methodology described in Svensson et al. [Svensson, E., Berntsson, T., Stroemberg, A.-B., Patriksson, M., 2008b. An optimization methodology for identifying robust process integration investments under uncertainty. Energy Policy, in press, doi:10.1016/j.enpol.2008.10.023] where a scenario-based approach is proposed for the modelling of uncertainties. The results show that the proposed methodology provides a way to handle the time dependence and the uncertainties of the parameters. For the analyzed case, a robust solution is found which turns out to be a combination of two opposing investment strategies. The difference between short-term and strategic views for the investment decision is analyzed and it is found that uncertainties are increasingly important to account for as a more strategic view is employed. Furthermore, the results imply that the obvious effect of policy instruments aimed at decreasing CO{sub 2} emissions is, in applications like this, an increased profitability for all energy efficiency investments, and not as much a shift between different alternatives. (author)

Benefits of using an optimization methodology for identifying robust process integration investments under uncertainty-A pulp mill example

International Nuclear Information System (INIS)

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

2009-01-01

This paper presents a case study on the optimization of process integration investments in a pulp mill considering uncertainties in future electricity and biofuel prices and CO 2 emissions charges. The work follows the methodology described in Svensson et al. [Svensson, E., Berntsson, T., Stroemberg, A.-B., Patriksson, M., 2008b. An optimization methodology for identifying robust process integration investments under uncertainty. Energy Policy, in press, (doi:10.1016/j.enpol.2008.10.023)] where a scenario-based approach is proposed for the modelling of uncertainties. The results show that the proposed methodology provides a way to handle the time dependence and the uncertainties of the parameters. For the analyzed case, a robust solution is found which turns out to be a combination of two opposing investment strategies. The difference between short-term and strategic views for the investment decision is analyzed and it is found that uncertainties are increasingly important to account for as a more strategic view is employed. Furthermore, the results imply that the obvious effect of policy instruments aimed at decreasing CO 2 emissions is, in applications like this, an increased profitability for all energy efficiency investments, and not as much a shift between different alternatives

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

The importance of input interactions in the uncertainty and sensitivity analysis of nuclear fuel behavior

Energy Technology Data Exchange (ETDEWEB)

Ikonen, T., E-mail: timo.ikonen@vtt.fi; Tulkki, V.

2014-08-15

Highlights: • Uncertainty and sensitivity analysis of modeled nuclear fuel behavior is performed. • Burnup dependency of the uncertainties and sensitivities is characterized. • Input interactions significantly increase output uncertainties for irradiated fuel. • Identification of uncertainty sources is greatly improved with higher order methods. • Results stress the importance of using methods that take interactions into account. - Abstract: The propagation of uncertainties in a PWR fuel rod under steady-state irradiation is analyzed by computational means. A hypothetical steady-state scenario of the Three Mile Island 1 reactor fuel rod is modeled with the fuel performance FRAPCON, using realistic input uncertainties for the fabrication and model parameters, boundary conditions and material properties. The uncertainty and sensitivity analysis is performed by extensive Monte Carlo sampling of the inputs’ probability distribution and by applying correlation coefficient and Sobol’ variance decomposition analyses. The latter includes evaluation of the second order and total effect sensitivity indices, allowing the study of interactions between input variables. The results show that the interactions play a large role in the propagation of uncertainties, and first order methods such as the correlation coefficient analyses are in general insufficient for sensitivity analysis of the fuel rod. Significant improvement over the first order methods can be achieved by using higher order methods. The results also show that both the magnitude of the uncertainties and their propagation depends not only on the output in question, but also on burnup. The latter is due to onset of new phenomena (such as the fission gas release) and the gradual closure of the pellet-cladding gap with increasing burnup. Increasing burnup also affects the importance of input interactions. Interaction effects are typically highest in the moderate burnup (of the order of 10–40 MWd

Uncertainty of Modal Parameters Estimated by ARMA Models

DEFF Research Database (Denmark)

Jensen, Jakob Laigaard; Brincker, Rune; Rytter, Anders

In this paper the uncertainties of identified modal parameters such as eigenfrequencies and damping ratios are assessed. From the measured response of dynamic excited structures the modal parameters may be identified and provide important structural knowledge. However the uncertainty of the param...

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)

An uncertainty inclusive un-mixing model to identify tracer non-conservativeness

Science.gov (United States)

Sherriff, Sophie; Rowan, John; Franks, Stewart; Fenton, Owen; Jordan, Phil; hUallacháin, Daire Ó.

2015-04-01

sensitive screening technique than assessing target values against source data. Non-conservative behaviour was identified in field data however only at a significant degree of corruption. Whilst further testing is required to determine the impact of individual and combined uncertainty components on synthetic, controlled experiments and field data, this study provides a framework for future assessment of uncertainty in un-mixing models.

Identifying the effects of parameter uncertainty on the reliability of riverbank stability modelling

Science.gov (United States)

Samadi, A.; Amiri-Tokaldany, E.; Darby, S. E.

2009-05-01

Bank retreat is a key process in fluvial dynamics affecting a wide range of physical, ecological and socioeconomic issues in the fluvial environment. To predict the undesirable effects of bank retreat and to inform effective measures to prevent it, a wide range of bank stability models have been presented in the literature. These models typically express bank stability by defining a factor of safety as the ratio of driving and resisting forces acting on the incipient failure block. These forces are affected by a range of controlling factors that include such aspects as the bank profile (bank height and angle), the geotechnical properties of the bank materials, as well as the hydrological status of the riverbanks. In this paper we evaluate the extent to which uncertainties in the parameterization of these controlling factors feed through to influence the reliability of the resulting bank stability estimate. This is achieved by employing a simple model of riverbank stability with respect to planar failure (which is the most common type of bank stability model) in a series of sensitivity tests and Monte Carlo analyses to identify, for each model parameter, the range of values that induce significant changes in the simulated factor of safety. These identified parameter value ranges are compared to empirically derived parameter uncertainties to determine whether they are likely to confound the reliability of the resulting bank stability calculations. Our results show that parameter uncertainties are typically high enough that the likelihood of generating unreliable predictions is typically very high (> ˜ 80% for predictions requiring a precision of < ± 15%). Because parameter uncertainties are derived primarily from the natural variability of the parameters, rather than measurement errors, much more careful attention should be paid to field sampling strategies, such that the parameter uncertainties and consequent prediction unreliabilities can be quantified more

Risk management of energy system for identifying optimal power mix with financial-cost minimization and environmental-impact mitigation under uncertainty

International Nuclear Information System (INIS)

Nie, S.; Li, Y.P.; Liu, J.; Huang, Charley Z.

2017-01-01

An interval-stochastic risk management (ISRM) method is launched to control the variability of the recourse cost as well as to capture the notion of risk in stochastic programming. The ISRM method can examine various policy scenarios that are associated with economic penalties under uncertainties presented as probability distributions and interval values. An ISRM model is then formulated to identify the optimal power mix for the Beijing's energy system. Tradeoffs between risk and cost are evaluated, indicating any change in targeted cost and risk level would yield different expected costs. Results reveal that the inherent uncertainty of system components and risk attitude of decision makers have significant effects on the city's energy-supply and electricity-generation schemes as well as system cost and probabilistic penalty. Results also disclose that import electricity as a recourse action to compensate the local shortage would be enforced. The import electricity would increase with a reduced risk level; under every risk level, more electricity would be imported with an increased demand. The findings can facilitate the local authority in identifying desired strategies for the city's energy planning and management in association with financial-cost minimization and environmental-impact mitigation. - Highlights: • Interval-stochastic risk management method is launched to identify optimal power mix. • It is advantageous in capturing the notion of risk in stochastic programming. • Results reveal that risk attitudes can affect optimal power mix and financial cost. • Developing renewable energies would enhance the sustainability of energy management. • Import electricity as an action to compensate the local shortage would be enforced.

Uncertainty importance analysis using parametric moment ratio functions.

Science.gov (United States)

Wei, Pengfei; Lu, Zhenzhou; Song, Jingwen

2014-02-01

This article presents a new importance analysis framework, called parametric moment ratio function, for measuring the reduction of model output uncertainty when the distribution parameters of inputs are changed, and the emphasis is put on the mean and variance ratio functions with respect to the variances of model inputs. The proposed concepts efficiently guide the analyst to achieve a targeted reduction on the model output mean and variance by operating on the variances of model inputs. The unbiased and progressive unbiased Monte Carlo estimators are also derived for the parametric mean and variance ratio functions, respectively. Only a set of samples is needed for implementing the proposed importance analysis by the proposed estimators, thus the computational cost is free of input dimensionality. An analytical test example with highly nonlinear behavior is introduced for illustrating the engineering significance of the proposed importance analysis technique and verifying the efficiency and convergence of the derived Monte Carlo estimators. Finally, the moment ratio function is applied to a planar 10-bar structure for achieving a targeted 50% reduction of the model output variance. © 2013 Society for Risk Analysis.

A bottom-up approach in estimating the measurement uncertainty and other important considerations for quantitative analyses in drug testing for horses.

Science.gov (United States)

Leung, Gary N W; Ho, Emmie N M; Kwok, W Him; Leung, David K K; Tang, Francis P W; Wan, Terence S M; Wong, April S Y; Wong, Colton H F; Wong, Jenny K Y; Yu, Nola H

2007-09-07

Quantitative determination, particularly for threshold substances in biological samples, is much more demanding than qualitative identification. A proper assessment of any quantitative determination is the measurement uncertainty (MU) associated with the determined value. The International Standard ISO/IEC 17025, "General requirements for the competence of testing and calibration laboratories", has more prescriptive requirements on the MU than its superseded document, ISO/IEC Guide 25. Under the 2005 or 1999 versions of the new standard, an estimation of the MU is mandatory for all quantitative determinations. To comply with the new requirement, a protocol was established in the authors' laboratory in 2001. The protocol has since evolved based on our practical experience, and a refined version was adopted in 2004. This paper describes our approach in establishing the MU, as well as some other important considerations, for the quantification of threshold substances in biological samples as applied in the area of doping control for horses. The testing of threshold substances can be viewed as a compliance test (or testing to a specified limit). As such, it should only be necessary to establish the MU at the threshold level. The steps in a "Bottom-Up" approach adopted by us are similar to those described in the EURACHEM/CITAC guide, "Quantifying Uncertainty in Analytical Measurement". They involve first specifying the measurand, including the relationship between the measurand and the input quantities upon which it depends. This is followed by identifying all applicable uncertainty contributions using a "cause and effect" diagram. The magnitude of each uncertainty component is then calculated and converted to a standard uncertainty. A recovery study is also conducted to determine if the method bias is significant and whether a recovery (or correction) factor needs to be applied. All standard uncertainties with values greater than 30% of the largest one are then used to

Characterizing Epistemic Uncertainty for Launch Vehicle Designs

Science.gov (United States)

Novack, Steven D.; Rogers, Jim; Hark, Frank; Al Hassan, Mohammad

2016-01-01

NASA Probabilistic Risk Assessment (PRA) has the task of estimating the aleatory (randomness) and epistemic (lack of knowledge) uncertainty of launch vehicle loss of mission and crew risk and communicating the results. Launch vehicles are complex engineered systems designed with sophisticated subsystems that are built to work together to accomplish mission success. Some of these systems or subsystems are in the form of heritage equipment, while some have never been previously launched. For these cases, characterizing the epistemic uncertainty is of foremost importance, and it is anticipated that the epistemic uncertainty of a modified launch vehicle design versus a design of well understood heritage equipment would be greater. For reasons that will be discussed, standard uncertainty propagation methods using Monte Carlo simulation produce counter intuitive results and significantly underestimate epistemic uncertainty for launch vehicle models. Furthermore, standard PRA methods such as Uncertainty-Importance analyses used to identify components that are significant contributors to uncertainty are rendered obsolete since sensitivity to uncertainty changes are not reflected in propagation of uncertainty using Monte Carlo methods.This paper provides a basis of the uncertainty underestimation for complex systems and especially, due to nuances of launch vehicle logic, for launch vehicles. It then suggests several alternative methods for estimating uncertainty and provides examples of estimation results. Lastly, the paper shows how to implement an Uncertainty-Importance analysis using one alternative approach, describes the results, and suggests ways to reduce epistemic uncertainty by focusing on additional data or testing of selected components.

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

International Nuclear Information System (INIS)

Lerche, I.; Noeth, S.

2002-01-01

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

Identifying uncertainty of the mean of some water quality variables along water quality monitoring network of Bahr El Baqar drain

Directory of Open Access Journals (Sweden)

Hussein G. Karaman

2013-10-01

Full Text Available Assigning objectives to the environmental monitoring network is the pillar of the design to these kinds of networks. Conflicting network objectives may affect the adequacy of the design in terms of sampling frequency and the spatial distribution of the monitoring stations which in turn affect the accuracy of the data and the information extracted. The first step in resolving this problem is to identify the uncertainty inherent in the network as the result of the vagueness of the design objective. Entropy has been utilized and adopted over the past decades to identify uncertainty in similar water data sets. Therefore it is used to identify the uncertainties inherent in the water quality monitoring network of Bahr El-Baqar drain located in the Eastern Delta. Toward investigating the applicability of the Entropy methodology, comprehensive analysis at the selected drain as well as their data sets is carried out. Furthermore, the uncertainty calculated by the entropy function will be presented by the means of the geographical information system to give the decision maker a global view to these uncertainties and to open the door to other researchers to find out innovative approaches to lower these uncertainties reaching optimal monitoring network in terms of the spatial distribution of the monitoring stations.

Small break LOCA RELAP5/MOD3 uncertainty quantification: Bias and uncertainty evaluation for important phenomena

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

Uncertainty of Modal Parameters Estimated by ARMA Models

DEFF Research Database (Denmark)

Jensen, Jacob Laigaard; Brincker, Rune; Rytter, Anders

1990-01-01

In this paper the uncertainties of identified modal parameters such as eidenfrequencies and damping ratios are assed. From the measured response of dynamic excited structures the modal parameters may be identified and provide important structural knowledge. However the uncertainty of the parameters...... by simulation study of a lightly damped single degree of freedom system. Identification by ARMA models has been choosen as system identification method. It is concluded that both the sampling interval and number of sampled points may play a significant role with respect to the statistical errors. Furthermore......, it is shown that the model errors may also contribute significantly to the uncertainty....

The estimation of uncertainty of radioactivity measurement on gamma counters in radiopharmacy

International Nuclear Information System (INIS)

Jovanovic, M.S.; Orlic, M.; Vranjes, S.; Stamenkovic, Lj. . E-mail address of corresponding author: nikijov@vin.bg.ac.yu; Jovanovic, M.S.)

2005-01-01

In this paper the estimation of uncertainty of measurement of radioactivity on gamma counter in Laboratory for radioisotopes is presented. The uncertainty components, which are important for these measurements, are identified and taken into account while estimating the uncertainty of measurement.(author)

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

International Nuclear Information System (INIS)

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

2014-01-01

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

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

Directory of Open Access Journals (Sweden)

Brzezicka Justyna

2014-07-01

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

An optimization methodology for identifying robust process integration investments under uncertainty

Energy Technology Data Exchange (ETDEWEB)

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

2009-02-15

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

An optimization methodology for identifying robust process integration investments under uncertainty

International Nuclear Information System (INIS)

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

2009-01-01

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

Measurement Uncertainty

Science.gov (United States)

Koch, Michael

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

Statistically based uncertainty analysis for ranking of component importance in the thermal-hydraulic safety analysis of the Advanced Neutron Source Reactor

International Nuclear Information System (INIS)

Wilson, G.E.

1992-01-01

The Analytic Hierarchy Process (AHP) has been used to help determine the importance of components and phenomena in thermal-hydraulic safety analyses of nuclear reactors. The AHP results are based, in part on expert opinion. Therefore, it is prudent to evaluate the uncertainty of the AHP ranks of importance. Prior applications have addressed uncertainty with experimental data comparisons and bounding sensitivity calculations. These methods work well when a sufficient experimental data base exists to justify the comparisons. However, in the case of limited or no experimental data the size of the uncertainty is normally made conservatively large. Accordingly, the author has taken another approach, that of performing a statistically based uncertainty analysis. The new work is based on prior evaluations of the importance of components and phenomena in the thermal-hydraulic safety analysis of the Advanced Neutron Source Reactor (ANSR), a new facility now in the design phase. The uncertainty during large break loss of coolant, and decay heat removal scenarios is estimated by assigning a probability distribution function (pdf) to the potential error in the initial expert estimates of pair-wise importance between the components. Using a Monte Carlo sampling technique, the error pdfs are propagated through the AHP software solutions to determine a pdf of uncertainty in the system wide importance of each component. To enhance the generality of the results, study of one other problem having different number of elements is reported, as are the effects of a larger assumed pdf error in the expert ranks. Validation of the Monte Carlo sample size and repeatability are also documented

A practical sensitivity analysis method for ranking sources of uncertainty in thermal–hydraulics applications

Energy Technology Data Exchange (ETDEWEB)

Pourgol-Mohammad, Mohammad, E-mail: pourgolmohammad@sut.ac.ir [Department of Mechanical Engineering, Sahand University of Technology, Tabriz (Iran, Islamic Republic of); Hoseyni, Seyed Mohsen [Department of Basic Sciences, East Tehran Branch, Islamic Azad University, Tehran (Iran, Islamic Republic of); Hoseyni, Seyed Mojtaba [Building & Housing Research Center, Tehran (Iran, Islamic Republic of); Sepanloo, Kamran [Nuclear Science and Technology Research Institute, Tehran (Iran, Islamic Republic of)

2016-08-15

Highlights: • Existing uncertainty ranking methods prove inconsistent for TH applications. • Introduction of a new method for ranking sources of uncertainty in TH codes. • Modified PIRT qualitatively identifies and ranks uncertainty sources more precisely. • The importance of parameters is calculated by a limited number of TH code executions. • Methodology is applied successfully on LOFT-LB1 test facility. - Abstract: In application to thermal–hydraulic calculations by system codes, sensitivity analysis plays an important role for managing the uncertainties of code output and risk analysis. Sensitivity analysis is also used to confirm the results of qualitative Phenomena Identification and Ranking Table (PIRT). Several methodologies have been developed to address uncertainty importance assessment. Generally, uncertainty importance measures, mainly devised for the Probabilistic Risk Assessment (PRA) applications, are not affordable for computationally demanding calculations of the complex thermal–hydraulics (TH) system codes. In other words, for effective quantification of the degree of the contribution of each phenomenon to the total uncertainty of the output, a practical approach is needed by considering high computational burden of TH calculations. This study aims primarily to show the inefficiency of the existing approaches and then introduces a solution to cope with the challenges in this area by modification of variance-based uncertainty importance method. Important parameters are identified by the modified PIRT approach qualitatively then their uncertainty importance is quantified by a local derivative index. The proposed index is attractive from its practicality point of view on TH applications. It is capable of calculating the importance of parameters by a limited number of TH code executions. Application of the proposed methodology is demonstrated on LOFT-LB1 test facility.

A practical sensitivity analysis method for ranking sources of uncertainty in thermal–hydraulics applications

International Nuclear Information System (INIS)

Pourgol-Mohammad, Mohammad; Hoseyni, Seyed Mohsen; Hoseyni, Seyed Mojtaba; Sepanloo, Kamran

2016-01-01

Highlights: • Existing uncertainty ranking methods prove inconsistent for TH applications. • Introduction of a new method for ranking sources of uncertainty in TH codes. • Modified PIRT qualitatively identifies and ranks uncertainty sources more precisely. • The importance of parameters is calculated by a limited number of TH code executions. • Methodology is applied successfully on LOFT-LB1 test facility. - Abstract: In application to thermal–hydraulic calculations by system codes, sensitivity analysis plays an important role for managing the uncertainties of code output and risk analysis. Sensitivity analysis is also used to confirm the results of qualitative Phenomena Identification and Ranking Table (PIRT). Several methodologies have been developed to address uncertainty importance assessment. Generally, uncertainty importance measures, mainly devised for the Probabilistic Risk Assessment (PRA) applications, are not affordable for computationally demanding calculations of the complex thermal–hydraulics (TH) system codes. In other words, for effective quantification of the degree of the contribution of each phenomenon to the total uncertainty of the output, a practical approach is needed by considering high computational burden of TH calculations. This study aims primarily to show the inefficiency of the existing approaches and then introduces a solution to cope with the challenges in this area by modification of variance-based uncertainty importance method. Important parameters are identified by the modified PIRT approach qualitatively then their uncertainty importance is quantified by a local derivative index. The proposed index is attractive from its practicality point of view on TH applications. It is capable of calculating the importance of parameters by a limited number of TH code executions. Application of the proposed methodology is demonstrated on LOFT-LB1 test facility.

Uncertainty estimation of ultrasonic thickness measurement

International Nuclear Information System (INIS)

Yassir Yassen, Abdul Razak Daud; Mohammad Pauzi Ismail; Abdul Aziz Jemain

2009-01-01

The most important factor that should be taken into consideration when selecting ultrasonic thickness measurement technique is its reliability. Only when the uncertainty of a measurement results is known, it may be judged if the result is adequate for intended purpose. The objective of this study is to model the ultrasonic thickness measurement function, to identify the most contributing input uncertainty components, and to estimate the uncertainty of the ultrasonic thickness measurement results. We assumed that there are five error sources significantly contribute to the final error, these sources are calibration velocity, transit time, zero offset, measurement repeatability and resolution, by applying the propagation of uncertainty law to the model function, a combined uncertainty of the ultrasonic thickness measurement was obtained. In this study the modeling function of ultrasonic thickness measurement was derived. By using this model the estimation of the uncertainty of the final output result was found to be reliable. It was also found that the most contributing input uncertainty components are calibration velocity, transit time linearity and zero offset. (author)

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)

CEC/USDOE workshop on uncertainty analysis

International Nuclear Information System (INIS)

Elderkin, C.E.; Kelly, G.N.

1990-07-01

Any measured or assessed quantity contains uncertainty. The quantitative estimation of such uncertainty is becoming increasingly important, especially in assuring that safety requirements are met in design, regulation, and operation of nuclear installations. The CEC/USDOE Workshop on Uncertainty Analysis, held in Santa Fe, New Mexico, on November 13 through 16, 1989, was organized jointly by the Commission of European Communities (CEC's) Radiation Protection Research program, dealing with uncertainties throughout the field of consequence assessment, and DOE's Atmospheric Studies in Complex Terrain (ASCOT) program, concerned with the particular uncertainties in time and space variant transport and dispersion. The workshop brought together US and European scientists who have been developing or applying uncertainty analysis methodologies, conducted in a variety of contexts, often with incomplete knowledge of the work of others in this area. Thus, it was timely to exchange views and experience, identify limitations of approaches to uncertainty and possible improvements, and enhance the interface between developers and users of uncertainty analysis methods. Furthermore, the workshop considered the extent to which consistent, rigorous methods could be used in various applications within consequence assessment. 3 refs

Addressing uncertainty in adaptation planning for agriculture.

Science.gov (United States)

Vermeulen, Sonja J; Challinor, Andrew J; Thornton, Philip K; Campbell, Bruce M; Eriyagama, Nishadi; Vervoort, Joost M; Kinyangi, James; Jarvis, Andy; Läderach, Peter; Ramirez-Villegas, Julian; Nicklin, Kathryn J; Hawkins, Ed; Smith, Daniel R

2013-05-21

We present a framework for prioritizing adaptation approaches at a range of timeframes. The framework is illustrated by four case studies from developing countries, each with associated characterization of uncertainty. Two cases on near-term adaptation planning in Sri Lanka and on stakeholder scenario exercises in East Africa show how the relative utility of capacity vs. impact approaches to adaptation planning differ with level of uncertainty and associated lead time. An additional two cases demonstrate that it is possible to identify uncertainties that are relevant to decision making in specific timeframes and circumstances. The case on coffee in Latin America identifies altitudinal thresholds at which incremental vs. transformative adaptation pathways are robust options. The final case uses three crop-climate simulation studies to demonstrate how uncertainty can be characterized at different time horizons to discriminate where robust adaptation options are possible. We find that impact approaches, which use predictive models, are increasingly useful over longer lead times and at higher levels of greenhouse gas emissions. We also find that extreme events are important in determining predictability across a broad range of timescales. The results demonstrate the potential for robust knowledge and actions in the face of uncertainty.

Identifying Importance-Performance Matrix Analysis (IPMA) of ...

African Journals Online (AJOL)

Identifying Importance-Performance Matrix Analysis (IPMA) of intellectual capital and Islamic work ethics in Malaysian SMES. ... capital and Islamic work ethics significantly influenced business performance. ... AJOL African Journals Online.

A Unified Approach for Reporting ARM Measurement Uncertainties Technical Report

Energy Technology Data Exchange (ETDEWEB)

Campos, E [Argonne National Lab. (ANL), Argonne, IL (United States); Sisterson, Douglas [Argonne National Lab. (ANL), Argonne, IL (United States)

2016-12-01

The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility is observationally based, and quantifying the uncertainty of its measurements is critically important. With over 300 widely differing instruments providing over 2,500 datastreams, concise expression of measurement uncertainty is quite challenging. The ARM Facility currently provides data and supporting metadata (information about the data or data quality) to its users through a number of sources. Because the continued success of the ARM Facility depends on the known quality of its measurements, the Facility relies on instrument mentors and the ARM Data Quality Office (DQO) to ensure, assess, and report measurement quality. Therefore, an easily accessible, well-articulated estimate of ARM measurement uncertainty is needed. Note that some of the instrument observations require mathematical algorithms (retrievals) to convert a measured engineering variable into a useful geophysical measurement. While those types of retrieval measurements are identified, this study does not address particular methods for retrieval uncertainty. As well, the ARM Facility also provides engineered data products, or value-added products (VAPs), based on multiple instrument measurements. This study does not include uncertainty estimates for those data products. We propose here that a total measurement uncertainty should be calculated as a function of the instrument uncertainty (calibration factors), the field uncertainty (environmental factors), and the retrieval uncertainty (algorithm factors). The study will not expand on methods for computing these uncertainties. Instead, it will focus on the practical identification, characterization, and inventory of the measurement uncertainties already available in the ARM community through the ARM instrument mentors and their ARM instrument handbooks. As a result, this study will address the first steps towards reporting ARM measurement uncertainty

Mind Your Product-Market Strategy on Selecting Marketing Inputs: An Uncertainty Approach in Indian Context

OpenAIRE

Susmita Ghosh; Bhaskar Bhowmick

2015-01-01

Market is an important factor for start-ups to look into during decision-making in product development and related areas. Emerging country markets are more uncertain in terms of information availability and institutional supports. The literature review of market uncertainty reveals the need for identifying factors representing the market uncertainty. This paper identifies factors for market uncertainty using Exploratory Factor Analysis (EFA) and confirmed the number of fa...

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

Modified Phenomena Identification and Ranking Table (PIRT) for Uncertainty Analysis

International Nuclear Information System (INIS)

Gol-Mohamad, Mohammad P.; Modarres, Mohammad; Mosleh, Ali

2006-01-01

This paper describes a methodology of characterizing important phenomena, which is also part of a broader research by the authors called 'Modified PIRT'. The methodology provides robust process of phenomena identification and ranking process for more precise quantification of uncertainty. It is a two-step process of identifying and ranking methodology based on thermal-hydraulics (TH) importance as well as uncertainty importance. Analytical Hierarchical Process (AHP) has been used for as a formal approach for TH identification and ranking. Formal uncertainty importance technique is used to estimate the degree of credibility of the TH model(s) used to represent the important phenomena. This part uses subjective justification by evaluating available information and data from experiments, and code predictions. The proposed methodology was demonstrated by developing a PIRT for large break loss of coolant accident LBLOCA for the LOFT integral facility with highest core power (test LB-1). (authors)

Recognizing and responding to uncertainty: a grounded theory of nurses' uncertainty.

Science.gov (United States)

Cranley, Lisa A; Doran, Diane M; Tourangeau, Ann E; Kushniruk, Andre; Nagle, Lynn

2012-08-01

There has been little research to date exploring nurses' uncertainty in their practice. Understanding nurses' uncertainty is important because it has potential implications for how care is delivered. The purpose of this study is to develop a substantive theory to explain how staff nurses experience and respond to uncertainty in their practice. Between 2006 and 2008, a grounded theory study was conducted that included in-depth semi-structured interviews. Fourteen staff nurses working in adult medical-surgical intensive care units at two teaching hospitals in Ontario, Canada, participated in the study. The theory recognizing and responding to uncertainty characterizes the processes through which nurses' uncertainty manifested and how it was managed. Recognizing uncertainty involved the processes of assessing, reflecting, questioning, and/or being unable to predict aspects of the patient situation. Nurses' responses to uncertainty highlighted the cognitive-affective strategies used to manage uncertainty. Study findings highlight the importance of acknowledging uncertainty and having collegial support to manage uncertainty. The theory adds to our understanding the processes involved in recognizing uncertainty, strategies and outcomes of managing uncertainty, and influencing factors. Tailored nursing education programs should be developed to assist nurses in developing skills in articulating and managing their uncertainty. Further research is needed to extend, test and refine the theory of recognizing and responding to uncertainty to develop strategies for managing uncertainty. This theory advances the nursing perspective of uncertainty in clinical practice. The theory is relevant to nurses who are faced with uncertainty and complex clinical decisions, to managers who support nurses in their clinical decision-making, and to researchers who investigate ways to improve decision-making and care delivery. ©2012 Sigma Theta Tau International.

Uncertainty analysis of energy consumption in dwellings

Energy Technology Data Exchange (ETDEWEB)

Pettersen, Trine Dyrstad

1997-12-31

This thesis presents a comprehensive study of an energy estimation model that can be used to examine the uncertainty of predicted energy consumption in a dwelling. The variation and uncertainty of input parameters due to the outdoor climate, the building construction and the inhabitants are studied as a basis for further energy evaluations. The occurring variations of energy consumption in nominal similar dwellings are also investigated due to verification of the simulated energy consumption. The main topics are (1) a study of expected variations and uncertainties in both input parameters used in energy consumption calculations and the energy consumption in the dwelling, (2) the development and evaluation of a simplified energy calculation model that considers uncertainties due to the input parameters, (3) an evaluation of the influence of the uncertain parameters on the total variation so that the most important parameters can be identified, and (4) the recommendation of a simplified procedure for treating uncertainties or possible deviations from average conditions. 90 refs., 182 figs., 73 tabs.

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)

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

International Nuclear Information System (INIS)

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

1992-06-01

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

Estimation of uncertainty in pKa values determined by potentiometric titration.

Science.gov (United States)

Koort, Eve; Herodes, Koit; Pihl, Viljar; Leito, Ivo

2004-06-01

A procedure is presented for estimation of uncertainty in measurement of the pK(a) of a weak acid by potentiometric titration. The procedure is based on the ISO GUM. The core of the procedure is a mathematical model that involves 40 input parameters. A novel approach is used for taking into account the purity of the acid, the impurities are not treated as inert compounds only, their possible acidic dissociation is also taken into account. Application to an example of practical pK(a) determination is presented. Altogether 67 different sources of uncertainty are identified and quantified within the example. The relative importance of different uncertainty sources is discussed. The most important source of uncertainty (with the experimental set-up of the example) is the uncertainty of pH measurement followed by the accuracy of the burette and the uncertainty of weighing. The procedure gives uncertainty separately for each point of the titration curve. The uncertainty depends on the amount of titrant added, being lowest in the central part of the titration curve. The possibilities of reducing the uncertainty and interpreting the drift of the pK(a) values obtained from the same curve are discussed.

Importance of atmospheric turbidity and associated uncertainties in solar radiation and luminous efficacy modelling

International Nuclear Information System (INIS)

Gueymard, Christian A.

2005-01-01

For many solar-related applications, it is important to separately predict the direct and diffuse components of irradiance or illuminance. Under clear skies, turbidity plays a determinant role in quantitatively affecting these components. In this paper, various aspects of the effect of turbidity on both spectral and broadband radiation are addressed, as well as the uncertainty in irradiance predictions due to inaccurate turbidity data, and the current improvements in obtaining the necessary turbidity data

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

Neural Correlates of Intolerance of Uncertainty in Clinical Disorders.

Science.gov (United States)

Wever, Mirjam; Smeets, Paul; Sternheim, Lot

2015-01-01

Intolerance of uncertainty is a key contributor to anxiety-related disorders. Recent studies highlight its importance in other clinical disorders. The link between its clinical presentation and the underlying neural correlates remains unclear. This review summarizes the emerging literature on the neural correlates of intolerance of uncertainty. In conclusion, studies focusing on the neural correlates of this construct are sparse, and findings are inconsistent across disorders. Future research should identify neural correlates of intolerance of uncertainty in more detail. This may unravel the neurobiology of a wide variety of clinical disorders and pave the way for novel therapeutic targets.

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...

A new importance measure for sensitivity analysis

International Nuclear Information System (INIS)

Liu, Qiao; Homma, Toshimitsu

2010-01-01

Uncertainty is an integral part of risk assessment of complex engineering systems, such as nuclear power plants and space crafts. The aim of sensitivity analysis is to identify the contribution of the uncertainty in model inputs to the uncertainty in the model output. In this study, a new importance measure that characterizes the influence of the entire input distribution on the entire output distribution was proposed. It represents the expected deviation of the cumulative distribution function (CDF) of the model output that would be obtained when one input parameter of interest were known. The applicability of this importance measure was tested with two models, a nonlinear nonmonotonic mathematical model and a risk model. In addition, a comparison of this new importance measure with several other importance measures was carried out and the differences between these measures were explained. (author)

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

Uncertainty related to Environmental Data and Estimated Extreme Events

DEFF Research Database (Denmark)

Burcharth, H. F.

The design loads on rubble mound breakwaters are almost entirely determined by the environmental conditions, i.e. sea state, water levels, sea bed characteristics, etc. It is the objective of sub-group B to identify the most important environmental parameters and evaluate the related uncertainties...... including those corresponding to extreme estimates typically used for design purposes. Basically a design condition is made up of a set of parameter values stemming from several environmental parameters. To be able to evaluate the uncertainty related to design states one must know the corresponding joint....... Consequently this report deals mainly with each parameter separately. Multi parameter problems are briefly discussed in section 9. It is important to notice that the quantified uncertainties reported in section 7.7 represent what might be regarded as typical figures to be used only when no more qualified...

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)

Peer review of HEDR uncertainty and sensitivity analyses plan

Energy Technology Data Exchange (ETDEWEB)

Hoffman, F.O.

1993-06-01

This report consists of a detailed documentation of the writings and deliberations of the peer review panel that met on May 24--25, 1993 in Richland, Washington to evaluate your draft report ``Uncertainty/Sensitivity Analysis Plan`` (PNWD-2124 HEDR). The fact that uncertainties are being considered in temporally and spatially varying parameters through the use of alternative time histories and spatial patterns deserves special commendation. It is important to identify early those model components and parameters that will have the most influence on the magnitude and uncertainty of the dose estimates. These are the items that should be investigated most intensively prior to committing to a final set of results.

Estimating the measurement uncertainty in forensic blood alcohol analysis.

Science.gov (United States)

Gullberg, Rod G

2012-04-01

For many reasons, forensic toxicologists are being asked to determine and report their measurement uncertainty in blood alcohol analysis. While understood conceptually, the elements and computations involved in determining measurement uncertainty are generally foreign to most forensic toxicologists. Several established and well-documented methods are available to determine and report the uncertainty in blood alcohol measurement. A straightforward bottom-up approach is presented that includes: (1) specifying the measurand, (2) identifying the major components of uncertainty, (3) quantifying the components, (4) statistically combining the components and (5) reporting the results. A hypothetical example is presented that employs reasonable estimates for forensic blood alcohol analysis assuming headspace gas chromatography. These computations are easily employed in spreadsheet programs as well. Determining and reporting measurement uncertainty is an important element in establishing fitness-for-purpose. Indeed, the demand for such computations and information from the forensic toxicologist will continue to increase.

Ocean Heat and Carbon Uptake in Transient Climate Change: Identifying Model Uncertainty

Science.gov (United States)

Romanou, Anastasia; Marshall, John

2015-01-01

Global warming on decadal and centennial timescales is mediated and ameliorated by the oceansequestering heat and carbon into its interior. Transient climate change is a function of the efficiency by whichanthropogenic heat and carbon are transported away from the surface into the ocean interior (Hansen et al. 1985).Gregory and Mitchell (1997) and Raper et al. (2002) were the first to identify the importance of the ocean heat uptakeefficiency in transient climate change. Observational estimates (Schwartz 2012) and inferences from coupledatmosphere-ocean general circulation models (AOGCMs; Gregory and Forster 2008; Marotzke et al. 2015), suggest thatocean heat uptake efficiency on decadal timescales lies in the range 0.5-1.5 W/sq m/K and is thus comparable to theclimate feedback parameter (Murphy et al. 2009). Moreover, the ocean not only plays a key role in setting the timing ofwarming but also its regional patterns (Marshall et al. 2014), which is crucial to our understanding of regional climate,carbon and heat uptake, and sea-level change. This short communication is based on a presentation given by A.Romanou at a recent workshop, Oceans Carbon and Heat Uptake: Uncertainties and Metrics, co-hosted by US CLIVARand OCB. As briefly reviewed below, we have incomplete but growing knowledge of how ocean models used in climatechange projections sequester heat and carbon into the interior. To understand and thence reduce errors and biases inthe ocean component of coupled models, as well as elucidate the key mechanisms at work, in the final section we outlinea proposed model intercomparison project named FAFMIP. In FAFMIP, coupled integrations would be carried out withprescribed overrides of wind stress and freshwater and heat fluxes acting at the sea surface.

Uncertainty and global climate change research

Energy Technology Data Exchange (ETDEWEB)

Tonn, B.E. [Oak Ridge National Lab., TN (United States); Weiher, R. [National Oceanic and Atmospheric Administration, Boulder, CO (United States)

1994-06-01

The Workshop on Uncertainty and Global Climate Change Research March 22--23, 1994, in Knoxville, Tennessee. This report summarizes the results and recommendations of the workshop. The purpose of the workshop was to examine in-depth the concept of uncertainty. From an analytical point of view, uncertainty is a central feature of global climate science, economics and decision making. The magnitude and complexity of uncertainty surrounding global climate change has made it quite difficult to answer even the most simple and important of questions-whether potentially costly action is required now to ameliorate adverse consequences of global climate change or whether delay is warranted to gain better information to reduce uncertainties. A major conclusion of the workshop is that multidisciplinary integrated assessments using decision analytic techniques as a foundation is key to addressing global change policy concerns. First, uncertainty must be dealt with explicitly and rigorously since it is and will continue to be a key feature of analysis and recommendations on policy questions for years to come. Second, key policy questions and variables need to be explicitly identified, prioritized, and their uncertainty characterized to guide the entire scientific, modeling, and policy analysis process. Multidisciplinary integrated assessment techniques and value of information methodologies are best suited for this task. In terms of timeliness and relevance of developing and applying decision analytic techniques, the global change research and policy communities are moving rapidly toward integrated approaches to research design and policy analysis.

The uncertainty of reference standards--a guide to understanding factors impacting uncertainty, uncertainty calculations, and vendor certifications.

Science.gov (United States)

Gates, Kevin; Chang, Ning; Dilek, Isil; Jian, Huahua; Pogue, Sherri; Sreenivasan, Uma

2009-10-01

Certified solution standards are widely used in forensic toxicological, clinical/diagnostic, and environmental testing. Typically, these standards are purchased as ampouled solutions with a certified concentration. Vendors present concentration and uncertainty differently on their Certificates of Analysis. Understanding the factors that impact uncertainty and which factors have been considered in the vendor's assignment of uncertainty are critical to understanding the accuracy of the standard and the impact on testing results. Understanding these variables is also important for laboratories seeking to comply with ISO/IEC 17025 requirements and for those preparing reference solutions from neat materials at the bench. The impact of uncertainty associated with the neat material purity (including residual water, residual solvent, and inorganic content), mass measurement (weighing techniques), and solvent addition (solution density) on the overall uncertainty of the certified concentration is described along with uncertainty calculations.

Moving Beyond 2% Uncertainty: A New Framework for Quantifying Lidar Uncertainty

Energy Technology Data Exchange (ETDEWEB)

Newman, Jennifer F.; Clifton, Andrew

2017-03-08

Remote sensing of wind using lidar is revolutionizing wind energy. However, current generations of wind lidar are ascribed a climatic value of uncertainty, which is based on a poor description of lidar sensitivity to external conditions. In this presentation, we show how it is important to consider the complete lidar measurement process to define the measurement uncertainty, which in turn offers the ability to define a much more granular and dynamic measurement uncertainty. This approach is a progression from the 'white box' lidar uncertainty method.

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)

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

International Nuclear Information System (INIS)

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

1994-12-01

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

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

Development of Property Models with Uncertainty Estimate for Process Design under Uncertainty

DEFF Research Database (Denmark)

Hukkerikar, Amol; Sarup, Bent; Abildskov, Jens

more reliable predictions with a new and improved set of model parameters for GC (group contribution) based and CI (atom connectivity index) based models and to quantify the uncertainties in the estimated property values from a process design point-of-view. This includes: (i) parameter estimation using....... The comparison of model prediction uncertainties with reported range of measurement uncertainties is presented for the properties with related available data. The application of the developed methodology to quantify the effect of these uncertainties on the design of different unit operations (distillation column......, the developed methodology can be used to quantify the sensitivity of process design to uncertainties in property estimates; obtain rationally the risk/safety factors in process design; and identify additional experimentation needs in order to reduce most critical uncertainties....

Parameter Uncertainty for Repository Thermal Analysis

Energy Technology Data Exchange (ETDEWEB)

Hardin, Ernest [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hadgu, Teklu [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Greenberg, Harris [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Dupont, Mark [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL)

2015-10-01

This report is one follow-on to a study of reference geologic disposal design concepts (Hardin et al. 2011a). Based on an analysis of maximum temperatures, that study concluded that certain disposal concepts would require extended decay storage prior to emplacement, or the use of small waste packages, or both. The study used nominal values for thermal properties of host geologic media and engineered materials, demonstrating the need for uncertainty analysis to support the conclusions. This report is a first step that identifies the input parameters of the maximum temperature calculation, surveys published data on measured values, uses an analytical approach to determine which parameters are most important, and performs an example sensitivity analysis. Using results from this first step, temperature calculations planned for FY12 can focus on only the important parameters, and can use the uncertainty ranges reported here. The survey of published information on thermal properties of geologic media and engineered materials, is intended to be sufficient for use in generic calculations to evaluate the feasibility of reference disposal concepts. A full compendium of literature data is beyond the scope of this report. The term “uncertainty” is used here to represent both measurement uncertainty and spatial variability, or variability across host geologic units. For the most important parameters (e.g., buffer thermal conductivity) the extent of literature data surveyed samples these different forms of uncertainty and variability. Finally, this report is intended to be one chapter or section of a larger FY12 deliverable summarizing all the work on design concepts and thermal load management for geologic disposal (M3FT-12SN0804032, due 15Aug2012).

Uncertainty and sensitivity studies supporting the interpretation of the results of TVO I/II PRA

International Nuclear Information System (INIS)

Holmberg, J.

1992-01-01

A comprehensive Level 1 probabilistic risk assessment (PRA) has been performed for the TVO I/II nuclear power units. As a part of the PRA project, uncertainties of risk models and methods were systematically studied in order to describe them and to demonstrate their impact by way of results. The uncertainty study was divided into two phases: a qualitative and a quantitative study. The qualitative study contained identification of uncertainties and qualitative assessments of their importance. The PRA was introduced, and identified assumptions and uncertainties behind the models were documented. The most significant uncertainties were selected by importance measures or other judgements for further quantitative studies. The quantitative study included sensitivity studies and propagation of uncertainty ranges. In the sensitivity studies uncertain assumptions or parameters were varied in order to illustrate the sensitivity of the models. The propagation of the uncertainty ranges demonstrated the impact of the statistical uncertainties of the parameter values. The Monte Carlo method was used as a propagation method. The most significant uncertainties were those involved in modelling human interactions, dependences and common cause failures (CCFs), loss of coolant accident (LOCA) frequencies and pressure suppression. The qualitative mapping out of the uncertainty factors turned out to be useful in planning quantitative studies. It also served as internal review of the assumptions made in the PRA. The sensitivity studies were perhaps the most advantageous part of the quantitative study because they allowed individual analyses of the significance of uncertainty sources identified. The uncertainty study was found reasonable in systematically and critically assessing uncertainties in a risk analysis. The usefulness of this study depends on the decision maker (power company) since uncertainty studies are primarily carried out to support decision making when uncertainties are

Confronting uncertainty in wildlife management: performance of grizzly bear management.

Science.gov (United States)

Artelle, Kyle A; Anderson, Sean C; Cooper, Andrew B; Paquet, Paul C; Reynolds, John D; Darimont, Chris T

2013-01-01

Scientific management of wildlife requires confronting the complexities of natural and social systems. Uncertainty poses a central problem. Whereas the importance of considering uncertainty has been widely discussed, studies of the effects of unaddressed uncertainty on real management systems have been rare. We examined the effects of outcome uncertainty and components of biological uncertainty on hunt management performance, illustrated with grizzly bears (Ursus arctos horribilis) in British Columbia, Canada. We found that both forms of uncertainty can have serious impacts on management performance. Outcome uncertainty alone--discrepancy between expected and realized mortality levels--led to excess mortality in 19% of cases (population-years) examined. Accounting for uncertainty around estimated biological parameters (i.e., biological uncertainty) revealed that excess mortality might have occurred in up to 70% of cases. We offer a general method for identifying targets for exploited species that incorporates uncertainty and maintains the probability of exceeding mortality limits below specified thresholds. Setting targets in our focal system using this method at thresholds of 25% and 5% probability of overmortality would require average target mortality reductions of 47% and 81%, respectively. Application of our transparent and generalizable framework to this or other systems could improve management performance in the presence of uncertainty.

Confronting uncertainty in wildlife management: performance of grizzly bear management.

Directory of Open Access Journals (Sweden)

Kyle A Artelle

Full Text Available Scientific management of wildlife requires confronting the complexities of natural and social systems. Uncertainty poses a central problem. Whereas the importance of considering uncertainty has been widely discussed, studies of the effects of unaddressed uncertainty on real management systems have been rare. We examined the effects of outcome uncertainty and components of biological uncertainty on hunt management performance, illustrated with grizzly bears (Ursus arctos horribilis in British Columbia, Canada. We found that both forms of uncertainty can have serious impacts on management performance. Outcome uncertainty alone--discrepancy between expected and realized mortality levels--led to excess mortality in 19% of cases (population-years examined. Accounting for uncertainty around estimated biological parameters (i.e., biological uncertainty revealed that excess mortality might have occurred in up to 70% of cases. We offer a general method for identifying targets for exploited species that incorporates uncertainty and maintains the probability of exceeding mortality limits below specified thresholds. Setting targets in our focal system using this method at thresholds of 25% and 5% probability of overmortality would require average target mortality reductions of 47% and 81%, respectively. Application of our transparent and generalizable framework to this or other systems could improve management performance in the presence of uncertainty.

Identifying and Analyzing Uncertainty Structures in the TRMM Microwave Imager Precipitation Product over Tropical Ocean Basins

Science.gov (United States)

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.

[Influence of Uncertainty and Uncertainty Appraisal on Self-management in Hemodialysis Patients].

Science.gov (United States)

Jang, Hyung Suk; Lee, Chang Suk; Yang, Young Hee

2015-04-01

This study was done to examine the relation of uncertainty, uncertainty appraisal, and self-management in patients undergoing hemodialysis, and to identify factors influencing self-management. A convenience sample of 92 patients receiving hemodialysis was selected. Data were collected using a structured questionnaire and medical records. The collected data were analyzed using descriptive statistics, t-test, ANOVA, Pearson correlations and multiple regression analysis with the SPSS/WIN 20.0 program. The participants showed a moderate level of uncertainty with the highest score being for ambiguity among the four uncertainty subdomains. Scores for uncertainty danger or opportunity appraisals were under the mid points. The participants were found to perform a high level of self-management such as diet control, management of arteriovenous fistula, exercise, medication, physical management, measurements of body weight and blood pressure, and social activity. The self-management of participants undergoing hemodialysis showed a significant relationship with uncertainty and uncertainty appraisal. The significant factors influencing self-management were uncertainty, uncertainty opportunity appraisal, hemodialysis duration, and having a spouse. These variables explained 32.8% of the variance in self-management. The results suggest that intervention programs to reduce the level of uncertainty and to increase the level of uncertainty opportunity appraisal among patients would improve the self-management of hemodialysis patients.

Climate policy uncertainty and investment risk

Energy Technology Data Exchange (ETDEWEB)

NONE

2007-06-21

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

Utilization of Software Tools for Uncertainty Calculation in Measurement Science Education

International Nuclear Information System (INIS)

Zangl, Hubert; Zine-Zine, Mariam; Hoermaier, Klaus

2015-01-01

Despite its importance, uncertainty is often neglected by practitioners in the design of system even in safety critical applications. Thus, problems arising from uncertainty may only be identified late in the design process and thus lead to additional costs. Although there exists numerous tools to support uncertainty calculation, reasons for limited usage in early design phases may be low awareness of the existence of the tools and insufficient training in the practical application. We present a teaching philosophy that addresses uncertainty from the very beginning of teaching measurement science, in particular with respect to the utilization of software tools. The developed teaching material is based on the GUM method and makes use of uncertainty toolboxes in the simulation environment. Based on examples in measurement science education we discuss advantages and disadvantages of the proposed teaching philosophy and include feedback from students

A Unified Approach for Reporting ARM Measurement Uncertainties Technical Report: Updated in 2016

Energy Technology Data Exchange (ETDEWEB)

Sisterson, Douglas [Argonne National Lab. (ANL), Argonne, IL (United States)

2017-01-15

The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility is observationally based, and quantifying the uncertainty of its measurements is critically important. With over 300 widely differing instruments providing over 2,500 datastreams, concise expression of measurement uncertainty is quite challenging. ARM currently provides data and supporting metadata (information about the data or data quality) to its users through several sources. Because the continued success of the ARM Facility depends on the known quality of its measurements, ARM relies on Instrument Mentors and the ARM Data Quality Office to ensure, assess, and report measurement quality. Therefore, an easily accessible, well-articulated estimate of ARM measurement uncertainty is needed. This report is a continuation of the work presented by Campos and Sisterson (2015) and provides additional uncertainty information from instruments not available in their report. As before, a total measurement uncertainty has been calculated as a function of the instrument uncertainty (calibration factors), the field uncertainty (environmental factors), and the retrieval uncertainty (algorithm factors). This study will not expand on methods for computing these uncertainties. As before, it will focus on the practical identification, characterization, and inventory of the measurement uncertainties already available to the ARM community through the ARM Instrument Mentors and their ARM instrument handbooks. This study continues the first steps towards reporting ARM measurement uncertainty as: (1) identifying how the uncertainty of individual ARM measurements is currently expressed, (2) identifying a consistent approach to measurement uncertainty, and then (3) reclassifying ARM instrument measurement uncertainties in a common framework.

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

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

International Nuclear Information System (INIS)

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

1999-01-01

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

Importance measures in nuclear PSA: how to control their uncertainty and develop new applications

International Nuclear Information System (INIS)

Duflot, N.

2007-01-01

This PhD thesis deals with the importance measures based on nuclear probabilistic safety analyses (PSA). With these indicators, the importance towards risk of the events considered in the PSA models can be measured. The first part of this thesis sets out the framework in which they are currently used. The information extracted from importance measures evaluation is used in industrial decision-making processes that may impact the safety of nuclear plants. In the second part of the thesis, we thus try to meet the requirements of reliability and simplicity with an approach minimising the uncertainties due to modelling. We also lay out a new truncation process of the set of the minimal cut set (MCS) corresponding to the baseline case which allows a quick, automatic and precise calculation of the importance measures. As PSA are increasingly used in risk-informed decision-making approaches, we have examined the extension of importance measures to groups of basic events. The third part of the thesis therefore presents the definition of the importance of events such as the failure of a system or the loss of a function, as well as their potential applications. PSA being considered to be a useful tool to design new nuclear power plants, the fourth part of the thesis sketches out a design process based both on classical importance measures and on new ones. (author)

Phenomenological uncertainty analysis of early containment failure at severe accident of nuclear power plant

Energy Technology Data Exchange (ETDEWEB)

Lee, Su Won

2011-02-15

The severe accident has inherently significant uncertainty due to wide range of conditions and performing experiments, validation and practical application are extremely difficult because of its high temperature and pressure. Although internal and external researches were put into practice, the reference used in Korean nuclear plants were foreign data of 1980s and safety analysis as the probabilistic safety assessment has not applied the newest methodology. Also, it is applied to containment pressure formed into point value as results of thermal hydraulic analysis to identify the probability of containment failure in level 2 PSA. In this paper, the uncertainty analysis methods for phenomena of severe accident influencing early containment failure were developed, the uncertainty analysis that apply Korean nuclear plants using the MELCOR code was performed and it is a point of view to present the distribution of containment pressure as a result of uncertainty analysis. Because early containment failure is important factor of Large Early Release Frequency(LERF) that is used as representative criteria of decision-making in nuclear power plants, it was selected in this paper among various modes of containment failure. Important phenomena of early containment failure at severe accident based on previous researches were comprehended and methodology of 7th steps to evaluate uncertainty was developed. The MELCOR input for analysis of the severe accident reflected natural circulation flow was developed and the accident scenario for station black out that was representative initial event of early containment failure was determined. By reviewing the internal model and correlation for MELCOR model relevant important phenomena of early containment failure, the uncertainty factors which could affect on the uncertainty were founded and the major factors were finally identified through the sensitivity analysis. In order to determine total number of MELCOR calculations which can

Analytic uncertainty and sensitivity analysis of models with input correlations

Science.gov (United States)

Zhu, Yueying; Wang, Qiuping A.; Li, Wei; Cai, Xu

2018-03-01

Probabilistic uncertainty analysis is a common means of evaluating mathematical models. In mathematical modeling, the uncertainty in input variables is specified through distribution laws. Its contribution to the uncertainty in model response is usually analyzed by assuming that input variables are independent of each other. However, correlated parameters are often happened in practical applications. In the present paper, an analytic method is built for the uncertainty and sensitivity analysis of models in the presence of input correlations. With the method, it is straightforward to identify the importance of the independence and correlations of input variables in determining the model response. This allows one to decide whether or not the input correlations should be considered in practice. Numerical examples suggest the effectiveness and validation of our analytic method in the analysis of general models. A practical application of the method is also proposed to the uncertainty and sensitivity analysis of a deterministic HIV model.

Uncertainty in techno-economic estimates of cellulosic ethanol production due to experimental measurement uncertainty

Directory of Open Access Journals (Sweden)

Vicari Kristin J

2012-04-01

Full Text Available Abstract Background Cost-effective production of lignocellulosic biofuels remains a major financial and technical challenge at the industrial scale. A critical tool in biofuels process development is the techno-economic (TE model, which calculates biofuel production costs using a process model and an economic model. The process model solves mass and energy balances for each unit, and the economic model estimates capital and operating costs from the process model based on economic assumptions. The process model inputs include experimental data on the feedstock composition and intermediate product yields for each unit. These experimental yield data are calculated from primary measurements. Uncertainty in these primary measurements is propagated to the calculated yields, to the process model, and ultimately to the economic model. Thus, outputs of the TE model have a minimum uncertainty associated with the uncertainty in the primary measurements. Results We calculate the uncertainty in the Minimum Ethanol Selling Price (MESP estimate for lignocellulosic ethanol production via a biochemical conversion process: dilute sulfuric acid pretreatment of corn stover followed by enzymatic hydrolysis and co-fermentation of the resulting sugars to ethanol. We perform a sensitivity analysis on the TE model and identify the feedstock composition and conversion yields from three unit operations (xylose from pretreatment, glucose from enzymatic hydrolysis, and ethanol from fermentation as the most important variables. The uncertainty in the pretreatment xylose yield arises from multiple measurements, whereas the glucose and ethanol yields from enzymatic hydrolysis and fermentation, respectively, are dominated by a single measurement: the fraction of insoluble solids (fIS in the biomass slurries. Conclusions We calculate a $0.15/gal uncertainty in MESP from the TE model due to uncertainties in primary measurements. This result sets a lower bound on the error bars of

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

Evacuation decision-making: process and uncertainty

Energy Technology Data Exchange (ETDEWEB)

Mileti, D.; Sorensen, J.; Bogard, W.

1985-09-01

The purpose was to describe the processes of evacuation decision-making, identify and document uncertainties in that process and discuss implications for federal assumption of liability for precautionary evacuations at nuclear facilities under the Price-Anderson Act. Four major categories of uncertainty are identified concerning the interpretation of hazard, communication problems, perceived impacts of evacuation decisions and exogenous influences. Over 40 historical accounts are reviewed and cases of these uncertainties are documented. The major findings are that all levels of government, including federal agencies experience uncertainties in some evacuation situations. Second, private sector organizations are subject to uncertainties at a variety of decision points. Third, uncertainties documented in the historical record have provided the grounds for liability although few legal actions have ensued. Finally it is concluded that if liability for evacuations is assumed by the federal government, the concept of a ''precautionary'' evacuation is not useful in establishing criteria for that assumption. 55 refs., 1 fig., 4 tabs.

Evacuation decision-making: process and uncertainty

International Nuclear Information System (INIS)

Mileti, D.; Sorensen, J.; Bogard, W.

1985-09-01

The purpose was to describe the processes of evacuation decision-making, identify and document uncertainties in that process and discuss implications for federal assumption of liability for precautionary evacuations at nuclear facilities under the Price-Anderson Act. Four major categories of uncertainty are identified concerning the interpretation of hazard, communication problems, perceived impacts of evacuation decisions and exogenous influences. Over 40 historical accounts are reviewed and cases of these uncertainties are documented. The major findings are that all levels of government, including federal agencies experience uncertainties in some evacuation situations. Second, private sector organizations are subject to uncertainties at a variety of decision points. Third, uncertainties documented in the historical record have provided the grounds for liability although few legal actions have ensued. Finally it is concluded that if liability for evacuations is assumed by the federal government, the concept of a ''precautionary'' evacuation is not useful in establishing criteria for that assumption. 55 refs., 1 fig., 4 tabs

Identifying the important factors in simulation models with many factors

NARCIS (Netherlands)

Bettonvil, B.; Kleijnen, J.P.C.

1994-01-01

Simulation models may have many parameters and input variables (together called factors), while only a few factors are really important (parsimony principle). For such models this paper presents an effective and efficient screening technique to identify and estimate those important factors. The

Funnel plot control limits to identify poorly performing healthcare providers when there is uncertainty in the value of the benchmark.

Science.gov (United States)

Manktelow, Bradley N; Seaton, Sarah E; Evans, T Alun

2016-12-01

There is an increasing use of statistical methods, such as funnel plots, to identify poorly performing healthcare providers. Funnel plots comprise the construction of control limits around a benchmark and providers with outcomes falling outside the limits are investigated as potential outliers. The benchmark is usually estimated from observed data but uncertainty in this estimate is usually ignored when constructing control limits. In this paper, the use of funnel plots in the presence of uncertainty in the value of the benchmark is reviewed for outcomes from a Binomial distribution. Two methods to derive the control limits are shown: (i) prediction intervals; (ii) tolerance intervals Tolerance intervals formally include the uncertainty in the value of the benchmark while prediction intervals do not. The probability properties of 95% control limits derived using each method were investigated through hypothesised scenarios. Neither prediction intervals nor tolerance intervals produce funnel plot control limits that satisfy the nominal probability characteristics when there is uncertainty in the value of the benchmark. This is not necessarily to say that funnel plots have no role to play in healthcare, but that without the development of intervals satisfying the nominal probability characteristics they must be interpreted with care. © The Author(s) 2014.

Spillovers between energy and FX markets: The importance of asymmetry, uncertainty and business cycle

International Nuclear Information System (INIS)

Khalifa, Ahmed; Caporin, Massimiliano; Hammoudeh, Shawkat

2015-01-01

This study constructs a theoretical volatility transmission model for petroleum and FX markets, taking into account major stylized facts and uncertainty measures and the interactions between them under stages of the business cycle. It examines the impacts of those different specifications and economic factors on the spillovers between those considered markets. The results show that the impacts of the “own” shocks (petroleum on petroleum and currency on currency) are statistically significant and positive in almost all cases as expected for the models of natural gas and WTI oil, irrespectively of the currency considered. The asymmetry effect is stronger in the oil than in the natural gas markets. There is stronger and significant evidence that uncertainty affects volatility much more the mean. For the WTI oil, almost all policy and other uncertainty measures lead to an increase in the conditional variance. For currencies, coefficients are commonly significant independent of the presence of petroleum commodities in the bivariate model. The striking result for natural gas is the limited statistical relevance of the economic policy and other uncertainty measures due to the long contracts that characterize this market. Finally, common macroeconomic forces associated with the business cycle can drive these petroleum and currency markets and may cause jumps and co-jumps in the volatility of these markets. The conclusion provides policy implications of the paper’s results. - Highlights: • Examine the impacts of uncertainty measures on energy and currency interaction. • Examine the impacts of asymmetry on energy and currency interactions. • There is stronger asymmetry in oil compared to natural gas. • Uncertainty measures have an impact on volatility dynamics for oil and currencies. • Uncertainty measures do not have an impact on natural gas.

Probabilistic numerics and uncertainty in computations.

Science.gov (United States)

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.

Uncertainty in a monthly water balance model using the generalized likelihood uncertainty estimation methodology

Science.gov (United States)

Rivera, Diego; Rivas, Yessica; Godoy, Alex

2015-02-01

Hydrological models are simplified representations of natural processes and subject to errors. Uncertainty bounds are a commonly used way to assess the impact of an input or model architecture uncertainty in model outputs. Different sets of parameters could have equally robust goodness-of-fit indicators, which is known as Equifinality. We assessed the outputs from a lumped conceptual hydrological model to an agricultural watershed in central Chile under strong interannual variability (coefficient of variability of 25%) by using the Equifinality concept and uncertainty bounds. The simulation period ran from January 1999 to December 2006. Equifinality and uncertainty bounds from GLUE methodology (Generalized Likelihood Uncertainty Estimation) were used to identify parameter sets as potential representations of the system. The aim of this paper is to exploit the use of uncertainty bounds to differentiate behavioural parameter sets in a simple hydrological model. Then, we analyze the presence of equifinality in order to improve the identification of relevant hydrological processes. The water balance model for Chillan River exhibits, at a first stage, equifinality. However, it was possible to narrow the range for the parameters and eventually identify a set of parameters representing the behaviour of the watershed (a behavioural model) in agreement with observational and soft data (calculation of areal precipitation over the watershed using an isohyetal map). The mean width of the uncertainty bound around the predicted runoff for the simulation period decreased from 50 to 20 m3s-1 after fixing the parameter controlling the areal precipitation over the watershed. This decrement is equivalent to decreasing the ratio between simulated and observed discharge from 5.2 to 2.5. Despite the criticisms against the GLUE methodology, such as the lack of statistical formality, it is identified as a useful tool assisting the modeller with the identification of critical parameters.

UNCERTAINTY IN THE PROCESS INTEGRATION FOR THE BIOREFINERIES DEVELOPMENT

Directory of Open Access Journals (Sweden)

Meilyn González Cortés

2015-07-01

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

Sources of uncertainty in individual monitoring for photographic,TL and OSL dosimetry techniques

Energy Technology Data Exchange (ETDEWEB)

Ferreira, Max S.; Silva, Everton R.; Mauricio, Claudia L.P., E-mail: max.das.ferreira@gmail.com, E-mail: everton@ird.gov.br, E-mail: claudia@ird.gov.br [Instituto de Radioprotecao e Dosimetria (IRD/CNEN-RJ), Rio de Janeiro, RJ (Brazil)

2015-07-01

The identification of the uncertainty sources and their quantification is essential to the quality of any dosimetric results. If uncertainties are not stated for all dose measurements informed in the monthly dose report to the monitored radiation facilities, they need to be known. This study aims to analyze the influence of different sources of uncertainties associated with photographic, TL and OSL dosimetric techniques, considering the evaluation of occupational doses of whole-body exposure for photons. To identify the sources of uncertainty it was conducted a bibliographic review in specific documents that deal with operational aspects of each technique and the uncertainties associated to each of them. Withal, technical visits to individual monitoring services were conducted to assist in this identification. The sources of uncertainty were categorized and their contributions were expressed in a qualitative way. The process of calibration and traceability are the most important sources of uncertainties, regardless the technique used. For photographic dosimetry, the remaining important uncertainty sources are due to: energy and angular dependence; linearity of response; variations in the films processing. For TL and OSL, the key process for a good performance is respectively the reproducibility of the thermal and optical cycles. For the three techniques, all procedures of the measurement process must be standardized, controlled and reproducible. Further studies can be performed to quantify the contribution of the sources of uncertainty. (author)

Information Seeking in Uncertainty Management Theory: Exposure to Information About Medical Uncertainty and Information-Processing Orientation as Predictors of Uncertainty Management Success.

Science.gov (United States)

Rains, Stephen A; Tukachinsky, Riva

2015-01-01

Uncertainty management theory outlines the processes through which individuals cope with health-related uncertainty. Information seeking has been frequently documented as an important uncertainty management strategy. The reported study investigates exposure to specific types of medical information during a search, and one's information-processing orientation as predictors of successful uncertainty management (i.e., a reduction in the discrepancy between the level of uncertainty one feels and the level one desires). A lab study was conducted in which participants were primed to feel more or less certain about skin cancer and then were allowed to search the World Wide Web for skin cancer information. Participants' search behavior was recorded and content analyzed. The results indicate that exposure to two health communication constructs that pervade medical forms of uncertainty (i.e., severity and susceptibility) and information-processing orientation predicted uncertainty management success.

Calibration/Validation Error Budgets, Uncertainties, Traceability and Their Importance to Imaging Spectrometry

Science.gov (United States)

Thome, K.

2016-01-01

Knowledge of uncertainties and errors are essential for comparisons of remote sensing data across time, space, and spectral domains. Vicarious radiometric calibration is used to demonstrate the need for uncertainty knowledge and to provide an example error budget. The sample error budget serves as an example of the questions and issues that need to be addressed by the calibrationvalidation community as accuracy requirements for imaging spectroscopy data will continue to become more stringent in the future. Error budgets will also be critical to ensure consistency between the range of imaging spectrometers expected to be launched in the next five years.

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 evaluation methods for waste package performance assessment

International Nuclear Information System (INIS)

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

1991-01-01

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

Inventories and sales uncertainty\\ud

OpenAIRE

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...

Quantifying chemical uncertainties in simulations of the ISM

Science.gov (United States)

Glover, Simon

2018-06-01

The ever-increasing power of large parallel computers now makes it possible to include increasingly sophisticated chemical models in three-dimensional simulations of the interstellar medium (ISM). This allows us to study the role that chemistry plays in the thermal balance of a realistically-structured, turbulent ISM, as well as enabling us to generated detailed synthetic observations of important atomic or molecular tracers. However, one major constraint on the accuracy of these models is the accuracy with which the input chemical rate coefficients are known. Uncertainties in these chemical rate coefficients inevitably introduce uncertainties into the model predictions. In this talk, I will review some of the methods we can use to quantify these uncertainties and to identify the key reactions where improved chemical data is most urgently required. I will also discuss a few examples, ranging from the local ISM to the high-redshift universe.

Entropic uncertainty relations-a survey

International Nuclear Information System (INIS)

Wehner, Stephanie; Winter, Andreas

2010-01-01

Uncertainty relations play a central role in quantum mechanics. Entropic uncertainty relations in particular have gained significant importance within quantum information, providing the foundation for the security of many quantum cryptographic protocols. Yet, little is known about entropic uncertainty relations with more than two measurement settings. In the present survey, we review known results and open questions.

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

Science.gov (United States)

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

2013-04-01

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

Results from the Application of Uncertainty Methods in the CSNI Uncertainty Methods Study (UMS)

International Nuclear Information System (INIS)

Glaeser, H.

2008-01-01

Within licensing procedures there is the incentive to replace the conservative requirements for code application by a - best estimate - concept supplemented by an uncertainty analysis to account for predictive uncertainties of code results. Methods have been developed to quantify these uncertainties. 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. Most of the methods identify and combine input uncertainties. The major differences between the predictions of the methods came from the choice of uncertain parameters and the quantification of the input uncertainties, i.e. the wideness of the uncertainty ranges. Therefore, suitable experimental and analytical information has to be selected to specify these uncertainty ranges or distributions. After the closure of the Uncertainty Method Study (UMS) and after the report was issued comparison calculations of experiment LSTF-SB-CL-18 were performed by University of Pisa using different versions of the RELAP 5 code. It turned out that the version used by two of the participants calculated a 170 K higher peak clad temperature compared with other versions using the same input deck. This may contribute to the differences of the upper limit of the uncertainty ranges.

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

Sensitivity and uncertainty analyses in aging risk-based prioritizations

International Nuclear Information System (INIS)

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

1993-01-01

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

Coping with uncertainty in environmental impact assessments: Open techniques

Energy Technology Data Exchange (ETDEWEB)

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

2016-09-15

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

Coping with uncertainty in environmental impact assessments: Open techniques

International Nuclear Information System (INIS)

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

2016-01-01

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

Methods and computer codes for probabilistic sensitivity and uncertainty analysis

International Nuclear Information System (INIS)

Vaurio, J.K.

1985-01-01

This paper describes the methods and applications experience with two computer codes that are now available from the National Energy Software Center at Argonne National Laboratory. The purpose of the SCREEN code is to identify a group of most important input variables of a code that has many (tens, hundreds) input variables with uncertainties, and do this without relying on judgment or exhaustive sensitivity studies. Purpose of the PROSA-2 code is to propagate uncertainties and calculate the distributions of interesting output variable(s) of a safety analysis code using response surface techniques, based on the same runs used for screening. Several applications are discussed, but the codes are generic, not tailored to any specific safety application code. They are compatible in terms of input/output requirements but also independent of each other, e.g., PROSA-2 can be used without first using SCREEN if a set of important input variables has first been selected by other methods. Also, although SCREEN can select cases to be run (by random sampling), a user can select cases by other methods if he so prefers, and still use the rest of SCREEN for identifying important input variables

Uncertainty Propagation in Hypersonic Vehicle Aerothermoelastic Analysis

Science.gov (United States)

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

An appraisal of uncertainties in the Western Australian wine industry supply chain

OpenAIRE

Islam, Nazrul; Quaddus, Mohammed

2005-01-01

Wine is one of the significant export items of Western Australia. In 2001/2002, the State’s wine exports amounted to about A$42 million. Despite its economic importance research on the supply chain aspects of WA wine industry is rather limited. This paper presents the sources of uncertainties in WA wine supply chain based on the results of an electronic focus group study with WA wine industry stakeholders. The group identified 74 items of uncertainties, which were then grouped into 26 unique ...

Coupled code analysis of uncertainty and sensitivity of Kalinin-3 benchmark

Energy Technology Data Exchange (ETDEWEB)

Pasichnyk, Ihor; Zwermann, Winfried; Velkov, Kiril [Gesellschaft fuer Anlagen- und Reaktorsicherheit (GRS) gGmbH, Garching (Germany); Nikonov, Sergey [VNIIAES, Moscow (Russian Federation)

2016-09-15

An uncertainty and sensitivity analysis is performed for the OECD/NEA coolant transient Benchmark (K-3) on measured data at Kalinin-3 Nuclear Power Plant (NPP). A switch off of one main coolant pump (MCP) at nominal reactor power is calculated using a coupled thermohydraulic and neutron-kinetic ATHLET-PARCS code. The objectives are to study uncertainty of total reactor power and to identify the main sources of reactor power uncertainty. The GRS uncertainty and sensitivity software package XSUSA is applied to propagate uncertainties in nuclear data libraries to the full core coupled transient calculations. A set of most important thermal-hydraulic parameters of the primary circuit is identified and a total of 23 thermohydraulic parameters are statistically varied using GRS code SUSA. The ATHLET model contains also a balance-of-plant (BOP) model which is simulated using ATHLET GCSM module. In particular the operation of the main steam generator regulators is modelled in detail. A set of 200 varied coupled ATHLET-PARCS calculations is analyzed. The results obtained show a clustering effect in the behavior of global reactor parameters. It is found that the GCSM system together with varied input parameters strongly influence the overall nuclear power plant behavior and can even lead to a new scenario. Possible reasons of the clustering effect are discussed in the paper. This work is a step forward in establishing a ''best-estimate calculations in combination with performing uncertainty analysis'' methodology for coupled full core calculations.

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...

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

Science.gov (United States)

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

2016-11-01

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

Identifying trial recruitment uncertainties using a James Lind Alliance Priority Setting Partnership - the PRioRiTy (Prioritising Recruitment in Randomised Trials) study.

Science.gov (United States)

Healy, Patricia; Galvin, Sandra; Williamson, Paula R; Treweek, Shaun; Whiting, Caroline; Maeso, Beccy; Bray, Christopher; Brocklehurst, Peter; Moloney, Mary Clarke; Douiri, Abdel; Gamble, Carrol; Gardner, Heidi R; Mitchell, Derick; Stewart, Derek; Jordan, Joan; O'Donnell, Martin; Clarke, Mike; Pavitt, Sue H; Guegan, Eleanor Woodford; Blatch-Jones, Amanda; Smith, Valerie; Reay, Hannah; Devane, Declan

2018-03-01

Despite the problem of inadequate recruitment to randomised trials, there is little evidence to guide researchers on decisions about how people are effectively recruited to take part in trials. The PRioRiTy study aimed to identify and prioritise important unanswered trial recruitment questions for research. The PRioRiTy study - Priority Setting Partnership (PSP) included members of the public approached to take part in a randomised trial or who have represented participants on randomised trial steering committees, health professionals and research staff with experience of recruiting to randomised trials, people who have designed, conducted, analysed or reported on randomised trials and people with experience of randomised trials methodology. This partnership was aided by the James Lind Alliance and involved eight stages: (i) identifying a unique, relevant prioritisation area within trial methodology; (ii) establishing a steering group (iii) identifying and engaging with partners and stakeholders; (iv) formulating an initial list of uncertainties; (v) collating the uncertainties into research questions; (vi) confirming that the questions for research are a current recruitment challenge; (vii) shortlisting questions and (viii) final prioritisation through a face-to-face workshop. A total of 790 survey respondents yielded 1693 open-text answers to 6 questions, from which 1880 potential questions for research were identified. After merging duplicates, the number of questions was reduced to 496. Questions were combined further, and those that were submitted by fewer than 15 people and/or fewer than 6 of the 7 stakeholder groups were excluded from the next round of prioritisation resulting in 31 unique questions for research. All 31 questions were confirmed as being unanswered after checking relevant, up-to-date research evidence. The 10 highest priority questions were ranked at a face-to-face workshop. The number 1 ranked question was "How can randomised trials become

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

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)

Uncertainty in geological and hydrogeological data

Directory of Open Access Journals (Sweden)

B. Nilsson

2007-09-01

Full Text Available Uncertainty in conceptual model structure and in environmental data is of essential interest when dealing with uncertainty in water resources management. To make quantification of uncertainty possible is it necessary to identify and characterise the uncertainty in geological and hydrogeological data. This paper discusses a range of available techniques to describe the uncertainty related to geological model structure and scale of support. Literature examples on uncertainty in hydrogeological variables such as saturated hydraulic conductivity, specific yield, specific storage, effective porosity and dispersivity are given. Field data usually have a spatial and temporal scale of support that is different from the one on which numerical models for water resources management operate. Uncertainty in hydrogeological data variables is characterised and assessed within the methodological framework of the HarmoniRiB classification.

Uncertainty analysis with a view towards applications in accident consequence assessments

International Nuclear Information System (INIS)

Fischer, F.; Erhardt, J.

1985-09-01

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

Uncertainty budget for k0-NAA

International Nuclear Information System (INIS)

Robouch, P.; Arana, G.; Eguskiza, M.; Etxebarria, N.

2000-01-01

The concepts of the Guide to the expression of Uncertainties in Measurements for chemical measurements (GUM) and the recommendations of the Eurachem document 'Quantifying Uncertainty in Analytical Methods' are applied to set up the uncertainty budget for k 0 -NAA. The 'universally applicable spreadsheet technique', described by KRAGTEN, is applied to the k 0 -NAA basic equations for the computation of uncertainties. The variance components - individual standard uncertainties - highlight the contribution and the importance of the different parameters to be taken into account. (author)

Uncertainty contributions to low flow projections in Austria

Science.gov (United States)

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

2015-11-01

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

Analysis of convergence of uncertainty and important factors affecting uncertainty in level 1 PSA for pressurized water reactors

International Nuclear Information System (INIS)

Shimada, Yoshio

2002-01-01

We analyzed how the convergence of mean core damage frequency (CDF) depends on the number of minimal cut sets, the sampling method and the random seed, using level 1 PSA models for Surry 1 and a Japanese 4 loop PWR plant. As a result, the followings were clarified: the good convergence efficiency of the latin hypercube sampling (LHS), the relationship between number of minimal cut sets and mean CDF, as well as the standard deviation and the easy method of judgment for mean CDF convergence. In addition, it was seen that the relationship between the number of probability variables (i.e. the number of basic events) and the number of samplings needed to converge for mean CDF. Analysis of important factors affecting uncertainty was also performed. As a result, it was found that the initiating events (especially loss of coolant accidents) were the dominant important factors. Finally, comparisons were made for the 95% confidence interval of the calculated results from the operating experience of the worldwide nuclear power plants with (1) the mean core damage frequency by PSA for 108 US plants and 51 Japanese plants and (2) the 95% confidence interval of the US and the Japanese Plant PSA model used in this research. As a result, it was clarified that the mean core damage frequency of almost all US pressurized and boiling light water reactors in the US was in the 90% confidence interval calculated from the operating experience of the nuclear power plants (PWRs and BWRs) in the world, but that of those reactors in Japan was smaller then that level. (author)

Analysis of convergence of uncertainty and important factors affecting uncertainty in level 1 PSA for pressurized water reactors

Energy Technology Data Exchange (ETDEWEB)

Shimada, Yoshio [Inst. of Nuclear Safety System Inc., Mihama, Fukui (Japan)

2002-09-01

We analyzed how the convergence of mean core damage frequency (CDF) depends on the number of minimal cut sets, the sampling method and the random seed, using level 1 PSA models for Surry 1 and a Japanese 4 loop PWR plant. As a result, the followings were clarified: the good convergence efficiency of the latin hypercube sampling (LHS), the relationship between number of minimal cut sets and mean CDF, as well as the standard deviation and the easy method of judgment for mean CDF convergence. In addition, it was seen that the relationship between the number of probability variables (i.e. the number of basic events) and the number of samplings needed to converge for mean CDF. Analysis of important factors affecting uncertainty was also performed. As a result, it was found that the initiating events (especially loss of coolant accidents) were the dominant important factors. Finally, comparisons were made for the 95% confidence interval of the calculated results from the operating experience of the worldwide nuclear power plants with (1) the mean core damage frequency by PSA for 108 US plants and 51 Japanese plants and (2) the 95% confidence interval of the US and the Japanese Plant PSA model used in this research. As a result, it was clarified that the mean core damage frequency of almost all US pressurized and boiling light water reactors in the US was in the 90% confidence interval calculated from the operating experience of the nuclear power plants (PWRs and BWRs) in the world, but that of those reactors in Japan was smaller then that level. (author)

Uncertainty identification for robust control using a nuclear power plant model

International Nuclear Information System (INIS)

Power, M.; Edwards, R.M.

1995-01-01

An on-line technique which identifies the uncertainty between a lower order and a higher order nuclear power plant model is presented. The uncertainty identifier produces a hard upper bound in H ∞ on the additive uncertainty. This additive uncertainty description can be used for the design of H infinity or μ-synthesis controllers

Religion in the face of uncertainty: an uncertainty-identity theory account of religiousness.

Science.gov (United States)

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.

Wastewater treatment modelling: dealing with uncertainties

DEFF Research Database (Denmark)

Belia, E.; Amerlinck, Y.; Benedetti, L.

2009-01-01

This paper serves as a problem statement of the issues surrounding uncertainty in wastewater treatment modelling. The paper proposes a structure for identifying the sources of uncertainty introduced during each step of an engineering project concerned with model-based design or optimisation...

Uncertainty Communication. Issues and good practice

International Nuclear Information System (INIS)

Kloprogge, P.; Van der Sluijs, J.; Wardekker, A.

2007-12-01

In 2003 the Netherlands Environmental Assessment Agency (MNP) published the RIVM/MNP Guidance for Uncertainty Assessment and Communication. The Guidance assists in dealing with uncertainty in environmental assessments. Dealing with uncertainty is essential because assessment results regarding complex environmental issues are of limited value if the uncertainties have not been taken into account adequately. A careful analysis of uncertainties in an environmental assessment is required, but even more important is the effective communication of these uncertainties in the presentation of assessment results. The Guidance yields rich and differentiated insights in uncertainty, but the relevance of this uncertainty information may vary across audiences and uses of assessment results. Therefore, the reporting of uncertainties is one of the six key issues that is addressed in the Guidance. In practice, users of the Guidance felt a need for more practical assistance in the reporting of uncertainty information. This report explores the issue of uncertainty communication in more detail, and contains more detailed guidance on the communication of uncertainty. In order to make this a 'stand alone' document several questions that are mentioned in the detailed Guidance have been repeated here. This document thus has some overlap with the detailed Guidance. Part 1 gives a general introduction to the issue of communicating uncertainty information. It offers guidelines for (fine)tuning the communication to the intended audiences and context of a report, discusses how readers of a report tend to handle uncertainty information, and ends with a list of criteria that uncertainty communication needs to meet to increase its effectiveness. Part 2 helps writers to analyze the context in which communication takes place, and helps to map the audiences, and their information needs. It further helps to reflect upon anticipated uses and possible impacts of the uncertainty information on the

Effect of Uncertainty Parameters in Blowdown and Reflood Models for OPR1000 LBLOCA Analysis

Energy Technology Data Exchange (ETDEWEB)

Huh, Byung Gil; Jin, Chang Yong; Seul, Kwangwon; Hwang, Taesuk [Korea Institute of Nuclear Safety, Daejeon (Korea, Republic of)

2014-05-15

KINS(Korea Institute of Nuclear Safety) has also performed the audit calculation with the KINS Realistic Evaluation Methodology(KINS-REM) to confirm the validity of licensee's calculation. In the BEPU method, it is very important to quantify the code and model uncertainty. It is referred in the following requirement: BE calculations in Regulatory Guide 1.157 - 'the code and models used are acceptable and applicable to the specific facility over the intended operating range and must quantify the uncertainty in the specific application'. In general, the uncertainty of model/code should be obtained through the data comparison with relevant integral- and separate-effect tests at different scales. However, it is not easy to determine these kinds of uncertainty because of the difficulty for evaluating accurately various experiments. Therefore, the expert judgment has been used in many cases even with the limitation that the uncertainty range of important parameters can be wide and inaccurate. In the KINS-REM, six heat transfer parameters in the blowdown phase have been used to consider the uncertainty of models. Recently, MARS-KS code was modified to consider the uncertainty of the five heat transfer parameters in the reflood phase. Accordingly, it is required that the uncertainty range for parameters of reflood models is determined and the effect of these ranges is evaluated. In this study, the large break LOCA (LBLOCA) analysis for OPR1000 was performed to identify the effect of uncertainty parameters in blowdown and reflood models.

Global impact of uncertainties in China’s gas market

International Nuclear Information System (INIS)

Xunpeng, Shi; Variam, Hari Malamakkavu Padinjare; Tao, Jacqueline

2017-01-01

This paper examines the uncertainties in Chinese gas markets, analyze the reasons and quantify their impact on the world gas market. A literature review found significant variability among the outlooks on China's gas sector. Further assessment found that uncertainties in economic growth, structural change in markets, environmental regulations, price and institutional changes contribute to the uncertainties. The analysis of China’s demand and supply uncertainties with a world gas-trading model found significant changes in global production, trade patterns and spot prices, with pipeline exporters being most affected. China's domestic production and pipeline imports from Central Asia are the major buffers that can offset much of the uncertainties. The study finds an asymmetric phenomenon. Pipeline imports are responding to China's uncertainties in both low and high demand scenarios while LNG imports are only responding to high demand scenario. The major reasons are higher TOP levels and the current practice of import only up to the minimum TOP levels for LNG, as well as a lack of liberalized gas markets. The study shows that it is necessary to create LNG markets that can respond to market dynamics, through either a reduction of TOP levels or change of pricing mechanisms to hub indexation. - Highlights: • Economic growth, regulations, reforms and shale gas cause the uncertainties. • Pipeline exporters to China and Southeast Asian and Australian LNG exporters affected the most. • China’s domestic production and pipe imports offset much of the uncertainties. • Pipeline imports are responding to China’s uncertainties in both low and high demand. • LNG imports are only responding to high demand scenario.

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

zone concentration. Models considering faster net downward flow in the upper part of the root zone predict a more rapid decline in root zone concentration than models that assume a constant infiltration throughout the soil column. A sensitivity analysis performed on two of the models shows that the important parameters are the effective precipitation, the root water uptake and the soil K{sub d}-values. For the advection-dispersion model, the dispersion length is also important for the maximum flux to the groundwater. The amount of dispersion in radionuclide transport is of importance for the release to groundwater. For the box models, an inherent dispersion is obtained by the assumption of instantaneous mixing in the boxes. The degree of dispersion in the calculation will be a function of the size of the boxes. It is therefore important that division of the soil column is made with care in order to obtain the intended values. For many models the uncertainty calculations give very skewed distributions for the flux to the groundwater. In some cases the mean of the stochastic calculation can be several orders of magnitude higher than the value from the deterministic calculations. In relation to the objectives set up for this study it can be concluded that: The analysis of the relationship between uncertainty and model complexity proved to be a difficult task. For the studied scenario, the uncertainty in the model predictions does not have a simple relationship with the complexity of the models used. However, a complete analysis could not be performed since uncertainty results were not available for the full range of models and furthermore were not the uncertainty analysis always carried out in a consistent way. The predicted uncertainty associated with the concentration in the root zone does not show very much variation between the modelling approaches. For the predictions of the flux to groundwater, the simple models and the more complex gave very different results for

Adjoint-Based Uncertainty Quantification with MCNP

Energy Technology Data Exchange (ETDEWEB)

Seifried, Jeffrey E. [Univ. of California, Berkeley, CA (United States)

2011-09-01

This work serves to quantify the instantaneous uncertainties in neutron transport simulations born from nuclear data and statistical counting uncertainties. Perturbation and adjoint theories are used to derive implicit sensitivity expressions. These expressions are transformed into forms that are convenient for construction with MCNP6, creating the ability to perform adjoint-based uncertainty quantification with MCNP6. These new tools are exercised on the depleted-uranium hybrid LIFE blanket, quantifying its sensitivities and uncertainties to important figures of merit. Overall, these uncertainty estimates are small (< 2%). Having quantified the sensitivities and uncertainties, physical understanding of the system is gained and some confidence in the simulation is acquired.

Advancing Uncertainty: Untangling and Discerning Related Concepts

Directory of Open Access Journals (Sweden)

Janice Penrod

2002-12-01

Full Text Available Methods of advancing concepts within the qualitative paradigm have been developed and articulated. In this section, I describe methodological perspectives of a project designed to advance the concept of uncertainty using multiple qualitative methods. Through a series of earlier studies, the concept of uncertainty arose repeatedly in varied contexts, working its way into prominence, and warranting further investigation. Processes of advanced concept analysis were used to initiate the formal investigation into the meaning of the concept. Through concept analysis, the concept was deconstructed to identify conceptual components and gaps in understanding. Using this skeletal framework of the concept identified through concept analysis, subsequent studies were carried out to add ‘flesh’ to the concept. First, a concept refinement using the literature as data was completed. Findings revealed that the current state of the concept of uncertainty failed to incorporate what was known of the lived experience. Therefore, using interview techniques as the primary data source, a phenomenological study of uncertainty among caregivers was conducted. Incorporating the findings of the phenomenology, the skeletal framework of the concept was further fleshed out using techniques of concept correction to produce a more mature conceptualization of uncertainty. In this section, I describe the flow of this qualitative project investigating the concept of uncertainty, with special emphasis on a particular threat to validity (called conceptual tunnel vision that was identified and addressed during the phases of concept correction. Though in this article I employ a study of uncertainty for illustration, limited substantive findings regarding uncertainty are presented to retain a clear focus on the methodological issues.

Parameter Uncertainty on AGCM-simulated Tropical Cyclones

Science.gov (United States)

He, F.

2015-12-01

This work studies the parameter uncertainty on tropical cyclone (TC) simulations in Atmospheric General Circulation Models (AGCMs) using the Reed-Jablonowski TC test case, which is illustrated in Community Atmosphere Model (CAM). It examines the impact from 24 parameters across the physical parameterization schemes that represent the convection, turbulence, precipitation and cloud processes in AGCMs. The one-at-a-time (OAT) sensitivity analysis method first quantifies their relative importance on TC simulations and identifies the key parameters to the six different TC characteristics: intensity, precipitation, longwave cloud radiative forcing (LWCF), shortwave cloud radiative forcing (SWCF), cloud liquid water path (LWP) and ice water path (IWP). Then, 8 physical parameters are chosen and perturbed using the Latin-Hypercube Sampling (LHS) method. The comparison between OAT ensemble run and LHS ensemble run shows that the simulated TC intensity is mainly affected by the parcel fractional mass entrainment rate in Zhang-McFarlane (ZM) deep convection scheme. The nonlinear interactive effect among different physical parameters is negligible on simulated TC intensity. In contrast, this nonlinear interactive effect plays a significant role in other simulated tropical cyclone characteristics (precipitation, LWCF, SWCF, LWP and IWP) and greatly enlarge their simulated uncertainties. The statistical emulator Extended Multivariate Adaptive Regression Splines (EMARS) is applied to characterize the response functions for nonlinear effect. Last, we find that the intensity uncertainty caused by physical parameters is in a degree comparable to uncertainty caused by model structure (e.g. grid) and initial conditions (e.g. sea surface temperature, atmospheric moisture). These findings suggest the importance of using the perturbed physics ensemble (PPE) method to revisit tropical cyclone prediction under climate change scenario.

Fundamental uncertainty limit of optical flow velocimetry according to Heisenberg's uncertainty principle.

Science.gov (United States)

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.

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

Summary from the epistemic uncertainty workshop: consensus amid diversity

International Nuclear Information System (INIS)

Ferson, Scott; Joslyn, Cliff A.; Helton, Jon C.; Oberkampf, William L.; Sentz, Kari

2004-01-01

The 'Epistemic Uncertainty Workshop' sponsored by Sandia National Laboratories was held in Albuquerque, New Mexico, on 6-7 August 2002. The workshop was organized around a set of Challenge Problems involving both epistemic and aleatory uncertainty that the workshop participants were invited to solve and discuss. This concluding article in a special issue of Reliability Engineering and System Safety based on the workshop discusses the intent of the Challenge Problems, summarizes some discussions from the workshop, and provides a technical comparison among the papers in this special issue. The Challenge Problems were computationally simple models that were intended as vehicles for the illustration and comparison of conceptual and numerical techniques for use in analyses that involve: (i) epistemic uncertainty, (ii) aggregation of multiple characterizations of epistemic uncertainty, (iii) combination of epistemic and aleatory uncertainty, and (iv) models with repeated parameters. There was considerable diversity of opinion at the workshop about both methods and fundamental issues, and yet substantial consensus about what the answers to the problems were, and even about how each of the four issues should be addressed. Among the technical approaches advanced were probability theory, Dempster-Shafer evidence theory, random sets, sets of probability measures, imprecise coherent probabilities, coherent lower previsions, probability boxes, possibility theory, fuzzy sets, joint distribution tableaux, polynomial chaos expansions, and info-gap models. Although some participants maintained that a purely probabilistic approach is fully capable of accounting for all forms of uncertainty, most agreed that the treatment of epistemic uncertainty introduces important considerations and that the issues underlying the Challenge Problems are legitimate and significant. Topics identified as meriting additional research include elicitation of uncertainty representations, aggregation of

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

International Nuclear Information System (INIS)

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

1985-01-01

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

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

International Nuclear Information System (INIS)

Burgazzi, L.

2000-01-01

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

Incorporating uncertainty in predictive species distribution modelling.

Science.gov (United States)

Beale, Colin M; Lennon, Jack J

2012-01-19

Motivated by the need to solve ecological problems (climate change, habitat fragmentation and biological invasions), there has been increasing interest in species distribution models (SDMs). Predictions from these models inform conservation policy, invasive species management and disease-control measures. However, predictions are subject to uncertainty, the degree and source of which is often unrecognized. Here, we review the SDM literature in the context of uncertainty, focusing on three main classes of SDM: niche-based models, demographic models and process-based models. We identify sources of uncertainty for each class and discuss how uncertainty can be minimized or included in the modelling process to give realistic measures of confidence around predictions. Because this has typically not been performed, we conclude that uncertainty in SDMs has often been underestimated and a false precision assigned to predictions of geographical distribution. We identify areas where development of new statistical tools will improve predictions from distribution models, notably the development of hierarchical models that link different types of distribution model and their attendant uncertainties across spatial scales. Finally, we discuss the need to develop more defensible methods for assessing predictive performance, quantifying model goodness-of-fit and for assessing the significance of model covariates.

Needs of the CSAU uncertainty method

International Nuclear Information System (INIS)

Prosek, A.; Mavko, B.

2000-01-01

The use of best estimate codes for safety analysis requires quantification of the uncertainties. These uncertainties are inherently linked to the chosen safety analysis methodology. Worldwide, various methods were proposed for this quantification. The purpose of this paper was to identify the needs of the Code Scaling, Applicability, and Uncertainty (CSAU) methodology and then to answer the needs. The specific procedural steps were combined from other methods for uncertainty evaluation and new tools and procedures were proposed. The uncertainty analysis approach and tools were then utilized for confirmatory study. The uncertainty was quantified for the RELAP5/MOD3.2 thermalhydraulic computer code. The results of the adapted CSAU approach to the small-break loss-of-coolant accident (SB LOCA) show that the adapted CSAU can be used for any thermal-hydraulic safety analysis with uncertainty evaluation. However, it was indicated that there are still some limitations in the CSAU approach that need to be resolved. (author)

Impact of Pitot tube calibration on the uncertainty of water flow rate measurement

Science.gov (United States)

de Oliveira Buscarini, Icaro; Costa Barsaglini, Andre; Saiz Jabardo, Paulo Jose; Massami Taira, Nilson; Nader, Gilder

2015-10-01

Water utility companies often use Cole type Pitot tubes to map velocity profiles and thus measure flow rate. Frequent monitoring and measurement of flow rate is an important step in identifying leaks and other types of losses. In Brazil losses as high as 42% are common and in some places even higher values are found. When using Cole type Pitot tubes to measure the flow rate, the uncertainty of the calibration coefficient (Cd) is a major component of the overall flow rate measurement uncertainty. A common practice is to employ the usual value Cd = 0.869, in use since Cole proposed his Pitot tube in 1896. Analysis of 414 calibrations of Cole type Pitot tubes show that Cd varies considerably and values as high 0.020 for the expanded uncertainty are common. Combined with other uncertainty sources, the overall velocity measurement uncertainty is 0.02, increasing flowrate measurement uncertainty by 1.5% which, for the Sao Paulo metropolitan area (Brazil) corresponds to 3.5 × 107 m3/year.

Do systematic reviews address community healthcare professionals' wound care uncertainties? Results from evidence mapping in wound care.

Science.gov (United States)

Christie, Janice; Gray, Trish A; Dumville, Jo C; Cullum, Nicky A

2018-01-01

Complex wounds such as leg and foot ulcers are common, resource intensive and have negative impacts on patients' wellbeing. Evidence-based decision-making, substantiated by high quality evidence such as from systematic reviews, is widely advocated for improving patient care and healthcare efficiency. Consequently, we set out to classify and map the extent to which up-to-date systematic reviews containing robust evidence exist for wound care uncertainties prioritised by community-based healthcare professionals. We asked healthcare professionals to prioritise uncertainties based on complex wound care decisions, and then classified 28 uncertainties according to the type and level of decision. For each uncertainty, we searched for relevant systematic reviews. Two independent reviewers screened abstracts and full texts of reviews against the following criteria: meeting an a priori definition of a systematic review, sufficiently addressing the uncertainty, published during or after 2012, and identifying high quality research evidence. The most common uncertainty type was 'interventions' 24/28 (85%); the majority concerned wound level decisions 15/28 (53%) however, service delivery level decisions (10/28) were given highest priority. Overall, we found 162 potentially relevant reviews of which 57 (35%) were not systematic reviews. Of 106 systematic reviews, only 28 were relevant to an uncertainty and 18 of these were published within the preceding five years; none identified high quality research evidence. Despite the growing volume of published primary research, healthcare professionals delivering wound care have important clinical uncertainties which are not addressed by up-to-date systematic reviews containing high certainty evidence. These are high priority topics requiring new research and systematic reviews which are regularly updated. To reduce clinical and research waste, we recommend systematic reviewers and researchers make greater efforts to ensure that research

Dealing with uncertainties in environmental burden of disease assessment

Directory of Open Access Journals (Sweden)

van der Sluijs Jeroen P

2009-04-01

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

Adult head CT scans: the uncertainties of effective dose estimates

International Nuclear Information System (INIS)

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

2008-01-01

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

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

African Journals Online (AJOL)

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

One Approach to the Fire PSA Uncertainty Analysis

International Nuclear Information System (INIS)

Simic, Z.; Mikulicic, V.; Vukovic, I.

2002-01-01

Experienced practical events and findings from the number of fire probabilistic safety assessment (PSA) studies show that fire has high relative importance for nuclear power plant safety. Fire PSA is a very challenging phenomenon and a number of issues are still in the area of research and development. This has a major impact on the conservatism of fire PSA findings. One way to reduce the level of conservatism is to conduct uncertainty analysis. At the top-level, uncertainty of the fire PSA can be separated in to three segments. The first segment is related to fire initiating events frequencies. The second uncertainty segment is connected to the uncertainty of fire damage. Finally, there is uncertainty related to the PSA model, which propagates this fire-initiated damage to the core damage or other analyzed risk. This paper discusses all three segments of uncertainty. Some recent experience with fire PSA study uncertainty analysis, usage of fire analysis code COMPBRN IIIe, and uncertainty evaluation importance to the final result is presented.(author)

Coping with uncertainty in environmental impact assessments: Open techniques

NARCIS (Netherlands)

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

2016-01-01

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

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...

[Dealing with diagnostic uncertainty in general practice].

Science.gov (United States)

Wübken, Magdalena; Oswald, Jana; Schneider, Antonius

2013-01-01

In general, the prevalence of diseases is low in primary care. Therefore, the positive predictive value of diagnostic tests is lower than in hospitals where patients are highly selected. In addition, the patients present with milder forms of disease; and many diseases might hide behind the initial symptom(s). These facts lead to diagnostic uncertainty which is somewhat inherent to general practice. This narrative review discusses different sources of and reasons for uncertainty and strategies to deal with it in the context of the current literature. Fear of uncertainty correlates with higher diagnostic activities. The attitude towards uncertainty correlates with the choice of medical speciality by vocational trainees or medical students. An intolerance of uncertainty, which still increases as medicine is making steady progress, might partly explain the growing shortage of general practitioners. The bio-psycho-social context appears to be important to diagnostic decision-making. The effect of intuition and heuristics are investigated by cognitive psychologists. It is still unclear whether these aspects are prone to bias or useful, which might depend on the context of medical decisions. Good communication is of great importance to share uncertainty with the patients in a transparent way and to alleviate shared decision-making. Dealing with uncertainty should be seen as an important core component of general practice and needs to be investigated in more detail to improve the respective medical decisions. Copyright © 2013. Published by Elsevier GmbH.

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

Science.gov (United States)

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

2017-09-05

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

Identifying significant uncertainties in thermally dependent processes for repository performance analysis

International Nuclear Information System (INIS)

Gansemer, J.D.; Lamont, A.

1994-01-01

In order to study the performance of the potential Yucca Mountain Nuclear Waste Repository, scientific investigations are being conducted to reduce the uncertainty about process models and system parameters. This paper is intended to demonstrate a method for determining a strategy for the cost effective management of these investigations. It is not meant to be a complete study of all processes and interactions, but does outline a method which can be applied to more in-depth investigations

Model-specification uncertainty in future forest pest outbreak.

Science.gov (United States)

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

2016-04-01

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

Identifying important nodes by adaptive LeaderRank

Science.gov (United States)

Xu, Shuang; Wang, Pei

2017-03-01

Spreading process is a common phenomenon in complex networks. Identifying important nodes in complex networks is of great significance in real-world applications. Based on the spreading process on networks, a lot of measures have been proposed to evaluate the importance of nodes. However, most of the existing measures are appropriate to static networks, which are fragile to topological perturbations. Many real-world complex networks are dynamic rather than static, meaning that the nodes and edges of such networks may change with time, which challenge numerous existing centrality measures. Based on a new weighted mechanism and the newly proposed H-index and LeaderRank (LR), this paper introduces a variant of the LR measure, called adaptive LeaderRank (ALR), which is a new member of the LR-family. Simulations on six real-world networks reveal that the new measure can well balance between prediction accuracy and robustness. More interestingly, the new measure can better adapt to the adjustment or local perturbations of network topologies, as compared with the existing measures. By discussing the detailed properties of the measures from the LR-family, we illustrate that the ALR has its competitive advantages over the other measures. The proposed algorithm enriches the measures to understand complex networks, and may have potential applications in social networks and biological systems.

Uncertainty governance: an integrated framework for managing and communicating uncertainties

International Nuclear Information System (INIS)

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

2004-01-01

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

UNCERTAINTY AND ORIENTATION TOWARDS ERRORS IN TIMES OF CRISIS. THE IMPORTANCE OF BUILDING CONFIDENCE, ENCOURAGING COLLECTIVE EFFICACY

Directory of Open Access Journals (Sweden)

Carmen Tabernero

2014-05-01

Full Text Available The current economic crisis is triggering a new scenario of uncertainty, which is affecting the organizational behavior of individuals and working teams. In contexts of uncertainty, organizational performance suffers a significant decline—workers are faced with the perceived threat of job loss, individuals distrust their organization and perceive that they must compete with their peers. This paper analyzes the effect of uncertainty on both performance and the affective states of workers, as well as the cognitive, affective and personality strategies (goals and error orientation to cope with uncertainty as either learning pportunities or as situations to be avoided. Moreover, this paper explores gender differences in both coping styles in situations of uncertainty and the results of a training program based on error affect inoculation in which positive emotional responses were emphasized. Finally, we discuss the relevance of generating practices and experiences of team cooperation that build trust and promote collective efficacy in work teams.

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

Science.gov (United States)

Ciurean, R. L.; Glade, T.

2012-04-01

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

Use of Sobol's quasirandom sequence generator for integration of modified uncertainty importance measure

International Nuclear Information System (INIS)

Homma, Toshimitsu; Saltelli, A.

1995-01-01

Sensitivity analysis of model output is relevant to a number of practices, including verification of models and computer code quality assurance. It deals with the identification of influential model parameters, especially in complex models implemented in computer programs with many uncertain input variables. In a recent article a new method for sensitivity analysis, named HIM * based on a rank transformation of the uncertainty importance measure suggested by Hora and Iman was proved very powerful for performing automated sensitivity analysis of model output, even in presence of model non-monotonicity. The same was not true of other widely used non-parametric techniques such as standardized rank regression coefficients. A drawback of the HIM * method was the large dimension of the stochastic sample needed for its estimation, which made HIM * impracticable for systems with large number of uncertain parameters. In the present note a more effective sampling algorithm, based on Sobol's quasirandom generator is coupled with HIM * , thereby greatly reducing the sample size needed for an effective identification of influential variables. The performances of the new technique are investigated for two different benchmarks. (author)

The Ethics of Ambiguity: Rethinking the Role and Importance of Uncertainty in Medical Education and Practice.

Science.gov (United States)

Domen, Ronald E

2016-01-01

Understanding and embracing uncertainty are critical for effective teacher-learner relationships as well as for shared decision-making in the physician-patient relationship. However, ambiguity has not been given serious consideration in either the undergraduate or graduate medical curricula or in the role it plays in patient-centered care. In this article, the author examines the ethics of ambiguity and argues for a pedagogy that includes education in the importance of, and tolerance of, ambiguity that is inherent in medical education and practice. Common threads running through the ethics of ambiguity are the virtue of respect, and the development of a culture of respect is required for the successful understanding and implementation of a pedagogy of ambiguity.

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

Validation of Fuel Performance Uncertainty for RIA Safety Analysis

Energy Technology Data Exchange (ETDEWEB)

Park, Nam-Gyu; Yoo, Jong-Sung; Jung, Yil-Sup [KEPCO Nuclear Fuel Co., Daejeon (Korea, Republic of)

2016-10-15

To achieve this the computer code performance has to be validated based on the experimental results. And for the uncertainty quantification, important uncertainty parameters need to be selected, and combined uncertainty has to be evaluated with an acceptable statistical treatment. And important uncertainty parameters to the rod performance such as fuel enthalpy, fission gas release, cladding hoop strain etc. were chosen through the rigorous sensitivity studies. And their validity has been assessed by utilizing the experimental results, which were tested in CABRI and NSRR. Analysis results revealed that several tested rods were not bounded within combined fuel performance uncertainty. Assessment of fuel performance with an extended fuel power uncertainty on tested rods in NSRR and CABRI has been done. Analysis results showed that several tested rods were not bounded within calculated fuel performance uncertainty. This implies that the currently considered uncertainty range of the parameters is not enough to cover the fuel performance sufficiently.

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.

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.

Uncertainty in oil projects

International Nuclear Information System (INIS)

Limperopoulos, G.J.

1995-01-01

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

Integrating uncertainty into public energy research and development decisions

Science.gov (United States)

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

2017-05-01

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

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

Genes Important for Schizosaccharomyces pombe Meiosis Identified Through a Functional Genomics Screen

Science.gov (United States)

Blyth, Julie; Makrantoni, Vasso; Barton, Rachael E.; Spanos, Christos; Rappsilber, Juri; Marston, Adele L.

2018-01-01

Meiosis is a specialized cell division that generates gametes, such as eggs and sperm. Errors in meiosis result in miscarriages and are the leading cause of birth defects; however, the molecular origins of these defects remain unknown. Studies in model organisms are beginning to identify the genes and pathways important for meiosis, but the parts list is still poorly defined. Here we present a comprehensive catalog of genes important for meiosis in the fission yeast, Schizosaccharomyces pombe. Our genome-wide functional screen surveyed all nonessential genes for roles in chromosome segregation and spore formation. Novel genes important at distinct stages of the meiotic chromosome segregation and differentiation program were identified. Preliminary characterization implicated three of these genes in centrosome/spindle pole body, centromere, and cohesion function. Our findings represent a near-complete parts list of genes important for meiosis in fission yeast, providing a valuable resource to advance our molecular understanding of meiosis. PMID:29259000

Differentiating intolerance of uncertainty from three related but distinct constructs.

Science.gov (United States)

Rosen, Natalie O; Ivanova, Elena; Knäuper, Bärbel

2014-01-01

Individual differences in uncertainty have been associated with heightened anxiety, stress and approach-oriented coping. Intolerance of uncertainty (IU) is a trait characteristic that arises from negative beliefs about uncertainty and its consequences. Researchers have established the central role of IU in the development of problematic worry and maladaptive coping, highlighting the importance of this construct to anxiety disorders. However, there is a need to improve our understanding of the phenomenology of IU. The goal of this paper was to present hypotheses regarding the similarities and differences between IU and three related constructs--intolerance of ambiguity, uncertainty orientation, and need for cognitive closure--and to call for future empirical studies to substantiate these hypotheses. To assist with achieving this goal, we conducted a systematic review of the literature, which also served to identify current gaps in knowledge. This paper differentiates these constructs by outlining each definition and general approaches to assessment, reviewing the existing empirical relations, and proposing theoretical similarities and distinctions. Findings may assist researchers in selecting the appropriate construct to address their research questions. Future research directions for the application of these constructs, particularly within the field of clinical and health psychology, are discussed.

Methodology for identifying boundaries of systems important to safety in CANDU nuclear power plants

International Nuclear Information System (INIS)

Therrien, S.; Komljenovic, D.; Therrien, P.; Ruest, C.; Prevost, P.; Vaillancourt, R.

2007-01-01

This paper presents a methodology developed to identify the boundaries of the systems important to safety (SIS) at the Gentilly-2 Nuclear Power Plant (NPP), Hydro-Quebec. The SIS boundaries identification considers nuclear safety only. Components that are not identified as important to safety are systematically identified as related to safety. A global assessment process such as WANO/INPO AP-913 'Equipment Reliability Process' will be needed to implement adequate changes in the management rules of those components. The paper depicts results in applying the methodology to the Shutdown Systems 1 and 2 (SDS 1, 2), and to the Emergency Core Cooling System (ECCS). This validation process enabled fine tuning the methodology, performing a better estimate of the effort required to evaluate a system, and identifying components important to safety of these systems. (author)

The importance of parameterization when simulating the hydrologic response of vegetative land-cover change

Science.gov (United States)

White, Jeremy; Stengel, Victoria; Rendon, Samuel; Banta, John

2017-08-01

Computer models of hydrologic systems are frequently used to investigate the hydrologic response of land-cover change. If the modeling results are used to inform resource-management decisions, then providing robust estimates of uncertainty in the simulated response is an important consideration. Here we examine the importance of parameterization, a necessarily subjective process, on uncertainty estimates of the simulated hydrologic response of land-cover change. Specifically, we applied the soil water assessment tool (SWAT) model to a 1.4 km2 watershed in southern Texas to investigate the simulated hydrologic response of brush management (the mechanical removal of woody plants), a discrete land-cover change. The watershed was instrumented before and after brush-management activities were undertaken, and estimates of precipitation, streamflow, and evapotranspiration (ET) are available; these data were used to condition and verify the model. The role of parameterization in brush-management simulation was evaluated by constructing two models, one with 12 adjustable parameters (reduced parameterization) and one with 1305 adjustable parameters (full parameterization). Both models were subjected to global sensitivity analysis as well as Monte Carlo and generalized likelihood uncertainty estimation (GLUE) conditioning to identify important model inputs and to estimate uncertainty in several quantities of interest related to brush management. Many realizations from both parameterizations were identified as behavioral in that they reproduce daily mean streamflow acceptably well according to Nash-Sutcliffe model efficiency coefficient, percent bias, and coefficient of determination. However, the total volumetric ET difference resulting from simulated brush management remains highly uncertain after conditioning to daily mean streamflow, indicating that streamflow data alone are not sufficient to inform the model inputs that influence the simulated outcomes of brush management

ASSESSMENT OF UNCERTAINTY IN THE RADIATION DOSES FOR THE TECHA RIVER DOSIMETRY SYSTEM

Energy Technology Data Exchange (ETDEWEB)

Napier, Bruce A.; Degteva, M. O.; Anspaugh, L. R.; Shagina, N. B.

2009-10-23

In order to provide more accurate and precise estimates of individual dose (and thus more precise estimates of radiation risk) for the members of the ETRC, a new dosimetric calculation system, the Techa River Dosimetry System-2009 (TRDS-2009) has been prepared. The deterministic version of the improved dosimetry system TRDS-2009D was basically completed in April 2009. Recent developments in evaluation of dose-response models in light of uncertain dose have highlighted the importance of different types of uncertainties in the development of individual dose estimates. These include uncertain parameters that may be either shared or unshared within the dosimetric cohort, and also the nature of the type of uncertainty as aleatory or epistemic and either classical or Berkson. This report identifies the nature of the various input parameters and calculational methods incorporated in the Techa River Dosimetry System (based on the TRDS-2009D implementation), with the intention of preparing a stochastic version to estimate the uncertainties in the dose estimates. This report reviews the equations, databases, and input parameters, and then identifies the author’s interpretations of their general nature. It presents the approach selected so that the stochastic, Monte-Carlo, implementation of the dosimetry System - TRDS-2009MC - will provide useful information regarding the uncertainties of the doses.

Noodles: a tool for visualization of numerical weather model ensemble uncertainty.

Science.gov (United States)

Sanyal, Jibonananda; Zhang, Song; Dyer, Jamie; Mercer, Andrew; Amburn, Philip; Moorhead, Robert J

2010-01-01

Numerical weather prediction ensembles are routinely used for operational weather forecasting. The members of these ensembles are individual simulations with either slightly perturbed initial conditions or different model parameterizations, or occasionally both. Multi-member ensemble output is usually large, multivariate, and challenging to interpret interactively. Forecast meteorologists are interested in understanding the uncertainties associated with numerical weather prediction; specifically variability between the ensemble members. Currently, visualization of ensemble members is mostly accomplished through spaghetti plots of a single mid-troposphere pressure surface height contour. In order to explore new uncertainty visualization methods, the Weather Research and Forecasting (WRF) model was used to create a 48-hour, 18 member parameterization ensemble of the 13 March 1993 "Superstorm". A tool was designed to interactively explore the ensemble uncertainty of three important weather variables: water-vapor mixing ratio, perturbation potential temperature, and perturbation pressure. Uncertainty was quantified using individual ensemble member standard deviation, inter-quartile range, and the width of the 95% confidence interval. Bootstrapping was employed to overcome the dependence on normality in the uncertainty metrics. A coordinated view of ribbon and glyph-based uncertainty visualization, spaghetti plots, iso-pressure colormaps, and data transect plots was provided to two meteorologists for expert evaluation. They found it useful in assessing uncertainty in the data, especially in finding outliers in the ensemble run and therefore avoiding the WRF parameterizations that lead to these outliers. Additionally, the meteorologists could identify spatial regions where the uncertainty was significantly high, allowing for identification of poorly simulated storm environments and physical interpretation of these model issues.

Uncertainty and validation. Effect of model complexity on uncertainty estimates

International Nuclear Information System (INIS)

Elert, M.

1996-09-01

zone concentration. Models considering faster net downward flow in the upper part of the root zone predict a more rapid decline in root zone concentration than models that assume a constant infiltration throughout the soil column. A sensitivity analysis performed on two of the models shows that the important parameters are the effective precipitation, the root water uptake and the soil K d -values. For the advection-dispersion model, the dispersion length is also important for the maximum flux to the groundwater. The amount of dispersion in radionuclide transport is of importance for the release to groundwater. For the box models, an inherent dispersion is obtained by the assumption of instantaneous mixing in the boxes. The degree of dispersion in the calculation will be a function of the size of the boxes. It is therefore important that division of the soil column is made with care in order to obtain the intended values. For many models the uncertainty calculations give very skewed distributions for the flux to the groundwater. In some cases the mean of the stochastic calculation can be several orders of magnitude higher than the value from the deterministic calculations. In relation to the objectives set up for this study it can be concluded that: The analysis of the relationship between uncertainty and model complexity proved to be a difficult task. For the studied scenario, the uncertainty in the model predictions does not have a simple relationship with the complexity of the models used. However, a complete analysis could not be performed since uncertainty results were not available for the full range of models and furthermore were not the uncertainty analysis always carried out in a consistent way. The predicted uncertainty associated with the concentration in the root zone does not show very much variation between the modelling approaches. For the predictions of the flux to groundwater, the simple models and the more complex gave very different results for the

Sensitivity and uncertainty analysis

CERN Document Server

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

Maximal Predictability Approach for Identifying the Right Descriptors for Electrocatalytic Reactions.

Science.gov (United States)

Krishnamurthy, Dilip; Sumaria, Vaidish; Viswanathan, Venkatasubramanian

2018-02-01

Density functional theory (DFT) calculations are being routinely used to identify new material candidates that approach activity near fundamental limits imposed by thermodynamics or scaling relations. DFT calculations are associated with inherent uncertainty, which limits the ability to delineate materials (distinguishability) that possess high activity. Development of error-estimation capabilities in DFT has enabled uncertainty propagation through activity-prediction models. In this work, we demonstrate an approach to propagating uncertainty through thermodynamic activity models leading to a probability distribution of the computed activity and thereby its expectation value. A new metric, prediction efficiency, is defined, which provides a quantitative measure of the ability to distinguish activity of materials and can be used to identify the optimal descriptor(s) ΔG opt . We demonstrate the framework for four important electrochemical reactions: hydrogen evolution, chlorine evolution, oxygen reduction and oxygen evolution. Future studies could utilize expected activity and prediction efficiency to significantly improve the prediction accuracy of highly active material candidates.

Quantification of uncertainties in source term estimates for a BWR with Mark I containment

International Nuclear Information System (INIS)

Khatib-Rahbar, M.; Cazzoli, E.; Davis, R.; Ishigami, T.; Lee, M.; Nourbakhsh, H.; Schmidt, E.; Unwin, S.

1988-01-01

A methodology for quantification and uncertainty analysis of source terms for severe accident in light water reactors (QUASAR) has been developed. The objectives of the QUASAR program are (1) to develop a framework for performing an uncertainty evaluation of the input parameters of the phenomenological models used in the Source Term Code Package (STCP), and (2) to quantify the uncertainties in certain phenomenological aspects of source terms (that are not modeled by STCP) using state-of-the-art methods. The QUASAR methodology consists of (1) screening sensitivity analysis, where the most sensitive input variables are selected for detailed uncertainty analysis, (2) uncertainty analysis, where probability density functions (PDFs) are established for the parameters identified by the screening stage and propagated through the codes to obtain PDFs for the outputs (i.e., release fractions to the environment), and (3) distribution sensitivity analysis, which is performed to determine the sensitivity of the output PDFs to the input PDFs. In this paper attention is limited to a single accident progression sequence, namely; a station blackout accident in a BWR with a Mark I containment buildings. Identified as an important accident in the draft NUREG-1150 a station blackout involves loss of both off-site power and DC power resulting in failure of the diesels to start and in the unavailability of the high pressure injection and core isolation coding systems

A probabilistic approach to cost and duration uncertainties in environmental decisions

International Nuclear Information System (INIS)

Boak, D.M.; Painton, L.

1996-01-01

Sandia National Laboratories has developed a method for analyzing life-cycle costs using probabilistic cost forecasting and utility theory to determine the most cost-effective alternatives for safe interim storage of radioactive materials. The method explicitly incorporates uncertainties in cost and storage duration by (1) treating uncertain component costs as random variables represented by probability distributions, (2) treating uncertain durations as chance nodes in a decision tree, and (3) using stochastic simulation tools to generate life-cycle cost forecasts for each storage alternative. The method applies utility functions to the forecasted costs to incorporate the decision maker's risk preferences, making it possible to compare alternatives on the basis of both cost and cost utility. Finally, the method is used to help identify key contributors to the uncertainty in forecasted costs to focus efforts aimed at reducing cost uncertainties. Where significant cost and duration uncertainties exist, and where programmatic decisions must be made despite these uncertainties, probabilistic forecasting techniques can yield important insights into decision alternatives, especially when used as part of a larger decision analysis framework and when properly balanced with deterministic analyses. Although the method is built around an interim storage example, it is potentially applicable to many other environmental decision problems

Fukushima Daiichi unit 1 uncertainty analysis--Preliminary selection of uncertain parameters and analysis methodology

Energy Technology Data Exchange (ETDEWEB)

Cardoni, Jeffrey N.; Kalinich, Donald A.

2014-02-01

Sandia National Laboratories (SNL) plans to conduct uncertainty analyses (UA) on the Fukushima Daiichi unit (1F1) plant with the MELCOR code. The model to be used was developed for a previous accident reconstruction investigation jointly sponsored by the US Department of Energy (DOE) and Nuclear Regulatory Commission (NRC). However, that study only examined a handful of various model inputs and boundary conditions, and the predictions yielded only fair agreement with plant data and current release estimates. The goal of this uncertainty study is to perform a focused evaluation of uncertainty in core melt progression behavior and its effect on key figures-of-merit (e.g., hydrogen production, vessel lower head failure, etc.). In preparation for the SNL Fukushima UA work, a scoping study has been completed to identify important core melt progression parameters for the uncertainty analysis. The study also lays out a preliminary UA methodology.

Facing uncertainty in ecosystem services-based resource management.

Science.gov (United States)

Grêt-Regamey, Adrienne; Brunner, Sibyl H; Altwegg, Jürg; Bebi, Peter

2013-09-01

The concept of ecosystem services is increasingly used as a support for natural resource management decisions. While the science for assessing ecosystem services is improving, appropriate methods to address uncertainties in a quantitative manner are missing. Ignoring parameter uncertainties, modeling uncertainties and uncertainties related to human-environment interactions can modify decisions and lead to overlooking important management possibilities. In this contribution, we present a new approach for mapping the uncertainties in the assessment of multiple ecosystem services. The spatially explicit risk approach links Bayesian networks to a Geographic Information System for forecasting the value of a bundle of ecosystem services and quantifies the uncertainties related to the outcomes in a spatially explicit manner. We demonstrate that mapping uncertainties in ecosystem services assessments provides key information for decision-makers seeking critical areas in the delivery of ecosystem services in a case study in the Swiss Alps. The results suggest that not only the total value of the bundle of ecosystem services is highly dependent on uncertainties, but the spatial pattern of the ecosystem services values changes substantially when considering uncertainties. This is particularly important for the long-term management of mountain forest ecosystems, which have long rotation stands and are highly sensitive to pressing climate and socio-economic changes. Copyright © 2012 Elsevier Ltd. All rights reserved.

Qualitative uncertainty analysis in probabilistic safety assessment context

International Nuclear Information System (INIS)

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

2007-01-01

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

Section summary: Uncertainty and design considerations

Science.gov (United States)

Stephen Hagen

2013-01-01

Well planned sampling designs and robust approaches to estimating uncertainty are critical components of forest monitoring. The importance of uncertainty estimation increases as deforestation and degradation issues become more closely tied to financing incentives for reducing greenhouse gas emissions in the forest sector. Investors like to know risk and risk is tightly...

Measurement uncertainty: Friend or foe?

Science.gov (United States)

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.

"Maybe the Algae Was from the Filter": Maybe and Similar Modifiers as Mediational Tools and Indicators of Uncertainty and Possibility in Children's Science Talk

Science.gov (United States)

Kirch, Susan A.; Siry, Christina A.

2012-01-01

Uncertainty is an essential component of scientific inquiry and it also permeates our daily lives. Understanding how to identify, evaluate, resolve and live in the presence of uncertainty is important for decision-making strategies and engaging in transformative actions. In contrast, confidence and certainty are prized in elementary school…

Gamma-Ray Telescope and Uncertainty Principle

Science.gov (United States)

Shivalingaswamy, T.; Kagali, B. A.

2012-01-01

Heisenberg's Uncertainty Principle is one of the important basic principles of quantum mechanics. In most of the books on quantum mechanics, this uncertainty principle is generally illustrated with the help of a gamma ray microscope, wherein neither the image formation criterion nor the lens properties are taken into account. Thus a better…

Uncertainty Quantification and Regional Sensitivity Analysis of Snow-related Parameters in the Canadian LAnd Surface Scheme (CLASS)

Science.gov (United States)

Badawy, B.; Fletcher, C. G.

2017-12-01

The parameterization of snow processes in land surface models is an important source of uncertainty in climate simulations. Quantifying the importance of snow-related parameters, and their uncertainties, may therefore lead to better understanding and quantification of uncertainty within integrated earth system models. However, quantifying the uncertainty arising from parameterized snow processes is challenging due to the high-dimensional parameter space, poor observational constraints, and parameter interaction. In this study, we investigate the sensitivity of the land simulation to uncertainty in snow microphysical parameters in the Canadian LAnd Surface Scheme (CLASS) using an uncertainty quantification (UQ) approach. A set of training cases (n=400) from CLASS is used to sample each parameter across its full range of empirical uncertainty, as determined from available observations and expert elicitation. A statistical learning model using support vector regression (SVR) is then constructed from the training data (CLASS output variables) to efficiently emulate the dynamical CLASS simulations over a much larger (n=220) set of cases. This approach is used to constrain the plausible range for each parameter using a skill score, and to identify the parameters with largest influence on the land simulation in CLASS at global and regional scales, using a random forest (RF) permutation importance algorithm. Preliminary sensitivity tests indicate that snow albedo refreshment threshold and the limiting snow depth, below which bare patches begin to appear, have the highest impact on snow output variables. The results also show a considerable reduction of the plausible ranges of the parameters values and hence reducing their uncertainty ranges, which can lead to a significant reduction of the model uncertainty. The implementation and results of this study will be presented and discussed in details.

Background and Qualification of Uncertainty Methods

International Nuclear Information System (INIS)

D'Auria, F.; Petruzzi, A.

2008-01-01

The evaluation of uncertainty constitutes the necessary supplement of Best Estimate calculations performed to understand accident scenarios in water cooled nuclear reactors. The needs come from the imperfection of computational tools on the one side and from the interest in using such tool to get more precise evaluation of safety margins. The paper reviews the salient features of two independent approaches for estimating uncertainties associated with predictions of complex system codes. Namely the propagation of code input error and the propagation of the calculation output error constitute the key-words for identifying the methods of current interest for industrial applications. Throughout the developed methods, uncertainty bands can be derived (both upper and lower) for any desired quantity of the transient of interest. For the second case, the uncertainty method is coupled with the thermal-hydraulic code to get the Code with capability of Internal Assessment of Uncertainty, whose features are discussed in more detail.

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

Uncertainties propagation and global sensitivity analysis of the frequency response function of piezoelectric energy harvesters

Science.gov (United States)

Ruiz, Rafael O.; Meruane, Viviana

2017-06-01

The goal of this work is to describe a framework to propagate uncertainties in piezoelectric energy harvesters (PEHs). These uncertainties are related to the incomplete knowledge of the model parameters. The framework presented could be employed to conduct prior robust stochastic predictions. The prior analysis assumes a known probability density function for the uncertain variables and propagates the uncertainties to the output voltage. The framework is particularized to evaluate the behavior of the frequency response functions (FRFs) in PEHs, while its implementation is illustrated by the use of different unimorph and bimorph PEHs subjected to different scenarios: free of uncertainties, common uncertainties, and uncertainties as a product of imperfect clamping. The common variability associated with the PEH parameters are tabulated and reported. A global sensitivity analysis is conducted to identify the Sobol indices. Results indicate that the elastic modulus, density, and thickness of the piezoelectric layer are the most relevant parameters of the output variability. The importance of including the model parameter uncertainties in the estimation of the FRFs is revealed. In this sense, the present framework constitutes a powerful tool in the robust design and prediction of PEH performance.

Uncertainty in biodiversity science, policy and management: a conceptual overview

Directory of Open Access Journals (Sweden)

Yrjö Haila

2014-10-01

Full Text Available The protection of biodiversity is a complex societal, political and ultimately practical imperative of current global society. The imperative builds upon scientific knowledge on human dependence on the life-support systems of the Earth. This paper aims at introducing main types of uncertainty inherent in biodiversity science, policy and management, as an introduction to a companion paper summarizing practical experiences of scientists and scholars (Haila et al. 2014. Uncertainty is a cluster concept: the actual nature of uncertainty is inherently context-bound. We use semantic space as a conceptual device to identify key dimensions of uncertainty in the context of biodiversity protection; these relate to [i] data; [ii] proxies; [iii] concepts; [iv] policy and management; and [v] normative goals. Semantic space offers an analytic perspective for drawing critical distinctions between types of uncertainty, identifying fruitful resonances that help to cope with the uncertainties, and building up collaboration between different specialists to support mutual social learning.

Using a Meniscus to Teach Uncertainty in Measurement

Science.gov (United States)

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…

Uncertainty, God, and scrupulosity: Uncertainty salience and priming God concepts interact to cause greater fears of sin.

Science.gov (United States)

Fergus, Thomas A; Rowatt, Wade C

2015-03-01

Difficulties tolerating uncertainty are considered central to scrupulosity, a moral/religious presentation of obsessive-compulsive disorder (OCD). We examined whether uncertainty salience (i.e., exposure to a state of uncertainty) caused fears of sin and fears of God, as well as whether priming God concepts affected the impact of uncertainty salience on those fears. An internet sample of community adults (N = 120) who endorsed holding a belief in God or a higher power were randomly assigned to an experimental manipulation of (1) salience (uncertainty or insecurity) and (2) prime (God concepts or neutral). As predicted, participants who received the uncertainty salience and God concept priming reported the greatest fears of sin. There were no mean-level differences in the other conditions. The effect was not attributable to religiosity and the manipulations did not cause negative affect. We used a nonclinical sample recruited from the internet. These results support cognitive-behavioral models suggesting that religious uncertainty is important to scrupulosity. Implications of these results for future research are discussed. Copyright © 2014 Elsevier Ltd. All rights reserved.

Parameter sensitivity and uncertainty of the forest carbon flux model FORUG : a Monte Carlo analysis

Energy Technology Data Exchange (ETDEWEB)

Verbeeck, H.; Samson, R.; Lemeur, R. [Ghent Univ., Ghent (Belgium). Laboratory of Plant Ecology; Verdonck, F. [Ghent Univ., Ghent (Belgium). Dept. of Applied Mathematics, Biometrics and Process Control

2006-06-15

The FORUG model is a multi-layer process-based model that simulates carbon dioxide (CO{sub 2}) and water exchange between forest stands and the atmosphere. The main model outputs are net ecosystem exchange (NEE), total ecosystem respiration (TER), gross primary production (GPP) and evapotranspiration. This study used a sensitivity analysis to identify the parameters contributing to NEE uncertainty in the FORUG model. The aim was to determine if it is necessary to estimate the uncertainty of all parameters of a model to determine overall output uncertainty. Data used in the study were the meteorological and flux data of beech trees in Hesse. The Monte Carlo method was used to rank sensitivity and uncertainty parameters in combination with a multiple linear regression. Simulations were run in which parameters were assigned probability distributions and the effect of variance in the parameters on the output distribution was assessed. The uncertainty of the output for NEE was estimated. Based on the arbitrary uncertainty of 10 key parameters, a standard deviation of 0.88 Mg C per year per NEE was found, which was equal to 24 per cent of the mean value of NEE. The sensitivity analysis showed that the overall output uncertainty of the FORUG model could be determined by accounting for only a few key parameters, which were identified as corresponding to critical parameters in the literature. It was concluded that the 10 most important parameters determined more than 90 per cent of the output uncertainty. High ranking parameters included soil respiration; photosynthesis; and crown architecture. It was concluded that the Monte Carlo technique is a useful tool for ranking the uncertainty of parameters of process-based forest flux models. 48 refs., 2 tabs., 2 figs.

Proposed standardized definitions for vertical resolution and uncertainty in the NDACC lidar ozone and temperature algorithms - Part 3: Temperature uncertainty budget

Science.gov (United States)

Leblanc, Thierry; Sica, Robert J.; van Gijsel, Joanna A. E.; Haefele, Alexander; Payen, Guillaume; Liberti, Gianluigi

2016-08-01

A standardized approach for the definition, propagation, and reporting of uncertainty in the temperature lidar data products contributing to the Network for the Detection for Atmospheric Composition Change (NDACC) database is proposed. One important aspect of the proposed approach is the ability to propagate all independent uncertainty components in parallel through the data processing chain. The individual uncertainty components are then combined together at the very last stage of processing to form the temperature combined standard uncertainty. The identified uncertainty sources comprise major components such as signal detection, saturation correction, background noise extraction, temperature tie-on at the top of the profile, and absorption by ozone if working in the visible spectrum, as well as other components such as molecular extinction, the acceleration of gravity, and the molecular mass of air, whose magnitudes depend on the instrument, data processing algorithm, and altitude range of interest. The expression of the individual uncertainty components and their step-by-step propagation through the temperature data processing chain are thoroughly estimated, taking into account the effect of vertical filtering and the merging of multiple channels. All sources of uncertainty except detection noise imply correlated terms in the vertical dimension, which means that covariance terms must be taken into account when vertical filtering is applied and when temperature is integrated from the top of the profile. Quantitatively, the uncertainty budget is presented in a generic form (i.e., as a function of instrument performance and wavelength), so that any NDACC temperature lidar investigator can easily estimate the expected impact of individual uncertainty components in the case of their own instrument. Using this standardized approach, an example of uncertainty budget is provided for the Jet Propulsion Laboratory (JPL) lidar at Mauna Loa Observatory, Hawai'i, which is

Development of a Prototype Model-Form Uncertainty Knowledge Base

Science.gov (United States)

Green, Lawrence L.

2016-01-01

Uncertainties are generally classified as either aleatory or epistemic. Aleatory uncertainties are those attributed to random variation, either naturally or through manufacturing processes. Epistemic uncertainties are generally attributed to a lack of knowledge. One type of epistemic uncertainty is called model-form uncertainty. The term model-form means that among the choices to be made during a design process within an analysis, there are different forms of the analysis process, which each give different results for the same configuration at the same flight conditions. Examples of model-form uncertainties include the grid density, grid type, and solver type used within a computational fluid dynamics code, or the choice of the number and type of model elements within a structures analysis. The objectives of this work are to identify and quantify a representative set of model-form uncertainties and to make this information available to designers through an interactive knowledge base (KB). The KB can then be used during probabilistic design sessions, so as to enable the possible reduction of uncertainties in the design process through resource investment. An extensive literature search has been conducted to identify and quantify typical model-form uncertainties present within aerospace design. An initial attempt has been made to assemble the results of this literature search into a searchable KB, usable in real time during probabilistic design sessions. A concept of operations and the basic structure of a model-form uncertainty KB are described. Key operations within the KB are illustrated. Current limitations in the KB, and possible workarounds are explained.

Uncertainty Quantification in Numerical Aerodynamics

KAUST Repository

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.

A model of designing as the intersection between uncertainty perception, information processing, and coevolution

DEFF Research Database (Denmark)

Lasso, Sarah Venturim; Cash, Philip; Daalhuizen, Jaap

2016-01-01

, the designer's perceived uncertainty is the motivation to start a process of collecting, exchanging, and integrating knowledge. This has been formalised in Information-Processing Theory and more generally described by authors such as Aurisicchio et al. (2013) who describe design as an information...... takes the first steps towards linking these disparate perspectives in a model of designing that synthesises coevolution and information processing. How designers act has been shown to play an important role in the process of New Product Development (NPD) (See e.g. Badke-Schaub and Frankenberger, 2012...... transformation process. Here the aim of the activity is to reduce the perceived uncertainty through identifying and integrating external information and knowledge within the design team. For2example, when perceiving uncertainty the designer might seek new information online, process this information, and share...

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

International Nuclear Information System (INIS)

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

2014-01-01

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

Uncertainties in s-process nucleosynthesis in massive stars determined by Monte Carlo variations

Science.gov (United States)

Nishimura, N.; Hirschi, R.; Rauscher, T.; St. J. Murphy, A.; Cescutti, G.

2017-08-01

The s-process in massive stars produces the weak component of the s-process (nuclei up to A ˜ 90), in amounts that match solar abundances. For heavier isotopes, such as barium, production through neutron capture is significantly enhanced in very metal-poor stars with fast rotation. However, detailed theoretical predictions for the resulting final s-process abundances have important uncertainties caused both by the underlying uncertainties in the nuclear physics (principally neutron-capture reaction and β-decay rates) as well as by the stellar evolution modelling. In this work, we investigated the impact of nuclear-physics uncertainties relevant to the s-process in massive stars. Using a Monte Carlo based approach, we performed extensive nuclear reaction network calculations that include newly evaluated upper and lower limits for the individual temperature-dependent reaction rates. We found that most of the uncertainty in the final abundances is caused by uncertainties in the neutron-capture rates, while β-decay rate uncertainties affect only a few nuclei near s-process branchings. The s-process in rotating metal-poor stars shows quantitatively different uncertainties and key reactions, although the qualitative characteristics are similar. We confirmed that our results do not significantly change at different metallicities for fast rotating massive stars in the very low metallicity regime. We highlight which of the identified key reactions are realistic candidates for improved measurement by future experiments.

Assessing climate change and socio-economic uncertainties in long term management of water resources

Science.gov (United States)

Jahanshahi, Golnaz; Dawson, Richard; Walsh, Claire; Birkinshaw, Stephen; Glenis, Vassilis

2015-04-01

Long term management of water resources is challenging for decision makers given the range of uncertainties that exist. Such uncertainties are a function of long term drivers of change, such as climate, environmental loadings, demography, land use and other socio economic drivers. Impacts of climate change on frequency of extreme events such as drought make it a serious threat to water resources and water security. The release of probabilistic climate information, such as the UKCP09 scenarios, provides improved understanding of some uncertainties in climate models. This has motivated a more rigorous approach to dealing with other uncertainties in order to understand the sensitivity of investment decisions to future uncertainty and identify adaptation options that are as far as possible robust. We have developed and coupled a system of models that includes a weather generator, simulations of catchment hydrology, demand for water and the water resource system. This integrated model has been applied in the Thames catchment which supplies the city of London, UK. This region is one of the driest in the UK and hence sensitive to water availability. In addition, it is one of the fastest growing parts of the UK and plays an important economic role. Key uncertainties in long term water resources in the Thames catchment, many of which result from earth system processes, are identified and quantified. The implications of these uncertainties are explored using a combination of uncertainty analysis and sensitivity testing. The analysis shows considerable uncertainty in future rainfall, river flow and consequently water resource. For example, results indicate that by the 2050s, low flow (Q95) in the Thames catchment will range from -44 to +9% compared with the control scenario (1970s). Consequently, by the 2050s the average number of drought days are expected to increase 4-6 times relative to the 1970s. Uncertainties associated with urban growth increase these risks further

Understanding the origin of Paris Agreement emission uncertainties

Science.gov (United States)

Rogelj, Joeri; Fricko, Oliver; Meinshausen, Malte; Krey, Volker; Zilliacus, Johanna J. J.; Riahi, Keywan

2017-06-01

The UN Paris Agreement puts in place a legally binding mechanism to increase mitigation action over time. Countries put forward pledges called nationally determined contributions (NDC) whose impact is assessed in global stocktaking exercises. Subsequently, actions can then be strengthened in light of the Paris climate objective: limiting global mean temperature increase to well below 2 °C and pursuing efforts to limit it further to 1.5 °C. However, pledged actions are currently described ambiguously and this complicates the global stocktaking exercise. Here, we systematically explore possible interpretations of NDC assumptions, and show that this results in estimated emissions for 2030 ranging from 47 to 63 GtCO2e yr-1. We show that this uncertainty has critical implications for the feasibility and cost to limit warming well below 2 °C and further to 1.5 °C. Countries are currently working towards clarifying the modalities of future NDCs. We identify salient avenues to reduce the overall uncertainty by about 10 percentage points through simple, technical clarifications regarding energy accounting rules. Remaining uncertainties depend to a large extent on politically valid choices about how NDCs are expressed, and therefore raise the importance of a thorough and robust process that keeps track of where emissions are heading over time.

Uncertainty in prediction and in inference

International Nuclear Information System (INIS)

Hilgevoord, J.; Uffink, J.

1991-01-01

The concepts of uncertainty in prediction and inference are introduced and illustrated using the diffraction of light as an example. The close relationship between the concepts of uncertainty in inference and resolving power is noted. A general quantitative measure of uncertainty in inference can be obtained by means of the so-called statistical distance between probability distributions. When applied to quantum mechanics, this distance leads to a measure of the distinguishability of quantum states, which essentially is the absolute value of the matrix element between the states. The importance of this result to the quantum mechanical uncertainty principle is noted. The second part of the paper provides a derivation of the statistical distance on the basis of the so-called method of support

Some reflections on uncertainty analysis and management

International Nuclear Information System (INIS)

Aven, Terje

2010-01-01

A guide to quantitative uncertainty analysis and management in industry has recently been issued. The guide provides an overall framework for uncertainty modelling and characterisations, using probabilities but also other uncertainty representations (including the Dempster-Shafer theory). A number of practical applications showing how to use the framework are presented. The guide is considered as an important contribution to the field, but there is a potential for improvements. These relate mainly to the scientific basis and clarification of critical issues, for example, concerning the meaning of a probability and the concept of model uncertainty. A reformulation of the framework is suggested using probabilities as the only representation of uncertainty. Several simple examples are included to motivate and explain the basic ideas of the modified framework.

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)

Approach to uncertainty in risk analysis

Energy Technology Data Exchange (ETDEWEB)

Rish, W.R.

1988-08-01

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

Approach to uncertainty in risk analysis

International Nuclear Information System (INIS)

Rish, W.R.

1988-08-01

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

Uncertainty and Sensitivity Analysis of Afterbody Radiative Heating Predictions for Earth Entry

Science.gov (United States)

West, Thomas K., IV; Johnston, Christopher O.; Hosder, Serhat

2016-01-01

The objective of this work was to perform sensitivity analysis and uncertainty quantification for afterbody radiative heating predictions of Stardust capsule during Earth entry at peak afterbody radiation conditions. The radiation environment in the afterbody region poses significant challenges for accurate uncertainty quantification and sensitivity analysis due to the complexity of the flow physics, computational cost, and large number of un-certain variables. In this study, first a sparse collocation non-intrusive polynomial chaos approach along with global non-linear sensitivity analysis was used to identify the most significant uncertain variables and reduce the dimensions of the stochastic problem. Then, a total order stochastic expansion was constructed over only the important parameters for an efficient and accurate estimate of the uncertainty in radiation. Based on previous work, 388 uncertain parameters were considered in the radiation model, which came from the thermodynamics, flow field chemistry, and radiation modeling. The sensitivity analysis showed that only four of these variables contributed significantly to afterbody radiation uncertainty, accounting for almost 95% of the uncertainty. These included the electronic- impact excitation rate for N between level 2 and level 5 and rates of three chemical reactions in uencing N, N(+), O, and O(+) number densities in the flow field.

A review on the CIRCE methodology to quantify the uncertainty of the physical models of a code

International Nuclear Information System (INIS)

Jeon, Seong Su; Hong, Soon Joon; Bang, Young Seok

2012-01-01

In the field of nuclear engineering, recent regulatory audit calculations of large break loss of coolant accident (LBLOCA) have been performed with the best estimate code such as MARS, RELAP5 and CATHARE. Since the credible regulatory audit calculation is very important in the evaluation of the safety of the nuclear power plant (NPP), there have been many researches to develop rules and methodologies for the use of best estimate codes. One of the major points is to develop the best estimate plus uncertainty (BEPU) method for uncertainty analysis. As a representative BEPU method, NRC proposes the CSAU (Code scaling, applicability and uncertainty) methodology, which clearly identifies the different steps necessary for an uncertainty analysis. The general idea is 1) to determine all the sources of uncertainty in the code, also called basic uncertainties, 2) quantify them and 3) combine them in order to obtain the final uncertainty for the studied application. Using the uncertainty analysis such as CSAU methodology, an uncertainty band for the code response (calculation result), important from the safety point of view is calculated and the safety margin of the NPP is quantified. An example of such a response is the peak cladding temperature (PCT) for a LBLOCA. However, there is a problem in the uncertainty analysis with the best estimate codes. Generally, it is very difficult to determine the uncertainties due to the empiricism of closure laws (also called correlations or constitutive relationships). So far the only proposed approach is based on the expert judgment. For this case, the uncertainty range of important parameters can be wide and inaccurate so that the confidence level of the BEPU calculation results can be decreased. In order to solve this problem, recently CEA (France) proposes a statistical method of data analysis, called CIRCE. The CIRCE method is intended to quantify the uncertainties of the correlations of a code. It may replace the expert judgment

Characterizing spatial uncertainty when integrating social data in conservation planning.

Science.gov (United States)

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

2014-12-01

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

Outcome and value uncertainties in global-change policy

International Nuclear Information System (INIS)

Hammitt, J.K.

1995-01-01

Choices among environmental policies can be informed by analysis of the potential physical, biological, and social outcomes of alternative choices, and analysis of social preferences among these outcomes. Frequently, however, the consequences of alternative policies cannot be accurately predicted because of substantial outcome uncertainties concerning physical, chemical, biological, and social processes linking policy choices to consequences. Similarly, assessments of social preferences among alternative outcomes are limited by value uncertainties arising from limitations of moral principles, the absence of economic markets for many environmental attributes, and other factors. Outcome and value uncertainties relevant to global-change policy are described and their magnitudes are examined for two cases: stratospheric-ozone depletion and global climate change. Analysis of information available in the mid 1980s, when international ozone regulations were adopted, suggests that contemporary uncertainties surrounding CFC emissions and the atmospheric response were so large that plausible ozone depletion, absent regulation, ranged from negligible to catastrophic, a range that exceeded the plausible effect of the regulations considered. Analysis of climate change suggests that, important as outcome uncertainties are, uncertainties about values may be even more important for policy choice. 53 refs., 3 figs., 3 tabs

Evaluating data worth for ground-water management under uncertainty

Science.gov (United States)

Wagner, B.J.

1999-01-01

A decision framework is presented for assessing the value of ground-water sampling within the context of ground-water management under uncertainty. The framework couples two optimization models-a chance-constrained ground-water management model and an integer-programing sampling network design model-to identify optimal pumping and sampling strategies. The methodology consists of four steps: (1) The optimal ground-water management strategy for the present level of model uncertainty is determined using the chance-constrained management model; (2) for a specified data collection budget, the monitoring network design model identifies, prior to data collection, the sampling strategy that will minimize model uncertainty; (3) the optimal ground-water management strategy is recalculated on the basis of the projected model uncertainty after sampling; and (4) the worth of the monitoring strategy is assessed by comparing the value of the sample information-i.e., the projected reduction in management costs-with the cost of data collection. Steps 2-4 are repeated for a series of data collection budgets, producing a suite of management/monitoring alternatives, from which the best alternative can be selected. A hypothetical example demonstrates the methodology's ability to identify the ground-water sampling strategy with greatest net economic benefit for ground-water management.A decision framework is presented for assessing the value of ground-water sampling within the context of ground-water management under uncertainty. The framework couples two optimization models - a chance-constrained ground-water management model and an integer-programming sampling network design model - to identify optimal pumping and sampling strategies. The methodology consists of four steps: (1) The optimal ground-water management strategy for the present level of model uncertainty is determined using the chance-constrained management model; (2) for a specified data collection budget, the monitoring

Application of intelligence based uncertainty analysis for HLW disposal

International Nuclear Information System (INIS)

Kato, Kazuyuki

2003-01-01

Safety assessment for geological disposal of high level radioactive waste inevitably involves factors that cannot be specified in a deterministic manner. These are namely: (1) 'variability' that arises from stochastic nature of the processes and features considered, e.g., distribution of canister corrosion times and spatial heterogeneity of a host geological formation; (2) 'ignorance' due to incomplete or imprecise knowledge of the processes and conditions expected in the future, e.g., uncertainty in the estimation of solubilities and sorption coefficients for important nuclides. In many cases, a decision in assessment, e.g., selection among model options or determination of a parameter value, is subjected to both variability and ignorance in a combined form. It is clearly important to evaluate both influences of variability and ignorance on the result of a safety assessment in a consistent manner. We developed a unified methodology to handle variability and ignorance by using probabilistic and possibilistic techniques respectively. The methodology has been applied to safety assessment of geological disposal of high level radioactive waste. Uncertainties associated with scenarios, models and parameters were defined in terms of fuzzy membership functions derived through a series of interviews to the experts while variability was formulated by means of probability density functions (pdfs) based on available data set. The exercise demonstrated applicability of the new methodology and, in particular, its advantage in quantifying uncertainties based on expert's opinion and in providing information on dependence of assessment result on the level of conservatism. In addition, it was also shown that sensitivity analysis could identify key parameters in reducing uncertainties associated with the overall assessment. The above information can be used to support the judgment process and guide the process of disposal system development in optimization of protection against

Reusable launch vehicle model uncertainties impact analysis

Science.gov (United States)

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).

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

Science.gov (United States)

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

2017-01-01

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

CSAU (code scaling, applicability and uncertainty), a tool to prioritize advanced reactor research

International Nuclear Information System (INIS)

Wilson, G.E.; Boyack, B.E.

1990-01-01

Best Estimate computer codes have been accepted by the US 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. At the process level, the method is generic to any application which relies on best estimate computer code simulations to determine safe operating margins. 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. Applied early, during the period when alternate designs are being evaluated, the methodology can identify the relative importance of the sources of uncertainty in the knowledge of each plant behavior and, thereby, help prioritize the research needed to bring the new designs to fruition. 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. 9 refs., 1 fig., 1 tab

Exploring Uncertainty Perception as a Driver of Design Activity

DEFF Research Database (Denmark)

Cash, Philip; Kreye, Melanie

2018-01-01

, and representation action. We bring together prior works on uncertainty perception in the design and management literatures to derive three contributions. First, we describe how uncertainty perception is associated with activity progression, linking all three core actions. Second, we identify characteristic patterns...

Cultural diversity teaching and issues of uncertainty: the findings of a qualitative study.

Science.gov (United States)

Dogra, Nisha; Giordano, James; France, Nicholas

2007-04-26

There is considerable ambiguity in the subjective dimensions that comprise much of the relational dynamic of the clinical encounter. Comfort with this ambiguity, and recognition of the potential uncertainty of particular domains of medicine (e.g.--cultural factors of illness expression, value bias in diagnoses, etc) is an important facet of medical education. This paper begins by defining ambiguity and uncertainty as relevant to clinical practice. Studies have shown differing patterns of students' tolerance for ambiguity and uncertainty that appear to reflect extant attitudinal predispositions toward technology, objectivity, culture, value- and theory-ladeness, and the need for self-examination. This paper reports on those findings specifically related to the theme of uncertainty as relevant to teaching about cultural diversity. Its focus is to identify how and where the theme of certainty arose in the teaching and learning of cultural diversity, what were the attitudes toward this theme and topic, and how these attitudes and responses reflect and inform this area of medical pedagogy. A semi-structured interview was undertaken with 61 stakeholders (including policymakers, diversity teachers, students and users). The data were analysed and themes identified. There were diverse views about what the term cultural diversity means and what should constitute the cultural diversity curriculum. There was a need to provide certainty in teaching cultural diversity with diversity teachers feeling under considerable pressure to provide information. Students discomfort with uncertainty was felt to drive cultural diversity teaching towards factual emphasis rather than reflection or taking a patient centred approach. Students and faculty may feel that cultural diversity teaching is more about how to avoid professional, medico-legal pitfalls, rather than improving the patient experience or the patient-physician relationship. There may be pressure to imbue cultural diversity issues

Decay heat uncertainty quantification of MYRRHA

Directory of Open Access Journals (Sweden)

Fiorito Luca

2017-01-01

Full Text Available MYRRHA is a lead-bismuth cooled MOX-fueled accelerator driven system (ADS currently in the design phase at SCK·CEN in Belgium. The correct evaluation of the decay heat and of its uncertainty level is very important for the safety demonstration of the reactor. In the first part of this work we assessed the decay heat released by the MYRRHA core using the ALEPH-2 burnup code. The second part of the study focused on the nuclear data uncertainty and covariance propagation to the MYRRHA decay heat. Radioactive decay data, independent fission yield and cross section uncertainties/covariances were propagated using two nuclear data sampling codes, namely NUDUNA and SANDY. According to the results, 238U cross sections and fission yield data are the largest contributors to the MYRRHA decay heat uncertainty. The calculated uncertainty values are deemed acceptable from the safety point of view as they are well within the available regulatory limits.

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

Uncertainty in Measurement: A Review of Monte Carlo Simulation Using Microsoft Excel for the Calculation of Uncertainties Through Functional Relationships, Including Uncertainties in Empirically Derived Constants

Science.gov (United States)

Farrance, Ian; Frenkel, Robert

2014-01-01

The Guide to the Expression of Uncertainty in Measurement (usually referred to as the GUM) provides the basic framework for evaluating uncertainty in measurement. The GUM however does not always provide clearly identifiable procedures suitable for medical laboratory applications, particularly when internal quality control (IQC) is used to derive most of the uncertainty estimates. The GUM modelling approach requires advanced mathematical skills for many of its procedures, but Monte Carlo simulation (MCS) can be used as an alternative for many medical laboratory applications. In particular, calculations for determining how uncertainties in the input quantities to a functional relationship propagate through to the output can be accomplished using a readily available spreadsheet such as Microsoft Excel. The MCS procedure uses algorithmically generated pseudo-random numbers which are then forced to follow a prescribed probability distribution. When IQC data provide the uncertainty estimates the normal (Gaussian) distribution is generally considered appropriate, but MCS is by no means restricted to this particular case. With input variations simulated by random numbers, the functional relationship then provides the corresponding variations in the output in a manner which also provides its probability distribution. The MCS procedure thus provides output uncertainty estimates without the need for the differential equations associated with GUM modelling. The aim of this article is to demonstrate the ease with which Microsoft Excel (or a similar spreadsheet) can be used to provide an uncertainty estimate for measurands derived through a functional relationship. In addition, we also consider the relatively common situation where an empirically derived formula includes one or more ‘constants’, each of which has an empirically derived numerical value. Such empirically derived ‘constants’ must also have associated uncertainties which propagate through the functional

Uncertainty in measurement: a review of monte carlo simulation using microsoft excel for the calculation of uncertainties through functional relationships, including uncertainties in empirically derived constants.

Science.gov (United States)

Farrance, Ian; Frenkel, Robert

2014-02-01

The Guide to the Expression of Uncertainty in Measurement (usually referred to as the GUM) provides the basic framework for evaluating uncertainty in measurement. The GUM however does not always provide clearly identifiable procedures suitable for medical laboratory applications, particularly when internal quality control (IQC) is used to derive most of the uncertainty estimates. The GUM modelling approach requires advanced mathematical skills for many of its procedures, but Monte Carlo simulation (MCS) can be used as an alternative for many medical laboratory applications. In particular, calculations for determining how uncertainties in the input quantities to a functional relationship propagate through to the output can be accomplished using a readily available spreadsheet such as Microsoft Excel. The MCS procedure uses algorithmically generated pseudo-random numbers which are then forced to follow a prescribed probability distribution. When IQC data provide the uncertainty estimates the normal (Gaussian) distribution is generally considered appropriate, but MCS is by no means restricted to this particular case. With input variations simulated by random numbers, the functional relationship then provides the corresponding variations in the output in a manner which also provides its probability distribution. The MCS procedure thus provides output uncertainty estimates without the need for the differential equations associated with GUM modelling. The aim of this article is to demonstrate the ease with which Microsoft Excel (or a similar spreadsheet) can be used to provide an uncertainty estimate for measurands derived through a functional relationship. In addition, we also consider the relatively common situation where an empirically derived formula includes one or more 'constants', each of which has an empirically derived numerical value. Such empirically derived 'constants' must also have associated uncertainties which propagate through the functional relationship

arXiv Uncertainties in WIMP Dark Matter Scattering Revisited

CERN Document Server

Ellis, John; Olive, Keith A.

We revisit the uncertainties in the calculation of spin-independent scattering matrix elements for the scattering of WIMP dark matter particles on nuclear matter. In addition to discussing the uncertainties due to limitations in our knowledge of the nucleonic matrix elements of the light quark scalar densities , we also discuss the importances of heavy quark scalar densities , and comment on uncertainties in quark mass ratios. We analyze estimates of the light-quark densities made over the past decade using lattice calculations and/or phenomenological inputs. We find an uncertainty in the combination that is larger than has been assumed in some phenomenological analyses, and a range of that is smaller but compatible with earlier estimates. We also analyze the importance of the {\\cal O}(\\alpha_s^3) calculations of the heavy-quark matrix elements that are now available, which provide an important refinement of the calculation of the spin-independent scattering cross section. We use for illustration a benchmar...

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

Bayesian uncertainty analyses of probabilistic risk models

International Nuclear Information System (INIS)

Pulkkinen, U.

1989-01-01

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

Global Sensitivity Analysis and Estimation of Model Error, Toward Uncertainty Quantification in Scramjet Computations

Science.gov (United States)

Huan, Xun; Safta, Cosmin; Sargsyan, Khachik; Geraci, Gianluca; Eldred, Michael S.; Vane, Zachary P.; Lacaze, Guilhem; Oefelein, Joseph C.; Najm, Habib N.

2018-03-01

The development of scramjet engines is an important research area for advancing hypersonic and orbital flights. Progress toward optimal engine designs requires accurate flow simulations together with uncertainty quantification. However, performing uncertainty quantification for scramjet simulations is challenging due to the large number of uncertain parameters involved and the high computational cost of flow simulations. These difficulties are addressed in this paper by developing practical uncertainty quantification algorithms and computational methods, and deploying them in the current study to large-eddy simulations of a jet in crossflow inside a simplified HIFiRE Direct Connect Rig scramjet combustor. First, global sensitivity analysis is conducted to identify influential uncertain input parameters, which can help reduce the systems stochastic dimension. Second, because models of different fidelity are used in the overall uncertainty quantification assessment, a framework for quantifying and propagating the uncertainty due to model error is presented. These methods are demonstrated on a nonreacting jet-in-crossflow test problem in a simplified scramjet geometry, with parameter space up to 24 dimensions, using static and dynamic treatments of the turbulence subgrid model, and with two-dimensional and three-dimensional geometries.

Global Sensitivity Analysis and Estimation of Model Error, Toward Uncertainty Quantification in Scramjet Computations

Energy Technology Data Exchange (ETDEWEB)

Huan, Xun [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Safta, Cosmin [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Sargsyan, Khachik [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Geraci, Gianluca [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Eldred, Michael S. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Vane, Zachary P. [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Lacaze, Guilhem [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Oefelein, Joseph C. [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Najm, Habib N. [Sandia National Lab. (SNL-CA), Livermore, CA (United States)

2018-02-09

The development of scramjet engines is an important research area for advancing hypersonic and orbital flights. Progress toward optimal engine designs requires accurate flow simulations together with uncertainty quantification. However, performing uncertainty quantification for scramjet simulations is challenging due to the large number of uncertain parameters involved and the high computational cost of flow simulations. These difficulties are addressed in this paper by developing practical uncertainty quantification algorithms and computational methods, and deploying them in the current study to large-eddy simulations of a jet in crossflow inside a simplified HIFiRE Direct Connect Rig scramjet combustor. First, global sensitivity analysis is conducted to identify influential uncertain input parameters, which can help reduce the system’s stochastic dimension. Second, because models of different fidelity are used in the overall uncertainty quantification assessment, a framework for quantifying and propagating the uncertainty due to model error is presented. Finally, these methods are demonstrated on a nonreacting jet-in-crossflow test problem in a simplified scramjet geometry, with parameter space up to 24 dimensions, using static and dynamic treatments of the turbulence subgrid model, and with two-dimensional and three-dimensional geometries.

Quantifying uncertainty in NDSHA estimates due to earthquake catalogue

Science.gov (United States)

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

Methodology for qualitative uncertainty assessment of climate impact indicators

Science.gov (United States)

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

2016-04-01

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

Application of uncertainty and sensitivity analysis to the air quality SHERPA modelling tool

Science.gov (United States)

Pisoni, E.; Albrecht, D.; Mara, T. A.; Rosati, R.; Tarantola, S.; Thunis, P.

2018-06-01

Air quality has significantly improved in Europe over the past few decades. Nonetheless we still find high concentrations in measurements mainly in specific regions or cities. This dimensional shift, from EU-wide to hot-spot exceedances, calls for a novel approach to regional air quality management (to complement EU-wide existing policies). The SHERPA (Screening for High Emission Reduction Potentials on Air quality) modelling tool was developed in this context. It provides an additional tool to be used in support to regional/local decision makers responsible for the design of air quality plans. It is therefore important to evaluate the quality of the SHERPA model, and its behavior in the face of various kinds of uncertainty. Uncertainty and sensitivity analysis techniques can be used for this purpose. They both reveal the links between assumptions and forecasts, help in-model simplification and may highlight unexpected relationships between inputs and outputs. Thus, a policy steered SHERPA module - predicting air quality improvement linked to emission reduction scenarios - was evaluated by means of (1) uncertainty analysis (UA) to quantify uncertainty in the model output, and (2) by sensitivity analysis (SA) to identify the most influential input sources of this uncertainty. The results of this study provide relevant information about the key variables driving the SHERPA output uncertainty, and advise policy-makers and modellers where to place their efforts for an improved decision-making process.

Multimodel Uncertainty Changes in Simulated River Flows Induced by Human Impact Parameterizations

Science.gov (United States)

Liu, Xingcai; Tang, Qiuhong; Cui, Huijuan; Mu, Mengfei; Gerten Dieter; Gosling, Simon; Masaki, Yoshimitsu; Satoh, Yusuke; Wada, Yoshihide

2017-01-01

Human impacts increasingly affect the global hydrological cycle and indeed dominate hydrological changes in some regions. Hydrologists have sought to identify the human-impact-induced hydrological variations via parameterizing anthropogenic water uses in global hydrological models (GHMs). The consequently increased model complexity is likely to introduce additional uncertainty among GHMs. Here, using four GHMs, between-model uncertainties are quantified in terms of the ratio of signal to noise (SNR) for average river flow during 1971-2000 simulated in two experiments, with representation of human impacts (VARSOC) and without (NOSOC). It is the first quantitative investigation of between-model uncertainty resulted from the inclusion of human impact parameterizations. Results show that the between-model uncertainties in terms of SNRs in the VARSOC annual flow are larger (about 2 for global and varied magnitude for different basins) than those in the NOSOC, which are particularly significant in most areas of Asia and northern areas to the Mediterranean Sea. The SNR differences are mostly negative (-20 to 5, indicating higher uncertainty) for basin-averaged annual flow. The VARSOC high flow shows slightly lower uncertainties than NOSOC simulations, with SNR differences mostly ranging from -20 to 20. The uncertainty differences between the two experiments are significantly related to the fraction of irrigation areas of basins. The large additional uncertainties in VARSOC simulations introduced by the inclusion of parameterizations of human impacts raise the urgent need of GHMs development regarding a better understanding of human impacts. Differences in the parameterizations of irrigation, reservoir regulation and water withdrawals are discussed towards potential directions of improvements for future GHM development. We also discuss the advantages of statistical approaches to reduce the between-model uncertainties, and the importance of calibration of GHMs for not only

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

Uncertainties in projecting climate-change impacts in marine ecosystems

DEFF Research Database (Denmark)

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

2016-01-01

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

GRAPH THEORY APPROACH TO QUANTIFY UNCERTAINTY OF PERFORMANCE MEASURES

Directory of Open Access Journals (Sweden)

Sérgio D. Sousa

2015-03-01

Full Text Available In this work, the performance measurement process is studied to quantify the uncertainty induced in the resulting performance measure (PM. To that end, the causes of uncertainty are identified, analysing the activities undertaken in the three following stages of the performance measurement process: design and implementation, data collection and record, and determination and analysis. A quantitative methodology based on graph theory and on the sources of uncertainty of the performance measurement process is used to calculate an uncertainty index to evaluate the level of uncertainty of a given PM or (key performance indicator. An application example is presented. The quantification of PM uncertainty could contribute to better represent the risk associated with a given decision and also to improve the PM to increase its precision and reliability.

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

Science.gov (United States)

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

2016-12-01

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

Maximizing probable oil field profit: uncertainties on well spacing

International Nuclear Information System (INIS)

MacKay, J.A.; Lerche, I.

1997-01-01

The influence of uncertainties in field development costs, well costs, lifting costs, selling price, discount factor, and oil field reserves are evaluated for their impact on assessing probable ranges of uncertainty on present day worth (PDW), oil field lifetime τ 2/3 , optimum number of wells (OWI), and the minimum (n-) and maximum (n+) number of wells to produce a PDW ≥ O. The relative importance of different factors in contributing to the uncertainties in PDW, τ 2/3 , OWI, nsub(-) and nsub(+) is also analyzed. Numerical illustrations indicate how the maximum PDW depends on the ranges of parameter values, drawn from probability distributions using Monte Carlo simulations. In addition, the procedure illustrates the relative importance of contributions of individual factors to the total uncertainty, so that one can assess where to place effort to improve ranges of uncertainty; while the volatility of each estimate allows one to determine when such effort is needful. (author)

Finite Project Life and Uncertainty Effects on Investment

NARCIS (Netherlands)

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

2006-01-01

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

Treasury bond volatility and uncertainty about monetary policy

NARCIS (Netherlands)

Arnold, I.J.M.; Vrugt, E.B.

2010-01-01

We show that dispersion-based uncertainty about the future course of monetary policy is the single most important determinant of Treasury bond volatility across all maturities. The link between Treasury bond volatility and uncertainty about macroeconomic variables is much stronger than for the more

Branch-and-Bound algorithm applied to uncertainty quantification of a Boiling Water Reactor Station Blackout

International Nuclear Information System (INIS)

Nielsen, Joseph; Tokuhiro, Akira; Hiromoto, Robert; Tu, Lei

2015-01-01

Highlights: • Dynamic Event Tree solutions have been optimized using the Branch-and-Bound algorithm. • A 60% efficiency in optimization has been achieved. • Modeling uncertainty within a risk-informed framework is evaluated. - Abstract: Evaluation of the impacts of uncertainty and sensitivity in modeling presents a significant set of challenges in particular to high fidelity modeling. Computational costs and validation of models creates a need for cost effective decision making with regards to experiment design. Experiments designed to validate computation models can be used to reduce uncertainty in the physical model. In some cases, large uncertainty in a particular aspect of the model may or may not have a large impact on the final results. For example, modeling of a relief valve may result in large uncertainty, however, the actual effects on final peak clad temperature in a reactor transient may be small and the large uncertainty with respect to valve modeling may be considered acceptable. Additionally, the ability to determine the adequacy of a model and the validation supporting it should be considered within a risk informed framework. Low fidelity modeling with large uncertainty may be considered adequate if the uncertainty is considered acceptable with respect to risk. In other words, models that are used to evaluate the probability of failure should be evaluated more rigorously with the intent of increasing safety margin. Probabilistic risk assessment (PRA) techniques have traditionally been used to identify accident conditions and transients. Traditional classical event tree methods utilize analysts’ knowledge and experience to identify the important timing of events in coordination with thermal-hydraulic modeling. These methods lack the capability to evaluate complex dynamic systems. In these systems, time and energy scales associated with transient events may vary as a function of transition times and energies to arrive at a different physical

Branch-and-Bound algorithm applied to uncertainty quantification of a Boiling Water Reactor Station Blackout

Energy Technology Data Exchange (ETDEWEB)

Nielsen, Joseph, E-mail: joseph.nielsen@inl.gov [Idaho National Laboratory, 1955 N. Fremont Avenue, P.O. Box 1625, Idaho Falls, ID 83402 (United States); University of Idaho, Department of Mechanical Engineering and Nuclear Engineering Program, 1776 Science Center Drive, Idaho Falls, ID 83402-1575 (United States); Tokuhiro, Akira [University of Idaho, Department of Mechanical Engineering and Nuclear Engineering Program, 1776 Science Center Drive, Idaho Falls, ID 83402-1575 (United States); Hiromoto, Robert [University of Idaho, Department of Computer Science, 1776 Science Center Drive, Idaho Falls, ID 83402-1575 (United States); Tu, Lei [University of Idaho, Department of Mechanical Engineering and Nuclear Engineering Program, 1776 Science Center Drive, Idaho Falls, ID 83402-1575 (United States)

2015-12-15

Highlights: • Dynamic Event Tree solutions have been optimized using the Branch-and-Bound algorithm. • A 60% efficiency in optimization has been achieved. • Modeling uncertainty within a risk-informed framework is evaluated. - Abstract: Evaluation of the impacts of uncertainty and sensitivity in modeling presents a significant set of challenges in particular to high fidelity modeling. Computational costs and validation of models creates a need for cost effective decision making with regards to experiment design. Experiments designed to validate computation models can be used to reduce uncertainty in the physical model. In some cases, large uncertainty in a particular aspect of the model may or may not have a large impact on the final results. For example, modeling of a relief valve may result in large uncertainty, however, the actual effects on final peak clad temperature in a reactor transient may be small and the large uncertainty with respect to valve modeling may be considered acceptable. Additionally, the ability to determine the adequacy of a model and the validation supporting it should be considered within a risk informed framework. Low fidelity modeling with large uncertainty may be considered adequate if the uncertainty is considered acceptable with respect to risk. In other words, models that are used to evaluate the probability of failure should be evaluated more rigorously with the intent of increasing safety margin. Probabilistic risk assessment (PRA) techniques have traditionally been used to identify accident conditions and transients. Traditional classical event tree methods utilize analysts’ knowledge and experience to identify the important timing of events in coordination with thermal-hydraulic modeling. These methods lack the capability to evaluate complex dynamic systems. In these systems, time and energy scales associated with transient events may vary as a function of transition times and energies to arrive at a different physical

Uncertainty estimates for theoretical atomic and molecular data

International Nuclear Information System (INIS)

Chung, H-K; Braams, B J; Bartschat, K; Császár, A G; Drake, G W F; Kirchner, T; Kokoouline, V; Tennyson, J

2016-01-01

Sources of uncertainty are reviewed for calculated atomic and molecular data that are important for plasma modeling: atomic and molecular structures and cross sections for electron-atom, electron-molecule, and heavy particle collisions. We concentrate on model uncertainties due to approximations to the fundamental many-body quantum mechanical equations and we aim to provide guidelines to estimate uncertainties as a routine part of computations of data for structure and scattering. (topical review)

Information Theory for Correlation Analysis and Estimation of Uncertainty Reduction in Maps and Models

Directory of Open Access Journals (Sweden)

J. Florian Wellmann

2013-04-01

Full Text Available The quantification and analysis of uncertainties is important in all cases where maps and models of uncertain properties are the basis for further decisions. Once these uncertainties are identified, the logical next step is to determine how they can be reduced. Information theory provides a framework for the analysis of spatial uncertainties when different subregions are considered as random variables. In the work presented here, joint entropy, conditional entropy, and mutual information are applied for a detailed analysis of spatial uncertainty correlations. The aim is to determine (i which areas in a spatial analysis share information, and (ii where, and by how much, additional information would reduce uncertainties. As an illustration, a typical geological example is evaluated: the case of a subsurface layer with uncertain depth, shape and thickness. Mutual information and multivariate conditional entropies are determined based on multiple simulated model realisations. Even for this simple case, the measures not only provide a clear picture of uncertainties and their correlations but also give detailed insights into the potential reduction of uncertainties at each position, given additional information at a different location. The methods are directly applicable to other types of spatial uncertainty evaluations, especially where multiple realisations of a model simulation are analysed. In summary, the application of information theoretic measures opens up the path to a better understanding of spatial uncertainties, and their relationship to information and prior knowledge, for cases where uncertain property distributions are spatially analysed and visualised in maps and models.

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

International Nuclear Information System (INIS)

Povilaitis, Mantas; Kelm, Stephan; Urbonavičius, Egidijus

2017-01-01

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

Modeling Uncertainty in Climate Change: A Multi-Model Comparison

Energy Technology Data Exchange (ETDEWEB)

Gillingham, Kenneth; Nordhaus, William; Anthoff, David; Blanford, Geoffrey J.; Bosetti, Valentina; Christensen, Peter; McJeon, Haewon C.; Reilly, J. M.; Sztorc, Paul

2015-10-01

The economics of climate change involves a vast array of uncertainties, complicating both the analysis and development of climate policy. This study presents the results of the first comprehensive study of uncertainty in climate change using multiple integrated assessment models. The study looks at model and parametric uncertainties for population, total factor productivity, and climate sensitivity and estimates the pdfs of key output variables, including CO₂ concentrations, temperature, damages, and the social cost of carbon (SCC). One key finding is that parametric uncertainty is more important than uncertainty in model structure. Our resulting pdfs also provide insight on tail events.

Quantification of uncertainties of modeling and simulation

International Nuclear Information System (INIS)

Ma Zhibo; Yin Jianwei

2012-01-01

The principles of Modeling and Simulation (M and S) is interpreted by a functional relation, from which the total uncertainties of M and S are identified and sorted to three parts considered to vary along with the conceptual models' parameters. According to the idea of verification and validation, the space of the parameters is parted to verified and applied domains, uncertainties in the verified domain are quantified by comparison between numerical and standard results, and those in the applied domain are quantified by a newly developed extrapolating method. Examples are presented to demonstrate and qualify the ideas aimed to build a framework to quantify the uncertainties of M and S. (authors)

Uncertainty information in climate data records from Earth observation

Science.gov (United States)

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

Understanding the origin of Paris Agreement emission uncertainties.

Science.gov (United States)

Rogelj, Joeri; Fricko, Oliver; Meinshausen, Malte; Krey, Volker; Zilliacus, Johanna J J; Riahi, Keywan

2017-06-06

The UN Paris Agreement puts in place a legally binding mechanism to increase mitigation action over time. Countries put forward pledges called nationally determined contributions (NDC) whose impact is assessed in global stocktaking exercises. Subsequently, actions can then be strengthened in light of the Paris climate objective: limiting global mean temperature increase to well below 2 °C and pursuing efforts to limit it further to 1.5 °C. However, pledged actions are currently described ambiguously and this complicates the global stocktaking exercise. Here, we systematically explore possible interpretations of NDC assumptions, and show that this results in estimated emissions for 2030 ranging from 47 to 63 GtCO 2 e yr -1 . We show that this uncertainty has critical implications for the feasibility and cost to limit warming well below 2 °C and further to 1.5 °C. Countries are currently working towards clarifying the modalities of future NDCs. We identify salient avenues to reduce the overall uncertainty by about 10 percentage points through simple, technical clarifications regarding energy accounting rules. Remaining uncertainties depend to a large extent on politically valid choices about how NDCs are expressed, and therefore raise the importance of a thorough and robust process that keeps track of where emissions are heading over time.

Optimisation of decision making under uncertainty throughout field lifetime: A fractured reservoir example

Science.gov (United States)

Arnold, Dan; Demyanov, Vasily; Christie, Mike; Bakay, Alexander; Gopa, Konstantin

2016-10-01

Assessing the change in uncertainty in reservoir production forecasts over field lifetime is rarely undertaken because of the complexity of joining together the individual workflows. This becomes particularly important in complex fields such as naturally fractured reservoirs. The impact of this problem has been identified in previous and many solutions have been proposed but never implemented on complex reservoir problems due to the computational cost of quantifying uncertainty and optimising the reservoir development, specifically knowing how many and what kind of simulations to run. This paper demonstrates a workflow that propagates uncertainty throughout field lifetime, and into the decision making process by a combination of a metric-based approach, multi-objective optimisation and Bayesian estimation of uncertainty. The workflow propagates uncertainty estimates from appraisal into initial development optimisation, then updates uncertainty through history matching and finally propagates it into late-life optimisation. The combination of techniques applied, namely the metric approach and multi-objective optimisation, help evaluate development options under uncertainty. This was achieved with a significantly reduced number of flow simulations, such that the combined workflow is computationally feasible to run for a real-field problem. This workflow is applied to two synthetic naturally fractured reservoir (NFR) case studies in appraisal, field development, history matching and mid-life EOR stages. The first is a simple sector model, while the second is a more complex full field example based on a real life analogue. This study infers geological uncertainty from an ensemble of models that are based on the carbonate Brazilian outcrop which are propagated through the field lifetime, before and after the start of production, with the inclusion of production data significantly collapsing the spread of P10-P90 in reservoir forecasts. The workflow links uncertainty

Uncertainty of forest carbon stock changes. Implications to the total uncertainty of GHG inventory of Finland

International Nuclear Information System (INIS)

Monni, S.; Savolainen, I.; Peltoniemi, M.; Lehtonen, A.; Makipaa, R.; Palosuo, T.

2007-01-01

Uncertainty analysis facilitates identification of the most important categories affecting greenhouse gas (GHG) inventory uncertainty and helps in prioritisation of the efforts needed for development of the inventory. This paper presents an uncertainty analysis of GHG emissions of all Kyoto sectors and gases for Finland consolidated with estimates of emissions/removals from LULUCF categories. In Finland, net GHG emissions in 2003 were around 69 Tg (±15 Tg) CO2 equivalents. The uncertainties in forest carbon sink estimates in 2003 were larger than in most other emission categories, but of the same order of magnitude as in carbon stock change estimates in other land use, land-use change and forestry (LULUCF) categories, and in N2O emissions from agricultural soils. Uncertainties in sink estimates of 1990 were lower, due to better availability of data. Results of this study indicate that inclusion of the forest carbon sink to GHG inventories reported to the UNFCCC increases uncertainties in net emissions notably. However, the decrease in precision is accompanied by an increase in the accuracy of the overall net GHG emissions due to improved completeness of the inventory. The results of this study can be utilised when planning future GHG mitigation protocols and emission trading schemes and when analysing environmental benefits of climate conventions

Assessing framing of uncertainties in water management practice

NARCIS (Netherlands)

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

2009-01-01

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

Uncertainties in Forecasting Streamflow using Entropy Theory

Science.gov (United States)

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.

Practical Policy Applications of Uncertainty Analysis for National Greenhouse Gas Inventories

International Nuclear Information System (INIS)

Gillenwater, M.; Sussman, F.; Cohen, J.

2007-01-01

International policy makers and climate researchers use greenhouse gas emissions inventory estimates in a variety of ways. Because of the varied uses of the inventory data, as well as the high uncertainty surrounding some of the source category estimates, considerable effort has been devoted to understanding the causes and magnitude of uncertainty in national emissions inventories. In this paper, we focus on two aspects of the rationale for quantifying uncertainty: (1) the possible uses of the quantified uncertainty estimates for policy (e.g., as a means of adjusting inventories used to determine compliance with international commitments); and (2) the direct benefits of the process of investigating uncertainties in terms of improving inventory quality. We find that there are particular characteristics that an inventory uncertainty estimate should have if it is to be used for policy purposes: (1) it should be comparable across countries; (2) it should be relatively objective, or at least subject to review and verification; (3) it should not be subject to gaming by countries acting in their own self-interest; (4) it should be administratively feasible to estimate and use; (5) the quality of the uncertainty estimate should be high enough to warrant the additional compliance costs that its use in an adjustment factor may impose on countries; and (6) it should attempt to address all types of inventory uncertainty. Currently, inventory uncertainty estimates for national greenhouse gas inventories do not have these characteristics. For example, the information used to develop quantitative uncertainty estimates for national inventories is often based on expert judgments, which are, by definition, subjective rather than objective, and therefore difficult to review and compare. Further, the practical design of a potential factor to adjust inventory estimates using uncertainty estimates would require policy makers to (1) identify clear environmental goals; (2) define these

Practical Policy Applications of Uncertainty Analysis for National Greenhouse Gas Inventories

Energy Technology Data Exchange (ETDEWEB)

Gillenwater, M. [Environmental Resources Trust (United States)], E-mail: mgillenwater@ert.net; Sussman, F.; Cohen, J. [ICF International (United States)

2007-09-15

International policy makers and climate researchers use greenhouse gas emissions inventory estimates in a variety of ways. Because of the varied uses of the inventory data, as well as the high uncertainty surrounding some of the source category estimates, considerable effort has been devoted to understanding the causes and magnitude of uncertainty in national emissions inventories. In this paper, we focus on two aspects of the rationale for quantifying uncertainty: (1) the possible uses of the quantified uncertainty estimates for policy (e.g., as a means of adjusting inventories used to determine compliance with international commitments); and (2) the direct benefits of the process of investigating uncertainties in terms of improving inventory quality. We find that there are particular characteristics that an inventory uncertainty estimate should have if it is to be used for policy purposes: (1) it should be comparable across countries; (2) it should be relatively objective, or at least subject to review and verification; (3) it should not be subject to gaming by countries acting in their own self-interest; (4) it should be administratively feasible to estimate and use; (5) the quality of the uncertainty estimate should be high enough to warrant the additional compliance costs that its use in an adjustment factor may impose on countries; and (6) it should attempt to address all types of inventory uncertainty. Currently, inventory uncertainty estimates for national greenhouse gas inventories do not have these characteristics. For example, the information used to develop quantitative uncertainty estimates for national inventories is often based on expert judgments, which are, by definition, subjective rather than objective, and therefore difficult to review and compare. Further, the practical design of a potential factor to adjust inventory estimates using uncertainty estimates would require policy makers to (1) identify clear environmental goals; (2) define these

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

International Nuclear Information System (INIS)

Ahn, Kwang Il; Yang, Joon Eon

2003-01-01

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

PREMIUM - Benchmark on the quantification of the uncertainty of the physical models in the system thermal-hydraulic codes

International Nuclear Information System (INIS)

Skorek, Tomasz; Crecy, Agnes de

2013-01-01

PREMIUM (Post BEMUSE Reflood Models Input Uncertainty Methods) is an activity launched with the aim to push forward the methods of quantification of physical models uncertainties in thermal-hydraulic codes. It is endorsed by OECD/NEA/CSNI/WGAMA. The benchmark PREMIUM is addressed to all who applies uncertainty evaluation methods based on input uncertainties quantification and propagation. The benchmark is based on a selected case of uncertainty analysis application to the simulation of quench front propagation in an experimental test facility. Application to an experiment enables evaluation and confirmation of the quantified probability distribution functions on the basis of experimental data. The scope of the benchmark comprises a review of the existing methods, selection of potentially important uncertain input parameters, preliminary quantification of the ranges and distributions of the identified parameters, evaluation of the probability density function using experimental results of tests performed on FEBA test facility and confirmation/validation of the performed quantification on the basis of blind calculation of Reflood 2-D PERICLES experiment. (authors)

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

Energy Technology Data Exchange (ETDEWEB)

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

1997-12-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

1998-04-01

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

Climate change decision-making: Model & parameter uncertainties explored

Energy Technology Data Exchange (ETDEWEB)

Dowlatabadi, H.; Kandlikar, M.; Linville, C.

1995-12-31

A critical aspect of climate change decision-making is uncertainties in current understanding of the socioeconomic, climatic and biogeochemical processes involved. Decision-making processes are much better informed if these uncertainties are characterized and their implications understood. Quantitative analysis of these uncertainties serve to inform decision makers about the likely outcome of policy initiatives, and help set priorities for research so that outcome ambiguities faced by the decision-makers are reduced. A family of integrated assessment models of climate change have been developed at Carnegie Mellon. These models are distinguished from other integrated assessment efforts in that they were designed from the outset to characterize and propagate parameter, model, value, and decision-rule uncertainties. The most recent of these models is ICAM 2.1. This model includes representation of the processes of demographics, economic activity, emissions, atmospheric chemistry, climate and sea level change and impacts from these changes and policies for emissions mitigation, and adaptation to change. The model has over 800 objects of which about one half are used to represent uncertainty. In this paper we show, that when considering parameter uncertainties, the relative contribution of climatic uncertainties are most important, followed by uncertainties in damage calculations, economic uncertainties and direct aerosol forcing uncertainties. When considering model structure uncertainties we find that the choice of policy is often dominated by model structure choice, rather than parameter uncertainties.

Evaluating measurement uncertainty in fluid phase equilibrium calculations

Science.gov (United States)

van der Veen, Adriaan M. H.

2018-04-01

The evaluation of measurement uncertainty in accordance with the ‘Guide to the expression of uncertainty in measurement’ (GUM) has not yet become widespread in physical chemistry. With only the law of the propagation of uncertainty from the GUM, many of these uncertainty evaluations would be cumbersome, as models are often non-linear and require iterative calculations. The methods from GUM supplements 1 and 2 enable the propagation of uncertainties under most circumstances. Experimental data in physical chemistry are used, for example, to derive reference property data and support trade—all applications where measurement uncertainty plays an important role. This paper aims to outline how the methods for evaluating and propagating uncertainty can be applied to some specific cases with a wide impact: deriving reference data from vapour pressure data, a flash calculation, and the use of an equation-of-state to predict the properties of both phases in a vapour-liquid equilibrium. The three uncertainty evaluations demonstrate that the methods of GUM and its supplements are a versatile toolbox that enable us to evaluate the measurement uncertainty of physical chemical measurements, including the derivation of reference data, such as the equilibrium thermodynamical properties of fluids.

Methods for handling uncertainty within pharmaceutical funding decisions

Science.gov (United States)

Stevenson, Matt; Tappenden, Paul; Squires, Hazel

2014-01-01

This article provides a position statement regarding decision making under uncertainty within the economic evaluation of pharmaceuticals, with a particular focus upon the National Institute for Health and Clinical Excellence context within England and Wales. This area is of importance as funding agencies have a finite budget from which to purchase a selection of competing health care interventions. The objective function generally used is that of maximising societal health with an explicit acknowledgement that there will be opportunity costs associated with purchasing a particular intervention. Three components of uncertainty are discussed within a pharmaceutical funding perspective: methodological uncertainty, parameter uncertainty and structural uncertainty, alongside a discussion of challenges that are particularly pertinent to health economic evaluation. The discipline has focused primarily on handling methodological and parameter uncertainty and a clear reference case has been developed for consistency across evaluations. However, uncertainties still remain. Less attention has been given to methods for handling structural uncertainty. The lack of adequate methods to explicitly incorporate this aspect of model development may result in the true uncertainty surrounding health care investment decisions being underestimated. Research in this area is ongoing as we review.

Evaluation of advanced coal gasification combined-cycle systems under uncertainty

International Nuclear Information System (INIS)

Frey, H.C.; Rubin, E.S.

1992-01-01

Advanced integrated gasification combined cycle (IGCC) systems have not been commercially demonstrated, and uncertainties remain regarding their commercial-scale performance and cost. Therefore, a probabilistic evaluation method has been developed and applied to explicitly consider these uncertainties. The insights afforded by this method are illustrated for an IGCC design featuring a fixed-bed gasifier and a hot gas cleanup system. Detailed case studies are conducted to characterize uncertainties in key measures of process performance and cost, evaluate design trade-offs under uncertainty, identify research priorities, evaluate the potential benefits of additional research, compare results for different uncertainty assumptions, and compare the advanced IGCC system to a conventional system under uncertainty. The implications of probabilistic results for research planning and technology selection are discussed in this paper

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

Piezoelectric energy harvesting with parametric uncertainty

International Nuclear Information System (INIS)

Ali, S F; Friswell, M I; Adhikari, S

2010-01-01

The design and analysis of energy harvesting devices is becoming increasing important in recent years. Most of the literature has focused on the deterministic analysis of these systems and the problem of uncertain parameters has received less attention. Energy harvesting devices exhibit parametric uncertainty due to errors in measurement, errors in modelling and variability in the parameters during manufacture. This paper investigates the effect of parametric uncertainty in the mechanical system on the harvested power, and derives approximate explicit formulae for the optimal electrical parameters that maximize the mean harvested power. The maximum of the mean harvested power decreases with increasing uncertainty, and the optimal frequency at which the maximum mean power occurs shifts. The effect of the parameter variance on the optimal electrical time constant and optimal coupling coefficient are reported. Monte Carlo based simulation results are used to further analyse the system under parametric uncertainty

Understanding uncertainty

CERN Document Server

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.

Importance of tree basic density in biomass estimation and associated uncertainties

DEFF Research Database (Denmark)

Njana, Marco Andrew; Meilby, Henrik; Eid, Tron

2016-01-01

Key message Aboveground and belowground tree basic densities varied between and within the three mangrove species. If appropriately determined and applied, basic density may be useful in estimation of tree biomass. Predictive accuracy of the common (i.e. multi-species) models including aboveground...... of sustainable forest management, conservation and enhancement of carbon stocks (REDD+) initiatives offer an opportunity for sustainable management of forests including mangroves. In carbon accounting for REDD+, it is required that carbon estimates prepared for monitoring reporting and verification schemes...... and examine uncertainties in estimation of tree biomass using indirect methods. Methods This study focused on three dominant mangrove species (Avicennia marina (Forssk.) Vierh, Sonneratia alba J. Smith and Rhizophora mucronata Lam.) in Tanzania. A total of 120 trees were destructively sampled for aboveground...

Uncertainties in extreme precipitation under climate change conditions

DEFF Research Database (Denmark)

Sunyer Pinya, Maria Antonia

of adaptation strategies, but these changes are subject to uncertainties. The focus of this PhD thesis is the quantification of uncertainties in changes in extreme precipitation. It addresses two of the main sources of uncertainty in climate change impact studies: regional climate models (RCMs) and statistical...... downscaling methods (SDMs). RCMs provide information on climate change at the regional scale. SDMs are used to bias-correct and downscale the outputs of the RCMs to the local scale of interest in adaptation strategies. In the first part of the study, a multi-model ensemble of RCMs from the European ENSEMBLES...... project was used to quantify the uncertainty in RCM projections over Denmark. Three aspects of the RCMs relevant for the uncertainty quantification were first identified and investigated. These are: the interdependency of the RCMs; the performance in current climate; and the change in the performance...

Report of a CSNI workshop on uncertainty analysis methods. Volume 1 + 2

International Nuclear Information System (INIS)

Wickett, A.J.; Yadigaroglu, G.

1994-08-01

The OECD NEA CSNI Principal Working Group 2 (PWG2) Task Group on Thermal Hydraulic System Behaviour (TGTHSB) has, in recent years, received presentations of a variety of different methods to analyze the uncertainty in the calculations of advanced unbiased (best estimate) codes. Proposals were also made for an International Standard Problem (ISP) to compare the uncertainty analysis methods. The objectives for the Workshop were to discuss and fully understand the principles of uncertainty analysis relevant to LOCA modelling and like problems, to examine the underlying issues from first principles, in preference to comparing and contrasting the currently proposed methods, to reach consensus on the issues identified as far as possible while not avoiding the controversial aspects, to identify as clearly as possible unreconciled differences, and to issue a Status Report. Eight uncertainty analysis methods were presented. A structured discussion of various aspects of uncertainty analysis followed - the need for uncertainty analysis, identification and ranking of uncertainties, characterisation, quantification and combination of uncertainties and applications, resources and future developments. As a result, the objectives set out above were, to a very large extent, achieved. Plans for the ISP were also discussed. Volume 1 contains a record of the discussions on uncertainty methods. Volume 2 is a compilation of descriptions of the eight uncertainty analysis methods presented at the workshop

Predicting ecological responses in a changing ocean: the effects of future climate uncertainty.

Science.gov (United States)

Freer, Jennifer J; Partridge, Julian C; Tarling, Geraint A; Collins, Martin A; Genner, Martin J

2018-01-01

Predicting how species will respond to climate change is a growing field in marine ecology, yet knowledge of how to incorporate the uncertainty from future climate data into these predictions remains a significant challenge. To help overcome it, this review separates climate uncertainty into its three components (scenario uncertainty, model uncertainty, and internal model variability) and identifies four criteria that constitute a thorough interpretation of an ecological response to climate change in relation to these parts (awareness, access, incorporation, communication). Through a literature review, the extent to which the marine ecology community has addressed these criteria in their predictions was assessed. Despite a high awareness of climate uncertainty, articles favoured the most severe emission scenario, and only a subset of climate models were used as input into ecological analyses. In the case of sea surface temperature, these models can have projections unrepresentative against a larger ensemble mean. Moreover, 91% of studies failed to incorporate the internal variability of a climate model into results. We explored the influence that the choice of emission scenario, climate model, and model realisation can have when predicting the future distribution of the pelagic fish, Electrona antarctica . Future distributions were highly influenced by the choice of climate model, and in some cases, internal variability was important in determining the direction and severity of the distribution change. Increased clarity and availability of processed climate data would facilitate more comprehensive explorations of climate uncertainty, and increase in the quality and standard of marine prediction studies.

Identifying important motivational factors for professionals in Greek hospitals

Science.gov (United States)

Kontodimopoulos, Nick; Paleologou, Victoria; Niakas, Dimitris

2009-01-01

Background The purpose of this study was to identify important motivational factors according to the views of health-care professionals in Greek hospitals and particularly to determine if these might differ in the public and private sectors. Methods A previously developed -and validated- instrument addressing four work-related motivators (job attributes, remuneration, co-workers and achievements) was used. Three categories of health care professionals, doctors (N = 354), nurses (N = 581) and office workers (N = 418), working in public and private hospitals, participated and motivation was compared across socio-demographic and occupational variables. Results The range of reported motivational factors was mixed and Maslow's conclusions that lower level motivational factors must be met before ascending to the next level were not confirmed. The highest ranked motivator for the entire sample, and by professional subgroup, was achievements (P motivators were similar, and only one significant difference was observed, namely between doctors and nurses in respect to co-workers (P motivated by all factors significantly more than their public-hospital counterparts. Conclusion The results are in agreement with the literature which focuses attention to management approaches employing both monetary and non-monetary incentives to motivate health care workers. This study showed that intrinsic factors are particularly important and should become a target for effective employee motivation. PMID:19754968

Cultural diversity teaching and issues of uncertainty: the findings of a qualitative study

Directory of Open Access Journals (Sweden)

Giordano James

2007-04-01

Full Text Available Abstract Background There is considerable ambiguity in the subjective dimensions that comprise much of the relational dynamic of the clinical encounter. Comfort with this ambiguity, and recognition of the potential uncertainty of particular domains of medicine (e.g. – cultural factors of illness expression, value bias in diagnoses, etc is an important facet of medical education. This paper begins by defining ambiguity and uncertainty as relevant to clinical practice. Studies have shown differing patterns of students' tolerance for ambiguity and uncertainty that appear to reflect extant attitudinal predispositions toward technology, objectivity, culture, value- and theory-ladeness, and the need for self-examination. This paper reports on those findings specifically related to the theme of uncertainty as relevant to teaching about cultural diversity. Its focus is to identify how and where the theme of certainty arose in the teaching and learning of cultural diversity, what were the attitudes toward this theme and topic, and how these attitudes and responses reflect and inform this area of medical pedagogy. Methods A semi-structured interview was undertaken with 61 stakeholders (including policymakers, diversity teachers, students and users. The data were analysed and themes identified. Results There were diverse views about what the term cultural diversity means and what should constitute the cultural diversity curriculum. There was a need to provide certainty in teaching cultural diversity with diversity teachers feeling under considerable pressure to provide information. Students discomfort with uncertainty was felt to drive cultural diversity teaching towards factual emphasis rather than reflection or taking a patient centred approach. Conclusion Students and faculty may feel that cultural diversity teaching is more about how to avoid professional, medico-legal pitfalls, rather than improving the patient experience or the patient

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.

Biosphere dose conversion Factor Importance and Sensitivity Analysis

International Nuclear Information System (INIS)

M. Wasiolek

2004-01-01

This report presents importance and sensitivity analysis for the environmental radiation model for Yucca Mountain, Nevada (ERMYN). ERMYN is a biosphere model supporting the total system performance assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis concerns the output of the model, biosphere dose conversion factors (BDCFs) for the groundwater, and the volcanic ash exposure scenarios. It identifies important processes and parameters that influence the BDCF values and distributions, enhances understanding of the relative importance of the physical and environmental processes on the outcome of the biosphere model, includes a detailed pathway analysis for key radionuclides, and evaluates the appropriateness of selected parameter values that are not site-specific or have large uncertainty

Uncertainty principle for angular position and angular momentum

International Nuclear Information System (INIS)

Franke-Arnold, Sonja; Barnett, Stephen M; Yao, Eric; Leach, Jonathan; Courtial, Johannes; Padgett, Miles

2004-01-01

The uncertainty principle places fundamental limits on the accuracy with which we are able to measure the values of different physical quantities (Heisenberg 1949 The Physical Principles of the Quantum Theory (New York: Dover); Robertson 1929 Phys. Rev. 34 127). This has profound effects not only on the microscopic but also on the macroscopic level of physical systems. The most familiar form of the uncertainty principle relates the uncertainties in position and linear momentum. Other manifestations include those relating uncertainty in energy to uncertainty in time duration, phase of an electromagnetic field to photon number and angular position to angular momentum (Vaccaro and Pegg 1990 J. Mod. Opt. 37 17; Barnett and Pegg 1990 Phys. Rev. A 41 3427). In this paper, we report the first observation of the last of these uncertainty relations and derive the associated states that satisfy the equality in the uncertainty relation. We confirm the form of these states by detailed measurement of the angular momentum of a light beam after passage through an appropriate angular aperture. The angular uncertainty principle applies to all physical systems and is particularly important for systems with cylindrical symmetry

Optical Model and Cross Section Uncertainties

Energy Technology Data Exchange (ETDEWEB)

Herman,M.W.; Pigni, M.T.; Dietrich, F.S.; Oblozinsky, P.

2009-10-05

Distinct minima and maxima in the neutron total cross section uncertainties were observed in model calculations using spherical optical potential. We found this oscillating structure to be a general feature of quantum mechanical wave scattering. Specifically, we analyzed neutron interaction with 56Fe from 1 keV up to 65 MeV, and investigated physical origin of the minima.We discuss their potential importance for practical applications as well as the implications for the uncertainties in total and absorption cross sections.

Evaluating Predictive Uncertainty of Hyporheic Exchange Modelling

Science.gov (United States)

Chow, R.; Bennett, J.; Dugge, J.; Wöhling, T.; Nowak, W.

2017-12-01

Hyporheic exchange is the interaction of water between rivers and groundwater, and is difficult to predict. One of the largest contributions to predictive uncertainty for hyporheic fluxes have been attributed to the representation of heterogeneous subsurface properties. This research aims to evaluate which aspect of the subsurface representation - the spatial distribution of hydrofacies or the model for local-scale (within-facies) heterogeneity - most influences the predictive uncertainty. Also, we seek to identify data types that help reduce this uncertainty best. For this investigation, we conduct a modelling study of the Steinlach River meander, in Southwest Germany. The Steinlach River meander is an experimental site established in 2010 to monitor hyporheic exchange at the meander scale. We use HydroGeoSphere, a fully integrated surface water-groundwater model, to model hyporheic exchange and to assess the predictive uncertainty of hyporheic exchange transit times (HETT). A highly parameterized complex model is built and treated as `virtual reality', which is in turn modelled with simpler subsurface parameterization schemes (Figure). Then, we conduct Monte-Carlo simulations with these models to estimate the predictive uncertainty. Results indicate that: Uncertainty in HETT is relatively small for early times and increases with transit times. Uncertainty from local-scale heterogeneity is negligible compared to uncertainty in the hydrofacies distribution. Introducing more data to a poor model structure may reduce predictive variance, but does not reduce predictive bias. Hydraulic head observations alone cannot constrain the uncertainty of HETT, however an estimate of hyporheic exchange flux proves to be more effective at reducing this uncertainty. Figure: Approach for evaluating predictive model uncertainty. A conceptual model is first developed from the field investigations. A complex model (`virtual reality') is then developed based on that conceptual model

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

Field manual for identifying and preserving high-water mark data

Science.gov (United States)

Feaster, Toby D.; Koenig, Todd A.

2017-09-26

This field manual provides general guidance for identifying and collecting high-water marks and is meant to be used by field personnel as a quick reference. The field manual describes purposes for collecting and documenting high-water marks along with the most common types of high-water marks. The manual provides a list of suggested field equipment, describes rules of thumb and best practices for finding high-water marks, and describes the importance of evaluating each high-water mark and assigning a numeric uncertainty value as part of the flagging process. The manual also includes an appendix of photographs of a variety of high-water marks obtained from various U.S. Geological Survey field investigations along with general comments about the logic for the assigned uncertainty values.

Communicating and dealing with uncertainty in general practice: the association with neuroticism.

Directory of Open Access Journals (Sweden)

Antonius Schneider

Full Text Available Diagnostic reasoning in primary care setting where presented problems and patients are mostly unselected appears as a complex process. The aim was to develop a questionnaire to describe how general practitioners (GPs deal with uncertainty to gain more insight into the decisional process. The association of personality traits with medical decision making was investigated additionally.Raw items were identified by literature research and focus group. Items were improved by interviewing ten GPs with thinking-aloud-method. A personal case vignette related to a complex and uncertainty situation was introduced. The final questionnaire was administered to 228 GPs in Germany. Factorial validity was calculated with explorative and confirmatory factor analysis. The results of the Communicating and Dealing with Uncertainty (CoDU-questionnaire were compared with the scales of the 'Physician Reaction to Uncertainty' (PRU questionnaire and with the personality traits which were determined with the Big Five Inventory (BFI-K.The items could be assigned to four scales with varying internal consistency, namely 'communicating uncertainty' (Cronbach alpha 0.79, 'diagnostic action' (0.60, 'intuition' (0.39 and 'extended social anamnesis' (0.69. Neuroticism was positively associated with all PRU scales 'anxiety due to uncertainty' (Pearson correlation 0.487, 'concerns about bad outcomes' (0.488, 'reluctance to disclose uncertainty to patients' (0.287, 'reluctance to disclose mistakes to physicians' (0.212 and negatively associated with the CoDU scale 'communicating uncertainty' (-0.242 (p<0.01 for all. 'Extraversion' (0.146; p<0.05, 'agreeableness' (0.145, p<0.05, 'conscientiousness' (0.168, p<0.05 and 'openness to experience' (0.186, p<0.01 were significantly positively associated with 'communicating uncertainty'. 'Extraversion' (0.162, 'consciousness' (0.158 and 'openness to experience' (0.155 were associated with 'extended social anamnesis' (p<0.05.The

The characterisation and evaluation of uncertainty in probabilistic risk analysis

International Nuclear Information System (INIS)

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

1980-10-01

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

Position-momentum uncertainty relations in the presence of quantum memory

DEFF Research Database (Denmark)

Furrer, Fabian; Berta, Mario; Tomamichel, Marco

2014-01-01

A prominent formulation of the uncertainty principle identifies the fundamental quantum feature that no particle may be prepared with certain outcomes for both position and momentum measurements. Often the statistical uncertainties are thereby measured in terms of entropies providing a clear oper....... As an illustration, we evaluate the uncertainty relations for position and momentum measurements, which is operationally significant in that it implies security of a quantum key distribution scheme based on homodyne detection of squeezed Gaussian states....

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

Decision Making Under Uncertainty

Science.gov (United States)

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

Investments in technology subject to uncertainty. Analysis and policy

DEFF Research Database (Denmark)

Pedersen, Jørgen Lindgaard

1997-01-01

Investments in technology are today of such a magnitude that it matters. In the paper there are three important questions. First on the question in which sense technological uncertainty can be said to be a problem. Second on strategies for diminishing technological uncertainties. Three on policy...

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...

Quantifying and managing uncertainty in operational modal analysis

Science.gov (United States)

Au, Siu-Kui; Brownjohn, James M. W.; Mottershead, John E.

2018-03-01

Operational modal analysis aims at identifying the modal properties (natural frequency, damping, etc.) of a structure using only the (output) vibration response measured under ambient conditions. Highly economical and feasible, it is becoming a common practice in full-scale vibration testing. In the absence of (input) loading information, however, the modal properties have significantly higher uncertainty than their counterparts identified from free or forced vibration (known input) tests. Mastering the relationship between identification uncertainty and test configuration is of great interest to both scientists and engineers, e.g., for achievable precision limits and test planning/budgeting. Addressing this challenge beyond the current state-of-the-art that are mostly concerned with identification algorithms, this work obtains closed form analytical expressions for the identification uncertainty (variance) of modal parameters that fundamentally explains the effect of test configuration. Collectively referred as 'uncertainty laws', these expressions are asymptotically correct for well-separated modes, small damping and long data; and are applicable under non-asymptotic situations. They provide a scientific basis for planning and standardization of ambient vibration tests, where factors such as channel noise, sensor number and location can be quantitatively accounted for. The work is reported comprehensively with verification through synthetic and experimental data (laboratory and field), scientific implications and practical guidelines for planning ambient vibration tests.

Decay heat uncertainty quantification of MYRRHA

OpenAIRE

Fiorito Luca; Buss Oliver; Hoefer Axel; Stankovskiy Alexey; Eynde Gert Van den

2017-01-01

MYRRHA is a lead-bismuth cooled MOX-fueled accelerator driven system (ADS) currently in the design phase at SCK·CEN in Belgium. The correct evaluation of the decay heat and of its uncertainty level is very important for the safety demonstration of the reactor. In the first part of this work we assessed the decay heat released by the MYRRHA core using the ALEPH-2 burnup code. The second part of the study focused on the nuclear data uncertainty and covariance propagation to the MYRRHA decay hea...

Estimating the uncertainty from sampling in pollution crime investigation: The importance of metrology in the forensic interpretation of environmental data.

Science.gov (United States)

Barazzetti Barbieri, Cristina; de Souza Sarkis, Jorge Eduardo

2018-07-01

The forensic interpretation of environmental analytical data is usually challenging due to the high geospatial variability of these data. The measurements' uncertainty includes contributions from the sampling and from the sample handling and preparation processes. These contributions are often disregarded in analytical techniques results' quality assurance. A pollution crime investigation case was used to carry out a methodology able to address these uncertainties in two different environmental compartments, freshwater sediments and landfill leachate. The methodology used to estimate the uncertainty was the duplicate method (that replicates predefined steps of the measurement procedure in order to assess its precision) and the parameters used to investigate the pollution were metals (Cr, Cu, Ni, and Zn) in the leachate, the suspect source, and in the sediment, the possible sink. The metal analysis results were compared to statutory limits and it was demonstrated that Cr and Ni concentrations in sediment samples exceeded the threshold levels at all sites downstream the pollution sources, considering the expanded uncertainty U of the measurements and a probability of contamination >0.975, at most sites. Cu and Zn concentrations were above the statutory limits at two sites, but the classification was inconclusive considering the uncertainties of the measurements. Metal analyses in leachate revealed that Cr concentrations were above the statutory limits with a probability of contamination >0.975 in all leachate ponds while the Cu, Ni and Zn probability of contamination was below 0.025. The results demonstrated that the estimation of the sampling uncertainty, which was the dominant component of the combined uncertainty, is required for a comprehensive interpretation of the environmental analyses results, particularly in forensic cases. Copyright © 2018 Elsevier B.V. All rights reserved.

Measurement Errors and Uncertainties Theory and Practice

CERN Document Server

Rabinovich, Semyon G

2006-01-01

Measurement Errors and Uncertainties addresses the most important problems that physicists and engineers encounter when estimating errors and uncertainty. Building from the fundamentals of measurement theory, the author develops the theory of accuracy of measurements and offers a wealth of practical recommendations and examples of applications. This new edition covers a wide range of subjects, including: - Basic concepts of metrology - Measuring instruments characterization, standardization and calibration -Estimation of errors and uncertainty of single and multiple measurements - Modern probability-based methods of estimating measurement uncertainty With this new edition, the author completes the development of the new theory of indirect measurements. This theory provides more accurate and efficient methods for processing indirect measurement data. It eliminates the need to calculate the correlation coefficient - a stumbling block in measurement data processing - and offers for the first time a way to obtain...

Modelling pesticide leaching under climate change: parameter vs. climate input uncertainty

Directory of Open Access Journals (Sweden)

K. Steffens

2014-02-01

Full Text Available Assessing climate change impacts on pesticide leaching requires careful consideration of different sources of uncertainty. We investigated the uncertainty related to climate scenario input and its importance relative to parameter uncertainty of the pesticide leaching model. The pesticide fate model MACRO was calibrated against a comprehensive one-year field data set for a well-structured clay soil in south-western Sweden. We obtained an ensemble of 56 acceptable parameter sets that represented the parameter uncertainty. Nine different climate model projections of the regional climate model RCA3 were available as driven by different combinations of global climate models (GCM, greenhouse gas emission scenarios and initial states of the GCM. The future time series of weather data used to drive the MACRO model were generated by scaling a reference climate data set (1970–1999 for an important agricultural production area in south-western Sweden based on monthly change factors for 2070–2099. 30 yr simulations were performed for different combinations of pesticide properties and application seasons. Our analysis showed that both the magnitude and the direction of predicted change in pesticide leaching from present to future depended strongly on the particular climate scenario. The effect of parameter uncertainty was of major importance for simulating absolute pesticide losses, whereas the climate uncertainty was relatively more important for predictions of changes of pesticide losses from present to future. The climate uncertainty should be accounted for by applying an ensemble of different climate scenarios. The aggregated ensemble prediction based on both acceptable parameterizations and different climate scenarios has the potential to provide robust probabilistic estimates of future pesticide losses.

Experimental uncertainty estimation and statistics for data having interval uncertainty.

Energy Technology Data Exchange (ETDEWEB)

Kreinovich, Vladik (Applied Biomathematics, Setauket, New York); Oberkampf, William Louis (Applied Biomathematics, Setauket, New York); Ginzburg, Lev (Applied Biomathematics, Setauket, New York); Ferson, Scott (Applied Biomathematics, Setauket, New York); Hajagos, Janos (Applied Biomathematics, Setauket, New York)

2007-05-01

This report addresses the characterization of measurements that include epistemic uncertainties in the form of intervals. It reviews the application of basic descriptive statistics to data sets which contain intervals rather than exclusively point estimates. It describes algorithms to compute various means, the median and other percentiles, variance, interquartile range, moments, confidence limits, and other important statistics and summarizes the computability of these statistics as a function of sample size and characteristics of the intervals in the data (degree of overlap, size and regularity of widths, etc.). It also reviews the prospects for analyzing such data sets with the methods of inferential statistics such as outlier detection and regressions. The report explores the tradeoff between measurement precision and sample size in statistical results that are sensitive to both. It also argues that an approach based on interval statistics could be a reasonable alternative to current standard methods for evaluating, expressing and propagating measurement uncertainties.

Visualizing Summary Statistics and Uncertainty

KAUST Repository

Potter, K.; Kniss, J.; Riesenfeld, R.; Johnson, C.R.

2010-01-01

The graphical depiction of uncertainty information is emerging as a problem of great importance. Scientific data sets are not considered complete without indications of error, accuracy, or levels of confidence. The visual portrayal of this information is a challenging task. This work takes inspiration from graphical data analysis to create visual representations that show not only the data value, but also important characteristics of the data including uncertainty. The canonical box plot is reexamined and a new hybrid summary plot is presented that incorporates a collection of descriptive statistics to highlight salient features of the data. Additionally, we present an extension of the summary plot to two dimensional distributions. Finally, a use-case of these new plots is presented, demonstrating their ability to present high-level overviews as well as detailed insight into the salient features of the underlying data distribution. © 2010 The Eurographics Association and Blackwell Publishing Ltd.

Visualizing Summary Statistics and Uncertainty

KAUST Repository

Potter, K.

2010-08-12

The graphical depiction of uncertainty information is emerging as a problem of great importance. Scientific data sets are not considered complete without indications of error, accuracy, or levels of confidence. The visual portrayal of this information is a challenging task. This work takes inspiration from graphical data analysis to create visual representations that show not only the data value, but also important characteristics of the data including uncertainty. The canonical box plot is reexamined and a new hybrid summary plot is presented that incorporates a collection of descriptive statistics to highlight salient features of the data. Additionally, we present an extension of the summary plot to two dimensional distributions. Finally, a use-case of these new plots is presented, demonstrating their ability to present high-level overviews as well as detailed insight into the salient features of the underlying data distribution. © 2010 The Eurographics Association and Blackwell Publishing Ltd.

Uncertainty Regarding Waste Handling in Everyday Life

Directory of Open Access Journals (Sweden)

Susanne Ewert

2010-09-01

Full Text Available According to our study, based on interviews with households in a residential area in Sweden, uncertainty is a cultural barrier to improved recycling. Four causes of uncertainty are identified. Firstly, professional categories not matching cultural categories—people easily discriminate between certain categories (e.g., materials such as plastic and paper but not between others (e.g., packaging and “non-packaging”. Thus a frequent cause of uncertainty is that the basic categories of the waste recycling system do not coincide with the basic categories used in everyday life. Challenged habits—source separation in everyday life is habitual, but when a habit is challenged, by a particular element or feature of the waste system, uncertainty can arise. Lacking fractions—some kinds of items cannot be left for recycling and this makes waste collection incomplete from the user’s point of view and in turn lowers the credibility of the system. Missing or contradictory rules of thumb—the above causes seem to be particularly relevant if no motivating principle or rule of thumb (within the context of use is successfully conveyed to the user. This paper discusses how reducing uncertainty can improve recycling.

Analytical Propagation of Uncertainty in Life Cycle Assessment Using Matrix Formulation

DEFF Research Database (Denmark)

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

2013-01-01

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

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.

Uncertainty analysis guide

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)

Uncertainty analysis guide

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)

Scientific uncertainties associated with risk assessment of radiation

International Nuclear Information System (INIS)

Hubert, P.; Fagnani, F.

1989-05-01

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

Scientific uncertainties associated with risk assessment of radiation

Energy Technology Data Exchange (ETDEWEB)

Hubert, P; Fagnani, F

1989-05-01

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

International survey for good practices in forecasting uncertainty assessment and communication

Science.gov (United States)

Berthet, Lionel; Piotte, Olivier

2014-05-01

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

Uncertainty in prostate cancer. Ethnic and family patterns.

Science.gov (United States)

Germino, B B; Mishel, M H; Belyea, M; Harris, L; Ware, A; Mohler, J

1998-01-01

Prostate cancer occurs 37% more often in African-American men than in white men. Patients and their family care providers (FCPs) may have different experiences of cancer and its treatment. This report addresses two questions: 1) What is the relationship of uncertainty to family coping, psychological adjustment to illness, and spiritual factors? and 2) Are these patterns of relationship similar for patients and their family care givers and for whites and African-Americans? A sample of white and African-American men and their family care givers (N = 403) was drawn from an ongoing study, testing the efficacy of an uncertainty management intervention with men with stage B prostate cancer. Data were collected at study entry, either 1 week after post-surgical catheter removal or at the beginning of primary radiation treatment. Measures of uncertainty, adult role behavior, problem solving, social support, importance of God in one's life, family coping, psychological adjustment to illness, and perceptions of health and illness met standard criteria for internal consistency. Analyses of baseline data using Pearson's product moment correlations were conducted to examine the relationships of person, disease, and contextual factors to uncertainty. For family coping, uncertainty was significantly and positively related to two domains in white family care providers only. In African-American and white family care providers, the more uncertainty experienced, the less positive they felt about treatment. Uncertainty for all care givers was related inversely to positive feelings about the patient recovering from the illness. For all patients and for white family members, uncertainty was related inversely to the quality of the domestic environment. For everyone, uncertainty was related inversely to psychological distress. Higher levels of uncertainty were related to a poorer social environment for African-American patients and for white family members. For white patients and their

Study of a methodology of identifying important research problems by the PIRT process

International Nuclear Information System (INIS)

Aoki, Takayuki; Takagi, Toshiyuki; Urayama, Ryoichi; Komura, Ichiro; Furukawa, Takashi; Yusa, Noritaka

2014-01-01

In this paper, we propose a new methodology of identifying important research problems to be solved to improve the performance of some specific scientific technologies by the phenomena identification and ranking table (PIRT) process which has been used as a methodology for demonstrating the validity of the best estimate simulation codes in US Nuclear Regulatory Commission (USNRC) licensing of nuclear power plants. The new methodology makes it possible to identify important factors affecting the performance of the technologies from the viewpoint of the figure of merit and problems associated with them while it keeps the fundamental concepts of the original PIRT process. Also in this paper, we demonstrate the effectiveness of the new methodology by applying it to a task of extracting research problems for improving an inspection accuracy of ultrasonic testing or eddy current testing in the inspection of objects having cracks due to fatigue or stress corrosion cracking. (author)

Study of a methodology of identifying important research problems by the PIRT process

International Nuclear Information System (INIS)

Aoki, Takayuki; Takagi, Toshiyuki; Urayama, Ryoichi; Komura, Ichiro; Furukawa, Takashi; Yusa, Noritaka

2013-01-01

In this paper, we propose a new methodology of identifying important research problems to be solved to improve the performance of some specific scientific technologies by the phenomena identification and ranking table (PIRT) process, which has been used as a methodology for demonstrating the validity of the best estimate simulation codes in USNRC licensing of nuclear power plants. It keeps the fundamental concepts of the original PIRT process but makes it possible to identify important factors affecting the performance of the technologies from the viewpoint of the figure of merit and problems associated with them, which need to be solved to improve the performance. Also in this paper, we demonstrate the effectiveness of the developed method by showing a specific example of the application to physical events or phenomena in objects having fatigue or SCC crack(s) under ultrasonic testing and eddy current testing. (author)

On uncertainty quantification in hydrogeology and hydrogeophysics

Science.gov (United States)

Linde, Niklas; Ginsbourger, David; Irving, James; Nobile, Fabio; Doucet, Arnaud

2017-12-01

Recent advances in sensor technologies, field methodologies, numerical modeling, and inversion approaches have contributed to unprecedented imaging of hydrogeological properties and detailed predictions at multiple temporal and spatial scales. Nevertheless, imaging results and predictions will always remain imprecise, which calls for appropriate uncertainty quantification (UQ). In this paper, we outline selected methodological developments together with pioneering UQ applications in hydrogeology and hydrogeophysics. The applied mathematics and statistics literature is not easy to penetrate and this review aims at helping hydrogeologists and hydrogeophysicists to identify suitable approaches for UQ that can be applied and further developed to their specific needs. To bypass the tremendous computational costs associated with forward UQ based on full-physics simulations, we discuss proxy-modeling strategies and multi-resolution (Multi-level Monte Carlo) methods. We consider Bayesian inversion for non-linear and non-Gaussian state-space problems and discuss how Sequential Monte Carlo may become a practical alternative. We also describe strategies to account for forward modeling errors in Bayesian inversion. Finally, we consider hydrogeophysical inversion, where petrophysical uncertainty is often ignored leading to overconfident parameter estimation. The high parameter and data dimensions encountered in hydrogeological and geophysical problems make UQ a complicated and important challenge that has only been partially addressed to date.

Assessment of uncertainties associated with characterization of geological environment in the Tono area. Japanese fiscal year, 2006 (Contract research)

International Nuclear Information System (INIS)

Toida, Masaru; Suyama, Yasuhiro; Seno, Shoji; Atsumi, Hiroyuki; Ogata, Nobuhisa

2008-03-01

'Geoscientific research' performed at the Tono Geoscience Center is developing site investigation, characterization and assessment techniques for understanding of geological environment. Their important themes are to establish a methodology for analyzing uncertainties in heterogeneous geological environment, and to develop investigation techniques for reducing the uncertainties efficiently. This study proposes a new approach where all the possible options in the models and data-sets that cannot be excluded in the light of the evidence available, are identified. This approach enables uncertainties associated with the understanding at a given stage of the site characterization to be made explicitly using an uncertainty analysis technique based on Fuzzy geostatistics. This, in turn, supports the design of the following investigation stage to reduce the uncertainties efficiently. In the study, current knowledge had been compiled, and the technique had been advanced through geological modeling and groundwater analyses in the Tono area. This report systematized the uncertainty analysis methodology associated with the characterization of the geological environment, and organized the procedure of the methodology with the application examples in the study. This report also dealt with investigation techniques for reducing the uncertainties efficiently, and underground facility design options for handling geological uncertainties based on the characterization of the geological environment. (author)

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

Low cost high performance uncertainty quantification

KAUST Repository

Bekas, C.; Curioni, A.; Fedulova, I.

2009-01-01

Uncertainty quantification in risk analysis has become a key application. In this context, computing the diagonal of inverse covariance matrices is of paramount importance. Standard techniques, that employ matrix factorizations, incur a cubic cost

Statistical Analyses of Scatterplots to Identify Important Factors in Large-Scale Simulations

Energy Technology Data Exchange (ETDEWEB)

Kleijnen, J.P.C.; Helton, J.C.

1999-04-01

The robustness of procedures for identifying patterns in scatterplots generated in Monte Carlo sensitivity analyses is investigated. These procedures are based on attempts to detect increasingly complex patterns in the scatterplots under consideration and involve the identification of (1) linear relationships with correlation coefficients, (2) monotonic relationships with rank correlation coefficients, (3) trends in central tendency as defined by means, medians and the Kruskal-Wallis statistic, (4) trends in variability as defined by variances and interquartile ranges, and (5) deviations from randomness as defined by the chi-square statistic. The following two topics related to the robustness of these procedures are considered for a sequence of example analyses with a large model for two-phase fluid flow: the presence of Type I and Type II errors, and the stability of results obtained with independent Latin hypercube samples. Observations from analysis include: (1) Type I errors are unavoidable, (2) Type II errors can occur when inappropriate analysis procedures are used, (3) physical explanations should always be sought for why statistical procedures identify variables as being important, and (4) the identification of important variables tends to be stable for independent Latin hypercube samples.

Inflation, inflation uncertainty and output growth in the USA

Science.gov (United States)

Bhar, Ramprasad; Mallik, Girijasankar

2010-12-01

Employing a multivariate EGARCH-M model, this study investigates the effects of inflation uncertainty and growth uncertainty on inflation and output growth in the United States. Our results show that inflation uncertainty has a positive and significant effect on the level of inflation and a negative and significant effect on the output growth. However, output uncertainty has no significant effect on output growth or inflation. The oil price also has a positive and significant effect on inflation. These findings are robust and have been corroborated by use of an impulse response function. These results have important implications for inflation-targeting monetary policy, and the aim of stabilization policy in general.

Development of a Dynamic Lidar Uncertainty Framework

Energy Technology Data Exchange (ETDEWEB)

Newman, Jennifer [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Clifton, Andrew [WindForS; Bonin, Timothy [CIRES/NOAA ESRL; Choukulkar, Aditya [CIRES/NOAA ESRL; Brewer, W. Alan [NOAA ESRL; Delgado, Ruben [University of Maryland Baltimore County

2017-08-07

As wind turbine sizes increase and wind energy expands to more complex and remote sites, remote-sensing devices such as lidars are expected to play a key role in wind resource assessment and power performance testing. The switch to remote-sensing devices represents a paradigm shift in the way the wind industry typically obtains and interprets measurement data for wind energy. For example, the measurement techniques and sources of uncertainty for a remote-sensing device are vastly different from those associated with a cup anemometer on a meteorological tower. Current IEC standards for quantifying remote sensing device uncertainty for power performance testing consider uncertainty due to mounting, calibration, and classification of the remote sensing device, among other parameters. Values of the uncertainty are typically given as a function of the mean wind speed measured by a reference device and are generally fixed, leading to climatic uncertainty values that apply to the entire measurement campaign. However, real-world experience and a consideration of the fundamentals of the measurement process have shown that lidar performance is highly dependent on atmospheric conditions, such as wind shear, turbulence, and aerosol content. At present, these conditions are not directly incorporated into the estimated uncertainty of a lidar device. In this presentation, we describe the development of a new dynamic lidar uncertainty framework that adapts to current flow conditions and more accurately represents the actual uncertainty inherent in lidar measurements under different conditions. In this new framework, sources of uncertainty are identified for estimation of the line-of-sight wind speed and reconstruction of the three-dimensional wind field. These sources are then related to physical processes caused by the atmosphere and lidar operating conditions. The framework is applied to lidar data from a field measurement site to assess the ability of the framework to predict

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

DEFF Research Database (Denmark)

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

2011-01-01

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

Reducing uncertainty in wind turbine blade health inspection with image processing techniques

Science.gov (United States)

Zhang, Huiyi

Structural health inspection has been widely applied in the operation of wind farms to find early cracks in wind turbine blades (WTBs). Increased numbers of turbines and expanded rotor diameters are driving up the workloads and safety risks for site employees. Therefore, it is important to automate the inspection process as well as minimize the uncertainties involved in routine blade health inspection. In addition, crack documentation and trending is vital to assess rotor blade and turbine reliability in the 20 year designed life span. A new crack recognition and classification algorithm is described that can support automated structural health inspection of the surface of large composite WTBs. The first part of the study investigated the feasibility of digital image processing in WTB health inspection and defined the capability of numerically detecting cracks as small as hairline thickness. The second part of the study identified and analyzed the uncertainty of the digital image processing method. A self-learning algorithm was proposed to recognize and classify cracks without comparing a blade image to a library of crack images. The last part of the research quantified the uncertainty in the field conditions and the image processing methods.

Uncertainty and endogenous technical change in climate policy models

International Nuclear Information System (INIS)

Baker, Erin; Shittu, Ekundayo

2008-01-01

Until recently endogenous technical change and uncertainty have been modeled separately in climate policy models. In this paper, we review the emerging literature that considers both these elements together. Taken as a whole the literature indicates that explicitly including uncertainty has important quantitative and qualitative impacts on optimal climate change technology policy. (author)

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

International Nuclear Information System (INIS)

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

1995-01-01

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

A framework for model-based optimization of bioprocesses under uncertainty: Identifying critical parameters and operating variables

DEFF Research Database (Denmark)

Morales Rodriguez, Ricardo; Meyer, Anne S.; Gernaey, Krist

2011-01-01

This study presents the development and application of a systematic model-based framework for bioprocess optimization, evaluated on a cellulosic ethanol production case study. The implementation of the framework involves the use of dynamic simulations, sophisticated uncertainty analysis (Monte...

Decision Making Under Uncertainty - Bridging the Gap Between End User Needs and Science Capability

Science.gov (United States)

Verdon-Kidd, D. C.; Kiem, A.; Austin, E. K.

2012-12-01

Successful adaptation outcomes depend on decision making based on the best available climate science information. However, a fundamental barrier exists, namely the 'gap' between information that climate science can currently provide and the information that is practically useful for end users and decision makers. This study identifies the major contributing factors to the 'gap' from an Australian perspective and provides recommendations as to ways in which the 'gap' may be narrowed. This was achieved via a literature review, online survey (targeted to providers of climate information and end users of that information), workshop (where both climate scientists and end users came together to discuss key issues) and focus group. The study confirmed that uncertainty in climate science is a key barrier to adaptation. The issue of uncertainty was found to be multi-faceted, with issues identified in terms of communication of uncertainty, misunderstanding of uncertainty and the lack of tools/methods to deal with uncertainty. There were also key differences in terms of expectations for the future - most end users were of the belief that uncertainty associated with future climate projections would reduce within the next five to 10 years, however producers of climate science information were well aware that this would most likely not be the case. This is a concerning finding as end users may delay taking action on adaptation and risk planning until the uncertainties are reduced - a situation which may never eventuate or may occur after the optimal time for action. Improved communication and packaging of climate information was another key theme that was highlighted in this study. Importantly, it was made clear that improved communication is not just about more glossy brochures and presentations by climate scientists, rather there is a role for a program or group to fill this role (coined a 'knowledge broker' during the workshop and focus group). The role of the 'knowledge

Radon measurements: the sources of uncertainties

International Nuclear Information System (INIS)

Zhukovsky, Michael; Onischenko, Alexandra; Bastrikov, Vladislav

2008-01-01

Full text: Radon measurements are quite complicated process and the correct estimation of uncertainties is very important. The sources of uncertainties for grab sampling, short term measurements (charcoal canisters), long term measurements (track detectors) and retrospective measurements (surface traps) are analyzed. The main sources of uncertainties for grab sampling measurements are: systematic bias of reference equipment; random Poisson and non-Poisson errors during calibration; random Poisson and non-Poisson errors during measurements. These sources are also common both for short term measurements (charcoal canisters) and long term measurements (track detectors). Usually during the calibration the high radon concentrations are used (1-5 kBq/m 3 ) and the Poisson random error rarely exceed some percents. Nevertheless the dispersion of measured values even during the calibration usually exceeds the Poisson dispersion expected on the basis of counting statistic. The origins of such non-Poisson random errors during calibration are different for different kinds of instrumental measurements. At present not all sources of non-Poisson random errors are trustworthy identified. The initial calibration accuracy of working devices rarely exceeds the value 20%. The real radon concentrations usually are in the range from some tens to some hundreds Becquerel per cubic meter and for low radon levels Poisson random error can reach up to 20%. The random non-Poisson errors and residual systematic biases are depends on the kind of measurement technique and the environmental conditions during radon measurements. For charcoal canisters there are additional sources of the measurement errors due to influence of air humidity and the variations of radon concentration during the canister exposure. The accuracy of long term measurements by track detectors will depend on the quality of chemical etching after exposure and the influence of season radon variations. The main sources of

Uncertainties about climate

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

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

Development and application of objective uncertainty measures for nuclear power plant transient analysis

International Nuclear Information System (INIS)

Vinai, P.

2007-10-01

For the development, design and licensing of a nuclear power plant (NPP), a sound safety analysis is necessary to study the diverse physical phenomena involved in the system behaviour under operational and transient conditions. Such studies are based on detailed computer simulations. With the progresses achieved in computer technology and the greater availability of experimental and plant data, the use of best estimate codes for safety evaluations has gained increasing acceptance. The application of best estimate safety analysis has raised new problems that need to be addressed: it has become more crucial to assess as to how reliable code predictions are, especially when they need to be compared against safety limits that must not be crossed. It becomes necessary to identify and quantify the various possible sources of uncertainty that affect the reliability of the results. Currently, such uncertainty evaluations are generally based on experts' opinion. In the present research, a novel methodology based on a non-parametric statistical approach has been developed for objective quantification of best-estimate code uncertainties related to the physical models used in the code. The basis is an evaluation of the accuracy of a given physical model achieved by comparing its predictions with experimental data from an appropriate set of separate-effect tests. The differences between measurements and predictions can be considered stochastically distributed, and thus a statistical approach can be employed. The first step was the development of a procedure for investigating the dependence of a given physical model's accuracy on the experimental conditions. Each separate-effect test effectively provides a random sample of discrepancies between measurements and predictions, corresponding to a location in the state space defined by a certain number of independent system variables. As a consequence, the samples of 'errors', achieved from analysis of the entire database, are

Scientific visualization uncertainty, multifield, biomedical, and scalable visualization

CERN Document Server

Chen, Min; Johnson, Christopher; Kaufman, Arie; Hagen, Hans

2014-01-01

Based on the seminar that took place in Dagstuhl, Germany in June 2011, this contributed volume studies the four important topics within the scientific visualization field: uncertainty visualization, multifield visualization, biomedical visualization and scalable visualization. • Uncertainty visualization deals with uncertain data from simulations or sampled data, uncertainty due to the mathematical processes operating on the data, and uncertainty in the visual representation, • Multifield visualization addresses the need to depict multiple data at individual locations and the combination of multiple datasets, • Biomedical is a vast field with select subtopics addressed from scanning methodologies to structural applications to biological applications, • Scalability in scientific visualization is critical as data grows and computational devices range from hand-held mobile devices to exascale computational platforms. Scientific Visualization will be useful to practitioners of scientific visualization, ...

Uncertainty and sensitivity analysis of control strategies using the benchmark simulation model No1 (BSM1).

Science.gov (United States)

Flores-Alsina, Xavier; Rodriguez-Roda, Ignasi; Sin, Gürkan; Gernaey, Krist V

2009-01-01

The objective of this paper is to perform an uncertainty and sensitivity analysis of the predictions of the Benchmark Simulation Model (BSM) No. 1, when comparing four activated sludge control strategies. The Monte Carlo simulation technique is used to evaluate the uncertainty in the BSM1 predictions, considering the ASM1 bio-kinetic parameters and influent fractions as input uncertainties while the Effluent Quality Index (EQI) and the Operating Cost Index (OCI) are focused on as model outputs. The resulting Monte Carlo simulations are presented using descriptive statistics indicating the degree of uncertainty in the predicted EQI and OCI. Next, the Standard Regression Coefficients (SRC) method is used for sensitivity analysis to identify which input parameters influence the uncertainty in the EQI predictions the most. The results show that control strategies including an ammonium (S(NH)) controller reduce uncertainty in both overall pollution removal and effluent total Kjeldahl nitrogen. Also, control strategies with an external carbon source reduce the effluent nitrate (S(NO)) uncertainty increasing both their economical cost and variability as a trade-off. Finally, the maximum specific autotrophic growth rate (micro(A)) causes most of the variance in the effluent for all the evaluated control strategies. The influence of denitrification related parameters, e.g. eta(g) (anoxic growth rate correction factor) and eta(h) (anoxic hydrolysis rate correction factor), becomes less important when a S(NO) controller manipulating an external carbon source addition is implemented.

Transient flow conditions in probabilistic wellhead protection: importance and ways to manage spatial and temporal uncertainty in capture zone delineation

Science.gov (United States)

Enzenhoefer, R.; Rodriguez-Pretelin, A.; Nowak, W.

2012-12-01

"From an engineering standpoint, the quantification of uncertainty is extremely important not only because it allows estimating risk but mostly because it allows taking optimal decisions in an uncertain framework" (Renard, 2007). The most common way to account for uncertainty in the field of subsurface hydrology and wellhead protection is to randomize spatial parameters, e.g. the log-hydraulic conductivity or porosity. This enables water managers to take robust decisions in delineating wellhead protection zones with rationally chosen safety margins in the spirit of probabilistic risk management. Probabilistic wellhead protection zones are commonly based on steady-state flow fields. However, several past studies showed that transient flow conditions may substantially influence the shape and extent of catchments. Therefore, we believe they should be accounted for in the probabilistic assessment and in the delineation process. The aim of our work is to show the significance of flow transients and to investigate the interplay between spatial uncertainty and flow transients in wellhead protection zone delineation. To this end, we advance our concept of probabilistic capture zone delineation (Enzenhoefer et al., 2012) that works with capture probabilities and other probabilistic criteria for delineation. The extended framework is able to evaluate the time fraction that any point on a map falls within a capture zone. In short, we separate capture probabilities into spatial/statistical and time-related frequencies. This will provide water managers additional information on how to manage a well catchment in the light of possible hazard conditions close to the capture boundary under uncertain and time-variable flow conditions. In order to save computational costs, we take advantage of super-positioned flow components with time-variable coefficients. We assume an instantaneous development of steady-state flow conditions after each temporal change in driving forces, following

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)

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

Public Perception of Uncertainties Within Climate Change Science.

Science.gov (United States)

Visschers, Vivianne H M

2018-01-01

Climate change is a complex, multifaceted problem involving various interacting systems and actors. Therefore, the intensities, locations, and timeframes of the consequences of climate change are hard to predict and cause uncertainties. Relatively little is known about how the public perceives this scientific uncertainty and how this relates to their concern about climate change. In this article, an online survey among 306 Swiss people is reported that investigated whether people differentiate between different types of uncertainty in climate change research. Also examined was the way in which the perception of uncertainty is related to people's concern about climate change, their trust in science, their knowledge about climate change, and their political attitude. The results of a principal component analysis showed that respondents differentiated between perceived ambiguity in climate research, measurement uncertainty, and uncertainty about the future impact of climate change. Using structural equation modeling, it was found that only perceived ambiguity was directly related to concern about climate change, whereas measurement uncertainty and future uncertainty were not. Trust in climate science was strongly associated with each type of uncertainty perception and was indirectly associated with concern about climate change. Also, more knowledge about climate change was related to less strong perceptions of each type of climate science uncertainty. Hence, it is suggested that to increase public concern about climate change, it may be especially important to consider the perceived ambiguity about climate research. Efforts that foster trust in climate science also appear highly worthwhile. © 2017 Society for Risk Analysis.

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

Position-momentum uncertainty relations in the presence of quantum memory

Energy Technology Data Exchange (ETDEWEB)

Furrer, Fabian, E-mail: furrer@eve.phys.s.u-tokyo.ac.jp [Department of Physics, Graduate School of Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033 (Japan); Berta, Mario [Institute for Quantum Information and Matter, Caltech, Pasadena, California 91125 (United States); Institute for Theoretical Physics, ETH Zurich, Wolfgang-Pauli-Str. 27, 8093 Zürich (Switzerland); Tomamichel, Marco [School of Physics, The University of Sydney, Sydney 2006 (Australia); Centre for Quantum Technologies, National University of Singapore, Singapore 117543 (Singapore); Scholz, Volkher B. [Institute for Theoretical Physics, ETH Zurich, Wolfgang-Pauli-Str. 27, 8093 Zürich (Switzerland); Christandl, Matthias [Institute for Theoretical Physics, ETH Zurich, Wolfgang-Pauli-Str. 27, 8093 Zürich (Switzerland); Department of Mathematical Sciences, University of Copenhagen, Universitetsparken 5, 2100 Copenhagen (Denmark)

2014-12-15

A prominent formulation of the uncertainty principle identifies the fundamental quantum feature that no particle may be prepared with certain outcomes for both position and momentum measurements. Often the statistical uncertainties are thereby measured in terms of entropies providing a clear operational interpretation in information theory and cryptography. Recently, entropic uncertainty relations have been used to show that the uncertainty can be reduced in the presence of entanglement and to prove security of quantum cryptographic tasks. However, much of this recent progress has been focused on observables with only a finite number of outcomes not including Heisenberg’s original setting of position and momentum observables. Here, we show entropic uncertainty relations for general observables with discrete but infinite or continuous spectrum that take into account the power of an entangled observer. As an illustration, we evaluate the uncertainty relations for position and momentum measurements, which is operationally significant in that it implies security of a quantum key distribution scheme based on homodyne detection of squeezed Gaussian states.

Financial globalisation uncertainty/instability is good for financial development

OpenAIRE

Asongu, Simplice A.; Koomson, Isaac; Tchamyou, Vanessa S.

2015-01-01

Purpose – This study assesses the effect of time-dynamic financial globalisation uncertainty on financial development in 53 African countries for the period 2000-2011. Design/methodology/approach – Financial globalisation uncertainty is estimated as time-dynamic to capture business cycle disturbances while all dimensions identified by the Financial Development and Structure Database of the World Bank are employed, namely: financial depth (money supply and liquid liabilities), financial sy...

Estimating uncertainty of inference for validation

Energy Technology Data Exchange (ETDEWEB)

Booker, Jane M [Los Alamos National Laboratory; Langenbrunner, James R [Los Alamos National Laboratory; Hemez, Francois M [Los Alamos National Laboratory; Ross, Timothy J [UNM

2010-09-30

We present a validation process based upon the concept that validation is an inference-making activity. This has always been true, but the association has not been as important before as it is now. Previously, theory had been confirmed by more data, and predictions were possible based on data. The process today is to infer from theory to code and from code to prediction, making the role of prediction somewhat automatic, and a machine function. Validation is defined as determining the degree to which a model and code is an accurate representation of experimental test data. Imbedded in validation is the intention to use the computer code to predict. To predict is to accept the conclusion that an observable final state will manifest; therefore, prediction is an inference whose goodness relies on the validity of the code. Quantifying the uncertainty of a prediction amounts to quantifying the uncertainty of validation, and this involves the characterization of uncertainties inherent in theory/models/codes and the corresponding data. An introduction to inference making and its associated uncertainty is provided as a foundation for the validation problem. A mathematical construction for estimating the uncertainty in the validation inference is then presented, including a possibility distribution constructed to represent the inference uncertainty for validation under uncertainty. The estimation of inference uncertainty for validation is illustrated using data and calculations from Inertial Confinement Fusion (ICF). The ICF measurements of neutron yield and ion temperature were obtained for direct-drive inertial fusion capsules at the Omega laser facility. The glass capsules, containing the fusion gas, were systematically selected with the intent of establishing a reproducible baseline of high-yield 10{sup 13}-10{sup 14} neutron output. The deuterium-tritium ratio in these experiments was varied to study its influence upon yield. This paper on validation inference is the

Uncertainties in environmental radiological assessment models and their implications

International Nuclear Information System (INIS)

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

1983-01-01

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

Uncertainty analysis in the applications of nuclear probabilistic risk assessment

International Nuclear Information System (INIS)

Le Duy, T.D.

2011-01-01

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

Uncertainty and Sensitivity Analysis Applied to the Validation of BWR Bundle Thermal-Hydraulic Calculations

International Nuclear Information System (INIS)

Hernandez-Solis, Augusto

2010-04-01

This work has two main objectives. The first one is to enhance the validation process of the thermal-hydraulic features of the Westinghouse code POLCA-T. This is achieved by computing a quantitative validation limit based on statistical uncertainty analysis. This validation theory is applied to some of the benchmark cases of the following macroscopic BFBT exercises: 1) Single and two phase bundle pressure drops, 2) Steady-state cross-sectional averaged void fraction, 3) Transient cross-sectional averaged void fraction and 4) Steady-state critical power tests. Sensitivity analysis is also performed to identify the most important uncertain parameters for each exercise. The second objective consists in showing the clear advantages of using the quasi-random Latin Hypercube Sampling (LHS) strategy over simple random sampling (SRS). LHS allows a much better coverage of the input uncertainties than SRS because it densely stratifies across the range of each input probability distribution. The aim here is to compare both uncertainty analyses on the BWR assembly void axial profile prediction in steady-state, and on the transient void fraction prediction at a certain axial level coming from a simulated re-circulation pump trip scenario. It is shown that the replicated void fraction mean (either in steady-state or transient conditions) has less variability when using LHS than SRS for the same number of calculations (i.e. same input space sample size) even if the resulting void fraction axial profiles are non-monotonic. It is also shown that the void fraction uncertainty limits achieved with SRS by running 458 calculations (sample size required to cover 95% of 8 uncertain input parameters with a 95% confidence), result in the same uncertainty limits achieved by LHS with only 100 calculations. These are thus clear indications on the advantages of using LHS. Finally, the present study contributes to a realistic analysis of nuclear reactors, in the sense that the uncertainties of

Managerial conflict management in five European countries : The importance of power distance, uncertainty avoidance, and masculinity

NARCIS (Netherlands)

Van Oudenhoven, J.P.; Mechelse, L.; De Dreu, C.K.W.

This research deals with managerial conflict management in Denmark, United Kingdom, The Netherlands, Spain, and Belgium. According to Hofstede (1991). these countries' cultures differ primarily in terms of uncertainty avoidance, power distance, and masculinity-femininity. The differences in

Use of importance measures in risk-informed regulatory applications

International Nuclear Information System (INIS)

Cheok, Michael C.; Parry, Gareth W.; Sherry, Richard R.

1998-01-01

The use of importance measures to analyze PRA results is discussed. Commonly used importance measures are defined. Some issues that have been identified as potentially limiting their usefulness are addressed, namely: there is no simple relationship between importance measures evaluated at the single component level and those evaluated at the level of a group of components, and, as a result, some of the commonly used importance measures are not realistic measures of the sensitivity of the overall risk to parameter value changes; and, importance measures do not typically take into account parameter uncertainties which raises the question of the robustness of conclusions drawn from importance analyses. The issues are explored in the context of both ranking and categorization of structures, systems, and components (SSCs) with respect to risk-significance and safety-significance for use in risk-informed regulatory analyses

Scientific Uncertainties in Climate Change Detection and Attribution Studies

Science.gov (United States)

Santer, B. D.

2017-12-01

It has been claimed that the treatment and discussion of key uncertainties in climate science is "confined to hushed sidebar conversations at scientific conferences". This claim is demonstrably incorrect. Climate change detection and attribution studies routinely consider key uncertainties in observational climate data, as well as uncertainties in model-based estimates of natural variability and the "fingerprints" in response to different external forcings. The goal is to determine whether such uncertainties preclude robust identification of a human-caused climate change fingerprint. It is also routine to investigate the impact of applying different fingerprint identification strategies, and to assess how detection and attribution results are impacted by differences in the ability of current models to capture important aspects of present-day climate. The exploration of the uncertainties mentioned above will be illustrated using examples from detection and attribution studies with atmospheric temperature and moisture.

Understanding the Role of Uncertainty in Jealousy Experience and Expression.

Science.gov (United States)

Afifi, Walid A.; Reichert, Tom

1996-01-01

Confirms the value of uncertainty for understanding jealousy. Finds that subjects were more likely to experience and less likely to directly express jealousy at high, versus low, levels of relational state uncertainty. Highlights the importance of differentiating jealousy experience from expression, and corroborates recent evidence showing a…

Uncertainty quantification an accelerated course with advanced applications in computational engineering

CERN Document Server

Soize, Christian

2017-01-01

This book presents the fundamental notions and advanced mathematical tools in the stochastic modeling of uncertainties and their quantification for large-scale computational models in sciences and engineering. In particular, it focuses in parametric uncertainties, and non-parametric uncertainties with applications from the structural dynamics and vibroacoustics of complex mechanical systems, from micromechanics and multiscale mechanics of heterogeneous materials. Resulting from a course developed by the author, the book begins with a description of the fundamental mathematical tools of probability and statistics that are directly useful for uncertainty quantification. It proceeds with a well carried out description of some basic and advanced methods for constructing stochastic models of uncertainties, paying particular attention to the problem of calibrating and identifying a stochastic model of uncertainty when experimental data is available. < This book is intended to be a graduate-level textbook for stu...

Uncertainty Quantification Bayesian Framework for Porous Media Flows

Science.gov (United States)

Demyanov, V.; Christie, M.; Erbas, D.

2005-12-01

Uncertainty quantification is an increasingly important aspect of many areas of applied science, where the challenge is to make reliable predictions about the performance of complex physical systems in the absence of complete or reliable data. Predicting flows of fluids through undersurface reservoirs is an example of a complex system where accuracy in prediction is needed (e.g. in oil industry it is essential for financial reasons). Simulation of fluid flow in oil reservoirs is usually carried out using large commercially written finite difference simulators solving conservation equations describing the multi-phase flow through the porous reservoir rocks, which is a highly computationally expensive task. This work examines a Bayesian Framework for uncertainty quantification in porous media flows that uses a stochastic sampling algorithm to generate models that match observed time series data. The framework is flexible for a wide range of general physical/statistical parametric models, which are used to describe the underlying hydro-geological process in its temporal dynamics. The approach is based on exploration of the parameter space and update of the prior beliefs about what the most likely model definitions are. Optimization problem for a highly parametric physical model usually have multiple solutions, which impact the uncertainty of the made predictions. Stochastic search algorithm (e.g. genetic algorithm) allows to identify multiple "good enough" models in the parameter space. Furthermore, inference of the generated model ensemble via MCMC based algorithm evaluates the posterior probability of the generated models and quantifies uncertainty of the predictions. Machine learning algorithm - Artificial Neural Networks - are used to speed up the identification of regions in parameter space where good matches to observed data can be found. Adaptive nature of ANN allows to develop different ways of integrating them into the Bayesian framework: as direct time

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

Directory of Open Access Journals (Sweden)

Elise Payzan-LeNestour

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

Calculation uncertainty of distribution-like parameters in NPP of PAKS

International Nuclear Information System (INIS)

Szecsenyi, Zsolt; Korpas, Layos

2000-01-01

In the reactor-physical point of view there were two important events in the Nuclear Power Plant of PAKS in this year. The Russian type profiled assemblies were loaded into the PAKS Unit 3, and new limitation system was introduced on the same Unit. It was required to solve a lot of problems because of these both events. One of these problems was the determination of uncertainty of quantities of the new limitation considering the fabrication uncertainties for the profiled assembly. The importance of determination of uncertainty is to guarantee on 99.9% level the avoidance of fuel failure. In this paper the principles of determination of calculation accuracy, applied methods and obtained results are presented in case of distribution-like parameters. A few elements of the method have been presented on earlier symposiums, so in this paper the whole method is just outlined. For example the GPT method was presented in the following paper: Uncertainty analysis of pin wise power distribution of WWER-440 assembly considering fabrication uncertainties. Finally in the summary of this paper additional intrinsic opportunities in the method are presented. (Authors)

Uncertainty and validation. Effect of user interpretation on uncertainty estimates

International Nuclear Information System (INIS)

Kirchner, G.; Peterson, R.

1996-11-01

variation between the best estimate predictions of the group. The assumptions of the users result in more uncertainty in the predictions (taking into account the 95% confidence intervals) than is shown by the confidence interval on the predictions of one user. Mistakes, being examples of incorrect user assumptions, cannot be ignored and must be accepted as contributing to the variability seen in the spread of predictions. The user's confidence in his/her understanding of a scenario description and/or confidence in working with a code does not necessarily mean that the predictions will be more accurate. Choice of parameter values contributed most to user-induced uncertainty followed by scenario interpretation. The contribution due to code implementation was low, but may have been limited due to the decision of the majority of the group not to submit predictions using the most complex of the three codes. Most modelers had difficulty adapting the models for certain expected output. Parameter values for wet and dry deposition, transfer from forage to milk and concentration ratios were mostly taken from the extensive database of Chernobyl fallout radionuclides, no matter what the scenario. Examples provided in the code manuals may influence code users considerably when preparing their own input files. A major problem concerns pasture concentrations given in fresh or dry weight: parameter values in codes have to be based on one or the other and the request for predictions in the scenario description may or may not be the same unit. This is a surprisingly common source of error. Most of the predictions showed order of magnitude discrepancies when best estimates are compared with the observations, although the participants had a highly professional background in radioecology and a good understanding of the importance of the processes modelled. When uncertainties are considered, however, mostly there was overlap between predictions and observations. A failure to reproduce the time

Uncertainty and validation. Effect of user interpretation on uncertainty estimates

Energy Technology Data Exchange (ETDEWEB)

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

1996-11-01

variation between the best estimate predictions of the group. The assumptions of the users result in more uncertainty in the predictions (taking into account the 95% confidence intervals) than is shown by the confidence interval on the predictions of one user. Mistakes, being examples of incorrect user assumptions, cannot be ignored and must be accepted as contributing to the variability seen in the spread of predictions. The user's confidence in his/her understanding of a scenario description and/or confidence in working with a code does not necessarily mean that the predictions will be more accurate. Choice of parameter values contributed most to user-induced uncertainty followed by scenario interpretation. The contribution due to code implementation was low, but may have been limited due to the decision of the majority of the group not to submit predictions using the most complex of the three codes. Most modelers had difficulty adapting the models for certain expected output. Parameter values for wet and dry deposition, transfer from forage to milk and concentration ratios were mostly taken from the extensive database of Chernobyl fallout radionuclides, no matter what the scenario. Examples provided in the code manuals may influence code users considerably when preparing their own input files. A major problem concerns pasture concentrations given in fresh or dry weight: parameter values in codes have to be based on one or the other and the request for predictions in the scenario description may or may not be the same unit. This is a surprisingly common source of error. Most of the predictions showed order of magnitude discrepancies when best estimates are compared with the observations, although the participants had a highly professional background in radioecology and a good understanding of the importance of the processes modelled. When uncertainties are considered, however, mostly there was overlap between predictions and observations. A failure to reproduce the

Calorimetric and reactor coolant system flow uncertainty

International Nuclear Information System (INIS)

Bates, L.; McLean, T.

1991-01-01

This paper describes a methodology for the quantification of errors associated with the determination of a feedwater flow, secondary power, and Reactor Coolant System (RCS) flow used at the Trojan Nuclear Plant to ensure compliance with regulatory requirements. The sources of error in Plant indications and process measurement are identified and tracked, using examples, through the mathematical processes necessary to calculate the uncertainty in the RCS flow measurement. An error of approximately 1.4 percent is calculated for secondary power. This error results, along with the consideration of other errors, in an uncertainty of approximately 3 percent in the RCS flow determination

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

Energy Technology Data Exchange (ETDEWEB)

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

1997-12-01

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

A New Framework for Quantifying Lidar Uncertainty

Energy Technology Data Exchange (ETDEWEB)

Newman, Jennifer, F.; Clifton, Andrew; Bonin, Timothy A.; Churchfield, Matthew J.

2017-03-24

As wind turbine sizes increase and wind energy expands to more complex and remote sites, remote sensing devices such as lidars are expected to play a key role in wind resource assessment and power performance testing. The switch to remote sensing devices represents a paradigm shift in the way the wind industry typically obtains and interprets measurement data for wind energy. For example, the measurement techniques and sources of uncertainty for a remote sensing device are vastly different from those associated with a cup anemometer on a meteorological tower. Current IEC standards discuss uncertainty due to mounting, calibration, and classification of the remote sensing device, among other parameters. Values of the uncertainty are typically given as a function of the mean wind speed measured by a reference device. However, real-world experience has shown that lidar performance is highly dependent on atmospheric conditions, such as wind shear, turbulence, and aerosol content. At present, these conditions are not directly incorporated into the estimated uncertainty of a lidar device. In this presentation, we propose the development of a new lidar uncertainty framework that adapts to current flow conditions and more accurately represents the actual uncertainty inherent in lidar measurements under different conditions. In this new framework, sources of uncertainty are identified for estimation of the line-of-sight wind speed and reconstruction of the three-dimensional wind field. These sources are then related to physical processes caused by the atmosphere and lidar operating conditions. The framework is applied to lidar data from an operational wind farm to assess the ability of the framework to predict errors in lidar-measured wind speed.

Uncertainty quantification and stochastic modeling with Matlab

CERN Document Server

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

Neural Mechanisms of Updating under Reducible and Irreducible Uncertainty.

Science.gov (United States)

Kobayashi, Kenji; Hsu, Ming

2017-07-19

Adaptive decision making depends on an agent's ability to use environmental signals to reduce uncertainty. However, because of multiple types of uncertainty, agents must take into account not only the extent to which signals violate prior expectations but also whether uncertainty can be reduced in the first place. Here we studied how human brains of both sexes respond to signals under conditions of reducible and irreducible uncertainty. We show behaviorally that subjects' value updating was sensitive to the reducibility of uncertainty, and could be quantitatively characterized by a Bayesian model where agents ignore expectancy violations that do not update beliefs or values. Using fMRI, we found that neural processes underlying belief and value updating were separable from responses to expectancy violation, and that reducibility of uncertainty in value modulated connections from belief-updating regions to value-updating regions. Together, these results provide insights into how agents use knowledge about uncertainty to make better decisions while ignoring mere expectancy violation. SIGNIFICANCE STATEMENT To make good decisions, a person must observe the environment carefully, and use these observations to reduce uncertainty about consequences of actions. Importantly, uncertainty should not be reduced purely based on how surprising the observations are, particularly because in some cases uncertainty is not reducible. Here we show that the human brain indeed reduces uncertainty adaptively by taking into account the nature of uncertainty and ignoring mere surprise. Behaviorally, we show that human subjects reduce uncertainty in a quasioptimal Bayesian manner. Using fMRI, we characterize brain regions that may be involved in uncertainty reduction, as well as the network they constitute, and dissociate them from brain regions that respond to mere surprise. Copyright © 2017 the authors 0270-6474/17/376972-11$15.00/0.

Tolerance for uncertainty in elderly people

Directory of Open Access Journals (Sweden)

KHRYSTYNA KACHMARYK

2014-09-01

Full Text Available The aim of the study. The aim of the paper is a comparison of tolerance to uncertainty in two groups of elderly: the students of the University of the Third Age (UTA and older people who are not enrolled but help to educate grandchildren. A relation to uncertainty was shown to influence on decision making strategy of elderly that indicates on importance of the researches. Methods. To obtain the objectives of the paper the following methods were used: 1 Personal change readiness survey (PCRS adapted by Nickolay Bazhanov and Galina Bardiyer; 2 Tolerance Ambiguity Scale (TAS adapted by Galina Soldatova; 3 Freiburg personality inventory (FPI and 4 The questionnaire of self-relation by Vladimir Stolin and Sergej Panteleev. 40 socially involved elderly people were investigated according the above methods, 20 from UTA and 20 who are not studied and served as control group. Results. It was shown that relations of tolerance to uncertainty in the study group of students of the University of the Third Age substantially differ from relations of tolerance to uncertainty in group of older people who do not learn. The majority of students of the University of the Third Age have an inherent low tolerance for uncertainty, which is associated with an increase in expression personality traits and characteristics in self-relation. The group of the elderly who are not enrolled increasingly shows tolerance of uncertainty, focusing on the social and trusting relationship to meet the needs of communication, and the ability to manage their own emotions and desires than a group of Third Age university students. Conclusions. The results of experimental research of the third age university student’s peculiarities of the tolerance to uncertainty were outlined. It was found that decision making in the ambiguity situations concerning social interaction is well developed in elderly who do not study. The students of the University of Third Age have greater needs in

Managing Measurement Uncertainty in Building Acoustics

Directory of Open Access Journals (Sweden)

Chiara Scrosati

2015-12-01

Full Text Available In general, uncertainties should preferably be determined following the principles laid down in ISO/IEC Guide 98-3, the Guide to the expression of uncertainty in measurement (GUM:1995. According to current knowledge, it seems impossible to formulate these models for the different quantities in building acoustics. Therefore, the concepts of repeatability and reproducibility are necessary to determine the uncertainty of building acoustics measurements. This study shows the uncertainty of field measurements of a lightweight wall, a heavyweight floor, a façade with a single glazing window and a façade with double glazing window that were analyzed by a Round Robin Test (RRT, conducted in a full-scale experimental building at ITC-CNR (Construction Technologies Institute of the National Research Council of Italy. The single number quantities and their uncertainties were evaluated in both narrow and enlarged range and it was shown that including or excluding the low frequencies leads to very significant differences, except in the case of the sound insulation of façades with single glazing window. The results obtained in these RRTs were compared with other results from literature, which confirm the increase of the uncertainty of single number quantities due to the low frequencies extension. Having stated the measurement uncertainty for a single measurement, in building acoustics, it is also very important to deal with sampling for the purposes of classification of buildings or building units. Therefore, this study also shows an application of the sampling included in the Italian Standard on the acoustic classification of building units on a serial type building consisting of 47 building units. It was found that the greatest variability is observed in the façade and it depends on both the great variability of window’s typologies and on workmanship. Finally, it is suggested how to manage the uncertainty in building acoustics, both for one single

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

International Nuclear Information System (INIS)

Cranwell, R.M.

1987-01-01

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

LOFT differential pressure uncertainty analysis

International Nuclear Information System (INIS)

Evans, R.P.; Biladeau, G.L.; Quinn, P.A.

1977-03-01

A performance analysis of the LOFT differential pressure (ΔP) measurement is presented. Along with completed descriptions of test programs and theoretical studies that have been conducted on the ΔP, specific sources of measurement uncertainty are identified, quantified, and combined to provide an assessment of the ability of this measurement to satisfy the SDD 1.4.1C (June 1975) requirement of measurement of differential pressure

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

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....

Uncertainty in hydrological signatures

Science.gov (United States)

McMillan, Hilary; Westerberg, Ida

2015-04-01

Information that summarises the hydrological behaviour or flow regime of a catchment is essential for comparing responses of different catchments to understand catchment organisation and similarity, and for many other modelling and water-management applications. Such information types derived as an index value from observed data are known as hydrological signatures, and can include descriptors of high flows (e.g. mean annual flood), low flows (e.g. mean annual low flow, recession shape), the flow variability, flow duration curve, and runoff ratio. Because the hydrological signatures are calculated from observed data such as rainfall and flow records, they are affected by uncertainty in those data. Subjective choices in the method used to calculate the signatures create a further source of uncertainty. Uncertainties in the signatures may affect our ability to compare different locations, to detect changes, or to compare future water resource management scenarios. The aim of this study was to contribute to the hydrological community's awareness and knowledge of data uncertainty in hydrological signatures, including typical sources, magnitude and methods for its assessment. We proposed a generally applicable method to calculate these uncertainties based on Monte Carlo sampling and demonstrated it for a variety of commonly used signatures. The study was made for two data rich catchments, the 50 km2 Mahurangi catchment in New Zealand and the 135 km2 Brue catchment in the UK. For rainfall data the uncertainty sources included point measurement uncertainty, the number of gauges used in calculation of the catchment spatial average, and uncertainties relating to lack of quality control. For flow data the uncertainty sources included uncertainties in stage/discharge measurement and in the approximation of the true stage-discharge relation by a rating curve. The resulting uncertainties were compared across the different signatures and catchments, to quantify uncertainty

A conceptual precipitation-runoff modeling suite: Model selection, calibration and predictive uncertainty assessment

Science.gov (United States)

Tyler Jon Smith

2008-01-01

In Montana and much of the Rocky Mountain West, the single most important parameter in forecasting the controls on regional water resources is snowpack. Despite the heightened importance of snowpack, few studies have considered the representation of uncertainty in coupled snowmelt/hydrologic conceptual models. Uncertainty estimation provides a direct interpretation of...

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

Collaboration patterns, external shocks and uncertainty: Swiss nuclear energy politics before and after Fukushima

International Nuclear Information System (INIS)

Fischer, Manuel

2015-01-01

Energy shocks like the Fukushima accident can have important political consequences. This article examines their impact on collaboration patterns between collective actors in policy processes. It argues that external shocks create both behavioral uncertainty, meaning that actors do not know about other actors’ preferences, and policy uncertainty on the choice and consequences of policy instruments. The context of uncertainty interacts with classical drivers of actor collaboration in policy processes. The analysis is based on a dataset comprising interview and survey data on political actors in two subsequent policy processes in Switzerland and Exponential Random Graph Models for network data. Results first show that under uncertainty, collaboration of actors in policy processes is less based on similar preferences than in stable contexts, but trust and knowledge of other actors are more important. Second, under uncertainty, scientific actors are not preferred collaboration partners. - Highlights: • Energy shocks create uncertainty in policy processes. • Behavioral and policy uncertainty have influence actors’ collaboration patterns. • Under uncertainty, collaboration is based on trust rather than on similar preferences. • Under uncertainty, scientific actors are not preferred collaboration partners, but are active themselves.

Limited entropic uncertainty as new principle of quantum physics

International Nuclear Information System (INIS)

Ion, D.B.; Ion, M.L.

2001-01-01

The Uncertainty Principle (UP) of quantum mechanics discovered by Heisenberg, which constitute the corner-stone of quantum physics, asserts that: there is an irreducible lower bound on the uncertainty in the result of a simultaneous measurement of non-commuting observables. In order to avoid this state-dependence many authors proposed to use the information entropy as a measure of the uncertainty instead of above standard quantitative formulation of the Heisenberg uncertainty principle. In this paper the Principle of Limited Entropic Uncertainty (LEU-Principle), as a new principle in quantum physics, is proved. Then, consistent experimental tests of the LEU-principle, obtained by using the available 49 sets of the pion-nucleus phase shifts, are presented for both, extensive (q=1) and nonextensive (q=0.5 and q=2.0) cases. Some results obtained by the application of LEU-Principle to the diffraction phenomena are also discussed. The main results and conclusions of our paper can be summarized as follows: (i) We introduced a new principle in quantum physics namely the Principle of Limited Entropic Uncertainty (LEU-Principle). This new principle includes in a more general and exact form not only the old Heisenberg uncertainty principle but also introduce an upper limit on the magnitude of the uncertainty in the quantum physics. The LEU-Principle asserts that: 'there is an irreducible lower bound as well as an upper bound on the uncertainty in the result of a simultaneous measurement of non-commuting observables for any extensive and nonextensive (q ≥ 0) quantum systems'; (ii) Two important concrete realizations of the LEU-Principle are explicitly obtained in this paper, namely: (a) the LEU-inequalities for the quantum scattering of spinless particles and (b) the LEU-inequalities for the diffraction on single slit of width 2a. In particular from our general results, in the limit y → +1 we recover in an exact form all the results previously reported. In our paper an

Measurement uncertainty analysis techniques applied to PV performance measurements

International Nuclear Information System (INIS)

Wells, C.

1992-10-01

The purpose of this presentation is to provide a brief introduction to measurement uncertainty analysis, outline how it is done, and illustrate uncertainty analysis with examples drawn from the PV field, with particular emphasis toward its use in PV performance measurements. The uncertainty information we know and state concerning a PV performance measurement or a module test result determines, to a significant extent, the value and quality of that result. What is measurement uncertainty analysis? It is an outgrowth of what has commonly been called error analysis. But uncertainty analysis, a more recent development, gives greater insight into measurement processes and tests, experiments, or calibration results. Uncertainty analysis gives us an estimate of the I interval about a measured value or an experiment's final result within which we believe the true value of that quantity will lie. Why should we take the time to perform an uncertainty analysis? A rigorous measurement uncertainty analysis: Increases the credibility and value of research results; allows comparisons of results from different labs; helps improve experiment design and identifies where changes are needed to achieve stated objectives (through use of the pre-test analysis); plays a significant role in validating measurements and experimental results, and in demonstrating (through the post-test analysis) that valid data have been acquired; reduces the risk of making erroneous decisions; demonstrates quality assurance and quality control measures have been accomplished; define Valid Data as data having known and documented paths of: Origin, including theory; measurements; traceability to measurement standards; computations; uncertainty analysis of results

Measurement uncertainty analysis techniques applied to PV performance measurements

Energy Technology Data Exchange (ETDEWEB)

Wells, C.

1992-10-01

The purpose of this presentation is to provide a brief introduction to measurement uncertainty analysis, outline how it is done, and illustrate uncertainty analysis with examples drawn from the PV field, with particular emphasis toward its use in PV performance measurements. The uncertainty information we know and state concerning a PV performance measurement or a module test result determines, to a significant extent, the value and quality of that result. What is measurement uncertainty analysis It is an outgrowth of what has commonly been called error analysis. But uncertainty analysis, a more recent development, gives greater insight into measurement processes and tests, experiments, or calibration results. Uncertainty analysis gives us an estimate of the I interval about a measured value or an experiment's final result within which we believe the true value of that quantity will lie. Why should we take the time to perform an uncertainty analysis A rigorous measurement uncertainty analysis: Increases the credibility and value of research results; allows comparisons of results from different labs; helps improve experiment design and identifies where changes are needed to achieve stated objectives (through use of the pre-test analysis); plays a significant role in validating measurements and experimental results, and in demonstrating (through the post-test analysis) that valid data have been acquired; reduces the risk of making erroneous decisions; demonstrates quality assurance and quality control measures have been accomplished; define Valid Data as data having known and documented paths of: Origin, including theory; measurements; traceability to measurement standards; computations; uncertainty analysis of results.

Measurement uncertainty analysis techniques applied to PV performance measurements

Energy Technology Data Exchange (ETDEWEB)

Wells, C

1992-10-01

The purpose of this presentation is to provide a brief introduction to measurement uncertainty analysis, outline how it is done, and illustrate uncertainty analysis with examples drawn from the PV field, with particular emphasis toward its use in PV performance measurements. The uncertainty information we know and state concerning a PV performance measurement or a module test result determines, to a significant extent, the value and quality of that result. What is measurement uncertainty analysis? It is an outgrowth of what has commonly been called error analysis. But uncertainty analysis, a more recent development, gives greater insight into measurement processes and tests, experiments, or calibration results. Uncertainty analysis gives us an estimate of the I interval about a measured value or an experiment`s final result within which we believe the true value of that quantity will lie. Why should we take the time to perform an uncertainty analysis? A rigorous measurement uncertainty analysis: Increases the credibility and value of research results; allows comparisons of results from different labs; helps improve experiment design and identifies where changes are needed to achieve stated objectives (through use of the pre-test analysis); plays a significant role in validating measurements and experimental results, and in demonstrating (through the post-test analysis) that valid data have been acquired; reduces the risk of making erroneous decisions; demonstrates quality assurance and quality control measures have been accomplished; define Valid Data as data having known and documented paths of: Origin, including theory; measurements; traceability to measurement standards; computations; uncertainty analysis of results.

UNCERTAINTIES IN GALACTIC CHEMICAL EVOLUTION MODELS

International Nuclear Information System (INIS)

Côté, Benoit; Ritter, Christian; Herwig, Falk; O’Shea, Brian W.; Pignatari, Marco; Jones, Samuel; Fryer, Chris L.

2016-01-01

We use a simple one-zone galactic chemical evolution model to quantify the uncertainties generated by the input parameters in numerical predictions for a galaxy with properties similar to those of the Milky Way. We compiled several studies from the literature to gather the current constraints for our simulations regarding the typical value and uncertainty of the following seven basic parameters: the lower and upper mass limits of the stellar initial mass function (IMF), the slope of the high-mass end of the stellar IMF, the slope of the delay-time distribution function of Type Ia supernovae (SNe Ia), the number of SNe Ia per M ⊙ formed, the total stellar mass formed, and the final mass of gas. We derived a probability distribution function to express the range of likely values for every parameter, which were then included in a Monte Carlo code to run several hundred simulations with randomly selected input parameters. This approach enables us to analyze the predicted chemical evolution of 16 elements in a statistical manner by identifying the most probable solutions, along with their 68% and 95% confidence levels. Our results show that the overall uncertainties are shaped by several input parameters that individually contribute at different metallicities, and thus at different galactic ages. The level of uncertainty then depends on the metallicity and is different from one element to another. Among the seven input parameters considered in this work, the slope of the IMF and the number of SNe Ia are currently the two main sources of uncertainty. The thicknesses of the uncertainty bands bounded by the 68% and 95% confidence levels are generally within 0.3 and 0.6 dex, respectively. When looking at the evolution of individual elements as a function of galactic age instead of metallicity, those same thicknesses range from 0.1 to 0.6 dex for the 68% confidence levels and from 0.3 to 1.0 dex for the 95% confidence levels. The uncertainty in our chemical evolution model

Site utility system optimization with operation adjustment under uncertainty

International Nuclear Information System (INIS)

Sun, Li; Gai, Limei; Smith, Robin

2017-01-01

Highlights: • Uncertainties are classified into time-based and probability-based uncertain factors. • Multi-period operation and recourses deal with uncertainty implementation. • Operation scheduling are specified at the design stage to deal with uncertainties. • Steam mains superheating affects steam distribution and power generation in the system. - Abstract: Utility systems must satisfy process energy and power demands under varying conditions. The system performance is decided by the system configuration and individual equipment operating load for boilers, gas turbines, steam turbines, condensers, and let down valves. Steam mains conditions in terms of steam pressures and steam superheating also play important roles on steam distribution in the system and power generation by steam expansion in steam turbines, and should be included in the system optimization. Uncertainties such as process steam power demand changes and electricity price fluctuations should be included in the system optimization to eliminate as much as possible the production loss caused by steam power deficits due to uncertainties. In this paper, uncertain factors are classified into time-based and probability-based uncertain factors, and operation scheduling containing multi-period equipment load sharing, redundant equipment start up, and electricity import to compensate for power deficits, have been presented to deal with the happens of uncertainties, and are formulated as a multi-period item and a recourse item in the optimization model. There are two case studies in this paper. One case illustrates the system design to determine system configuration, equipment selection, and system operation scheduling at the design stage to deal with uncertainties. The other case provides operational optimization scenarios for an existing system, especially when the steam superheating varies. The proposed method can provide practical guidance to system energy efficiency improvement.

The magnitude and causes of uncertainty in global model simulations of cloud condensation nuclei

Directory of Open Access Journals (Sweden)

L. A. Lee

2013-09-01

Full Text Available Aerosol–cloud interaction effects are a major source of uncertainty in climate models so it is important to quantify the sources of uncertainty and thereby direct research efforts. However, the computational expense of global aerosol models has prevented a full statistical analysis of their outputs. Here we perform a variance-based analysis of a global 3-D aerosol microphysics model to quantify the magnitude and leading causes of parametric uncertainty in model-estimated present-day concentrations of cloud condensation nuclei (CCN. Twenty-eight model parameters covering essentially all important aerosol processes, emissions and representation of aerosol size distributions were defined based on expert elicitation. An uncertainty analysis was then performed based on a Monte Carlo-type sampling of an emulator built for each model grid cell. The standard deviation around the mean CCN varies globally between about ±30% over some marine regions to ±40–100% over most land areas and high latitudes, implying that aerosol processes and emissions are likely to be a significant source of uncertainty in model simulations of aerosol–cloud effects on climate. Among the most important contributors to CCN uncertainty are the sizes of emitted primary particles, including carbonaceous combustion particles from wildfires, biomass burning and fossil fuel use, as well as sulfate particles formed on sub-grid scales. Emissions of carbonaceous combustion particles affect CCN uncertainty more than sulfur emissions. Aerosol emission-related parameters dominate the uncertainty close to sources, while uncertainty in aerosol microphysical processes becomes increasingly important in remote regions, being dominated by deposition and aerosol sulfate formation during cloud-processing. The results lead to several recommendations for research that would result in improved modelling of cloud–active aerosol on a global scale.

Uncertainty and measurement

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)

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

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.

Analysis and evaluation of regulatory uncertainties in 10 CFR 60 subparts B and E

International Nuclear Information System (INIS)

Weiner, R.F.; Patrick, W.C.

1990-01-01

This paper presents an attribute analysis scheme for prioritizing the resolution of regulatory uncertainties. Attributes are presented which assist in identifying the need for timeliness and durability of the resolution of an uncertainty

Model parameter uncertainty analysis for annual field-scale P loss model

Science.gov (United States)

Phosphorous (P) loss models are important tools for developing and evaluating conservation practices aimed at reducing P losses from agricultural fields. All P loss models, however, have an inherent amount of uncertainty associated with them. In this study, we conducted an uncertainty analysis with ...

Neural mechanisms mediating degrees of strategic uncertainty.

Science.gov (United States)

Nagel, Rosemarie; Brovelli, Andrea; Heinemann, Frank; Coricelli, Giorgio

2018-01-01

In social interactions, strategic uncertainty arises when the outcome of one's choice depends on the choices of others. An important question is whether strategic uncertainty can be resolved by assessing subjective probabilities to the counterparts' behavior, as if playing against nature, and thus transforming the strategic interaction into a risky (individual) situation. By means of functional magnetic resonance imaging with human participants we tested the hypothesis that choices under strategic uncertainty are supported by the neural circuits mediating choices under individual risk and deliberation in social settings (i.e. strategic thinking). Participants were confronted with risky lotteries and two types of coordination games requiring different degrees of strategic thinking of the kind 'I think that you think that I think etc.' We found that the brain network mediating risk during lotteries (anterior insula, dorsomedial prefrontal cortex and parietal cortex) is also engaged in the processing of strategic uncertainty in games. In social settings, activity in this network is modulated by the level of strategic thinking that is reflected in the activity of the dorsomedial and dorsolateral prefrontal cortex. These results suggest that strategic uncertainty is resolved by the interplay between the neural circuits mediating risk and higher order beliefs (i.e. beliefs about others' beliefs). © The Author(s) (2017). Published by Oxford University Press.

Uncertainty and Complementarity in Axiomatic Quantum Mechanics

Science.gov (United States)

Lahti, Pekka J.

1980-11-01

In this work an investigation of the uncertainty principle and the complementarity principle is carried through. A study of the physical content of these principles and their representation in the conventional Hilbert space formulation of quantum mechanics forms a natural starting point for this analysis. Thereafter is presented more general axiomatic framework for quantum mechanics, namely, a probability function formulation of the theory. In this general framework two extra axioms are stated, reflecting the ideas of the uncertainty principle and the complementarity principle, respectively. The quantal features of these axioms are explicated. The sufficiency of the state system guarantees that the observables satisfying the uncertainty principle are unbounded and noncompatible. The complementarity principle implies a non-Boolean proposition structure for the theory. Moreover, nonconstant complementary observables are always noncompatible. The uncertainty principle and the complementarity principle, as formulated in this work, are mutually independent. Some order is thus brought into the confused discussion about the interrelations of these two important principles. A comparison of the present formulations of the uncertainty principle and the complementarity principle with the Jauch formulation of the superposition principle is also given. The mutual independence of the three fundamental principles of the quantum theory is hereby revealed.

Quality in environmental science for policy: assessing uncertainty as a component of policy analysis

NARCIS (Netherlands)

Maxim, L.; van der Sluijs, J.P.

2011-01-01

The sheer number of attempts to define and classify uncertainty reveals an awareness of its importance in environmental science for policy, though the nature of uncertainty is often misunderstood. The interdisciplinary field of uncertainty analysis is unstable; there are currently several incomplete

Rapid research and implementation priority setting for wound care uncertainties.

Directory of Open Access Journals (Sweden)

Trish A Gray

nurses, seven podiatrists and six managers. Participants had been qualified for a mean of 20.7 years with a mean of 16.8 years of wound care experience. One hundred and thirty-nine uncertainties were submitted electronically and a further 20 were identified on the day of the workshop following lively, interactive group discussions. Twenty-five uncertainties from the total of 159 generated made it to the final prioritised list. These included six of the 20 new uncertainties. The uncertainties varied in focus, but could be broadly categorised into three themes: service delivery and organisation, patient centred care and treatment options. Specialist nurses were more likely to vote for service delivery and organisation topics, podiatrists for patient centred topics, district nurses for treatment options and operational leads for a broad range.This collaborative priority setting project is the first to engage front-line clinicians in prioritising research and implementation topics in wound care. We have shown that it is feasible to conduct topic prioritisation in a short time frame. This project has demonstrated that with careful planning and rigor, important questions that are raised in the course of clinicians' daily decision making can be translated into meaningful research and implementation initiatives that could make a difference to service delivery and patient care.

Rapid research and implementation priority setting for wound care uncertainties

Science.gov (United States)

Dumville, Jo C.; Christie, Janice; Cullum, Nicky A.

2017-01-01

, 10 district nurses, seven podiatrists and six managers. Participants had been qualified for a mean of 20.7 years with a mean of 16.8 years of wound care experience. One hundred and thirty-nine uncertainties were submitted electronically and a further 20 were identified on the day of the workshop following lively, interactive group discussions. Twenty-five uncertainties from the total of 159 generated made it to the final prioritised list. These included six of the 20 new uncertainties. The uncertainties varied in focus, but could be broadly categorised into three themes: service delivery and organisation, patient centred care and treatment options. Specialist nurses were more likely to vote for service delivery and organisation topics, podiatrists for patient centred topics, district nurses for treatment options and operational leads for a broad range. Conclusions This collaborative priority setting project is the first to engage front-line clinicians in prioritising research and implementation topics in wound care. We have shown that it is feasible to conduct topic prioritisation in a short time frame. This project has demonstrated that with careful planning and rigor, important questions that are raised in the course of clinicians’ daily decision making can be translated into meaningful research and implementation initiatives that could make a difference to service delivery and patient care. PMID:29206884

Drivers and uncertainties of forecasted range shifts for warm-water fishes under climate and land cover change

Science.gov (United States)

Bouska, Kristen; Whitledge, Gregory W.; Lant, Christopher; Schoof, Justin

2018-01-01

Land cover is an important determinant of aquatic habitat and is projected to shift with climate changes, yet climate-driven land cover changes are rarely factored into climate assessments. To quantify impacts and uncertainty of coupled climate and land cover change on warm-water fish species’ distributions, we used an ensemble model approach to project distributions of 14 species. For each species, current range projections were compared to 27 scenario-based projections and aggregated to visualize uncertainty. Multiple regression and model selection techniques were used to identify drivers of range change. Novel, or no-analogue, climates were assessed to evaluate transferability of models. Changes in total probability of occurrence ranged widely across species, from a 63% increase to a 65% decrease. Distributional gains and losses were largely driven by temperature and flow variables and underscore the importance of habitat heterogeneity and connectivity to facilitate adaptation to changing conditions. Finally, novel climate conditions were driven by mean annual maximum temperature, which stresses the importance of understanding the role of temperature on fish physiology and the role of temperature-mitigating management practices.

Essential information: Uncertainty and optimal control of Ebola outbreaks.

Science.gov (United States)

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

Science.gov (United States)

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.

Optimization Under Uncertainty for Wake Steering Strategies: Preprint

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

2017-05-01

Wind turbines in a wind power plant experience significant power losses because of aerodynamic interactions between turbines. One control strategy to reduce these losses is known as 'wake steering,' in which upstream turbines are yawed to direct wakes away from downstream turbines. Previous wake steering research has assumed perfect information, however, there can be significant uncertainty in many aspects of the problem, including wind inflow and various turbine measurements. Uncertainty has significant implications for performance of wake steering strategies. Consequently, the authors formulate and solve an optimization under uncertainty (OUU) problem for finding optimal wake steering strategies in the presence of yaw angle uncertainty. The OUU wake steering strategy is demonstrated on a two-turbine test case and on the utility-scale, offshore Princess Amalia Wind Farm. When we accounted for yaw angle uncertainty in the Princess Amalia Wind Farm case, inflow-direction-specific OUU solutions produced between 0% and 1.4% more power than the deterministically optimized steering strategies, resulting in an overall annual average improvement of 0.2%. More importantly, the deterministic optimization is expected to perform worse and with more downside risk than the OUU result when realistic uncertainty is taken into account. Additionally, the OUU solution produces fewer extreme yaw situations than the deterministic solution.

Reducing the top quark mass uncertainty with jet grooming

Science.gov (United States)

Andreassen, Anders; Schwartz, Matthew D.

2017-10-01

The measurement of the top quark mass has large systematic uncertainties coming from the Monte Carlo simulations that are used to match theory and experiment. We explore how much that uncertainty can be reduced by using jet grooming procedures. Using the ATLAS A14 tunes of pythia, we estimate the uncertainty from the choice of tuning parameters in what is meant by the Monte Carlo mass to be around 530 MeV without any corrections. This uncertainty can be reduced by 60% to 200 MeV by calibrating to the W mass and by 70% to 140 MeV by additionally applying soft-drop jet grooming (or to 170 MeV using trimming). At e + e - colliders, the associated uncertainty is around 110 MeV, reducing to 50 MeV after calibrating to the W mass. By analyzing the tuning parameters, we conclude that the importance of jet grooming after calibrating to the W -mass is to reduce sensitivity to the underlying event.

Compliance uncertainty of diameter characteristic in the next-generation geometrical product specifications and verification

International Nuclear Information System (INIS)

Lu, W L; Jiang, X; Liu, X J; Xu, Z G

2008-01-01

Compliance uncertainty is one of the most important elements in the next-generation geometrical product specifications and verification (GPS). It consists of specification uncertainty, method uncertainty and implementation uncertainty, which are three of the four fundamental uncertainties in the next-generation GPS. This paper analyzes the key factors that influence compliance uncertainty and then proposes a procedure to manage the compliance uncertainty. A general model on evaluation of compliance uncertainty has been devised and a specific formula for diameter characteristic has been derived based on this general model. The case study was conducted and it revealed that the completeness of currently dominant diameter characteristic specification needs to be improved

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

Directory of Open Access Journals (Sweden)

Kelly C. Chang

2017-11-01

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

Resolving structural uncertainty in natural resources management using POMDP approaches

Science.gov (United States)

Williams, B.K.

2011-01-01

In recent years there has been a growing focus on the uncertainties of natural resources management, and the importance of accounting for uncertainty in assessing management effectiveness. This paper focuses on uncertainty in resource management in terms of discrete-state Markov decision processes (MDP) under structural uncertainty and partial observability. It describes the treatment of structural uncertainty with approaches developed for partially observable resource systems. In particular, I show how value iteration for partially observable MDPs (POMDP) can be extended to structurally uncertain MDPs. A key difference between these process classes is that structurally uncertain MDPs require the tracking of system state as well as a probability structure for the structure uncertainty, whereas with POMDPs require only a probability structure for the observation uncertainty. The added complexity of the optimization problem under structural uncertainty is compensated by reduced dimensionality in the search for optimal strategy. A solution algorithm for structurally uncertain processes is outlined for a simple example in conservation biology. By building on the conceptual framework developed for POMDPs, natural resource analysts and decision makers who confront structural uncertainties in natural resources can take advantage of the rapid growth in POMDP methods and approaches, and thereby produce better conservation strategies over a larger class of resource problems. ?? 2011.

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.))

The neurobiology of uncertainty: implications for statistical learning.

Science.gov (United States)

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 in Reference and Information Service

Science.gov (United States)

VanScoy, Amy

2015-01-01

Introduction: Uncertainty is understood as an important component of the information seeking process, but it has not been explored as a component of reference and information service. Method: Interpretative phenomenological analysis was used to examine the practitioner perspective of reference and information service for eight academic research…

Optimal Sizing of Energy Storage Systems for the Energy Procurement Problem in Multi-Period Markets under Uncertainties

Directory of Open Access Journals (Sweden)

Ryusuke Konishi

2018-01-01

Full Text Available In deregulated electricity markets, minimizing the procurement costs of electricity is a critical problem for procurement agencies (PAs. However, uncertainty is inevitable for PAs and includes multiple factors such as market prices, photovoltaic system (PV output and demand. This study focuses on settlements in multi-period markets (a day-ahead market and a real-time market and the installation of energy storage systems (ESSs. ESSs can be utilized for time arbitrage in the day-ahead market and to reduce the purchasing/selling of electricity in the real-time market. However, the high costs of an ESS mean the size of the system needs to be minimized. In addition, when determining the size of an ESS, it is important to identify the size appropriate for each role. Therefore, we employ the concept of a “slow” and a “fast” ESS to quantify the size of a system’s role, based on the values associated with the various uncertainties. Because the problem includes nonlinearity and non-convexity, we solve it within a realistic computational burden by reformulating the problem using reasonable assumptions. Therefore, this study identifies the optimal sizes of ESSs and procurement, taking into account the uncertainties of prices in multi-period markets, PV output and demand.

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

Science.gov (United States)

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

2012-12-01

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

Assessing and communicating climate change uncertainties : case of the Rhine basin

NARCIS (Netherlands)

Pelt, van S.C.

2014-01-01

The main aim of this thesis is to analyse the climate change uncertainties that are important to take into account for long term water management and to explore the communication of these uncertainties. The study design combines natural and social scientific theories and methods and consists of

Uncertainty analysis and validation of environmental models. The empirically based uncertainty analysis

International Nuclear Information System (INIS)

Monte, Luigi; Hakanson, Lars; Bergstroem, Ulla; Brittain, John; Heling, Rudie

1996-01-01

The principles of Empirically Based Uncertainty Analysis (EBUA) are described. EBUA is based on the evaluation of 'performance indices' that express the level of agreement between the model and sets of empirical independent data collected in different experimental circumstances. Some of these indices may be used to evaluate the confidence limits of the model output. The method is based on the statistical analysis of the distribution of the index values and on the quantitative relationship of these values with the ratio 'experimental data/model output'. Some performance indices are described in the present paper. Among these, the so-called 'functional distance' (d) between the logarithm of model output and the logarithm of the experimental data, defined as d 2 =Σ n 1 ( ln M i - ln O i ) 2 /n where M i is the i-th experimental value, O i the corresponding model evaluation and n the number of the couplets 'experimental value, predicted value', is an important tool for the EBUA method. From the statistical distribution of this performance index, it is possible to infer the characteristics of the distribution of the ratio 'experimental data/model output' and, consequently to evaluate the confidence limits for the model predictions. This method was applied to calculate the uncertainty level of a model developed to predict the migration of radiocaesium in lacustrine systems. Unfortunately, performance indices are affected by the uncertainty of the experimental data used in validation. Indeed, measurement results of environmental levels of contamination are generally associated with large uncertainty due to the measurement and sampling techniques and to the large variability in space and time of the measured quantities. It is demonstrated that this non-desired effect, in some circumstances, may be corrected by means of simple formulae

Uncertainty evaluation in 2008 IAEA proficiency test using phosphogypsum

International Nuclear Information System (INIS)

Dias, Fabiana F.; Taddei, Maria Helena T.; Geraldo, Bianca; Jacomino, Vanusa M.F.; Pontedeiro, Elizabeth M.B.

2009-01-01

LAPOC participated in the 2008 IAEA ALMERA (Analytical Laboratories for the Measurement of Environmental Radioactivity) Proficiency Test (PT) for phosphogypsum, which is a NORM (Naturally Occurring Radioactive Material) derived from phosphate industry, an abundant solid waste of low cost. Its reutilization would avoid environmental impact in large areas where the product is stored. Research involving possible uses for phosphogypsum is ever more important, from economic, technological, and environmental points of view. This paper describes results from this Proficiency Test (measured radionuclides: 234 U, 238 U, 226 Ra, 230 Th, and 210 Pb), as well as a short description of the nuclear analytical techniques emphasizing sources of uncertainty, such as Alpha Spectrometry (Alpha Analyst, Canberra, surface barrier detectors) and Gamma Spectrometry (Canberra, Hyper Pure Germanium Detector with 45 % efficiency). Corrections for decay, reference date, and recovery were applied. As an example, results obtained for 210 Pb through the use of a specific uncertainty calculation software are presented below. Each parameter whose uncertainty is quantified was carefully described, with appropriate numerical value and unit, to determine its partial contribution to the combined total uncertainty. Results from PTs provide independent information on performance of a Laboratory and have an important role in method validation; especially because it allows the assessment of the method performance over an entire range of concentrations and matrices. PTs are an important tool to demonstrate equivalence of measurements, if not their metrological comparability, and to promote education and improvement of Laboratory practice. (author)

Impact of Climate Change. Policy Uncertainty in Power Investment

International Nuclear Information System (INIS)

Blyth, W.; Yang, M.

2006-10-01

Climate change policies are being introduced or actively considered in all IEA member countries, changing the investment conditions and technology choices in the energy sector. Many of these policies are at a formative stage, and policy uncertainty is currently high. The objective of this paper is to quantify the impacts of climate change policy on power investment. We use Real Options Analysis approach in the study and model uncertain carbon price and fuel price with stochastic variables. The analysis compares the effects of climate policy uncertainty with fuel price uncertainty, showing the relative importance of these sources of risk for different technologies. This paper considers views on the importance of climate policy risk, how it is managed, and how it might affect investment behaviour. The implications for policymakers are analyzed, allowing the key messages to be transferred into policy design decisions. We found that in many cases, the dominant risks facing base-load generation investment decisions will be market risks associated with electricity and fuel prices. However, under certain conditions and for some technologies, climate policy uncertainty can be an important risk factor, creating an incentive to delay investment and raising investment thresholds. This paper concludes that government climate change policies to promote investment in low-carbon technologies should aim to overcome this incentive to delay by sending long-term investment signals backed up by strengthened international policy action to enhance domestic policy credibility

General Practitioners' Experiences of, and Responses to, Uncertainty in Prostate Cancer Screening: Insights from a Qualitative Study.

Directory of Open Access Journals (Sweden)

Kristen Pickles

Full Text Available Prostate-specific antigen (PSA testing for prostate cancer is controversial. There are unresolved tensions and disagreements amongst experts, and clinical guidelines conflict. This both reflects and generates significant uncertainty about the appropriateness of screening. Little is known about general practitioners' (GPs' perspectives and experiences in relation to PSA testing of asymptomatic men. In this paper we asked the following questions: (1 What are the primary sources of uncertainty as described by GPs in the context of PSA testing? (2 How do GPs experience and respond to different sources of uncertainty?This was a qualitative study that explored general practitioners' current approaches to, and reasoning about, PSA testing of asymptomatic men. We draw on accounts generated from interviews with 69 general practitioners located in Australia (n = 40 and the United Kingdom (n = 29. The interviews were conducted in 2013-2014. Data were analysed using grounded theory methods. Uncertainty in PSA testing was identified as a core issue.Australian GPs reported experiencing substantially more uncertainty than UK GPs. This seemed partly explainable by notable differences in conditions of practice between the two countries. Using Han et al's taxonomy of uncertainty as an initial framework, we first outline the different sources of uncertainty GPs (mostly Australian described encountering in relation to prostate cancer screening and what the uncertainty was about. We then suggest an extension to Han et al's taxonomy based on our analysis of data relating to the varied ways that GPs manage uncertainties in the context of PSA testing. We outline three broad strategies: (1 taking charge of uncertainty; (2 engaging others in managing uncertainty; and (3 transferring the responsibility for reducing or managing some uncertainties to other parties.Our analysis suggests some GPs experienced uncertainties associated with ambiguous guidance and the

The cerebellum and decision making under uncertainty.

Science.gov (United States)

Blackwood, Nigel; Ffytche, Dominic; Simmons, Andrew; Bentall, Richard; Murray, Robin; Howard, Robert

2004-06-01

This study aimed to identify the neural basis of probabilistic reasoning, a type of inductive inference that aids decision making under conditions of uncertainty. Eight normal subjects performed two separate two-alternative-choice tasks (the balls in a bottle and personality survey tasks) while undergoing functional magnetic resonance imaging (fMRI). The experimental conditions within each task were chosen so that they differed only in their requirement to make a decision under conditions of uncertainty (probabilistic reasoning and frequency determination required) or under conditions of certainty (frequency determination required). The same visual stimuli and motor responses were used in the experimental conditions. We provide evidence that the neo-cerebellum, in conjunction with the premotor cortex, inferior parietal lobule and medial occipital cortex, mediates the probabilistic inferences that guide decision making under uncertainty. We hypothesise that the neo-cerebellum constructs internal working models of uncertain events in the external world, and that such probabilistic models subserve the predictive capacity central to induction. Copyright 2004 Elsevier B.V.

Identify the Important Decision Factors of Online Shopping Adoption in Indonesia