Uncertainty Estimate in Resources Assessment: A Geostatistical Contribution

International Nuclear Information System (INIS)

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

2004-01-01

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

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.

Evaluating Uncertainties in Sap Flux Scaled Estimates of Forest Transpiration, Canopy Conductance and Photosynthesis

Science.gov (United States)

Ward, E. J.; Bell, D. M.; Clark, J. S.; Kim, H.; Oren, R.

2009-12-01

Thermal dissipation probes (TDPs) are a common method for estimating forest transpiration and canopy conductance from sap flux rates in trees, but their implementation is plagued by uncertainties arising from missing data and variability in the diameter and canopy position of trees, as well as sapwood conductivity within individual trees. Uncertainties in estimates of canopy conductance also translate into uncertainties in carbon assimilation in models such as the Canopy Conductance Constrained Carbon Assimilation (4CA) model that combine physiological and environmental data to estimate photosynthetic rates. We developed a method to propagate these uncertainties in the scaling and imputation of TDP data to estimates of canopy transpiration and conductance using a state-space Jarvis-type conductance model in a hierarchical Bayesian framework. This presentation will focus on the impact of these uncertainties on estimates of water and carbon fluxes using 4CA and data from the Duke Free Air Carbon Enrichment (FACE) project, which incorporates both elevated carbon dioxide and soil nitrogen treatments. We will also address the response of canopy conductance to vapor pressure deficit, incident radiation and soil moisture, as well as the effect of treatment-related stand structure differences in scaling TDP measurements. Preliminary results indicate that in 2006, a year of normal precipitation (1127 mm), canopy transpiration increased in elevated carbon dioxide ~8% on a ground area basis. In 2007, a year with a pronounced drought (800 mm precipitation), this increase was only present in the combined carbon dioxide and fertilization treatment. The seasonal dynamics of water and carbon fluxes will be discussed in detail.

Calibration and Measurement Uncertainty Estimation of Radiometric Data: Preprint

Energy Technology Data Exchange (ETDEWEB)

Habte, A.; Sengupta, M.; Reda, I.; Andreas, A.; Konings, J.

2014-11-01

Evaluating the performance of photovoltaic cells, modules, and arrays that form large solar deployments relies on accurate measurements of the available solar resource. Therefore, determining the accuracy of these solar radiation measurements provides a better understanding of investment risks. This paper provides guidelines and recommended procedures for estimating the uncertainty in calibrations and measurements by radiometers using methods that follow the International Bureau of Weights and Measures Guide to the Expression of Uncertainty (GUM). Standardized analysis based on these procedures ensures that the uncertainty quoted is well documented.

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)

Verification and uncertainty evaluation of HELIOS/MASTER nuclear design system

Energy Technology Data Exchange (ETDEWEB)

Song, Jae Seung; Kim, J. C.; Cho, B. O. [Korea Atomic Energy Research Institute, Taejon (Korea)

1999-03-01

A nuclear design system HELIOS/MASTER was established and core follow calculations were performed for Yonggwang Unit 1 cycles 1 through 7 and Yonggwang Unit 3 cycles 1 through 2. The accuracy of HELIOS/MASTER system was evaluated by estimations of uncertainties of reactivity and peaking factors and by comparisons of the maximum differences of isothermal temperature coefficient, inverse boron worth and control rod worth with the CASMO-3/MASTER uncertainties. The reactivity uncertainty was estimated by 362 pcm, and the uncertainties of three-dimensional, axially integrated radial, and planar peaking factors were evaluated by 0.048, 0.034, and 0.044 in relative power unit, respectively. The maximum differences of isothermal temperature coefficient, inverse boron worth and control rod worth were within the CASMO-3/MASTER uncertainties. 17 refs., 17 figs., 10 tabs. (Author)

Approximate Bayesian evaluations of measurement uncertainty

Science.gov (United States)

Possolo, Antonio; Bodnar, Olha

2018-04-01

The Guide to the Expression of Uncertainty in Measurement (GUM) includes formulas that produce an estimate of a scalar output quantity that is a function of several input quantities, and an approximate evaluation of the associated standard uncertainty. This contribution presents approximate, Bayesian counterparts of those formulas for the case where the output quantity is a parameter of the joint probability distribution of the input quantities, also taking into account any information about the value of the output quantity available prior to measurement expressed in the form of a probability distribution on the set of possible values for the measurand. The approximate Bayesian estimates and uncertainty evaluations that we present have a long history and illustrious pedigree, and provide sufficiently accurate approximations in many applications, yet are very easy to implement in practice. Differently from exact Bayesian estimates, which involve either (analytical or numerical) integrations, or Markov Chain Monte Carlo sampling, the approximations that we describe involve only numerical optimization and simple algebra. Therefore, they make Bayesian methods widely accessible to metrologists. We illustrate the application of the proposed techniques in several instances of measurement: isotopic ratio of silver in a commercial silver nitrate; odds of cryptosporidiosis in AIDS patients; height of a manometer column; mass fraction of chromium in a reference material; and potential-difference in a Zener voltage standard.

Estimating annual bole biomass production using uncertainty analysis

Science.gov (United States)

Travis J. Woolley; Mark E. Harmon; Kari B. O' Connell

2007-01-01

Two common sampling methodologies coupled with a simple statistical model were evaluated to determine the accuracy and precision of annual bole biomass production (BBP) and inter-annual variability estimates using this type of approach. We performed an uncertainty analysis using Monte Carlo methods in conjunction with radial growth core data from trees in three Douglas...

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...

Supporting qualified database for V and V and uncertainty evaluation of best-estimate system codes

International Nuclear Information System (INIS)

Petruzzi, A.; D'Auria, F.

2014-01-01

Uncertainty evaluation constitutes a key feature of BEPU (Best Estimate Plus Uncertainty) process. The uncertainty can be the result of a Monte Carlo type analysis involving input uncertainty parameters or the outcome of a process involving the use of experimental data and connected code calculations. Those uncertainty methods are discussed in several papers and guidelines (IAEA-SRS- 52, OECD/NEA BEMUSE reports). The present paper aims at discussing the role and the depth of the analysis required for merging from one side suitable experimental data and on the other side qualified code calculation results. This aspect is mostly connected with the second approach for uncertainty mentioned above, but it can be used also in the framework of the first approach. Namely, the paper discusses the features and structure of the database that includes the following kinds of documents: 1. The' RDS-facility' (Reference Data Set for the selected facility): this includes the description of the facility, the geometrical characterization of any component of the facility, the instrumentations, the data acquisition system, the evaluation of pressure losses, the physical properties of the material and the characterization of pumps, valves and heat losses; 2. The 'RDS-test' (Reference Data Set for the selected test of the facility): this includes the description of the main phenomena investigated during the test, the configuration of the facility for the selected test (possible new evaluation of pressure and heat losses if needed) and the specific boundary and initial conditions; 3. The 'QP' (Qualification Report) of the code calculation results: this includes the description of the nodalization developed following a set of homogeneous techniques, the achievement of the steady state conditions and the qualitative and quantitative analysis of the transient with the characterization of the Relevant Thermal-Hydraulics Aspects (RTA); 4. The EH (Engineering

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

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.

Top-down instead of bottom-up estimates of uncertainty in INAA results?

International Nuclear Information System (INIS)

Bode, P.; De Nadai Fernandes, E.A.

2005-01-01

The initial publication of the ISO Guide to the Expression of Uncertainty in Measurement (GUM) and many related documents has resulted in a worldwide awareness of the importance of a realistic estimate of the value reported after the +/- sign. The evaluation of uncertainty in measurement, as introduced by the GUM, is derived from the principles applied in physical measurements. Many testing laboratories have already experienced large problems in applying these principles in e.g. (bio)chemical measurements, resulting in time-consuming evaluations and costly additional experiments. Other, more pragmatic and less costly approaches have been proposed to obtain a realistic estimate of the range in which the true value of the measurement may be found with a certain degree of probability. One of these approaches, the 'top-down method', is based on the standard deviation in the results of intercomparison data. This approach is much easier for tests for which it is either difficult to establish a full measurement equation, or if e.g. matrix-matching reference materials are absent. It has been demonstrated that the GUM 'bottom-up' approach of evaluating uncertainty in measurement can easily be applied in instrumental neutron activation analysis (INAA) as all significant sources of uncertainty can be evaluated. INAA is therefore a valuable technique to test the validity of the top-down approach. In this contribution, examples of the top-down evaluation of uncertainty in INAA derived from participation in intercomparison rounds and proficiency testing schemes will be presented. The results will be compared with the bottom-up evaluation of uncertainty, and ease of applicability, validity and usefullness of both approaches will be discussed.

Sensitivity and uncertainty analysis for the annual phosphorus loss estimator model.

Science.gov (United States)

Bolster, Carl H; Vadas, Peter A

2013-07-01

Models are often used to predict phosphorus (P) loss from agricultural fields. Although it is commonly recognized that model predictions are inherently uncertain, few studies have addressed prediction uncertainties using P loss models. In this study we assessed the effect of model input error on predictions of annual P loss by the Annual P Loss Estimator (APLE) model. Our objectives were (i) to conduct a sensitivity analyses for all APLE input variables to determine which variables the model is most sensitive to, (ii) to determine whether the relatively easy-to-implement first-order approximation (FOA) method provides accurate estimates of model prediction uncertainties by comparing results with the more accurate Monte Carlo simulation (MCS) method, and (iii) to evaluate the performance of the APLE model against measured P loss data when uncertainties in model predictions and measured data are included. Our results showed that for low to moderate uncertainties in APLE input variables, the FOA method yields reasonable estimates of model prediction uncertainties, although for cases where manure solid content is between 14 and 17%, the FOA method may not be as accurate as the MCS method due to a discontinuity in the manure P loss component of APLE at a manure solid content of 15%. The estimated uncertainties in APLE predictions based on assumed errors in the input variables ranged from ±2 to 64% of the predicted value. Results from this study highlight the importance of including reasonable estimates of model uncertainty when using models to predict P loss. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Evaluation and uncertainty analysis of regional-scale CLM4.5 net carbon flux estimates

Science.gov (United States)

Post, Hanna; Hendricks Franssen, Harrie-Jan; Han, Xujun; Baatz, Roland; Montzka, Carsten; Schmidt, Marius; Vereecken, Harry

2018-01-01

Modeling net ecosystem exchange (NEE) at the regional scale with land surface models (LSMs) is relevant for the estimation of regional carbon balances, but studies on it are very limited. Furthermore, it is essential to better understand and quantify the uncertainty of LSMs in order to improve them. An important key variable in this respect is the prognostic leaf area index (LAI), which is very sensitive to forcing data and strongly affects the modeled NEE. We applied the Community Land Model (CLM4.5-BGC) to the Rur catchment in western Germany and compared estimated and default ecological key parameters for modeling carbon fluxes and LAI. The parameter estimates were previously estimated with the Markov chain Monte Carlo (MCMC) approach DREAM(zs) for four of the most widespread plant functional types in the catchment. It was found that the catchment-scale annual NEE was strongly positive with default parameter values but negative (and closer to observations) with the estimated values. Thus, the estimation of CLM parameters with local NEE observations can be highly relevant when determining regional carbon balances. To obtain a more comprehensive picture of model uncertainty, CLM ensembles were set up with perturbed meteorological input and uncertain initial states in addition to uncertain parameters. C3 grass and C3 crops were particularly sensitive to the perturbed meteorological input, which resulted in a strong increase in the standard deviation of the annual NEE sum (σ ∑ NEE) for the different ensemble members from ˜ 2 to 3 g C m-2 yr-1 (with uncertain parameters) to ˜ 45 g C m-2 yr-1 (C3 grass) and ˜ 75 g C m-2 yr-1 (C3 crops) with perturbed forcings. This increase in uncertainty is related to the impact of the meteorological forcings on leaf onset and senescence, and enhanced/reduced drought stress related to perturbation of precipitation. The NEE uncertainty for the forest plant functional type (PFT) was considerably lower (σ ∑ NEE ˜ 4.0-13.5 g C

Uncertainty and conservatism in safety evaluations based on a BEPU approach

International Nuclear Information System (INIS)

Yamaguchi, A.; Mizokami, S.; Kudo, Y.; Hotta, A.

2009-01-01

Atomic Energy Society of Japan has published 'Standard Method for Safety Evaluation using Best Estimate Code Based on Uncertainty and Scaling Analyses with Statistical Approach' to be applied to accidents and AOOs in the safety evaluation of LWRs. In this method, hereafter named as the AESJ-SSE (Statistical Safety Evaluation) method, identification and quantification of uncertainties will be performed and then a combination of the best estimate code and the evaluation of uncertainty propagation will be performed. Uncertainties are categorized into bias and variability. In general, bias is related to our state-of-knowledge on uncertainty objects (modeling, scaling, input data, etc.) while variability reflects stochastic features involved in these objects. Considering many kinds of uncertainties in thermal-hydraulics models and experimental databases show variabilities that will be strongly influenced by our state of knowledge, it seems reasonable that these variabilities are also related to state-of-knowledge. The design basis events (DBEs) that are employed for licensing analyses form a main part of the given or prior conservatism. The regulatory acceptance criterion is also regarded as the prior conservatism. In addition to these prior conservatisms, a certain amount of the posterior conservatism is added with maintaining intimate relationships with state-of-knowledge. In the AESJ-SSE method, this posterior conservatism can be incorporated into the safety evaluation in a combination of the following three ways, (1) broadening ranges of variability relevant to uncertainty objects, (2) employing more disadvantageous biases relevant to uncertainty objects and (3) adding an extra bias to the safety evaluation results. Knowing implemented quantitative bases of uncertainties and conservatism, the AESJ-SSE method provides a useful ground for rational decision-making. In order to seek for 'the best estimation' as well as reasonably setting the analytical margin, a degree

Estimates of Uncertainty around the RBA's Forecasts

OpenAIRE

Peter Tulip; Stephanie Wallace

2012-01-01

We use past forecast errors to construct confidence intervals and other estimates of uncertainty around the Reserve Bank of Australia's forecasts of key macroeconomic variables. Our estimates suggest that uncertainty about forecasts is high. We find that the RBA's forecasts have substantial explanatory power for the inflation rate but not for GDP growth.

Uncertainty estimation of uranium determination in urine by fluorometry

International Nuclear Information System (INIS)

Shakhashiro, A.; Al-Khateeb, S.

2003-11-01

In this study an applicable mathematical model is proposed for the estimation of uncertainty in uranium determination by fluorometry in urine sample. The study based on EURACHEM guide for uncertainty estimation. This model was tested on a sample containing 0.02 μg/ml uranium, where calculated uncertainty was 0.007 μg/ml. The sources of uncertainty were shown on fish-bone plane as the following: In addition, the weight of each uncertainty parameter was shown in a histogram: Finally, it was found that the estimated uncertainty by the proposed model was 3 to 4 time more that the usually reported standard deviation. (author)

Estimation of uncertainties in predictions of environmental transfer models: evaluation of methods and application to CHERPAC

International Nuclear Information System (INIS)

Koch, J.; Peterson, S-R.

1995-10-01

Models used to simulate environmental transfer of radionuclides typically include many parameters, the values of which are uncertain. An estimation of the uncertainty associated with the predictions is therefore essential. Difference methods to quantify the uncertainty in the prediction parameter uncertainties are reviewed. A statistical approach using random sampling techniques is recommended for complex models with many uncertain parameters. In this approach, the probability density function of the model output is obtained from multiple realizations of the model according to a multivariate random sample of the different input parameters. Sampling efficiency can be improved by using a stratified scheme (Latin Hypercube Sampling). Sample size can also be restricted when statistical tolerance limits needs to be estimated. Methods to rank parameters according to their contribution to uncertainty in the model prediction are also reviewed. Recommended are measures of sensitivity, correlation and regression coefficients that can be calculated on values of input and output variables generated during the propagation of uncertainties through the model. A parameter uncertainty analysis is performed for the CHERPAC food chain model which estimates subjective confidence limits and intervals on the predictions at a 95% confidence level. A sensitivity analysis is also carried out using partial rank correlation coefficients. This identified and ranks the parameters which are the main contributors to uncertainty in the predictions, thereby guiding further research efforts. (author). 44 refs., 2 tabs., 4 figs

Estimation of uncertainties in predictions of environmental transfer models: evaluation of methods and application to CHERPAC

Energy Technology Data Exchange (ETDEWEB)

Koch, J. [Israel Atomic Energy Commission, Yavne (Israel). Soreq Nuclear Research Center; Peterson, S-R.

1995-10-01

Models used to simulate environmental transfer of radionuclides typically include many parameters, the values of which are uncertain. An estimation of the uncertainty associated with the predictions is therefore essential. Difference methods to quantify the uncertainty in the prediction parameter uncertainties are reviewed. A statistical approach using random sampling techniques is recommended for complex models with many uncertain parameters. In this approach, the probability density function of the model output is obtained from multiple realizations of the model according to a multivariate random sample of the different input parameters. Sampling efficiency can be improved by using a stratified scheme (Latin Hypercube Sampling). Sample size can also be restricted when statistical tolerance limits needs to be estimated. Methods to rank parameters according to their contribution to uncertainty in the model prediction are also reviewed. Recommended are measures of sensitivity, correlation and regression coefficients that can be calculated on values of input and output variables generated during the propagation of uncertainties through the model. A parameter uncertainty analysis is performed for the CHERPAC food chain model which estimates subjective confidence limits and intervals on the predictions at a 95% confidence level. A sensitivity analysis is also carried out using partial rank correlation coefficients. This identified and ranks the parameters which are the main contributors to uncertainty in the predictions, thereby guiding further research efforts. (author). 44 refs., 2 tabs., 4 figs.

Parameter estimation techniques and uncertainty in ground water flow model predictions

International Nuclear Information System (INIS)

Zimmerman, D.A.; Davis, P.A.

1990-01-01

Quantification of uncertainty in predictions of nuclear waste repository performance is a requirement of Nuclear Regulatory Commission regulations governing the licensing of proposed geologic repositories for high-level radioactive waste disposal. One of the major uncertainties in these predictions is in estimating the ground-water travel time of radionuclides migrating from the repository to the accessible environment. The cause of much of this uncertainty has been attributed to a lack of knowledge about the hydrogeologic properties that control the movement of radionuclides through the aquifers. A major reason for this lack of knowledge is the paucity of data that is typically available for characterizing complex ground-water flow systems. Because of this, considerable effort has been put into developing parameter estimation techniques that infer property values in regions where no measurements exist. Currently, no single technique has been shown to be superior or even consistently conservative with respect to predictions of ground-water travel time. This work was undertaken to compare a number of parameter estimation techniques and to evaluate how differences in the parameter estimates and the estimation errors are reflected in the behavior of the flow model predictions. That is, we wished to determine to what degree uncertainties in flow model predictions may be affected simply by the choice of parameter estimation technique used. 3 refs., 2 figs

Mass discharge estimation from contaminated sites: Multi-model solutions for assessment of conceptual uncertainty

DEFF Research Database (Denmark)

Thomsen, Nanna Isbak; Troldborg, Mads; McKnight, Ursula S.

2012-01-01

site. The different conceptual models consider different source characterizations and hydrogeological descriptions. The idea is to include a set of essentially different conceptual models where each model is believed to be realistic representation of the given site, based on the current level...... the appropriate management option. The uncertainty of mass discharge estimates depends greatly on the extent of the site characterization. A good approach for uncertainty estimation will be flexible with respect to the investigation level, and account for both parameter and conceptual model uncertainty. We...... propose a method for quantifying the uncertainty of dynamic mass discharge estimates from contaminant point sources on the local scale. The method considers both parameter and conceptual uncertainty through a multi-model approach. The multi-model approach evaluates multiple conceptual models for the same...

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

Uncertainty quantification of surface-water/groundwater exchange estimates in large wetland systems using Python

Science.gov (United States)

Hughes, J. D.; Metz, P. A.

2014-12-01

Most watershed studies include observation-based water budget analyses to develop first-order estimates of significant flow terms. Surface-water/groundwater (SWGW) exchange is typically assumed to be equal to the residual of the sum of inflows and outflows in a watershed. These estimates of SWGW exchange, however, are highly uncertain as a result of the propagation of uncertainty inherent in the calculation or processing of the other terms of the water budget, such as stage-area-volume relations, and uncertainties associated with land-cover based evapotranspiration (ET) rate estimates. Furthermore, the uncertainty of estimated SWGW exchanges can be magnified in large wetland systems that transition from dry to wet during wet periods. Although it is well understood that observation-based estimates of SWGW exchange are uncertain it is uncommon for the uncertainty of these estimates to be directly quantified. High-level programming languages like Python can greatly reduce the effort required to (1) quantify the uncertainty of estimated SWGW exchange in large wetland systems and (2) evaluate how different approaches for partitioning land-cover data in a watershed may affect the water-budget uncertainty. We have used Python with the Numpy, Scipy.stats, and pyDOE packages to implement an unconstrained Monte Carlo approach with Latin Hypercube sampling to quantify the uncertainty of monthly estimates of SWGW exchange in the Floral City watershed of the Tsala Apopka wetland system in west-central Florida, USA. Possible sources of uncertainty in the water budget analysis include rainfall, ET, canal discharge, and land/bathymetric surface elevations. Each of these input variables was assigned a probability distribution based on observation error or spanning the range of probable values. The Monte Carlo integration process exposes the uncertainties in land-cover based ET rate estimates as the dominant contributor to the uncertainty in SWGW exchange estimates. We will discuss

Addressing Uncertainties in Cost Estimates for Decommissioning Nuclear Facilities

International Nuclear Information System (INIS)

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

2017-01-01

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

Uncertainties in Organ Burdens Estimated from PAS

International Nuclear Information System (INIS)

La Bone, T.R.

2004-01-01

To calculate committed effective dose equivalent, one needs to know the quantity of the radionuclide in all significantly irradiated organs (the organ burden) as a function of time following the intake. There are two major sources of uncertainty in an organ burden estimated from personal air sampling (PAS) data: (1) The uncertainty in going from the exposure measured with the PAS to the quantity of aerosol inhaled by the individual, and (2) The uncertainty in going from the intake to the organ burdens at any given time, taking into consideration the biological variability of the biokinetic models from person to person (interperson variability) and in one person over time (intra-person variability). We have been using biokinetic modeling methods developed by researchers at the University of Florida to explore the impact of inter-person variability on the uncertainty of organ burdens estimated from PAS data. These initial studies suggest that the uncertainties are so large that PAS might be considered to be a qualitative (rather than quantitative) technique. These results indicate that more studies should be performed to properly classify the reliability and usefulness of using PAS monitoring data to estimate organ burdens, organ dose, and ultimately CEDE

Gaussian Process Interpolation for Uncertainty Estimation in Image Registration

Science.gov (United States)

Wachinger, Christian; Golland, Polina; Reuter, Martin; Wells, William

2014-01-01

Intensity-based image registration requires resampling images on a common grid to evaluate the similarity function. The uncertainty of interpolation varies across the image, depending on the location of resampled points relative to the base grid. We propose to perform Bayesian inference with Gaussian processes, where the covariance matrix of the Gaussian process posterior distribution estimates the uncertainty in interpolation. The Gaussian process replaces a single image with a distribution over images that we integrate into a generative model for registration. Marginalization over resampled images leads to a new similarity measure that includes the uncertainty of the interpolation. We demonstrate that our approach increases the registration accuracy and propose an efficient approximation scheme that enables seamless integration with existing registration methods. PMID:25333127

A new evaluation of the uncertainty associated with CDIAC estimates of fossil fuel carbon dioxide emission

Directory of Open Access Journals (Sweden)

Robert J. Andres

2014-07-01

Full Text Available Three uncertainty assessments associated with the global total of carbon dioxide emitted from fossil fuel use and cement production are presented. Each assessment has its own strengths and weaknesses and none give a full uncertainty assessment of the emission estimates. This approach grew out of the lack of independent measurements at the spatial and temporal scales of interest. Issues of dependent and independent data are considered as well as the temporal and spatial relationships of the data. The result is a multifaceted examination of the uncertainty associated with fossil fuel carbon dioxide emission estimates. The three assessments collectively give a range that spans from 1.0 to 13% (2 σ. Greatly simplifying the assessments give a global fossil fuel carbon dioxide uncertainty value of 8.4% (2 σ. In the largest context presented, the determination of fossil fuel emission uncertainty is important for a better understanding of the global carbon cycle and its implications for the physical, economic and political world.

Uncertainty estimation and risk prediction in air quality

International Nuclear Information System (INIS)

Garaud, Damien

2011-01-01

This work is about uncertainty estimation and risk prediction in air quality. Firstly, we build a multi-model ensemble of air quality simulations which can take into account all uncertainty sources related to air quality modeling. Ensembles of photochemical simulations at continental and regional scales are automatically generated. Then, these ensemble are calibrated with a combinatorial optimization method. It selects a sub-ensemble which is representative of uncertainty or shows good resolution and reliability for probabilistic forecasting. This work shows that it is possible to estimate and forecast uncertainty fields related to ozone and nitrogen dioxide concentrations or to improve the reliability of threshold exceedance predictions. The approach is compared with Monte Carlo simulations, calibrated or not. The Monte Carlo approach appears to be less representative of the uncertainties than the multi-model approach. Finally, we quantify the observational error, the representativeness error and the modeling errors. The work is applied to the impact of thermal power plants, in order to quantify the uncertainty on the impact estimates. (author) [fr

Estimation of the uncertainties considered in NPP PSA level 2

International Nuclear Information System (INIS)

Kalchev, B.; Hristova, R.

2005-01-01

The main approaches of the uncertainties analysis are presented. The sources of uncertainties which should be considered in PSA level 2 for WWER reactor such as: uncertainties propagated from level 1 PSA; uncertainties in input parameters; uncertainties related to the modelling of physical phenomena during the accident progression and uncertainties related to the estimation of source terms are defined. The methods for estimation of the uncertainties are also discussed in this paper

Estimation of the uncertainty in wind power forecasting

International Nuclear Information System (INIS)

Pinson, P.

2006-03-01

WIND POWER experiences a tremendous development of its installed capacities in Europe. Though, the intermittence of wind generation causes difficulties in the management of power systems. Also, in the context of the deregulation of electricity markets, wind energy is penalized by its intermittent nature. It is recognized today that the forecasting of wind power for horizons up to 2/3-day ahead eases the integration of wind generation. Wind power forecasts are traditionally provided in the form of point predictions, which correspond to the most-likely power production for a given horizon. That sole information is not sufficient for developing optimal management or trading strategies. Therefore, we investigate on possible ways for estimating the uncertainty of wind power forecasts. The characteristics of the prediction uncertainty are described by a thorough study of the performance of some of the state-of-the-art approaches, and by underlining the influence of some variables e.g. level of predicted power on distributions of prediction errors. Then, a generic method for the estimation of prediction intervals is introduced. This statistical method is non-parametric and utilizes fuzzy logic concepts for integrating expertise on the prediction uncertainty characteristics. By estimating several prediction intervals at once, one obtains predictive distributions of wind power output. The proposed method is evaluated in terms of its reliability, sharpness and resolution. In parallel, we explore the potential use of ensemble predictions for skill forecasting. Wind power ensemble forecasts are obtained either by converting meteorological ensembles (from ECMWF and NCEP) to power or by applying a poor man's temporal approach. A proposal for the definition of prediction risk indices is given, reflecting the disagreement between ensemble members over a set of successive look-ahead times. Such prediction risk indices may comprise a more comprehensive signal on the expected level

REDD+ emissions estimation and reporting: dealing with uncertainty

International Nuclear Information System (INIS)

Pelletier, Johanne; Potvin, Catherine; Martin, Davy

2013-01-01

used to evaluate reference level and emission reductions would strengthen the credibility of the system by promoting accountability and transparency. To secure conservativeness and deal with uncertainty, we consider the need for further research using real data available to developing countries to test the applicability of conservative discounts including the trend uncertainty and other possible options that would allow real incentives and stimulate improvements over time. Finally, we argue that REDD+ result-based actions assessed on the basis of a dashboard of performance indicators, not only in ‘tonnes CO 2 equ. per year’ might provide a more holistic approach, at least until better accuracy and certainty of forest carbon stocks emission and removal estimates to support a REDD+ policy can be reached. (letter)

REDD+ emissions estimation and reporting: dealing with uncertainty

Science.gov (United States)

Pelletier, Johanne; Martin, Davy; Potvin, Catherine

2013-09-01

used to evaluate reference level and emission reductions would strengthen the credibility of the system by promoting accountability and transparency. To secure conservativeness and deal with uncertainty, we consider the need for further research using real data available to developing countries to test the applicability of conservative discounts including the trend uncertainty and other possible options that would allow real incentives and stimulate improvements over time. Finally, we argue that REDD+ result-based actions assessed on the basis of a dashboard of performance indicators, not only in ‘tonnes CO2 equ. per year’ might provide a more holistic approach, at least until better accuracy and certainty of forest carbon stocks emission and removal estimates to support a REDD+ policy can be reached.

Uncertainty in Population Estimates for Endangered Animals and Improving the Recovery Process

Directory of Open Access Journals (Sweden)

Janet L. Rachlow

2013-08-01

Full Text Available United States recovery plans contain biological information for a species listed under the Endangered Species Act and specify recovery criteria to provide basis for species recovery. The objective of our study was to evaluate whether recovery plans provide uncertainty (e.g., variance with estimates of population size. We reviewed all finalized recovery plans for listed terrestrial vertebrate species to record the following data: (1 if a current population size was given, (2 if a measure of uncertainty or variance was associated with current estimates of population size and (3 if population size was stipulated for recovery. We found that 59% of completed recovery plans specified a current population size, 14.5% specified a variance for the current population size estimate and 43% specified population size as a recovery criterion. More recent recovery plans reported more estimates of current population size, uncertainty and population size as a recovery criterion. Also, bird and mammal recovery plans reported more estimates of population size and uncertainty compared to reptiles and amphibians. We suggest the use of calculating minimum detectable differences to improve confidence when delisting endangered animals and we identified incentives for individuals to get involved in recovery planning to improve access to quantitative data.

Uncertainty relations for approximation and estimation

Energy Technology Data Exchange (ETDEWEB)

Lee, Jaeha, E-mail: jlee@post.kek.jp [Department of Physics, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033 (Japan); Tsutsui, Izumi, E-mail: izumi.tsutsui@kek.jp [Department of Physics, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033 (Japan); Theory Center, Institute of Particle and Nuclear Studies, High Energy Accelerator Research Organization (KEK), 1-1 Oho, Tsukuba, Ibaraki 305-0801 (Japan)

2016-05-27

We present a versatile inequality of uncertainty relations which are useful when one approximates an observable and/or estimates a physical parameter based on the measurement of another observable. It is shown that the optimal choice for proxy functions used for the approximation is given by Aharonov's weak value, which also determines the classical Fisher information in parameter estimation, turning our inequality into the genuine Cramér–Rao inequality. Since the standard form of the uncertainty relation arises as a special case of our inequality, and since the parameter estimation is available as well, our inequality can treat both the position–momentum and the time–energy relations in one framework albeit handled differently. - Highlights: • Several inequalities interpreted as uncertainty relations for approximation/estimation are derived from a single ‘versatile inequality’. • The ‘versatile inequality’ sets a limit on the approximation of an observable and/or the estimation of a parameter by another observable. • The ‘versatile inequality’ turns into an elaboration of the Robertson–Kennard (Schrödinger) inequality and the Cramér–Rao inequality. • Both the position–momentum and the time–energy relation are treated in one framework. • In every case, Aharonov's weak value arises as a key geometrical ingredient, deciding the optimal choice for the proxy functions.

Uncertainty relations for approximation and estimation

International Nuclear Information System (INIS)

Lee, Jaeha; Tsutsui, Izumi

2016-01-01

We present a versatile inequality of uncertainty relations which are useful when one approximates an observable and/or estimates a physical parameter based on the measurement of another observable. It is shown that the optimal choice for proxy functions used for the approximation is given by Aharonov's weak value, which also determines the classical Fisher information in parameter estimation, turning our inequality into the genuine Cramér–Rao inequality. Since the standard form of the uncertainty relation arises as a special case of our inequality, and since the parameter estimation is available as well, our inequality can treat both the position–momentum and the time–energy relations in one framework albeit handled differently. - Highlights: • Several inequalities interpreted as uncertainty relations for approximation/estimation are derived from a single ‘versatile inequality’. • The ‘versatile inequality’ sets a limit on the approximation of an observable and/or the estimation of a parameter by another observable. • The ‘versatile inequality’ turns into an elaboration of the Robertson–Kennard (Schrödinger) inequality and the Cramér–Rao inequality. • Both the position–momentum and the time–energy relation are treated in one framework. • In every case, Aharonov's weak value arises as a key geometrical ingredient, deciding the optimal choice for the proxy functions.

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

Uncertainties in estimating heart doses from 2D-tangential breast cancer radiotherapy

DEFF Research Database (Denmark)

Laugaard Lorenzen, Ebbe; Brink, Carsten; Taylor, Carolyn W.

2016-01-01

BACKGROUND AND PURPOSE: We evaluated the accuracy of three methods of estimating radiation dose to the heart from two-dimensional tangential radiotherapy for breast cancer, as used in Denmark during 1982-2002. MATERIAL AND METHODS: Three tangential radiotherapy regimens were reconstructed using CT......-based planning scans for 40 patients with left-sided and 10 with right-sided breast cancer. Setup errors and organ motion were simulated using estimated uncertainties. For left-sided patients, mean heart dose was related to maximum heart distance in the medial field. RESULTS: For left-sided breast cancer, mean...... to the uncertainty of estimates based on individual CT-scans. For right-sided breast cancer patients, mean heart dose based on individual CT-scans was always

Examples of measurement uncertainty evaluations in accordance with the revised GUM

Science.gov (United States)

Runje, B.; Horvatic, A.; Alar, V.; Medic, S.; Bosnjakovic, A.

2016-11-01

The paper presents examples of the evaluation of uncertainty components in accordance with the current and revised Guide to the expression of uncertainty in measurement (GUM). In accordance with the proposed revision of the GUM a Bayesian approach was conducted for both type A and type B evaluations.The law of propagation of uncertainty (LPU) and the law of propagation of distribution applied through the Monte Carlo method, (MCM) were used to evaluate associated standard uncertainties, expanded uncertainties and coverage intervals. Furthermore, the influence of the non-Gaussian dominant input quantity and asymmetric distribution of the output quantity y on the evaluation of measurement uncertainty was analyzed. In the case when the probabilistically coverage interval is not symmetric, the coverage interval for the probability P is estimated from the experimental probability density function using the Monte Carlo method. Key highlights of the proposed revision of the GUM were analyzed through a set of examples.

On Evaluation of Recharge Model Uncertainty: a Priori and a Posteriori

International Nuclear Information System (INIS)

Ming Ye; Karl Pohlmann; Jenny Chapman; David Shafer

2006-01-01

Hydrologic environments are open and complex, rendering them prone to multiple interpretations and mathematical descriptions. Hydrologic analyses typically rely on a single conceptual-mathematical model, which ignores conceptual model uncertainty and may result in bias in predictions and under-estimation of predictive uncertainty. This study is to assess conceptual model uncertainty residing in five recharge models developed to date by different researchers based on different theories for Nevada and Death Valley area, CA. A recently developed statistical method, Maximum Likelihood Bayesian Model Averaging (MLBMA), is utilized for this analysis. In a Bayesian framework, the recharge model uncertainty is assessed, a priori, using expert judgments collected through an expert elicitation in the form of prior probabilities of the models. The uncertainty is then evaluated, a posteriori, by updating the prior probabilities to estimate posterior model probability. The updating is conducted through maximum likelihood inverse modeling by calibrating the Death Valley Regional Flow System (DVRFS) model corresponding to each recharge model against observations of head and flow. Calibration results of DVRFS for the five recharge models are used to estimate three information criteria (AIC, BIC, and KIC) used to rank and discriminate these models. Posterior probabilities of the five recharge models, evaluated using KIC, are used as weights to average head predictions, which gives posterior mean and variance. The posterior quantities incorporate both parametric and conceptual model uncertainties

Neglect Of Parameter Estimation Uncertainty Can Significantly Overestimate Structural Reliability

Directory of Open Access Journals (Sweden)

Rózsás Árpád

2015-12-01

Full Text Available Parameter estimation uncertainty is often neglected in reliability studies, i.e. point estimates of distribution parameters are used for representative fractiles, and in probabilistic models. A numerical example examines the effect of this uncertainty on structural reliability using Bayesian statistics. The study reveals that the neglect of parameter estimation uncertainty might lead to an order of magnitude underestimation of failure probability.

Uncertainty in urban flood damage assessment due to urban drainage modelling and depth-damage curve estimation.

Science.gov (United States)

Freni, G; La Loggia, G; Notaro, V

2010-01-01

Due to the increased occurrence of flooding events in urban areas, many procedures for flood damage quantification have been defined in recent decades. The lack of large databases in most cases is overcome by combining the output of urban drainage models and damage curves linking flooding to expected damage. The application of advanced hydraulic models as diagnostic, design and decision-making support tools has become a standard practice in hydraulic research and application. Flooding damage functions are usually evaluated by a priori estimation of potential damage (based on the value of exposed goods) or by interpolating real damage data (recorded during historical flooding events). Hydraulic models have undergone continuous advancements, pushed forward by increasing computer capacity. The details of the flooding propagation process on the surface and the details of the interconnections between underground and surface drainage systems have been studied extensively in recent years, resulting in progressively more reliable models. The same level of was advancement has not been reached with regard to damage curves, for which improvements are highly connected to data availability; this remains the main bottleneck in the expected flooding damage estimation. Such functions are usually affected by significant uncertainty intrinsically related to the collected data and to the simplified structure of the adopted functional relationships. The present paper aimed to evaluate this uncertainty by comparing the intrinsic uncertainty connected to the construction of the damage-depth function to the hydraulic model uncertainty. In this way, the paper sought to evaluate the role of hydraulic model detail level in the wider context of flood damage estimation. This paper demonstrated that the use of detailed hydraulic models might not be justified because of the higher computational cost and the significant uncertainty in damage estimation curves. This uncertainty occurs mainly

Large break LOCA uncertainty evaluation and comparison with conservative calculation

International Nuclear Information System (INIS)

Glaeser, H.G.

2004-01-01

The first formulation of the USA Code of Federal Regulations (CFR) 10CFR50 with applicable sections specific to NPP licensing requirements was released 1976. Over a decade later 10CFR 50.46 allowed the use of BE codes instead of conservative code models but uncertainties have to be identified and quantified. Guidelines were released that described interpretations developed over the intervening years that are applicable. Other countries established similar conservative procedures and acceptance criteria. Because conservative methods were used to calculate the peak values of key parameters, such as peak clad temperature (PCT), it was always acknowledged that a large margin, between the 'conservative' calculated value and the 'true' value, existed. Beside USA, regulation in other countries, like Germany, for example, allowed that the state of science and technology is applied in licensing. I.e. the increase of experimental evidence and progress in code development during time could be used. There was no requirement to apply a pure evaluation methodology with licensed assumptions and frozen codes. The thermal-hydraulic system codes became more and more best-estimate codes based on comprehensive validation. This development was and is possible because the rules and guidelines provide the necessary latitude to consider further development of safety technology. Best estimate codes are allowed to be used in licensing in combination with conservative initial and boundary conditions. However, uncertainty quantification is not required. Since some of the initial and boundary conditions are more conservative compared with those internationally used (e.g. 106% reactor power instead 102%, a single failure plus a non-availability due to preventive maintenance is assumed, etc.) it is claimed that the uncertainties of code models are covered. Since many utilities apply for power increase, calculation results come closer to some licensing criteria. The situation in German licensing

Impact of dose-distribution uncertainties on rectal ntcp modeling I: Uncertainty estimates

International Nuclear Information System (INIS)

Fenwick, John D.; Nahum, Alan E.

2001-01-01

A trial of nonescalated conformal versus conventional radiotherapy treatment of prostate cancer has been carried out at the Royal Marsden NHS Trust (RMH) and Institute of Cancer Research (ICR), demonstrating a significant reduction in the rate of rectal bleeding reported for patients treated using the conformal technique. The relationship between planned rectal dose-distributions and incidences of bleeding has been analyzed, showing that the rate of bleeding falls significantly as the extent of the rectal wall receiving a planned dose-level of more than 57 Gy is reduced. Dose-distributions delivered to the rectal wall over the course of radiotherapy treatment inevitably differ from planned distributions, due to sources of uncertainty such as patient setup error, rectal wall movement and variation in the absolute rectal wall surface area. In this paper estimates of the differences between planned and treated rectal dose-distribution parameters are obtained for the RMH/ICR nonescalated conformal technique, working from a distribution of setup errors observed during the RMH/ICR trial, movement data supplied by Lebesque and colleagues derived from repeat CT scans, and estimates of rectal circumference variations extracted from the literature. Setup errors and wall movement are found to cause only limited systematic differences between mean treated and planned rectal dose-distribution parameter values, but introduce considerable uncertainties into the treated values of some dose-distribution parameters: setup errors lead to 22% and 9% relative uncertainties in the highly dosed fraction of the rectal wall and the wall average dose, respectively, with wall movement leading to 21% and 9% relative uncertainties. Estimates obtained from the literature of the uncertainty in the absolute surface area of the distensible rectal wall are of the order of 13%-18%. In a subsequent paper the impact of these uncertainties on analyses of the relationship between incidences of bleeding

Estimating Coastal Digital Elevation Model (DEM) Uncertainty

Science.gov (United States)

Amante, C.; Mesick, S.

2017-12-01

Integrated bathymetric-topographic digital elevation models (DEMs) are representations of the Earth's solid surface and are fundamental to the modeling of coastal processes, including tsunami, storm surge, and sea-level rise inundation. Deviations in elevation values from the actual seabed or land surface constitute errors in DEMs, which originate from numerous sources, including: (i) the source elevation measurements (e.g., multibeam sonar, lidar), (ii) the interpolative gridding technique (e.g., spline, kriging) used to estimate elevations in areas unconstrained by source measurements, and (iii) the datum transformation used to convert bathymetric and topographic data to common vertical reference systems. The magnitude and spatial distribution of the errors from these sources are typically unknown, and the lack of knowledge regarding these errors represents the vertical uncertainty in the DEM. The National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Information (NCEI) has developed DEMs for more than 200 coastal communities. This study presents a methodology developed at NOAA NCEI to derive accompanying uncertainty surfaces that estimate DEM errors at the individual cell-level. The development of high-resolution (1/9th arc-second), integrated bathymetric-topographic DEMs along the southwest coast of Florida serves as the case study for deriving uncertainty surfaces. The estimated uncertainty can then be propagated into the modeling of coastal processes that utilize DEMs. Incorporating the uncertainty produces more reliable modeling results, and in turn, better-informed coastal management decisions.

Value assignment and uncertainty evaluation for single-element reference solutions

Science.gov (United States)

Possolo, Antonio; Bodnar, Olha; Butler, Therese A.; Molloy, John L.; Winchester, Michael R.

2018-06-01

A Bayesian statistical procedure is proposed for value assignment and uncertainty evaluation for the mass fraction of the elemental analytes in single-element solutions distributed as NIST standard reference materials. The principal novelty that we describe is the use of information about relative differences observed historically between the measured values obtained via gravimetry and via high-performance inductively coupled plasma optical emission spectrometry, to quantify the uncertainty component attributable to between-method differences. This information is encapsulated in a prior probability distribution for the between-method uncertainty component, and it is then used, together with the information provided by current measurement data, to produce a probability distribution for the value of the measurand from which an estimate and evaluation of uncertainty are extracted using established statistical procedures.

Uncertainty Evaluation with Multi-Dimensional Model of LBLOCA in OPR1000 Plant

Energy Technology Data Exchange (ETDEWEB)

Kim, Jieun; Oh, Deog Yeon; Seul, Kwang-Won; Lee, Jin Ho [Korea Institute of Nuclear Safety, Daejeon (Korea, Republic of)

2016-10-15

KINS has used KINS-REM (KINS-Realistic Evaluation Methodology) which developed for Best- Estimate (BE) calculation and uncertainty quantification for regulatory audit. This methodology has been improved continuously by numerous studies, such as uncertainty parameters and uncertainty ranges. In this study, to evaluate the applicability of improved KINS-REM for OPR1000 plant, uncertainty evaluation with multi-dimensional model for confirming multi-dimensional phenomena was conducted with MARS-KS code. In this study, the uncertainty evaluation with multi- dimensional model of OPR1000 plant was conducted for confirming the applicability of improved KINS- REM The reactor vessel modeled using MULTID component of MARS-KS code, and total 29 uncertainty parameters were considered by 124 sampled calculations. Through 124 calculations using Mosaique program with MARS-KS code, peak cladding temperature was calculated and final PCT was determined by the 3rd order Wilks' formula. The uncertainty parameters which has strong influence were investigated by Pearson coefficient analysis. They were mostly related with plant operation and fuel material properties. Evaluation results through the 124 calculations and sensitivity analysis show that improved KINS-REM could be reasonably applicable for uncertainty evaluation with multi-dimensional model calculations of OPR1000 plants.

GRS Method for Uncertainty and Sensitivity Evaluation of Code Results and Applications

International Nuclear Information System (INIS)

Glaeser, H.

2008-01-01

During the recent years, an increasing interest in computational reactor safety analysis is to replace the conservative evaluation model calculations by best estimate calculations supplemented by uncertainty analysis of the code results. The evaluation of the margin to acceptance criteria, for example, the maximum fuel rod clad temperature, should be based on the upper limit of the calculated uncertainty range. Uncertainty analysis is needed if useful conclusions are to be obtained from best estimate thermal-hydraulic code calculations, otherwise single values of unknown accuracy would be presented for comparison with regulatory acceptance limits. Methods have been developed and presented to quantify the uncertainty of computer code results. The basic techniques proposed by GRS are presented together with applications to a large break loss of coolant accident on a reference reactor as well as on an experiment simulating containment behaviour

Evaluation and uncertainty estimates of Charpy-impact data

International Nuclear Information System (INIS)

Stallman, F.W.

1982-01-01

Shifts in transition temperature and upper-shelf energy from Charpy tests are used to determine the extent of radiation embrittlement in steels. In order to determine these parameters reliably and to obtain uncertainty estimates, curve fitting procedures need to be used. The hyperbolic tangent or similar models have been proposed to fit the temperature-impact-energy curve. These models are not based on the actual fracture mechanics and are indeed poorly suited in many applications. The results may be falsified by forcing an inflexible curve through too many data points. The nonlinearity of the fit poses additional problems. In this paper, a simple linear fit is proposed. By eliminating data which are irrelevant for the determination of a given parameter, better reliability and accuracy can be achieved. Additional input parameters like fluence and irradiation temperature can be included. This is important if there is a large variation of fluence and temperature in different test specimens. The method has been tested with Charpy specimens from the NRC-HSST experiments

Uncertainty quantification metrics for whole product life cycle cost estimates in aerospace innovation

Science.gov (United States)

Schwabe, O.; Shehab, E.; Erkoyuncu, J.

2015-08-01

The lack of defensible methods for quantifying cost estimate uncertainty over the whole product life cycle of aerospace innovations such as propulsion systems or airframes poses a significant challenge to the creation of accurate and defensible cost estimates. Based on the axiomatic definition of uncertainty as the actual prediction error of the cost estimate, this paper provides a comprehensive overview of metrics used for the uncertainty quantification of cost estimates based on a literature review, an evaluation of publicly funded projects such as part of the CORDIS or Horizon 2020 programs, and an analysis of established approaches used by organizations such NASA, the U.S. Department of Defence, the ESA, and various commercial companies. The metrics are categorized based on their foundational character (foundations), their use in practice (state-of-practice), their availability for practice (state-of-art) and those suggested for future exploration (state-of-future). Insights gained were that a variety of uncertainty quantification metrics exist whose suitability depends on the volatility of available relevant information, as defined by technical and cost readiness level, and the number of whole product life cycle phases the estimate is intended to be valid for. Information volatility and number of whole product life cycle phases can hereby be considered as defining multi-dimensional probability fields admitting various uncertainty quantification metric families with identifiable thresholds for transitioning between them. The key research gaps identified were the lacking guidance grounded in theory for the selection of uncertainty quantification metrics and lacking practical alternatives to metrics based on the Central Limit Theorem. An innovative uncertainty quantification framework consisting of; a set-theory based typology, a data library, a classification system, and a corresponding input-output model are put forward to address this research gap as the basis

Estimating uncertainty of data limited stock assessments

DEFF Research Database (Denmark)

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

2017-01-01

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

Sediment Curve Uncertainty Estimation Using GLUE and Bootstrap Methods

Directory of Open Access Journals (Sweden)

aboalhasan fathabadi

2017-02-01

Full Text Available Introduction: In order to implement watershed practices to decrease soil erosion effects it needs to estimate output sediment of watershed. Sediment rating curve is used as the most conventional tool to estimate sediment. Regarding to sampling errors and short data, there are some uncertainties in estimating sediment using sediment curve. In this research, bootstrap and the Generalized Likelihood Uncertainty Estimation (GLUE resampling techniques were used to calculate suspended sediment loads by using sediment rating curves. Materials and Methods: The total drainage area of the Sefidrood watershed is about 560000 km2. In this study uncertainty in suspended sediment rating curves was estimated in four stations including Motorkhane, Miyane Tonel Shomare 7, Stor and Glinak constructed on Ayghdamosh, Ghrangho, GHezelOzan and Shahrod rivers, respectively. Data were randomly divided into a training data set (80 percent and a test set (20 percent by Latin hypercube random sampling.Different suspended sediment rating curves equations were fitted to log-transformed values of sediment concentration and discharge and the best fit models were selected based on the lowest root mean square error (RMSE and the highest correlation of coefficient (R2. In the GLUE methodology, different parameter sets were sampled randomly from priori probability distribution. For each station using sampled parameter sets and selected suspended sediment rating curves equation suspended sediment concentration values were estimated several times (100000 to 400000 times. With respect to likelihood function and certain subjective threshold, parameter sets were divided into behavioral and non-behavioral parameter sets. Finally using behavioral parameter sets the 95% confidence intervals for suspended sediment concentration due to parameter uncertainty were estimated. In bootstrap methodology observed suspended sediment and discharge vectors were resampled with replacement B (set to

Uncertainty Estimation using Bootstrapped Kriging Predictions for Precipitation Isoscapes

Science.gov (United States)

Ma, C.; Bowen, G. J.; Vander Zanden, H.; Wunder, M.

2017-12-01

Isoscapes are spatial models representing the distribution of stable isotope values across landscapes. Isoscapes of hydrogen and oxygen in precipitation are now widely used in a diversity of fields, including geology, biology, hydrology, and atmospheric science. To generate isoscapes, geostatistical methods are typically applied to extend predictions from limited data measurements. Kriging is a popular method in isoscape modeling, but quantifying the uncertainty associated with the resulting isoscapes is challenging. Applications that use precipitation isoscapes to determine sample origin require estimation of uncertainty. Here we present a simple bootstrap method (SBM) to estimate the mean and uncertainty of the krigged isoscape and compare these results with a generalized bootstrap method (GBM) applied in previous studies. We used hydrogen isotopic data from IsoMAP to explore these two approaches for estimating uncertainty. We conducted 10 simulations for each bootstrap method and found that SBM results in more kriging predictions (9/10) compared to GBM (4/10). Prediction from SBM was closer to the original prediction generated without bootstrapping and had less variance than GBM. SBM was tested on different datasets from IsoMAP with different numbers of observation sites. We determined that predictions from the datasets with fewer than 40 observation sites using SBM were more variable than the original prediction. The approaches we used for estimating uncertainty will be compiled in an R package that is under development. We expect that these robust estimates of precipitation isoscape uncertainty can be applied in diagnosing the origin of samples ranging from various type of waters to migratory animals, food products, and humans.

Uncertainty Measures of Regional Flood Frequency Estimators

DEFF Research Database (Denmark)

Rosbjerg, Dan; Madsen, Henrik

1995-01-01

Regional flood frequency models have different assumptions regarding homogeneity and inter-site independence. Thus, uncertainty measures of T-year event estimators are not directly comparable. However, having chosen a particular method, the reliability of the estimate should always be stated, e...

Mass discharge estimation from contaminated sites: Multi-model solutions for assessment of conceptual uncertainty

Science.gov (United States)

Thomsen, N. I.; Troldborg, M.; McKnight, U. S.; Binning, P. J.; Bjerg, P. L.

2012-04-01

Mass discharge estimates are increasingly being used in the management of contaminated sites. Such estimates have proven useful for supporting decisions related to the prioritization of contaminated sites in a groundwater catchment. Potential management options can be categorised as follows: (1) leave as is, (2) clean up, or (3) further investigation needed. However, mass discharge estimates are often very uncertain, which may hamper the management decisions. If option 1 is incorrectly chosen soil and water quality will decrease, threatening or destroying drinking water resources. The risk of choosing option 2 is to spend money on remediating a site that does not pose a problem. Choosing option 3 will often be safest, but may not be the optimal economic solution. Quantification of the uncertainty in mass discharge estimates can therefore greatly improve the foundation for selecting the appropriate management option. The uncertainty of mass discharge estimates depends greatly on the extent of the site characterization. A good approach for uncertainty estimation will be flexible with respect to the investigation level, and account for both parameter and conceptual model uncertainty. We propose a method for quantifying the uncertainty of dynamic mass discharge estimates from contaminant point sources on the local scale. The method considers both parameter and conceptual uncertainty through a multi-model approach. The multi-model approach evaluates multiple conceptual models for the same site. The different conceptual models consider different source characterizations and hydrogeological descriptions. The idea is to include a set of essentially different conceptual models where each model is believed to be realistic representation of the given site, based on the current level of information. Parameter uncertainty is quantified using Monte Carlo simulations. For each conceptual model we calculate a transient mass discharge estimate with uncertainty bounds resulting from

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

International Nuclear Information System (INIS)

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

1994-01-01

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

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)

Evaluation of uncertainty sources and propagation from irradiance sensors to PV yield

OpenAIRE

Mariottini, Francesco; Gottschalg, Ralph; Betts, Tom; Zhu, Jiang

2018-01-01

This work quantifies the uncertainties of a pyranometer. Sensitivity to errors is analysed regarding the effects generated by adopting different time resolutions. Estimation of irradiance measurand and error is extended throughout an annual data set. This study represents an attempt to provide a more exhaustive overview of both systematic (i.e. physical) and random uncertainties in the evaluation of pyranometer measurements. Starting from expanded uncertainty in a monitored ...

Supporting Qualified Database for Uncertainty Evaluation

International Nuclear Information System (INIS)

Petruzzi, A.; Fiori, F.; Kovtonyuk, A.; Lisovyy, O.; D'Auria, F.

2013-01-01

Uncertainty evaluation constitutes a key feature of BEPU (Best Estimate Plus Uncertainty) process. The uncertainty can be the result of a Monte Carlo type analysis involving input uncertainty parameters or the outcome of a process involving the use of experimental data and connected code calculations. Those uncertainty methods are discussed in several papers and guidelines (IAEA-SRS-52, OECD/NEA BEMUSE reports). The present paper aims at discussing the role and the depth of the analysis required for merging from one side suitable experimental data and on the other side qualified code calculation results. This aspect is mostly connected with the second approach for uncertainty mentioned above, but it can be used also in the framework of the first approach. Namely, the paper discusses the features and structure of the database that includes the following kinds of documents: 1. The 'RDS-facility' (Reference Data Set for the selected facility): this includes the description of the facility, the geometrical characterization of any component of the facility, the instrumentations, the data acquisition system, the evaluation of pressure losses, the physical properties of the material and the characterization of pumps, valves and heat losses; 2. The 'RDS-test' (Reference Data Set for the selected test of the facility): this includes the description of the main phenomena investigated during the test, the configuration of the facility for the selected test (possible new evaluation of pressure and heat losses if needed) and the specific boundary and initial conditions; 3. The 'QP' (Qualification Report) of the code calculation results: this includes the description of the nodalization developed following a set of homogeneous techniques, the achievement of the steady state conditions and the qualitative and quantitative analysis of the transient with the characterization of the Relevant Thermal-Hydraulics Aspects (RTA); 4. The EH (Engineering Handbook) of the input nodalization

Supporting qualified database for uncertainty evaluation

Energy Technology Data Exchange (ETDEWEB)

Petruzzi, A.; Fiori, F.; Kovtonyuk, A.; D' Auria, F. [Nuclear Research Group of San Piero A Grado, Univ. of Pisa, Via Livornese 1291, 56122 Pisa (Italy)

2012-07-01

Uncertainty evaluation constitutes a key feature of BEPU (Best Estimate Plus Uncertainty) process. The uncertainty can be the result of a Monte Carlo type analysis involving input uncertainty parameters or the outcome of a process involving the use of experimental data and connected code calculations. Those uncertainty methods are discussed in several papers and guidelines (IAEA-SRS-52, OECD/NEA BEMUSE reports). The present paper aims at discussing the role and the depth of the analysis required for merging from one side suitable experimental data and on the other side qualified code calculation results. This aspect is mostly connected with the second approach for uncertainty mentioned above, but it can be used also in the framework of the first approach. Namely, the paper discusses the features and structure of the database that includes the following kinds of documents: 1. The' RDS-facility' (Reference Data Set for the selected facility): this includes the description of the facility, the geometrical characterization of any component of the facility, the instrumentations, the data acquisition system, the evaluation of pressure losses, the physical properties of the material and the characterization of pumps, valves and heat losses; 2. The 'RDS-test' (Reference Data Set for the selected test of the facility): this includes the description of the main phenomena investigated during the test, the configuration of the facility for the selected test (possible new evaluation of pressure and heat losses if needed) and the specific boundary and initial conditions; 3. The 'QR' (Qualification Report) of the code calculation results: this includes the description of the nodalization developed following a set of homogeneous techniques, the achievement of the steady state conditions and the qualitative and quantitative analysis of the transient with the characterization of the Relevant Thermal-Hydraulics Aspects (RTA); 4. The EH (Engineering

Expanded uncertainty estimation methodology in determining the sandy soils filtration coefficient

Science.gov (United States)

Rusanova, A. D.; Malaja, L. D.; Ivanov, R. N.; Gruzin, A. V.; Shalaj, V. V.

2018-04-01

The combined standard uncertainty estimation methodology in determining the sandy soils filtration coefficient has been developed. The laboratory researches were carried out which resulted in filtration coefficient determination and combined uncertainty estimation obtaining.

Uncertainty estimation in nuclear power plant probabilistic safety assessment

International Nuclear Information System (INIS)

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

1989-01-01

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

Uncertainty Evaluation of a Postulated LBLOCA for APR+ using KINS Realistic Evaluation Methodology and MARS-KS

Energy Technology Data Exchange (ETDEWEB)

Hwang, Min Jeong; Marigomena, Ralph; Yoo, Tae Ho; Kim, Y. S.; Sim, S. K. [Environment and Energy Technology, Inc., Daejeon (Korea, Republic of); Bang, Young Seok [KINS, Daejeon (Korea, Republic of)

2014-05-15

As a part of the regulatory safety research, Korea Institute of Nuclear Safety(KINS) also developed a best estimate safety analysis regulatory audit code, MARS-KS, to realistically predict and better understand the physical phenomena of the design basis accidents. KINS improved uncertainty propagation methodology using MARS-KS and applied the improved uncertainty evaluation method for the Shinkori Units 3 and 4 LBLOC. This study is to evaluate the uncertainty propagation of a postulated LBLOCA and quantify the safety margin using KINS-REM and MARS-KS code for the APR+ (Advanced Pressurizer Reactor Plus) Standard Safety Analysis Report(SSAR) which is under regulatory review by the KINS for its design approval. KINS-REM LBLOCA realistic evaluation methodology was used for the regulatory assessment of the APR+ LBLOCA using MARS-KS to evaluate the uncertainty propagation of the uncertainty variables as well as to assess the safety margin during the limiting case of the APR+ double ended guillotine cold leg LBLOCA. Uncertainty evaluation for the APR+ LBLOCA shows that the reflood PCT with upper limit of 95% probability at 95% confidence level is 1363.2 K and is higher than the blowdown PCT95/95 of 1275.3 K. The result shows that the current evaluation of APR+ LBLOCA PCT is within the acceptance criteria of 1477 K ECCS.

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)

Evaluation of uncertainties in the calibration of radiation survey meter

International Nuclear Information System (INIS)

Potiens, M.P.A.; Santos, G.P.

2006-01-01

In order to meet the requirements of ISO 17025, the quantification of the expanded uncertainties of experimental data in the calibration of survey meters must be carried out using well defined concepts, like those expressed in the 'ISO-Guide to the Expression of Uncertainty in Measurement'. The calibration procedure of gamma ray survey meters involves two values that have to get their uncertainties clearly known: measurements of the instrument under calibration and the conventional true values of a quantity. Considering the continuous improvement of the calibration methods and set-ups, it is necessary to evaluate periodically the involved uncertainties in the procedures. In this work it is shown how the measurement uncertainties of an individual calibration can be estimated and how it can be generalized to be valid for others radiation survey meters. (authors)

Estimating uncertainty in multivariate responses to selection.

Science.gov (United States)

Stinchcombe, John R; Simonsen, Anna K; Blows, Mark W

2014-04-01

Predicting the responses to natural selection is one of the key goals of evolutionary biology. Two of the challenges in fulfilling this goal have been the realization that many estimates of natural selection might be highly biased by environmentally induced covariances between traits and fitness, and that many estimated responses to selection do not incorporate or report uncertainty in the estimates. Here we describe the application of a framework that blends the merits of the Robertson-Price Identity approach and the multivariate breeder's equation to address these challenges. The approach allows genetic covariance matrices, selection differentials, selection gradients, and responses to selection to be estimated without environmentally induced bias, direct and indirect selection and responses to selection to be distinguished, and if implemented in a Bayesian-MCMC framework, statistically robust estimates of uncertainty on all of these parameters to be made. We illustrate our approach with a worked example of previously published data. More generally, we suggest that applying both the Robertson-Price Identity and the multivariate breeder's equation will facilitate hypothesis testing about natural selection, genetic constraints, and evolutionary responses. © 2013 The Author(s). Evolution © 2013 The Society for the Study of Evolution.

Aboveground Forest Biomass Estimation with Landsat and LiDAR Data and Uncertainty Analysis of the Estimates

Directory of Open Access Journals (Sweden)

Dengsheng Lu

2012-01-01

Full Text Available Landsat Thematic mapper (TM image has long been the dominate data source, and recently LiDAR has offered an important new structural data stream for forest biomass estimations. On the other hand, forest biomass uncertainty analysis research has only recently obtained sufficient attention due to the difficulty in collecting reference data. This paper provides a brief overview of current forest biomass estimation methods using both TM and LiDAR data. A case study is then presented that demonstrates the forest biomass estimation methods and uncertainty analysis. Results indicate that Landsat TM data can provide adequate biomass estimates for secondary succession but are not suitable for mature forest biomass estimates due to data saturation problems. LiDAR can overcome TM’s shortcoming providing better biomass estimation performance but has not been extensively applied in practice due to data availability constraints. The uncertainty analysis indicates that various sources affect the performance of forest biomass/carbon estimation. With that said, the clear dominate sources of uncertainty are the variation of input sample plot data and data saturation problem related to optical sensors. A possible solution to increasing the confidence in forest biomass estimates is to integrate the strengths of multisensor data.

Estimate of the uncertainty in measurement for the determination of mercury in seafood by TDA AAS.

Science.gov (United States)

Torres, Daiane Placido; Olivares, Igor R B; Queiroz, Helena Müller

2015-01-01

An approach for the estimate of the uncertainty in measurement considering the individual sources related to the different steps of the method under evaluation as well as the uncertainties estimated from the validation data for the determination of mercury in seafood by using thermal decomposition/amalgamation atomic absorption spectrometry (TDA AAS) is proposed. The considered method has been fully optimized and validated in an official laboratory of the Ministry of Agriculture, Livestock and Food Supply of Brazil, in order to comply with national and international food regulations and quality assurance. The referred method has been accredited under the ISO/IEC 17025 norm since 2010. The approach of the present work in order to reach the aim of estimating of the uncertainty in measurement was based on six sources of uncertainty for mercury determination in seafood by TDA AAS, following the validation process, which were: Linear least square regression, Repeatability, Intermediate precision, Correction factor of the analytical curve, Sample mass, and Standard reference solution. Those that most influenced the uncertainty in measurement were sample weight, repeatability, intermediate precision and calibration curve. The obtained result for the estimate of uncertainty in measurement in the present work reached a value of 13.39%, which complies with the European Regulation EC 836/2011. This figure represents a very realistic estimate of the routine conditions, since it fairly encompasses the dispersion obtained from the value attributed to the sample and the value measured by the laboratory analysts. From this outcome, it is possible to infer that the validation data (based on calibration curve, recovery and precision), together with the variation on sample mass, can offer a proper estimate of uncertainty in measurement.

GUM approach to uncertainty estimations for online 220Rn concentration measurements using Lucas scintillation cell

International Nuclear Information System (INIS)

Sathyabama, N.

2014-01-01

It is now widely recognized that, when all of the known or suspected components of errors have been evaluated and corrected, there still remains an uncertainty, that is, a doubt about how well the result of the measurement represents the value of the quantity being measured. Evaluation of measurement data - Guide to the expression of Uncertainty in Measurement (GUM) is a guidance document, the purpose of which is to promote full information on how uncertainty statements are arrived at and to provide a basis for the international comparison of measurement results. In this paper, uncertainty estimations following GUM guidelines have been made for the measured values of online thoron concentrations using Lucas scintillation cell to prove that the correction for disequilibrium between 220 Rn and 216 Po is significant in online 220 Rn measurements

Uncertainty estimation of core safety parameters using cross-correlations of covariance matrix

International Nuclear Information System (INIS)

Yamamoto, A.; Yasue, Y.; Endo, T.; Kodama, Y.; Ohoka, Y.; Tatsumi, M.

2012-01-01

An uncertainty estimation method for core safety parameters, for which measurement values are not obtained, is proposed. We empirically recognize the correlations among the prediction errors among core safety parameters, e.g., a correlation between the control rod worth and assembly relative power of corresponding position. Correlations of uncertainties among core safety parameters are theoretically estimated using the covariance of cross sections and sensitivity coefficients for core parameters. The estimated correlations among core safety parameters are verified through the direct Monte-Carlo sampling method. Once the correlation of uncertainties among core safety parameters is known, we can estimate the uncertainty of a safety parameter for which measurement value is not obtained. Furthermore, the correlations can be also used for the reduction of uncertainties of core safety parameters. (authors)

On the uncertainties in effective dose estimates of adult CT head scans

International Nuclear Information System (INIS)

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

2008-01-01

Estimates of the effective dose to adult patients from computed tomography (CT) head scanning can be calculated using a number of different methods. These estimates can be used for a variety of purposes, such as improving scanning protocols, comparing different CT imaging centers, and weighing the benefits of the scan against the risk of radiation-induced cancer. The question arises: What is the uncertainty in these effective dose estimates? This study calculates the uncertainty of effective dose estimates produced by three computer programs (CT-EXPO, CTDosimetry, and ImpactDose) and one method that makes use of dose-length product (DLP) values. Uncertainties were calculated in accordance with an internationally recognized uncertainty analysis guide. For each of the four methods, the smallest and largest overall uncertainties (stated at the 95% confidence interval) were: 20%-31% (CT-EXPO), 15%-28% (CTDosimetry), 20%-36% (ImpactDose), and 22%-32% (DLP), respectively. The overall uncertainties for each method vary due to differences in the uncertainties of factors used in each method. The smallest uncertainties apply when the CT dose index for the scanner has been measured using a calibrated pencil ionization chamber

Uncertainty Estimates: A New Editorial Standard

International Nuclear Information System (INIS)

Drake, Gordon W.F.

2014-01-01

Full text: The objective of achieving higher standards for uncertainty estimates in the publication of theoretical data for atoms and molecules requires a concerted effort by both the authors of papers and the editors who send them out for peer review. In April, 2011, the editors of Physical Review A published an Editorial announcing a new standard that uncertainty estimates would be required whenever practicable, and in particular in the following circumstances: 1. If the authors claim high accuracy, or improvements on the accuracy of previous work. 2. If the primary motivation for the paper is to make comparisons with present or future high precision experimental measurements. 3. If the primary motivation is to provide interpolations or extrapolations of known experimental measurements. The new policy means that papers that do not meet these standards are not sent out for peer review until they have been suitably revised, and the authors are so notified immediately upon receipt. The policy has now been in effect for three years. (author

Approach to uncertainty evaluation for safety analysis

International Nuclear Information System (INIS)

Ogura, Katsunori

2005-01-01

Nuclear power plant safety used to be verified and confirmed through accident simulations using computer codes generally because it is very difficult to perform integrated experiments or tests for the verification and validation of the plant safety due to radioactive consequence, cost, and scaling to the actual plant. Traditionally the plant safety had been secured owing to the sufficient safety margin through the conservative assumptions and models to be applied to those simulations. Meanwhile the best-estimate analysis based on the realistic assumptions and models in support of the accumulated insights could be performed recently, inducing the reduction of safety margin in the analysis results and the increase of necessity to evaluate the reliability or uncertainty of the analysis results. This paper introduces an approach to evaluate the uncertainty of accident simulation and its results. (Note: This research had been done not in the Japan Nuclear Energy Safety Organization but in the Tokyo Institute of Technology.) (author)

Estimation of Uncertainty in Aerosol Concentration Measured by Aerosol Sampling System

Energy Technology Data Exchange (ETDEWEB)

Lee, Jong Chan; Song, Yong Jae; Jung, Woo Young; Lee, Hyun Chul; Kim, Gyu Tae; Lee, Doo Yong [FNC Technology Co., Yongin (Korea, Republic of)

2016-10-15

FNC Technology Co., Ltd has been developed test facilities for the aerosol generation, mixing, sampling and measurement under high pressure and high temperature conditions. The aerosol generation system is connected to the aerosol mixing system which injects SiO{sub 2}/ethanol mixture. In the sampling system, glass fiber membrane filter has been used to measure average mass concentration. Based on the experimental results using main carrier gas of steam and air mixture, the uncertainty estimation of the sampled aerosol concentration was performed by applying Gaussian error propagation law. FNC Technology Co., Ltd. has been developed the experimental facilities for the aerosol measurement under high pressure and high temperature. The purpose of the tests is to develop commercial test module for aerosol generation, mixing and sampling system applicable to environmental industry and safety related system in nuclear power plant. For the uncertainty calculation of aerosol concentration, the value of the sampled aerosol concentration is not measured directly, but must be calculated from other quantities. The uncertainty of the sampled aerosol concentration is a function of flow rates of air and steam, sampled mass, sampling time, condensed steam mass and its absolute errors. These variables propagate to the combination of variables in the function. Using operating parameters and its single errors from the aerosol test cases performed at FNC, the uncertainty of aerosol concentration evaluated by Gaussian error propagation law is less than 1%. The results of uncertainty estimation in the aerosol sampling system will be utilized for the system performance data.

Estimation of the measurement uncertainty in magnetic resonance velocimetry based on statistical models

Energy Technology Data Exchange (ETDEWEB)

Bruschewski, Martin; Schiffer, Heinz-Peter [Technische Universitaet Darmstadt, Institute of Gas Turbines and Aerospace Propulsion, Darmstadt (Germany); Freudenhammer, Daniel [Technische Universitaet Darmstadt, Institute of Fluid Mechanics and Aerodynamics, Center of Smart Interfaces, Darmstadt (Germany); Buchenberg, Waltraud B. [University Medical Center Freiburg, Medical Physics, Department of Radiology, Freiburg (Germany); Grundmann, Sven [University of Rostock, Institute of Fluid Mechanics, Rostock (Germany)

2016-05-15

Velocity measurements with magnetic resonance velocimetry offer outstanding possibilities for experimental fluid mechanics. The purpose of this study was to provide practical guidelines for the estimation of the measurement uncertainty in such experiments. Based on various test cases, it is shown that the uncertainty estimate can vary substantially depending on how the uncertainty is obtained. The conventional approach to estimate the uncertainty from the noise in the artifact-free background can lead to wrong results. A deviation of up to -75% is observed with the presented experiments. In addition, a similarly high deviation is demonstrated with the data from other studies. As a more accurate approach, the uncertainty is estimated directly from the image region with the flow sample. Two possible estimation methods are presented. (orig.)

Estimation of the measurement uncertainty in magnetic resonance velocimetry based on statistical models

Science.gov (United States)

Bruschewski, Martin; Freudenhammer, Daniel; Buchenberg, Waltraud B.; Schiffer, Heinz-Peter; Grundmann, Sven

2016-05-01

Velocity measurements with magnetic resonance velocimetry offer outstanding possibilities for experimental fluid mechanics. The purpose of this study was to provide practical guidelines for the estimation of the measurement uncertainty in such experiments. Based on various test cases, it is shown that the uncertainty estimate can vary substantially depending on how the uncertainty is obtained. The conventional approach to estimate the uncertainty from the noise in the artifact-free background can lead to wrong results. A deviation of up to -75 % is observed with the presented experiments. In addition, a similarly high deviation is demonstrated with the data from other studies. As a more accurate approach, the uncertainty is estimated directly from the image region with the flow sample. Two possible estimation methods are presented.

Evaluating Prognostics Performance for Algorithms Incorporating Uncertainty Estimates

Data.gov (United States)

National Aeronautics and Space Administration — Uncertainty Representation and Management (URM) are an integral part of the prognostic system development.1As capabilities of prediction algorithms evolve, research...

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

Routine internal- and external-quality control data in clinical laboratories for estimating measurement and diagnostic uncertainty using GUM principles.

Science.gov (United States)

Magnusson, Bertil; Ossowicki, Haakan; Rienitz, Olaf; Theodorsson, Elvar

2012-05-01

Healthcare laboratories are increasingly joining into larger laboratory organizations encompassing several physical laboratories. This caters for important new opportunities for re-defining the concept of a 'laboratory' to encompass all laboratories and measurement methods measuring the same measurand for a population of patients. In order to make measurement results, comparable bias should be minimized or eliminated and measurement uncertainty properly evaluated for all methods used for a particular patient population. The measurement as well as diagnostic uncertainty can be evaluated from internal and external quality control results using GUM principles. In this paper the uncertainty evaluations are described in detail using only two main components, within-laboratory reproducibility and uncertainty of the bias component according to a Nordtest guideline. The evaluation is exemplified for the determination of creatinine in serum for a conglomerate of laboratories both expressed in absolute units (μmol/L) and relative (%). An expanded measurement uncertainty of 12 μmol/L associated with concentrations of creatinine below 120 μmol/L and of 10% associated with concentrations above 120 μmol/L was estimated. The diagnostic uncertainty encompasses both measurement uncertainty and biological variation, and can be estimated for a single value and for a difference. This diagnostic uncertainty for the difference for two samples from the same patient was determined to be 14 μmol/L associated with concentrations of creatinine below 100 μmol/L and 14 % associated with concentrations above 100 μmol/L.

Incorporation of various uncertainties in dependent failure-probability estimation

International Nuclear Information System (INIS)

Samanta, P.K.; Mitra, S.P.

1982-01-01

This paper describes an approach that allows the incorporation of various types of uncertainties in the estimation of dependent failure (common mode failure) probability. The types of uncertainties considered are attributable to data, modeling and coupling. The method developed is applied to a class of dependent failures, i.e., multiple human failures during testing, maintenance and calibration. Estimation of these failures is critical as they have been shown to be significant contributors to core melt probability in pressurized water reactors

Evaluating the uncertainty of input quantities in measurement models

Science.gov (United States)

Possolo, Antonio; Elster, Clemens

2014-06-01

The Guide to the Expression of Uncertainty in Measurement (GUM) gives guidance about how values and uncertainties should be assigned to the input quantities that appear in measurement models. This contribution offers a concrete proposal for how that guidance may be updated in light of the advances in the evaluation and expression of measurement uncertainty that were made in the course of the twenty years that have elapsed since the publication of the GUM, and also considering situations that the GUM does not yet contemplate. Our motivation is the ongoing conversation about a new edition of the GUM. While generally we favour a Bayesian approach to uncertainty evaluation, we also recognize the value that other approaches may bring to the problems considered here, and focus on methods for uncertainty evaluation and propagation that are widely applicable, including to cases that the GUM has not yet addressed. In addition to Bayesian methods, we discuss maximum-likelihood estimation, robust statistical methods, and measurement models where values of nominal properties play the same role that input quantities play in traditional models. We illustrate these general-purpose techniques in concrete examples, employing data sets that are realistic but that also are of conveniently small sizes. The supplementary material available online lists the R computer code that we have used to produce these examples (stacks.iop.org/Met/51/3/339/mmedia). Although we strive to stay close to clause 4 of the GUM, which addresses the evaluation of uncertainty for input quantities, we depart from it as we review the classes of measurement models that we believe are generally useful in contemporary measurement science. We also considerably expand and update the treatment that the GUM gives to Type B evaluations of uncertainty: reviewing the state-of-the-art, disciplined approach to the elicitation of expert knowledge, and its encapsulation in probability distributions that are usable in

Triangular and Trapezoidal Fuzzy State Estimation with Uncertainty on Measurements

Directory of Open Access Journals (Sweden)

Mohammad Sadeghi Sarcheshmah

2012-01-01

Full Text Available In this paper, a new method for uncertainty analysis in fuzzy state estimation is proposed. The uncertainty is expressed in measurements. Uncertainties in measurements are modelled with different fuzzy membership functions (triangular and trapezoidal. To find the fuzzy distribution of any state variable, the problem is formulated as a constrained linear programming (LP optimization. The viability of the proposed method would be verified with the ones obtained from the weighted least squares (WLS and the fuzzy state estimation (FSE in the 6-bus system and in the IEEE-14 and 30 bus system.

Uncertainty quantification for radiation measurements: Bottom-up error variance estimation using calibration information

International Nuclear Information System (INIS)

Burr, T.; Croft, S.; Krieger, T.; Martin, K.; Norman, C.; Walsh, S.

2016-01-01

One example of top-down uncertainty quantification (UQ) involves comparing two or more measurements on each of multiple items. One example of bottom-up UQ expresses a measurement result as a function of one or more input variables that have associated errors, such as a measured count rate, which individually (or collectively) can be evaluated for impact on the uncertainty in the resulting measured value. In practice, it is often found that top-down UQ exhibits larger error variances than bottom-up UQ, because some error sources are present in the fielded assay methods used in top-down UQ that are not present (or not recognized) in the assay studies used in bottom-up UQ. One would like better consistency between the two approaches in order to claim understanding of the measurement process. The purpose of this paper is to refine bottom-up uncertainty estimation by using calibration information so that if there are no unknown error sources, the refined bottom-up uncertainty estimate will agree with the top-down uncertainty estimate to within a specified tolerance. Then, in practice, if the top-down uncertainty estimate is larger than the refined bottom-up uncertainty estimate by more than the specified tolerance, there must be omitted sources of error beyond those predicted from calibration uncertainty. The paper develops a refined bottom-up uncertainty approach for four cases of simple linear calibration: (1) inverse regression with negligible error in predictors, (2) inverse regression with non-negligible error in predictors, (3) classical regression followed by inversion with negligible error in predictors, and (4) classical regression followed by inversion with non-negligible errors in predictors. Our illustrations are of general interest, but are drawn from our experience with nuclear material assay by non-destructive assay. The main example we use is gamma spectroscopy that applies the enrichment meter principle. Previous papers that ignore error in predictors

GLUE Based Uncertainty Estimation of Urban Drainage Modeling Using Weather Radar Precipitation Estimates

DEFF Research Database (Denmark)

Nielsen, Jesper Ellerbæk; Thorndahl, Søren Liedtke; Rasmussen, Michael R.

2011-01-01

Distributed weather radar precipitation measurements are used as rainfall input for an urban drainage model, to simulate the runoff from a small catchment of Denmark. It is demonstrated how the Generalized Likelihood Uncertainty Estimation (GLUE) methodology can be implemented and used to estimate...

Estimation of spatial uncertainties of tomographic velocity models

Energy Technology Data Exchange (ETDEWEB)

Jordan, M.; Du, Z.; Querendez, E. [SINTEF Petroleum Research, Trondheim (Norway)

2012-12-15

This research project aims to evaluate the possibility of assessing the spatial uncertainties in tomographic velocity model building in a quantitative way. The project is intended to serve as a test of whether accurate and specific uncertainty estimates (e.g., in meters) can be obtained. The project is based on Monte Carlo-type perturbations of the velocity model as obtained from the tomographic inversion guided by diagonal and off-diagonal elements of the resolution and the covariance matrices. The implementation and testing of this method was based on the SINTEF in-house stereotomography code, using small synthetic 2D data sets. To test the method the calculation and output of the covariance and resolution matrices was implemented, and software to perform the error estimation was created. The work included the creation of 2D synthetic data sets, the implementation and testing of the software to conduct the tests (output of the covariance and resolution matrices which are not implicitly provided by stereotomography), application to synthetic data sets, analysis of the test results, and creating the final report. The results show that this method can be used to estimate the spatial errors in tomographic images quantitatively. The results agree with' the known errors for our synthetic models. However, the method can only be applied to structures in the model, where the change of seismic velocity is larger than the predicted error of the velocity parameter amplitudes. In addition, the analysis is dependent on the tomographic method, e.g., regularization and parameterization. The conducted tests were very successful and we believe that this method could be developed further to be applied to third party tomographic images.

Risk estimation and evaluation

Energy Technology Data Exchange (ETDEWEB)

Ferguson, R A.D.

1982-10-01

Risk assessment involves subjectivity, which makes objective decision making difficult in the nuclear power debate. The author reviews the process and uncertainties of estimating risks as well as the potential for misinterpretation and misuse. Risk data from a variety of aspects cannot be summed because the significance of different risks is not comparable. A method for including political, social, moral, psychological, and economic factors, environmental impacts, catastrophes, and benefits in the evaluation process could involve a broad base of lay and technical consultants, who would explain and argue their evaluation positions. 15 references. (DCK)

Estimation of CO2 emissions from China’s cement production: Methodologies and uncertainties

International Nuclear Information System (INIS)

Ke, Jing; McNeil, Michael; Price, Lynn; Khanna, Nina Zheng; Zhou, Nan

2013-01-01

In 2010, China’s cement output was 1.9 Gt, which accounted for 56% of world cement production. Total carbon dioxide (CO 2 ) emissions from Chinese cement production could therefore exceed 1.2 Gt. The magnitude of emissions from this single industrial sector in one country underscores the need to understand the uncertainty of current estimates of cement emissions in China. This paper compares several methodologies for calculating CO 2 emissions from cement production, including the three main components of emissions: direct emissions from the calcination process for clinker production, direct emissions from fossil fuel combustion and indirect emissions from electricity consumption. This paper examines in detail the differences between common methodologies for each emission component, and considers their effect on total emissions. We then evaluate the overall level of uncertainty implied by the differences among methodologies according to recommendations of the Joint Committee for Guides in Metrology. We find a relative uncertainty in China’s cement-related emissions in the range of 10 to 18%. This result highlights the importance of understanding and refining methods of estimating emissions in this important industrial sector. - Highlights: ► CO 2 emission estimates are critical given China’s cement production scale. ► Methodological differences for emission components are compared. ► Results show relative uncertainty in China’s cement-related emissions of about 10%. ► IPCC Guidelines and CSI Cement CO 2 and Energy Protocol are recommended

Uncertainty of feedback and state estimation determines the speed of motor adaptation

Directory of Open Access Journals (Sweden)

Kunlin Wei

2010-05-01

Full Text Available Humans can adapt their motor behaviors to deal with ongoing changes. To achieve this, the nervous system needs to estimate central variables for our movement based on past knowledge and new feedback, both of which are uncertain. In the Bayesian framework, rates of adaptation characterize how noisy feedback is in comparison to the uncertainty of the state estimate. The predictions of Bayesian models are intuitive: the nervous system should adapt slower when sensory feedback is more noisy and faster when its state estimate is more uncertain. Here we want to quantitatively understand how uncertainty in these two factors affects motor adaptation. In a hand reaching experiment we measured trial-by-trial adaptation to a randomly changing visual perturbation to characterize the way the nervous system handles uncertainty in state estimation and feedback. We found both qualitative predictions of Bayesian models confirmed. Our study provides evidence that the nervous system represents and uses uncertainty in state estimate and feedback during motor adaptation.

Sensitivity of process design to uncertainties in property estimates applied to extractive distillation

DEFF Research Database (Denmark)

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

thermodynamic and thermo-physical models is critical to obtain a feasible and operable process design and many guidelines pertaining to this can be found in the literature. But even if appropriate models have been chosen, the user needs to keep in mind that these models contain uncertainties which may propagate...... through the calculation steps to such an extent that the final design might not be feasible or lead to poor performance. Therefore it is necessary to evaluate the sensitivity of process design to the uncertainties in property estimates obtained from thermo-physical property models. Uncertainty...... of the methodology is illustrated using a case study of extractive distillation in which acetone is separated from methanol using water as a solvent. Among others, the vapour pressure of acetone and water was found to be the most critical and even small uncertainties from -0.25 % to +0.75 % in vapour pressure data...

Uncertainty estimation in nuclear material weighing

Energy Technology Data Exchange (ETDEWEB)

Thaure, Bernard [Institut de Radioprotection et de Surete Nucleaire, Fontenay aux Roses, (France)

2011-12-15

The assessment of nuclear material quantities located in nuclear plants requires knowledge of additions and subtractions of amounts of different types of materials. Most generally, the quantity of nuclear material held is deduced from 3 parameters: a mass (or a volume of product); a concentration of nuclear material in the product considered; and an isotopic composition. Global uncertainties associated with nuclear material quantities depend upon the confidence level of results obtained in the measurement of every different parameter. Uncertainties are generally estimated by considering five influencing parameters (ISHIKAWA's rule): the material itself; the measurement system; the applied method; the environmental conditions; and the operator. A good practice guide, to be used to deal with weighing errors and problems encountered, is presented in the paper.

Uncertainties in fatal cancer risk estimates used in radiation protection

International Nuclear Information System (INIS)

Kai, Michiaki

1999-01-01

Although ICRP and NCRP had not described the details of uncertainties in cancer risk estimates in radiation protection, NCRP, in 1997, firstly reported the results of uncertainty analysis (NCRP No.126) and which is summarized in this paper. The NCRP report pointed out that there are following five factors which uncertainty possessing: uncertainty in epidemiological studies, in dose assessment, in transforming the estimates to risk assessment, in risk prediction and in extrapolation to the low dose/dose rate. These individual factors were analyzed statistically to obtain the relationship between the probability of cancer death in the US population and life time risk coefficient (% per Sv), which showed that, for the latter, the mean value was 3.99 x 10 -2 /Sv, median, 3.38 x 10 -2 /Sv, GSD (geometrical standard deviation), 1.83 x 10 -2 /Sv and 95% confidential limit, 1.2-8.84 x 10 -2 /Sv. The mean value was smaller than that of ICRP recommendation (5 x 10 -2 /Sv), indicating that the value has the uncertainty factor of 2.5-3. Moreover, the most important factor was shown to be the uncertainty in DDREF (dose/dose rate reduction factor). (K.H.)

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

Uncertainty estimation and multi sensor fusion for kinematic laser tracker measurements

Science.gov (United States)

Ulrich, Thomas

2013-08-01

Laser trackers are widely used to measure kinematic tasks such as tracking robot movements. Common methods to evaluate the uncertainty in the kinematic measurement include approximations specified by the manufacturers, various analytical adjustment methods and the Kalman filter. In this paper a new, real-time technique is proposed, which estimates the 4D-path (3D-position + time) uncertainty of an arbitrary path in space. Here a hybrid system estimator is applied in conjunction with the kinematic measurement model. This method can be applied to processes, which include various types of kinematic behaviour, constant velocity, variable acceleration or variable turn rates. The new approach is compared with the Kalman filter and a manufacturer's approximations. The comparison was made using data obtained by tracking an industrial robot's tool centre point with a Leica laser tracker AT901 and a Leica laser tracker LTD500. It shows that the new approach is more appropriate to analysing kinematic processes than the Kalman filter, as it reduces overshoots and decreases the estimated variance. In comparison with the manufacturer's approximations, the new approach takes account of kinematic behaviour with an improved description of the real measurement process and a reduction in estimated variance. This approach is therefore well suited to the analysis of kinematic processes with unknown changes in kinematic behaviour as well as the fusion among laser trackers.

On the influence of uncertainties in estimating risk aversion and working interest

International Nuclear Information System (INIS)

MacKay, J.A.; Lerche, I.

1996-01-01

The influence of uncertainties in costs, value, success probability, risk tolerance and mandated working interest are evaluated for their impact on assessing probable ranges of uncertainty on risk adjusted value, RAV, using different models. The relative importance of different factors in contributing to the uncertainty in RAV is analyzed, as is the influence of different probability distributions for the intrinsic variables entering the RAV model formulae. Numerical illustrations indicate how the RAV probabilities depend not only on the model functions (Cozzolino, hyperbolic tangent) used to provide RAV estimates, but also on the intrinsic shapes of the probability distributions from which are drawn input parameter values for Monte Carlo simulations. In addition, a mandated range of working interest can be addressed as an extra variable contributing to the probabilistic range of RAV; while negative RAV values for high-cost project can be used to assess the probable buy-out amount one should be prepared to pay depending on corporate risk philosophy. Also, the procedures illustrate how the relative contributions of scientific factors influence uncertainty of reserve assessments, allowing one to determine where to concentrate effort to improve the ranges of uncertainty. (Author)

A statistical methodology for quantification of uncertainty in best estimate code physical models

International Nuclear Information System (INIS)

Vinai, Paolo; Macian-Juan, Rafael; Chawla, Rakesh

2007-01-01

A novel uncertainty assessment methodology, based on a statistical non-parametric approach, is presented in this paper. It achieves quantification of code physical model uncertainty by making use of model performance information obtained from studies of appropriate separate-effect tests. Uncertainties are quantified in the form of estimated probability density functions (pdf's), calculated with a newly developed non-parametric estimator. The new estimator objectively predicts the probability distribution of the model's 'error' (its uncertainty) from databases reflecting the model's accuracy on the basis of available experiments. The methodology is completed by applying a novel multi-dimensional clustering technique based on the comparison of model error samples with the Kruskall-Wallis test. This takes into account the fact that a model's uncertainty depends on system conditions, since a best estimate code can give predictions for which the accuracy is affected by the regions of the physical space in which the experiments occur. The final result is an objective, rigorous and accurate manner of assigning uncertainty to coded models, i.e. the input information needed by code uncertainty propagation methodologies used for assessing the accuracy of best estimate codes in nuclear systems analysis. The new methodology has been applied to the quantification of the uncertainty in the RETRAN-3D void model and then used in the analysis of an independent separate-effect experiment. This has clearly demonstrated the basic feasibility of the approach, as well as its advantages in yielding narrower uncertainty bands in quantifying the code's accuracy for void fraction predictions

Uncertainty in population growth rates: determining confidence intervals from point estimates of parameters.

Directory of Open Access Journals (Sweden)

Eleanor S Devenish Nelson

Full Text Available BACKGROUND: Demographic models are widely used in conservation and management, and their parameterisation often relies on data collected for other purposes. When underlying data lack clear indications of associated uncertainty, modellers often fail to account for that uncertainty in model outputs, such as estimates of population growth. METHODOLOGY/PRINCIPAL FINDINGS: We applied a likelihood approach to infer uncertainty retrospectively from point estimates of vital rates. Combining this with resampling techniques and projection modelling, we show that confidence intervals for population growth estimates are easy to derive. We used similar techniques to examine the effects of sample size on uncertainty. Our approach is illustrated using data on the red fox, Vulpes vulpes, a predator of ecological and cultural importance, and the most widespread extant terrestrial mammal. We show that uncertainty surrounding estimated population growth rates can be high, even for relatively well-studied populations. Halving that uncertainty typically requires a quadrupling of sampling effort. CONCLUSIONS/SIGNIFICANCE: Our results compel caution when comparing demographic trends between populations without accounting for uncertainty. Our methods will be widely applicable to demographic studies of many species.

Bayesian analysis for uncertainty estimation of a canopy transpiration model

Science.gov (United States)

Samanta, S.; Mackay, D. S.; Clayton, M. K.; Kruger, E. L.; Ewers, B. E.

2007-04-01

A Bayesian approach was used to fit a conceptual transpiration model to half-hourly transpiration rates for a sugar maple (Acer saccharum) stand collected over a 5-month period and probabilistically estimate its parameter and prediction uncertainties. The model used the Penman-Monteith equation with the Jarvis model for canopy conductance. This deterministic model was extended by adding a normally distributed error term. This extension enabled using Markov chain Monte Carlo simulations to sample the posterior parameter distributions. The residuals revealed approximate conformance to the assumption of normally distributed errors. However, minor systematic structures in the residuals at fine timescales suggested model changes that would potentially improve the modeling of transpiration. Results also indicated considerable uncertainties in the parameter and transpiration estimates. This simple methodology of uncertainty analysis would facilitate the deductive step during the development cycle of deterministic conceptual models by accounting for these uncertainties while drawing inferences from data.

Estimation of a multivariate mean under model selection uncertainty

Directory of Open Access Journals (Sweden)

Georges Nguefack-Tsague

2014-05-01

Full Text Available Model selection uncertainty would occur if we selected a model based on one data set and subsequently applied it for statistical inferences, because the "correct" model would not be selected with certainty.  When the selection and inference are based on the same dataset, some additional problems arise due to the correlation of the two stages (selection and inference. In this paper model selection uncertainty is considered and model averaging is proposed. The proposal is related to the theory of James and Stein of estimating more than three parameters from independent normal observations. We suggest that a model averaging scheme taking into account the selection procedure could be more appropriate than model selection alone. Some properties of this model averaging estimator are investigated; in particular we show using Stein's results that it is a minimax estimator and can outperform Stein-type estimators.

Uncertainty in exposure of underground miners to radon daughters and the effect of uncertainty on risk estimates

International Nuclear Information System (INIS)

1989-10-01

Studies of underground miners provide the principal basis for assessing the risk from radon daughter exposure. An important problem in all epidemiological studies of underground miners is the reliability of the estimates of the miners' exposures. This study examines the various sources of uncertainty in exposure estimation for the principal epidemiologic studies reported in the literature including the temporal and spatial variability of radon sources and, with the passage of time, changes to both mining methods and ventilation conditions. Uncertainties about work histories and the role of other hard rock mining experience are also discussed. The report also describes two statistical approaches, both based on Bayesian methods, by which the effects on the estimated risk coefficient of uncertainty in exposure (WLM) can be examined. One approach requires only an estimate of the cumulative WLM exposure of a group of miners, an estimate of the number of (excess) lung cancers potentially attributable to that exposure, and a specification of the uncertainty about the cumulative exposure of the group. The second approach is based on a linear regression model which incorporates errors (uncertainty) in the independent variable (WLM) and allows the dependent variable (cases) to be Poisson distributed. The method permits the calculation of marginal probability distributions for either slope (risk coefficient) or intercept. The regression model approach is applied to several published data sets from epidemiological studies of miners. Specific results are provided for each data set and apparent differences in risk coefficients are discussed. The studies of U.S. uranium miners, Ontario uranium miners and Czechoslovakian uranium miners are argued to provide the best basis for risk estimation at this time. In general terms, none of the analyses performed are inconsistent with a linear exposure-effect relation. Based on analyses of the overall miner groups, the most likely ranges

Uncertainty and validation. Effect of user interpretation on uncertainty estimates

International Nuclear Information System (INIS)

Kirchner, G.; Peterson, R.

1996-11-01

Uncertainty in predictions of environmental transfer models arises from, among other sources, the adequacy of the conceptual model, the approximations made in coding the conceptual model, the quality of the input data, the uncertainty in parameter values, and the assumptions made by the user. In recent years efforts to quantify the confidence that can be placed in predictions have been increasing, but have concentrated on a statistical propagation of the influence of parameter uncertainties on the calculational results. The primary objective of this Working Group of BIOMOVS II was to test user's influence on model predictions on a more systematic basis than has been done before. The main goals were as follows: To compare differences between predictions from different people all using the same model and the same scenario description with the statistical uncertainties calculated by the model. To investigate the main reasons for different interpretations by users. To create a better awareness of the potential influence of the user on the modeling results. Terrestrial food chain models driven by deposition of radionuclides from the atmosphere were used. Three codes were obtained and run with three scenarios by a maximum of 10 users. A number of conclusions can be drawn some of which are general and independent of the type of models and processes studied, while others are restricted to the few processes that were addressed directly: For any set of predictions, the variation in best estimates was greater than one order of magnitude. Often the range increased from deposition to pasture to milk probably due to additional transfer processes. The 95% confidence intervals about the predictions calculated from the parameter distributions prepared by the participants did not always overlap the observations; similarly, sometimes the confidence intervals on the predictions did not overlap. Often the 95% confidence intervals of individual predictions were smaller than the

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

Uncertainty in predictions of environmental transfer models arises from, among other sources, the adequacy of the conceptual model, the approximations made in coding the conceptual model, the quality of the input data, the uncertainty in parameter values, and the assumptions made by the user. In recent years efforts to quantify the confidence that can be placed in predictions have been increasing, but have concentrated on a statistical propagation of the influence of parameter uncertainties on the calculational results. The primary objective of this Working Group of BIOMOVS II was to test user's influence on model predictions on a more systematic basis than has been done before. The main goals were as follows: To compare differences between predictions from different people all using the same model and the same scenario description with the statistical uncertainties calculated by the model. To investigate the main reasons for different interpretations by users. To create a better awareness of the potential influence of the user on the modeling results. Terrestrial food chain models driven by deposition of radionuclides from the atmosphere were used. Three codes were obtained and run with three scenarios by a maximum of 10 users. A number of conclusions can be drawn some of which are general and independent of the type of models and processes studied, while others are restricted to the few processes that were addressed directly: For any set of predictions, the variation in best estimates was greater than one order of magnitude. Often the range increased from deposition to pasture to milk probably due to additional transfer processes. The 95% confidence intervals about the predictions calculated from the parameter distributions prepared by the participants did not always overlap the observations; similarly, sometimes the confidence intervals on the predictions did not overlap. Often the 95% confidence intervals of individual predictions were smaller than the

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.

Uncertainties in Early Stage Capital Cost Estimation of Process Design – A case study on biorefinery design

Directory of Open Access Journals (Sweden)

Gurkan eSin

2015-02-01

Full Text Available Capital investment, next to the product demand, sales and production costs, is one of the key metrics commonly used for project evaluation and feasibility assessment. Estimating the investment costs of a new product/process alternative during early stage design is a challenging task. This is especially important in biorefinery research, where available information and experiences with new technologies is limited. A systematic methodology for uncertainty analysis of cost data is proposed that employs (a Bootstrapping as a regression method when cost data is available and (b the Monte Carlo technique as an error propagation method based on expert input when cost data is not available. Four well-known models for early stage cost estimation are reviewed an analyzed using the methodology. The significance of uncertainties of cost data for early stage process design is highlighted using the synthesis and design of a biorefinery as a case study. The impact of uncertainties in cost estimation on the identification of optimal processing paths is found to be profound. To tackle this challenge, a comprehensive techno-economic risk analysis framework is presented to enable robust decision making under uncertainties. One of the results using an order-of-magnitude estimate shows that the production of diethyl ether and 1,3-butadiene are the most promising with economic risks of 0.24 MM$/a and 4.6 MM$/a due to uncertainties in cost estimations, respectively.

Approach and methods to evaluate the uncertainty in system thermalhydraulic calculations

International Nuclear Information System (INIS)

D'Auria, F.

2004-01-01

The evaluation of uncertainty constitutes the necessary supplement of Best Estimate (BE) 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. In the present paper the approaches to uncertainty are outlined and the CIAU (Code with capability of Internal Assessment of Uncertainty) method proposed by the University of Pisa is described including ideas at the basis and results from applications. An activity in progress at the International Atomic Energy Agency (IAEA) is considered. Two approaches are distinguished that are characterized as 'propagation of code input uncertainty' and 'propagation of code output errors'. For both methods, the thermal-hydraulic code is at the centre of the process of uncertainty evaluation: in the former case the code itself is adopted to compute the error bands and to propagate the input errors, in the latter case the errors in code application to relevant measurements are used to derive the error bands. The CIAU method exploits the idea of the 'status approach' for identifying the thermalhydraulic conditions of an accident in any Nuclear Power Plant (NPP). Errors in predicting such status are derived from the comparison between predicted and measured quantities and, in the stage of the application of the method, are used to compute the uncertainty. (author)

Methodology for uncertainty estimation of Hanford tank chemical and radionuclide inventories and concentrations

International Nuclear Information System (INIS)

Chen, G.; Ferryman, T.A.; Remund, K.M.

1998-02-01

The exact physical and chemical nature of 55 million gallons of toxic waste held in 177 underground waste tanks at the Hanford Site is not known with sufficient detail to support the safety, retrieval, and immobilization missions presented to Hanford. The Hanford Best Basis team has made point estimates of the inventories in each tank. The purpose of this study is to estimate probability distributions for each of the 71 analytes and 177 tanks that the Hanford Best Basis team has made point estimates for. This will enable uncertainty intervals to be calculated for the Best Basis inventories and should facilitate the safety, retrieval, and immobilization missions. Section 2 of this document describes the overall approach used to estimate tank inventory uncertainties. Three major components are considered in this approach: chemical concentration, density, and waste volume. Section 2 also describes the two different methods used to evaluate the tank wastes in terms of sludges and in terms of supernatant or saltcakes. Sections 3 and 4 describe in detail the methodology to assess the probability distributions for each of the three components, as well as the data sources for implementation. The conclusions are given in Section 5

Stability Analysis for Li-Ion Battery Model Parameters and State of Charge Estimation by Measurement Uncertainty Consideration

Directory of Open Access Journals (Sweden)

Shifei Yuan

2015-07-01

Full Text Available Accurate estimation of model parameters and state of charge (SoC is crucial for the lithium-ion battery management system (BMS. In this paper, the stability of the model parameters and SoC estimation under measurement uncertainty is evaluated by three different factors: (i sampling periods of 1/0.5/0.1 s; (ii current sensor precisions of ±5/±50/±500 mA; and (iii voltage sensor precisions of ±1/±2.5/±5 mV. Firstly, the numerical model stability analysis and parametric sensitivity analysis for battery model parameters are conducted under sampling frequency of 1–50 Hz. The perturbation analysis is theoretically performed of current/voltage measurement uncertainty on model parameter variation. Secondly, the impact of three different factors on the model parameters and SoC estimation was evaluated with the federal urban driving sequence (FUDS profile. The bias correction recursive least square (CRLS and adaptive extended Kalman filter (AEKF algorithm were adopted to estimate the model parameters and SoC jointly. Finally, the simulation results were compared and some insightful findings were concluded. For the given battery model and parameter estimation algorithm, the sampling period, and current/voltage sampling accuracy presented a non-negligible effect on the estimation results of model parameters. This research revealed the influence of the measurement uncertainty on the model parameter estimation, which will provide the guidelines to select a reasonable sampling period and the current/voltage sensor sampling precisions in engineering applications.

Uncertainty estimation of shape and roughness measurement

NARCIS (Netherlands)

Morel, M.A.A.

2006-01-01

One of the most common techniques to measure a surface or form is mechanical probing. Although used since the early 30s of the 20th century, a method to calculate a task specific uncertainty budget was not yet devised. Guidelines and statistical estimates are common in certain cases but an

A New Form of Nondestructive Strength-Estimating Statistical Models Accounting for Uncertainty of Model and Aging Effect of Concrete

International Nuclear Information System (INIS)

Hong, Kee Jeung; Kim, Jee Sang

2009-01-01

As concrete ages, the surrounding environment is expected to have growing influences on the concrete. As all the impacts of the environment cannot be considered in the strength-estimating model of a nondestructive concrete test, the increase in concrete age leads to growing uncertainty in the strength-estimating model. Therefore, the variation of the model error increases. It is necessary to include those impacts in the probability model of concrete strength attained from the nondestructive tests so as to build a more accurate reliability model for structural performance evaluation. This paper reviews and categorizes the existing strength-estimating statistical models of nondestructive concrete test, and suggests a new form of the strength-estimating statistical models to properly reflect the model uncertainty due to aging of the concrete. This new form of the statistical models will lay foundation for more accurate structural performance evaluation.

Uncertainty Estimation of Neutron Activation Analysis in Zinc Elemental Determination in Food Samples

International Nuclear Information System (INIS)

Endah Damastuti; Muhayatun; Diah Dwiana L

2009-01-01

Beside to complished the requirements of international standard of ISO/IEC 17025:2005, uncertainty estimation should be done to increase quality and confidence of analysis results and also to establish traceability of the analysis results to SI unit. Neutron activation analysis is a major technique used by Radiometry technique analysis laboratory and is included as scope of accreditation under ISO/IEC 17025:2005, therefore uncertainty estimation of neutron activation analysis is needed to be carried out. Sample and standard preparation as well as, irradiation and measurement using gamma spectrometry were the main activities which could give contribution to uncertainty. The components of uncertainty sources were specifically explained. The result of expanded uncertainty was 4,0 mg/kg with level of confidence 95% (coverage factor=2) and Zn concentration was 25,1 mg/kg. Counting statistic of cuplikan and standard were the major contribution of combined uncertainty. The uncertainty estimation was expected to increase the quality of the analysis results and could be applied further to other kind of samples. (author)

Comparison between bottom-up and top-down approaches in the estimation of measurement uncertainty.

Science.gov (United States)

Lee, Jun Hyung; Choi, Jee-Hye; Youn, Jae Saeng; Cha, Young Joo; Song, Woonheung; Park, Ae Ja

2015-06-01

Measurement uncertainty is a metrological concept to quantify the variability of measurement results. There are two approaches to estimate measurement uncertainty. In this study, we sought to provide practical and detailed examples of the two approaches and compare the bottom-up and top-down approaches to estimating measurement uncertainty. We estimated measurement uncertainty of the concentration of glucose according to CLSI EP29-A guideline. Two different approaches were used. First, we performed a bottom-up approach. We identified the sources of uncertainty and made an uncertainty budget and assessed the measurement functions. We determined the uncertainties of each element and combined them. Second, we performed a top-down approach using internal quality control (IQC) data for 6 months. Then, we estimated and corrected systematic bias using certified reference material of glucose (NIST SRM 965b). The expanded uncertainties at the low glucose concentration (5.57 mmol/L) by the bottom-up approach and top-down approaches were ±0.18 mmol/L and ±0.17 mmol/L, respectively (all k=2). Those at the high glucose concentration (12.77 mmol/L) by the bottom-up and top-down approaches were ±0.34 mmol/L and ±0.36 mmol/L, respectively (all k=2). We presented practical and detailed examples for estimating measurement uncertainty by the two approaches. The uncertainties by the bottom-up approach were quite similar to those by the top-down approach. Thus, we demonstrated that the two approaches were approximately equivalent and interchangeable and concluded that clinical laboratories could determine measurement uncertainty by the simpler top-down approach.

Development of Evaluation Code for MUF Uncertainty

International Nuclear Information System (INIS)

Won, Byung Hee; Han, Bo Young; Shin, Hee Sung; Ahn, Seong-Kyu; Park, Geun-Il; Park, Se Hwan

2015-01-01

Material Unaccounted For (MUF) is the material balance evaluated by measured nuclear material in a Material Balance Area (MBA). Assuming perfect measurements and no diversion from a facility, one can expect a zero MUF. However, non-zero MUF is always occurred because of measurement uncertainty even though the facility is under normal operation condition. Furthermore, there are many measurements using different equipment at various Key Measurement Points (KMPs), and the MUF uncertainty is affected by errors of those measurements. Evaluating MUF uncertainty is essentially required to develop safeguards system including nuclear measurement system in pyroprocessing, which is being developed for reducing radioactive waste from spent fuel in Korea Atomic Energy Research Institute (KAERI). The evaluation code for analyzing MUF uncertainty has been developed and it was verified using sample problem from the IAEA reference. MUF uncertainty can be simply and quickly calculated by using this evaluation code which is made based on graphical user interface for user friendly. It is also expected that the code will make the sensitivity analysis on the MUF uncertainty for the various safeguards systems easy and more systematic. It is suitable for users who want to evaluate the conventional safeguards system as well as to develop a new system for developing facilities

Development of Evaluation Code for MUF Uncertainty

Energy Technology Data Exchange (ETDEWEB)

Won, Byung Hee; Han, Bo Young; Shin, Hee Sung; Ahn, Seong-Kyu; Park, Geun-Il; Park, Se Hwan [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2015-05-15

Material Unaccounted For (MUF) is the material balance evaluated by measured nuclear material in a Material Balance Area (MBA). Assuming perfect measurements and no diversion from a facility, one can expect a zero MUF. However, non-zero MUF is always occurred because of measurement uncertainty even though the facility is under normal operation condition. Furthermore, there are many measurements using different equipment at various Key Measurement Points (KMPs), and the MUF uncertainty is affected by errors of those measurements. Evaluating MUF uncertainty is essentially required to develop safeguards system including nuclear measurement system in pyroprocessing, which is being developed for reducing radioactive waste from spent fuel in Korea Atomic Energy Research Institute (KAERI). The evaluation code for analyzing MUF uncertainty has been developed and it was verified using sample problem from the IAEA reference. MUF uncertainty can be simply and quickly calculated by using this evaluation code which is made based on graphical user interface for user friendly. It is also expected that the code will make the sensitivity analysis on the MUF uncertainty for the various safeguards systems easy and more systematic. It is suitable for users who want to evaluate the conventional safeguards system as well as to develop a new system for developing facilities.

Hydrological model uncertainty due to spatial evapotranspiration estimation methods

Science.gov (United States)

Yu, Xuan; Lamačová, Anna; Duffy, Christopher; Krám, Pavel; Hruška, Jakub

2016-05-01

Evapotranspiration (ET) continues to be a difficult process to estimate in seasonal and long-term water balances in catchment models. Approaches to estimate ET typically use vegetation parameters (e.g., leaf area index [LAI], interception capacity) obtained from field observation, remote sensing data, national or global land cover products, and/or simulated by ecosystem models. In this study we attempt to quantify the uncertainty that spatial evapotranspiration estimation introduces into hydrological simulations when the age of the forest is not precisely known. The Penn State Integrated Hydrologic Model (PIHM) was implemented for the Lysina headwater catchment, located 50°03‧N, 12°40‧E in the western part of the Czech Republic. The spatial forest patterns were digitized from forest age maps made available by the Czech Forest Administration. Two ET methods were implemented in the catchment model: the Biome-BGC forest growth sub-model (1-way coupled to PIHM) and with the fixed-seasonal LAI method. From these two approaches simulation scenarios were developed. We combined the estimated spatial forest age maps and two ET estimation methods to drive PIHM. A set of spatial hydrologic regime and streamflow regime indices were calculated from the modeling results for each method. Intercomparison of the hydrological responses to the spatial vegetation patterns suggested considerable variation in soil moisture and recharge and a small uncertainty in the groundwater table elevation and streamflow. The hydrologic modeling with ET estimated by Biome-BGC generated less uncertainty due to the plant physiology-based method. The implication of this research is that overall hydrologic variability induced by uncertain management practices was reduced by implementing vegetation models in the catchment models.

Uncertainty Estimation of Shear-wave Velocity Structure from Bayesian Inversion of Microtremor Array Dispersion Data

Science.gov (United States)

Dosso, S. E.; Molnar, S.; Cassidy, J.

2010-12-01

Bayesian inversion of microtremor array dispersion data is applied, with evaluation of data errors and model parameterization, to produce the most-probable shear-wave velocity (VS) profile together with quantitative uncertainty estimates. Generally, the most important property characterizing earthquake site response is the subsurface VS structure. The microtremor array method determines phase velocity dispersion of Rayleigh surface waves from multi-instrument recordings of urban noise. Inversion of dispersion curves for VS structure is a non-unique and nonlinear problem such that meaningful evaluation of confidence intervals is required. Quantitative uncertainty estimation requires not only a nonlinear inversion approach that samples models proportional to their probability, but also rigorous estimation of the data error statistics and an appropriate model parameterization. A Bayesian formulation represents the solution of the inverse problem in terms of the posterior probability density (PPD) of the geophysical model parameters. Markov-chain Monte Carlo methods are used with an efficient implementation of Metropolis-Hastings sampling to provide an unbiased sample from the PPD to compute parameter uncertainties and inter-relationships. Nonparametric estimation of a data error covariance matrix from residual analysis is applied with rigorous a posteriori statistical tests to validate the covariance estimate and the assumption of a Gaussian error distribution. The most appropriate model parameterization is determined using the Bayesian information criterion (BIC), which provides the simplest model consistent with the resolving power of the data. Parameter uncertainties are found to be under-estimated when data error correlations are neglected and when compressional-wave velocity and/or density (nuisance) parameters are fixed in the inversion. Bayesian inversion of microtremor array data is applied at two sites in British Columbia, the area of highest seismic risk in

The Effect of Uncertainty in Exposure Estimation on the Exposure-Response Relation between 1,3-Butadiene and Leukemia

Directory of Open Access Journals (Sweden)

George Maldonado

2009-09-01

Full Text Available Abstract: In a follow-up study of mortality among North American synthetic rubber industry workers, cumulative exposure to 1,3-butadiene was positively associated with leukemia. Problems with historical exposure estimation, however, may have distorted the association. To evaluate the impact of potential inaccuracies in exposure estimation, we conducted uncertainty analyses of the relation between cumulative exposure to butadiene and leukemia. We created the 1,000 sets of butadiene estimates using job-exposure matrices consisting of exposure values that corresponded to randomly selected percentiles of the approximate probability distribution of plant-, work area/job group-, and year specific butadiene ppm. We then analyzed the relation between cumulative exposure to butadiene and leukemia for each of the 1,000 sets of butadiene estimates. In the uncertainty analysis, the point estimate of the RR for the first non zero exposure category (>0–<37.5 ppm-years was most likely to be about 1.5. The rate ratio for the second exposure category (37.5–<184.7 ppm-years was most likely to range from 1.5 to 1.8. The RR for category 3 of exposure (184.7–<425.0 ppm-years was most likely between 2.1 and 3.0. The RR for the highest exposure category (425.0+ ppm-years was likely to be between 2.9 and 3.7. This range off RR point estimates can best be interpreted as a probability distribution that describes our uncertainty in RR point estimates due to uncertainty in exposure estimation. After considering the complete probability distributions of butadiene exposure estimates, the exposure-response association of butadiene and leukemia was maintained. This exercise was a unique example of how uncertainty analyses can be used to investigate and support an observed measure of effect when occupational exposure estimates are employed in the absence of direct exposure measurements.

Modeling Input Errors to Improve Uncertainty Estimates for Sediment Transport Model Predictions

Science.gov (United States)

Jung, J. Y.; Niemann, J. D.; Greimann, B. P.

2016-12-01

Bayesian methods using Markov chain Monte Carlo algorithms have recently been applied to sediment transport models to assess the uncertainty in the model predictions due to the parameter values. Unfortunately, the existing approaches can only attribute overall uncertainty to the parameters. This limitation is critical because no model can produce accurate forecasts if forced with inaccurate input data, even if the model is well founded in physical theory. In this research, an existing Bayesian method is modified to consider the potential errors in input data during the uncertainty evaluation process. The input error is modeled using Gaussian distributions, and the means and standard deviations are treated as uncertain parameters. The proposed approach is tested by coupling it to the Sedimentation and River Hydraulics - One Dimension (SRH-1D) model and simulating a 23-km reach of the Tachia River in Taiwan. The Wu equation in SRH-1D is used for computing the transport capacity for a bed material load of non-cohesive material. Three types of input data are considered uncertain: (1) the input flowrate at the upstream boundary, (2) the water surface elevation at the downstream boundary, and (3) the water surface elevation at a hydraulic structure in the middle of the reach. The benefits of modeling the input errors in the uncertainty analysis are evaluated by comparing the accuracy of the most likely forecast and the coverage of the observed data by the credible intervals to those of the existing method. The results indicate that the internal boundary condition has the largest uncertainty among those considered. Overall, the uncertainty estimates from the new method are notably different from those of the existing method for both the calibration and forecast periods.

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.

Approaches to Evaluating Probability of Collision Uncertainty

Science.gov (United States)

Hejduk, Matthew D.; Johnson, Lauren C.

2016-01-01

While the two-dimensional probability of collision (Pc) calculation has served as the main input to conjunction analysis risk assessment for over a decade, it has done this mostly as a point estimate, with relatively little effort made to produce confidence intervals on the Pc value based on the uncertainties in the inputs. The present effort seeks to try to carry these uncertainties through the calculation in order to generate a probability density of Pc results rather than a single average value. Methods for assessing uncertainty in the primary and secondary objects' physical sizes and state estimate covariances, as well as a resampling approach to reveal the natural variability in the calculation, are presented; and an initial proposal for operationally-useful display and interpretation of these data for a particular conjunction is given.

Uncertainties of flood frequency estimation approaches based on continuous simulation using data resampling

Science.gov (United States)

Arnaud, Patrick; Cantet, Philippe; Odry, Jean

2017-11-01

Flood frequency analyses (FFAs) are needed for flood risk management. Many methods exist ranging from classical purely statistical approaches to more complex approaches based on process simulation. The results of these methods are associated with uncertainties that are sometimes difficult to estimate due to the complexity of the approaches or the number of parameters, especially for process simulation. This is the case of the simulation-based FFA approach called SHYREG presented in this paper, in which a rainfall generator is coupled with a simple rainfall-runoff model in an attempt to estimate the uncertainties due to the estimation of the seven parameters needed to estimate flood frequencies. The six parameters of the rainfall generator are mean values, so their theoretical distribution is known and can be used to estimate the generator uncertainties. In contrast, the theoretical distribution of the single hydrological model parameter is unknown; consequently, a bootstrap method is applied to estimate the calibration uncertainties. The propagation of uncertainty from the rainfall generator to the hydrological model is also taken into account. This method is applied to 1112 basins throughout France. Uncertainties coming from the SHYREG method and from purely statistical approaches are compared, and the results are discussed according to the length of the recorded observations, basin size and basin location. Uncertainties of the SHYREG method decrease as the basin size increases or as the length of the recorded flow increases. Moreover, the results show that the confidence intervals of the SHYREG method are relatively small despite the complexity of the method and the number of parameters (seven). This is due to the stability of the parameters and takes into account the dependence of uncertainties due to the rainfall model and the hydrological calibration. Indeed, the uncertainties on the flow quantiles are on the same order of magnitude as those associated with

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)

Evaluation of uncertainty in dosimetry of irradiator system

International Nuclear Information System (INIS)

Santos, Gelson P.; Potiens, Maria P.A.; Vivolo, Vitor

2005-01-01

This paper describes the study of uncertainties in the estimates of dosimetry irradiator system STS 0B85 of LCI IPEN/CNEN-SP. This study is relevant for determination of best measurement capability when the laboratory performs routine calibrations of measuring radiation next the optimal measures designed to radioprotection. It is also a requirement for obtaining the accreditation of the laboratory by the INMETRO. For this dosimetry was used a reference system of the laboratory composed of a electrometer and a spherical ionization chamber of 1 liter. Measurements were made at five distances selected so to include the whole range of the optical bench tests and using three attenuators filters so as to extend the measurement capability. The magnitude used for evaluation was the rate of air kerma for 1 37C s and 6 0C o beams. Were carried out four series of measurements. It was verified the inverse square law to these series and their sets of uncertainty. Unfiltered, with one and two filters series showed good agreement with the inverse square low and the maximum uncertainty obtained was approximately 1.7%. In series with all the filters was a major deviation of the inverse square law and wide increase in uncertainty to measurements at the end of the optical bench

Estimation of uncertainty in tracer gas measurement of air change rates.

Science.gov (United States)

Iizuka, Atsushi; Okuizumi, Yumiko; Yanagisawa, Yukio

2010-12-01

Simple and economical measurement of air change rates can be achieved with a passive-type tracer gas doser and sampler. However, this is made more complex by the fact many buildings are not a single fully mixed zone. This means many measurements are required to obtain information on ventilation conditions. In this study, we evaluated the uncertainty of tracer gas measurement of air change rate in n completely mixed zones. A single measurement with one tracer gas could be used to simply estimate the air change rate when n = 2. Accurate air change rates could not be obtained for n ≥ 2 due to a lack of information. However, the proposed method can be used to estimate an air change rate with an accuracy of air change rate can be avoided. The proposed estimation method will be useful in practical ventilation measurements.

Thermal-Hydraulic Analysis for SBLOCA in OPR1000 and Evaluation of Uncertainty for PSA

International Nuclear Information System (INIS)

Kim, Tae Jin; Park, Goon Cherl

2012-01-01

Probabilistic Safety assessment (PSA) is a mathematical tool to evaluate numerical estimates of risk for nuclear power plants (NPPs). But PSA has the problems about quality and reliability since the quantification of uncertainties from thermal hydraulic (TH) analysis has not been included in the quantification of overall uncertainties in PSA. From the former research, it is proved that the quantification of uncertainties from best-estimate LBLOCA analysis can improve the PSA quality by modifying the core damage frequency (CDF) from the existing PSA report. Basing on the similar concept, this study considers the quantification of SBLOCA analysis results. In this study, however, operator error parameters are also included in addition to the phenomenon parameters which are considered in LBLOCA analysis

Different top-down approaches to estimate measurement uncertainty of whole blood tacrolimus mass concentration values.

Science.gov (United States)

Rigo-Bonnin, Raül; Blanco-Font, Aurora; Canalias, Francesca

2018-05-08

Values of mass concentration of tacrolimus in whole blood are commonly used by the clinicians for monitoring the status of a transplant patient and for checking whether the administered dose of tacrolimus is effective. So, clinical laboratories must provide results as accurately as possible. Measurement uncertainty can allow ensuring reliability of these results. The aim of this study was to estimate measurement uncertainty of whole blood mass concentration tacrolimus values obtained by UHPLC-MS/MS using two top-down approaches: the single laboratory validation approach and the proficiency testing approach. For the single laboratory validation approach, we estimated the uncertainties associated to the intermediate imprecision (using long-term internal quality control data) and the bias (utilizing a certified reference material). Next, we combined them together with the uncertainties related to the calibrators-assigned values to obtain a combined uncertainty for, finally, to calculate the expanded uncertainty. For the proficiency testing approach, the uncertainty was estimated in a similar way that the single laboratory validation approach but considering data from internal and external quality control schemes to estimate the uncertainty related to the bias. The estimated expanded uncertainty for single laboratory validation, proficiency testing using internal and external quality control schemes were 11.8%, 13.2%, and 13.0%, respectively. After performing the two top-down approaches, we observed that their uncertainty results were quite similar. This fact would confirm that either two approaches could be used to estimate the measurement uncertainty of whole blood mass concentration tacrolimus values in clinical laboratories. Copyright © 2018 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

Leaf area index uncertainty estimates for model-data fusion applications

Science.gov (United States)

Andrew D. Richardson; D. Bryan Dail; D.Y. Hollinger

2011-01-01

Estimates of data uncertainties are required to integrate different observational data streams as model constraints using model-data fusion. We describe an approach with which random and systematic uncertainties in optical measurements of leaf area index [LAI] can be quantified. We use data from a measurement campaign at the spruce-dominated Howland Forest AmeriFlux...

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

DEFF Research Database (Denmark)

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

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

Uncertainty evaluation of a regional real-time system for rain-induced landslides

Science.gov (United States)

Kirschbaum, Dalia; Stanley, Thomas; Yatheendradas, Soni

2015-04-01

A new prototype regional model and evaluation framework has been developed over Central America and the Caribbean region using satellite-based information including precipitation estimates, modeled soil moisture, topography, soils, as well as regionally available datasets such as road networks and distance to fault zones. The algorithm framework incorporates three static variables: a susceptibility map; a 24-hr rainfall triggering threshold; and an antecedent soil moisture variable threshold, which have been calibrated using historic landslide events. The thresholds are regionally heterogeneous and are based on the percentile distribution of the rainfall or antecedent moisture time series. A simple decision tree algorithm framework integrates all three variables with the rainfall and soil moisture time series and generates a landslide nowcast in real-time based on the previous 24 hours over this region. This system has been evaluated using several available landslide inventories over the Central America and Caribbean region. Spatiotemporal uncertainty and evaluation metrics of the model are presented here based on available landslides reports. This work also presents a probabilistic representation of potential landslide activity over the region which can be used to further refine and improve the real-time landslide hazard assessment system as well as better identify and characterize the uncertainties inherent in this type of regional approach. The landslide algorithm provides a flexible framework to improve hazard estimation and reduce uncertainty at any spatial and temporal scale.

Assessment of uncertainties of external dose estimation after the Chernobyl accident

International Nuclear Information System (INIS)

Kruk, Julianna

2008-01-01

Full text: In the remote period of time after the Chernobyl accident the estimation of an external exposure with using of direct dose rate measurements or individual monitoring of inhabitants is rationally only for settlements where the preliminary estimation makes the range equal or greater 1.0 mSv per year. For inhabitancies of settlements where the preliminary estimation makes the range less 1.0 mSv per year the external dose is correctly to estimate by calculation. For the last cases the uncertainty should be assessed. The most accessible initial parameter for calculation of a dose of an external exposure is the average ground deposition of Cs-137 for the settlements. The character of density distribution of Cs-137 deposition in an area of one settlement is well enough studied. The best agreement of distribution of this parameter is reached with log-normal distribution practically for all settlements of the investigated territories with factor of a variation 0.3-0.6 and the standard geometrical deviation lying within the limits of 1.4-1.7. The dose factors which correspond to the structure of an available housing of settlement (type of apartment houses: wooden, stone, multi-storey) and age structure of the population are bring the main contribution into uncertainty of the external dose estimation. The situations with a different level of known information have been considered for the estimation of influence of those parameters on the general uncertainty. Thus the estimation of the uncertainty of the external dose was done for two variant: optimistic and pessimistic. In the optimistic case the estimation of external doses will be spent for specific settlement with known structure of housing and according to a known share of the living population in houses of the certain type. In that case, variability value dose factor will be limited to the chosen type of a residential building (for example - the one-storied wooden house), and a share of the living population

Deterministic sensitivity and uncertainty methodology for best estimate system codes applied in nuclear technology

International Nuclear Information System (INIS)

Petruzzi, A.; D'Auria, F.; Cacuci, D.G.

2009-01-01

Nuclear Power Plant (NPP) technology has been developed based on the traditional defense in depth philosophy supported by deterministic and overly conservative methods for safety analysis. In the 1970s [1], conservative hypotheses were introduced for safety analyses to address existing uncertainties. Since then, intensive thermal-hydraulic experimental research has resulted in a considerable increase in knowledge and consequently in the development of best-estimate codes able to provide more realistic information about the physical behaviour and to identify the most relevant safety issues allowing the evaluation of the existing actual margins between the results of the calculations and the acceptance criteria. However, the best-estimate calculation results from complex thermal-hydraulic system codes (like Relap5, Cathare, Athlet, Trace, etc..) are affected by unavoidable approximations that are un-predictable without the use of computational tools that account for the various sources of uncertainty. Therefore the use of best-estimate codes (BE) within the reactor technology, either for design or safety purposes, implies understanding and accepting the limitations and the deficiencies of those codes. Taking into consideration the above framework, a comprehensive approach for utilizing quantified uncertainties arising from Integral Test Facilities (ITFs, [2]) and Separate Effect Test Facilities (SETFs, [3]) in the process of calibrating complex computer models for the application to NPP transient scenarios has been developed. The methodology proposed is capable of accommodating multiple SETFs and ITFs to learn as much as possible about uncertain parameters, allowing for the improvement of the computer model predictions based on the available experimental evidences. The proposed methodology constitutes a major step forward with respect to the generally used expert judgment and statistical methods as it permits a) to establish the uncertainties of any parameter

Uncertainty analysis methods for estimation of reliability of passive system of VHTR

International Nuclear Information System (INIS)

Han, S.J.

2012-01-01

An estimation of reliability of passive system for the probabilistic safety assessment (PSA) of a very high temperature reactor (VHTR) is under development in Korea. The essential approach of this estimation is to measure the uncertainty of the system performance under a specific accident condition. The uncertainty propagation approach according to the simulation of phenomenological models (computer codes) is adopted as a typical method to estimate the uncertainty for this purpose. This presentation introduced the uncertainty propagation and discussed the related issues focusing on the propagation object and its surrogates. To achieve a sufficient level of depth of uncertainty results, the applicability of the propagation should be carefully reviewed. For an example study, Latin-hypercube sampling (LHS) method as a direct propagation was tested for a specific accident sequence of VHTR. The reactor cavity cooling system (RCCS) developed by KAERI was considered for this example study. This is an air-cooled type passive system that has no active components for its operation. The accident sequence is a low pressure conduction cooling (LPCC) accident that is considered as a design basis accident for the safety design of VHTR. This sequence is due to a large failure of the pressure boundary of the reactor system such as a guillotine break of coolant pipe lines. The presentation discussed the obtained insights (benefit and weakness) to apply an estimation of reliability of passive system

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

International Nuclear Information System (INIS)

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

2009-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2009-09-15

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

Epistemic uncertainties when estimating component failure rate

International Nuclear Information System (INIS)

Jordan Cizelj, R.; Mavko, B.; Kljenak, I.

2000-01-01

A method for specific estimation of a component failure rate, based on specific quantitative and qualitative data other than component failures, was developed and is described in the proposed paper. The basis of the method is the Bayesian updating procedure. A prior distribution is selected from a generic database, whereas likelihood is built using fuzzy logic theory. With the proposed method, the component failure rate estimation is based on a much larger quantity of information compared to the presently used classical methods. Consequently, epistemic uncertainties, which are caused by lack of knowledge about a component or phenomenon are reduced. (author)

Uncertainties in Steric Sea Level Change Estimation During the Satellite Altimeter Era: Concepts and Practices

Science.gov (United States)

MacIntosh, C. R.; Merchant, C. J.; von Schuckmann, K.

2017-01-01

This article presents a review of current practice in estimating steric sea level change, focussed on the treatment of uncertainty. Steric sea level change is the contribution to the change in sea level arising from the dependence of density on temperature and salinity. It is a significant component of sea level rise and a reflection of changing ocean heat content. However, tracking these steric changes still remains a significant challenge for the scientific community. We review the importance of understanding the uncertainty in estimates of steric sea level change. Relevant concepts of uncertainty are discussed and illustrated with the example of observational uncertainty propagation from a single profile of temperature and salinity measurements to steric height. We summarise and discuss the recent literature on methodologies and techniques used to estimate steric sea level in the context of the treatment of uncertainty. Our conclusions are that progress in quantifying steric sea level uncertainty will benefit from: greater clarity and transparency in published discussions of uncertainty, including exploitation of international standards for quantifying and expressing uncertainty in measurement; and the development of community "recipes" for quantifying the error covariances in observations and from sparse sampling and for estimating and propagating uncertainty across spatio-temporal scales.

Statistical Methods for Estimating the Uncertainty in the Best Basis Inventories

International Nuclear Information System (INIS)

WILMARTH, S.R.

2000-01-01

This document describes the statistical methods used to determine sample-based uncertainty estimates for the Best Basis Inventory (BBI). For each waste phase, the equation for the inventory of an analyte in a tank is Inventory (Kg or Ci) = Concentration x Density x Waste Volume. the total inventory is the sum of the inventories in the different waste phases. Using tanks sample data: statistical methods are used to obtain estimates of the mean concentration of an analyte the density of the waste, and their standard deviations. The volumes of waste in the different phases, and their standard deviations, are estimated based on other types of data. The three estimates are multiplied to obtain the inventory estimate. The standard deviations are combined to obtain a standard deviation of the inventory. The uncertainty estimate for the Best Basis Inventory (BBI) is the approximate 95% confidence interval on the inventory

Estimation of Model Uncertainties in Closed-loop Systems

DEFF Research Database (Denmark)

Niemann, Hans Henrik; Poulsen, Niels Kjølstad

2008-01-01

This paper describe a method for estimation of parameters or uncertainties in closed-loop systems. The method is based on an application of the dual YJBK (after Youla, Jabr, Bongiorno and Kucera) parameterization of all systems stabilized by a given controller. The dual YJBK transfer function...

Licensing in BE system code calculations. Applications and uncertainty evaluation by CIAU method

International Nuclear Information System (INIS)

Petruzzi, Alessandro; D'Auria, Francesco

2007-01-01

The evaluation of uncertainty constitutes the necessary supplement of Best Estimate (BE) 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. In the present paper the approaches to uncertainty are outlined and the CIAU (Code with capability of Internal Assessment of Uncertainty) method proposed by the University of Pisa is described including ideas at the basis and results from applications. Two approaches are distinguished that are characterized as 'propagation of code input uncertainty' and 'propagation of code output errors'. For both methods, the thermal-hydraulic code is at the centre of the process of uncertainty evaluation: in the former case the code itself is adopted to compute the error bands and to propagate the input errors, in the latter case the errors in code application to relevant measurements are used to derive the error bands. The CIAU method exploits the idea of the 'status approach' for identifying the thermal-hydraulic conditions of an accident in any Nuclear Power Plant (NPP). Errors in predicting such status are derived from the comparison between predicted and measured quantities and, in the stage of the application of the method, are used to compute the uncertainty. (author)

Review of best estimate plus uncertainty methods of thermal-hydraulic safety analysis

International Nuclear Information System (INIS)

Prosek, A.; Mavko, B.

2003-01-01

In 1988 United States Nuclear Regulatory Commission approved the revised rule on the acceptance of emergency core cooling system (ECCS) performance. Since that there has been significant interest in the development of codes and methodologies for best-estimate loss-of-coolant accident (LOCAs) analyses. Several new best estimate plus uncertainty methods (BEPUs) were developed in the world. The purpose of the paper is to review the developments in the direction of best estimate approaches with uncertainty quantification and to discuss the problems in practical applications of BEPU methods. In general, the licensee methods are following original methods. The study indicated 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 and mature approach. (author)

GUM2DFT—a software tool for uncertainty evaluation of transient signals in the frequency domain

International Nuclear Information System (INIS)

Eichstädt, S; Wilkens, V

2016-01-01

The Fourier transform and its counterpart for discrete time signals, the discrete Fourier transform (DFT), are common tools in measurement science and application. Although almost every scientific software package offers ready-to-use implementations of the DFT, the propagation of uncertainties in line with the guide to the expression of uncertainty in measurement (GUM) is typically neglected. This is of particular importance in dynamic metrology, when input estimation is carried out by deconvolution in the frequency domain. To this end, we present the new open-source software tool GUM2DFT, which utilizes closed formulas for the efficient propagation of uncertainties for the application of the DFT, inverse DFT and input estimation in the frequency domain. It handles different frequency domain representations, accounts for autocorrelation and takes advantage of the symmetry inherent in the DFT result for real-valued time domain signals. All tools are presented in terms of examples which form part of the software package. GUM2DFT will foster GUM-compliant evaluation of uncertainty in a DFT-based analysis and enable metrologists to include uncertainty evaluations in their routine work. (paper)

Uncertainty Evaluation of the SFR Subchannel Thermal-Hydraulic Modeling Using a Hot Channel Factors Analysis

International Nuclear Information System (INIS)

Choi, Sun Rock; Cho, Chung Ho; Kim, Sang Ji

2011-01-01

In an SFR core analysis, a hot channel factors (HCF) method is most commonly used to evaluate uncertainty. It was employed to the early design such as the CRBRP and IFR. In other ways, the improved thermal design procedure (ITDP) is able to calculate the overall uncertainty based on the Root Sum Square technique and sensitivity analyses of each design parameters. The Monte Carlo method (MCM) is also employed to estimate the uncertainties. In this method, all the input uncertainties are randomly sampled according to their probability density functions and the resulting distribution for the output quantity is analyzed. Since an uncertainty analysis is basically calculated from the temperature distribution in a subassembly, the core thermal-hydraulic modeling greatly affects the resulting uncertainty. At KAERI, the SLTHEN and MATRA-LMR codes have been utilized to analyze the SFR core thermal-hydraulics. The SLTHEN (steady-state LMR core thermal hydraulics analysis code based on the ENERGY model) code is a modified version of the SUPERENERGY2 code, which conducts a multi-assembly, steady state calculation based on a simplified ENERGY model. The detailed subchannel analysis code MATRA-LMR (Multichannel Analyzer for Steady-State and Transients in Rod Arrays for Liquid Metal Reactors), an LMR version of MATRA, was also developed specifically for the SFR core thermal-hydraulic analysis. This paper describes comparative studies for core thermal-hydraulic models. The subchannel analysis and a hot channel factors based uncertainty evaluation system is established to estimate the core thermofluidic uncertainties using the MATRA-LMR code and the results are compared to those of the SLTHEN code

A method countries can use to estimate changes in carbon stored in harvested wood products and the uncertainty of such estimates

Science.gov (United States)

Kenneth E. Skog; Kim Pingoud; James E. Smith

2004-01-01

A method is suggested for estimating additions to carbon stored in harvested wood products (HWP) and for evaluating uncertainty. The method uses data on HWP production and trade from several decades and tracks annual additions to pools of HWP in use, removals from use, additions to solid waste disposal sites (SWDS), and decay from SWDS. The method is consistent with...

Best-estimate analysis and decision making under uncertainty

International Nuclear Information System (INIS)

Orechwa, Y.

2004-01-01

In many engineering analyses of system safety the traditional reliance on conservative evaluation model calculations is being replaced with so called best-estimate analysis. These best-estimate analyses differentiate themselves from the traditional conservative analyses through two ingredients, namely realistic models and an account of the residual uncertainty associated with the model calculations. Best-estimate analysis, in the context of this paper, refers to the numerical evaluation of system properties of interest in situations where direct confirmatory measurements are not feasible. A decision with regard to the safety of the system is then made based on the computed numerical values of the system properties of interest. These situations generally arise in the design of systems that require computed and generally nontrivial extrapolations from the available data. In the case of nuclear reactors, examples are criticality of spent fuel pools, neutronic parameters of new advanced designs where insufficient material is available for mockup critical experiments and, the large break loss of coolant accident (LOCA). In this paper the case of LOCA, is taken to discuss the best-estimate analysis and decision making. Central to decision making is information. Thus, of interest is the source, quantity and quality of the information obtained in a best-estimate analysis, and used to define the acceptance criteria and to formulate a decision rule. This in effect expands the problem from the calculation of a conservative margin to a predefined acceptance criterion, to the formulation of a consistent decision rule and the computation of a test statistic for application of the decision rule. The latter view is a necessary condition for developing risk informed decision rules, and, thus, the relation between design basis analysis criteria and probabilistic risk assessment criteria is key. The discussion is in the context of making a decision under uncertainty for a reactor

Uncertainty estimation of Intensity-Duration-Frequency relationships: A regional analysis

Science.gov (United States)

Mélèse, Victor; Blanchet, Juliette; Molinié, Gilles

2018-03-01

We propose in this article a regional study of uncertainties in IDF curves derived from point-rainfall maxima. We develop two generalized extreme value models based on the simple scaling assumption, first in the frequentist framework and second in the Bayesian framework. Within the frequentist framework, uncertainties are obtained i) from the Gaussian density stemming from the asymptotic normality theorem of the maximum likelihood and ii) with a bootstrap procedure. Within the Bayesian framework, uncertainties are obtained from the posterior densities. We confront these two frameworks on the same database covering a large region of 100, 000 km2 in southern France with contrasted rainfall regime, in order to be able to draw conclusion that are not specific to the data. The two frameworks are applied to 405 hourly stations with data back to the 1980's, accumulated in the range 3 h-120 h. We show that i) the Bayesian framework is more robust than the frequentist one to the starting point of the estimation procedure, ii) the posterior and the bootstrap densities are able to better adjust uncertainty estimation to the data than the Gaussian density, and iii) the bootstrap density give unreasonable confidence intervals, in particular for return levels associated to large return period. Therefore our recommendation goes towards the use of the Bayesian framework to compute uncertainty.

Quantifying reactor safety margins: Part 1: An overview of the code scaling, applicability, and uncertainty evaluation methodology

International Nuclear Information System (INIS)

Boyack, B.E.; Duffey, R.B.; Griffith, P.

1988-01-01

In August 1988, the Nuclear Regulatory Commission (NRC) approved the final version of a revised rule on the acceptance of emergency core cooling systems (ECCS) entitled ''Emergency Core Cooling System; Revisions to Acceptance Criteria.'' The revised rule states an alternate ECCS performance analysis, based on best-estimate methods, may be used to provide more realistic estimates of plant safety margins, provided the licensee quantifies the uncertainty of the estimates and included that uncertainty when comparing the calculated results with prescribed acceptance limits. To support the revised ECCS rule, the NRC and its contractors and consultants have developed and demonstrated a method called the Code Scaling, Applicability, and Uncertainty (CSAU) evaluation methodology. It is an auditable, traceable, and practical method for combining quantitative analyses and expert opinions to arrive at computed values of uncertainty. This paper provides an overview of the CSAU evaluation methodology and its application to a postulated cold-leg, large-break loss-of-coolant accident in a Westinghouse four-loop pressurized water reactor with 17 /times/ 17 fuel. The code selected for this demonstration of the CSAU methodology was TRAC-PF1/MOD1, Version 14.3. 23 refs., 5 figs., 1 tab

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

Estimation of Uncertainty in Tracer Gas Measurement of Air Change Rates

Directory of Open Access Journals (Sweden)

Atsushi Iizuka

2010-12-01

Full Text Available Simple and economical measurement of air change rates can be achieved with a passive-type tracer gas doser and sampler. However, this is made more complex by the fact many buildings are not a single fully mixed zone. This means many measurements are required to obtain information on ventilation conditions. In this study, we evaluated the uncertainty of tracer gas measurement of air change rate in n completely mixed zones. A single measurement with one tracer gas could be used to simply estimate the air change rate when n = 2. Accurate air change rates could not be obtained for n ≥ 2 due to a lack of information. However, the proposed method can be used to estimate an air change rate with an accuracy of

RELAP5 simulation of surge line break accident using combined and best estimate plus uncertainty approaches

International Nuclear Information System (INIS)

Kristof, Marian; Kliment, Tomas; Petruzzi, Alessandro; Lipka, Jozef

2009-01-01

Licensing calculations in a majority of countries worldwide still rely on the application of combined approach using best estimate computer code without evaluation of the code models uncertainty and conservative assumptions on initial and boundary, availability of systems and components and additional conservative assumptions. However best estimate plus uncertainty (BEPU) approach representing the state-of-the-art in the area of safety analysis has a clear potential to replace currently used combined approach. There are several applications of BEPU approach in the area of licensing calculations, but some questions are discussed, namely from the regulatory point of view. In order to find a proper solution to these questions and to support the BEPU approach to become a standard approach for licensing calculations, a broad comparison of both approaches for various transients is necessary. Results of one of such comparisons on the example of the VVER-440/213 NPP pressurizer surge line break event are described in this paper. A Kv-scaled simulation based on PH4-SLB experiment from PMK-2 integral test facility applying its volume and power scaling factor is performed for qualitative assessment of the RELAP5 computer code calculation using the VVER-440/213 plant model. Existing hardware differences are identified and explained. The CIAU method is adopted for performing the uncertainty evaluation. Results using combined and BEPU approaches are in agreement with the experimental values in PMK-2 facility. Only minimal difference between combined and BEPU approached has been observed in the evaluation of the safety margins for the peak cladding temperature. Benefits of the CIAU uncertainty method are highlighted.

Uncertainty estimation and ensemble forecast with a chemistry-transport model - Application to air-quality modeling and simulation

International Nuclear Information System (INIS)

Mallet, Vivien

2005-01-01

The thesis deals with the evaluation of a chemistry-transport model, not primarily with classical comparisons to observations, but through the estimation of its a priori uncertainties due to input data, model formulation and numerical approximations. These three uncertainty sources are studied respectively on the basis of Monte Carlos simulations, multi-models simulations and numerical schemes inter-comparisons. A high uncertainty is found, in output ozone concentrations. In order to overtake the limitations due to the uncertainty, a solution is ensemble forecast. Through combinations of several models (up to forty-eight models) on the basis of past observations, the forecast can be significantly improved. The achievement of this work has also led to develop the innovative modelling-system Polyphemus. (author) [fr

Comparison of Two Methods for Estimating the Sampling-Related Uncertainty of Satellite Rainfall Averages Based on a Large Radar Data Set

Science.gov (United States)

Lau, William K. M. (Technical Monitor); Bell, Thomas L.; Steiner, Matthias; Zhang, Yu; Wood, Eric F.

2002-01-01

The uncertainty of rainfall estimated from averages of discrete samples collected by a satellite is assessed using a multi-year radar data set covering a large portion of the United States. The sampling-related uncertainty of rainfall estimates is evaluated for all combinations of 100 km, 200 km, and 500 km space domains, 1 day, 5 day, and 30 day rainfall accumulations, and regular sampling time intervals of 1 h, 3 h, 6 h, 8 h, and 12 h. These extensive analyses are combined to characterize the sampling uncertainty as a function of space and time domain, sampling frequency, and rainfall characteristics by means of a simple scaling law. Moreover, it is shown that both parametric and non-parametric statistical techniques of estimating the sampling uncertainty produce comparable results. Sampling uncertainty estimates, however, do depend on the choice of technique for obtaining them. They can also vary considerably from case to case, reflecting the great variability of natural rainfall, and should therefore be expressed in probabilistic terms. Rainfall calibration errors are shown to affect comparison of results obtained by studies based on data from different climate regions and/or observation platforms.

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

International Nuclear Information System (INIS)

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

2013-01-01

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

Methods for the calculation of uncertainty in analytical chemistry

Energy Technology Data Exchange (ETDEWEB)

Suh, M. Y.; Sohn, S. C.; Park, Y. J.; Park, K. K.; Jee, K. Y.; Joe, K. S.; Kim, W. H

2000-07-01

This report describes the statistical rules for evaluating and expressing uncertainty in analytical chemistry. The procedures for the evaluation of uncertainty in chemical analysis are illustrated by worked examples. This report, in particular, gives guidance on how uncertainty can be estimated from various chemical analyses. This report can be also used for planning the experiments which will provide the information required to obtain an estimate of uncertainty for the method.

Quantifying measurement uncertainty and spatial variability in the context of model evaluation

Science.gov (United States)

Choukulkar, A.; Brewer, A.; Pichugina, Y. L.; Bonin, T.; Banta, R. M.; Sandberg, S.; Weickmann, A. M.; Djalalova, I.; McCaffrey, K.; Bianco, L.; Wilczak, J. M.; Newman, J. F.; Draxl, C.; Lundquist, J. K.; Wharton, S.; Olson, J.; Kenyon, J.; Marquis, M.

2017-12-01

In an effort to improve wind forecasts for the wind energy sector, the Department of Energy and the NOAA funded the second Wind Forecast Improvement Project (WFIP2). As part of the WFIP2 field campaign, a large suite of in-situ and remote sensing instrumentation was deployed to the Columbia River Gorge in Oregon and Washington from October 2015 - March 2017. The array of instrumentation deployed included 915-MHz wind profiling radars, sodars, wind- profiling lidars, and scanning lidars. The role of these instruments was to provide wind measurements at high spatial and temporal resolution for model evaluation and improvement of model physics. To properly determine model errors, the uncertainties in instrument-model comparisons need to be quantified accurately. These uncertainties arise from several factors such as measurement uncertainty, spatial variability, and interpolation of model output to instrument locations, to name a few. In this presentation, we will introduce a formalism to quantify measurement uncertainty and spatial variability. The accuracy of this formalism will be tested using existing datasets such as the eXperimental Planetary boundary layer Instrumentation Assessment (XPIA) campaign. Finally, the uncertainties in wind measurement and the spatial variability estimates from the WFIP2 field campaign will be discussed to understand the challenges involved in model evaluation.

Systematic Evaluation of Uncertainty in Material Flow Analysis

DEFF Research Database (Denmark)

Laner, David; Rechberger, Helmut; Astrup, Thomas Fruergaard

2014-01-01

Material flow analysis (MFA) is a tool to investigate material flows and stocks in defined systems as a basis for resource management or environmental pollution control. Because of the diverse nature of sources and the varying quality and availability of data, MFA results are inherently uncertain....... Uncertainty analyses have received increasing attention in recent MFA studies, but systematic approaches for selection of appropriate uncertainty tools are missing. This article reviews existing literature related to handling of uncertainty in MFA studies and evaluates current practice of uncertainty analysis......) and exploratory MFA (identification of critical parameters and system behavior). Whereas mathematically simpler concepts focusing on data uncertainty characterization are appropriate for descriptive MFAs, statistical approaches enabling more-rigorous evaluation of uncertainty and model sensitivity are needed...

The use of multiwavelets for uncertainty estimation in seismic surface wave dispersion.

Energy Technology Data Exchange (ETDEWEB)

Poppeliers, Christian [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-12-01

This report describes a new single-station analysis method to estimate the dispersion and uncer- tainty of seismic surface waves using the multiwavelet transform. Typically, when estimating the dispersion of a surface wave using only a single seismic station, the seismogram is decomposed into a series of narrow-band realizations using a bank of narrow-band filters. By then enveloping and normalizing the filtered seismograms and identifying the maximum power as a function of frequency, the group velocity can be estimated if the source-receiver distance is known. However, using the filter bank method, there is no robust way to estimate uncertainty. In this report, I in- troduce a new method of estimating the group velocity that includes an estimate of uncertainty. The method is similar to the conventional filter bank method, but uses a class of functions, called Slepian wavelets, to compute a series of wavelet transforms of the data. Each wavelet transform is mathematically similar to a filter bank, however, the time-frequency tradeoff is optimized. By taking multiple wavelet transforms, I form a population of dispersion estimates from which stan- dard statistical methods can be used to estimate uncertainty. I demonstrate the utility of this new method by applying it to synthetic data as well as ambient-noise surface-wave cross-correlelograms recorded by the University of Nevada Seismic Network.

Uncertainties in Early-Stage Capital Cost Estimation of Process Design – A Case Study on Biorefinery Design

International Nuclear Information System (INIS)

Cheali, Peam; Gernaey, Krist V.; Sin, Gürkan

2015-01-01

Capital investment, next to the product demand, sales, and production costs, is one of the key metrics commonly used for project evaluation and feasibility assessment. Estimating the investment costs of a new product/process alternative during early-stage design is a challenging task, which is especially relevant in biorefinery research where information about new technologies and experience with new technologies is limited. A systematic methodology for uncertainty analysis of cost data is proposed that employs: (a) bootstrapping as a regression method when cost data are available; and, (b) the Monte Carlo technique as an error propagation method based on expert input when cost data are not available. Four well-known models for early-stage cost estimation are reviewed and analyzed using the methodology. The significance of uncertainties of cost data for early-stage process design is highlighted using the synthesis and design of a biorefinery as a case study. The impact of uncertainties in cost estimation on the identification of optimal processing paths is indeed found to be profound. To tackle this challenge, a comprehensive techno-economic risk analysis framework is presented to enable robust decision-making under uncertainties. One of the results using order-of-magnitude estimates shows that the production of diethyl ether and 1,3-butadiene are the most promising with the lowest economic risks (among the alternatives considered) of 0.24 MM$/a and 4.6 MM$/a, respectively.

Uncertainties in Early-Stage Capital Cost Estimation of Process Design – A Case Study on Biorefinery Design

Energy Technology Data Exchange (ETDEWEB)

Cheali, Peam; Gernaey, Krist V.; Sin, Gürkan, E-mail: gsi@kt.dtu.dk [Department of Chemical and Biochemical Engineering, Technical University of Denmark, Lyngby (Denmark)

2015-02-06

Capital investment, next to the product demand, sales, and production costs, is one of the key metrics commonly used for project evaluation and feasibility assessment. Estimating the investment costs of a new product/process alternative during early-stage design is a challenging task, which is especially relevant in biorefinery research where information about new technologies and experience with new technologies is limited. A systematic methodology for uncertainty analysis of cost data is proposed that employs: (a) bootstrapping as a regression method when cost data are available; and, (b) the Monte Carlo technique as an error propagation method based on expert input when cost data are not available. Four well-known models for early-stage cost estimation are reviewed and analyzed using the methodology. The significance of uncertainties of cost data for early-stage process design is highlighted using the synthesis and design of a biorefinery as a case study. The impact of uncertainties in cost estimation on the identification of optimal processing paths is indeed found to be profound. To tackle this challenge, a comprehensive techno-economic risk analysis framework is presented to enable robust decision-making under uncertainties. One of the results using order-of-magnitude estimates shows that the production of diethyl ether and 1,3-butadiene are the most promising with the lowest economic risks (among the alternatives considered) of 0.24 MM$/a and 4.6 MM$/a, respectively.

Uncertainties estimation in surveying measurands: application to lengths, perimeters and areas

Science.gov (United States)

Covián, E.; Puente, V.; Casero, M.

2017-10-01

The present paper develops a series of methods for the estimation of uncertainty when measuring certain measurands of interest in surveying practice, such as points elevation given a planimetric position within a triangle mesh, 2D and 3D lengths (including perimeters enclosures), 2D areas (horizontal surfaces) and 3D areas (natural surfaces). The basis for the proposed methodology is the law of propagation of variance-covariance, which, applied to the corresponding model for each measurand, allows calculating the resulting uncertainty from known measurement errors. The methods are tested first in a small example, with a limited number of measurement points, and then in two real-life measurements. In addition, the proposed methods have been incorporated to commercial software used in the field of surveying engineering and focused on the creation of digital terrain models. The aim of this evolution is, firstly, to comply with the guidelines of the BIPM (Bureau International des Poids et Mesures), as the international reference agency in the field of metrology, in relation to the determination and expression of uncertainty; and secondly, to improve the quality of the measurement by indicating the uncertainty associated with a given level of confidence. The conceptual and mathematical developments for the uncertainty estimation in the aforementioned cases were conducted by researchers from the AssIST group at the University of Oviedo, eventually resulting in several different mathematical algorithms implemented in the form of MATLAB code. Based on these prototypes, technicians incorporated the referred functionality to commercial software, developed in C++. As a result of this collaboration, in early 2016 a new version of this commercial software was made available, which will be the first, as far as the authors are aware, that incorporates the possibility of estimating the uncertainty for a given level of confidence when computing the aforementioned surveying

Evaluation of cutting force uncertainty components in turning

DEFF Research Database (Denmark)

Axinte, Dragos Aurelian; Belluco, Walter; De Chiffre, Leonardo

2000-01-01

A procedure is proposed for the evaluation of those uncertainty components of a single cutting force measurement in turning that are related to the contributions of the dynamometer calibration and the cutting process itself. Based on an empirical model including errors form both sources......, the uncertainty for a single measurement of cutting force is presented, and expressions for the expected uncertainty vs. cutting parameters are proposed. This approach gives the possibility of evaluating cutting force uncertainty components in turning, for a defined range of cutting parameters, based on few...

Uncertainty during breast diagnostic evaluation: state of the science.

Science.gov (United States)

Montgomery, Mariann

2010-01-01

To present the state of the science on uncertainty in relationship to the experiences of women undergoing diagnostic evaluation for suspected breast cancer. Published articles from Medline, CINAHL, PubMED, and PsycINFO from 1983-2008 using the following key words: breast biopsy, mammography, uncertainty, reframing, inner strength, and disruption. Fifty research studies were examined with all reporting the presence of anxiety persisting throughout the diagnostic evaluation until certitude is achieved through the establishment of a definitive diagnosis. Indirect determinants of uncertainty for women undergoing breast diagnostic evaluation include measures of anxiety, depression, social support, emotional responses, defense mechanisms, and the psychological impact of events. Understanding and influencing the uncertainty experience have been suggested to be key in relieving psychosocial distress and positively influencing future screening behaviors. Several studies examine correlational relationships among anxiety, selection of coping methods, and demographic factors that influence uncertainty. A gap exists in the literature with regard to the relationship of inner strength and uncertainty. Nurses can be invaluable in assisting women in coping with the uncertainty experience by providing positive communication and support. Nursing interventions should be designed and tested for their effects on uncertainty experienced by women undergoing a breast diagnostic evaluation.

Uncertainty evaluation in the chloroquine phosphate potentiometric titration: application of three different approaches.

Science.gov (United States)

Rodomonte, Andrea Luca; Montinaro, Annalisa; Bartolomei, Monica

2006-09-11

A measurement result cannot be properly interpreted if not accompanied by its uncertainty. Several methods to estimate uncertainty have been developed. From those methods three in particular were chosen in this work to estimate the uncertainty of the Eu. Ph. chloroquine phosphate assay, a potentiometric titration commonly used in medicinal control laboratories. The famous error-budget approach (also called bottom-up or step-by-step) described by the ISO Guide to the expression of Uncertainty in Measurement (GUM) was the first method chosen. It is based on the combination of uncertainty contributions that have to be directly derived from the measurement process. The second method employed was the Analytical Method Committee top-down which estimates uncertainty through reproducibility obtained during inter-laboratory studies. Data for its application were collected in a proficiency testing study carried out by over 50 laboratories throughout Europe. The last method chosen was the one proposed by Barwick and Ellison. It uses a combination of precision, trueness and ruggedness data to estimate uncertainty. These data were collected from a validation process specifically designed for uncertainty estimation. All the three approaches presented a distinctive set of advantages and drawbacks in their implementation. An expanded uncertainty of about 1% was assessed for the assay investigated.

An evaluation of uncertainties in radioecological models

International Nuclear Information System (INIS)

Hoffmann, F.O.; Little, C.A.; Miller, C.W.; Dunning, D.E. Jr.; Rupp, E.M.; Shor, R.W.; Schaeffer, D.L.; Baes, C.F. III

1978-01-01

The paper presents results of analyses for seven selected parameters commonly used in environmental radiological assessment models, assuming that the available data are representative of the true distribution of parameter values and that their respective distributions are lognormal. Estimates of the most probable, median, mean, and 99th percentile for each parameter are fiven and compared to U.S. NRC default values. The regulatory default values are generally greater than the median values for the selected parameters, but some are associated with percentiles significantly less than the 50th. The largest uncertainties appear to be associated with aquatic bioaccumulation factors for fresh water fish. Approximately one order of magnitude separates median values and values of the 99th percentile. The uncertainty is also estimated for the annual dose rate predicted by a multiplicative chain model for the transport of molecular iodine-131 via the air-pasture-cow-milk-child's thyroid pathway. The value for the 99th percentile is ten times larger than the median value of the predicted dose normalized for a given air concentration of 131 I 2 . About 72% of the uncertainty in this model is contributed by the dose conversion factor and the milk transfer coefficient. Considering the difficulties in obtaining a reliable quantification of the true uncertainties in model predictions, methods for taking these uncertainties into account when determining compliance with regulatory statutes are discussed. (orig./HP) [de

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.

Sampling of systematic errors to estimate likelihood weights in nuclear data uncertainty propagation

International Nuclear Information System (INIS)

Helgesson, P.; Sjöstrand, H.; Koning, A.J.; Rydén, J.; Rochman, D.; Alhassan, E.; Pomp, S.

2016-01-01

In methodologies for nuclear data (ND) uncertainty assessment and propagation based on random sampling, likelihood weights can be used to infer experimental information into the distributions for the ND. As the included number of correlated experimental points grows large, the computational time for the matrix inversion involved in obtaining the likelihood can become a practical problem. There are also other problems related to the conventional computation of the likelihood, e.g., the assumption that all experimental uncertainties are Gaussian. In this study, a way to estimate the likelihood which avoids matrix inversion is investigated; instead, the experimental correlations are included by sampling of systematic errors. It is shown that the model underlying the sampling methodology (using univariate normal distributions for random and systematic errors) implies a multivariate Gaussian for the experimental points (i.e., the conventional model). It is also shown that the likelihood estimates obtained through sampling of systematic errors approach the likelihood obtained with matrix inversion as the sample size for the systematic errors grows large. In studied practical cases, it is seen that the estimates for the likelihood weights converge impractically slowly with the sample size, compared to matrix inversion. The computational time is estimated to be greater than for matrix inversion in cases with more experimental points, too. Hence, the sampling of systematic errors has little potential to compete with matrix inversion in cases where the latter is applicable. Nevertheless, the underlying model and the likelihood estimates can be easier to intuitively interpret than the conventional model and the likelihood function involving the inverted covariance matrix. Therefore, this work can both have pedagogical value and be used to help motivating the conventional assumption of a multivariate Gaussian for experimental data. The sampling of systematic errors could also

Uncertainties Involved in the Iopospheric Conductivity Estimation

Directory of Open Access Journals (Sweden)

Young-Sil Kwak

2002-12-01

Full Text Available Various uncertainties involved in ionospheric conductivity estimation utilizing the electron density profile obtained from the Sondrestrom incoherent scatter radar are examined. First, we compare the conductivity which is based on raw electron density and the one based on corrected electron density that takes into account the effects of the difference between the electron and ion temperatures and the Debye length. The corrected electron density yields higher Pedersen and Hall conductivities than the raw electron density does. Second, the dependence of collision frequency model on the conductivity estimation is examined. Below 110 km conductivity does not depend significantly on collision frequency models. Above 110 km, however, the collision models affect the conductivity estimation. Third, the influence of the electron and ion temperatures on the conductivity estimation is examined. Electron and ion temperatures carrying an error of about 10% do not seem to affect significantly the conductivity estimation. Fourth, also examined is the effect of the choice of the altitude range of integration in calculating the height-integrated conductivity, conductance. It has been demonstrated that the lower and upper boundaries of the integration are quite sensitive to the estimation of the Hall and Pedersen conductances, respectively.

Added Value of uncertainty Estimates of SOurce term and Meteorology (AVESOME)

DEFF Research Database (Denmark)

Sørensen, Jens Havskov; Schönfeldt, Fredrik; Sigg, Robert

In the early phase of a nuclear accident, two large sources of uncertainty exist: one related to the source term and one associated with the meteorological data. Operational methods are being developed in AVESOME for quantitative estimation of uncertainties in atmospheric dispersion prediction.......g. at national meteorological services, the proposed methodology is feasible for real-time use, thereby adding value to decision support. In the recent NKS-B projects MUD, FAUNA and MESO, the implications of meteorological uncertainties for nuclear emergency preparedness and management have been studied...... uncertainty in atmospheric dispersion model forecasting stemming from both the source term and the meteorological data is examined. Ways to implement the uncertainties of forecasting in DSSs, and the impacts on real-time emergency management are described. The proposed methodology allows for efficient real...

Uncertainty estimation of the velocity model for the TrigNet GPS network

Science.gov (United States)

Hackl, Matthias; Malservisi, Rocco; Hugentobler, Urs; Wonnacott, Richard

2010-05-01

Satellite based geodetic techniques - above all GPS - provide an outstanding tool to measure crustal motions. They are widely used to derive geodetic velocity models that are applied in geodynamics to determine rotations of tectonic blocks, to localize active geological features, and to estimate rheological properties of the crust and the underlying asthenosphere. However, it is not a trivial task to derive GPS velocities and their uncertainties from positioning time series. In general time series are assumed to be represented by linear models (sometimes offsets, annual, and semi-annual signals are included) and noise. It has been shown that models accounting only for white noise tend to underestimate the uncertainties of rates derived from long time series and that different colored noise components (flicker noise, random walk, etc.) need to be considered. However, a thorough error analysis including power spectra analyses and maximum likelihood estimates is quite demanding and are usually not carried out for every site, but the uncertainties are scaled by latitude dependent factors. Analyses of the South Africa continuous GPS network TrigNet indicate that the scaled uncertainties overestimate the velocity errors. So we applied a method similar to the Allan Variance that is commonly used in the estimation of clock uncertainties and is able to account for time dependent probability density functions (colored noise) to the TrigNet time series. Finally, we compared these estimates to the results obtained by spectral analyses using CATS. Comparisons with synthetic data show that the noise can be represented quite well by a power law model in combination with a seasonal signal in agreement with previous studies.

Estimation and Uncertainty Analysis of Flammability Properties of Chemicals using Group-Contribution Property Models

DEFF Research Database (Denmark)

Frutiger, Jerome; Abildskov, Jens; Sin, Gürkan

Process safety studies and assessments rely on accurate property data. Flammability data like the lower and upper flammability limit (LFL and UFL) play an important role in quantifying the risk of fire and explosion. If experimental values are not available for the safety analysis due to cost...... or time constraints, property prediction models like group contribution (GC) models can estimate flammability data. The estimation needs to be accurate, reliable and as less time consuming as possible. However, GC property prediction methods frequently lack rigorous uncertainty analysis. Hence....... In this study, the MG-GC-factors are estimated using a systematic data and model evaluation methodology in the following way: 1) Data. Experimental flammability data is used from AIChE DIPPR 801 Database. 2) Initialization and sequential parameter estimation. An approximation using linear algebra provides...

Generalized Likelihood Uncertainty Estimation (GLUE) Using Multi-Optimization Algorithm as Sampling Method

Science.gov (United States)

Wang, Z.

2015-12-01

For decades, distributed and lumped hydrological models have furthered our understanding of hydrological system. The development of hydrological simulation in large scale and high precision elaborated the spatial descriptions and hydrological behaviors. Meanwhile, the new trend is also followed by the increment of model complexity and number of parameters, which brings new challenges of uncertainty quantification. Generalized Likelihood Uncertainty Estimation (GLUE) has been widely used in uncertainty analysis for hydrological models referring to Monte Carlo method coupled with Bayesian estimation. However, the stochastic sampling method of prior parameters adopted by GLUE appears inefficient, especially in high dimensional parameter space. The heuristic optimization algorithms utilizing iterative evolution show better convergence speed and optimality-searching performance. In light of the features of heuristic optimization algorithms, this study adopted genetic algorithm, differential evolution, shuffled complex evolving algorithm to search the parameter space and obtain the parameter sets of large likelihoods. Based on the multi-algorithm sampling, hydrological model uncertainty analysis is conducted by the typical GLUE framework. To demonstrate the superiority of the new method, two hydrological models of different complexity are examined. The results shows the adaptive method tends to be efficient in sampling and effective in uncertainty analysis, providing an alternative path for uncertainty quantilization.

Uncertainty estimates for predictions of the impact of breeder-reactor radionuclide releases

International Nuclear Information System (INIS)

Miller, C.W.; Little, C.A.

1982-01-01

This paper summarizes estimates, compiled in a larger report, of the uncertainty associated with models and parameters used to assess the impact on man radionuclide releases to the environment by breeder reactor facilities. These estimates indicate that, for many sites, generic models and representative parameter values may reasonably be used to calculate doses from annual average radionuclide releases when these calculated doses are on the order of one-tenth or less of a relevant dose limit. For short-term, accidental releases, the uncertainty in the dose calculations may be much larger than an order of magnitude. As a result, it may be necessary to incorporate site-specific information into the dose calculation under such circumstances. However, even using site-specific information, inherent natural variability within human receptors, and the uncertainties in the dose conversion factor will likely result in an overall uncertainty of greater than an order of magnitude for predictions of dose following short-term releases

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.

Eigenspace perturbations for structural uncertainty estimation of turbulence closure models

Science.gov (United States)

Jofre, Lluis; Mishra, Aashwin; Iaccarino, Gianluca

2017-11-01

With the present state of computational resources, a purely numerical resolution of turbulent flows encountered in engineering applications is not viable. Consequently, investigations into turbulence rely on various degrees of modeling. Archetypal amongst these variable resolution approaches would be RANS models in two-equation closures, and subgrid-scale models in LES. However, owing to the simplifications introduced during model formulation, the fidelity of all such models is limited, and therefore the explicit quantification of the predictive uncertainty is essential. In such scenario, the ideal uncertainty estimation procedure must be agnostic to modeling resolution, methodology, and the nature or level of the model filter. The procedure should be able to give reliable prediction intervals for different Quantities of Interest, over varied flows and flow conditions, and at diametric levels of modeling resolution. In this talk, we present and substantiate the Eigenspace perturbation framework as an uncertainty estimation paradigm that meets these criteria. Commencing from a broad overview, we outline the details of this framework at different modeling resolution. Thence, using benchmark flows, along with engineering problems, the efficacy of this procedure is established. This research was partially supported by NNSA under the Predictive Science Academic Alliance Program (PSAAP) II, and by DARPA under the Enabling Quantification of Uncertainty in Physical Systems (EQUiPS) project (technical monitor: Dr Fariba Fahroo).

Proficiency testing as a basis for estimating uncertainty of measurement: application to forensic alcohol and toxicology quantitations.

Science.gov (United States)

Wallace, Jack

2010-05-01

While forensic laboratories will soon be required to estimate uncertainties of measurement for those quantitations reported to the end users of the information, the procedures for estimating this have been little discussed in the forensic literature. This article illustrates how proficiency test results provide the basis for estimating uncertainties in three instances: (i) For breath alcohol analyzers the interlaboratory precision is taken as a direct measure of uncertainty. This approach applies when the number of proficiency tests is small. (ii) For blood alcohol, the uncertainty is calculated from the differences between the laboratory's proficiency testing results and the mean quantitations determined by the participants; this approach applies when the laboratory has participated in a large number of tests. (iii) For toxicology, either of these approaches is useful for estimating comparability between laboratories, but not for estimating absolute accuracy. It is seen that data from proficiency tests enable estimates of uncertainty that are empirical, simple, thorough, and applicable to a wide range of concentrations.

Estimating and managing uncertainties in order to detect terrestrial greenhouse gas removals

International Nuclear Information System (INIS)

Rypdal, Kristin; Baritz, Rainer

2002-01-01

Inventories of emissions and removals of greenhouse gases will be used under the United Nations Framework Convention on Climate Change and the Kyoto Protocol to demonstrate compliance with obligations. During the negotiation process of the Kyoto Protocol it has been a concern that uptake of carbon in forest sinks can be difficult to verify. The reason for large uncertainties are high temporal and spatial variability and lack of representative estimation parameters. Additional uncertainties will be a consequence of definitions made in the Kyoto Protocol reporting. In the Nordic countries the national forest inventories will be very useful to estimate changes in carbon stocks. The main uncertainty lies in the conversion from changes in tradable timber to changes in total carbon biomass. The uncertainties in the emissions of the non-CO 2 carbon from forest soils are particularly high. On the other hand the removals reported under the Kyoto Protocol will only be a fraction of the total uptake and are not expected to constitute a high share of the total inventory. It is also expected that the Nordic countries will be able to implement a high tier methodology. As a consequence total uncertainties may not be extremely high. (Author)

Estimating uncertainty in subsurface glider position using transmissions from fixed acoustic tomography sources.

Science.gov (United States)

Van Uffelen, Lora J; Nosal, Eva-Marie; Howe, Bruce M; Carter, Glenn S; Worcester, Peter F; Dzieciuch, Matthew A; Heaney, Kevin D; Campbell, Richard L; Cross, Patrick S

2013-10-01

Four acoustic Seagliders were deployed in the Philippine Sea November 2010 to April 2011 in the vicinity of an acoustic tomography array. The gliders recorded over 2000 broadband transmissions at ranges up to 700 km from moored acoustic sources as they transited between mooring sites. The precision of glider positioning at the time of acoustic reception is important to resolve the fundamental ambiguity between position and sound speed. The Seagliders utilized GPS at the surface and a kinematic model below for positioning. The gliders were typically underwater for about 6.4 h, diving to depths of 1000 m and traveling on average 3.6 km during a dive. Measured acoustic arrival peaks were unambiguously associated with predicted ray arrivals. Statistics of travel-time offsets between received arrivals and acoustic predictions were used to estimate range uncertainty. Range (travel time) uncertainty between the source and the glider position from the kinematic model is estimated to be 639 m (426 ms) rms. Least-squares solutions for glider position estimated from acoustically derived ranges from 5 sources differed by 914 m rms from modeled positions, with estimated uncertainty of 106 m rms in horizontal position. Error analysis included 70 ms rms of uncertainty due to oceanic sound-speed variability.

Improved linear least squares estimation using bounded data uncertainty

KAUST Repository

Ballal, Tarig

2015-04-01

This paper addresses the problemof linear least squares (LS) estimation of a vector x from linearly related observations. In spite of being unbiased, the original LS estimator suffers from high mean squared error, especially at low signal-to-noise ratios. The mean squared error (MSE) of the LS estimator can be improved by introducing some form of regularization based on certain constraints. We propose an improved LS (ILS) estimator that approximately minimizes the MSE, without imposing any constraints. To achieve this, we allow for perturbation in the measurement matrix. Then we utilize a bounded data uncertainty (BDU) framework to derive a simple iterative procedure to estimate the regularization parameter. Numerical results demonstrate that the proposed BDU-ILS estimator is superior to the original LS estimator, and it converges to the best linear estimator, the linear-minimum-mean-squared error estimator (LMMSE), when the elements of x are statistically white.

Improved linear least squares estimation using bounded data uncertainty

KAUST Repository

Ballal, Tarig; Al-Naffouri, Tareq Y.

2015-01-01

This paper addresses the problemof linear least squares (LS) estimation of a vector x from linearly related observations. In spite of being unbiased, the original LS estimator suffers from high mean squared error, especially at low signal-to-noise ratios. The mean squared error (MSE) of the LS estimator can be improved by introducing some form of regularization based on certain constraints. We propose an improved LS (ILS) estimator that approximately minimizes the MSE, without imposing any constraints. To achieve this, we allow for perturbation in the measurement matrix. Then we utilize a bounded data uncertainty (BDU) framework to derive a simple iterative procedure to estimate the regularization parameter. Numerical results demonstrate that the proposed BDU-ILS estimator is superior to the original LS estimator, and it converges to the best linear estimator, the linear-minimum-mean-squared error estimator (LMMSE), when the elements of x are statistically white.

Uncertainty estimation of core safety parameters using cross-correlations of covariance matrix

International Nuclear Information System (INIS)

Yamamoto, Akio; Yasue, Yoshihiro; Endo, Tomohiro; Kodama, Yasuhiro; Ohoka, Yasunori; Tatsumi, Masahiro

2013-01-01

An uncertainty reduction method for core safety parameters, for which measurement values are not obtained, is proposed. We empirically recognize that there exist some correlations among the prediction errors of core safety parameters, e.g., a correlation between the control rod worth and the assembly relative power at corresponding position. Correlations of errors among core safety parameters are theoretically estimated using the covariance of cross sections and sensitivity coefficients of core parameters. The estimated correlations of errors among core safety parameters are verified through the direct Monte Carlo sampling method. Once the correlation of errors among core safety parameters is known, we can estimate the uncertainty of a safety parameter for which measurement value is not obtained. (author)

Comprehensive analysis of proton range uncertainties related to patient stopping-power-ratio estimation using the stoichiometric calibration

Science.gov (United States)

Yang, Ming; Zhu, X. Ronald; Park, Peter C.; Titt, Uwe; Mohan, Radhe; Virshup, Gary; Clayton, James E.; Dong, Lei

2012-07-01

The purpose of this study was to analyze factors affecting proton stopping-power-ratio (SPR) estimations and range uncertainties in proton therapy planning using the standard stoichiometric calibration. The SPR uncertainties were grouped into five categories according to their origins and then estimated based on previously published reports or measurements. For the first time, the impact of tissue composition variations on SPR estimation was assessed and the uncertainty estimates of each category were determined for low-density (lung), soft, and high-density (bone) tissues. A composite, 95th percentile water-equivalent-thickness uncertainty was calculated from multiple beam directions in 15 patients with various types of cancer undergoing proton therapy. The SPR uncertainties (1σ) were quite different (ranging from 1.6% to 5.0%) in different tissue groups, although the final combined uncertainty (95th percentile) for different treatment sites was fairly consistent at 3.0-3.4%, primarily because soft tissue is the dominant tissue type in the human body. The dominant contributing factor for uncertainties in soft tissues was the degeneracy of Hounsfield numbers in the presence of tissue composition variations. To reduce the overall uncertainties in SPR estimation, the use of dual-energy computed tomography is suggested. The values recommended in this study based on typical treatment sites and a small group of patients roughly agree with the commonly referenced value (3.5%) used for margin design. By using tissue-specific range uncertainties, one could estimate the beam-specific range margin by accounting for different types and amounts of tissues along a beam, which may allow for customization of range uncertainty for each beam direction.

Uncertainty analysis for results of thermal hydraulic codes of best-estimate-type

International Nuclear Information System (INIS)

Alva N, J.

2010-01-01

In this thesis, some fundamental knowledge is presented about uncertainty analysis and about diverse methodologies applied in the study of nuclear power plant transient event analysis, particularly related to thermal hydraulics phenomena. These concepts and methodologies mentioned in this work come from a wide bibliographical research in the nuclear power subject. Methodologies for uncertainty analysis have been developed by quite diverse institutions, and they have been widely used worldwide for application to results from best-estimate-type computer codes in nuclear reactor thermal hydraulics and safety analysis. Also, the main uncertainty sources, types of uncertainties, and aspects related to best estimate modeling and methods are introduced. Once the main bases of uncertainty analysis have been set, and some of the known methodologies have been introduced, it is presented in detail the CSAU methodology, which will be applied in the analyses. The main objective of this thesis is to compare the results of an uncertainty and sensibility analysis by using the Response Surface Technique to the application of W ilks formula, apply through a loss coolant experiment and an event of rise in a BWR. Both techniques are options in the part of uncertainty and sensibility analysis of the CSAU methodology, which was developed for the analysis of transients and accidents at nuclear power plants, and it is the base of most of the methodologies used in licensing of nuclear power plants practically everywhere. Finally, the results of applying both techniques are compared and discussed. (Author)

Some sources of the underestimation of evaluated cross section uncertainties

International Nuclear Information System (INIS)

Badikov, S.A.; Gai, E.V.

2003-01-01

The problem of the underestimation of evaluated cross-section uncertainties is addressed. Two basic sources of the underestimation of evaluated cross-section uncertainties - a) inconsistency between declared and observable experimental uncertainties and b) inadequacy between applied statistical models and processed experimental data - are considered. Both the sources of the underestimation are mainly a consequence of existence of the uncertainties unrecognized by experimenters. A model of a 'constant shift' is proposed for taking unrecognised experimental uncertainties into account. The model is applied for statistical analysis of the 238 U(n,f)/ 235 U(n,f) reaction cross-section ratio measurements. It is demonstrated that multiplication by sqrt(χ 2 ) as instrument for correction of underestimated evaluated cross-section uncertainties fails in case of correlated measurements. It is shown that arbitrary assignment of uncertainties and correlation in a simple least squares fit of two correlated measurements of unknown mean leads to physically incorrect evaluated results. (author)

Quantifying uncertainties in the estimation of safety parameters by using bootstrapped artificial neural networks

Energy Technology Data Exchange (ETDEWEB)

Secchi, Piercesare [MOX, Department of Mathematics, Polytechnic of Milan (Italy); Zio, Enrico [Department of Energy, Polytechnic of Milan, Via Ponzio 34/3, 20133 Milano (Italy)], E-mail: enrico.zio@polimi.it; Di Maio, Francesco [Department of Energy, Polytechnic of Milan, Via Ponzio 34/3, 20133 Milano (Italy)

2008-12-15

For licensing purposes, safety cases of Nuclear Power Plants (NPPs) must be presented at the Regulatory Authority with the necessary confidence on the models used to describe the plant safety behavior. In principle, this requires the repetition of a large number of model runs to account for the uncertainties inherent in the model description of the true plant behavior. The present paper propounds the use of bootstrapped Artificial Neural Networks (ANNs) for performing the numerous model output calculations needed for estimating safety margins with appropriate confidence intervals. Account is given both to the uncertainties inherent in the plant model and to those introduced by the ANN regression models used for performing the repeated safety parameter evaluations. The proposed framework of analysis is first illustrated with reference to a simple analytical model and then to the estimation of the safety margin on the maximum fuel cladding temperature reached during a complete group distribution header blockage scenario in a RBMK-1500 nuclear reactor. The results are compared with those obtained by a traditional parametric approach.

Uncertainty Evaluation for SMART Synthesized Power Distribution

International Nuclear Information System (INIS)

Cho, J. Y.; Song, J. S.; Lee, C. C.; Park, S. Y.; Kim, K. Y.; Lee, K. H.

2010-07-01

This report performs the uncertainty analysis for the SMART synthesis power distribution generated by a SSUN (SMART core SUpporting system coupled by Nuclear design code) code. SSUN runs coupled with the MASTER neutronics code and generates the core 3-D synthesis power distribution by using DPCM3D. The MASTER code plays a role to provide the DPCM3D constants to the SSUN code for the current core states. The uncertainties evaluated in this report are the form of 95%/95% probability/confidence one-sided tolerance limits and can be used in conjunction with Technical Specification limits on these quantities to establish appropriate LCO (Limiting Conditions of Operation) and LSSS (Limiting Safety System Settings) limits. This report is applicable to SMART nuclear reactor using fixed rhodium detector systems. The unknown true power distribution should be given for the uncertainty evaluation of the synthesis power distribution. This report produces virtual distributions for the true power distribution by imposing the CASMO-3/MASTER uncertainty to the MASTER power distribution. Detector signals are generated from these virtual distribution and the DPCM3D constants are from the MASTER power distribution. The SSUN code synthesizes the core 3-D power distribution by using these detector signals and the DPCM3D constants. The following summarizes the uncertainty evaluation procedure for the synthesis power distribution. (1) Generation of 3-D power distribution by MASTER -> Determination of the DPCM3D constants. (2) Generation of virtual power distribution (assumed to be true power distribution) -> Generation of detector signals. (3) Generation of synthesis power distribution. (4) Uncertainty evaluation for the synthesis power distribution. Chi-Square normality test rejects the hypothesis of normal distribution for the synthesis power error distribution. Therefore, the KRUSKAL WALLIS test and the non-parametric statistics are used for data pooling and the tolerance limits. The

THE STOCKS ACCOUNTING EVALUATION AND ESTIMATION INFLUENCE ON THE ENTITY PERFORMANCE

Directory of Open Access Journals (Sweden)

TULVINSCHI MIHAELA

2015-12-01

Full Text Available Improving the performance of a company involves an operative and accurate measurement of the efforts and effects, the efficient use of the company resources and also identifying ways to reduce consumption, a category in which stocks occupy a significant position. The purpose of this article is to demonstrate that the accounting information on stocks can not rely only on the accuracy assessment of past and current events, but must take into account estimations of future events, even if these involve uncertainty and risk taking. Different methods for evaluating stocks at the exit of the entity lead to different results but does not affect the entity performance. Opposed to the evaluation, when we speak about the accounting estimation, there is a significant freedom of action when choosing methods. The economic entity is always in the present, and for this reason it must take into consideration both the evaluation accuracy and the accounting estimations uncertainty. Estimating the net achievable value is influenced by the purpose for which the inventory is held. Accounting estimations are influenced by the judgment which is sometimes subjected to inherent bias, but this bias should not turn into a form of manipulating the entity's performance.

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

Incorporating uncertainty analysis into life cycle estimates of greenhouse gas emissions from biomass production

International Nuclear Information System (INIS)

Johnson, David R.; Willis, Henry H.; Curtright, Aimee E.; Samaras, Constantine; Skone, Timothy

2011-01-01

Before further investments are made in utilizing biomass as a source of renewable energy, both policy makers and the energy industry need estimates of the net greenhouse gas (GHG) reductions expected from substituting biobased fuels for fossil fuels. Such GHG reductions depend greatly on how the biomass is cultivated, transported, processed, and converted into fuel or electricity. Any policy aiming to reduce GHGs with biomass-based energy must account for uncertainties in emissions at each stage of production, or else it risks yielding marginal reductions, if any, while potentially imposing great costs. This paper provides a framework for incorporating uncertainty analysis specifically into estimates of the life cycle GHG emissions from the production of biomass. We outline the sources of uncertainty, discuss the implications of uncertainty and variability on the limits of life cycle assessment (LCA) models, and provide a guide for practitioners to best practices in modeling these uncertainties. The suite of techniques described herein can be used to improve the understanding and the representation of the uncertainties associated with emissions estimates, thus enabling improved decision making with respect to the use of biomass for energy and fuel production. -- Highlights: → We describe key model, scenario and data uncertainties in LCAs of biobased fuels. → System boundaries and allocation choices should be consistent with study goals. → Scenarios should be designed around policy levers that can be controlled. → We describe a new way to analyze the importance of covariance between inputs.

Estimating and managing uncertainties in order to detect terrestrial greenhouse gas removals

Energy Technology Data Exchange (ETDEWEB)

Rypdal, Kristin; Baritz, Rainer

2002-07-01

Inventories of emissions and removals of greenhouse gases will be used under the United Nations Framework Convention on Climate Change and the Kyoto Protocol to demonstrate compliance with obligations. During the negotiation process of the Kyoto Protocol it has been a concern that uptake of carbon in forest sinks can be difficult to verify. The reason for large uncertainties are high temporal and spatial variability and lack of representative estimation parameters. Additional uncertainties will be a consequence of definitions made in the Kyoto Protocol reporting. In the Nordic countries the national forest inventories will be very useful to estimate changes in carbon stocks. The main uncertainty lies in the conversion from changes in tradable timber to changes in total carbon biomass. The uncertainties in the emissions of the non-CO{sub 2} carbon from forest soils are particularly high. On the other hand the removals reported under the Kyoto Protocol will only be a fraction of the total uptake and are not expected to constitute a high share of the total inventory. It is also expected that the Nordic countries will be able to implement a high tier methodology. As a consequence total uncertainties may not be extremely high. (Author)

Uncertainty of chromatic dispersion estimation from transmitted waveforms in direct detection systems

Science.gov (United States)

Lach, Zbigniew T.

2017-08-01

A possibility is shown of a non-disruptive estimation of chromatic dispersion in a fiber of an intensity modulation communication line under work conditions. Uncertainty of the chromatic dispersion estimates is analyzed and quantified with the use of confidence intervals.

Linear minimax estimation for random vectors with parametric uncertainty

KAUST Repository

Bitar, E

2010-06-01

In this paper, we take a minimax approach to the problem of computing a worst-case linear mean squared error (MSE) estimate of X given Y , where X and Y are jointly distributed random vectors with parametric uncertainty in their distribution. We consider two uncertainty models, PA and PB. Model PA represents X and Y as jointly Gaussian whose covariance matrix Λ belongs to the convex hull of a set of m known covariance matrices. Model PB characterizes X and Y as jointly distributed according to a Gaussian mixture model with m known zero-mean components, but unknown component weights. We show: (a) the linear minimax estimator computed under model PA is identical to that computed under model PB when the vertices of the uncertain covariance set in PA are the same as the component covariances in model PB, and (b) the problem of computing the linear minimax estimator under either model reduces to a semidefinite program (SDP). We also consider the dynamic situation where x(t) and y(t) evolve according to a discrete-time LTI state space model driven by white noise, the statistics of which is modeled by PA and PB as before. We derive a recursive linear minimax filter for x(t) given y(t).

Statistical characterization of roughness uncertainty and impact on wind resource estimation

Directory of Open Access Journals (Sweden)

M. Kelly

2017-04-01

Full Text Available In this work we relate uncertainty in background roughness length (z0 to uncertainty in wind speeds, where the latter are predicted at a wind farm location based on wind statistics observed at a different site. Sensitivity of predicted winds to roughness is derived analytically for the industry-standard European Wind Atlas method, which is based on the geostrophic drag law. We statistically consider roughness and its corresponding uncertainty, in terms of both z0 derived from measured wind speeds as well as that chosen in practice by wind engineers. We show the combined effect of roughness uncertainty arising from differing wind-observation and turbine-prediction sites; this is done for the case of roughness bias as well as for the general case. For estimation of uncertainty in annual energy production (AEP, we also develop a generalized analytical turbine power curve, from which we derive a relation between mean wind speed and AEP. Following our developments, we provide guidance on approximate roughness uncertainty magnitudes to be expected in industry practice, and we also find that sites with larger background roughness incur relatively larger uncertainties.

Achieving 95% probability level using best estimate codes and the code scaling, applicability and uncertainty (CSAU) [Code Scaling, Applicability and Uncertainty] methodology

International Nuclear Information System (INIS)

Wilson, G.E.; Boyack, B.E.; Duffey, R.B.; Griffith, P.; Katsma, K.R.; Lellouche, G.S.; Rohatgi, U.S.; Wulff, W.; Zuber, N.

1988-01-01

Issue of a revised rule for loss of coolant accident/emergency core cooling system (LOCA/ECCS) analysis of light water reactors will allow the use of best estimate (BE) computer codes in safety analysis, with uncertainty analysis. This paper describes a systematic methodology, CSAU (Code Scaling, Applicability and Uncertainty), which will provide uncertainty bounds in a cost effective, auditable, rational and practical manner. 8 figs., 2 tabs

Uncertainties in the Item Parameter Estimates and Robust Automated Test Assembly

Science.gov (United States)

Veldkamp, Bernard P.; Matteucci, Mariagiulia; de Jong, Martijn G.

2013-01-01

Item response theory parameters have to be estimated, and because of the estimation process, they do have uncertainty in them. In most large-scale testing programs, the parameters are stored in item banks, and automated test assembly algorithms are applied to assemble operational test forms. These algorithms treat item parameters as fixed values,…

Uncertainty estimation of a complex water quality model: The influence of Box-Cox transformation on Bayesian approaches and comparison with a non-Bayesian method

Science.gov (United States)

Freni, Gabriele; Mannina, Giorgio

In urban drainage modelling, uncertainty analysis is of undoubted necessity. However, uncertainty analysis in urban water-quality modelling is still in its infancy and only few studies have been carried out. Therefore, several methodological aspects still need to be experienced and clarified especially regarding water quality modelling. The use of the Bayesian approach for uncertainty analysis has been stimulated by its rigorous theoretical framework and by the possibility of evaluating the impact of new knowledge on the modelling predictions. Nevertheless, the Bayesian approach relies on some restrictive hypotheses that are not present in less formal methods like the Generalised Likelihood Uncertainty Estimation (GLUE). One crucial point in the application of Bayesian method is the formulation of a likelihood function that is conditioned by the hypotheses made regarding model residuals. Statistical transformations, such as the use of Box-Cox equation, are generally used to ensure the homoscedasticity of residuals. However, this practice may affect the reliability of the analysis leading to a wrong uncertainty estimation. The present paper aims to explore the influence of the Box-Cox equation for environmental water quality models. To this end, five cases were considered one of which was the “real” residuals distributions (i.e. drawn from available data). The analysis was applied to the Nocella experimental catchment (Italy) which is an agricultural and semi-urbanised basin where two sewer systems, two wastewater treatment plants and a river reach were monitored during both dry and wet weather periods. The results show that the uncertainty estimation is greatly affected by residual transformation and a wrong assumption may also affect the evaluation of model uncertainty. The use of less formal methods always provide an overestimation of modelling uncertainty with respect to Bayesian method but such effect is reduced if a wrong assumption is made regarding the

Implementation of unscented transform to estimate the uncertainty of a liquid flow standard system

Energy Technology Data Exchange (ETDEWEB)

Chun, Sejong; Choi, Hae-Man; Yoon, Byung-Ro; Kang, Woong [Korea Research Institute of Standards and Science, Daejeon (Korea, Republic of)

2017-03-15

First-order partial derivatives of a mathematical model are an essential part of evaluating the measurement uncertainty of a liquid flow standard system according to the Guide to the expression of uncertainty in measurement (GUM). Although the GUM provides a straightforward method to evaluate the measurement uncertainty of volume flow rate, the first-order partial derivatives can be complicated. The mathematical model of volume flow rate in a liquid flow standard system has a cross-correlation between liquid density and buoyancy correction factor. This cross-correlation can make derivation of the first-order partial derivatives difficult. Monte Carlo simulation can be used as an alternative method to circumvent the difficulty in partial derivation. However, the Monte Carlo simulation requires large computational resources for a correct simulation because it considers the completeness issue whether an ideal or a real operator conducts an experiment to evaluate the measurement uncertainty. Thus, the Monte Carlo simulation needs a large number of samples to ensure that the uncertainty evaluation is as close to the GUM as possible. Unscented transform can alleviate this problem because unscented transform can be regarded as a Monte Carlo simulation with an infinite number of samples. This idea means that unscented transform considers the uncertainty evaluation with respect to the ideal operator. Thus, unscented transform can evaluate the measurement uncertainty the same as the uncertainty that the GUM provides.

A super-resolution approach for uncertainty estimation of PIV measurements

NARCIS (Netherlands)

Sciacchitano, A.; Wieneke, B.; Scarano, F.

2012-01-01

A super-resolution approach is proposed for the a posteriori uncertainty estimation of PIV measurements. The measured velocity field is employed to determine the displacement of individual particle images. A disparity set is built from the residual distance between paired particle images of

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.

Impact of Hydrogeological Uncertainty on Estimation of Environmental Risks Posed by Hydrocarbon Transportation Networks

Science.gov (United States)

Ciriello, V.; Lauriola, I.; Bonvicini, S.; Cozzani, V.; Di Federico, V.; Tartakovsky, Daniel M.

2017-11-01

Ubiquitous hydrogeological uncertainty undermines the veracity of quantitative predictions of soil and groundwater contamination due to accidental hydrocarbon spills from onshore pipelines. Such predictions, therefore, must be accompanied by quantification of predictive uncertainty, especially when they are used for environmental risk assessment. We quantify the impact of parametric uncertainty on quantitative forecasting of temporal evolution of two key risk indices, volumes of unsaturated and saturated soil contaminated by a surface spill of light nonaqueous-phase liquids. This is accomplished by treating the relevant uncertain parameters as random variables and deploying two alternative probabilistic models to estimate their effect on predictive uncertainty. A physics-based model is solved with a stochastic collocation method and is supplemented by a global sensitivity analysis. A second model represents the quantities of interest as polynomials of random inputs and has a virtually negligible computational cost, which enables one to explore any number of risk-related contamination scenarios. For a typical oil-spill scenario, our method can be used to identify key flow and transport parameters affecting the risk indices, to elucidate texture-dependent behavior of different soils, and to evaluate, with a degree of confidence specified by the decision-maker, the extent of contamination and the correspondent remediation costs.

Evaluating uncertainty in 7Be-based soil erosion estimates: an experimental plot approach

Science.gov (United States)

Blake, Will; Taylor, Alex; Abdelli, Wahid; Gaspar, Leticia; Barri, Bashar Al; Ryken, Nick; Mabit, Lionel

2014-05-01

Soil erosion remains a major concern for the international community and there is a growing need to improve the sustainability of agriculture to support future food security. High resolution soil erosion data are a fundamental requirement for underpinning soil conservation and management strategies but representative data on soil erosion rates are difficult to achieve by conventional means without interfering with farming practice and hence compromising the representativeness of results. Fallout radionuclide (FRN) tracer technology offers a solution since FRN tracers are delivered to the soil surface by natural processes and, where irreversible binding can be demonstrated, redistributed in association with soil particles. While much work has demonstrated the potential of short-lived 7Be (half-life 53 days), particularly in quantification of short-term inter-rill erosion, less attention has focussed on sources of uncertainty in derived erosion measurements and sampling strategies to minimise these. This poster outlines and discusses potential sources of uncertainty in 7Be-based soil erosion estimates and the experimental design considerations taken to quantify these in the context of a plot-scale validation experiment. Traditionally, gamma counting statistics have been the main element of uncertainty propagated and reported but recent work has shown that other factors may be more important such as: (i) spatial variability in the relaxation mass depth that describes the shape of the 7Be depth distribution for an uneroded point; (ii) spatial variability in fallout (linked to rainfall patterns and shadowing) over both reference site and plot; (iii) particle size sorting effects; (iv) preferential mobility of fallout over active runoff contributing areas. To explore these aspects in more detail, a plot of 4 x 35 m was ploughed and tilled to create a bare, sloped soil surface at the beginning of winter 2013/2014 in southwest UK. The lower edge of the plot was bounded by

Evaluating Variability and Uncertainty of Geological Strength Index at a Specific Site

Science.gov (United States)

Wang, Yu; Aladejare, Adeyemi Emman

2016-09-01

Geological Strength Index (GSI) is an important parameter for estimating rock mass properties. GSI can be estimated from quantitative GSI chart, as an alternative to the direct observational method which requires vast geological experience of rock. GSI chart was developed from past observations and engineering experience, with either empiricism or some theoretical simplifications. The GSI chart thereby contains model uncertainty which arises from its development. The presence of such model uncertainty affects the GSI estimated from GSI chart at a specific site; it is, therefore, imperative to quantify and incorporate the model uncertainty during GSI estimation from the GSI chart. A major challenge for quantifying the GSI chart model uncertainty is a lack of the original datasets that have been used to develop the GSI chart, since the GSI chart was developed from past experience without referring to specific datasets. This paper intends to tackle this problem by developing a Bayesian approach for quantifying the model uncertainty in GSI chart when using it to estimate GSI at a specific site. The model uncertainty in the GSI chart and the inherent spatial variability in GSI are modeled explicitly in the Bayesian approach. The Bayesian approach generates equivalent samples of GSI from the integrated knowledge of GSI chart, prior knowledge and observation data available from site investigation. Equations are derived for the Bayesian approach, and the proposed approach is illustrated using data from a drill and blast tunnel project. The proposed approach effectively tackles the problem of how to quantify the model uncertainty that arises from using GSI chart for characterization of site-specific GSI in a transparent manner.

Comparison of two perturbation methods to estimate the land surface modeling uncertainty

Science.gov (United States)

Su, H.; Houser, P.; Tian, Y.; Kumar, S.; Geiger, J.; Belvedere, D.

2007-12-01

In land surface modeling, it is almost impossible to simulate the land surface processes without any error because the earth system is highly complex and the physics of the land processes has not yet been understood sufficiently. In most cases, people want to know not only the model output but also the uncertainty in the modeling, to estimate how reliable the modeling is. Ensemble perturbation is an effective way to estimate the uncertainty in land surface modeling, since land surface models are highly nonlinear which makes the analytical approach not applicable in this estimation. The ideal perturbation noise is zero mean Gaussian distribution, however, this requirement can't be satisfied if the perturbed variables in land surface model have physical boundaries because part of the perturbation noises has to be removed to feed the land surface models properly. Two different perturbation methods are employed in our study to investigate their impact on quantifying land surface modeling uncertainty base on the Land Information System (LIS) framework developed by NASA/GSFC land team. One perturbation method is the built-in algorithm named "STATIC" in LIS version 5; the other is a new perturbation algorithm which was recently developed to minimize the overall bias in the perturbation by incorporating additional information from the whole time series for the perturbed variable. The statistical properties of the perturbation noise generated by the two different algorithms are investigated thoroughly by using a large ensemble size on a NASA supercomputer and then the corresponding uncertainty estimates based on the two perturbation methods are compared. Their further impacts on data assimilation are also discussed. Finally, an optimal perturbation method is suggested.

Estimating the Accuracy of the Return on Investment (ROI Performance Evaluations

Directory of Open Access Journals (Sweden)

Alexei Botchkarev

2015-12-01

Full Text Available Return on Investment (ROI is one of the most popular performance measurement and evaluation metrics. ROI analysis (when applied correctly is a powerful tool in comparing solutions and making informed decisions on the acquisitions of information systems. The purpose of this study is to provide a systematic research of the accuracy of the ROI evaluations in the context of information systems implementations. Measurements theory and error analysis, specifically propagation of uncertainties methods, were used to derive analytical expressions for ROI errors. Monte Carlo simulation methodology was used to design and deliver a quantitative experiment to model costs and returns estimating errors and calculate ROI accuracies. Spreadsheet simulation (Microsoft Excel spreadsheets enhanced with Visual Basic for Applications was used to implement Monte Carlo simulations. The main contribution of the study is that this is the first systematic effort to evaluate ROI accuracy. Analytical expressions have been derived for estimating errors of the ROI evaluations. Results of the Monte Carlo simulation will help practitioners in making informed decisions based on explicitly stated factors influencing the ROI uncertainties.

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

Science.gov (United States)

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

2018-01-01

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

A Best-Estimate Reactor Core Monitor Using State Feedback Strategies to Reduce Uncertainties

International Nuclear Information System (INIS)

Martin, Robert P.; Edwards, Robert M.

2000-01-01

The development and demonstration of a new algorithm to reduce modeling and state-estimation uncertainty in best-estimate simulation codes has been investigated. Demonstration is given by way of a prototype reactor core monitor. The architecture of this monitor integrates a control-theory-based, distributed-parameter estimation technique into a production-grade best-estimate simulation code. The Kalman Filter-Sequential Least-Squares (KFSLS) parameter estimation algorithm has been extended for application into the computational environment of the best-estimate simulation code RELAP5-3D. In control system terminology, this configuration can be thought of as a 'best-estimate' observer. The application to a distributed-parameter reactor system involves a unique modal model that approximates physical components, such as the reactor, by describing both states and parameters by an orthogonal expansion. The basic KFSLS parameter estimation is used to dynamically refine a spatially varying (distributed) parameter. The application of the distributed-parameter estimator is expected to complement a traditional nonlinear best-estimate simulation code by providing a mechanism for reducing both code input (modeling) and output (state-estimation) uncertainty in complex, distributed-parameter systems

Estimation of sampling error uncertainties in observed surface air temperature change in China

Science.gov (United States)

Hua, Wei; Shen, Samuel S. P.; Weithmann, Alexander; Wang, Huijun

2017-08-01

This study examines the sampling error uncertainties in the monthly surface air temperature (SAT) change in China over recent decades, focusing on the uncertainties of gridded data, national averages, and linear trends. Results indicate that large sampling error variances appear at the station-sparse area of northern and western China with the maximum value exceeding 2.0 K2 while small sampling error variances are found at the station-dense area of southern and eastern China with most grid values being less than 0.05 K2. In general, the negative temperature existed in each month prior to the 1980s, and a warming in temperature began thereafter, which accelerated in the early and mid-1990s. The increasing trend in the SAT series was observed for each month of the year with the largest temperature increase and highest uncertainty of 0.51 ± 0.29 K (10 year)-1 occurring in February and the weakest trend and smallest uncertainty of 0.13 ± 0.07 K (10 year)-1 in August. The sampling error uncertainties in the national average annual mean SAT series are not sufficiently large to alter the conclusion of the persistent warming in China. In addition, the sampling error uncertainties in the SAT series show a clear variation compared with other uncertainty estimation methods, which is a plausible reason for the inconsistent variations between our estimate and other studies during this period.

Uncertainty in BMP evaluation and optimization for watershed management

Science.gov (United States)

Chaubey, I.; Cibin, R.; Sudheer, K.; Her, Y.

2012-12-01

Use of computer simulation models have increased substantially to make watershed management decisions and to develop strategies for water quality improvements. These models are often used to evaluate potential benefits of various best management practices (BMPs) for reducing losses of pollutants from sources areas into receiving waterbodies. Similarly, use of simulation models in optimizing selection and placement of best management practices under single (maximization of crop production or minimization of pollutant transport) and multiple objective functions has increased recently. One of the limitations of the currently available assessment and optimization approaches is that the BMP strategies are considered deterministic. Uncertainties in input data (e.g. precipitation, streamflow, sediment, nutrient and pesticide losses measured, land use) and model parameters may result in considerable uncertainty in watershed response under various BMP options. We have developed and evaluated options to include uncertainty in BMP evaluation and optimization for watershed management. We have also applied these methods to evaluate uncertainty in ecosystem services from mixed land use watersheds. In this presentation, we will discuss methods to to quantify uncertainties in BMP assessment and optimization solutions due to uncertainties in model inputs and parameters. We have used a watershed model (Soil and Water Assessment Tool or SWAT) to simulate the hydrology and water quality in mixed land use watershed located in Midwest USA. The SWAT model was also used to represent various BMPs in the watershed needed to improve water quality. SWAT model parameters, land use change parameters, and climate change parameters were considered uncertain. It was observed that model parameters, land use and climate changes resulted in considerable uncertainties in BMP performance in reducing P, N, and sediment loads. In addition, climate change scenarios also affected uncertainties in SWAT

Evaluation of peaking factors uncertainty for CASMO-3

Energy Technology Data Exchange (ETDEWEB)

Kim, Kang Suk; Song, Jae Seung; Kim, Yong Rae; Ji, Seong Kyun [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

1996-02-01

This document evaluates the pin-to-box factor uncertainty based on using the CASMO-3 with 40-group J-library. Five CE criticals performed by Westinghouse, two by B and W and four RPI criticals were analyzed, using cross sections by CASMO-3. DOT was used for the core calculation. THis is one hof series of efforts to verify ADONIS procedure which is a new core design package under development by KAERI. The expected outcome of this analysis is CASMO-3 pin peak uncertainty applicable to CE type fuel assembly design. The evaluated uncertainty of peaking factors for CASMO-3 was 1.863%. 21 tabs., 23 figs., 12 refs. (Author) .new.

Developing first time-series of land surface temperature from AATSR with uncertainty estimates

Science.gov (United States)

Ghent, Darren; Remedios, John

2013-04-01

Land surface temperature (LST) is the radiative skin temperature of the land, and is one of the key parameters in the physics of land-surface processes on regional and global scales. Earth Observation satellites provide the opportunity to obtain global coverage of LST approximately every 3 days or less. One such source of satellite retrieved LST has been the Advanced Along-Track Scanning Radiometer (AATSR); with LST retrieval being implemented in the AATSR Instrument Processing Facility in March 2004. Here we present first regional and global time-series of LST data from AATSR with estimates of uncertainty. Mean changes in temperature over the last decade will be discussed along with regional patterns. Although time-series across all three ATSR missions have previously been constructed (Kogler et al., 2012), the use of low resolution auxiliary data in the retrieval algorithm and non-optimal cloud masking resulted in time-series artefacts. As such, considerable ESA supported development has been carried out on the AATSR data to address these concerns. This includes the integration of high resolution auxiliary data into the retrieval algorithm and subsequent generation of coefficients and tuning parameters, plus the development of an improved cloud mask based on the simulation of clear sky conditions from radiance transfer modelling (Ghent et al., in prep.). Any inference on this LST record is though of limited value without the accompaniment of an uncertainty estimate; wherein the Joint Committee for Guides in Metrology quote an uncertainty as "a parameter associated with the result of a measurement that characterizes the dispersion of the values that could reasonably be attributed to the measurand that is the value of the particular quantity to be measured". Furthermore, pixel level uncertainty fields are a mandatory requirement in the on-going preparation of the LST product for the upcoming Sea and Land Surface Temperature (SLSTR) instrument on-board Sentinel-3

Estimation of uncertainties in resonance parameters of {sup 56}Fe, {sup 239}Pu, {sup 240}Pu and {sup 238}U

Energy Technology Data Exchange (ETDEWEB)

Nakagawa, Tsuneo; Shibata, Keiichi [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment

1997-05-01

Uncertainties have been estimated for the resonance parameters of {sup 56}Fe, {sup 239}Pu, {sup 240}Pu and {sup 238}U contained in JENDL-3.2. Errors of the parameters were determined from the measurements which the evaluation was based on. The estimated errors have been compiled in the MF32 of the ENDF format. The numerical results are given in tables. (author)

Sensitivity of Process Design due to Uncertainties in Property Estimates

DEFF Research Database (Denmark)

Hukkerikar, Amol; Jones, Mark Nicholas; Sarup, Bent

2012-01-01

The objective of this paper is to present a systematic methodology for performing analysis of sensitivity of process design due to uncertainties in property estimates. The methodology provides the following results: a) list of properties with critical importance on design; b) acceptable levels of...... in chemical processes. Among others vapour pressure accuracy for azeotropic mixtures is critical and needs to be measured or estimated with a ±0.25% accuracy to satisfy acceptable safety levels in design....

Error Estimation and Uncertainty Propagation in Computational Fluid Mechanics

Science.gov (United States)

Zhu, J. Z.; He, Guowei; Bushnell, Dennis M. (Technical Monitor)

2002-01-01

Numerical simulation has now become an integral part of engineering design process. Critical design decisions are routinely made based on the simulation results and conclusions. Verification and validation of the reliability of the numerical simulation is therefore vitally important in the engineering design processes. We propose to develop theories and methodologies that can automatically provide quantitative information about the reliability of the numerical simulation by estimating numerical approximation error, computational model induced errors and the uncertainties contained in the mathematical models so that the reliability of the numerical simulation can be verified and validated. We also propose to develop and implement methodologies and techniques that can control the error and uncertainty during the numerical simulation so that the reliability of the numerical simulation can be improved.

Improving the precision of lake ecosystem metabolism estimates by identifying predictors of model uncertainty

Science.gov (United States)

Rose, Kevin C.; Winslow, Luke A.; Read, Jordan S.; Read, Emily K.; Solomon, Christopher T.; Adrian, Rita; Hanson, Paul C.

2014-01-01

Diel changes in dissolved oxygen are often used to estimate gross primary production (GPP) and ecosystem respiration (ER) in aquatic ecosystems. Despite the widespread use of this approach to understand ecosystem metabolism, we are only beginning to understand the degree and underlying causes of uncertainty for metabolism model parameter estimates. Here, we present a novel approach to improve the precision and accuracy of ecosystem metabolism estimates by identifying physical metrics that indicate when metabolism estimates are highly uncertain. Using datasets from seventeen instrumented GLEON (Global Lake Ecological Observatory Network) lakes, we discovered that many physical characteristics correlated with uncertainty, including PAR (photosynthetically active radiation, 400-700 nm), daily variance in Schmidt stability, and wind speed. Low PAR was a consistent predictor of high variance in GPP model parameters, but also corresponded with low ER model parameter variance. We identified a threshold (30% of clear sky PAR) below which GPP parameter variance increased rapidly and was significantly greater in nearly all lakes compared with variance on days with PAR levels above this threshold. The relationship between daily variance in Schmidt stability and GPP model parameter variance depended on trophic status, whereas daily variance in Schmidt stability was consistently positively related to ER model parameter variance. Wind speeds in the range of ~0.8-3 m s–1 were consistent predictors of high variance for both GPP and ER model parameters, with greater uncertainty in eutrophic lakes. Our findings can be used to reduce ecosystem metabolism model parameter uncertainty and identify potential sources of that uncertainty.

Uncertainties in early-stage capital cost estimation of process design – a case study on biorefinery design

DEFF Research Database (Denmark)

Cheali, Peam; Gernaey, Krist; Sin, Gürkan

2015-01-01

Capital investment, next to the product demand, sales, and production costs, is one of the key metrics commonly used for project evaluation and feasibility assessment. Estimating the investment costs of a new product/process alternative during early-stage design is a challenging task, which......) the Monte Carlo technique as an error propagation method based on expert input when cost data are not available. Four well-known models for early-stage cost estimation are reviewed and analyzed using the methodology. The significance of uncertainties of cost data for early-stage process design...

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

International Nuclear Information System (INIS)

Miller, C.; Little, C.A.

1982-08-01

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

Uncertainty evaluation of a modified elimination weighing for source preparation

Energy Technology Data Exchange (ETDEWEB)

Cacais, F.L.; Loayza, V.M., E-mail: facacais@gmail.com [Instituto Nacional de Metrologia, Qualidade e Tecnologia, (INMETRO), Rio de Janeiro, RJ (Brazil); Delgado, J.U. [Instituto de Radioproteção e Dosimetria (IRD/CNEN-RJ), Rio de Janeiro, RJ (Brazil). Lab. de Metrologia das Radiações Ionizantes

2017-07-01

Some modification in elimination weighing method for radioactive source allowed correcting weighing results without non-linearity problems assign a uncertainty contribution for the correction of the same order of the mass of drop uncertainty and check weighing variability in series source preparation. This analysis has focused in knowing the achievable weighing accuracy and the uncertainty estimated by Monte Carlo method for a mass of a 20 mg drop was at maximum of 0.06%. (author)

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

Study of the uncertainty in estimation of the exposure of non-human biota to ionising radiation.

Science.gov (United States)

Avila, R; Beresford, N A; Agüero, A; Broed, R; Brown, J; Iospje, M; Robles, B; Suañez, A

2004-12-01

Uncertainty in estimations of the exposure of non-human biota to ionising radiation may arise from a number of sources including values of the model parameters, empirical data, measurement errors and biases in the sampling. The significance of the overall uncertainty of an exposure assessment will depend on how the estimated dose compares with reference doses used for risk characterisation. In this paper, we present the results of a study of the uncertainty in estimation of the exposure of non-human biota using some of the models and parameters recommended in the FASSET methodology. The study was carried out for semi-natural terrestrial, agricultural and marine ecosystems, and for four radionuclides (137Cs, 239Pu, 129I and 237Np). The parameters of the radionuclide transfer models showed the highest sensitivity and contributed the most to the uncertainty in the predictions of doses to biota. The most important ones were related to the bioavailability and mobility of radionuclides in the environment, for example soil-to-plant transfer factors, the bioaccumulation factors for marine biota and the gut uptake fraction for terrestrial mammals. In contrast, the dose conversion coefficients showed low sensitivity and contributed little to the overall uncertainty. Radiobiological effectiveness contributed to the overall uncertainty of the dose estimations for alpha emitters although to a lesser degree than a number of transfer model parameters.

Uncertainty estimation of the velocity model for stations of the TrigNet GPS network

Science.gov (United States)

Hackl, M.; Malservisi, R.; Hugentobler, U.

2010-12-01

Satellite based geodetic techniques - above all GPS - provide an outstanding tool to measure crustal motions. They are widely used to derive geodetic velocity models that are applied in geodynamics to determine rotations of tectonic blocks, to localize active geological features, and to estimate rheological properties of the crust and the underlying asthenosphere. However, it is not a trivial task to derive GPS velocities and their uncertainties from positioning time series. In general time series are assumed to be represented by linear models (sometimes offsets, annual, and semi-annual signals are included) and noise. It has been shown that error models accounting only for white noise tend to underestimate the uncertainties of rates derived from long time series and that different colored noise components (flicker noise, random walk, etc.) need to be considered. However, a thorough error analysis including power spectra analyses and maximum likelihood estimates is computationally expensive and is usually not carried out for every site, but the uncertainties are scaled by latitude dependent factors. Analyses of the South Africa continuous GPS network TrigNet indicate that the scaled uncertainties overestimate the velocity errors. So we applied a method similar to the Allan Variance that is commonly used in the estimation of clock uncertainties and is able to account for time dependent probability density functions (colored noise) to the TrigNet time series. Comparisons with synthetic data show that the noise can be represented quite well by a power law model in combination with a seasonal signal in agreement with previous studies, which allows for a reliable estimation of the velocity error. Finally, we compared these estimates to the results obtained by spectral analyses using CATS. Small differences may originate from non-normal distribution of the noise.

A Proposal of Estimation Methodology to Improve Calculation Efficiency of Sampling-based Method in Nuclear Data Sensitivity and Uncertainty Analysis

International Nuclear Information System (INIS)

Song, Myung Sub; Kim, Song Hyun; Kim, Jong Kyung; Noh, Jae Man

2014-01-01

The uncertainty with the sampling-based method is evaluated by repeating transport calculations with a number of cross section data sampled from the covariance uncertainty data. In the transport calculation with the sampling-based method, the transport equation is not modified; therefore, all uncertainties of the responses such as k eff , reaction rates, flux and power distribution can be directly obtained all at one time without code modification. However, a major drawback with the sampling-based method is that it requires expensive computational load for statistically reliable results (inside confidence level 0.95) in the uncertainty analysis. The purpose of this study is to develop a method for improving the computational efficiency and obtaining highly reliable uncertainty result in using the sampling-based method with Monte Carlo simulation. The proposed method is a method to reduce the convergence time of the response uncertainty by using the multiple sets of sampled group cross sections in a single Monte Carlo simulation. The proposed method was verified by estimating GODIVA benchmark problem and the results were compared with that of conventional sampling-based method. In this study, sampling-based method based on central limit theorem is proposed to improve calculation efficiency by reducing the number of repetitive Monte Carlo transport calculation required to obtain reliable uncertainty analysis results. Each set of sampled group cross sections is assigned to each active cycle group in a single Monte Carlo simulation. The criticality uncertainty for the GODIVA problem is evaluated by the proposed and previous method. The results show that the proposed sampling-based method can efficiently decrease the number of Monte Carlo simulation required for evaluate uncertainty of k eff . It is expected that the proposed method will improve computational efficiency of uncertainty analysis with sampling-based method

Evaluation of Uncertainties in the Determination of Phosphorus by RNAA

International Nuclear Information System (INIS)

Rick L. Paul

2000-01-01

A radiochemical neutron activation analysis (RNAA) procedure for the determination of phosphorus in metals and other materials has been developed and critically evaluated. Uncertainties evaluated as type A include those arising from measurement replication, yield determination, neutron self-shielding, irradiation geometry, measurement of the quantity for concentration normalization (sample mass, area, etc.), and analysis of standards. Uncertainties evaluated as type B include those arising from beta contamination corrections, beta decay curve fitting, and beta self-absorption corrections. The evaluation of uncertainties in the determination of phosphorus is illustrated for three different materials in Table I. The metal standard reference materials (SRMs) 2175 and 861 were analyzed for value assignment of phosphorus; implanted silicon was analyzed to evaluate the technique for certification of phosphorus. The most significant difference in the error evaluation of the three materials lies in the type B uncertainties. The relatively uncomplicated matrix of the high-purity silicon allows virtually complete purification of phosphorus from other beta emitters; hence, minimal contamination correction is needed. Furthermore, because the chemistry is less rigorous, the carrier yield is more reproducible, and self-absorption corrections are less significant. Improvements in the chemical purification procedures for phosphorus in complex matrices will decrease the type B uncertainties for all samples. Uncertainties in the determination of carrier yield, the most significant type A error in the analysis of the silicon, also need to be evaluated more rigorously and minimized in the future

Data-Driven Model Uncertainty Estimation in Hydrologic Data Assimilation

Science.gov (United States)

Pathiraja, S.; Moradkhani, H.; Marshall, L.; Sharma, A.; Geenens, G.

2018-02-01

The increasing availability of earth observations necessitates mathematical methods to optimally combine such data with hydrologic models. Several algorithms exist for such purposes, under the umbrella of data assimilation (DA). However, DA methods are often applied in a suboptimal fashion for complex real-world problems, due largely to several practical implementation issues. One such issue is error characterization, which is known to be critical for a successful assimilation. Mischaracterized errors lead to suboptimal forecasts, and in the worst case, to degraded estimates even compared to the no assimilation case. Model uncertainty characterization has received little attention relative to other aspects of DA science. Traditional methods rely on subjective, ad hoc tuning factors or parametric distribution assumptions that may not always be applicable. We propose a novel data-driven approach (named SDMU) to model uncertainty characterization for DA studies where (1) the system states are partially observed and (2) minimal prior knowledge of the model error processes is available, except that the errors display state dependence. It includes an approach for estimating the uncertainty in hidden model states, with the end goal of improving predictions of observed variables. The SDMU is therefore suited to DA studies where the observed variables are of primary interest. Its efficacy is demonstrated through a synthetic case study with low-dimensional chaotic dynamics and a real hydrologic experiment for one-day-ahead streamflow forecasting. In both experiments, the proposed method leads to substantial improvements in the hidden states and observed system outputs over a standard method involving perturbation with Gaussian noise.

Monte Carlo uncertainty analysis of dose estimates in radiochromic film dosimetry with single-channel and multichannel algorithms.

Science.gov (United States)

Vera-Sánchez, Juan Antonio; Ruiz-Morales, Carmen; González-López, Antonio

2018-03-01

To provide a multi-stage model to calculate uncertainty in radiochromic film dosimetry with Monte-Carlo techniques. This new approach is applied to single-channel and multichannel algorithms. Two lots of Gafchromic EBT3 are exposed in two different Varian linacs. They are read with an EPSON V800 flatbed scanner. The Monte-Carlo techniques in uncertainty analysis provide a numerical representation of the probability density functions of the output magnitudes. From this numerical representation, traditional parameters of uncertainty analysis as the standard deviations and bias are calculated. Moreover, these numerical representations are used to investigate the shape of the probability density functions of the output magnitudes. Also, another calibration film is read in four EPSON scanners (two V800 and two 10000XL) and the uncertainty analysis is carried out with the four images. The dose estimates of single-channel and multichannel algorithms show a Gaussian behavior and low bias. The multichannel algorithms lead to less uncertainty in the final dose estimates when the EPSON V800 is employed as reading device. In the case of the EPSON 10000XL, the single-channel algorithms provide less uncertainty in the dose estimates for doses higher than four Gy. A multi-stage model has been presented. With the aid of this model and the use of the Monte-Carlo techniques, the uncertainty of dose estimates for single-channel and multichannel algorithms are estimated. The application of the model together with Monte-Carlo techniques leads to a complete characterization of the uncertainties in radiochromic film dosimetry. Copyright © 2018 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Estimation of uncertainty of measurements of 3D mechanisms after kinematic calibration

International Nuclear Information System (INIS)

Takamasu, K; Sato, O; Shimojima, K; Takahashi, S; Furutani, R

2005-01-01

Calibration methods for 3D mechanisms are necessary to use the mechanisms as coordinate measuring machines. The calibration method of coordinate measuring machine using artifacts, the artifact calibration method, is proposed in taking account of traceability of the mechanism. There are kinematic parameters and form-deviation parameters in geometric parameters for describing the forward kinematic of the mechanism. In this article, the estimation methods of uncertainties using the calibrated coordinate measuring machine after the calibration are formulated. Firstly, the calculation method which takes out the values of kinematic parameters using least squares method is formulated. Secondly, the estimation value of uncertainty of the measuring machine is calculated using the error propagation method

Estimating predictive hydrological uncertainty by dressing deterministic and ensemble forecasts; a comparison, with application to Meuse and Rhine

Science.gov (United States)

Verkade, J. S.; Brown, J. D.; Davids, F.; Reggiani, P.; Weerts, A. H.

2017-12-01

Two statistical post-processing approaches for estimation of predictive hydrological uncertainty are compared: (i) 'dressing' of a deterministic forecast by adding a single, combined estimate of both hydrological and meteorological uncertainty and (ii) 'dressing' of an ensemble streamflow forecast by adding an estimate of hydrological uncertainty to each individual streamflow ensemble member. Both approaches aim to produce an estimate of the 'total uncertainty' that captures both the meteorological and hydrological uncertainties. They differ in the degree to which they make use of statistical post-processing techniques. In the 'lumped' approach, both sources of uncertainty are lumped by post-processing deterministic forecasts using their verifying observations. In the 'source-specific' approach, the meteorological uncertainties are estimated by an ensemble of weather forecasts. These ensemble members are routed through a hydrological model and a realization of the probability distribution of hydrological uncertainties (only) is then added to each ensemble member to arrive at an estimate of the total uncertainty. The techniques are applied to one location in the Meuse basin and three locations in the Rhine basin. Resulting forecasts are assessed for their reliability and sharpness, as well as compared in terms of multiple verification scores including the relative mean error, Brier Skill Score, Mean Continuous Ranked Probability Skill Score, Relative Operating Characteristic Score and Relative Economic Value. The dressed deterministic forecasts are generally more reliable than the dressed ensemble forecasts, but the latter are sharper. On balance, however, they show similar quality across a range of verification metrics, with the dressed ensembles coming out slightly better. Some additional analyses are suggested. Notably, these include statistical post-processing of the meteorological forecasts in order to increase their reliability, thus increasing the reliability

Treatment simulation approaches for the estimation of the distributions of treatment quality parameters generated by geometrical uncertainties

International Nuclear Information System (INIS)

Baum, C; Alber, M; Birkner, M; Nuesslin, F

2004-01-01

Geometric uncertainties arise during treatment planning and treatment and mean that dose-dependent parameters such as EUD are random variables with a patient specific probability distribution. Treatment planning with highly conformal treatment techniques such as intensity modulated radiation therapy requires new evaluation tools which allow us to estimate this influence of geometrical uncertainties on the probable treatment dose for a planned dose distribution. Monte Carlo simulations of treatment courses with recalculation of the dose according to the daily geometric errors are a gold standard for such an evaluation. Distribution histograms which show the relative frequency of a treatment quality parameter in the treatment simulations can be used to evaluate the potential risks and chances of a planned dose distribution. As treatment simulations with dose recalculation are very time consuming for sufficient statistical accuracy, it is proposed to do treatment simulations in the dose parameter space where the result is mainly determined by the systematic and random component of the geometrical uncertainties. Comparison of the parameter space simulation method with the gold standard for prostate cases and a head and neck case shows good agreement as long as the number of fractions is high enough and the influence of tissue inhomogeneities and surface curvature on the dose is small

Neutron flux uncertainty and covariances for spectrum adjustment and estimation of WWER-1000 pressure vessel fluences

International Nuclear Information System (INIS)

Boehmer, Bertram

2000-01-01

Results of estimation of the covariance matrix of the neutron spectrum in the WWER-1000 reactor cavity and pressure vessel positions are presented. Two-dimensional calculations with the discrete ordinates transport code DORT in r-theta and r-z-geometry used to determine the neutron group spectrum covariances including gross-correlations between interesting positions. The new Russian ABBN-93 data set and CONSYST code used to supply all transport calculations with group neutron data. All possible sources of uncertainties namely caused by the neutron gross sections, fission sources, geometrical dimensions and material densities considered, whereas the uncertainty of the calculation method was considered negligible in view of the available precision of Monte Carlo simulation used for more precise evaluation of the neutron fluence. (Authors)

Measuring Cross-Section and Estimating Uncertainties with the fissionTPC

Energy Technology Data Exchange (ETDEWEB)

Bowden, N. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Manning, B. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Sangiorgio, S. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Seilhan, B. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2015-01-30

The purpose of this document is to outline the prescription for measuring fission cross-sections with the NIFFTE fissionTPC and estimating the associated uncertainties. As such it will serve as a work planning guide for NIFFTE collaboration members and facilitate clear communication of the procedures used to the broader community.

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

Applying the conservativeness principle to REDD to deal with the uncertainties of the estimates

International Nuclear Information System (INIS)

Grassi, Giacomo; Monni, Suvi; Achard, Frederic; Mollicone, Danilo; Federici, Sandro

2008-01-01

A common paradigm when the reduction of emissions from deforestations is estimated for the purpose of promoting it as a mitigation option in the context of the United Nations Framework Convention on Climate Change (UNFCCC) is that high uncertainties in input data-i.e., area change and C stock change/area-may seriously undermine the credibility of the estimates and therefore of reduced deforestation as a mitigation option. In this paper, we show how a series of concepts and methodological tools-already existing in UNFCCC decisions and IPCC guidance documents-may greatly help to deal with the uncertainties of the estimates of reduced emissions from deforestation

Applying the conservativeness principle to REDD to deal with the uncertainties of the estimates

Energy Technology Data Exchange (ETDEWEB)

Grassi, Giacomo; Monni, Suvi; Achard, Frederic [Institute for Environment and Sustainability, Joint Research Centre of the European Commission, I-21020 Ispra (Italy); Mollicone, Danilo [Department of Geography, University of Alcala de Henares, Madrid (Spain); Federici, Sandro

2008-07-15

A common paradigm when the reduction of emissions from deforestations is estimated for the purpose of promoting it as a mitigation option in the context of the United Nations Framework Convention on Climate Change (UNFCCC) is that high uncertainties in input data-i.e., area change and C stock change/area-may seriously undermine the credibility of the estimates and therefore of reduced deforestation as a mitigation option. In this paper, we show how a series of concepts and methodological tools-already existing in UNFCCC decisions and IPCC guidance documents-may greatly help to deal with the uncertainties of the estimates of reduced emissions from deforestation.

Evaluation of the uncertainty of environmental measurements of radioactivity

International Nuclear Information System (INIS)

Heydorn, K.

2003-01-01

sampling constant, but for natural material this way of expressing uncertainty is rarely justifiable. While no established method accounting for this effect has been found, several methods to estimate its contribution to the uncertainty of measurement results will be discussed. Contemporary estimates of uncertainty must be shown to accommodate future results, and a continuous quality control based on replication of samples must be implemented to ascertain the validity of the quoted uncertainties. Illustration of a practical system that can take this effect into account will be presented

Degradation and performance evaluation of PV module in desert climate conditions with estimate uncertainty in measuring

Directory of Open Access Journals (Sweden)

Fezzani Amor

2017-01-01

Full Text Available The performance of photovoltaic (PV module is affected by outdoor conditions. Outdoor testing consists installing a module, and collecting electrical performance data and climatic data over a certain period of time. It can also include the study of long-term performance under real work conditions. Tests are operated in URAER located in desert region of Ghardaïa (Algeria characterized by high irradiation and temperature levels. The degradation of PV module with temperature and time exposure to sunlight contributes significantly to the final output from the module, as the output reduces each year. This paper presents a comparative study of different methods to evaluate the degradation of PV module after a long term exposure of more than 12 years in desert region and calculates uncertainties in measuring. Firstly, this evaluation uses three methods: Visual inspection, data given by Solmetric PVA-600 Analyzer translated at Standard Test Condition (STC and based on the investigation results of the translation equations as ICE 60891. Secondly, the degradation rates calculated for all methods. Finally, a comparison between a degradation rates given by Solmetric PVA-600 analyzer, calculated by simulation model and calculated by two methods (ICE 60891 procedures 1, 2. We achieved a detailed uncertainty study in order to improve the procedure and measurement instrument.

Uncertainties in Transport Project Evaluation: Editorial

DEFF Research Database (Denmark)

Salling, Kim Bang; Nielsen, Otto Anker

2015-01-01

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

Epistemic Uncertainty in Evaluation of Evapotranspiration and Net Infiltration Using Analogue Meteorological Data

International Nuclear Information System (INIS)

B. Faybishenko

2006-01-01

Uncertainty is typically defined as a potential deficiency in the modeling of a physical process, owing to a lack of knowledge. Uncertainty can be categorized as aleatoric (inherent uncertainty caused by the intrinsic randomness of the system) or epistemic (uncertainty caused by using various model simplifications and their parameters). One of the main reasons for model simplifications is a limited amount of meteorological data. This paper is devoted to the epistemic uncertainty quantification involved in two components of the hydrologic balance-evapotranspiration and net infiltration for interglacial (present day), and future monsoon, glacial transition, and glacial climates at Yucca Mountain, using the data from analogue meteorological stations. In particular, the author analyzes semi-empirical models used for evaluating (1) reference-surface potential evapotranspiration, including temperature-based models (Hargreaves-Samani, Thornthwaite, Hamon, Jensen-Haise, and Turc) and radiation-based models (Priestly-Taylor and Penman), and (2) surface-dependent potential evapotranspiration (Penman-Monteith and Shuttleworth-Wallace models). Evapotranspiration predictions are then used as inputs for the evaluation of net infiltration using the semi-empirical models of Budyko, Fu, Milly, Turc-Pike, and Zhang. Results show that net infiltration ranges are expected to generally increase from the present-day climate to monsoon climate, to glacial transition climate, and then to the glacial climate. The propagation of uncertainties through model predictions for different climates is characterized using statistical measures. Predicted evapotranspiration ranges are reasonably corroborated against the data from Class A pan evaporometers (taking into account evaporation-pan adjustment coefficients), and ranges of net infiltration predictions are corroborated against the geochemical and temperature-based estimates of groundwater recharge and percolation rates through the unsaturated

Uncertainty theory

CERN Document Server

Liu, Baoding

2015-01-01

When no samples are available to estimate a probability distribution, we have to invite some domain experts to evaluate the belief degree that each event will happen. Perhaps some people think that the belief degree should be modeled by subjective probability or fuzzy set theory. However, it is usually inappropriate because both of them may lead to counterintuitive results in this case. In order to rationally deal with belief degrees, uncertainty theory was founded in 2007 and subsequently studied by many researchers. Nowadays, uncertainty theory has become a branch of axiomatic mathematics for modeling belief degrees. This is an introductory textbook on uncertainty theory, uncertain programming, uncertain statistics, uncertain risk analysis, uncertain reliability analysis, uncertain set, uncertain logic, uncertain inference, uncertain process, uncertain calculus, and uncertain differential equation. This textbook also shows applications of uncertainty theory to scheduling, logistics, networks, data mining, c...

Estimation of environment-related properties of chemicals for design of sustainable processes: development of group-contribution+ (GC+) property models and uncertainty analysis.

Science.gov (United States)

Hukkerikar, Amol Shivajirao; Kalakul, Sawitree; Sarup, Bent; Young, Douglas M; Sin, Gürkan; Gani, Rafiqul

2012-11-26

of the developed property models for the estimation of environment-related properties and uncertainties of the estimated property values is highlighted through an illustrative example. The developed property models provide reliable estimates of environment-related properties needed to perform process synthesis, design, and analysis of sustainable chemical processes and allow one to evaluate the effect of uncertainties of estimated property values on the calculated performance of processes giving useful insights into quality and reliability of the design of sustainable processes.

Fault-tolerant embedded system design and optimization considering reliability estimation uncertainty

International Nuclear Information System (INIS)

Wattanapongskorn, Naruemon; Coit, David W.

2007-01-01

In this paper, we model embedded system design and optimization, considering component redundancy and uncertainty in the component reliability estimates. The systems being studied consist of software embedded in associated hardware components. Very often, component reliability values are not known exactly. Therefore, for reliability analysis studies and system optimization, it is meaningful to consider component reliability estimates as random variables with associated estimation uncertainty. In this new research, the system design process is formulated as a multiple-objective optimization problem to maximize an estimate of system reliability, and also, to minimize the variance of the reliability estimate. The two objectives are combined by penalizing the variance for prospective solutions. The two most common fault-tolerant embedded system architectures, N-Version Programming and Recovery Block, are considered as strategies to improve system reliability by providing system redundancy. Four distinct models are presented to demonstrate the proposed optimization techniques with or without redundancy. For many design problems, multiple functionally equivalent software versions have failure correlation even if they have been independently developed. The failure correlation may result from faults in the software specification, faults from a voting algorithm, and/or related faults from any two software versions. Our approach considers this correlation in formulating practical optimization models. Genetic algorithms with a dynamic penalty function are applied in solving this optimization problem, and reasonable and interesting results are obtained and discussed

Evaluation of incremental reactivity and its uncertainty in Southern California.

Science.gov (United States)

Martien, Philip T; Harley, Robert A; Milford, Jana B; Russell, Armistead G

2003-04-15

The incremental reactivity (IR) and relative incremental reactivity (RIR) of carbon monoxide and 30 individual volatile organic compounds (VOC) were estimated for the South Coast Air Basin using two photochemical air quality models: a 3-D, grid-based model and a vertically resolved trajectory model. Both models include an extended version of the SAPRC99 chemical mechanism. For the 3-D modeling, the decoupled direct method (DDM-3D) was used to assess reactivities. The trajectory model was applied to estimate uncertainties in reactivities due to uncertainties in chemical rate parameters, deposition parameters, and emission rates using Monte Carlo analysis with Latin hypercube sampling. For most VOC, RIRs were found to be consistent in rankings with those produced by Carter using a box model. However, 3-D simulations show that coastal regions, upwind of most of the emissions, have comparatively low IR but higher RIR than predicted by box models for C4-C5 alkenes and carbonyls that initiate the production of HOx radicals. Biogenic VOC emissions were found to have a lower RIR than predicted by box model estimates, because emissions of these VOC were mostly downwind of the areas of primary ozone production. Uncertainties in RIR of individual VOC were found to be dominated by uncertainties in the rate parameters of their primary oxidation reactions. The coefficient of variation (COV) of most RIR values ranged from 20% to 30%, whereas the COV of absolute incremental reactivity ranged from about 30% to 40%. In general, uncertainty and variability both decreased when relative rather than absolute reactivity metrics were used.

An estimation of uncertainties in containment P/T analysis using CONTEMPT/LT code

International Nuclear Information System (INIS)

Kang, Y.M.; Park, G.C.; Lee, U.C.; Kang, C.S.

1991-01-01

In a nuclear power plant, the containment design pressure and temperature (P/T) have been established based on the unrealistic conservatism with suffering from a drawback in the economics. Thus, it is necessary that the uncertainties of design P/T values have to be well defined through an extensive uncertainty analysis with plant-specific input data and or models used in the computer code. This study is to estimate plant-specific uncertainties of containment design P/T using the Monte Carlo method in Kori-3 reactor. Kori-3 plant parameters and Uchida heat transfer coefficient are selected to be treated statistically after the sensitivity study. The Monte Carlo analysis has performed based on the response surface method with the CONTEMPT/LT code and Latin Hypercube sampling technique. Finally, the design values based on 95 %/95 % probability are compared with worst estimated values to assess the design margin. (author)

Methods to estimate the between‐study variance and its uncertainty in meta‐analysis†

Science.gov (United States)

Jackson, Dan; Viechtbauer, Wolfgang; Bender, Ralf; Bowden, Jack; Knapp, Guido; Kuss, Oliver; Higgins, Julian PT; Langan, Dean; Salanti, Georgia

2015-01-01

Meta‐analyses are typically used to estimate the overall/mean of an outcome of interest. However, inference about between‐study variability, which is typically modelled using a between‐study variance parameter, is usually an additional aim. The DerSimonian and Laird method, currently widely used by default to estimate the between‐study variance, has been long challenged. Our aim is to identify known methods for estimation of the between‐study variance and its corresponding uncertainty, and to summarise the simulation and empirical evidence that compares them. We identified 16 estimators for the between‐study variance, seven methods to calculate confidence intervals, and several comparative studies. Simulation studies suggest that for both dichotomous and continuous data the estimator proposed by Paule and Mandel and for continuous data the restricted maximum likelihood estimator are better alternatives to estimate the between‐study variance. Based on the scenarios and results presented in the published studies, we recommend the Q‐profile method and the alternative approach based on a ‘generalised Cochran between‐study variance statistic’ to compute corresponding confidence intervals around the resulting estimates. Our recommendations are based on a qualitative evaluation of the existing literature and expert consensus. Evidence‐based recommendations require an extensive simulation study where all methods would be compared under the same scenarios. © 2015 The Authors. Research Synthesis Methods published by John Wiley & Sons Ltd. PMID:26332144

Revised cost savings estimate with uncertainty for enhanced sludge washing of underground storage tank waste

International Nuclear Information System (INIS)

DeMuth, S.

1998-01-01

Enhanced Sludge Washing (ESW) has been selected to reduce the amount of sludge-based underground storage tank (UST) high-level waste at the Hanford site. During the past several years, studies have been conducted to determine the cost savings derived from the implementation of ESW. The tank waste inventory and ESW performance continues to be revised as characterization and development efforts advance. This study provides a new cost savings estimate based upon the most recent inventory and ESW performance revisions, and includes an estimate of the associated cost uncertainty. Whereas the author's previous cost savings estimates for ESW were compared against no sludge washing, this study assumes the baseline to be simple water washing which more accurately reflects the retrieval activity along. The revised ESW cost savings estimate for all UST waste at Hanford is $6.1 B ± $1.3 B within 95% confidence. This is based upon capital and operating cost savings, but does not include development costs. The development costs are assumed negligible since they should be at least an order of magnitude less than the savings. The overall cost savings uncertainty was derived from process performance uncertainties and baseline remediation cost uncertainties, as determined by the author's engineering judgment

Aboveground Forest Biomass Estimation with Landsat and LiDAR Data and Uncertainty Analysis of the Estimates

OpenAIRE

Dengsheng Lu; Qi Chen; Guangxing Wang; Emilio Moran; Mateus Batistella; Maozhen Zhang; Gaia Vaglio Laurin; David Saah

2012-01-01

Landsat Thematic mapper (TM) image has long been the dominate data source, and recently LiDAR has offered an important new structural data stream for forest biomass estimations. On the other hand, forest biomass uncertainty analysis research has only recently obtained sufficient attention due to the difficulty in collecting reference data. This paper provides a brief overview of current forest biomass estimation methods using both TM and LiDAR data. A case study is then presented that demonst...

Evaluation of Uncertainty in Precipitation Datasets for New Mexico, USA

Science.gov (United States)

Besha, A. A.; Steele, C. M.; Fernald, A.

2014-12-01

Climate change, population growth and other factors are endangering water availability and sustainability in semiarid/arid areas particularly in the southwestern United States. Wide coverage of spatial and temporal measurements of precipitation are key for regional water budget analysis and hydrological operations which themselves are valuable tool for water resource planning and management. Rain gauge measurements are usually reliable and accurate at a point. They measure rainfall continuously, but spatial sampling is limited. Ground based radar and satellite remotely sensed precipitation have wide spatial and temporal coverage. However, these measurements are indirect and subject to errors because of equipment, meteorological variability, the heterogeneity of the land surface itself and lack of regular recording. This study seeks to understand precipitation uncertainty and in doing so, lessen uncertainty propagation into hydrological applications and operations. We reviewed, compared and evaluated the TRMM (Tropical Rainfall Measuring Mission) precipitation products, NOAA's (National Oceanic and Atmospheric Administration) Global Precipitation Climatology Centre (GPCC) monthly precipitation dataset, PRISM (Parameter elevation Regression on Independent Slopes Model) data and data from individual climate stations including Cooperative Observer Program (COOP), Remote Automated Weather Stations (RAWS), Soil Climate Analysis Network (SCAN) and Snowpack Telemetry (SNOTEL) stations. Though not yet finalized, this study finds that the uncertainty within precipitation estimates datasets is influenced by regional topography, season, climate and precipitation rate. Ongoing work aims to further evaluate precipitation datasets based on the relative influence of these phenomena so that we can identify the optimum datasets for input to statewide water budget analysis.

Estimation of sedimentary proxy records together with associated uncertainty

OpenAIRE

Goswami, B.; Heitzig, J.; Rehfeld, K.; Marwan, N.; Anoop, A.; Prasad, S.; Kurths, J.

2014-01-01

Sedimentary proxy records constitute a significant portion of the recorded evidence that allows us to investigate paleoclimatic conditions and variability. However, uncertainties in the dating of proxy archives limit our ability to fix the timing of past events and interpret proxy record intercomparisons. While there are various age-modeling approaches to improve the estimation of the age–depth relations of archives, relatively little focus has been placed on the propagation...

Classification in hyperspectral images by independent component analysis, segmented cross-validation and uncertainty estimates

Directory of Open Access Journals (Sweden)

Beatriz Galindo-Prieto

2018-02-01

Full Text Available Independent component analysis combined with various strategies for cross-validation, uncertainty estimates by jack-knifing and critical Hotelling’s T2 limits estimation, proposed in this paper, is used for classification purposes in hyperspectral images. To the best of our knowledge, the combined approach of methods used in this paper has not been previously applied to hyperspectral imaging analysis for interpretation and classification in the literature. The data analysis performed here aims to distinguish between four different types of plastics, some of them containing brominated flame retardants, from their near infrared hyperspectral images. The results showed that the method approach used here can be successfully used for unsupervised classification. A comparison of validation approaches, especially leave-one-out cross-validation and regions of interest scheme validation is also evaluated.

Economic evaluation of private power production under uncertainties

Energy Technology Data Exchange (ETDEWEB)

Weiguo Xing; Wu, F.F. [University of Hong Kong (China). Centre for Electrical Energy Systems

2003-02-01

Private power production is becoming an increasingly important source of electricity generation. In developing countries, build-operate-transfer (BOT) arrangement has emerged as a dominant form of private investment. Pricing private power production at its avoided cost is the breakeven point for the utility in economic evaluation, and uncertainties must be taken into account. In this paper, an approach of calculating the breakeven cost to the utility of a BOT power plant whose contract lasts for 10-25 years is proposed. The proposed approach requires the computation of production costs from long-term generation expansion planning (GEP) under future uncertainties. To facilitate the inclusion of constraints introduced by BOT plants in GEP and uncertainties, a genetic algorithm method is utilized in GEP. The breakeven cost is a useful measure in the economic evaluation of BOT power plants. An example is presented to illustrate the economic evaluation of BOT plants using the concept of breakeven cost.(author)

Uncertainty Estimates in Cold Critical Eigenvalue Predictions

International Nuclear Information System (INIS)

Karve, Atul A.; Moore, Brian R.; Mills, Vernon W.; Marrotte, Gary N.

2005-01-01

A recent cycle of a General Electric boiling water reactor performed two beginning-of-cycle local cold criticals. The eigenvalues estimated by the core simulator were 0.99826 and 1.00610. The large spread in them (= 0.00784) is a source of concern, and it is studied here. An analysis process is developed using statistical techniques, where first a transfer function relating the core observable Y (eigenvalue) to various factors (X's) is established. Engineering judgment is used to recognize the best candidates for X's. They are identified as power-weighted assembly k ∞ 's of selected assemblies around the withdrawn rods. These are a small subset of many X's that could potentially influence Y. However, the intention here is not to do a comprehensive study by accounting for all the X's. Rather, the scope is to demonstrate that the process developed is reasonable and to show its applicability to performing detailed studies. Variability in X's is obtained by perturbing nodal k ∞ 's since they directly influence the buckling term in the quasi-two-group diffusion equation model of the core simulator. Any perturbations introduced in them are bounded by standard well-established uncertainties. The resulting perturbations in the X's may not necessarily be directly correlated to physical attributes, but they encompass numerous biases and uncertainties credited to input and modeling uncertainties. The 'vital few' from the 'unimportant many' X's are determined, and then they are subgrouped according to assembly type, location, exposure, and control rod insertion. The goal is to study how the subgroups influence Y in order to have a better understanding of the variability observed in it

Uncertainty in reliability estimation : when do we know everything we know?

NARCIS (Netherlands)

Houben, M.J.H.A.; Sonnemans, P.J.M.; Newby, M.J.; Bris, R.; Guedes Soares, C.; Martorell, S.

2009-01-01

In this paperwe demonstrate the use of an adapted GroundedTheory approach through interviews and their analysis to determine explicit uncertainty (known unknowns) for reliability estimation in the early phases of product development.We have applied the adapted Grounded Theory approach in a case

Uncertainty Evaluation of Residential Central Air-conditioning Test System

Science.gov (United States)

Li, Haoxue

2018-04-01

According to national standards, property tests of air-conditioning are required. However, test results could be influenced by the precision of apparatus or measure errors. Therefore, uncertainty evaluation of property tests should be conducted. In this paper, the uncertainties are calculated on the property tests of Xinfei13.6 kW residential central air-conditioning. The evaluation result shows that the property tests are credible.

Evaluating a multispecies adaptive management framework: Must uncertainty impede effective decision-making?

Science.gov (United States)

Smith, David R.; McGowan, Conor P.; Daily, Jonathan P.; Nichols, James D.; Sweka, John A.; Lyons, James E.

2013-01-01

Application of adaptive management to complex natural resource systems requires careful evaluation to ensure that the process leads to improved decision-making. As part of that evaluation, adaptive policies can be compared with alternative nonadaptive management scenarios. Also, the value of reducing structural (ecological) uncertainty to achieving management objectives can be quantified.A multispecies adaptive management framework was recently adopted by the Atlantic States Marine Fisheries Commission for sustainable harvest of Delaware Bay horseshoe crabs Limulus polyphemus, while maintaining adequate stopover habitat for migrating red knots Calidris canutus rufa, the focal shorebird species. The predictive model set encompassed the structural uncertainty in the relationships between horseshoe crab spawning, red knot weight gain and red knot vital rates. Stochastic dynamic programming was used to generate a state-dependent strategy for harvest decisions given that uncertainty. In this paper, we employed a management strategy evaluation approach to evaluate the performance of this adaptive management framework. Active adaptive management was used by including model weights as state variables in the optimization and reducing structural uncertainty by model weight updating.We found that the value of information for reducing structural uncertainty is expected to be low, because the uncertainty does not appear to impede effective management. Harvest policy responded to abundance levels of both species regardless of uncertainty in the specific relationship that generated those abundances. Thus, the expected horseshoe crab harvest and red knot abundance were similar when the population generating model was uncertain or known, and harvest policy was robust to structural uncertainty as specified.Synthesis and applications. The combination of management strategy evaluation with state-dependent strategies from stochastic dynamic programming was an informative approach to

Reduced uncertainty of regional scale CLM predictions of net carbon fluxes and leaf area indices with estimated plant-specific parameters

Science.gov (United States)

Post, Hanna; Hendricks Franssen, Harrie-Jan; Han, Xujun; Baatz, Roland; Montzka, Carsten; Schmidt, Marius; Vereecken, Harry

2016-04-01

Reliable estimates of carbon fluxes and states at regional scales are required to reduce uncertainties in regional carbon balance estimates and to support decision making in environmental politics. In this work the Community Land Model version 4.5 (CLM4.5-BGC) was applied at a high spatial resolution (1 km2) for the Rur catchment in western Germany. In order to improve the model-data consistency of net ecosystem exchange (NEE) and leaf area index (LAI) for this study area, five plant functional type (PFT)-specific CLM4.5-BGC parameters were estimated with time series of half-hourly NEE data for one year in 2011/2012, using the DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm, a Markov Chain Monte Carlo (MCMC) approach. The parameters were estimated separately for four different plant functional types (needleleaf evergreen temperate tree, broadleaf deciduous temperate tree, C3-grass and C3-crop) at four different sites. The four sites are located inside or close to the Rur catchment. We evaluated modeled NEE for one year in 2012/2013 with NEE measured at seven eddy covariance sites in the catchment, including the four parameter estimation sites. Modeled LAI was evaluated by means of LAI derived from remotely sensed RapidEye images of about 18 days in 2011/2012. Performance indices were based on a comparison between measurements and (i) a reference run with CLM default parameters, and (ii) a 60 instance CLM ensemble with parameters sampled from the DREAM posterior probability density functions (pdfs). The difference between the observed and simulated NEE sum reduced 23% if estimated parameters instead of default parameters were used as input. The mean absolute difference between modeled and measured LAI was reduced by 59% on average. Simulated LAI was not only improved in terms of the absolute value but in some cases also in terms of the timing (beginning of vegetation onset), which was directly related to a substantial improvement of the NEE estimates in

Analysis of uncertainties in a probabilistic seismic hazard estimation, example for France

International Nuclear Information System (INIS)

Beauval, C.

2003-12-01

This thesis proposes a new methodology that allows to pinpoint the key parameters that control probabilistic seismic hazard assessment (PSHA) and at the same time to quantify the impact of these parameters uncertainties on hazard estimates. Cornell-McGuire's method is used here. First, uncertainties on magnitude and location determinations are modeled and quantified: resulting variability on hazard estimates ranges between 5% and 25% (=COV), depending on the site and the return period. An impact study is then performed, in order to determine the hierarchy between the impacts on hazard of the choices of four other parameters: intensity-magnitude correlation, minimum and maximum magnitudes, the truncation of the attenuation relationship. The results at 34 Hz (PGA) indicate that the maximum magnitude is the less influent parameter (from 100 to 10000 years); whereas the intensity-magnitude correlation and the truncation of ground motion predictions (>2σ) are the controlling parameters at all return periods (up to 30% decrease each at 10000 years). An increase in the minimum magnitude contributing to the hazard, from 3.5 to 4.5, can also produce non-negligible impacts at small return periods (up to 20% decrease of hazard results at 475 years). Finally, the overall variability on hazard estimates due to the combined choices of the four parameters can reach up to 30% (COV, at 34 Hz). For lower frequencies (<5 Hz), the overall variability increases and maximum magnitude becomes a controlling parameter. Therefore, variability of estimates due to catalog uncertainties and to the choices of these four parameters must be taken into account in all probabilistic seismic hazard studies in France. To reduce variability in hazard estimates, future research should concentrate on the elaboration of an appropriate intensity- magnitude correlation, as well as on a more realistic way of taking into account ground motion dispersion. (author)

Application of a virtual coordinate measuring machine for measurement uncertainty estimation of aspherical lens parameters

International Nuclear Information System (INIS)

Küng, Alain; Meli, Felix; Nicolet, Anaïs; Thalmann, Rudolf

2014-01-01

Tactile ultra-precise coordinate measuring machines (CMMs) are very attractive for accurately measuring optical components with high slopes, such as aspheres. The METAS µ-CMM, which exhibits a single point measurement repeatability of a few nanometres, is routinely used for measurement services of microparts, including optical lenses. However, estimating the measurement uncertainty is very demanding. Because of the many combined influencing factors, an analytic determination of the uncertainty of parameters that are obtained by numerical fitting of the measured surface points is almost impossible. The application of numerical simulation (Monte Carlo methods) using a parametric fitting algorithm coupled with a virtual CMM based on a realistic model of the machine errors offers an ideal solution to this complex problem: to each measurement data point, a simulated measurement variation calculated from the numerical model of the METAS µ-CMM is added. Repeated several hundred times, these virtual measurements deliver the statistical data for calculating the probability density function, and thus the measurement uncertainty for each parameter. Additionally, the eventual cross-correlation between parameters can be analyzed. This method can be applied for the calibration and uncertainty estimation of any parameter of the equation representing a geometric element. In this article, we present the numerical simulation model of the METAS µ-CMM and the application of a Monte Carlo method for the uncertainty estimation of measured asphere parameters. (paper)

Best-estimate reactor core monitor using state feedback strategies to resolve uncertainties

International Nuclear Information System (INIS)

Martin, R.P.

1997-01-01

The development and demonstration of a new algorithm for quantifying uncertainty in best-estimate simulation codes has been investigated. Demonstration is given by way of a prototype reactor core monitor. The architecture of this monitor integrates a distributed parameter estimation technique and the infrastructure required to support this control theory-based algorithm into a production-grade best-estimate simulation code. The Kalman filter with the sequential least-squares parameter estimation algorithm has been extended for application into the computational environment of a best-estimate simulation code, i.e., RELAP5/DOE. In control system terminology this configuration can be thought of as a best-estimate observer

BOOK REVIEW: Evaluating the Measurement Uncertainty: Fundamentals and practical guidance

Science.gov (United States)

Lira, Ignacio

2003-08-01

Evaluating the Measurement Uncertainty is a book written for anyone who makes and reports measurements. It attempts to fill the gaps in the ISO Guide to the Expression of Uncertainty in Measurement, or the GUM, and does a pretty thorough job. The GUM was written with the intent of being applicable by all metrologists, from the shop floor to the National Metrology Institute laboratory; however, the GUM has often been criticized for its lack of user-friendliness because it is primarily filled with statements, but with little explanation. Evaluating the Measurement Uncertainty gives lots of explanations. It is well written and makes use of many good figures and numerical examples. Also important, this book is written by a metrologist from a National Metrology Institute, and therefore up-to-date ISO rules, style conventions and definitions are correctly used and supported throughout. The author sticks very closely to the GUM in topical theme and with frequent reference, so readers who have not read GUM cover-to-cover may feel as if they are missing something. The first chapter consists of a reprinted lecture by T J Quinn, Director of the Bureau International des Poids et Mesures (BIPM), on the role of metrology in today's world. It is an interesting and informative essay that clearly outlines the importance of metrology in our modern society, and why accurate measurement capability, and by definition uncertainty evaluation, should be so important. Particularly interesting is the section on the need for accuracy rather than simply reproducibility. Evaluating the Measurement Uncertainty then begins at the beginning, with basic concepts and definitions. The third chapter carefully introduces the concept of standard uncertainty and includes many derivations and discussion of probability density functions. The author also touches on Monte Carlo methods, calibration correction quantities, acceptance intervals or guardbanding, and many other interesting cases. The book goes

A formal statistical approach to representing uncertainty in rainfall-runoff modelling with focus on residual analysis and probabilistic output evaluation - Distinguishing simulation and prediction

DEFF Research Database (Denmark)

Breinholt, Anders; Møller, Jan Kloppenborg; Madsen, Henrik

2012-01-01

While there seems to be consensus that hydrological model outputs should be accompanied with an uncertainty estimate the appropriate method for uncertainty estimation is not agreed upon and a debate is ongoing between advocators of formal statistical methods who consider errors as stochastic...... and GLUE advocators who consider errors as epistemic, arguing that the basis of formal statistical approaches that requires the residuals to be stationary and conform to a statistical distribution is unrealistic. In this paper we take a formal frequentist approach to parameter estimation and uncertainty...... necessary but the statistical assumptions were nevertheless not 100% justified. The residual analysis showed that significant autocorrelation was present for all simulation models. We believe users of formal approaches to uncertainty evaluation within hydrology and within environmental modelling in general...

Interlaboratory analytical performance studies; a way to estimate measurement uncertainty

Directory of Open Access Journals (Sweden)

El¿bieta £ysiak-Pastuszak

2004-09-01

Full Text Available Comparability of data collected within collaborative programmes became the key challenge of analytical chemistry in the 1990s, including monitoring of the marine environment. To obtain relevant and reliable data, the analytical process has to proceed under a well-established Quality Assurance (QA system with external analytical proficiency tests as an inherent component. A programme called Quality Assurance in Marine Monitoring in Europe (QUASIMEME was established in 1993 and evolved over the years as the major provider of QA proficiency tests for nutrients, trace metals and chlorinated organic compounds in marine environment studies. The article presents an evaluation of results obtained in QUASIMEME Laboratory Performance Studies by the monitoring laboratory of the Institute of Meteorology and Water Management (Gdynia, Poland in exercises on nutrient determination in seawater. The measurement uncertainty estimated from routine internal quality control measurements and from results of analytical performance exercises is also presented in the paper.

Uncertainties related to the fault tree reliability data

International Nuclear Information System (INIS)

Apostol, Minodora; Nitoi, Mirela; Farcasiu, M.

2003-01-01

Uncertainty analyses related to the fault trees evaluate the system variability which appears from the uncertainties of the basic events probabilities. Having a logical model which describes a system, to obtain outcomes means to evaluate it, using estimations for each basic event of the model. If the model has basic events that incorporate uncertainties, then the results of the model should incorporate the uncertainties of the events. Uncertainties estimation in the final result of the fault tree means first the uncertainties evaluation for the basic event probabilities and then combination of these uncertainties, to calculate the top event uncertainty. To calculate the propagating uncertainty, a knowledge of the probability density function as well as the range of possible values of the basic event probabilities is required. The following data are defined, using suitable probability density function: the components failure rates; the human error probabilities; the initiating event frequencies. It was supposed that the possible value distribution of the basic event probabilities is given by the lognormal probability density function. To know the range of possible value of the basic event probabilities, the error factor or the uncertainty factor is required. The aim of this paper is to estimate the error factor for the failure rates and for the human errors probabilities from the reliability data base used in Cernavoda Probabilistic Safety Evaluation. The top event chosen as an example is FEED3, from the Pressure and Inventory Control System. The quantitative evaluation of this top event was made by using EDFT code, developed in Institute for Nuclear Research Pitesti (INR). It was supposed that the error factors for the component failures are the same as for the failure rates. Uncertainty analysis was made with INCERT application, which uses the moment method and Monte Carlo method. The reliability data base used at INR Pitesti does not contain the error factors (ef

Method for estimating effects of unknown correlations in spectral irradiance data on uncertainties of spectrally integrated colorimetric quantities

Science.gov (United States)

Kärhä, Petri; Vaskuri, Anna; Mäntynen, Henrik; Mikkonen, Nikke; Ikonen, Erkki

2017-08-01

Spectral irradiance data are often used to calculate colorimetric properties, such as color coordinates and color temperatures of light sources by integration. The spectral data may contain unknown correlations that should be accounted for in the uncertainty estimation. We propose a new method for estimating uncertainties in such cases. The method goes through all possible scenarios of deviations using Monte Carlo analysis. Varying spectral error functions are produced by combining spectral base functions, and the distorted spectra are used to calculate the colorimetric quantities. Standard deviations of the colorimetric quantities at different scenarios give uncertainties assuming no correlations, uncertainties assuming full correlation, and uncertainties for an unfavorable case of unknown correlations, which turn out to be a significant source of uncertainty. With 1% standard uncertainty in spectral irradiance, the expanded uncertainty of the correlated color temperature of a source corresponding to the CIE Standard Illuminant A may reach as high as 37.2 K in unfavorable conditions, when calculations assuming full correlation give zero uncertainty, and calculations assuming no correlations yield the expanded uncertainties of 5.6 K and 12.1 K, with wavelength steps of 1 nm and 5 nm used in spectral integrations, respectively. We also show that there is an absolute limit of 60.2 K in the error of the correlated color temperature for Standard Illuminant A when assuming 1% standard uncertainty in the spectral irradiance. A comparison of our uncorrelated uncertainties with those obtained using analytical methods by other research groups shows good agreement. We re-estimated the uncertainties for the colorimetric properties of our 1 kW photometric standard lamps using the new method. The revised uncertainty of color temperature is a factor of 2.5 higher than the uncertainty assuming no correlations.

Opportunities and challenges for evaluating precipitation estimates during GPM mission

Energy Technology Data Exchange (ETDEWEB)

Amitai, E. [George Mason Univ. and NASA Goddard Space Flight Center, Greenbelt, MD (United States); NASA Goddard Space Flight Center, Greenbelt, MD (United States); Llort, X.; Sempere-Torres, D. [GRAHI/Univ. Politecnica de Catalunya, Barcelona (Spain)

2006-10-15

Data assimilation in conjunction with numerical weather prediction and a variety of hydrologic applications now depend on satellite observations of precipitation. However, providing values of precipitation is not sufficient unless they are accompanied by the associated uncertainty estimates. The main approach of quantifying satellite precipitation uncertainties generally requires establishment of reliable uncertainty estimates for the ground validation rainfall products. This paper discusses several of the relevant validation concepts evolving from the tropical rainfall measuring mission (TRMM) era to the global precipitation measurement mission (GPM) era in the context of determining and reducing uncertainties of ground and space-based radar rainfall estimates. From comparisons of probability distribution functions of rain rates derived from TRMM precipitation radar and co-located ground based radar data - using the new NASA TRMM radar rainfall products (version 6) - this paper provides (1) a brief review of the importance of comparing pdfs of rain rate for statistical and physical verification of space-borne radar estimates of precipitation; (2) a brief review of how well the ground validation estimates compare to the TRMM radar retrieved estimates; and (3) discussion on opportunities and challenges to determine and reduce the uncertainties in space-based and ground-based radar estimates of rain rate distributions. (orig.)

Preliminary uncertainty analysis for the doses estimated using the Techa River dosimetry system - 2000

International Nuclear Information System (INIS)

Napier, Bruce A.; Shagina, N B.; Degteva, M O.; Tolstykh, E I.; Vorobiova, M I.; Anspaugh, L R.

2000-01-01

The Mayak Production Association (MPA) was the first facility in the former Soviet Union for the production of plutonium. As a result of failures in the technological processes in the late 1940's and early 1950's, members of the public were exposed via discharge of about 1017 Bq of liquid wastes into the Techa River (1949-1956). Residents of many villages downstream on the Techa River were exposed via a variety of pathways; the more significant included drinking of water from the river and external gamma exposure due to proximity to sediments and shoreline. The specific aim of this project is to enhance the reconstruction of external and internal radiation doses for individuals in the Extended Techa River Cohort. The purpose of this paper is to present the approaches being used to evaluate the uncertainty in the calculated individual doses and to provide example and representative results of the uncertainty analyses. The magnitude of the uncertainties varies depending on location and time of individual exposure, but the results from reference-individual calculations indicate that for external doses, the range of uncertainty is about factors of four to five. For internal doses, the range of uncertainty depends on village of residence, which is actually a surrogate for source of drinking water. For villages with single sources of drinking water (river or well), the ratio of the 97.5th percentile-to 2.5th percentile estimates can be a factor of 20 to 30. For villages with mixed sources of drinking water (river and well), the ratio of the range can be over two orders of magnitude

ON THE ESTIMATION OF RANDOM UNCERTAINTIES OF STAR FORMATION HISTORIES

Energy Technology Data Exchange (ETDEWEB)

Dolphin, Andrew E., E-mail: adolphin@raytheon.com [Raytheon Company, Tucson, AZ, 85734 (United States)

2013-09-20

The standard technique for measurement of random uncertainties of star formation histories (SFHs) is the bootstrap Monte Carlo, in which the color-magnitude diagram (CMD) is repeatedly resampled. The variation in SFHs measured from the resampled CMDs is assumed to represent the random uncertainty in the SFH measured from the original data. However, this technique systematically and significantly underestimates the uncertainties for times in which the measured star formation rate is low or zero, leading to overly (and incorrectly) high confidence in that measurement. This study proposes an alternative technique, the Markov Chain Monte Carlo (MCMC), which samples the probability distribution of the parameters used in the original solution to directly estimate confidence intervals. While the most commonly used MCMC algorithms are incapable of adequately sampling a probability distribution that can involve thousands of highly correlated dimensions, the Hybrid Monte Carlo algorithm is shown to be extremely effective and efficient for this particular task. Several implementation details, such as the handling of implicit priors created by parameterization of the SFH, are discussed in detail.

ON THE ESTIMATION OF RANDOM UNCERTAINTIES OF STAR FORMATION HISTORIES

International Nuclear Information System (INIS)

Dolphin, Andrew E.

2013-01-01

The standard technique for measurement of random uncertainties of star formation histories (SFHs) is the bootstrap Monte Carlo, in which the color-magnitude diagram (CMD) is repeatedly resampled. The variation in SFHs measured from the resampled CMDs is assumed to represent the random uncertainty in the SFH measured from the original data. However, this technique systematically and significantly underestimates the uncertainties for times in which the measured star formation rate is low or zero, leading to overly (and incorrectly) high confidence in that measurement. This study proposes an alternative technique, the Markov Chain Monte Carlo (MCMC), which samples the probability distribution of the parameters used in the original solution to directly estimate confidence intervals. While the most commonly used MCMC algorithms are incapable of adequately sampling a probability distribution that can involve thousands of highly correlated dimensions, the Hybrid Monte Carlo algorithm is shown to be extremely effective and efficient for this particular task. Several implementation details, such as the handling of implicit priors created by parameterization of the SFH, are discussed in detail

Uncertainty Model for Total Solar Irradiance Estimation on Australian Rooftops

Science.gov (United States)

Al-Saadi, Hassan; Zivanovic, Rastko; Al-Sarawi, Said

2017-11-01

The installations of solar panels on Australian rooftops have been in rise for the last few years, especially in the urban areas. This motivates academic researchers, distribution network operators and engineers to accurately address the level of uncertainty resulting from grid-connected solar panels. The main source of uncertainty is the intermittent nature of radiation, therefore, this paper presents a new model to estimate the total radiation incident on a tilted solar panel. Where a probability distribution factorizes clearness index, the model is driven upon clearness index with special attention being paid for Australia with the utilization of best-fit-correlation for diffuse fraction. The assessment of the model validity is achieved with the adoption of four goodness-of-fit techniques. In addition, the Quasi Monte Carlo and sparse grid methods are used as sampling and uncertainty computation tools, respectively. High resolution data resolution of solar irradiations for Adelaide city were used for this assessment, with an outcome indicating a satisfactory agreement between actual data variation and model.

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)

Model uncertainty of various settlement estimation methods in shallow tunnels excavation; case study: Qom subway tunnel

Science.gov (United States)

Khademian, Amir; Abdollahipour, Hamed; Bagherpour, Raheb; Faramarzi, Lohrasb

2017-10-01

In addition to the numerous planning and executive challenges, underground excavation in urban areas is always followed by certain destructive effects especially on the ground surface; ground settlement is the most important of these effects for which estimation there exist different empirical, analytical and numerical methods. Since geotechnical models are associated with considerable model uncertainty, this study characterized the model uncertainty of settlement estimation models through a systematic comparison between model predictions and past performance data derived from instrumentation. To do so, the amount of surface settlement induced by excavation of the Qom subway tunnel was estimated via empirical (Peck), analytical (Loganathan and Poulos) and numerical (FDM) methods; the resulting maximum settlement value of each model were 1.86, 2.02 and 1.52 cm, respectively. The comparison of these predicted amounts with the actual data from instrumentation was employed to specify the uncertainty of each model. The numerical model outcomes, with a relative error of 3.8%, best matched the reality and the analytical method, with a relative error of 27.8%, yielded the highest level of model uncertainty.

Analysis of uncertainties in the estimates of nitrous oxide and methane emissions in the UK's greenhouse gas inventory for agriculture

Science.gov (United States)

Milne, Alice E.; Glendining, Margaret J.; Bellamy, Pat; Misselbrook, Tom; Gilhespy, Sarah; Rivas Casado, Monica; Hulin, Adele; van Oijen, Marcel; Whitmore, Andrew P.

2014-01-01

The UK's greenhouse gas inventory for agriculture uses a model based on the IPCC Tier 1 and Tier 2 methods to estimate the emissions of methane and nitrous oxide from agriculture. The inventory calculations are disaggregated at country level (England, Wales, Scotland and Northern Ireland). Before now, no detailed assessment of the uncertainties in the estimates of emissions had been done. We used Monte Carlo simulation to do such an analysis. We collated information on the uncertainties of each of the model inputs. The uncertainties propagate through the model and result in uncertainties in the estimated emissions. Using a sensitivity analysis, we found that in England and Scotland the uncertainty in the emission factor for emissions from N inputs (EF1) affected uncertainty the most, but that in Wales and Northern Ireland, the emission factor for N leaching and runoff (EF5) had greater influence. We showed that if the uncertainty in any one of these emission factors is reduced by 50%, the uncertainty in emissions of nitrous oxide reduces by 10%. The uncertainty in the estimate for the emissions of methane emission factors for enteric fermentation in cows and sheep most affected the uncertainty in methane emissions. When inventories are disaggregated (as that for the UK is) correlation between separate instances of each emission factor will affect the uncertainty in emissions. As more countries move towards inventory models with disaggregation, it is important that the IPCC give firm guidance on this topic.

Impacts of uncertainties in weather and streamflow observations in calibration and evaluation of an elevation distributed HBV-model

Science.gov (United States)

Engeland, K.; Steinsland, I.; Petersen-Øverleir, A.; Johansen, S.

2012-04-01

The aim of this study is to assess the uncertainties in streamflow simulations when uncertainties in both observed inputs (precipitation and temperature) and streamflow observations used in the calibration of the hydrological model are explicitly accounted for. To achieve this goal we applied the elevation distributed HBV model operating on daily time steps to a small catchment in high elevation in Southern Norway where the seasonal snow cover is important. The uncertainties in precipitation inputs were quantified using conditional simulation. This procedure accounts for the uncertainty related to the density of the precipitation network, but neglects uncertainties related to measurement bias/errors and eventual elevation gradients in precipitation. The uncertainties in temperature inputs were quantified using a Bayesian temperature interpolation procedure where the temperature lapse rate is re-estimated every day. The uncertainty in the lapse rate was accounted for whereas the sampling uncertainty related to network density was neglected. For every day a random sample of precipitation and temperature inputs were drawn to be applied as inputs to the hydrologic model. The uncertainties in observed streamflow were assessed based on the uncertainties in the rating curve model. A Bayesian procedure was applied to estimate the probability for rating curve models with 1 to 3 segments and the uncertainties in their parameters. This method neglects uncertainties related to errors in observed water levels. Note that one rating curve was drawn to make one realisation of a whole time series of streamflow, thus the rating curve errors lead to a systematic bias in the streamflow observations. All these uncertainty sources were linked together in both calibration and evaluation of the hydrologic model using a DREAM based MCMC routine. Effects of having less information (e.g. missing one streamflow measurement for defining the rating curve or missing one precipitation station

Uncertainties in the estimation of specific absorption rate during radiofrequency alternating magnetic field induced non-adiabatic heating of ferrofluids

Science.gov (United States)

Lahiri, B. B.; Ranoo, Surojit; Philip, John

2017-11-01

Magnetic fluid hyperthermia (MFH) is becoming a viable cancer treatment methodology where the alternating magnetic field induced heating of magnetic fluid is utilized for ablating the cancerous cells or making them more susceptible to the conventional treatments. The heating efficiency in MFH is quantified in terms of specific absorption rate (SAR), which is defined as the heating power generated per unit mass. In majority of the experimental studies, SAR is evaluated from the temperature rise curves, obtained under non-adiabatic experimental conditions, which is prone to various thermodynamic uncertainties. A proper understanding of the experimental uncertainties and its remedies is a prerequisite for obtaining accurate and reproducible SAR. Here, we study the thermodynamic uncertainties associated with peripheral heating, delayed heating, heat loss from the sample and spatial variation in the temperature profile within the sample. Using first order approximations, an adiabatic reconstruction protocol for the measured temperature rise curves is developed for SAR estimation, which is found to be in good agreement with those obtained from the computationally intense slope corrected method. Our experimental findings clearly show that the peripheral and delayed heating are due to radiation heat transfer from the heating coils and slower response time of the sensor, respectively. Our results suggest that the peripheral heating is linearly proportional to the sample area to volume ratio and coil temperature. It is also observed that peripheral heating decreases in presence of a non-magnetic insulating shielding. The delayed heating is found to contribute up to ~25% uncertainties in SAR values. As the SAR values are very sensitive to the initial slope determination method, explicit mention of the range of linear regression analysis is appropriate to reproduce the results. The effect of sample volume to area ratio on linear heat loss rate is systematically studied and the

Uncertainties in the estimation of specific absorption rate during radiofrequency alternating magnetic field induced non-adiabatic heating of ferrofluids

International Nuclear Information System (INIS)

Lahiri, B B; Ranoo, Surojit; Philip, John

2017-01-01

Magnetic fluid hyperthermia (MFH) is becoming a viable cancer treatment methodology where the alternating magnetic field induced heating of magnetic fluid is utilized for ablating the cancerous cells or making them more susceptible to the conventional treatments. The heating efficiency in MFH is quantified in terms of specific absorption rate (SAR), which is defined as the heating power generated per unit mass. In majority of the experimental studies, SAR is evaluated from the temperature rise curves, obtained under non-adiabatic experimental conditions, which is prone to various thermodynamic uncertainties. A proper understanding of the experimental uncertainties and its remedies is a prerequisite for obtaining accurate and reproducible SAR. Here, we study the thermodynamic uncertainties associated with peripheral heating, delayed heating, heat loss from the sample and spatial variation in the temperature profile within the sample. Using first order approximations, an adiabatic reconstruction protocol for the measured temperature rise curves is developed for SAR estimation, which is found to be in good agreement with those obtained from the computationally intense slope corrected method. Our experimental findings clearly show that the peripheral and delayed heating are due to radiation heat transfer from the heating coils and slower response time of the sensor, respectively. Our results suggest that the peripheral heating is linearly proportional to the sample area to volume ratio and coil temperature. It is also observed that peripheral heating decreases in presence of a non-magnetic insulating shielding. The delayed heating is found to contribute up to ∼25% uncertainties in SAR values. As the SAR values are very sensitive to the initial slope determination method, explicit mention of the range of linear regression analysis is appropriate to reproduce the results. The effect of sample volume to area ratio on linear heat loss rate is systematically studied and

Model uncertainty and multimodel inference in reliability estimation within a longitudinal framework.

Science.gov (United States)

Alonso, Ariel; Laenen, Annouschka

2013-05-01

Laenen, Alonso, and Molenberghs (2007) and Laenen, Alonso, Molenberghs, and Vangeneugden (2009) proposed a method to assess the reliability of rating scales in a longitudinal context. The methodology is based on hierarchical linear models, and reliability coefficients are derived from the corresponding covariance matrices. However, finding a good parsimonious model to describe complex longitudinal data is a challenging task. Frequently, several models fit the data equally well, raising the problem of model selection uncertainty. When model uncertainty is high one may resort to model averaging, where inferences are based not on one but on an entire set of models. We explored the use of different model building strategies, including model averaging, in reliability estimation. We found that the approach introduced by Laenen et al. (2007, 2009) combined with some of these strategies may yield meaningful results in the presence of high model selection uncertainty and when all models are misspecified, in so far as some of them manage to capture the most salient features of the data. Nonetheless, when all models omit prominent regularities in the data, misleading results may be obtained. The main ideas are further illustrated on a case study in which the reliability of the Hamilton Anxiety Rating Scale is estimated. Importantly, the ambit of model selection uncertainty and model averaging transcends the specific setting studied in the paper and may be of interest in other areas of psychometrics. © 2012 The British Psychological Society.

Estimating statistical uncertainty of Monte Carlo efficiency-gain in the context of a correlated sampling Monte Carlo code for brachytherapy treatment planning with non-normal dose distribution.

Science.gov (United States)

Mukhopadhyay, Nitai D; Sampson, Andrew J; Deniz, Daniel; Alm Carlsson, Gudrun; Williamson, Jeffrey; Malusek, Alexandr

2012-01-01

Correlated sampling Monte Carlo methods can shorten computing times in brachytherapy treatment planning. Monte Carlo efficiency is typically estimated via efficiency gain, defined as the reduction in computing time by correlated sampling relative to conventional Monte Carlo methods when equal statistical uncertainties have been achieved. The determination of the efficiency gain uncertainty arising from random effects, however, is not a straightforward task specially when the error distribution is non-normal. The purpose of this study is to evaluate the applicability of the F distribution and standardized uncertainty propagation methods (widely used in metrology to estimate uncertainty of physical measurements) for predicting confidence intervals about efficiency gain estimates derived from single Monte Carlo runs using fixed-collision correlated sampling in a simplified brachytherapy geometry. A bootstrap based algorithm was used to simulate the probability distribution of the efficiency gain estimates and the shortest 95% confidence interval was estimated from this distribution. It was found that the corresponding relative uncertainty was as large as 37% for this particular problem. The uncertainty propagation framework predicted confidence intervals reasonably well; however its main disadvantage was that uncertainties of input quantities had to be calculated in a separate run via a Monte Carlo method. The F distribution noticeably underestimated the confidence interval. These discrepancies were influenced by several photons with large statistical weights which made extremely large contributions to the scored absorbed dose difference. The mechanism of acquiring high statistical weights in the fixed-collision correlated sampling method was explained and a mitigation strategy was proposed. Copyright © 2011 Elsevier Ltd. All rights reserved.

Development of electrical efficiency measurement techniques for 10 kW-class SOFC system: Part II. Uncertainty estimation

International Nuclear Information System (INIS)

Tanaka, Yohei; Momma, Akihiko; Kato, Ken; Negishi, Akira; Takano, Kiyonami; Nozaki, Ken; Kato, Tohru

2009-01-01

Uncertainty of electrical efficiency measurement was investigated for a 10 kW-class SOFC system using town gas. Uncertainty of heating value measured by the gas chromatography method on a mole base was estimated as ±0.12% at 95% level of confidence. Micro-gas chromatography with/without CH 4 quantification may be able to reduce uncertainty of measurement. Calibration and uncertainty estimation methods are proposed for flow-rate measurement of town gas with thermal mass-flow meters or controllers. By adequate calibrations for flowmeters, flow rate of town gas or natural gas at 35 standard litters per minute can be measured within relative uncertainty ±1.0% at 95 % level of confidence. Uncertainty of power measurement can be as low as ±0.14% when a precise wattmeter is used and calibrated properly. It is clarified that electrical efficiency for non-pressurized 10 kW-class SOFC systems can be measured within ±1.0% relative uncertainty at 95% level of confidence with the developed techniques when the SOFC systems are operated relatively stably

Uncertainty in CH4 and N2O emission estimates from a managed fen meadow using EC measurements

International Nuclear Information System (INIS)

Kroon, P.S.; Hensen, A.; Van 't Veen, W.H.; Vermeulen, A.T.; Jonker, H.

2009-02-01

The overall uncertainty in annual flux estimates derived from chamber measurements may be as high as 50% due to the temporal and spatial variability in the fluxes. As even a large number of chamber plots still cover typically less than 1% of the total field area, the field-scale integrated emission necessarily remains a matter of speculation. High frequency micrometeorological methods are a good option for obtaining integrated estimates on a hectare scale with a continuous coverage in time. Instrumentation is now becoming available that meets the requirements for CH4 and N2O eddy covariance (EC) measurements. A system consisting of a quantum cascade laser (QCL) spectrometer and a sonic anemometer has recently been proven to be suitable for performing EC measurements. This study analyses the EC flux measurements of CH4 and N2O and its corrections, like calibration, Webb-correction, and corrections for high and low frequency losses, and assesses the magnitude of the uncertainties associated with the precision of the measurement instruments, measurement set-up and the methodology. The uncertainty of one single EC flux measurement, a daily, monthly and 3-monthly average EC flux is estimated. In addition, the cumulative emission of C-CH4 and N-N2O and their uncertainties are determined over several fertilizing events at a dairy farm site in the Netherlands. These fertilizing events are selected from the continuously EC flux measurements from August 2006 to September 2008. The EC flux uncertainties are compared by the overall uncertainty in annual flux estimates derived from chamber measurements. It will be shown that EC flux measurements can decrease the overall uncertainty in annual flux estimates

Uncertainty in CH4 and N2O emission estimates from a managed fen meadow using EC measurements

Energy Technology Data Exchange (ETDEWEB)

Kroon, P.S.; Hensen, A.; Van ' t Veen, W.H.; Vermeulen, A.T. [ECN Biomass, Coal and Environment, Petten (Netherlands); Jonker, H. [Delft University of Technology, Delft (Netherlands)

2009-02-15

The overall uncertainty in annual flux estimates derived from chamber measurements may be as high as 50% due to the temporal and spatial variability in the fluxes. As even a large number of chamber plots still cover typically less than 1% of the total field area, the field-scale integrated emission necessarily remains a matter of speculation. High frequency micrometeorological methods are a good option for obtaining integrated estimates on a hectare scale with a continuous coverage in time. Instrumentation is now becoming available that meets the requirements for CH4 and N2O eddy covariance (EC) measurements. A system consisting of a quantum cascade laser (QCL) spectrometer and a sonic anemometer has recently been proven to be suitable for performing EC measurements. This study analyses the EC flux measurements of CH4 and N2O and its corrections, like calibration, Webb-correction, and corrections for high and low frequency losses, and assesses the magnitude of the uncertainties associated with the precision of the measurement instruments, measurement set-up and the methodology. The uncertainty of one single EC flux measurement, a daily, monthly and 3-monthly average EC flux is estimated. In addition, the cumulative emission of C-CH4 and N-N2O and their uncertainties are determined over several fertilizing events at a dairy farm site in the Netherlands. These fertilizing events are selected from the continuously EC flux measurements from August 2006 to September 2008. The EC flux uncertainties are compared by the overall uncertainty in annual flux estimates derived from chamber measurements. It will be shown that EC flux measurements can decrease the overall uncertainty in annual flux estimates.

Estimating radar reflectivity - snowfall rate relationships and their uncertainties over Antarctica by combining disdrometer and radar observations

Science.gov (United States)

Souverijns, Niels; Gossart, Alexandra; Lhermitte, Stef; Gorodetskaya, Irina; Kneifel, Stefan; Maahn, Maximilian; Bliven, Francis; van Lipzig, Nicole

2017-04-01

The Antarctic Ice Sheet (AIS) is the largest ice body on earth, having a volume equivalent to 58.3 m global mean sea level rise. Precipitation is the dominant source term in the surface mass balance of the AIS. However, this quantity is not well constrained in both models and observations. Direct observations over the AIS are also not coherent, as they are sparse in space and time and acquisition techniques differ. As a result, precipitation observations stay mostly limited to continent-wide averages based on satellite radar observations. Snowfall rate (SR) at high temporal resolution can be derived from the ground-based radar effective reflectivity factor (Z) using information about snow particle size and shape. Here we present reflectivity snowfall rate relations (Z = aSRb) for the East Antarctic escarpment region using the measurements at the Princess Elisabeth (PE) station and an overview of their uncertainties. A novel technique is developed by combining an optical disdrometer (NASA's Precipitation Imaging Package; PIP) and a vertically pointing 24 GHz FMCW micro rain radar (Metek's MRR) in order to reduce the uncertainty in SR estimates. PIP is used to obtain information about snow particle characteristics and to get an estimate of Z, SR and the Z-SR relation. For PE, located 173 km inland, the relation equals Z = 18SR1.1. The prefactor (a) of the relation is sensitive to the median diameter of the particles. Larger particles, found closer to the coast, lead to an increase of the value of the prefactor. More inland locations, where smaller snow particles are found, obtain lower values for the prefactor. The exponent of the Z-SR relation (b) is insensitive to the median diameter of the snow particles. This dependence of the prefactor of the Z-SR relation to the particle size needs to be taken into account when converting radar reflectivities to snowfall rates over Antarctica. The uncertainty on the Z-SR relations is quantified using a bootstrapping approach

Uncertainty of Water-hammer Loads for Safety Related Systems

Energy Technology Data Exchange (ETDEWEB)

Lee, Seung Chan; Yoon, Duk Joo [Korea Hydro and Nuclear Power Co., LT., Daejeon (Korea, Republic of)

2013-10-15

In this study, the basic methodology is base on ISO GUM (Guide to the Expression of Uncertainty in Measurements). For a given gas void volumes in the discharge piping, the maximum pressure of water hammer is defined in equation. From equation, uncertainty parameter is selected as U{sub s} (superficial velocity for the specific pipe size and corresponding area) of equation. The main uncertainty parameter (U{sub s}) is estimated by measurement method and Monte Carlo simulation. Two methods are in good agreement with the extended uncertainty. Extended uncertainty of the measurement and Monte Carlo simulation is 1.30 and 1.34 respectively in 95% confidence interval. In 99% confidence interval, the uncertainties are 1.95 and 1.97 respectively. NRC Generic Letter 2008-01 requires nuclear power plant operators to evaluate the possibility of noncondensable gas accumulation for the Emergency Core Cooling System. Specially, gas accumulation can result in system pressure transient in pump discharge piping at a pump start. Consequently, this evolves into a gas water, a water-hammer event and the force imbalances on the piping segments. In this paper, MCS (Monte Carlo Simulation) method is introduced in estimating the uncertainty of water hammer. The aim is to evaluate the uncertainty of the water hammer estimation results carried out by KHNP CRI in 2013.

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

Energy Technology Data Exchange (ETDEWEB)

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

2018-02-19

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

Proof of concept and dose estimation with binary responses under model uncertainty.

Science.gov (United States)

Klingenberg, B

2009-01-30

This article suggests a unified framework for testing Proof of Concept (PoC) and estimating a target dose for the benefit of a more comprehensive, robust and powerful analysis in phase II or similar clinical trials. From a pre-specified set of candidate models, we choose the ones that best describe the observed dose-response. To decide which models, if any, significantly pick up a dose effect, we construct the permutation distribution of the minimum P-value over the candidate set. This allows us to find critical values and multiplicity adjusted P-values that control the familywise error rate of declaring any spurious effect in the candidate set as significant. Model averaging is then used to estimate a target dose. Popular single or multiple contrast tests for PoC, such as the Cochran-Armitage, Dunnett or Williams tests, are only optimal for specific dose-response shapes and do not provide target dose estimates with confidence limits. A thorough evaluation and comparison of our approach to these tests reveal that its power is as good or better in detecting a dose-response under various shapes with many more additional benefits: It incorporates model uncertainty in PoC decisions and target dose estimation, yields confidence intervals for target dose estimates and extends to more complicated data structures. We illustrate our method with the analysis of a Phase II clinical trial. Copyright (c) 2008 John Wiley & Sons, Ltd.

Analysis of uncertainties in the IAEA/WHO TLD postal dose audit system

Energy Technology Data Exchange (ETDEWEB)

Izewska, J. [Department of Nuclear Sciences and Applications, International Atomic Energy Agency, Wagramer Strasse 5, Vienna (Austria)], E-mail: j.izewska@iaea.org; Hultqvist, M. [Department of Medical Radiation Physics, Karolinska Institute, Stockholm University, Stockholm (Sweden); Bera, P. [Department of Nuclear Sciences and Applications, International Atomic Energy Agency, Wagramer Strasse 5, Vienna (Austria)

2008-02-15

The International Atomic Energy Agency (IAEA) and the World Health Organisation (WHO) operate the IAEA/WHO TLD postal dose audit programme. Thermoluminescence dosimeters (TLDs) are used as transfer devices in this programme. In the present work the uncertainties in the dose determination from TLD measurements have been evaluated. The analysis of uncertainties comprises uncertainties in the calibration coefficient of the TLD system and uncertainties in factors correcting for dose response non-linearity, fading of TL signal, energy response and influence of TLD holder. The individual uncertainties have been combined to estimate the total uncertainty in the dose evaluated from TLD measurements. The combined relative standard uncertainty in the dose determined from TLD measurements has been estimated to be 1.2% for irradiations with Co-60 {gamma}-rays and 1.6% for irradiations with high-energy X-rays. Results from irradiations by the Bureau international des poids et mesures (BIPM), Primary Standard Dosimetry Laboratories (PSDLs) and Secondary Standards Dosimetry Laboratories (SSDLs) compare favourably with the estimated uncertainties, whereas TLD results of radiotherapy centres show higher standard deviations than those derived theoretically.

Uncertainty in action-value estimation affects both action choice and learning rate of the choice behaviors of rats.

Science.gov (United States)

Funamizu, Akihiro; Ito, Makoto; Doya, Kenji; Kanzaki, Ryohei; Takahashi, Hirokazu

2012-04-01

The estimation of reward outcomes for action candidates is essential for decision making. In this study, we examined whether and how the uncertainty in reward outcome estimation affects the action choice and learning rate. We designed a choice task in which rats selected either the left-poking or right-poking hole and received a reward of a food pellet stochastically. The reward probabilities of the left and right holes were chosen from six settings (high, 100% vs. 66%; mid, 66% vs. 33%; low, 33% vs. 0% for the left vs. right holes, and the opposites) in every 20-549 trials. We used Bayesian Q-learning models to estimate the time course of the probability distribution of action values and tested if they better explain the behaviors of rats than standard Q-learning models that estimate only the mean of action values. Model comparison by cross-validation revealed that a Bayesian Q-learning model with an asymmetric update for reward and non-reward outcomes fit the choice time course of the rats best. In the action-choice equation of the Bayesian Q-learning model, the estimated coefficient for the variance of action value was positive, meaning that rats were uncertainty seeking. Further analysis of the Bayesian Q-learning model suggested that the uncertainty facilitated the effective learning rate. These results suggest that the rats consider uncertainty in action-value estimation and that they have an uncertainty-seeking action policy and uncertainty-dependent modulation of the effective learning rate. © 2012 The Authors. European Journal of Neuroscience © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

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

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

Science.gov (United States)

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

2012-12-01

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

Uncertainty and Cognitive Control

Directory of Open Access Journals (Sweden)

Faisal eMushtaq

2011-10-01

Full Text Available A growing trend of neuroimaging, behavioural and computational research has investigated the topic of outcome uncertainty in decision-making. Although evidence to date indicates that humans are very effective in learning to adapt to uncertain situations, the nature of the specific cognitive processes involved in the adaptation to uncertainty are still a matter of debate. In this article, we reviewed evidence suggesting that cognitive control processes are at the heart of uncertainty in decision-making contexts. Available evidence suggests that: (1 There is a strong conceptual overlap between the constructs of uncertainty and cognitive control; (2 There is a remarkable overlap between the neural networks associated with uncertainty and the brain networks subserving cognitive control; (3 The perception and estimation of uncertainty might play a key role in monitoring processes and the evaluation of the need for control; (4 Potential interactions between uncertainty and cognitive control might play a significant role in several affective disorders.

Regional inversion of CO2 ecosystem fluxes from atmospheric measurements. Reliability of the uncertainty estimates

Energy Technology Data Exchange (ETDEWEB)

Broquet, G.; Chevallier, F.; Breon, F.M.; Yver, C.; Ciais, P.; Ramonet, M.; Schmidt, M. [Laboratoire des Sciences du Climat et de l' Environnement, CEA-CNRS-UVSQ, UMR8212, IPSL, Gif-sur-Yvette (France); Alemanno, M. [Servizio Meteorologico dell' Aeronautica Militare Italiana, Centro Aeronautica Militare di Montagna, Monte Cimone/Sestola (Italy); Apadula, F. [Research on Energy Systems, RSE, Environment and Sustainable Development Department, Milano (Italy); Hammer, S. [Universitaet Heidelberg, Institut fuer Umweltphysik, Heidelberg (Germany); Haszpra, L. [Hungarian Meteorological Service, Budapest (Hungary); Meinhardt, F. [Federal Environmental Agency, Kirchzarten (Germany); Necki, J. [AGH University of Science and Technology, Krakow (Poland); Piacentino, S. [ENEA, Laboratory for Earth Observations and Analyses, Palermo (Italy); Thompson, R.L. [Max Planck Institute for Biogeochemistry, Jena (Germany); Vermeulen, A.T. [Energy research Centre of the Netherlands ECN, EEE-EA, Petten (Netherlands)

2013-07-01

The Bayesian framework of CO2 flux inversions permits estimates of the retrieved flux uncertainties. Here, the reliability of these theoretical estimates is studied through a comparison against the misfits between the inverted fluxes and independent measurements of the CO2 Net Ecosystem Exchange (NEE) made by the eddy covariance technique at local (few hectares) scale. Regional inversions at 0.5{sup 0} resolution are applied for the western European domain where {approx}50 eddy covariance sites are operated. These inversions are conducted for the period 2002-2007. They use a mesoscale atmospheric transport model, a prior estimate of the NEE from a terrestrial ecosystem model and rely on the variational assimilation of in situ continuous measurements of CO2 atmospheric mole fractions. Averaged over monthly periods and over the whole domain, the misfits are in good agreement with the theoretical uncertainties for prior and inverted NEE, and pass the chi-square test for the variance at the 30% and 5% significance levels respectively, despite the scale mismatch and the independence between the prior (respectively inverted) NEE and the flux measurements. The theoretical uncertainty reduction for the monthly NEE at the measurement sites is 53% while the inversion decreases the standard deviation of the misfits by 38 %. These results build confidence in the NEE estimates at the European/monthly scales and in their theoretical uncertainty from the regional inverse modelling system. However, the uncertainties at the monthly (respectively annual) scale remain larger than the amplitude of the inter-annual variability of monthly (respectively annual) fluxes, so that this study does not engender confidence in the inter-annual variations. The uncertainties at the monthly scale are significantly smaller than the seasonal variations. The seasonal cycle of the inverted fluxes is thus reliable. In particular, the CO2 sink period over the European continent likely ends later than

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

International Nuclear Information System (INIS)

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

2005-01-01

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

Estimating Uncertainties of Ship Course and Speed in Early Navigations using ICOADS3.0

Science.gov (United States)

Chan, D.; Huybers, P. J.

2017-12-01

Information on ship position and its uncertainty is potentially important for mapping out climatologists and changes in SSTs. Using the 2-hourly ship reports from the International Comprehensive Ocean Atmosphere Dataset 3.0 (ICOADS 3.0), we estimate the uncertainties of ship course, ship speed, and latitude/longitude corrections during 1870-1900. After reviewing the techniques used in early navigations, we build forward navigation model that uses dead reckoning technique, celestial latitude corrections, and chronometer longitude corrections. The modeled ship tracks exhibit jumps in longitude and latitude, when a position correction is applied. These jumps are also seen in ICOADS3.0 observations. In this model, position error at the end of each day increases following a 2D random walk; the latitudinal/longitude errors are reset when a latitude/longitude correction is applied.We fit the variance of the magnitude of latitude/longitude corrections in the observation against model outputs, and estimate that the standard deviation of uncertainty is 5.5 degree for ship course, 32% for ship speed, 22km for latitude correction, and 27km for longitude correction. The estimates here are informative priors for Bayesian methods that quantify position errors of individual tracks.

Estimation of Nonlinear Functions of State Vector for Linear Systems with Time-Delays and Uncertainties

Directory of Open Access Journals (Sweden)

Il Young Song

2015-01-01

Full Text Available This paper focuses on estimation of a nonlinear function of state vector (NFS in discrete-time linear systems with time-delays and model uncertainties. The NFS represents a multivariate nonlinear function of state variables, which can indicate useful information of a target system for control. The optimal nonlinear estimator of an NFS (in mean square sense represents a function of the receding horizon estimate and its error covariance. The proposed receding horizon filter represents the standard Kalman filter with time-delays and special initial horizon conditions described by the Lyapunov-like equations. In general case to calculate an optimal estimator of an NFS we propose using the unscented transformation. Important class of polynomial NFS is considered in detail. In the case of polynomial NFS an optimal estimator has a closed-form computational procedure. The subsequent application of the proposed receding horizon filter and nonlinear estimator to a linear stochastic system with time-delays and uncertainties demonstrates their effectiveness.

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)

Classification and moral evaluation of uncertainties in engineering modeling.

Science.gov (United States)

Murphy, Colleen; Gardoni, Paolo; Harris, Charles E

2011-09-01

Engineers must deal with risks and uncertainties as a part of their professional work and, in particular, uncertainties are inherent to engineering models. Models play a central role in engineering. Models often represent an abstract and idealized version of the mathematical properties of a target. Using models, engineers can investigate and acquire understanding of how an object or phenomenon will perform under specified conditions. This paper defines the different stages of the modeling process in engineering, classifies the various sources of uncertainty that arise in each stage, and discusses the categories into which these uncertainties fall. The paper then considers the way uncertainty and modeling are approached in science and the criteria for evaluating scientific hypotheses, in order to highlight the very different criteria appropriate for the development of models and the treatment of the inherent uncertainties in engineering. Finally, the paper puts forward nine guidelines for the treatment of uncertainty in engineering modeling.

Estimation of uncertainties in {sup 1}H, Zr and {sup 238}U nuclear data contained in JENDL-3.2

Energy Technology Data Exchange (ETDEWEB)

Shibata, Keiichi; Nakajima, Yutaka; Fukahori, Tokio; Chiba, Satoshi; Nakagawa, Tsuneo [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment; Kawano, Toshihiko

1996-08-01

Uncertainties have been estimated for the total, elastic scattering and capture cross sections of {sup 1}H, the capture, (n,2n) reaction and inelastic scattering cross sections of natural Zr, and the inelastic scattering cross sections and resolved resonance parameters of {sup 238}U. Considering the evaluation method taken for each data, standard deviations and correlation matrices were determined in 18 energy structure. (author). 50 refs.

The use of kragten spreadsheets for uncertainty evaluation of uranium potentiometric analysis by the Brazilian Safeguards Laboratory

International Nuclear Information System (INIS)

Silva, Jose Wanderley S. da; Barros, Pedro Dionisio de; Araujo, Radier Mario S. de

2009-01-01

In safeguards, independent analysis of uranium content and enrichment of nuclear materials to verify operator's declarations is an important tool to evaluate the accountability system applied by nuclear installations. This determination may be performed by nondestructive (NDA) methods, generally done in the field using portable radiation detection systems, or destructive (DA) methods by chemical analysis when more accurate and precise results are necessary. Samples for DA analysis are collected by inspectors during safeguards inspections and sent to Safeguards Laboratory (LASAL) of the Brazilian Nuclear Energy Commission - (CNEN), where the analysis take place. The method used by LASAL for determination of uranium in different physical and chemical forms is the Davies and Gray/NBL using an automatic potentiometric titrator, which performs the titration of uranium IV by a standard solution of K 2 Cr 2 O 7 . Uncertainty budgets have been determined based on the concepts of the ISO 'Guide to the Expression of Uncertainty in Measurement' (GUM). In order to simplify the calculation of the uncertainty, a computational tool named Kragten Spreadsheet was used. Such spreadsheet uses the concepts established by the GUM and provides results that numerically approximates to those obtained by propagation of uncertainty with analytically determined sensitivity coefficients. The main parameters (input quantities) interfering on the uncertainty were studied. In order to evaluate their contribution in the final uncertainty, the uncertainties of all steps of the analytical method were estimated and compiled. (author)

SU-G-BRA-09: Estimation of Motion Tracking Uncertainty for Real-Time Adaptive Imaging

Energy Technology Data Exchange (ETDEWEB)

Yan, H [Capital Medical University, Beijing, Beijing (China); Chen, Z [Yale New Haven Hospital, New Haven, CT (United States); Nath, R; Liu, W [Yale University School of Medicine, New Haven, CT (United States)

2016-06-15

Purpose: kV fluoroscopic imaging combined with MV treatment beam imaging has been investigated for intrafractional motion monitoring and correction. It is, however, subject to additional kV imaging dose to normal tissue. To balance tracking accuracy and imaging dose, we previously proposed an adaptive imaging strategy to dynamically decide future imaging type and moments based on motion tracking uncertainty. kV imaging may be used continuously for maximal accuracy or only when the position uncertainty (probability of out of threshold) is high if a preset imaging dose limit is considered. In this work, we propose more accurate methods to estimate tracking uncertainty through analyzing acquired data in real-time. Methods: We simulated motion tracking process based on a previously developed imaging framework (MV + initial seconds of kV imaging) using real-time breathing data from 42 patients. Motion tracking errors for each time point were collected together with the time point’s corresponding features, such as tumor motion speed and 2D tracking error of previous time points, etc. We tested three methods for error uncertainty estimation based on the features: conditional probability distribution, logistic regression modeling, and support vector machine (SVM) classification to detect errors exceeding a threshold. Results: For conditional probability distribution, polynomial regressions on three features (previous tracking error, prediction quality, and cosine of the angle between the trajectory and the treatment beam) showed strong correlation with the variation (uncertainty) of the mean 3D tracking error and its standard deviation: R-square = 0.94 and 0.90, respectively. The logistic regression and SVM classification successfully identified about 95% of tracking errors exceeding 2.5mm threshold. Conclusion: The proposed methods can reliably estimate the motion tracking uncertainty in real-time, which can be used to guide adaptive additional imaging to confirm the

SU-G-BRA-09: Estimation of Motion Tracking Uncertainty for Real-Time Adaptive Imaging

International Nuclear Information System (INIS)

Yan, H; Chen, Z; Nath, R; Liu, W

2016-01-01

Purpose: kV fluoroscopic imaging combined with MV treatment beam imaging has been investigated for intrafractional motion monitoring and correction. It is, however, subject to additional kV imaging dose to normal tissue. To balance tracking accuracy and imaging dose, we previously proposed an adaptive imaging strategy to dynamically decide future imaging type and moments based on motion tracking uncertainty. kV imaging may be used continuously for maximal accuracy or only when the position uncertainty (probability of out of threshold) is high if a preset imaging dose limit is considered. In this work, we propose more accurate methods to estimate tracking uncertainty through analyzing acquired data in real-time. Methods: We simulated motion tracking process based on a previously developed imaging framework (MV + initial seconds of kV imaging) using real-time breathing data from 42 patients. Motion tracking errors for each time point were collected together with the time point’s corresponding features, such as tumor motion speed and 2D tracking error of previous time points, etc. We tested three methods for error uncertainty estimation based on the features: conditional probability distribution, logistic regression modeling, and support vector machine (SVM) classification to detect errors exceeding a threshold. Results: For conditional probability distribution, polynomial regressions on three features (previous tracking error, prediction quality, and cosine of the angle between the trajectory and the treatment beam) showed strong correlation with the variation (uncertainty) of the mean 3D tracking error and its standard deviation: R-square = 0.94 and 0.90, respectively. The logistic regression and SVM classification successfully identified about 95% of tracking errors exceeding 2.5mm threshold. Conclusion: The proposed methods can reliably estimate the motion tracking uncertainty in real-time, which can be used to guide adaptive additional imaging to confirm the

Uncertainty analysis of neutron transport calculation

International Nuclear Information System (INIS)

Oka, Y.; Furuta, K.; Kondo, S.

1987-01-01

A cross section sensitivity-uncertainty analysis code, SUSD was developed. The code calculates sensitivity coefficients for one and two-dimensional transport problems based on the first order perturbation theory. Variance and standard deviation of detector responses or design parameters can be obtained using cross section covariance matrix. The code is able to perform sensitivity-uncertainty analysis for secondary neutron angular distribution(SAD) and secondary neutron energy distribution(SED). Covariances of 6 Li and 7 Li neutron cross sections in JENDL-3PR1 were evaluated including SAD and SED. Covariances of Fe and Be were also evaluated. The uncertainty of tritium breeding ratio, fast neutron leakage flux and neutron heating was analysed on four types of blanket concepts for a commercial tokamak fusion reactor. The uncertainty of tritium breeding ratio was less than 6 percent. Contribution from SAD/SED uncertainties are significant for some parameters. Formulas to estimate the errors of numerical solution of the transport equation were derived based on the perturbation theory. This method enables us to deterministically estimate the numerical errors due to iterative solution, spacial discretization and Legendre polynomial expansion of transfer cross-sections. The calculational errors of the tritium breeding ratio and the fast neutron leakage flux of the fusion blankets were analysed. (author)

A new Method for the Estimation of Initial Condition Uncertainty Structures in Mesoscale Models

Science.gov (United States)

Keller, J. D.; Bach, L.; Hense, A.

2012-12-01

The estimation of fast growing error modes of a system is a key interest of ensemble data assimilation when assessing uncertainty in initial conditions. Over the last two decades three methods (and variations of these methods) have evolved for global numerical weather prediction models: ensemble Kalman filter, singular vectors and breeding of growing modes (or now ensemble transform). While the former incorporates a priori model error information and observation error estimates to determine ensemble initial conditions, the latter two techniques directly address the error structures associated with Lyapunov vectors. However, in global models these structures are mainly associated with transient global wave patterns. When assessing initial condition uncertainty in mesoscale limited area models, several problems regarding the aforementioned techniques arise: (a) additional sources of uncertainty on the smaller scales contribute to the error and (b) error structures from the global scale may quickly move through the model domain (depending on the size of the domain). To address the latter problem, perturbation structures from global models are often included in the mesoscale predictions as perturbed boundary conditions. However, the initial perturbations (when used) are often generated with a variant of an ensemble Kalman filter which does not necessarily focus on the large scale error patterns. In the framework of the European regional reanalysis project of the Hans-Ertel-Center for Weather Research we use a mesoscale model with an implemented nudging data assimilation scheme which does not support ensemble data assimilation at all. In preparation of an ensemble-based regional reanalysis and for the estimation of three-dimensional atmospheric covariance structures, we implemented a new method for the assessment of fast growing error modes for mesoscale limited area models. The so-called self-breeding is development based on the breeding of growing modes technique

Estimation of the thermal diffusion coefficient in fusion plasmas taking frequency measurement uncertainties into account

International Nuclear Information System (INIS)

Van Berkel, M; Hogeweij, G M D; Van den Brand, H; De Baar, M R; Zwart, H J; Vandersteen, G

2014-01-01

In this paper, the estimation of the thermal diffusivity from perturbative experiments in fusion plasmas is discussed. The measurements used to estimate the thermal diffusivity suffer from stochastic noise. Accurate estimation of the thermal diffusivity should take this into account. It will be shown that formulas found in the literature often result in a thermal diffusivity that has a bias (a difference between the estimated value and the actual value that remains even if more measurements are added) or have an unnecessarily large uncertainty. This will be shown by modeling a plasma using only diffusion as heat transport mechanism and measurement noise based on ASDEX Upgrade measurements. The Fourier coefficients of a temperature perturbation will exhibit noise from the circular complex normal distribution (CCND). Based on Fourier coefficients distributed according to a CCND, it is shown that the resulting probability density function of the thermal diffusivity is an inverse non-central chi-squared distribution. The thermal diffusivity that is found by sampling this distribution will always be biased, and averaging of multiple estimated diffusivities will not necessarily improve the estimation. Confidence bounds are constructed to illustrate the uncertainty in the diffusivity using several formulas that are equivalent in the noiseless case. Finally, a different method of averaging, that reduces the uncertainty significantly, is suggested. The methodology is also extended to the case where damping is included, and it is explained how to include the cylindrical geometry. (paper)

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

Energy Technology Data Exchange (ETDEWEB)

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

2018-03-08

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

Volcano deformation source parameters estimated from InSAR: Sensitivities to uncertainties in seismic tomography

Science.gov (United States)

Masterlark, Timothy; Donovan, Theodore; Feigl, Kurt L.; Haney, Matt; Thurber, Clifford H.; Tung, Sui

2016-01-01

The eruption cycle of a volcano is controlled in part by the upward migration of magma. The characteristics of the magma flux produce a deformation signature at the Earth's surface. Inverse analyses use geodetic data to estimate strategic controlling parameters that describe the position and pressurization of a magma chamber at depth. The specific distribution of material properties controls how observed surface deformation translates to source parameter estimates. Seismic tomography models describe the spatial distributions of material properties that are necessary for accurate models of volcano deformation. This study investigates how uncertainties in seismic tomography models propagate into variations in the estimates of volcano deformation source parameters inverted from geodetic data. We conduct finite element model-based nonlinear inverse analyses of interferometric synthetic aperture radar (InSAR) data for Okmok volcano, Alaska, as an example. We then analyze the estimated parameters and their uncertainties to characterize the magma chamber. Analyses are performed separately for models simulating a pressurized chamber embedded in a homogeneous domain as well as for a domain having a heterogeneous distribution of material properties according to seismic tomography. The estimated depth of the source is sensitive to the distribution of material properties. The estimated depths for the homogeneous and heterogeneous domains are 2666 ± 42 and 3527 ± 56 m below mean sea level, respectively (99% confidence). A Monte Carlo analysis indicates that uncertainties of the seismic tomography cannot account for this discrepancy at the 99% confidence level. Accounting for the spatial distribution of elastic properties according to seismic tomography significantly improves the fit of the deformation model predictions and significantly influences estimates for parameters that describe the location of a pressurized magma chamber.

Justification for recommended uncertainties

International Nuclear Information System (INIS)

Pronyaev, V.G.; Badikov, S.A.; Carlson, A.D.

2007-01-01

The uncertainties obtained in an earlier standards evaluation were considered to be unrealistically low by experts of the US Cross Section Evaluation Working Group (CSEWG). Therefore, the CSEWG Standards Subcommittee replaced the covariance matrices of evaluated uncertainties by expanded percentage errors that were assigned to the data over wide energy groups. There are a number of reasons that might lead to low uncertainties of the evaluated data: Underestimation of the correlations existing between the results of different measurements; The presence of unrecognized systematic uncertainties in the experimental data can lead to biases in the evaluated data as well as to underestimations of the resulting uncertainties; Uncertainties for correlated data cannot only be characterized by percentage uncertainties or variances. Covariances between evaluated value at 0.2 MeV and other points obtained in model (RAC R matrix and PADE2 analytical expansion) and non-model (GMA) fits of the 6 Li(n,t) TEST1 data and the correlation coefficients are presented and covariances between the evaluated value at 0.045 MeV and other points (along the line or column of the matrix) as obtained in EDA and RAC R matrix fits of the data available for reactions that pass through the formation of the 7 Li system are discussed. The GMA fit with the GMA database is shown for comparison. The following diagrams are discussed: Percentage uncertainties of the evaluated cross section for the 6 Li(n,t) reaction and the for the 235 U(n,f) reaction; estimation given by CSEWG experts; GMA result with full GMA database, including experimental data for the 6 Li(n,t), 6 Li(n,n) and 6 Li(n,total) reactions; uncertainties in the GMA combined fit for the standards; EDA and RAC R matrix results, respectively. Uncertainties of absolute and 252 Cf fission spectrum averaged cross section measurements, and deviations between measured and evaluated values for 235 U(n,f) cross-sections in the neutron energy range 1

Lidar-derived estimate and uncertainty of carbon sink in successional phases of woody encroachment

Science.gov (United States)

Sankey, Temuulen; Shrestha, Rupesh; Sankey, Joel B.; Hardgree, Stuart; Strand, Eva

2013-01-01

Woody encroachment is a globally occurring phenomenon that contributes to the global carbon sink. The magnitude of this contribution needs to be estimated at regional and local scales to address uncertainties present in the global- and continental-scale estimates, and guide regional policy and management in balancing restoration activities, including removal of woody plants, with greenhouse gas mitigation goals. The objective of this study was to estimate carbon stored in various successional phases of woody encroachment. Using lidar measurements of individual trees, we present high-resolution estimates of aboveground carbon storage in juniper woodlands. Segmentation analysis of lidar point cloud data identified a total of 60,628 juniper tree crowns across four watersheds. Tree heights, canopy cover, and density derived from lidar were strongly correlated with field measurements of 2613 juniper stems measured in 85 plots (30 × 30 m). Aboveground total biomass of individual trees was estimated using a regression model with lidar-derived height and crown area as predictors (Adj. R2 = 0.76, p 2. Uncertainty in carbon storage estimates was examined with a Monte Carlo approach that addressed major error sources. Ranges predicted with uncertainty analysis in the mean, individual tree, aboveground woody C, and associated standard deviation were 0.35 – 143.6 kg and 0.5 – 1.25 kg, respectively. Later successional phases of woody encroachment had, on average, twice the aboveground carbon relative to earlier phases. Woody encroachment might be more successfully managed and balanced with carbon storage goals by identifying priority areas in earlier phases of encroachment where intensive treatments are most effective.

Estimating U.S. Methane Emissions from the Natural Gas Supply Chain. Approaches, Uncertainties, Current Estimates, and Future Studies

Energy Technology Data Exchange (ETDEWEB)

Heath, Garvin [Joint Inst. for Strategic Energy Analysis, Golden, CO (United States); Warner, Ethan [Joint Inst. for Strategic Energy Analysis, Golden, CO (United States); Steinberg, Daniel [Joint Inst. for Strategic Energy Analysis, Golden, CO (United States); Brandt, Adam [Stanford Univ., CA (United States)

2015-08-01

A growing number of studies have raised questions regarding uncertainties in our understanding of methane (CH₄) emissions from fugitives and venting along the natural gas (NG) supply chain. In particular, a number of measurement studies have suggested that actual levels of CH₄ emissions may be higher than estimated by EPA" tm s U.S. GHG Emission Inventory. We reviewed the literature to identify the growing number of studies that have raised questions regarding uncertainties in our understanding of methane (CH₄) emissions from fugitives and venting along the natural gas (NG) supply chain.

Estimation of high-pT Jet Energy Scale Uncertainty from single hadron response with the ATLAS detector

CERN Document Server

AUTHOR|(INSPIRE)INSPIRE-00534683; The ATLAS collaboration

2016-01-01

The jet energy scale (JES) uncertainty is estimated using different methods at different pT ranges. In situ techniques exploiting the pT balance between a jet and a reference object (e.g. Z or gamma) are used at lower pT, but at very high pT (> 2.5 TeV) there is not enough statistics for in-situ techniques. The JES uncertainty at high-pT is important in several searches for new phenomena, e.g. the dijet resonance and angular searches. In the highest pT range, the JES uncertainty is estimated using the calorimeter response to single hadrons. In this method, jets are treated as a superposition of energy depositions of single particles. An uncertainty is applied to each energy depositions belonging to the particles within the jet, and propagated to the final jet energy scale. This poster presents the JES uncertainty found with this method at sqrt(s) = 8 TeV and its developments.

Uncertainty and validation. Effect of model complexity on uncertainty estimates

Energy Technology Data Exchange (ETDEWEB)

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

1996-09-01

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

Observational uncertainty and regional climate model evaluation: A pan-European perspective

Science.gov (United States)

Kotlarski, Sven; Szabó, Péter; Herrera, Sixto; Räty, Olle; Keuler, Klaus; Soares, Pedro M.; Cardoso, Rita M.; Bosshard, Thomas; Pagé, Christian; Boberg, Fredrik; Gutiérrez, José M.; Jaczewski, Adam; Kreienkamp, Frank; Liniger, Mark. A.; Lussana, Cristian; Szepszo, Gabriella

2017-04-01

Local and regional climate change assessments based on downscaling methods crucially depend on the existence of accurate and reliable observational reference data. In dynamical downscaling via regional climate models (RCMs) observational data can influence model development itself and, later on, model evaluation, parameter calibration and added value assessment. In empirical-statistical downscaling, observations serve as predictand data and directly influence model calibration with corresponding effects on downscaled climate change projections. Focusing on the evaluation of RCMs, we here analyze the influence of uncertainties in observational reference data on evaluation results in a well-defined performance assessment framework and on a European scale. For this purpose we employ three different gridded observational reference grids, namely (1) the well-established EOBS dataset (2) the recently developed EURO4M-MESAN regional re-analysis, and (3) several national high-resolution and quality-controlled gridded datasets that recently became available. In terms of climate models five reanalysis-driven experiments carried out by five different RCMs within the EURO-CORDEX framework are used. Two variables (temperature and precipitation) and a range of evaluation metrics that reflect different aspects of RCM performance are considered. We furthermore include an illustrative model ranking exercise and relate observational spread to RCM spread. The results obtained indicate a varying influence of observational uncertainty on model evaluation depending on the variable, the season, the region and the specific performance metric considered. Over most parts of the continent, the influence of the choice of the reference dataset for temperature is rather small for seasonal mean values and inter-annual variability. Here, model uncertainty (as measured by the spread between the five RCM simulations considered) is typically much larger than reference data uncertainty. For

A novel Bayesian approach to accounting for uncertainty in fMRI-derived estimates of cerebral oxygen metabolism fluctuations.

Science.gov (United States)

Simon, Aaron B; Dubowitz, David J; Blockley, Nicholas P; Buxton, Richard B

2016-04-01

Calibrated blood oxygenation level dependent (BOLD) imaging is a multimodal functional MRI technique designed to estimate changes in cerebral oxygen metabolism from measured changes in cerebral blood flow and the BOLD signal. This technique addresses fundamental ambiguities associated with quantitative BOLD signal analysis; however, its dependence on biophysical modeling creates uncertainty in the resulting oxygen metabolism estimates. In this work, we developed a Bayesian approach to estimating the oxygen metabolism response to a neural stimulus and used it to examine the uncertainty that arises in calibrated BOLD estimation due to the presence of unmeasured model parameters. We applied our approach to estimate the CMRO2 response to a visual task using the traditional hypercapnia calibration experiment as well as to estimate the metabolic response to both a visual task and hypercapnia using the measurement of baseline apparent R2' as a calibration technique. Further, in order to examine the effects of cerebral spinal fluid (CSF) signal contamination on the measurement of apparent R2', we examined the effects of measuring this parameter with and without CSF-nulling. We found that the two calibration techniques provided consistent estimates of the metabolic response on average, with a median R2'-based estimate of the metabolic response to CO2 of 1.4%, and R2'- and hypercapnia-calibrated estimates of the visual response of 27% and 24%, respectively. However, these estimates were sensitive to different sources of estimation uncertainty. The R2'-calibrated estimate was highly sensitive to CSF contamination and to uncertainty in unmeasured model parameters describing flow-volume coupling, capillary bed characteristics, and the iso-susceptibility saturation of blood. The hypercapnia-calibrated estimate was relatively insensitive to these parameters but highly sensitive to the assumed metabolic response to CO2. Copyright © 2016 Elsevier Inc. All rights reserved.

A novel Bayesian approach to accounting for uncertainty in fMRI-derived estimates of cerebral oxygen metabolism fluctuations

Science.gov (United States)

Simon, Aaron B.; Dubowitz, David J.; Blockley, Nicholas P.; Buxton, Richard B.

2016-01-01

Calibrated blood oxygenation level dependent (BOLD) imaging is a multimodal functional MRI technique designed to estimate changes in cerebral oxygen metabolism from measured changes in cerebral blood flow and the BOLD signal. This technique addresses fundamental ambiguities associated with quantitative BOLD signal analysis; however, its dependence on biophysical modeling creates uncertainty in the resulting oxygen metabolism estimates. In this work, we developed a Bayesian approach to estimating the oxygen metabolism response to a neural stimulus and used it to examine the uncertainty that arises in calibrated BOLD estimation due to the presence of unmeasured model parameters. We applied our approach to estimate the CMRO2 response to a visual task using the traditional hypercapnia calibration experiment as well as to estimate the metabolic response to both a visual task and hypercapnia using the measurement of baseline apparent R2′ as a calibration technique. Further, in order to examine the effects of cerebral spinal fluid (CSF) signal contamination on the measurement of apparent R2′, we examined the effects of measuring this parameter with and without CSF-nulling. We found that the two calibration techniques provided consistent estimates of the metabolic response on average, with a median R2′-based estimate of the metabolic response to CO2 of 1.4%, and R2′- and hypercapnia-calibrated estimates of the visual response of 27% and 24%, respectively. However, these estimates were sensitive to different sources of estimation uncertainty. The R2′-calibrated estimate was highly sensitive to CSF contamination and to uncertainty in unmeasured model parameters describing flow-volume coupling, capillary bed characteristics, and the iso-susceptibility saturation of blood. The hypercapnia-calibrated estimate was relatively insensitive to these parameters but highly sensitive to the assumed metabolic response to CO2. PMID:26790354

Implicit Treatment of Technical Specification and Thermal Hydraulic Parameter Uncertainties in Gaussian Process Model to Estimate Safety Margin

Directory of Open Access Journals (Sweden)

Douglas A. Fynan

2016-06-01

Full Text Available The Gaussian process model (GPM is a flexible surrogate model that can be used for nonparametric regression for multivariate problems. A unique feature of the GPM is that a prediction variance is automatically provided with the regression function. In this paper, we estimate the safety margin of a nuclear power plant by performing regression on the output of best-estimate simulations of a large-break loss-of-coolant accident with sampling of safety system configuration, sequence timing, technical specifications, and thermal hydraulic parameter uncertainties. The key aspect of our approach is that the GPM regression is only performed on the dominant input variables, the safety injection flow rate and the delay time for AC powered pumps to start representing sequence timing uncertainty, providing a predictive model for the peak clad temperature during a reflood phase. Other uncertainties are interpreted as contributors to the measurement noise of the code output and are implicitly treated in the GPM in the noise variance term, providing local uncertainty bounds for the peak clad temperature. We discuss the applicability of the foregoing method to reduce the use of conservative assumptions in best estimate plus uncertainty (BEPU and Level 1 probabilistic safety assessment (PSA success criteria definitions while dealing with a large number of uncertainties.

Best estimate analysis of LOFT L2-5 with CATHARE: uncertainty and sensitivity analysis

Energy Technology Data Exchange (ETDEWEB)

JOUCLA, Jerome; PROBST, Pierre [Institute for Radiological Protection and Nuclear Safety, Fontenay-aux-Roses (France); FOUET, Fabrice [APTUS, Versailles (France)

2008-07-01

The revision of the 10 CFR50.46 in 1988 has made possible the use of best-estimate codes. They may be used in safety demonstration and licensing, provided that uncertainties are added to the relevant output parameters before comparing them with the acceptance criteria. In the safety analysis of the large break loss of coolant accident, it was agreed that the 95. percentile estimated with a high degree of confidence should be lower than the acceptance criteria. It appeared necessary to IRSN, technical support of the French Safety Authority, to get more insight into these strategies which are being developed not only in thermal-hydraulics but in other fields such as in neutronics. To estimate the 95. percentile with a high confidence level, we propose to use rank statistics or bootstrap. Toward the objective of assessing uncertainty, it is useful to determine and to classify the main input parameters. We suggest approximating the code by a surrogate model, the Kriging model, which will be used to make a sensitivity analysis with the SOBOL methodology. This paper presents the application of two new methodologies of how to make the uncertainty and sensitivity analysis on the maximum peak cladding temperature of the LOFT L2-5 test with the CATHARE code. (authors)

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.

Uncertainties of estimating average radon and radon decay product concentrations in occupied houses

International Nuclear Information System (INIS)

Ronca-Battista, M.; Magno, P.; Windham, S.

1986-01-01

Radon and radon decay product measurements made in up to 68 Butte, Montana homes over a period of 18 months were used to estimate the uncertainty in estimating long-term average radon and radon decay product concentrations from a short-term measurement. This analysis was performed in support of the development of radon and radon decay product measurement protocols by the Environmental Protection Agency (EPA). The results of six measurement methods were analyzed: continuous radon and working level monitors, radon progeny integrating sampling units, alpha-track detectors, and grab radon and radon decay product techniques. Uncertainties were found to decrease with increasing sampling time and to be smaller when measurements were conducted during the winter months. In general, radon measurements had a smaller uncertainty than radon decay product measurements. As a result of this analysis, the EPA measurements protocols specify that all measurements be made under closed-house (winter) conditions, and that sampling times of at least a 24 hour period be used when the measurement will be the basis for a decision about remedial action or long-term health risks. 13 references, 3 tables

Considering sampling strategy and cross-section complexity for estimating the uncertainty of discharge measurements using the velocity-area method

Science.gov (United States)

Despax, Aurélien; Perret, Christian; Garçon, Rémy; Hauet, Alexandre; Belleville, Arnaud; Le Coz, Jérôme; Favre, Anne-Catherine

2016-02-01

Streamflow time series provide baseline data for many hydrological investigations. Errors in the data mainly occur through uncertainty in gauging (measurement uncertainty) and uncertainty in the determination of the stage-discharge relationship based on gaugings (rating curve uncertainty). As the velocity-area method is the measurement technique typically used for gaugings, it is fundamental to estimate its level of uncertainty. Different methods are available in the literature (ISO 748, Q + , IVE), all with their own limitations and drawbacks. Among the terms forming the combined relative uncertainty in measured discharge, the uncertainty component relating to the limited number of verticals often includes a large part of the relative uncertainty. It should therefore be estimated carefully. In ISO 748 standard, proposed values of this uncertainty component only depend on the number of verticals without considering their distribution with respect to the depth and velocity cross-sectional profiles. The Q + method is sensitive to a user-defined parameter while it is questionable whether the IVE method is applicable to stream-gaugings performed with a limited number of verticals. To address the limitations of existing methods, this paper presents a new methodology, called FLow Analog UnceRtainty Estimation (FLAURE), to estimate the uncertainty component relating to the limited number of verticals. High-resolution reference gaugings (with 31 and more verticals) are used to assess the uncertainty component through a statistical analysis. Instead of subsampling purely randomly the verticals of these reference stream-gaugings, a subsampling method is developed in a way that mimicks the behavior of a hydrometric technician. A sampling quality index (SQI) is suggested and appears to be a more explanatory variable than the number of verticals. This index takes into account the spacing between verticals and the variation of unit flow between two verticals. To compute the

A non-linear and stochastic response surface method for Bayesian estimation of uncertainty in soil moisture simulation from a land surface model

Directory of Open Access Journals (Sweden)

F. Hossain

2004-01-01

Full Text Available This study presents a simple and efficient scheme for Bayesian estimation of uncertainty in soil moisture simulation by a Land Surface Model (LSM. The scheme is assessed within a Monte Carlo (MC simulation framework based on the Generalized Likelihood Uncertainty Estimation (GLUE methodology. A primary limitation of using the GLUE method is the prohibitive computational burden imposed by uniform random sampling of the model's parameter distributions. Sampling is improved in the proposed scheme by stochastic modeling of the parameters' response surface that recognizes the non-linear deterministic behavior between soil moisture and land surface parameters. Uncertainty in soil moisture simulation (model output is approximated through a Hermite polynomial chaos expansion of normal random variables that represent the model's parameter (model input uncertainty. The unknown coefficients of the polynomial are calculated using limited number of model simulation runs. The calibrated polynomial is then used as a fast-running proxy to the slower-running LSM to predict the degree of representativeness of a randomly sampled model parameter set. An evaluation of the scheme's efficiency in sampling is made through comparison with the fully random MC sampling (the norm for GLUE and the nearest-neighborhood sampling technique. The scheme was able to reduce computational burden of random MC sampling for GLUE in the ranges of 10%-70%. The scheme was also found to be about 10% more efficient than the nearest-neighborhood sampling method in predicting a sampled parameter set's degree of representativeness. The GLUE based on the proposed sampling scheme did not alter the essential features of the uncertainty structure in soil moisture simulation. The scheme can potentially make GLUE uncertainty estimation for any LSM more efficient as it does not impose any additional structural or distributional assumptions.

Evaluation of uncertainty and detection limits in radioactivity measurements

Energy Technology Data Exchange (ETDEWEB)

Herranz, M. [Universidad del Pais Vasco/Euskal Herriko Unibertsitatea, Escuela Tecnica Superior de Ingenieria de Bilbao, Alda. Urquijo, s/n, 48013 Bilbao (Spain); Idoeta, R. [Universidad del Pais Vasco/Euskal Herriko Unibertsitatea, Escuela Tecnica Superior de Ingenieria de Bilbao, Alda. Urquijo, s/n, 48013 Bilbao (Spain)], E-mail: raquel.idoeta@ehu.es; Legarda, F. [Universidad del Pais Vasco/Euskal Herriko Unibertsitatea, Escuela Tecnica Superior de Ingenieria de Bilbao, Alda. Urquijo, s/n, 48013 Bilbao (Spain)

2008-10-01

The uncertainty associated with the assessment of the radioactive content of any sample depends on the net counting rate registered during the measuring process and on the different weighting factors needed to transform this counting rate into activity, activity per unit mass or activity concentration. This work analyses the standard uncertainties in these weighting factors as well as their contribution to the uncertainty in the activity reported for three typical determinations for environmental radioactivity measurements in the laboratory. It also studies the corresponding characteristic limits and their dependence on the standard uncertainty related to those weighting factors, offering an analysis of the effectiveness of the simplified characteristic limits as evaluated by various measuring software and laboratories.

Evaluation of uncertainty and detection limits in radioactivity measurements

International Nuclear Information System (INIS)

Herranz, M.; Idoeta, R.; Legarda, F.

2008-01-01

The uncertainty associated with the assessment of the radioactive content of any sample depends on the net counting rate registered during the measuring process and on the different weighting factors needed to transform this counting rate into activity, activity per unit mass or activity concentration. This work analyses the standard uncertainties in these weighting factors as well as their contribution to the uncertainty in the activity reported for three typical determinations for environmental radioactivity measurements in the laboratory. It also studies the corresponding characteristic limits and their dependence on the standard uncertainty related to those weighting factors, offering an analysis of the effectiveness of the simplified characteristic limits as evaluated by various measuring software and laboratories

Cost Implications of Uncertainty in CO{sub 2} Storage Resource Estimates: A Review

Energy Technology Data Exchange (ETDEWEB)

Anderson, Steven T., E-mail: sanderson@usgs.gov [National Center, U.S. Geological Survey (United States)

2017-04-15

Carbon capture from stationary sources and geologic storage of carbon dioxide (CO{sub 2}) is an important option to include in strategies to mitigate greenhouse gas emissions. However, the potential costs of commercial-scale CO{sub 2} storage are not well constrained, stemming from the inherent uncertainty in storage resource estimates coupled with a lack of detailed estimates of the infrastructure needed to access those resources. Storage resource estimates are highly dependent on storage efficiency values or storage coefficients, which are calculated based on ranges of uncertain geological and physical reservoir parameters. If dynamic factors (such as variability in storage efficiencies, pressure interference, and acceptable injection rates over time), reservoir pressure limitations, boundaries on migration of CO{sub 2}, consideration of closed or semi-closed saline reservoir systems, and other possible constraints on the technically accessible CO{sub 2} storage resource (TASR) are accounted for, it is likely that only a fraction of the TASR could be available without incurring significant additional costs. Although storage resource estimates typically assume that any issues with pressure buildup due to CO{sub 2} injection will be mitigated by reservoir pressure management, estimates of the costs of CO{sub 2} storage generally do not include the costs of active pressure management. Production of saline waters (brines) could be essential to increasing the dynamic storage capacity of most reservoirs, but including the costs of this critical method of reservoir pressure management could increase current estimates of the costs of CO{sub 2} storage by two times, or more. Even without considering the implications for reservoir pressure management, geologic uncertainty can significantly impact CO{sub 2} storage capacities and costs, and contribute to uncertainty in carbon capture and storage (CCS) systems. Given the current state of available information and the

Contribution to uncertainties evaluation for fast reactors neutronic cross sections

International Nuclear Information System (INIS)

Privas, Edwin

2015-01-01

The thesis has been motivated by a wish to increase the uncertainty knowledge on nuclear data, for safety criteria. It aims the cross sections required by core calculation for sodium fast reactors (SFR), and new tools to evaluate its.The main objective of this work is to provide new tools in order to create coherent evaluated files, with reliable and mastered uncertainties. To answer those problematic, several methods have been implemented within the CONRAD code, which is developed at CEA of Cadarache. After a summary of all the elements required to understand the evaluation world, stochastic methods are presented in order to solve the Bayesian inference. They give the evaluator more information about probability density and they also can be used as validation tools. The algorithms have been successfully tested, despite long calculation time. Then, microscopic constraints have been implemented in CONRAD. They are defined as new information that should be taken into account during the evaluation process. An algorithm has been developed in order to solve, for example, continuity issues between two energy domains, with the Lagrange multiplier formalism. Another method is given by using a marginalization procedure, in order to either complete an existing evaluation with new covariance or add systematic uncertainty on an experiment described by two theories. The algorithms are well performed along examples, such the 238 U total cross section. The last parts focus on the integral data feedback, using methods of integral data assimilation to reduce the uncertainties on cross sections. This work ends with uncertainty reduction on key nuclear reactions, such the capture and fission cross sections of 238 U and 239 Pu, thanks to PROFIL and PROFIL-2 experiments in Phenix and the Jezebel benchmark. (author) [fr

Uncertainty Analysis for the Evaluation of a Passive Runway Arresting System

Science.gov (United States)

Deloach, Richard; Marlowe, Jill M.; Yager, Thomas J.

2009-01-01

This paper considers the stopping distance of an aircraft involved in a runway overrun incident when the runway has been provided with an extension comprised of a material engineered to induce high levels of rolling friction and drag. A formula for stopping distance is derived that is shown to be the product of a known formula for the case of friction without drag, and a dimensionless constant between 0 and 1 that quantifies the further reduction in stopping distance when drag is introduced. This additional quantity, identified as the Drag Reduction Factor, D, is shown to depend on the ratio of drag force to friction force experienced by the aircraft as it enters the overrun area. The specific functional form of D is shown to depend on how drag varies with speed. A detailed uncertainty analysis is presented which reveals how the uncertainty in estimates of stopping distance are influenced by experimental error in the force measurements that are acquired in a typical evaluation experiment conducted to assess candidate overrun materials.

Transfer of Nuclear Data Uncertainties to the Uncertainties of Fuel Characteristic by Interval Calculation

International Nuclear Information System (INIS)

Ukraintsev, V.F.; Kolesov, V.V.

2006-01-01

Usually for evaluation of reactor functionals uncertainties, the perturbation theory and sensitivity analysis techniques are used. Of cause linearization approach of perturbation theory is used. This approach has several disadvantages and that is why a new method, based on application of a special interval calculations technique has been created. Basically, the problem of dependency of fuel cycle characteristic uncertainties from source group neutron cross-sections and decay parameters uncertainties can be solved (to some extent) as well by use of sensitivity analysis. However such procedure is rather labor consuming and does not give guaranteed estimations for received parameters since it works, strictly speaking, only for small deviations because it is initially based on linearization of the mathematical problems. The technique of fuel cycle characteristics uncertainties estimation is based on so-called interval analysis (or interval calculations). The basic advantage of this technique is the opportunity of deriving correct estimations. This technique consists in introducing a new special type of data such as Interval data in codes and the definition for them of all arithmetic operations. A technique of problem decision for system of linear equations (isotope kinetics) with use of interval arithmetic for the fuel burning up problem, has been realized. Thus there is an opportunity to compute a neutron flux, fission and capture cross-section uncertainties impact on nuclide concentration uncertainties and on fuel cycle characteristics (such as K eff , breeding ratio, decay heat power etc). By this time the code for interval calculation of burn-up computing has been developed and verified

Impact of geometric uncertainties on evaluation of treatment techniques for prostate cancer

International Nuclear Information System (INIS)

Craig, Tim; Wong, Eugene; Bauman, Glenn; Battista, Jerry; Van Dyk, Jake

2005-01-01

Purpose: To assess the impact of patient repositioning and internal organ motion on prostate treatment plans using three-dimensional conformal and intensity-modulated radiotherapy. Methods and materials: Four-field, six-field, and simplified intensity-modulated arc therapy plans were generated for 5 prostate cancer patients. The planning target volume was created by adding a 1-cm margin to the clinical target volume. A convolution model was used to estimate the effect of random geometric uncertainties during treatment. Dose statistics, tumor control probabilities, and normal tissue complication probabilities were compared with and without the presence of uncertainty. The impact of systematic uncertainties was also investigated. Results: Compared with the planned treatments, the delivered dose distribution with random geometric uncertainties displayed an increase in the apparent minimal dose to the prostate and seminal vesicles and a decrease in the rectal volume receiving a high dose. This increased the tumor control probabilities and decreased the normal tissue complication probabilities. Changes were seen in the percentage of prostate volume receiving 100% and 95% of the prescribed dose, and the minimal dose and tumor control probabilities for the target volume. In addition, the volume receiving at least 65 Gy, the minimal dose, and normal tissue complication probabilities changed considerably for the rectum. The simplified intensity-modulated arc therapy technique was the most sensitive to systematic errors, especially in the anterior-posterior and superior-inferior directions. Conclusion: Geometric uncertainties should be considered when evaluating treatment plans. Contrary to the widely held belief, increased conformation of the dose distribution is not always associated with increased sensitivity to random geometric uncertainties if a sufficient planning target volume margin is used. Systematic errors may have a variable effect, depending on the treatment

Effects of uncertainty in model predictions of individual tree volume on large area volume estimates

Science.gov (United States)

Ronald E. McRoberts; James A. Westfall

2014-01-01

Forest inventory estimates of tree volume for large areas are typically calculated by adding model predictions of volumes for individual trees. However, the uncertainty in the model predictions is generally ignored with the result that the precision of the large area volume estimates is overestimated. The primary study objective was to estimate the effects of model...

Lidar-derived estimate and uncertainty of carbon sink in successional phases of woody encroachment

Science.gov (United States)

Sankey, Temuulen; Shrestha, Rupesh; Sankey, Joel B.; Hardegree, Stuart; Strand, Eva

2013-07-01

encroachment is a globally occurring phenomenon that contributes to the global carbon sink. The magnitude of this contribution needs to be estimated at regional and local scales to address uncertainties present in the global- and continental-scale estimates, and guide regional policy and management in balancing restoration activities, including removal of woody plants, with greenhouse gas mitigation goals. The objective of this study was to estimate carbon stored in various successional phases of woody encroachment. Using lidar measurements of individual trees, we present high-resolution estimates of aboveground carbon storage in juniper woodlands. Segmentation analysis of lidar point cloud data identified a total of 60,628 juniper tree crowns across four watersheds. Tree heights, canopy cover, and density derived from lidar were strongly correlated with field measurements of 2613 juniper stems measured in 85 plots (30 × 30 m). Aboveground total biomass of individual trees was estimated using a regression model with lidar-derived height and crown area as predictors (Adj. R2 = 0.76, p < 0.001, RMSE = 0.58 kg). The predicted mean aboveground woody carbon storage for the study area was 677 g/m2. Uncertainty in carbon storage estimates was examined with a Monte Carlo approach that addressed major error sources. Ranges predicted with uncertainty analysis in the mean, individual tree, aboveground woody C, and associated standard deviation were 0.35 - 143.6 kg and 0.5 - 1.25 kg, respectively. Later successional phases of woody encroachment had, on average, twice the aboveground carbon relative to earlier phases. Woody encroachment might be more successfully managed and balanced with carbon storage goals by identifying priority areas in earlier phases of encroachment where intensive treatments are most effective.

A Bayesian analysis of sensible heat flux estimation: Quantifying uncertainty in meteorological forcing to improve model prediction

KAUST Repository

Ershadi, Ali

2013-05-01

The influence of uncertainty in land surface temperature, air temperature, and wind speed on the estimation of sensible heat flux is analyzed using a Bayesian inference technique applied to the Surface Energy Balance System (SEBS) model. The Bayesian approach allows for an explicit quantification of the uncertainties in input variables: a source of error generally ignored in surface heat flux estimation. An application using field measurements from the Soil Moisture Experiment 2002 is presented. The spatial variability of selected input meteorological variables in a multitower site is used to formulate the prior estimates for the sampling uncertainties, and the likelihood function is formulated assuming Gaussian errors in the SEBS model. Land surface temperature, air temperature, and wind speed were estimated by sampling their posterior distribution using a Markov chain Monte Carlo algorithm. Results verify that Bayesian-inferred air temperature and wind speed were generally consistent with those observed at the towers, suggesting that local observations of these variables were spatially representative. Uncertainties in the land surface temperature appear to have the strongest effect on the estimated sensible heat flux, with Bayesian-inferred values differing by up to ±5°C from the observed data. These differences suggest that the footprint of the in situ measured land surface temperature is not representative of the larger-scale variability. As such, these measurements should be used with caution in the calculation of surface heat fluxes and highlight the importance of capturing the spatial variability in the land surface temperature: particularly, for remote sensing retrieval algorithms that use this variable for flux estimation.

Comparison of two different methods for the uncertainty estimation of circle diameter measurements using an optical coordinate measuring machine

DEFF Research Database (Denmark)

Morace, Renata Erica; Hansen, Hans Nørgaard; De Chiffre, Leonardo

2005-01-01

This paper deals with the uncertainty estimation of measurements performed on optical coordinate measuring machines (CMMs). Two different methods were used to assess the uncertainty of circle diameter measurements using an optical CMM: the sensitivity analysis developing an uncertainty budget...

Accounting for uncertainty in marine reserve design.

Science.gov (United States)

Halpern, Benjamin S; Regan, Helen M; Possingham, Hugh P; McCarthy, Michael A

2006-01-01

Ecosystems and the species and communities within them are highly complex systems that defy predictions with any degree of certainty. Managing and conserving these systems in the face of uncertainty remains a daunting challenge, particularly with respect to developing networks of marine reserves. Here we review several modelling frameworks that explicitly acknowledge and incorporate uncertainty, and then use these methods to evaluate reserve spacing rules given increasing levels of uncertainty about larval dispersal distances. Our approach finds similar spacing rules as have been proposed elsewhere - roughly 20-200 km - but highlights several advantages provided by uncertainty modelling over more traditional approaches to developing these estimates. In particular, we argue that uncertainty modelling can allow for (1) an evaluation of the risk associated with any decision based on the assumed uncertainty; (2) a method for quantifying the costs and benefits of reducing uncertainty; and (3) a useful tool for communicating to stakeholders the challenges in managing highly uncertain systems. We also argue that incorporating rather than avoiding uncertainty will increase the chances of successfully achieving conservation and management goals.

Metamodel for Efficient Estimation of Capacity-Fade Uncertainty in Li-Ion Batteries for Electric Vehicles

Directory of Open Access Journals (Sweden)

Jaewook Lee

2015-06-01

Full Text Available This paper presents an efficient method for estimating capacity-fade uncertainty in lithium-ion batteries (LIBs in order to integrate them into the battery-management system (BMS of electric vehicles, which requires simple and inexpensive computation for successful application. The study uses the pseudo-two-dimensional (P2D electrochemical model, which simulates the battery state by solving a system of coupled nonlinear partial differential equations (PDEs. The model parameters that are responsible for electrode degradation are identified and estimated, based on battery data obtained from the charge cycles. The Bayesian approach, with parameters estimated by probability distributions, is employed to account for uncertainties arising in the model and battery data. The Markov Chain Monte Carlo (MCMC technique is used to draw samples from the distributions. The complex computations that solve a PDE system for each sample are avoided by employing a polynomial-based metamodel. As a result, the computational cost is reduced from 5.5 h to a few seconds, enabling the integration of the method into the vehicle BMS. Using this approach, the conservative bound of capacity fade can be determined for the vehicle in service, which represents the safety margin reflecting the uncertainty.

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...

Evaluation method for uncertainty of effective delayed neutron fraction βeff

International Nuclear Information System (INIS)

Zukeran, Atsushi

1999-01-01

Uncertainty of effective delayed neutron fraction β eff is evaluated in terms of three quantities; uncertainties of the basic delayed neutron constants, energy dependence of delayed neutron yield ν d m , and the uncertainties of the fission cross sections of fuel elements. The uncertainty of β eff due to the delayed neutron yield is expressed by a linearized formula assuming that the delayed neutron yield does not depend on the incident energy, and the energy dependence is supplemented by using the detailed energy dependence proposed by D'Angelo and Filip. The third quantity, uncertainties of fission cross section, is evaluated on the basis of the generalized perturbation theory in relation to reaction rate rations such as central spectral indexes or average reaction rate ratios. Resultant uncertainty of β eff is about 4 to 5%s, in which primary factor is the delayed neutron yield, and the secondary one is the fission cross section uncertainty, especially for 238 U. The energy dependence of ν d m systematically reduces the magnitude of β eff about 1.4% to 1.7%, depending on the model of the energy vs. ν d m correlation curve. (author)

Quantifying Uncertainty in Estimation of Potential Recharge in Tropical and Temperate Catchments using a Crop Model and Microwave Remote Sensing

Science.gov (United States)

Krishnan Kutty, S.; Sekhar, M.; Ruiz, L.; Tomer, S. K.; Bandyopadhyay, S.; Buis, S.; Guerif, M.; Gascuel-odoux, C.

2012-12-01

Groundwater recharge in a semi-arid region is generally low, but could exhibit high spatial variability depending on the soil type and plant cover. The potential recharge (the drainage flux just beneath the root zone) is found to be sensitive to water holding capacity and rooting depth (Rushton, 2003). Simple water balance approaches for recharge estimation often fail to consider the effect of plant cover, growth phases and rooting depth. Hence a crop model based approach might be better suited to assess sensitivity of recharge for various crop-soil combinations in agricultural catchments. Martinez et al. (2009) using a root zone modelling approach to estimate groundwater recharge stressed that future studies should focus on quantifying the uncertainty in recharge estimates due to uncertainty in soil water parameters such as soil layers, field capacity, rooting depth etc. Uncertainty in the parameters may arise due to the uncertainties in retrieved variables (surface soil moisture and leaf area index) from satellite. Hence a good estimate of parameters as well as their uncertainty is essential for a reliable estimate of the potential recharge. In this study we focus on assessing the sensitivity of crop and soil types on the potential recharge by using a generic crop model STICS. The effect of uncertainty in the soil parameters on the estimates of recharge and its uncertainty is investigated. The multi-layer soil water parameters and their uncertainty is estimated by inversion of STICS model using the GLUE approach. Surface soil moisture and LAI either retrieved from microwave remote sensing data or measured in field plots (Sreelash et al., 2012) were found to provide good estimates of the soil water properties and therefore both these data sets were used in this study to estimate the parameters and the potential recharge for a combination of soil-crop systems. These investigations were made in two field experimental catchments. The first one is in the tropical semi

The grey relational approach for evaluating measurement uncertainty with poor information

International Nuclear Information System (INIS)

Luo, Zai; Wang, Yanqing; Zhou, Weihu; Wang, Zhongyu

2015-01-01

The Guide to the Expression of Uncertainty in Measurement (GUM) is the master document for measurement uncertainty evaluation. However, the GUM may encounter problems and does not work well when the measurement data have poor information. In most cases, poor information means a small data sample and an unknown probability distribution. In these cases, the evaluation of measurement uncertainty has become a bottleneck in practical measurement. To solve this problem, a novel method called the grey relational approach (GRA), different from the statistical theory, is proposed in this paper. The GRA does not require a large sample size or probability distribution information of the measurement data. Mathematically, the GRA can be divided into three parts. Firstly, according to grey relational analysis, the grey relational coefficients between the ideal and the practical measurement output series are obtained. Secondly, the weighted coefficients and the measurement expectation function will be acquired based on the grey relational coefficients. Finally, the measurement uncertainty is evaluated based on grey modeling. In order to validate the performance of this method, simulation experiments were performed and the evaluation results show that the GRA can keep the average error around 5%. Besides, the GRA was also compared with the grey method, the Bessel method, and the Monte Carlo method by a real stress measurement. Both the simulation experiments and real measurement show that the GRA is appropriate and effective to evaluate the measurement uncertainty with poor information. (paper)

Inferring uncertainty from interval estimates: Effects of alpha level and numeracy

Directory of Open Access Journals (Sweden)

Luke F. Rinne

2013-05-01

Full Text Available Interval estimates are commonly used to descriptively communicate the degree of uncertainty in numerical values. Conventionally, low alpha levels (e.g., .05 ensure a high probability of capturing the target value between interval endpoints. Here, we test whether alpha levels and individual differences in numeracy influence distributional inferences. In the reported experiment, participants received prediction intervals for fictitious towns' annual rainfall totals (assuming approximately normal distributions. Then, participants estimated probabilities that future totals would be captured within varying margins about the mean, indicating the approximate shapes of their inferred probability distributions. Results showed that low alpha levels (vs. moderate levels; e.g., .25 more frequently led to inferences of over-dispersed approximately normal distributions or approximately uniform distributions, reducing estimate accuracy. Highly numerate participants made more accurate estimates overall, but were more prone to inferring approximately uniform distributions. These findings have important implications for presenting interval estimates to various audiences.

Comparing welfare estimates across stated preference and uncertainty elicitation formats for air quality improvements in Nairobi, Kenya

NARCIS (Netherlands)

Ndambiri, H.; Brouwer, R.; Mungatana, E.

2016-01-01

The effect of preference uncertainty on estimated willingness to pay (WTP) is examined using identical payment cards and alternative uncertainty elicitation procedures in three split samples, focusing on air quality improvement in Nairobi. The effect of the stochastic payment card (SPC) and

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)

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.

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.

Sensitivity of Earthquake Loss Estimates to Source Modeling Assumptions and Uncertainty

Science.gov (United States)

Reasenberg, Paul A.; Shostak, Nan; Terwilliger, Sharon

2006-01-01

Introduction: This report explores how uncertainty in an earthquake source model may affect estimates of earthquake economic loss. Specifically, it focuses on the earthquake source model for the San Francisco Bay region (SFBR) created by the Working Group on California Earthquake Probabilities. The loss calculations are made using HAZUS-MH, a publicly available computer program developed by the Federal Emergency Management Agency (FEMA) for calculating future losses from earthquakes, floods and hurricanes within the United States. The database built into HAZUS-MH includes a detailed building inventory, population data, data on transportation corridors, bridges, utility lifelines, etc. Earthquake hazard in the loss calculations is based upon expected (median value) ground motion maps called ShakeMaps calculated for the scenario earthquake sources defined in WGCEP. The study considers the effect of relaxing certain assumptions in the WG02 model, and explores the effect of hypothetical reductions in epistemic uncertainty in parts of the model. For example, it addresses questions such as what would happen to the calculated loss distribution if the uncertainty in slip rate in the WG02 model were reduced (say, by obtaining additional geologic data)? What would happen if the geometry or amount of aseismic slip (creep) on the region's faults were better known? And what would be the effect on the calculated loss distribution if the time-dependent earthquake probability were better constrained, either by eliminating certain probability models or by better constraining the inherent randomness in earthquake recurrence? The study does not consider the effect of reducing uncertainty in the hazard introduced through models of attenuation and local site characteristics, although these may have a comparable or greater effect than does source-related uncertainty. Nor does it consider sources of uncertainty in the building inventory, building fragility curves, and other assumptions

Estimation of Peaking Factor Uncertainty due to Manufacturing Tolerance using Statistical Sampling Method

Energy Technology Data Exchange (ETDEWEB)

Lee, Kyung Hoon; Park, Ho Jin; Lee, Chung Chan; Cho, Jin Young [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2015-10-15

The purpose of this paper is to study the effect on output parameters in the lattice physics calculation due to the last input uncertainty such as manufacturing deviations from nominal value for material composition and geometric dimensions. In a nuclear design and analysis, the lattice physics calculations are usually employed to generate lattice parameters for the nodal core simulation and pin power reconstruction. These lattice parameters which consist of homogenized few-group cross-sections, assembly discontinuity factors, and form-functions can be affected by input uncertainties which arise from three different sources: 1) multi-group cross-section uncertainties, 2) the uncertainties associated with methods and modeling approximations utilized in lattice physics codes, and 3) fuel/assembly manufacturing uncertainties. In this paper, data provided by the light water reactor (LWR) uncertainty analysis in modeling (UAM) benchmark has been used as the manufacturing uncertainties. First, the effect of each input parameter has been investigated through sensitivity calculations at the fuel assembly level. Then, uncertainty in prediction of peaking factor due to the most sensitive input parameter has been estimated using the statistical sampling method, often called the brute force method. For our analysis, the two-dimensional transport lattice code DeCART2D and its ENDF/B-VII.1 based 47-group library were used to perform the lattice physics calculation. Sensitivity calculations have been performed in order to study the influence of manufacturing tolerances on the lattice parameters. The manufacturing tolerance that has the largest influence on the k-inf is the fuel density. The second most sensitive parameter is the outer clad diameter.

Uncertainty of Volatility Estimates from Heston Greeks

Directory of Open Access Journals (Sweden)

Oliver Pfante

2018-01-01

Full Text Available Volatility is a widely recognized measure of market risk. As volatility is not observed it has to be estimated from market prices, i.e., as the implied volatility from option prices. The volatility index VIX making volatility a tradeable asset in its own right is computed from near- and next-term put and call options on the S&P 500 with more than 23 days and less than 37 days to expiration and non-vanishing bid. In the present paper we quantify the information content of the constituents of the VIX about the volatility of the S&P 500 in terms of the Fisher information matrix. Assuming that observed option prices are centered on the theoretical price provided by Heston's model perturbed by additive Gaussian noise we relate their Fisher information matrix to the Greeks in the Heston model. We find that the prices of options contained in the VIX basket allow for reliable estimates of the volatility of the S&P 500 with negligible uncertainty as long as volatility is large enough. Interestingly, if volatility drops below a critical value of roughly 3%, inferences from option prices become imprecise because Vega, the derivative of a European option w.r.t. volatility, and thereby the Fisher information nearly vanishes.

Best estimate approach for the evaluation of critical heat flux phenomenon in the boiling water reactors

Energy Technology Data Exchange (ETDEWEB)

Kaliatka, Tadas; Kaliatka, Algirdas; Uspuras, Eudenijus; Vaisnoras, Mindaugas [Lithuanian Energy Institute, Kaunas (Lithuania); Mochizuki, Hiroyasu; Rooijen, W.F.G. van [Fukui Univ. (Japan). Research Inst. of Nuclear Engineering

2017-05-15

Because of the uncertainties associated with the definition of Critical Heat Flux (CHF), the best estimate approach should be used. In this paper the application of best-estimate approach for the analysis of CHF phenomenon in the boiling water reactors is presented. At first, the nodalization of RBMK-1500, BWR-5 and ABWR fuel assemblies were developed using RELAP5 code. Using developed models the CHF and Critical Heat Flux Ratio (CHFR) for different types of reactors were evaluated. The calculation results of CHF were compared with the well-known experimental data for light water reactors. The uncertainty and sensitivity analysis of ABWR 8 x 8 fuel assembly CHFR calculation result was performed using the GRS (Germany) methodology with the SUSA tool. Finally, the values of Minimum Critical Power Ratio (MCPR) were calculated for RBMK-1500, BWR-5 and ABWR fuel assemblies. The paper demonstrate how, using the results of sensitivity analysis, to receive the MCPR values, which covers all uncertainties and remains best estimated.

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

Advanced probabilistic methods for quantifying the effects of various uncertainties in structural response

Science.gov (United States)

Nagpal, Vinod K.

1988-01-01

The effects of actual variations, also called uncertainties, in geometry and material properties on the structural response of a space shuttle main engine turbopump blade are evaluated. A normal distribution was assumed to represent the uncertainties statistically. Uncertainties were assumed to be totally random, partially correlated, and fully correlated. The magnitude of these uncertainties were represented in terms of mean and variance. Blade responses, recorded in terms of displacements, natural frequencies, and maximum stress, was evaluated and plotted in the form of probabilistic distributions under combined uncertainties. These distributions provide an estimate of the range of magnitudes of the response and probability of occurrence of a given response. Most importantly, these distributions provide the information needed to estimate quantitatively the risk in a structural design.

Estimating the Uncertainty of Tensile Strength Measurement for A Photocured Material Produced by Additive Manufacturing

Directory of Open Access Journals (Sweden)

Adamczak Stanisław

2014-08-01

Full Text Available The aim of this study was to estimate the measurement uncertainty for a material produced by additive manufacturing. The material investigated was FullCure 720 photocured resin, which was applied to fabricate tensile specimens with a Connex 350 3D printer based on PolyJet technology. The tensile strength of the specimens established through static tensile testing was used to determine the measurement uncertainty. There is a need for extensive research into the performance of model materials obtained via 3D printing as they have not been studied sufficiently like metal alloys or plastics, the most common structural materials. In this analysis, the measurement uncertainty was estimated using a larger number of samples than usual, i.e., thirty instead of typical ten. The results can be very useful to engineers who design models and finished products using this material. The investigations also show how wide the scatter of results is.

Comparison of the uncertainties calculated for the results of radiochemical determinations using the law of propagation of uncertainty and a Monte Carlo simulation

International Nuclear Information System (INIS)

Berne, A.

2001-01-01

Quantitative determinations of many radioactive analytes in environmental samples are based on a process in which several independent measurements of different properties are taken. The final results that are calculated using the data have to be evaluated for accuracy and precision. The estimate of the standard deviation, s, also called the combined standard uncertainty (CSU) associated with the result of this combined measurement can be used to evaluate the precision of the result. The CSU can be calculated by applying the law of propagation of uncertainty, which is based on the Taylor series expansion of the equation used to calculate the analytical result. The estimate of s can also be obtained from a Monte Carlo simulation. The data used in this simulation includes the values resulting from the individual measurements, the estimate of the variance of each value, including the type of distribution, and the equation used to calculate the analytical result. A comparison is made between these two methods of estimating the uncertainty of the calculated result. (author)

Uncertainty and validation. Effect of model complexity on uncertainty estimates

International Nuclear Information System (INIS)

Elert, M.

1996-09-01

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

Assessment of compliance with regulatory requirements for a best estimate methodology for evaluation of ECCS

Energy Technology Data Exchange (ETDEWEB)

Lee, Un Chul; Jang, Jin Wook; Lim, Ho Gon; Jeong, Ik [Seoul National Univ., Seoul (Korea, Republic of); Sim, Suk Ku [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

2000-03-15

Best estimate methodology for evaluation of ECCS proposed by KEPCO(KREM) os using thermal-hydraulic best-estimate code and the topical report for the methodology is described that it meets the regulatory requirement of USNRC regulatory guide. In this research the assessment of compliance with regulatory guide. In this research the assessment of compliance with regulatory requirements for the methodology is performed. The state of licensing procedure of other countries and best-estimate evaluation methodologies of Europe is also investigated, The applicability of models and propriety of procedure of uncertainty analysis of KREM are appraised and compliance with USNRC regulatory guide is assessed.

Strain gauge measurement uncertainties on hydraulic turbine runner blade

International Nuclear Information System (INIS)

Arpin-Pont, J; Gagnon, M; Tahan, S A; Coutu, A; Thibault, D

2012-01-01

Strains experimentally measured with strain gauges can differ from those evaluated using the Finite Element (FE) method. This difference is due mainly to the assumptions and uncertainties inherent to each method. To circumvent this difficulty, we developed a numerical method based on Monte Carlo simulations to evaluate measurement uncertainties produced by the behaviour of a unidirectional welded gauge, its position uncertainty and its integration effect. This numerical method uses the displacement fields of the studied part evaluated by an FE analysis. The paper presents a study case using in situ data measured on a hydraulic turbine runner. The FE analysis of the turbine runner blade was computed, and our numerical method used to evaluate uncertainties on strains measured at five locations with welded strain gauges. Then, measured strains and their uncertainty ranges are compared to the estimated strains. The uncertainty ranges obtained extended from 74 με to 165 με. Furthermore, the biases observed between the median of the uncertainty ranges and the FE strains varied from −36 to 36 με. Note that strain gauge measurement uncertainties depend mainly on displacement fields and gauge geometry.

Estimated of associated uncertainties of the linearity test of dose calibrators

International Nuclear Information System (INIS)

Sousa, Carlos H.S.; Peixoto, Jose G.P.

2013-01-01

Activimeters determine the activity of radioactive samples and them are validated by performance tests. This research determined the expanded uncertainties associated to the linearity test. Were used three dose calibrators and three sources of 99 Tc m for testing using recommended protocol by the IAEA, which considered the decay of radioactive samples. The expanded uncertainties evaluated were not correlated with each other and their analysis considered a rectangular probability distribution. The results are also presented in graphical form by the function of normalized activity measured in terms of conventional true value. (author)

How should epistemic uncertainty in modelling water resources management problems shape evaluations of their operations?

Science.gov (United States)

Dobson, B.; Pianosi, F.; Reed, P. M.; Wagener, T.

2017-12-01

In previous work, we have found that water supply companies are typically hesitant to use reservoir operation tools to inform their release decisions. We believe that this is, in part, due to a lack of faith in the fidelity of the optimization exercise with regards to its ability to represent the real world. In an attempt to quantify this, recent literature has studied the impact on performance from uncertainty arising in: forcing (e.g. reservoir inflows), parameters (e.g. parameters for the estimation of evaporation rate) and objectives (e.g. worst first percentile or worst case). We suggest that there is also epistemic uncertainty in the choices made during model creation, for example in the formulation of an evaporation model or aggregating regional storages. We create `rival framings' (a methodology originally developed to demonstrate the impact of uncertainty arising from alternate objective formulations), each with different modelling choices, and determine their performance impacts. We identify the Pareto approximate set of policies for several candidate formulations and then make them compete with one another in a large ensemble re-evaluation in each other's modelled spaces. This enables us to distinguish the impacts of different structural changes in the model used to evaluate system performance in an effort to generalize the validity of the optimized performance expectations.

Group-Contribution based Property Estimation and Uncertainty analysis for Flammability-related Properties