Renormalisation scale uncertainty in the DIS 2+1 jet cross-section

International Nuclear Information System (INIS)

Ingelman, G.

1994-05-01

The Deep Inelastic Scattering 2+1 jet cross-section is a useful observable for precision tests of QCD, e.g. measuring the strong coupling constant α s . A consistent analysis requires a good understanding of the theoretical uncertainties and one of the fundamental ones in QCD is due to the renormalisation scheme and scale ambiguity. Different methods, which have been proposed to resolve the scale ambiguity, are applied to the 2+1 jet cross-section and the uncertainty is estimated. It is shown that the uncertainty can be made smaller by choosing the jet definition in a suitable way. (orig.)

Uncertainties in modeling and scaling in the prediction of fuel stored energy and thermal response

International Nuclear Information System (INIS)

Wulff, W.

1987-01-01

The steady-state temperature distribution and the stored energy in nuclear fuel elements are computed by analytical methods and used to rank, in the order of importance, the effects on stored energy from statistical uncertainties in modeling parameters, in boundary and in operating conditions. An integral technique is used to calculate the transient fuel temperature and to estimate the uncertainties in predicting the fuel thermal response and the peak clad temperature during a large-break loss of coolant accident. The uncertainty analysis presented here is an important part of evaluating the applicability, the uncertainties and the scaling capabilities of computer codes for nuclear reactor safety analyses. The methods employed in this analysis merit general attention because of their simplicity. It is shown that the blowdown peak is dominated by fuel stored energy alone or, equivalently, by linear heating rate. Gap conductance, peaking factors and fuel thermal conductivity are the three most important fuel modeling parameters affecting peak clad temperature uncertainty. 26 refs., 10 figs., 6 tabs

Uncertainty Quantification for Large-Scale Ice Sheet Modeling

Energy Technology Data Exchange (ETDEWEB)

Ghattas, Omar [Univ. of Texas, Austin, TX (United States)

2016-02-05

This report summarizes our work to develop advanced forward and inverse solvers and uncertainty quantification capabilities for a nonlinear 3D full Stokes continental-scale ice sheet flow model. The components include: (1) forward solver: a new state-of-the-art parallel adaptive scalable high-order-accurate mass-conservative Newton-based 3D nonlinear full Stokes ice sheet flow simulator; (2) inverse solver: a new adjoint-based inexact Newton method for solution of deterministic inverse problems governed by the above 3D nonlinear full Stokes ice flow model; and (3) uncertainty quantification: a novel Hessian-based Bayesian method for quantifying uncertainties in the inverse ice sheet flow solution and propagating them forward into predictions of quantities of interest such as ice mass flux to the ocean.

Innovative supply chain optimization models with multiple uncertainty factors

DEFF Research Database (Denmark)

Choi, Tsan Ming; Govindan, Kannan; Li, Xiang

2017-01-01

Uncertainty is an inherent factor that affects all dimensions of supply chain activities. In today’s business environment, initiatives to deal with one specific type of uncertainty might not be effective since other types of uncertainty factors and disruptions may be present. These factors relate...... to supply chain competition and coordination. Thus, to achieve a more efficient and effective supply chain requires the deployment of innovative optimization models and novel methods. This preface provides a concise review of critical research issues regarding innovative supply chain optimization models...

Extreme-Scale Bayesian Inference for Uncertainty Quantification of Complex Simulations

Energy Technology Data Exchange (ETDEWEB)

Biros, George [Univ. of Texas, Austin, TX (United States)

2018-01-12

Uncertainty quantification (UQ)—that is, quantifying uncertainties in complex mathematical models and their large-scale computational implementations—is widely viewed as one of the outstanding challenges facing the field of CS&E over the coming decade. The EUREKA project set to address the most difficult class of UQ problems: those for which both the underlying PDE model as well as the uncertain parameters are of extreme scale. In the project we worked on these extreme-scale challenges in the following four areas: 1. Scalable parallel algorithms for sampling and characterizing the posterior distribution that exploit the structure of the underlying PDEs and parameter-to-observable map. These include structure-exploiting versions of the randomized maximum likelihood method, which aims to overcome the intractability of employing conventional MCMC methods for solving extreme-scale Bayesian inversion problems by appealing to and adapting ideas from large-scale PDE-constrained optimization, which have been very successful at exploring high-dimensional spaces. 2. Scalable parallel algorithms for construction of prior and likelihood functions based on learning methods and non-parametric density estimation. Constructing problem-specific priors remains a critical challenge in Bayesian inference, and more so in high dimensions. Another challenge is construction of likelihood functions that capture unmodeled couplings between observations and parameters. We will create parallel algorithms for non-parametric density estimation using high dimensional N-body methods and combine them with supervised learning techniques for the construction of priors and likelihood functions. 3. Bayesian inadequacy models, which augment physics models with stochastic models that represent their imperfections. The success of the Bayesian inference framework depends on the ability to represent the uncertainty due to imperfections of the mathematical model of the phenomena of interest. This is a

Scaling Factor Estimation Using an Optimized Mass Change Strategy, Part 1: Theory

DEFF Research Database (Denmark)

Aenlle, Manuel López; Fernández, Pelayo Fernández; Brincker, Rune

2007-01-01

In natural input modal analysis, only un-scaled mode shapes can be obtained. The mass change method is, in many cases, the simplest way to estimate the scaling factors, which involves repeated modal testing after changing the mass in different points of the structure where the mode shapes are known....... The scaling factors are determined using the natural frequencies and mode shapes of both the modified and the unmodified structure. However, the uncertainty on the scaling factor estimation depends on the modal analysis and the mass change strategy (number, magnitude and location of the masses) used to modify...

Calibration sets and the accuracy of vibrational scaling factors: A case study with the X3LYP hybrid functional

Science.gov (United States)

Teixeira, Filipe; Melo, André; Cordeiro, M. Natália D. S.

2010-09-01

A linear least-squares methodology was used to determine the vibrational scaling factors for the X3LYP density functional. Uncertainties for these scaling factors were calculated according to the method devised by Irikura et al. [J. Phys. Chem. A 109, 8430 (2005)]. The calibration set was systematically partitioned according to several of its descriptors and the scaling factors for X3LYP were recalculated for each subset. The results show that the scaling factors are only significant up to the second digit, irrespective of the calibration set used. Furthermore, multivariate statistical analysis allowed us to conclude that the scaling factors and the associated uncertainties are independent of the size of the calibration set and strongly suggest the practical impossibility of obtaining vibrational scaling factors with more than two significant digits.

Simulating space-time uncertainty in continental-scale gridded precipitation fields for agrometeorological modelling

NARCIS (Netherlands)

Wit, de A.J.W.; Bruin, de S.

2006-01-01

Previous analyses of the effects of uncertainty in precipitation fields on the output of EU Crop Growth Monitoring System (CGMS) demonstrated that the influence on simulated crop yield was limited at national scale, but considerable at local and regional scales. We aim to propagate uncertainty due

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.

Uncertainty in soil physical data at river basin scale – a review

Directory of Open Access Journals (Sweden)

P. van der Keur

2006-01-01

Full Text Available For hydrological modelling studies at the river basin scale, decision makers need guidance in assessing the implications of uncertain data used by modellers as an input to modelling tools. Simulated solute transport through the unsaturated zone is associated with uncertainty due to spatial variability of soil hydraulic properties and derived hydraulic model parameters. In general for modelling studies at the river basin scale spatially available data at various scales must be aggregated to an appropriate scale. Estimating soil properties at unsampled points by means of geostatistical techniques require reliable information on the spatial structure of soil data. In this paper this information is assessed by reviewing current developments in the field of soil physical data uncertainty and adopting a classification system. Then spatial variability and structure is inspected by reviewing experimental work on determining spatial length scales for soil physical (and soil chemical data. Available literature on spatial length scales for soil physical- and chemical properties is reviewed and their use in facilitating change of spatial support discussed. Uncertainty associated to the derivation of hydraulic properties from soil physical properties in this context is also discussed.

Uncertainty and sensitivity analysis of fission gas behavior in engineering-scale fuel modeling

Energy Technology Data Exchange (ETDEWEB)

Pastore, Giovanni, E-mail: Giovanni.Pastore@inl.gov [Fuel Modeling and Simulation, Idaho National Laboratory, P.O. Box 1625, Idaho Falls, ID 83415-3840 (United States); Swiler, L.P., E-mail: LPSwile@sandia.gov [Optimization and Uncertainty Quantification, Sandia National Laboratories, P.O. Box 5800, Albuquerque, NM 87185-1318 (United States); Hales, J.D., E-mail: Jason.Hales@inl.gov [Fuel Modeling and Simulation, Idaho National Laboratory, P.O. Box 1625, Idaho Falls, ID 83415-3840 (United States); Novascone, S.R., E-mail: Stephen.Novascone@inl.gov [Fuel Modeling and Simulation, Idaho National Laboratory, P.O. Box 1625, Idaho Falls, ID 83415-3840 (United States); Perez, D.M., E-mail: Danielle.Perez@inl.gov [Fuel Modeling and Simulation, Idaho National Laboratory, P.O. Box 1625, Idaho Falls, ID 83415-3840 (United States); Spencer, B.W., E-mail: Benjamin.Spencer@inl.gov [Fuel Modeling and Simulation, Idaho National Laboratory, P.O. Box 1625, Idaho Falls, ID 83415-3840 (United States); Luzzi, L., E-mail: Lelio.Luzzi@polimi.it [Politecnico di Milano, Department of Energy, Nuclear Engineering Division, via La Masa 34, I-20156 Milano (Italy); Van Uffelen, P., E-mail: Paul.Van-Uffelen@ec.europa.eu [European Commission, Joint Research Centre, Institute for Transuranium Elements, Hermann-von-Helmholtz-Platz 1, D-76344 Karlsruhe (Germany); Williamson, R.L., E-mail: Richard.Williamson@inl.gov [Fuel Modeling and Simulation, Idaho National Laboratory, P.O. Box 1625, Idaho Falls, ID 83415-3840 (United States)

2015-01-15

The role of uncertainties in fission gas behavior calculations as part of engineering-scale nuclear fuel modeling is investigated using the BISON fuel performance code with a recently implemented physics-based model for fission gas release and swelling. Through the integration of BISON with the DAKOTA software, a sensitivity analysis of the results to selected model parameters is carried out based on UO{sub 2} single-pellet simulations covering different power regimes. The parameters are varied within ranges representative of the relative uncertainties and consistent with the information in the open literature. The study leads to an initial quantitative assessment of the uncertainty in fission gas behavior predictions with the parameter characterization presently available. Also, the relative importance of the single parameters is evaluated. Moreover, a sensitivity analysis is carried out based on simulations of a fuel rod irradiation experiment, pointing out a significant impact of the considered uncertainties on the calculated fission gas release and cladding diametral strain. The results of the study indicate that the commonly accepted deviation between calculated and measured fission gas release by a factor of 2 approximately corresponds to the inherent modeling uncertainty at high fission gas release. Nevertheless, significantly higher deviations may be expected for values around 10% and lower. Implications are discussed in terms of directions of research for the improved modeling of fission gas behavior for engineering purposes.

Investment Decisions with Two-Factor Uncertainty

NARCIS (Netherlands)

Compernolle, T.; Huisman, Kuno; Kort, Peter; Lavrutich, Maria; Nunes, Claudia; Thijssen, J.J.J.

2018-01-01

This paper considers investment problems in real options with non-homogeneous two-factor uncertainty. It shows that, despite claims made in the literature, the method used to derive an analytical solution in one dimensional problems cannot be straightforwardly extended to problems with two

Radar subpixel-scale rainfall variability and uncertainty: lessons learned from observations of a dense rain-gauge network

Directory of Open Access Journals (Sweden)

N. Peleg

2013-06-01

Full Text Available Runoff and flash flood generation are very sensitive to rainfall's spatial and temporal variability. The increasing use of radar and satellite data in hydrological applications, due to the sparse distribution of rain gauges over most catchments worldwide, requires furthering our knowledge of the uncertainties of these data. In 2011, a new super-dense network of rain gauges containing 14 stations, each with two side-by-side gauges, was installed within a 4 km2 study area near Kibbutz Galed in northern Israel. This network was established for a detailed exploration of the uncertainties and errors regarding rainfall variability within a common pixel size of data obtained from remote sensing systems for timescales of 1 min to daily. In this paper, we present the analysis of the first year's record collected from this network and from the Shacham weather radar, located 63 km from the study area. The gauge–rainfall spatial correlation and uncertainty were examined along with the estimated radar error. The nugget parameter of the inter-gauge rainfall correlations was high (0.92 on the 1 min scale and increased as the timescale increased. The variance reduction factor (VRF, representing the uncertainty from averaging a number of rain stations per pixel, ranged from 1.6% for the 1 min timescale to 0.07% for the daily scale. It was also found that at least three rain stations are needed to adequately represent the rainfall (VRF < 5% on a typical radar pixel scale. The difference between radar and rain gauge rainfall was mainly attributed to radar estimation errors, while the gauge sampling error contributed up to 20% to the total difference. The ratio of radar rainfall to gauge-areal-averaged rainfall, expressed by the error distribution scatter parameter, decreased from 5.27 dB for 3 min timescale to 3.21 dB for the daily scale. The analysis of the radar errors and uncertainties suggest that a temporal scale of at least 10 min should be used for

Deterministic sensitivity and uncertainty analysis for large-scale computer models

International Nuclear Information System (INIS)

Worley, B.A.; Pin, F.G.; Oblow, E.M.; Maerker, R.E.; Horwedel, J.E.; Wright, R.Q.

1988-01-01

This paper presents a comprehensive approach to sensitivity and uncertainty analysis of large-scale computer models that is analytic (deterministic) in principle and that is firmly based on the model equations. The theory and application of two systems based upon computer calculus, GRESS and ADGEN, are discussed relative to their role in calculating model derivatives and sensitivities without a prohibitive initial manpower investment. Storage and computational requirements for these two systems are compared for a gradient-enhanced version of the PRESTO-II computer model. A Deterministic Uncertainty Analysis (DUA) method that retains the characteristics of analytically computing result uncertainties based upon parameter probability distributions is then introduced and results from recent studies are shown. 29 refs., 4 figs., 1 tab

Uncertainty in Analyzed Water and Energy Budgets at Continental Scales

Science.gov (United States)

Bosilovich, Michael G.; Robertson, F. R.; Mocko, D.; Chen, J.

2011-01-01

Operational analyses and retrospective-analyses provide all the physical terms of mater and energy budgets, guided by the assimilation of atmospheric observations. However, there is significant reliance on the numerical models, and so, uncertainty in the budget terms is always present. Here, we use a recently developed data set consisting of a mix of 10 analyses (both operational and retrospective) to quantify the uncertainty of analyzed water and energy budget terms for GEWEX continental-scale regions, following the evaluation of Dr. John Roads using individual reanalyses data sets.

How uncertainty in socio-economic variables affects large-scale transport model forecasts

DEFF Research Database (Denmark)

Manzo, Stefano; Nielsen, Otto Anker; Prato, Carlo Giacomo

2015-01-01

A strategic task assigned to large-scale transport models is to forecast the demand for transport over long periods of time to assess transport projects. However, by modelling complex systems transport models have an inherent uncertainty which increases over time. As a consequence, the longer...... the period forecasted the less reliable is the forecasted model output. Describing uncertainty propagation patterns over time is therefore important in order to provide complete information to the decision makers. Among the existing literature only few studies analyze uncertainty propagation patterns over...

Sources of errors and uncertainties in the assessment of forest soil carbon stocks at different scales

DEFF Research Database (Denmark)

Vanguelova, E. I.; Bonifacio, E.; De Vos, B.

2016-01-01

temporal changes and spatial differences in SOC. This requires sufficiently detailed data to predict SOC stocks at appropriate scales within the required accuracy so that only significant changes are accounted for. When designing sampling campaigns, taking into account factors influencing SOC spatial...... and temporal distribution (such as soil type, topography, climate and vegetation) are needed to optimise sampling depths and numbers of samples, thereby ensuring that samples accurately reflect the distribution of SOC at a site. Furthermore, the appropriate scales related to the research question need...... to be defined: profile, plot, forests, catchment, national or wider. Scaling up SOC stocks from point sample to landscape unit is challenging, and thus requires reliable baseline data. Knowledge of the associated uncertainties related to SOC measures at each particular scale and how to reduce them is crucial...

Crossing Science-Policy-Societal Boundaries to Reduce Scientific and Institutional Uncertainty in Small-Scale Fisheries

Science.gov (United States)

Sutton, Abigail M.; Rudd, Murray A.

2016-10-01

The governance of small-scale fisheries (SSF) is challenging due to the uncertainty, complexity, and interconnectedness of social, political, ecological, and economical processes. Conventional SSF management has focused on a centralized and top-down approach. A major criticism of conventional management is the over-reliance on `expert science' to guide decision-making and poor consideration of fishers' contextually rich knowledge. That is thought to exacerbate the already low governance potential of SSF. Integrating scientific knowledge with fishers' knowledge is increasingly popular and is often assumed to help reduce levels of biophysical and institutional uncertainties. Many projects aimed at encouraging knowledge integration have, however, been unsuccessful. Our objective in this research was to assess factors that influence knowledge integration and the uptake of integrated knowledge into policy-making. We report results from 54 semi-structured interviews with SSF researchers and practitioners from around the globe. Our analysis is framed in terms of scientific credibility, societal legitimacy, and policy saliency, and we discuss cases that have been partially or fully successful in reducing uncertainty via push-and-pull-oriented boundary crossing initiatives. Our findings suggest that two important factors affect the science-policy-societal boundary: a lack of consensus among stakeholders about what constitutes credible knowledge and institutional uncertainty resulting from shifting policies and leadership change. A lack of training for scientific leaders and an apparent `shelf-life' for community organizations highlight the importance of ongoing institutional support for knowledge integration projects. Institutional support may be enhanced through such investments, such as capacity building and specialized platforms for knowledge integration.

Crossing Science-Policy-Societal Boundaries to Reduce Scientific and Institutional Uncertainty in Small-Scale Fisheries.

Science.gov (United States)

Sutton, Abigail M; Rudd, Murray A

2016-10-01

The governance of small-scale fisheries (SSF) is challenging due to the uncertainty, complexity, and interconnectedness of social, political, ecological, and economical processes. Conventional SSF management has focused on a centralized and top-down approach. A major criticism of conventional management is the over-reliance on 'expert science' to guide decision-making and poor consideration of fishers' contextually rich knowledge. That is thought to exacerbate the already low governance potential of SSF. Integrating scientific knowledge with fishers' knowledge is increasingly popular and is often assumed to help reduce levels of biophysical and institutional uncertainties. Many projects aimed at encouraging knowledge integration have, however, been unsuccessful. Our objective in this research was to assess factors that influence knowledge integration and the uptake of integrated knowledge into policy-making. We report results from 54 semi-structured interviews with SSF researchers and practitioners from around the globe. Our analysis is framed in terms of scientific credibility, societal legitimacy, and policy saliency, and we discuss cases that have been partially or fully successful in reducing uncertainty via push-and-pull-oriented boundary crossing initiatives. Our findings suggest that two important factors affect the science-policy-societal boundary: a lack of consensus among stakeholders about what constitutes credible knowledge and institutional uncertainty resulting from shifting policies and leadership change. A lack of training for scientific leaders and an apparent 'shelf-life' for community organizations highlight the importance of ongoing institutional support for knowledge integration projects. Institutional support may be enhanced through such investments, such as capacity building and specialized platforms for knowledge integration.

Developing scales measuring disorder-specific intolerance of uncertainty (DSIU) : a new perspective on transdiagnostic

NARCIS (Netherlands)

Thibodeau, Michel A; Carleton, R Nicholas; McEvoy, Peter M; Zvolensky, Michael J; Brandt, Charles P; Boelen, Paul A; Mahoney, Alison E J; Deacon, Brett J; Asmundson, Gordon J G

Intolerance of uncertainty (IU) is a construct of growing prominence in literature on anxiety disorders and major depressive disorder. Existing measures of IU do not define the uncertainty that respondents perceive as distressing. To address this limitation, we developed eight scales measuring

Scaling Factor Estimation Using Optimized Mass Change Strategy, Part 2: Experimental Results

DEFF Research Database (Denmark)

Fernández, Pelayo Fernández; Aenlle, Manuel López; Garcia, Luis M. Villa

2007-01-01

The mass change method is used to estimate the scaling factors, the uncertainty is reduced when, for each mode, the frequency shift is maximized and the changes in the mode shapes are minimized, which in turn, depends on the mass change strategy chosen to modify the dynamic behavior of the struct...

A Comparison of the 27-Item and 12-Item Intolerance of Uncertainty Scales

Science.gov (United States)

Khawaja, Nigar G.; Yu, Lai Ngo Heidi

2010-01-01

The 27-item Intolerance of Uncertainty Scale (IUS) has become one of the most frequently used measures of Intolerance of Uncertainty. More recently, an abridged, 12-item version of the IUS has been developed. The current research used clinical (n = 50) and non-clinical (n = 56) samples to examine and compare the psychometric properties of both…

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 p$_\\text{T}$ ranges. In-situ techniques exploiting the p$_\\text{T}$ balance between a jet and a reference object (e.g. Z or gamma) are used at lower p$_\\text{T}$, but at very high p$_\\text{T}$ (> 2.5 TeV) there is not enough statistics for such in-situ techniques. A low JES uncertainty at high-p$_\\text{T}$ is important in several searches for new phenomena, e.g. the dijet resonance and angular searches. In the highest p$_\\text{T}$ 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 deposition 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.

Pore-scale uncertainty quantification with multilevel Monte Carlo

KAUST Repository

Icardi, Matteo

2014-01-06

Computational fluid dynamics (CFD) simulations of pore-scale transport processes in porous media have recently gained large popularity. However the geometrical details of the pore structures can be known only in a very low number of samples and the detailed flow computations can be carried out only on a limited number of cases. The explicit introduction of randomness in the geometry and in other setup parameters can be crucial for the optimization of pore-scale investigations for random homogenization. Since there are no generic ways to parametrize the randomness in the porescale structures, Monte Carlo techniques are the most accessible to compute statistics. We propose a multilevel Monte Carlo (MLMC) technique to reduce the computational cost of estimating quantities of interest within a prescribed accuracy constraint. Random samples of pore geometries with a hierarchy of geometrical complexities and grid refinements, are synthetically generated and used to propagate the uncertainties in the flow simulations and compute statistics of macro-scale effective parameters.

Characterizing Sources of Uncertainty in Item Response Theory Scale Scores

Science.gov (United States)

Yang, Ji Seung; Hansen, Mark; Cai, Li

2012-01-01

Traditional estimators of item response theory scale scores ignore uncertainty carried over from the item calibration process, which can lead to incorrect estimates of the standard errors of measurement (SEMs). Here, the authors review a variety of approaches that have been applied to this problem and compare them on the basis of their statistical…

Methods for Quantifying the Uncertainties of LSIT Test Parameters, Test Results, and Full-Scale Mixing Performance Using Models Developed from Scaled Test Data

Energy Technology Data Exchange (ETDEWEB)

Piepel, Gregory F. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Cooley, Scott K. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Kuhn, William L. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Rector, David R. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Heredia-Langner, Alejandro [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

2015-05-01

This report discusses the statistical methods for quantifying uncertainties in 1) test responses and other parameters in the Large Scale Integrated Testing (LSIT), and 2) estimates of coefficients and predictions of mixing performance from models that relate test responses to test parameters. Testing at a larger scale has been committed to by Bechtel National, Inc. and the U.S. Department of Energy (DOE) to “address uncertainties and increase confidence in the projected, full-scale mixing performance and operations” in the Waste Treatment and Immobilization Plant (WTP).

Impact of measurement uncertainty from experimental load distribution factors on bridge load rating

Science.gov (United States)

Gangone, Michael V.; Whelan, Matthew J.

2018-03-01

Load rating and testing of highway bridges is important in determining the capacity of the structure. Experimental load rating utilizes strain transducers placed at critical locations of the superstructure to measure normal strains. These strains are then used in computing diagnostic performance measures (neutral axis of bending, load distribution factor) and ultimately a load rating. However, it has been shown that experimentally obtained strain measurements contain uncertainties associated with the accuracy and precision of the sensor and sensing system. These uncertainties propagate through to the diagnostic indicators that in turn transmit into the load rating calculation. This paper will analyze the effect that measurement uncertainties have on the experimental load rating results of a 3 span multi-girder/stringer steel and concrete bridge. The focus of this paper will be limited to the uncertainty associated with the experimental distribution factor estimate. For the testing discussed, strain readings were gathered at the midspan of each span of both exterior girders and the center girder. Test vehicles of known weight were positioned at specified locations on each span to generate maximum strain response for each of the five girders. The strain uncertainties were used in conjunction with a propagation formula developed by the authors to determine the standard uncertainty in the distribution factor estimates. This distribution factor uncertainty is then introduced into the load rating computation to determine the possible range of the load rating. The results show the importance of understanding measurement uncertainty in experimental load testing.

Predicting the performance uncertainty of a 1-MW pilot-scale carbon capture system after hierarchical laboratory-scale calibration and validation

Energy Technology Data Exchange (ETDEWEB)

Xu, Zhijie; Lai, Canhai; Marcy, Peter William; Dietiker, Jean-François; Li, Tingwen; Sarkar, Avik; Sun, Xin

2017-05-01

A challenging problem in designing pilot-scale carbon capture systems is to predict, with uncertainty, the adsorber performance and capture efficiency under various operating conditions where no direct experimental data exist. Motivated by this challenge, we previously proposed a hierarchical framework in which relevant parameters of physical models were sequentially calibrated from different laboratory-scale carbon capture unit (C2U) experiments. Specifically, three models of increasing complexity were identified based on the fundamental physical and chemical processes of the sorbent-based carbon capture technology. Results from the corresponding laboratory experiments were used to statistically calibrate the physical model parameters while quantifying some of their inherent uncertainty. The parameter distributions obtained from laboratory-scale C2U calibration runs are used in this study to facilitate prediction at a larger scale where no corresponding experimental results are available. In this paper, we first describe the multiphase reactive flow model for a sorbent-based 1-MW carbon capture system then analyze results from an ensemble of simulations with the upscaled model. The simulation results are used to quantify uncertainty regarding the design’s predicted efficiency in carbon capture. In particular, we determine the minimum gas flow rate necessary to achieve 90% capture efficiency with 95% confidence.

Significant uncertainty in global scale hydrological modeling from precipitation data errors

Science.gov (United States)

Sperna Weiland, Frederiek C.; Vrugt, Jasper A.; van Beek, Rens (L.) P. H.; Weerts, Albrecht H.; Bierkens, Marc F. P.

2015-10-01

In the past decades significant progress has been made in the fitting of hydrologic models to data. Most of this work has focused on simple, CPU-efficient, lumped hydrologic models using discharge, water table depth, soil moisture, or tracer data from relatively small river basins. In this paper, we focus on large-scale hydrologic modeling and analyze the effect of parameter and rainfall data uncertainty on simulated discharge dynamics with the global hydrologic model PCR-GLOBWB. We use three rainfall data products; the CFSR reanalysis, the ERA-Interim reanalysis, and a combined ERA-40 reanalysis and CRU dataset. Parameter uncertainty is derived from Latin Hypercube Sampling (LHS) using monthly discharge data from five of the largest river systems in the world. Our results demonstrate that the default parameterization of PCR-GLOBWB, derived from global datasets, can be improved by calibrating the model against monthly discharge observations. Yet, it is difficult to find a single parameterization of PCR-GLOBWB that works well for all of the five river basins considered herein and shows consistent performance during both the calibration and evaluation period. Still there may be possibilities for regionalization based on catchment similarities. Our simulations illustrate that parameter uncertainty constitutes only a minor part of predictive uncertainty. Thus, the apparent dichotomy between simulations of global-scale hydrologic behavior and actual data cannot be resolved by simply increasing the model complexity of PCR-GLOBWB and resolving sub-grid processes. Instead, it would be more productive to improve the characterization of global rainfall amounts at spatial resolutions of 0.5° and smaller.

Methods for Quantifying the Uncertainties of LSIT Test Parameters, Test Results, and Full-Scale Mixing Performance Using Models Developed from Scaled Test Data

International Nuclear Information System (INIS)

Piepel, Gregory F.; Cooley, Scott K.; Kuhn, William L.; Rector, David R.; Heredia-Langner, Alejandro

2015-01-01

This report discusses the statistical methods for quantifying uncertainties in 1) test responses and other parameters in the Large Scale Integrated Testing (LSIT), and 2) estimates of coefficients and predictions of mixing performance from models that relate test responses to test parameters. Testing at a larger scale has been committed to by Bechtel National, Inc. and the U.S. Department of Energy (DOE) to ''address uncertainties and increase confidence in the projected, full-scale mixing performance and operations'' in the Waste Treatment and Immobilization Plant (WTP).

Evaluating uncertainties in regional climate simulations over South America at the seasonal scale

Energy Technology Data Exchange (ETDEWEB)

Solman, Silvina A. [Centro de Investigaciones del Mar y la Atmosfera CIMA/CONICET-UBA, DCAO/FCEN, UMI-IFAECI/CNRS, CIMA-Ciudad Universitaria, Buenos Aires (Argentina); Pessacg, Natalia L. [Centro Nacional Patagonico (CONICET), Puerto Madryn, Chubut (Argentina)

2012-07-15

This work focuses on the evaluation of different sources of uncertainty affecting regional climate simulations over South America at the seasonal scale, using the MM5 model. The simulations cover a 3-month period for the austral spring season. Several four-member ensembles were performed in order to quantify the uncertainty due to: the internal variability; the definition of the regional model domain; the choice of physical parameterizations and the selection of physical parameters within a particular cumulus scheme. The uncertainty was measured by means of the spread among individual members of each ensemble during the integration period. Results show that the internal variability, triggered by differences in the initial conditions, represents the lowest level of uncertainty for every variable analyzed. The geographic distribution of the spread among ensemble members depends on the variable: for precipitation and temperature the largest spread is found over tropical South America while for the mean sea level pressure the largest spread is located over the southeastern Atlantic Ocean, where large synoptic-scale activity occurs. Using nudging techniques to ingest the boundary conditions reduces dramatically the internal variability. The uncertainty due to the domain choice displays a similar spatial pattern compared with the internal variability, except for the mean sea level pressure field, though its magnitude is larger all over the model domain for every variable. The largest spread among ensemble members is found for the ensemble in which different combinations of physical parameterizations are selected. The perturbed physics ensemble produces a level of uncertainty slightly larger than the internal variability. This study suggests that no matter what the source of uncertainty is, the geographical distribution of the spread among members of the ensembles is invariant, particularly for precipitation and temperature. (orig.)

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

International Nuclear Information System (INIS)

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

2003-01-01

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

Quantification of structural uncertainties in multi-scale models; case study of the Lublin Basin, Poland

Science.gov (United States)

Małolepszy, Zbigniew; Szynkaruk, Ewa

2015-04-01

The multiscale static modeling of regional structure of the Lublin Basin is carried on in the Polish Geological Institute, in accordance with principles of integrated 3D geological modelling. The model is based on all available geospatial data from Polish digital databases and analogue archives. Mapped regional structure covers the area of 260x80 km located between Warsaw and Polish-Ukrainian border, along NW-SE-trending margin of the East European Craton. Within the basin, the Paleozoic beds with coalbearing Carboniferous and older formations containing hydrocarbons and unconventional prospects are covered unconformably by Permo-Mesozoic and younger rocks. Vertical extent of the regional model is set from topographic surface to 6000 m ssl and at the bottom includes some Proterozoic crystalline formations of the craton. The project focuses on internal consistency of the models built at different scales - from basin (small) scale to field-scale (large-scale). The models, nested in the common structural framework, are being constructed with regional geological knowledge, ensuring smooth transition in the 3D model resolution and amount of geological detail. Major challenge of the multiscale approach to subsurface modelling is the assessment and consistent quantification of various types of geological uncertainties tied to those various scale sub-models. Decreasing amount of information with depth and, particularly, very limited data collected below exploration targets, as well as accuracy and quality of data, all have the most critical impact on the modelled structure. In deeper levels of the Lublin Basin model, seismic interpretation of 2D surveys is sparsely tied to well data. Therefore time-to-depth conversion carries one of the major uncertainties in the modeling of structures, especially below 3000 m ssl. Furthermore, as all models at different scales are based on the same dataset, we must deal with different levels of generalization of geological structures. The

Development of Risk Uncertainty Factors from Historical NASA Projects

Science.gov (United States)

Amer, Tahani R.

2011-01-01

NASA is a good investment of federal funds and strives to provide the best value to the nation. NASA has consistently budgeted to unrealistic cost estimates, which are evident in the cost growth in many of its programs. In this investigation, NASA has been using available uncertainty factors from the Aerospace Corporation, Air Force, and Booz Allen Hamilton to develop projects risk posture. NASA has no insight into the developmental of these factors and, as demonstrated here, this can lead to unrealistic risks in many NASA Programs and projects (P/p). The primary contribution of this project is the development of NASA missions uncertainty factors, from actual historical NASA projects, to aid cost-estimating as well as for independent reviews which provide NASA senior management with information and analysis to determine the appropriate decision regarding P/p. In general terms, this research project advances programmatic analysis for NASA projects.

Uncertainty modelling and code calibration for composite materials

DEFF Research Database (Denmark)

Toft, Henrik Stensgaard; Branner, Kim; Mishnaevsky, Leon, Jr

2013-01-01

and measurement uncertainties which are introduced on the different scales. Typically, these uncertainties are taken into account in the design process using characteristic values and partial safety factors specified in a design standard. The value of the partial safety factors should reflect a reasonable balance...... to wind turbine blades are calibrated for two typical lay-ups using a large number of load cases and ratios between the aerodynamic forces and the inertia forces....

Understanding uncertainties in non-linear population trajectories: a Bayesian semi-parametric hierarchical approach to large-scale surveys of coral cover.

Directory of Open Access Journals (Sweden)

Julie Vercelloni

Full Text Available Recently, attempts to improve decision making in species management have focussed on uncertainties associated with modelling temporal fluctuations in populations. Reducing model uncertainty is challenging; while larger samples improve estimation of species trajectories and reduce statistical errors, they typically amplify variability in observed trajectories. In particular, traditional modelling approaches aimed at estimating population trajectories usually do not account well for nonlinearities and uncertainties associated with multi-scale observations characteristic of large spatio-temporal surveys. We present a Bayesian semi-parametric hierarchical model for simultaneously quantifying uncertainties associated with model structure and parameters, and scale-specific variability over time. We estimate uncertainty across a four-tiered spatial hierarchy of coral cover from the Great Barrier Reef. Coral variability is well described; however, our results show that, in the absence of additional model specifications, conclusions regarding coral trajectories become highly uncertain when considering multiple reefs, suggesting that management should focus more at the scale of individual reefs. The approach presented facilitates the description and estimation of population trajectories and associated uncertainties when variability cannot be attributed to specific causes and origins. We argue that our model can unlock value contained in large-scale datasets, provide guidance for understanding sources of uncertainty, and support better informed decision making.

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.

SFR inverse modelling Part 2. Uncertainty factors of predicted flow in deposition tunnels and uncertainty in distribution of flow paths from deposition tunnels

International Nuclear Information System (INIS)

Holmen, Johan

2007-10-01

The Swedish Nuclear Fuel and Waste Management Co (SKB) is operating the SFR repository for low- and intermediate-level nuclear waste. An update of the safety analysis of SFR was carried out by SKB as the SAFE project (Safety Assessment of Final Disposal of Operational Radioactive Waste). The aim of the project was to update the safety analysis and to produce a safety report. The safety report has been submitted to the Swedish authorities. This study is a continuation of the SAFE project, and concerns the hydrogeological modelling of the SFR repository, which was carried out as part of the SAFE project, it describes the uncertainty in the tunnel flow and distributions of flow paths from the storage tunnels. Uncertainty factors are produced for two different flow situations, corresponding to 2,000 AD (the sea covers the repository) and 4,000 AD (the sea has retreated form the repository area). Uncertainty factors are produced for the different deposition tunnels. The uncertainty factors are discussed in Chapter 2 and two lists (matrix) of uncertainty factors have been delivered as a part of this study. Flow paths are produced for two different flow situations, corresponding to 2,000 AD (the sea covers the repository) and 5,000 AD (the sea has retreated form the repository area). Flow paths from the different deposition tunnels have been simulated, considering the above discussed base case and the 60 realisation that passed all tests of this base case. The flow paths are presented and discussed in Chapter 3 and files presenting the results of the flow path analyses have been delivered as part of this study. The uncertainty factors (see Chapter 2) are not independent from the flow path data (see Chapter 3). When stochastic calculations are performed by use of a transport model and the data presented in this study is used as input to such calculations, the corresponding uncertainty factors and flow path data should be used. This study also includes a brief discussion of

Jet energy scale uncertainty correlations between ATLAS and CMS at 8 TeV

CERN Document Server

CMS and ATLAS Collaborations

2015-01-01

An evaluation of the correlations between ATLAS and CMS jet energy scale uncertainties is presented for $\\sqrt{s}=8$ TeV $pp$ collisions recorded in 2012. Uncertainties within each experiment are grouped based on the general type of systematic effect they are intended to cover and the means by which they are derived. Inter-experimental correlation value ranges are established for each corresponding group of uncertainty components. This correlation range is intended to cover the possible correlation values when performing combinations between the two experiments, where the most conservative value obtained from scanning over the correlation range should be used for the final combined measurement. The procedure described here is primarily aimed at single-observable analyses, and has limitations when applied to multi-observable measurements.

Single hadron response measurement and calorimeter jet energy scale uncertainty with the ATLAS detector at the LHC

CERN Document Server

Aad, Georges; Abdallah, Jalal; Abdelalim, Ahmed Ali; Abdesselam, Abdelouahab; Abdinov, Ovsat; Abi, Babak; Abolins, Maris; AbouZeid, Ossama; Abramowicz, Halina; Abreu, Henso; Acerbi, Emilio; Acharya, Bobby Samir; Adamczyk, Leszek; Adams, David; Addy, Tetteh; Adelman, Jahred; Aderholz, Michael; Adomeit, Stefanie; Adragna, Paolo; Adye, Tim; Aefsky, Scott; Aguilar-Saavedra, Juan Antonio; Aharrouche, Mohamed; Ahlen, Steven; Ahles, Florian; Ahmad, Ashfaq; Ahsan, Mahsana; Aielli, Giulio; Akdogan, Taylan; Åkesson, Torsten Paul Ake; Akimoto, Ginga; Akimov, Andrei; Akiyama, Kunihiro; Alam, Mohammad; Alam, Muhammad Aftab; Albert, Justin; Albrand, Solveig; Aleksa, Martin; Aleksandrov, Igor; Alessandria, Franco; Alexa, Calin; Alexander, Gideon; Alexandre, Gauthier; Alexopoulos, Theodoros; Alhroob, Muhammad; Aliev, Malik; Alimonti, Gianluca; Alison, John; Aliyev, Magsud; Allbrooke, Benedict; Allport, Phillip; Allwood-Spiers, Sarah; Almond, John; Aloisio, Alberto; Alon, Raz; Alonso, Alejandro; Alvarez Gonzalez, Barbara; Alviggi, Mariagrazia; Amako, Katsuya; Amaral, Pedro; Amelung, Christoph; Ammosov, Vladimir; Amorim, Antonio; Amorós, Gabriel; Amram, Nir; Anastopoulos, Christos; Ancu, Lucian Stefan; Andari, Nansi; Andeen, Timothy; Anders, Christoph Falk; Anders, Gabriel; Anderson, Kelby; Andreazza, Attilio; Andrei, George Victor; Andrieux, Marie-Laure; Anduaga, Xabier; Angerami, Aaron; Anghinolfi, Francis; Anisenkov, Alexey; Anjos, Nuno; Annovi, Alberto; Antonaki, Ariadni; Antonelli, Mario; Antonov, Alexey; Antos, Jaroslav; Anulli, Fabio; Aoun, Sahar; Aperio Bella, Ludovica; Apolle, Rudi; Arabidze, Giorgi; Aracena, Ignacio; Arai, Yasuo; Arce, Ayana; Arfaoui, Samir; Arguin, Jean-Francois; Arik, Engin; Arik, Metin; Armbruster, Aaron James; Arnaez, Olivier; Arnault, Christian; Artamonov, Andrei; Artoni, Giacomo; Arutinov, David; Asai, Shoji; Asfandiyarov, Ruslan; Ask, Stefan; Åsman, Barbro; Asquith, Lily; Assamagan, Ketevi; Astbury, Alan; Astvatsatourov, Anatoli; Aubert, Bernard; Auge, Etienne; Augsten, Kamil; Aurousseau, Mathieu; Avolio, Giuseppe; Avramidou, Rachel Maria; Axen, David; Ay, Cano; Azuelos, Georges; Azuma, Yuya; Baak, Max; Baccaglioni, Giuseppe; Bacci, Cesare; Bach, Andre; Bachacou, Henri; Bachas, Konstantinos; Backes, Moritz; Backhaus, Malte; Badescu, Elisabeta; Bagnaia, Paolo; Bahinipati, Seema; Bai, Yu; Bailey, David; Bain, Travis; Baines, John; Baker, Oliver Keith; Baker, Mark; Baker, Sarah; Banas, Elzbieta; Banerjee, Piyali; Banerjee, Swagato; Banfi, Danilo; Bangert, Andrea Michelle; Bansal, Vikas; Bansil, Hardeep Singh; Barak, Liron; Baranov, Sergei; Barashkou, Andrei; Barbaro Galtieri, Angela; Barber, Tom; Barberio, Elisabetta Luigia; Barberis, Dario; Barbero, Marlon; Bardin, Dmitri; Barillari, Teresa; Barisonzi, Marcello; Barklow, Timothy; Barlow, Nick; Barnett, Bruce; Barnett, Michael; Baroncelli, Antonio; Barone, Gaetano; Barr, Alan; Barreiro, Fernando; Barreiro Guimarães da Costa, João; Barrillon, Pierre; Bartoldus, Rainer; Barton, Adam Edward; Bartsch, Valeria; Bates, Richard; Batkova, Lucia; Batley, Richard; Battaglia, Andreas; Battistin, Michele; Bauer, Florian; Bawa, Harinder Singh; Beale, Steven; Beau, Tristan; Beauchemin, Pierre-Hugues; Beccherle, Roberto; Bechtle, Philip; Beck, Hans Peter; Becker, Sebastian; Beckingham, Matthew; Becks, Karl-Heinz; Beddall, Andrew; Beddall, Ayda; Bedikian, Sourpouhi; Bednyakov, Vadim; Bee, Christopher; Begel, Michael; Behar Harpaz, Silvia; Behera, Prafulla; Beimforde, Michael; Belanger-Champagne, Camille; Bell, Paul; Bell, William; Bella, Gideon; Bellagamba, Lorenzo; Bellina, Francesco; Bellomo, Massimiliano; Belloni, Alberto; Beloborodova, Olga; Belotskiy, Konstantin; Beltramello, Olga; Ben Ami, Sagi; Benary, Odette; Benchekroun, Driss; Benchouk, Chafik; Bendel, Markus; Benekos, Nektarios; Benhammou, Yan; Benhar Noccioli, Eleonora; Benitez Garcia, Jorge-Armando; Benjamin, Douglas; Benoit, Mathieu; Bensinger, James; Benslama, Kamal; Bentvelsen, Stan; Berge, David; Bergeaas Kuutmann, Elin; Berger, Nicolas; Berghaus, Frank; Berglund, Elina; Beringer, Jürg; Bernat, Pauline; Bernhard, Ralf; Bernius, Catrin; Berry, Tracey; Bertella, Claudia; Bertin, Antonio; Bertinelli, Francesco; Bertolucci, Federico; Besana, Maria Ilaria; Besson, Nathalie; Bethke, Siegfried; Bhimji, Wahid; Bianchi, Riccardo-Maria; Bianco, Michele; Biebel, Otmar; Bieniek, Stephen Paul; Bierwagen, Katharina; Biesiada, Jed; Biglietti, Michela; Bilokon, Halina; Bindi, Marcello; Binet, Sebastien; Bingul, Ahmet; Bini, Cesare; Biscarat, Catherine; Bitenc, Urban; Black, Kevin; Blair, Robert; Blanchard, Jean-Baptiste; Blanchot, Georges; Blazek, Tomas; Blocker, Craig; Blocki, Jacek; Blondel, Alain; Blum, Walter; Blumenschein, Ulrike; Bobbink, Gerjan; Bobrovnikov, Victor; Bocchetta, Simona Serena; Bocci, Andrea; Boddy, Christopher Richard; Boehler, Michael; Boek, Jennifer; Boelaert, Nele; Bogaerts, Joannes Andreas; Bogdanchikov, Alexander; Bogouch, Andrei; Bohm, Christian; Boisvert, Veronique; Bold, Tomasz; Boldea, Venera; Bolnet, Nayanka Myriam; Bona, Marcella; Bondarenko, Valery; Bondioli, Mario; Boonekamp, Maarten; Booth, Chris; Bordoni, Stefania; Borer, Claudia; Borisov, Anatoly; Borissov, Guennadi; Borjanovic, Iris; Borri, Marcello; Borroni, Sara; Bortolotto, Valerio; Bos, Kors; Boscherini, Davide; Bosman, Martine; Boterenbrood, Hendrik; Botterill, David; Bouchami, Jihene; Boudreau, Joseph; Bouhova-Thacker, Evelina Vassileva; Boumediene, Djamel Eddine; Bourdarios, Claire; Bousson, Nicolas; Boveia, Antonio; Boyd, James; Boyko, Igor; Bozhko, Nikolay; Bozovic-Jelisavcic, Ivanka; Bracinik, Juraj; Braem, André; Branchini, Paolo; Brandenburg, George; Brandt, Andrew; Brandt, Gerhard; Brandt, Oleg; Bratzler, Uwe; Brau, Benjamin; Brau, James; Braun, Helmut; Brelier, Bertrand; Bremer, Johan; Brenner, Richard; Bressler, Shikma; Britton, Dave; Brochu, Frederic; Brock, Ian; Brock, Raymond; Brodbeck, Timothy; Brodet, Eyal; Broggi, Francesco; Bromberg, Carl; Bronner, Johanna; Brooijmans, Gustaaf; Brooks, William; Brown, Gareth; Brown, Heather; Bruckman de Renstrom, Pawel; Bruncko, Dusan; Bruneliere, Renaud; Brunet, Sylvie; Bruni, Alessia; Bruni, Graziano; Bruschi, Marco; Buanes, Trygve; Buat, Quentin; Bucci, Francesca; Buchanan, James; Buchanan, Norman; Buchholz, Peter; Buckingham, Ryan; Buckley, Andrew; Buda, Stelian Ioan; Budagov, Ioulian; Budick, Burton; Büscher, Volker; Bugge, Lars; Bulekov, Oleg; Bunse, Moritz; Buran, Torleiv; Burckhart, Helfried; Burdin, Sergey; Burgard, Carsten Daniel; Burgess, Thomas; Burke, Stephen; Busato, Emmanuel; Bussey, Peter; Buszello, Claus-Peter; Butin, François; Butler, Bart; Butler, John; Buttar, Craig; Butterworth, Jonathan; Buttinger, William; Cabrera Urbán, Susana; Caforio, Davide; Cakir, Orhan; Calafiura, Paolo; Calderini, Giovanni; Calfayan, Philippe; Calkins, Robert; Caloba, Luiz; Caloi, Rita; Calvet, David; Calvet, Samuel; Camacho Toro, Reina; Camarri, Paolo; Cambiaghi, Mario; Cameron, David; Caminada, Lea Michaela; Campana, Simone; Campanelli, Mario; Canale, Vincenzo; Canelli, Florencia; Canepa, Anadi; Cantero, Josu; Capasso, Luciano; Capeans Garrido, Maria Del Mar; Caprini, Irinel; Caprini, Mihai; Capriotti, Daniele; Capua, Marcella; Caputo, Regina; Caramarcu, Costin; Cardarelli, Roberto; Carli, Tancredi; Carlino, Gianpaolo; Carminati, Leonardo; Caron, Bryan; Caron, Sascha; Carrillo Montoya, German D; Carter, Antony; Carter, Janet; Carvalho, João; Casadei, Diego; Casado, Maria Pilar; Cascella, Michele; Caso, Carlo; Castaneda Hernandez, Alfredo Martin; Castaneda-Miranda, Elizabeth; Castillo Gimenez, Victoria; Castro, Nuno Filipe; Cataldi, Gabriella; Cataneo, Fernando; Catinaccio, Andrea; Catmore, James; Cattai, Ariella; Cattani, Giordano; Caughron, Seth; Cauz, Diego; Cavalleri, Pietro; Cavalli, Donatella; Cavalli-Sforza, Matteo; Cavasinni, Vincenzo; Ceradini, Filippo; Santiago Cerqueira, Augusto; Cerri, Alessandro; Cerrito, Lucio; Cerutti, Fabio; Cetin, Serkant Ali; Cevenini, Francesco; Chafaq, Aziz; Chakraborty, Dhiman; Chan, Kevin; Chapleau, Bertrand; Chapman, John Derek; Chapman, John Wehrley; Chareyre, Eve; Charlton, Dave; Chavda, Vikash; Chavez Barajas, Carlos Alberto; Cheatham, Susan; Chekanov, Sergei; Chekulaev, Sergey; Chelkov, Gueorgui; Chelstowska, Magda Anna; Chen, Chunhui; Chen, Hucheng; Chen, Shenjian; Chen, Tingyang; Chen, Xin; Cheng, Shaochen; Cheplakov, Alexander; Chepurnov, Vladimir; Cherkaoui El Moursli, Rajaa; Chernyatin, Valeriy; Cheu, Elliott; Cheung, Sing-Leung; Chevalier, Laurent; Chiefari, Giovanni; Chikovani, Leila; Childers, John Taylor; Chilingarov, Alexandre; Chiodini, Gabriele; Chisholm, Andrew; Chizhov, Mihail; Choudalakis, Georgios; Chouridou, Sofia; Christidi, Illectra-Athanasia; Christov, Asen; Chromek-Burckhart, Doris; Chu, Ming-Lee; Chudoba, Jiri; Ciapetti, Guido; Ciba, Krzysztof; Ciftci, Abbas Kenan; Ciftci, Rena; Cinca, Diane; Cindro, Vladimir; Ciobotaru, Matei Dan; Ciocca, Claudia; Ciocio, Alessandra; Cirilli, Manuela; Citterio, Mauro; Ciubancan, Mihai; Clark, Allan G; Clark, Philip James; Cleland, Bill; Clemens, Jean-Claude; Clement, Benoit; Clement, Christophe; Clifft, Roger; Coadou, Yann; Cobal, Marina; Coccaro, Andrea; Cochran, James H; Coe, Paul; Cogan, Joshua Godfrey; Coggeshall, James; Cogneras, Eric; Colas, Jacques; Colijn, Auke-Pieter; Collard, Caroline; Collins, Neil; Collins-Tooth, Christopher; Collot, Johann; Colon, German; Conde Muiño, Patricia; Coniavitis, Elias; Conidi, Maria Chiara; Consonni, Michele; Consorti, Valerio; Constantinescu, Serban; Conta, Claudio; Conventi, Francesco; Cook, James; Cooke, Mark; Cooper, Ben; Cooper-Sarkar, Amanda; Copic, Katherine; Cornelissen, Thijs; Corradi, Massimo; Corriveau, Francois; Cortes-Gonzalez, Arely; Cortiana, Giorgio; Costa, Giuseppe; Costa, María José; Costanzo, Davide; Costin, Tudor; Côté, David; Coura Torres, Rodrigo; Courneyea, Lorraine; Cowan, Glen; Cowden, Christopher; Cox, Brian; Cranmer, Kyle; Crescioli, Francesco; Cristinziani, Markus; Crosetti, Giovanni; Crupi, Roberto; Crépé-Renaudin, Sabine; Cuciuc, Constantin-Mihai; Cuenca Almenar, Cristóbal; Cuhadar Donszelmann, Tulay; Curatolo, Maria; Curtis, Chris; Cuthbert, Cameron; Cwetanski, Peter; Czirr, Hendrik; Czodrowski, Patrick; Czyczula, Zofia; D'Auria, Saverio; D'Onofrio, Monica; D'Orazio, Alessia; Da Silva, Paulo Vitor; Da Via, Cinzia; Dabrowski, Wladyslaw; Dai, Tiesheng; Dallapiccola, Carlo; Dam, Mogens; Dameri, Mauro; Damiani, Daniel; Danielsson, Hans Olof; Dannheim, Dominik; Dao, Valerio; Darbo, Giovanni; Darlea, Georgiana Lavinia; Davey, Will; Davidek, Tomas; Davidson, Nadia; Davidson, Ruth; Davies, Eleanor; Davies, Merlin; Davison, Adam; Davygora, Yuriy; Dawe, Edmund; Dawson, Ian; Dawson, John; Daya, Rozmin; De, Kaushik; de Asmundis, Riccardo; De Castro, Stefano; De Castro Faria Salgado, Pedro; De Cecco, Sandro; de Graat, Julien; De Groot, Nicolo; de Jong, Paul; De La Taille, Christophe; De la Torre, Hector; De Lotto, Barbara; de Mora, Lee; De Nooij, Lucie; De Pedis, Daniele; De Salvo, Alessandro; De Sanctis, Umberto; De Santo, Antonella; De Vivie De Regie, Jean-Baptiste; Dean, Simon; Dearnaley, William James; Debbe, Ramiro; Debenedetti, Chiara; Dedovich, Dmitri; Degenhardt, James; Dehchar, Mohamed; Del Papa, Carlo; Del Peso, Jose; Del Prete, Tarcisio; Delemontex, Thomas; Deliyergiyev, Maksym; Dell'Acqua, Andrea; Dell'Asta, Lidia; Della Pietra, Massimo; della Volpe, Domenico; Delmastro, Marco; Delruelle, Nicolas; Delsart, Pierre-Antoine; Deluca, Carolina; Demers, Sarah; Demichev, Mikhail; Demirkoz, Bilge; Deng, Jianrong; Denisov, Sergey; Derendarz, Dominik; Derkaoui, Jamal Eddine; Derue, Frederic; Dervan, Paul; Desch, Klaus Kurt; Devetak, Erik; Deviveiros, Pier-Olivier; Dewhurst, Alastair; DeWilde, Burton; Dhaliwal, Saminder; Dhullipudi, Ramasudhakar; Di Ciaccio, Anna; Di Ciaccio, Lucia; Di Girolamo, Alessandro; Di Girolamo, Beniamino; Di Luise, Silvestro; Di Mattia, Alessandro; Di Micco, Biagio; Di Nardo, Roberto; Di Simone, Andrea; Di Sipio, Riccardo; Diaz, Marco Aurelio; Diblen, Faruk; Diehl, Edward; Dietrich, Janet; Dietzsch, Thorsten; Diglio, Sara; Dindar Yagci, Kamile; Dingfelder, Jochen; Dionisi, Carlo; Dita, Petre; Dita, Sanda; Dittus, Fridolin; Djama, Fares; Djobava, Tamar; Barros do Vale, Maria Aline; Do Valle Wemans, André; Doan, Thi Kieu Oanh; Dobbs, Matt; Dobinson, Robert; Dobos, Daniel; Dobson, Ellie; Dobson, Marc; Dodd, Jeremy; Doglioni, Caterina; Doherty, Tom; Doi, Yoshikuni; Dolejsi, Jiri; Dolenc, Irena; Dolezal, Zdenek; Dolgoshein, Boris; Dohmae, Takeshi; Donadelli, Marisilvia; Donega, Mauro; Donini, Julien; Dopke, Jens; Doria, Alessandra; Dos Anjos, Andre; Dosil, Mireia; Dotti, Andrea; Dova, Maria-Teresa; Dowell, John; Doxiadis, Alexander; Doyle, Tony; Drasal, Zbynek; Drees, Jürgen; Dressnandt, Nandor; Drevermann, Hans; Driouichi, Chafik; Dris, Manolis; Dubbert, Jörg; Dube, Sourabh; Duchovni, Ehud; Duckeck, Guenter; Dudarev, Alexey; Dudziak, Fanny; Dührssen, Michael; Duerdoth, Ian; Duflot, Laurent; Dufour, Marc-Andre; Dunford, Monica; Duran Yildiz, Hatice; Duxfield, Robert; Dwuznik, Michal; Dydak, Friedrich; Düren, Michael; Ebenstein, William; Ebke, Johannes; Eckweiler, Sebastian; Edmonds, Keith; Edwards, Clive; Edwards, Nicholas Charles; Ehrenfeld, Wolfgang; Ehrich, Thies; Eifert, Till; Eigen, Gerald; Einsweiler, Kevin; Eisenhandler, Eric; Ekelof, Tord; El Kacimi, Mohamed; Ellert, Mattias; Elles, Sabine; Ellinghaus, Frank; Ellis, Katherine; Ellis, Nicolas; Elmsheuser, Johannes; Elsing, Markus; Emeliyanov, Dmitry; Engelmann, Roderich; Engl, Albert; Epp, Brigitte; Eppig, Andrew; Erdmann, Johannes; Ereditato, Antonio; Eriksson, Daniel; Ernst, Jesse; Ernst, Michael; Ernwein, Jean; Errede, Deborah; Errede, Steven; Ertel, Eugen; Escalier, Marc; Escobar, Carlos; Espinal Curull, Xavier; Esposito, Bellisario; Etienne, Francois; Etienvre, Anne-Isabelle; Etzion, Erez; Evangelakou, Despoina; Evans, Hal; Fabbri, Laura; Fabre, Caroline; Fakhrutdinov, Rinat; Falciano, Speranza; Fang, Yaquan; Fanti, Marcello; Farbin, Amir; Farilla, Addolorata; Farley, Jason; Farooque, Trisha; Farrington, Sinead; Farthouat, Philippe; Fassnacht, Patrick; Fassouliotis, Dimitrios; Fatholahzadeh, Baharak; Favareto, Andrea; Fayard, Louis; Fazio, Salvatore; Febbraro, Renato; Federic, Pavol; Fedin, Oleg; Fedorko, Woiciech; Fehling-Kaschek, Mirjam; Feligioni, Lorenzo; Fellmann, Denis; Feng, Cunfeng; Feng, Eric; Fenyuk, Alexander; Ferencei, Jozef; Ferland, Jonathan; Fernando, Waruna; Ferrag, Samir; Ferrando, James; Ferrara, Valentina; Ferrari, Arnaud; Ferrari, Pamela; Ferrari, Roberto; Ferreira de Lima, Danilo Enoque; Ferrer, Antonio; Ferrer, Maria Lorenza; Ferrere, Didier; Ferretti, Claudio; Ferretto Parodi, Andrea; Fiascaris, Maria; Fiedler, Frank; Filipčič, Andrej; Filippas, Anastasios; Filthaut, Frank; Fincke-Keeler, Margret; Fiolhais, Miguel; Fiorini, Luca; Firan, Ana; Fischer, Gordon; Fischer, Peter; Fisher, Matthew; Flechl, Martin; Fleck, Ivor; Fleckner, Johanna; Fleischmann, Philipp; Fleischmann, Sebastian; Flick, Tobias; Floderus, Anders; Flores Castillo, Luis; Flowerdew, Michael; Fokitis, Manolis; Fonseca Martin, Teresa; Forbush, David Alan; Formica, Andrea; Forti, Alessandra; Fortin, Dominique; Foster, Joe; Fournier, Daniel; Foussat, Arnaud; Fowler, Andrew; Fowler, Ken; Fox, Harald; Francavilla, Paolo; Franchino, Silvia; Francis, David; Frank, Tal; Franklin, Melissa; Franz, Sebastien; Fraternali, Marco; Fratina, Sasa; French, Sky; Friedrich, Felix; Froeschl, Robert; Froidevaux, Daniel; Frost, James; Fukunaga, Chikara; Fullana Torregrosa, Esteban; Fuster, Juan; Gabaldon, Carolina; Gabizon, Ofir; Gadfort, Thomas; Gadomski, Szymon; Gagliardi, Guido; Gagnon, Pauline; Galea, Cristina; Gallas, Elizabeth; Gallo, Valentina Santina; Gallop, Bruce; Gallus, Petr; Gan, KK; Gao, Yongsheng; Gapienko, Vladimir; Gaponenko, Andrei; Garberson, Ford; Garcia-Sciveres, Maurice; García, Carmen; García Navarro, José Enrique; Gardner, Robert; Garelli, Nicoletta; Garitaonandia, Hegoi; Garonne, Vincent; Garvey, John; Gatti, Claudio; Gaudio, Gabriella; Gaur, Bakul; Gauthier, Lea; Gavrilenko, Igor; Gay, Colin; Gaycken, Goetz; Gayde, Jean-Christophe; Gazis, Evangelos; Ge, Peng; Gee, Norman; Geerts, Daniël Alphonsus Adrianus; Geich-Gimbel, Christoph; Gellerstedt, Karl; Gemme, Claudia; Gemmell, Alistair; Genest, Marie-Hélène; Gentile, Simonetta; George, Matthias; George, Simon; Gerlach, Peter; Gershon, Avi; Geweniger, Christoph; Ghazlane, Hamid; Ghodbane, Nabil; Giacobbe, Benedetto; Giagu, Stefano; Giakoumopoulou, Victoria; Giangiobbe, Vincent; Gianotti, Fabiola; Gibbard, Bruce; Gibson, Adam; Gibson, Stephen; Gilbert, Laura; Gilewsky, Valentin; Gillberg, Dag; Gillman, Tony; Gingrich, Douglas; Ginzburg, Jonatan; Giokaris, Nikos; Giordani, MarioPaolo; Giordano, Raffaele; Giorgi, Francesco Michelangelo; Giovannini, Paola; Giraud, Pierre-Francois; Giugni, Danilo; Giunta, Michele; Giusti, Paolo; Gjelsten, Børge Kile; Gladilin, Leonid; Glasman, Claudia; Glatzer, Julian; Glazov, Alexandre; Glitza, Karl-Walter; Glonti, George; Goddard, Jack Robert; Godfrey, Jennifer; Godlewski, Jan; Goebel, Martin; Göpfert, Thomas; Goeringer, Christian; Gössling, Claus; Göttfert, Tobias; Goldfarb, Steven; Golling, Tobias; Gomes, Agostinho; Gomez Fajardo, Luz Stella; Gonçalo, Ricardo; Goncalves Pinto Firmino Da Costa, Joao; Gonella, Laura; Gonidec, Allain; Gonzalez, Saul; González de la Hoz, Santiago; Gonzalez Parra, Garoe; Gonzalez Silva, Laura; Gonzalez-Sevilla, Sergio; Goodson, Jeremiah Jet; Goossens, Luc; Gorbounov, Petr Andreevich; Gordon, Howard; Gorelov, Igor; Gorfine, Grant; Gorini, Benedetto; Gorini, Edoardo; Gorišek, Andrej; Gornicki, Edward; Gorokhov, Serguei; Goryachev, Vladimir; Gosdzik, Bjoern; Gosselink, Martijn; Gostkin, Mikhail Ivanovitch; Gough Eschrich, Ivo; Gouighri, Mohamed; Goujdami, Driss; Goulette, Marc Phillippe; Goussiou, Anna; Goy, Corinne; Gozpinar, Serdar; Grabowska-Bold, Iwona; Grafström, Per; Grahn, Karl-Johan; Grancagnolo, Francesco; Grancagnolo, Sergio; Grassi, Valerio; Gratchev, Vadim; Grau, Nathan; Gray, Heather; Gray, Julia Ann; Graziani, Enrico; Grebenyuk, Oleg; Greenshaw, Timothy; Greenwood, Zeno Dixon; Gregersen, Kristian; Gregor, Ingrid-Maria; Grenier, Philippe; Griffiths, Justin; Grigalashvili, Nugzar; Grillo, Alexander; Grinstein, Sebastian; Grishkevich, Yaroslav; Grivaz, Jean-Francois; Groh, Manfred; Gross, Eilam; Grosse-Knetter, Joern; Groth-Jensen, Jacob; Grybel, Kai; Guarino, Victor; Guest, Daniel; Guicheney, Christophe; Guida, Angelo; Guindon, Stefan; Guler, Hulya; Gunther, Jaroslav; Guo, Bin; Guo, Jun; Gupta, Ambreesh; Gusakov, Yury; Gushchin, Vladimir; Gutierrez, Phillip; Guttman, Nir; Gutzwiller, Olivier; Guyot, Claude; Gwenlan, Claire; Gwilliam, Carl; Haas, Andy; Haas, Stefan; Haber, Carl; Hackenburg, Robert; Hadavand, Haleh Khani; Hadley, David; Haefner, Petra; Hahn, Ferdinand; Haider, Stefan; Hajduk, Zbigniew; Hakobyan, Hrachya; Hall, David; Haller, Johannes; Hamacher, Klaus; Hamal, Petr; Hamer, Matthias; Hamilton, Andrew; Hamilton, Samuel; Han, Hongguang; Han, Liang; Hanagaki, Kazunori; Hanawa, Keita; Hance, Michael; Handel, Carsten; Hanke, Paul; Hansen, John Renner; Hansen, Jørgen Beck; Hansen, Jorn Dines; Hansen, Peter Henrik; Hansson, Per; Hara, Kazuhiko; Hare, Gabriel; Harenberg, Torsten; Harkusha, Siarhei; Harper, Devin; Harrington, Robert; Harris, Orin; Harrison, Karl; Hartert, Jochen; Hartjes, Fred; Haruyama, Tomiyoshi; Harvey, Alex; Hasegawa, Satoshi; Hasegawa, Yoji; Hassani, Samira; Hatch, Mark; Hauff, Dieter; Haug, Sigve; Hauschild, Michael; Hauser, Reiner; Havranek, Miroslav; Hawes, Brian; Hawkes, Christopher; Hawkings, Richard John; Hawkins, Anthony David; Hawkins, Donovan; Hayakawa, Takashi; Hayashi, Takayasu; Hayden, Daniel; Hayward, Helen; Haywood, Stephen; Hazen, Eric; He, Mao; Head, Simon; Hedberg, Vincent; Heelan, Louise; Heim, Sarah; Heinemann, Beate; Heisterkamp, Simon; Helary, Louis; Heller, Claudio; Heller, Matthieu; Hellman, Sten; Hellmich, Dennis; Helsens, Clement; Henderson, Robert; Henke, Michael; Henrichs, Anna; Henriques Correia, Ana Maria; Henrot-Versille, Sophie; Henry-Couannier, Frédéric; Hensel, Carsten; Henß, Tobias; Medina Hernandez, Carlos; Hernández Jiménez, Yesenia; Herrberg, Ruth; Hershenhorn, Alon David; Herten, Gregor; Hertenberger, Ralf; Hervas, Luis; Hesketh, Gavin Grant; Hessey, Nigel; Higón-Rodriguez, Emilio; Hill, Daniel; Hill, John; Hill, Norman; Hiller, Karl Heinz; Hillert, Sonja; Hillier, Stephen; Hinchliffe, Ian; Hines, Elizabeth; Hirose, Minoru; Hirsch, Florian; Hirschbuehl, Dominic; Hobbs, John; Hod, Noam; Hodgkinson, Mark; Hodgson, Paul; Hoecker, Andreas; Hoeferkamp, Martin; Hoffman, Julia; Hoffmann, Dirk; Hohlfeld, Marc; Holder, Martin; Holmgren, Sven-Olof; Holy, Tomas; Holzbauer, Jenny; Homma, Yasuhiro; Hong, Tae Min; Hooft van Huysduynen, Loek; Horazdovsky, Tomas; Horn, Claus; Horner, Stephan; Hostachy, Jean-Yves; Hou, Suen; Houlden, Michael; Hoummada, Abdeslam; Howarth, James; Howell, David; Hristova, Ivana; Hrivnac, Julius; Hruska, Ivan; Hryn'ova, Tetiana; Hsu, Pai-hsien Jennifer; Hsu, Shih-Chieh; Huang, Guang Shun; Hubacek, Zdenek; Hubaut, Fabrice; Huegging, Fabian; Huettmann, Antje; Huffman, Todd Brian; Hughes, Emlyn; Hughes, Gareth; Hughes-Jones, Richard; Huhtinen, Mika; Hurst, Peter; Hurwitz, Martina; Husemann, Ulrich; Huseynov, Nazim; Huston, Joey; Huth, John; Iacobucci, Giuseppe; Iakovidis, Georgios; Ibbotson, Michael; Ibragimov, Iskander; Ichimiya, Ryo; Iconomidou-Fayard, Lydia; Idarraga, John; Iengo, Paolo; Igonkina, Olga; Ikegami, Yoichi; Ikeno, Masahiro; Ilchenko, Yuri; Iliadis, Dimitrios; Ilic, Nikolina; Imori, Masatoshi; Ince, Tayfun; Inigo-Golfin, Joaquin; Ioannou, Pavlos; Iodice, Mauro; Ippolito, Valerio; Irles Quiles, Adrian; Isaksson, Charlie; Ishikawa, Akimasa; Ishino, Masaya; Ishmukhametov, Renat; Issever, Cigdem; Istin, Serhat; Ivashin, Anton; Iwanski, Wieslaw; Iwasaki, Hiroyuki; Izen, Joseph; Izzo, Vincenzo; Jackson, Brett; Jackson, John; Jackson, Paul; Jaekel, Martin; Jain, Vivek; Jakobs, Karl; Jakobsen, Sune; Jakubek, Jan; Jana, Dilip; Jankowski, Ernest; Jansen, Eric; Jansen, Hendrik; Jantsch, Andreas; Janus, Michel; Jarlskog, Göran; Jeanty, Laura; Jelen, Kazimierz; Jen-La Plante, Imai; Jenni, Peter; Jeremie, Andrea; Jež, Pavel; Jézéquel, Stéphane; Jha, Manoj Kumar; Ji, Haoshuang; Ji, Weina; Jia, Jiangyong; Jiang, Yi; Jimenez Belenguer, Marcos; Jin, Ge; Jin, Shan; Jinnouchi, Osamu; Joergensen, Morten Dam; Joffe, David; Johansen, Lars; Johansen, Marianne; Johansson, Erik; Johansson, Per; Johnert, Sebastian; Johns, Kenneth; Jon-And, Kerstin; Jones, Graham; Jones, Roger; Jones, Tegid; Jones, Tim; Jonsson, Ove; Joram, Christian; Jorge, Pedro; Joseph, John; Jovicevic, Jelena; Jovin, Tatjana; Ju, Xiangyang; Jung, Christian; Jungst, Ralph Markus; Juranek, Vojtech; Jussel, Patrick; Juste Rozas, Aurelio; Kabachenko, Vasily; Kabana, Sonja; Kaci, Mohammed; Kaczmarska, Anna; Kadlecik, Peter; Kado, Marumi; Kagan, Harris; Kagan, Michael; Kaiser, Steffen; Kajomovitz, Enrique; Kalinin, Sergey; Kalinovskaya, Lidia; Kama, Sami; Kanaya, Naoko; Kaneda, Michiru; Kaneti, Steven; Kanno, Takayuki; Kantserov, Vadim; Kanzaki, Junichi; Kaplan, Benjamin; Kapliy, Anton; Kaplon, Jan; Kar, Deepak; Karagoz, Muge; Karnevskiy, Mikhail; Karr, Kristo; Kartvelishvili, Vakhtang; Karyukhin, Andrey; Kashif, Lashkar; Kasieczka, Gregor; Kasmi, Azzedine; Kass, Richard; Kastanas, Alex; Kataoka, Mayuko; Kataoka, Yousuke; Katsoufis, Elias; Katzy, Judith; Kaushik, Venkatesh; Kawagoe, Kiyotomo; Kawamoto, Tatsuo; Kawamura, Gen; Kayl, Manuel; Kazanin, Vassili; Kazarinov, Makhail; Keeler, Richard; Kehoe, Robert; Keil, Markus; Kekelidze, George; Kennedy, John; Kenney, Christopher John; Kenyon, Mike; Kepka, Oldrich; Kerschen, Nicolas; Kerševan, Borut Paul; Kersten, Susanne; Kessoku, Kohei; Keung, Justin; Khakzad, Mohsen; Khalil-zada, Farkhad; Khandanyan, Hovhannes; Khanov, Alexander; Kharchenko, Dmitri; Khodinov, Alexander; Kholodenko, Anatoli; Khomich, Andrei; Khoo, Teng Jian; Khoriauli, Gia; Khoroshilov, Andrey; Khovanskiy, Nikolai; Khovanskiy, Valery; Khramov, Evgeniy; Khubua, Jemal; Kim, Hyeon Jin; Kim, Min Suk; Kim, Shinhong; Kimura, Naoki; Kind, Oliver; King, Barry; King, Matthew; King, Robert Steven Beaufoy; Kirk, Julie; Kirsch, Lawrence; Kiryunin, Andrey; Kishimoto, Tomoe; Kisielewska, Danuta; Kittelmann, Thomas; Kiver, Andrey; Kladiva, Eduard; Klaiber-Lodewigs, Jonas; Klein, Max; Klein, Uta; Kleinknecht, Konrad; Klemetti, Miika; Klier, Amit; Klimek, Pawel; Klimentov, Alexei; Klingenberg, Reiner; Klinger, Joel Alexander; Klinkby, Esben; Klioutchnikova, Tatiana; Klok, Peter; Klous, Sander; Kluge, Eike-Erik; Kluge, Thomas; Kluit, Peter; Kluth, Stefan; Knecht, Neil; Kneringer, Emmerich; Knobloch, Juergen; Knoops, Edith; Knue, Andrea; Ko, Byeong Rok; Kobayashi, Tomio; Kobel, Michael; Kocian, Martin; Kodys, Peter; Köneke, Karsten; König, Adriaan; Koenig, Sebastian; Köpke, Lutz; Koetsveld, Folkert; Koevesarki, Peter; Koffas, Thomas; Koffeman, Els; Kogan, Lucy Anne; Kohn, Fabian; Kohout, Zdenek; Kohriki, Takashi; Koi, Tatsumi; Kokott, Thomas; Kolachev, Guennady; Kolanoski, Hermann; Kolesnikov, Vladimir; Koletsou, Iro; Koll, James; Kollefrath, Michael; Kolya, Scott; Komar, Aston; Komori, Yuto; Kondo, Takahiko; Kono, Takanori; Kononov, Anatoly; Konoplich, Rostislav; Konstantinidis, Nikolaos; Kootz, Andreas; Koperny, Stefan; Korcyl, Krzysztof; Kordas, Kostantinos; Koreshev, Victor; Korn, Andreas; Korol, Aleksandr; Korolkov, Ilya; Korolkova, Elena; Korotkov, Vladislav; Kortner, Oliver; Kortner, Sandra; Kostyukhin, Vadim; Kotamäki, Miikka Juhani; Kotov, Sergey; Kotov, Vladislav; Kotwal, Ashutosh; Kourkoumelis, Christine; Kouskoura, Vasiliki; Koutsman, Alex; Kowalewski, Robert Victor; Kowalski, Tadeusz; Kozanecki, Witold; Kozhin, Anatoly; Kral, Vlastimil; Kramarenko, Viktor; Kramberger, Gregor; Krasny, Mieczyslaw Witold; Krasznahorkay, Attila; Kraus, James; Kraus, Jana; Kreisel, Arik; Krejci, Frantisek; Kretzschmar, Jan; Krieger, Nina; Krieger, Peter; Kroeninger, Kevin; Kroha, Hubert; Kroll, Joe; Kroseberg, Juergen; Krstic, Jelena; Kruchonak, Uladzimir; Krüger, Hans; Kruker, Tobias; Krumnack, Nils; Krumshteyn, Zinovii; Kruth, Andre; Kubota, Takashi; Kuday, Sinan; Kuehn, Susanne; Kugel, Andreas; Kuhl, Thorsten; Kuhn, Dietmar; Kukhtin, Victor; Kulchitsky, Yuri; Kuleshov, Sergey; Kummer, Christian; Kuna, Marine; Kundu, Nikhil; Kunkle, Joshua; Kupco, Alexander; Kurashige, Hisaya; Kurata, Masakazu; Kurochkin, Yurii; Kus, Vlastimil; Kuwertz, Emma Sian; Kuze, Masahiro; Kvita, Jiri; Kwee, Regina; La Rosa, Alessandro; La Rotonda, Laura; Labarga, Luis; Labbe, Julien; Lablak, Said; Lacasta, Carlos; Lacava, Francesco; Lacker, Heiko; Lacour, Didier; Lacuesta, Vicente Ramón; Ladygin, Evgueni; Lafaye, Remi; Laforge, Bertrand; Lagouri, Theodota; Lai, Stanley; Laisne, Emmanuel; Lamanna, Massimo; Lampen, Caleb; Lampl, Walter; Lancon, Eric; Landgraf, Ulrich; Landon, Murrough; Lane, Jenna; Lange, Clemens; Lankford, Andrew; Lanni, Francesco; Lantzsch, Kerstin; Laplace, Sandrine; Lapoire, Cecile; Laporte, Jean-Francois; Lari, Tommaso; Larionov, Anatoly; Larner, Aimee; Lasseur, Christian; Lassnig, Mario; Laurelli, Paolo; Lavorini, Vincenzo; Lavrijsen, Wim; Laycock, Paul; Lazarev, Alexandre; Le Dortz, Olivier; Le Guirriec, Emmanuel; Le Maner, Christophe; Le Menedeu, Eve; Lebel, Céline; LeCompte, Thomas; Ledroit-Guillon, Fabienne Agnes Marie; Lee, Hurng-Chun; Lee, Jason; Lee, Shih-Chang; Lee, Lawrence; Lefebvre, Michel; Legendre, Marie; Leger, Annie; LeGeyt, Benjamin; Legger, Federica; Leggett, Charles; Lehmacher, Marc; Lehmann Miotto, Giovanna; Lei, Xiaowen; Leite, Marco Aurelio Lisboa; Leitner, Rupert; Lellouch, Daniel; Leltchouk, Mikhail; Lemmer, Boris; Lendermann, Victor; Leney, Katharine; Lenz, Tatiana; Lenzen, Georg; Lenzi, Bruno; Leonhardt, Kathrin; Leontsinis, Stefanos; Leroy, Claude; Lessard, Jean-Raphael; Lesser, Jonas; Lester, Christopher; Leung Fook Cheong, Annabelle; Levêque, Jessica; Levin, Daniel; Levinson, Lorne; Levitski, Mikhail; Lewis, Adrian; Lewis, George; Leyko, Agnieszka; Leyton, Michael; Li, Bo; Li, Haifeng; Li, Shu; Li, Xuefei; Liang, Zhijun; Liao, Hongbo; Liberti, Barbara; Lichard, Peter; Lichtnecker, Markus; Lie, Ki; Liebig, Wolfgang; Lifshitz, Ronen; Lilley, Joseph; Limbach, Christian; Limosani, Antonio; Limper, Maaike; Lin, Simon; Linde, Frank; Linnemann, James; Lipeles, Elliot; Lipinsky, Lukas; Lipniacka, Anna; Liss, Tony; Lissauer, David; Lister, Alison; Litke, Alan; Liu, Chuanlei; Liu, Dong; Liu, Hao; Liu, Jianbei; Liu, Minghui; Liu, Yanwen; Livan, Michele; Livermore, Sarah; Lleres, Annick; Llorente Merino, Javier; Lloyd, Stephen; Lobodzinska, Ewelina; Loch, Peter; Lockman, William; Loddenkoetter, Thomas; Loebinger, Fred; Loginov, Andrey; Loh, Chang Wei; Lohse, Thomas; Lohwasser, Kristin; Lokajicek, Milos; Loken, James; Lombardo, Vincenzo Paolo; Long, Robin Eamonn; Lopes, Lourenco; Lopez Mateos, David; Lorenz, Jeanette; Lorenzo Martinez, Narei; Losada, Marta; Loscutoff, Peter; Lo Sterzo, Francesco; Losty, Michael; Lou, Xinchou; Lounis, Abdenour; Loureiro, Karina; Love, Jeremy; Love, Peter; Lowe, Andrew; Lu, Feng; Lubatti, Henry; Luci, Claudio; Lucotte, Arnaud; Ludwig, Andreas; Ludwig, Dörthe; Ludwig, Inga; Ludwig, Jens; Luehring, Frederick; Luijckx, Guy; Lumb, Debra; Luminari, Lamberto; Lund, Esben; Lund-Jensen, Bengt; Lundberg, Björn; Lundberg, Johan; Lundquist, Johan; Lungwitz, Matthias; Lutz, Gerhard; Lynn, David; Lys, Jeremy; Lytken, Else; Ma, Hong; Ma, Lian Liang; Macana Goia, Jorge Andres; Maccarrone, Giovanni; Macchiolo, Anna; Maček, Boštjan; Machado Miguens, Joana; Mackeprang, Rasmus; Madaras, Ronald; Mader, Wolfgang; Maenner, Reinhard; Maeno, Tadashi; Mättig, Peter; Mättig, Stefan; Magnoni, Luca; Magradze, Erekle; Mahalalel, Yair; Mahboubi, Kambiz; Mahout, Gilles; Maiani, Camilla; Maidantchik, Carmen; Maio, Amélia; Majewski, Stephanie; Makida, Yasuhiro; Makovec, Nikola; Mal, Prolay; Malaescu, Bogdan; Malecki, Pawel; Malecki, Piotr; Maleev, Victor; Malek, Fairouz; Mallik, Usha; Malon, David; Malone, Caitlin; Maltezos, Stavros; Malyshev, Vladimir; Malyukov, Sergei; Mameghani, Raphael; Mamuzic, Judita; Manabe, Atsushi; Mandelli, Luciano; Mandić, Igor; Mandrysch, Rocco; Maneira, José; Mangeard, Pierre-Simon; Manhaes de Andrade Filho, Luciano; Manjavidze, Ioseb; Mann, Alexander; Manning, Peter; Manousakis-Katsikakis, Arkadios; Mansoulie, Bruno; Manz, Andreas; Mapelli, Alessandro; Mapelli, Livio; March, Luis; Marchand, Jean-Francois; Marchese, Fabrizio; Marchiori, Giovanni; Marcisovsky, Michal; Marin, Alexandru; Marino, Christopher; Marroquim, Fernando; Marshall, Robin; Marshall, Zach; Martens, Kalen; Marti-Garcia, Salvador; Martin, Andrew; Martin, Brian; Martin, Brian Thomas; Martin, Franck Francois; Martin, Jean-Pierre; Martin, Philippe; Martin, Tim; Martin, Victoria Jane; Martin dit Latour, Bertrand; Martin-Haugh, Stewart; Martinez, Mario; Martinez Outschoorn, Verena; Martyniuk, Alex; Marx, Marilyn; Marzano, Francesco; Marzin, Antoine; Masetti, Lucia; Mashimo, Tetsuro; Mashinistov, Ruslan; Masik, Jiri; Maslennikov, Alexey; Massa, Ignazio; Massaro, Graziano; Massol, Nicolas; Mastrandrea, Paolo; Mastroberardino, Anna; Masubuchi, Tatsuya; Mathes, Markus; Matricon, Pierre; Matsumoto, Hiroshi; Matsunaga, Hiroyuki; Matsushita, Takashi; Mattravers, Carly; Maugain, Jean-Marie; Maurer, Julien; Maxfield, Stephen; Maximov, Dmitriy; May, Edward; Mayne, Anna; Mazini, Rachid; Mazur, Michael; Mazzanti, Marcello; Mazzoni, Enrico; Mc Kee, Shawn Patrick; McCarn, Allison; McCarthy, Robert; McCarthy, Tom; McCubbin, Norman; McFarlane, Kenneth; Mcfayden, Josh; McGlone, Helen; Mchedlidze, Gvantsa; McLaren, Robert Andrew; Mclaughlan, Tom; McMahon, Steve; McPherson, Robert; Meade, Andrew; Mechnich, Joerg; Mechtel, Markus; Medinnis, Mike; Meera-Lebbai, Razzak; Meguro, Tatsuma; Mehdiyev, Rashid; Mehlhase, Sascha; Mehta, Andrew; Meier, Karlheinz; Meirose, Bernhard; Melachrinos, Constantinos; Mellado Garcia, Bruce Rafael; Mendoza Navas, Luis; Meng, Zhaoxia; Mengarelli, Alberto; Menke, Sven; Menot, Claude; Meoni, Evelin; Mercurio, Kevin Michael; Mermod, Philippe; Merola, Leonardo; Meroni, Chiara; Merritt, Frank; Merritt, Hayes; Messina, Andrea; Metcalfe, Jessica; Mete, Alaettin Serhan; Meyer, Carsten; Meyer, Christopher; Meyer, Jean-Pierre; Meyer, Jochen; Meyer, Joerg; Meyer, Thomas Christian; Meyer, W Thomas; Miao, Jiayuan; Michal, Sebastien; Micu, Liliana; Middleton, Robin; Migas, Sylwia; Mijović, Liza; Mikenberg, Giora; Mikestikova, Marcela; Mikuž, Marko; Miller, David; Miller, Robert; Mills, Bill; Mills, Corrinne; Milov, Alexander; Milstead, David; Milstein, Dmitry; Minaenko, Andrey; Miñano Moya, Mercedes; Minashvili, Irakli; Mincer, Allen; Mindur, Bartosz; Mineev, Mikhail; Ming, Yao; Mir, Lluisa-Maria; Mirabelli, Giovanni; Miralles Verge, Lluis; Misiejuk, Andrzej; Mitrevski, Jovan; Mitrofanov, Gennady; Mitsou, Vasiliki A; Mitsui, Shingo; Miyagawa, Paul; Miyazaki, Kazuki; Mjörnmark, Jan-Ulf; Moa, Torbjoern; Mockett, Paul; Moed, Shulamit; Moeller, Victoria; Mönig, Klaus; Möser, Nicolas; Mohapatra, Soumya; Mohr, Wolfgang; Mohrdieck-Möck, Susanne; Moisseev, Artemy; Moles-Valls, Regina; Molina-Perez, Jorge; Monk, James; Monnier, Emmanuel; Montesano, Simone; Monticelli, Fernando; Monzani, Simone; Moore, Roger; Moorhead, Gareth; Mora Herrera, Clemencia; Moraes, Arthur; Morange, Nicolas; Morel, Julien; Morello, Gianfranco; Moreno, Deywis; Moreno Llácer, María; Morettini, Paolo; Morgenstern, Marcus; Morii, Masahiro; Morin, Jerome; Morley, Anthony Keith; Mornacchi, Giuseppe; Morozov, Sergey; Morris, John; Morvaj, Ljiljana; Moser, Hans-Guenther; Mosidze, Maia; Moss, Josh; Mount, Richard; Mountricha, Eleni; Mouraviev, Sergei; Moyse, Edward; Mudrinic, Mihajlo; Mueller, Felix; Mueller, James; Mueller, Klemens; Müller, Thomas; Mueller, Timo; Muenstermann, Daniel; Muir, Alex; Munwes, Yonathan; Murray, Bill; Mussche, Ido; Musto, Elisa; Myagkov, Alexey; Nadal, Jordi; Nagai, Koichi; Nagano, Kunihiro; Nagarkar, Advait; Nagasaka, Yasushi; Nagel, Martin; Nairz, Armin Michael; Nakahama, Yu; Nakamura, Koji; Nakamura, Tomoaki; Nakano, Itsuo; Nanava, Gizo; Napier, Austin; Narayan, Rohin; Nash, Michael; Nation, Nigel; Nattermann, Till; Naumann, Thomas; Navarro, Gabriela; Neal, Homer; Nebot, Eduardo; Nechaeva, Polina; Neep, Thomas James; Negri, Andrea; Negri, Guido; Nektarijevic, Snezana; Nelson, Andrew; Nelson, Silke; Nelson, Timothy Knight; Nemecek, Stanislav; Nemethy, Peter; Nepomuceno, Andre Asevedo; Nessi, Marzio; Neubauer, Mark; Neusiedl, Andrea; Neves, Ricardo; Nevski, Pavel; Newman, Paul; Nguyen Thi Hong, Van; Nickerson, Richard; Nicolaidou, Rosy; Nicolas, Ludovic; Nicquevert, Bertrand; Niedercorn, Francois; Nielsen, Jason; Niinikoski, Tapio; Nikiforou, Nikiforos; Nikiforov, Andriy; Nikolaenko, Vladimir; Nikolaev, Kirill; Nikolic-Audit, Irena; Nikolics, Katalin; Nikolopoulos, Konstantinos; Nilsen, Henrik; Nilsson, Paul; Ninomiya, Yoichi; Nisati, Aleandro; Nishiyama, Tomonori; Nisius, Richard; Nodulman, Lawrence; Nomachi, Masaharu; Nomidis, Ioannis; Nordberg, Markus; Nordkvist, Bjoern; Norton, Peter; Novakova, Jana; Nozaki, Mitsuaki; Nozka, Libor; Nugent, Ian Michael; Nuncio-Quiroz, Adriana-Elizabeth; Nunes Hanninger, Guilherme; Nunnemann, Thomas; Nurse, Emily; O'Brien, Brendan Joseph; O'Neale, Steve; O'Neil, Dugan; O'Shea, Val; Oakes, Louise Beth; Oakham, Gerald; Oberlack, Horst; Ocariz, Jose; Ochi, Atsuhiko; Oda, Susumu; Odaka, Shigeru; Odier, Jerome; Ogren, Harold; Oh, Alexander; Oh, Seog; Ohm, Christian; Ohshima, Takayoshi; Ohshita, Hidetoshi; Ohsugi, Takashi; Okada, Shogo; Okawa, Hideki; Okumura, Yasuyuki; Okuyama, Toyonobu; Olariu, Albert; Olcese, Marco; Olchevski, Alexander; Olivares Pino, Sebastian Andres; Oliveira, Miguel Alfonso; Oliveira Damazio, Denis; Oliver Garcia, Elena; Olivito, Dominick; Olszewski, Andrzej; Olszowska, Jolanta; Omachi, Chihiro; Onofre, António; Onyisi, Peter; Oram, Christopher; Oreglia, Mark; Oren, Yona; Orestano, Domizia; Orlov, Iliya; Oropeza Barrera, Cristina; Orr, Robert; Osculati, Bianca; Ospanov, Rustem; Osuna, Carlos; Otero y Garzon, Gustavo; Ottersbach, John; Ouchrif, Mohamed; Ouellette, Eric; Ould-Saada, Farid; Ouraou, Ahmimed; Ouyang, Qun; Ovcharova, Ana; Owen, Mark; Owen, Simon; Ozcan, Veysi Erkcan; Ozturk, Nurcan; Pacheco Pages, Andres; Padilla Aranda, Cristobal; Pagan Griso, Simone; Paganis, Efstathios; Paige, Frank; Pais, Preema; Pajchel, Katarina; Palacino, Gabriel; Paleari, Chiara; Palestini, Sandro; Pallin, Dominique; Palma, Alberto; Palmer, Jody; Pan, Yibin; Panagiotopoulou, Evgenia; Panes, Boris; Panikashvili, Natalia; Panitkin, Sergey; Pantea, Dan; Panuskova, Monika; Paolone, Vittorio; Papadelis, Aras; Papadopoulou, Theodora; Paramonov, Alexander; Park, Woochun; Parker, Andy; Parodi, Fabrizio; Parsons, John; Parzefall, Ulrich; Pasqualucci, Enrico; Passaggio, Stefano; Passeri, Antonio; Pastore, Fernanda; Pastore, Francesca; Pásztor, Gabriella; Pataraia, Sophio; Patel, Nikhul; Pater, Joleen; Patricelli, Sergio; Pauly, Thilo; Pecsy, Martin; Pedraza Morales, Maria Isabel; Peleganchuk, Sergey; Peng, Haiping; Pengo, Ruggero; Penning, Bjoern; Penson, Alexander; Penwell, John; Perantoni, Marcelo; Perez, Kerstin; Perez Cavalcanti, Tiago; Perez Codina, Estel; Pérez García-Estañ, María Teresa; Perez Reale, Valeria; Perini, Laura; Pernegger, Heinz; Perrino, Roberto; Perrodo, Pascal; Persembe, Seda; Perus, Antoine; Peshekhonov, Vladimir; Peters, Krisztian; Petersen, Brian; Petersen, Jorgen; Petersen, Troels; Petit, Elisabeth; Petridis, Andreas; Petridou, Chariclia; Petrolo, Emilio; Petrucci, Fabrizio; Petschull, Dennis; Petteni, Michele; Pezoa, Raquel; Phan, Anna; Phillips, Peter William; Piacquadio, Giacinto; Piccaro, Elisa; Piccinini, Maurizio; Piec, Sebastian Marcin; Piegaia, Ricardo; Pignotti, David; Pilcher, James; Pilkington, Andrew; Pina, João Antonio; Pinamonti, Michele; Pinder, Alex; Pinfold, James; Ping, Jialun; Pinto, Belmiro; Pirotte, Olivier; Pizio, Caterina; Placakyte, Ringaile; Plamondon, Mathieu; Pleier, Marc-Andre; Pleskach, Anatoly; Poblaguev, Andrei; Poddar, Sahill; Podlyski, Fabrice; Poggioli, Luc; Poghosyan, Tatevik; Pohl, Martin; Polci, Francesco; Polesello, Giacomo; Policicchio, Antonio; Polini, Alessandro; Poll, James; Polychronakos, Venetios; Pomarede, Daniel Marc; Pomeroy, Daniel; Pommès, Kathy; Pontecorvo, Ludovico; Pope, Bernard; Popeneciu, Gabriel Alexandru; Popovic, Dragan; Poppleton, Alan; Portell Bueso, Xavier; Posch, Christoph; Pospelov, Guennady; Pospisil, Stanislav; Potrap, Igor; Potter, Christina; Potter, Christopher; Poulard, Gilbert; Poveda, Joaquin; Pozdnyakov, Valery; Prabhu, Robindra; Pralavorio, Pascal; Pranko, Aliaksandr; Prasad, Srivas; Pravahan, Rishiraj; Prell, Soeren; Pretzl, Klaus Peter; Pribyl, Lukas; Price, Darren; Price, Joe; Price, Lawrence; Price, Michael John; Prieur, Damien; Primavera, Margherita; Prokofiev, Kirill; Prokoshin, Fedor; Protopopescu, Serban; Proudfoot, James; Prudent, Xavier; Przybycien, Mariusz; Przysiezniak, Helenka; Psoroulas, Serena; Ptacek, Elizabeth; Pueschel, Elisa; Purdham, John; Purohit, Milind; Puzo, Patrick; Pylypchenko, Yuriy; Qian, Jianming; Qian, Zuxuan; Qin, Zhonghua; Quadt, Arnulf; Quarrie, David; Quayle, William; Quinonez, Fernando; Raas, Marcel; Radescu, Voica; Radics, Balint; Radloff, Peter; Rador, Tonguc; Ragusa, Francesco; Rahal, Ghita; Rahimi, Amir; Rahm, David; Rajagopalan, Srinivasan; Rammensee, Michael; Rammes, Marcus; Randle-Conde, Aidan Sean; Randrianarivony, Koloina; Ratoff, Peter; Rauscher, Felix; Rave, Tobias Christian; Raymond, Michel; Read, Alexander Lincoln; Rebuzzi, Daniela; Redelbach, Andreas; Redlinger, George; Reece, Ryan; Reeves, Kendall; Reichold, Armin; Reinherz-Aronis, Erez; Reinsch, Andreas; Reisinger, Ingo; Rembser, Christoph; Ren, Zhongliang; Renaud, Adrien; Renkel, Peter; Rescigno, Marco; Resconi, Silvia; Resende, Bernardo; Reznicek, Pavel; Rezvani, Reyhaneh; Richards, Alexander; Richter, Robert; Richter-Was, Elzbieta; Ridel, Melissa; Rijpstra, Manouk; Rijssenbeek, Michael; Rimoldi, Adele; Rinaldi, Lorenzo; Rios, Ryan Randy; Riu, Imma; Rivoltella, Giancesare; Rizatdinova, Flera; Rizvi, Eram; Robertson, Steven; Robichaud-Veronneau, Andree; Robinson, Dave; Robinson, James; Robinson, Mary; Robson, Aidan; Rocha de Lima, Jose Guilherme; Roda, Chiara; Roda Dos Santos, Denis; Rodriguez, Diego; Roe, Adam; Roe, Shaun; Røhne, Ole; Rojo, Victoria; Rolli, Simona; Romaniouk, Anatoli; Romano, Marino; Romanov, Victor; Romeo, Gaston; Romero Adam, Elena; Roos, Lydia; Ros, Eduardo; Rosati, Stefano; Rosbach, Kilian; Rose, Anthony; Rose, Matthew; Rosenbaum, Gabriel; Rosenberg, Eli; Rosendahl, Peter Lundgaard; Rosenthal, Oliver; Rosselet, Laurent; Rossetti, Valerio; Rossi, Elvira; Rossi, Leonardo Paolo; Rotaru, Marina; Roth, Itamar; Rothberg, Joseph; Rousseau, David; Royon, Christophe; Rozanov, Alexander; Rozen, Yoram; Ruan, Xifeng; Rubinskiy, Igor; Ruckert, Benjamin; Ruckstuhl, Nicole; Rud, Viacheslav; Rudolph, Christian; Rudolph, Gerald; Rühr, Frederik; Ruggieri, Federico; Ruiz-Martinez, Aranzazu; Rumiantsev, Viktor; Rumyantsev, Leonid; Runge, Kay; Rurikova, Zuzana; Rusakovich, Nikolai; Rust, Dave; Rutherfoord, John; Ruwiedel, Christoph; Ruzicka, Pavel; Ryabov, Yury; Ryadovikov, Vasily; Ryan, Patrick; Rybar, Martin; Rybkin, Grigori; Ryder, Nick; Rzaeva, Sevda; Saavedra, Aldo; Sadeh, Iftach; Sadrozinski, Hartmut; Sadykov, Renat; Safai Tehrani, Francesco; Sakamoto, Hiroshi; Salamanna, Giuseppe; Salamon, Andrea; Saleem, Muhammad; Salihagic, Denis; Salnikov, Andrei; Salt, José; Salvachua Ferrando, Belén; Salvatore, Daniela; Salvatore, Pasquale Fabrizio; Salvucci, Antonio; Salzburger, Andreas; Sampsonidis, Dimitrios; Samset, Björn Hallvard; Sanchez, Arturo; Sanchez Martinez, Victoria; Sandaker, Heidi; Sander, Heinz Georg; Sanders, Michiel; Sandhoff, Marisa; Sandoval, Tanya; Sandoval, Carlos; Sandstroem, Rikard; Sandvoss, Stephan; Sankey, Dave; Sansoni, Andrea; Santamarina Rios, Cibran; Santoni, Claudio; Santonico, Rinaldo; Santos, Helena; Saraiva, João; Sarangi, Tapas; Sarkisyan-Grinbaum, Edward; Sarri, Francesca; Sartisohn, Georg; Sasaki, Osamu; Sasaki, Takashi; Sasao, Noboru; Satsounkevitch, Igor; Sauvage, Gilles; Sauvan, Emmanuel; Sauvan, Jean-Baptiste; Savard, Pierre; Savinov, Vladimir; Savu, Dan Octavian; Sawyer, Lee; Saxon, David; Says, Louis-Pierre; Sbarra, Carla; Sbrizzi, Antonio; Scallon, Olivia; Scannicchio, Diana; Scarcella, Mark; Schaarschmidt, Jana; Schacht, Peter; Schäfer, Uli; Schaepe, Steffen; Schaetzel, Sebastian; Schaffer, Arthur; Schaile, Dorothee; Schamberger, R. Dean; Schamov, Andrey; Scharf, Veit; Schegelsky, Valery; Scheirich, Daniel; Schernau, Michael; Scherzer, Max; Schiavi, Carlo; Schieck, Jochen; Schioppa, Marco; Schlenker, Stefan; Schlereth, James; Schmidt, Evelyn; Schmieden, Kristof; Schmitt, Christian; Schmitt, Sebastian; Schmitz, Martin; Schöning, André; Schott, Matthias; Schouten, Doug; Schovancova, Jaroslava; Schram, Malachi; Schroeder, Christian; Schroer, Nicolai; Schuh, Silvia; Schuler, Georges; Schultens, Martin Johannes; Schultes, Joachim; Schultz-Coulon, Hans-Christian; Schulz, Holger; Schumacher, Jan; Schumacher, Markus; Schumm, Bruce; Schune, Philippe; Schwanenberger, Christian; Schwartzman, Ariel; Schwemling, Philippe; Schwienhorst, Reinhard; Schwierz, Rainer; Schwindling, Jerome; Schwindt, Thomas; Schwoerer, Maud; Scott, Bill; Searcy, Jacob; Sedov, George; Sedykh, Evgeny; Segura, Ester; Seidel, Sally; Seiden, Abraham; Seifert, Frank; Seixas, José; Sekhniaidze, Givi; Selbach, Karoline Elfriede; Seliverstov, Dmitry; Sellden, Bjoern; Sellers, Graham; Seman, Michal; Semprini-Cesari, Nicola; Serfon, Cedric; Serin, Laurent; Serkin, Leonid; Seuster, Rolf; Severini, Horst; Sevior, Martin; Sfyrla, Anna; Shabalina, Elizaveta; Shamim, Mansoora; Shan, Lianyou; Shank, James; Shao, Qi Tao; Shapiro, Marjorie; Shatalov, Pavel; Shaver, Leif; Shaw, Kate; Sherman, Daniel; Sherwood, Peter; Shibata, Akira; Shichi, Hideharu; Shimizu, Shima; Shimojima, Makoto; Shin, Taeksu; Shiyakova, Maria; Shmeleva, Alevtina; Shochet, Mel; Short, Daniel; Shrestha, Suyog; Shulga, Evgeny; Shupe, Michael; Sicho, Petr; Sidoti, Antonio; Siegert, Frank; Sijacki, Djordje; Silbert, Ohad; Silva, José; Silver, Yiftah; Silverstein, Daniel; Silverstein, Samuel; Simak, Vladislav; Simard, Olivier; Simic, Ljiljana; Simion, Stefan; Simmons, Brinick; Simonyan, Margar; Sinervo, Pekka; Sinev, Nikolai; Sipica, Valentin; Siragusa, Giovanni; Sircar, Anirvan; Sisakyan, Alexei; Sivoklokov, Serguei; Sjölin, Jörgen; Sjursen, Therese; Skinnari, Louise Anastasia; Skottowe, Hugh Philip; Skovpen, Kirill; Skubic, Patrick; Skvorodnev, Nikolai; Slater, Mark; Slavicek, Tomas; Sliwa, Krzysztof; Sloper, John erik; Smakhtin, Vladimir; Smart, Ben; Smirnov, Sergei; Smirnov, Yury; Smirnova, Lidia; Smirnova, Oxana; Smith, Ben Campbell; Smith, Douglas; Smith, Kenway; Smizanska, Maria; Smolek, Karel; Snesarev, Andrei; Snow, Steve; Snow, Joel; Snuverink, Jochem; Snyder, Scott; Soares, Mara; Sobie, Randall; Sodomka, Jaromir; Soffer, Abner; Solans, Carlos; Solar, Michael; Solc, Jaroslav; Soldatov, Evgeny; Soldevila, Urmila; Solfaroli Camillocci, Elena; Solodkov, Alexander; Solovyanov, Oleg; Soni, Nitesh; Sopko, Vit; Sopko, Bruno; Sosebee, Mark; Soualah, Rachik; Soukharev, Andrey; Spagnolo, Stefania; Spanò, Francesco; Spighi, Roberto; Spigo, Giancarlo; Spila, Federico; Spiwoks, Ralf; Spousta, Martin; Spreitzer, Teresa; Spurlock, Barry; St Denis, Richard Dante; Stahlman, Jonathan; Stamen, Rainer; Stanecka, Ewa; Stanek, Robert; Stanescu, Cristian; Stapnes, Steinar; Starchenko, Evgeny; Stark, Jan; Staroba, Pavel; Starovoitov, Pavel; Staude, Arnold; Stavina, Pavel; Stavropoulos, Georgios; Steele, Genevieve; Steinbach, Peter; Steinberg, Peter; Stekl, Ivan; Stelzer, Bernd; Stelzer, Harald Joerg; Stelzer-Chilton, Oliver; Stenzel, Hasko; Stern, Sebastian; Stevenson, Kyle; Stewart, Graeme; Stillings, Jan Andre; Stockton, Mark; Stoerig, Kathrin; Stoicea, Gabriel; Stonjek, Stefan; Strachota, Pavel; Stradling, Alden; Straessner, Arno; Strandberg, Jonas; Strandberg, Sara; Strandlie, Are; Strang, Michael; Strauss, Emanuel; Strauss, Michael; Strizenec, Pavol; Ströhmer, Raimund; Strom, David; Strong, John; Stroynowski, Ryszard; Strube, Jan; Stugu, Bjarne; Stumer, Iuliu; Stupak, John; Sturm, Philipp; Styles, Nicholas Adam; Soh, Dart-yin; Su, Dong; Subramania, Halasya Siva; Succurro, Antonella; Sugaya, Yorihito; Sugimoto, Takuya; Suhr, Chad; Suita, Koichi; Suk, Michal; Sulin, Vladimir; Sultansoy, Saleh; Sumida, Toshi; Sun, Xiaohu; Sundermann, Jan Erik; Suruliz, Kerim; Sushkov, Serge; Susinno, Giancarlo; Sutton, Mark; Suzuki, Yu; Suzuki, Yuta; Svatos, Michal; Sviridov, Yuri; Swedish, Stephen; Sykora, Ivan; Sykora, Tomas; Szeless, Balazs; Sánchez, Javier; Ta, Duc; Tackmann, Kerstin; Taffard, Anyes; Tafirout, Reda; Taiblum, Nimrod; Takahashi, Yuta; Takai, Helio; Takashima, Ryuichi; Takeda, Hiroshi; Takeshita, Tohru; Takubo, Yosuke; Talby, Mossadek; Talyshev, Alexey; Tamsett, Matthew; Tanaka, Junichi; Tanaka, Reisaburo; Tanaka, Satoshi; Tanaka, Shuji; Tanaka, Yoshito; Tanasijczuk, Andres Jorge; Tani, Kazutoshi; Tannoury, Nancy; Tappern, Geoffrey; Tapprogge, Stefan; Tardif, Dominique; Tarem, Shlomit; Tarrade, Fabien; Tartarelli, Giuseppe Francesco; Tas, Petr; Tasevsky, Marek; Tassi, Enrico; Tatarkhanov, Mous; Tayalati, Yahya; Taylor, Christopher; Taylor, Frank; Taylor, Geoffrey; Taylor, Wendy; Teinturier, Marthe; Teixeira Dias Castanheira, Matilde; Teixeira-Dias, Pedro; Temming, Kim Katrin; Ten Kate, Herman; Teng, Ping-Kun; Terada, Susumu; Terashi, Koji; Terron, Juan; Testa, Marianna; Teuscher, Richard; Thadome, Jocelyn; Therhaag, Jan; Theveneaux-Pelzer, Timothée; Thioye, Moustapha; Thoma, Sascha; Thomas, Juergen; Thompson, Emily; Thompson, Paul; Thompson, Peter; Thompson, Stan; Thomsen, Lotte Ansgaard; Thomson, Evelyn; Thomson, Mark; Thun, Rudolf; Tian, Feng; Tibbetts, Mark James; Tic, Tomáš; Tikhomirov, Vladimir; Tikhonov, Yury; Timoshenko, Sergey; Tipton, Paul; Tique Aires Viegas, Florbela De Jes; Tisserant, Sylvain; Tobias, Jürgen; Toczek, Barbara; Todorov, Theodore; Todorova-Nova, Sharka; Toggerson, Brokk; Tojo, Junji; Tokár, Stanislav; Tokunaga, Kaoru; Tokushuku, Katsuo; Tollefson, Kirsten; Tomoto, Makoto; Tompkins, Lauren; Toms, Konstantin; Tong, Guoliang; Tonoyan, Arshak; Topfel, Cyril; Topilin, Nikolai; Torchiani, Ingo; Torrence, Eric; Torres, Heberth; Torró Pastor, Emma; Toth, Jozsef; Touchard, Francois; Tovey, Daniel; Trefzger, Thomas; Tremblet, Louis; Tricoli, Alesandro; Trigger, Isabel Marian; Trincaz-Duvoid, Sophie; Trinh, Thi Nguyet; Tripiana, Martin; Trischuk, William; Trivedi, Arjun; Trocmé, Benjamin; Troncon, Clara; Trottier-McDonald, Michel; Trzebinski, Maciej; Trzupek, Adam; Tsarouchas, Charilaos; Tseng, Jeffrey; Tsiakiris, Menelaos; Tsiareshka, Pavel; Tsionou, Dimitra; Tsipolitis, Georgios; Tsiskaridze, Vakhtang; Tskhadadze, Edisher; Tsukerman, Ilya; Tsulaia, Vakhtang; Tsung, Jieh-Wen; Tsuno, Soshi; Tsybychev, Dmitri; Tua, Alan; Tudorache, Alexandra; Tudorache, Valentina; Tuggle, Joseph; Turala, Michal; Turecek, Daniel; Turk Cakir, Ilkay; Turlay, Emmanuel; Turra, Ruggero; Tuts, Michael; Tykhonov, Andrii; Tylmad, Maja; Tyndel, Mike; Tzanakos, George; Uchida, Kirika; Ueda, Ikuo; Ueno, Ryuichi; Ugland, Maren; Uhlenbrock, Mathias; Uhrmacher, Michael; Ukegawa, Fumihiko; Unal, Guillaume; Underwood, David; Undrus, Alexander; Unel, Gokhan; Unno, Yoshinobu; Urbaniec, Dustin; Usai, Giulio; Uslenghi, Massimiliano; Vacavant, Laurent; Vacek, Vaclav; Vachon, Brigitte; Vahsen, Sven; Valenta, Jan; Valente, Paolo; Valentinetti, Sara; Valkar, Stefan; Valladolid Gallego, Eva; Vallecorsa, Sofia; Valls Ferrer, Juan Antonio; van der Graaf, Harry; van der Kraaij, Erik; Van Der Leeuw, Robin; van der Poel, Egge; van der Ster, Daniel; van Eldik, Niels; van Gemmeren, Peter; van Kesteren, Zdenko; van Vulpen, Ivo; Vanadia, Marco; Vandelli, Wainer; Vandoni, Giovanna; Vaniachine, Alexandre; Vankov, Peter; Vannucci, Francois; Varela Rodriguez, Fernando; Vari, Riccardo; Varnes, Erich; Varouchas, Dimitris; Vartapetian, Armen; Varvell, Kevin; Vassilakopoulos, Vassilios; Vazeille, Francois; Vegni, Guido; Veillet, Jean-Jacques; Vellidis, Constantine; Veloso, Filipe; Veness, Raymond; Veneziano, Stefano; Ventura, Andrea; Ventura, Daniel; Venturi, Manuela; Venturi, Nicola; Vercesi, Valerio; Verducci, Monica; Verkerke, Wouter; Vermeulen, Jos; Vest, Anja; Vetterli, Michel; Vichou, Irene; Vickey, Trevor; Vickey Boeriu, Oana Elena; Viehhauser, Georg; Viel, Simon; Villa, Mauro; Villaplana Perez, Miguel; Vilucchi, Elisabetta; Vincter, Manuella; Vinek, Elisabeth; Vinogradov, Vladimir; Virchaux, Marc; Virzi, Joseph; Vitells, Ofer; Viti, Michele; Vivarelli, Iacopo; Vives Vaque, Francesc; Vlachos, Sotirios; Vladoiu, Dan; Vlasak, Michal; Vlasov, Nikolai; Vogel, Adrian; Vokac, Petr; Volpi, Guido; Volpi, Matteo; Volpini, Giovanni; von der Schmitt, Hans; von Loeben, Joerg; von Radziewski, Holger; von Toerne, Eckhard; Vorobel, Vit; Vorobiev, Alexander; Vorwerk, Volker; Vos, Marcel; Voss, Rudiger; Voss, Thorsten Tobias; Vossebeld, Joost; Vranjes, Nenad; Vranjes Milosavljevic, Marija; Vrba, Vaclav; Vreeswijk, Marcel; Vu Anh, Tuan; Vuillermet, Raphael; Vukotic, Ilija; Wagner, Wolfgang; Wagner, Peter; Wahlen, Helmut; Wakabayashi, Jun; Walbersloh, Jorg; Walch, Shannon; Walder, James; Walker, Rodney; Walkowiak, Wolfgang; Wall, Richard; Waller, Peter; Wang, Chiho; Wang, Haichen; Wang, Hulin; Wang, Jike; Wang, Jin; Wang, Joshua C; Wang, Rui; Wang, Song-Ming; Warburton, Andreas; Ward, Patricia; Warsinsky, Markus; Watkins, Peter; Watson, Alan; Watson, Ian; Watson, Miriam; Watts, Gordon; Watts, Stephen; Waugh, Anthony; Waugh, Ben; Weber, Marc; Weber, Michele; Weber, Pavel; Weidberg, Anthony; Weigell, Philipp; Weingarten, Jens; Weiser, Christian; Wellenstein, Hermann; Wells, Phillippa; Wen, Mei; Wenaus, Torre; Wendland, Dennis; Wendler, Shanti; Weng, Zhili; Wengler, Thorsten; Wenig, Siegfried; Wermes, Norbert; Werner, Matthias; Werner, Per; Werth, Michael; Wessels, Martin; Weydert, Carole; Whalen, Kathleen; Wheeler-Ellis, Sarah Jane; Whitaker, Scott; White, Andrew; White, Martin; Whitehead, Samuel Robert; Whiteson, Daniel; Whittington, Denver; Wicek, Francois; Wicke, Daniel; Wickens, Fred; Wiedenmann, Werner; Wielers, Monika; Wienemann, Peter; Wiglesworth, Craig; Wiik, Liv Antje Mari; Wijeratne, Peter Alexander; Wildauer, Andreas; Wildt, Martin Andre; Wilhelm, Ivan; Wilkens, Henric George; Will, Jonas Zacharias; Williams, Eric; Williams, Hugh; Willis, William; Willocq, Stephane; Wilson, John; Wilson, Michael Galante; Wilson, Alan; Wingerter-Seez, Isabelle; Winkelmann, Stefan; Winklmeier, Frank; Wittgen, Matthias; Wolter, Marcin Wladyslaw; Wolters, Helmut; Wong, Wei-Cheng; Wooden, Gemma; Wosiek, Barbara; Wotschack, Jorg; Woudstra, Martin; Wozniak, Krzysztof; Wraight, Kenneth; Wright, Catherine; Wright, Michael; Wrona, Bozydar; Wu, Sau Lan; Wu, Xin; Wu, Yusheng; Wulf, Evan; Wunstorf, Renate; Wynne, Benjamin; Xella, Stefania; Xiao, Meng; Xie, Song; Xie, Yigang; Xu, Chao; Xu, Da; Xu, Guofa; Yabsley, Bruce; Yacoob, Sahal; Yamada, Miho; Yamaguchi, Hiroshi; Yamamoto, Akira; Yamamoto, Kyoko; Yamamoto, Shimpei; Yamamura, Taiki; Yamanaka, Takashi; Yamaoka, Jared; Yamazaki, Takayuki; Yamazaki, Yuji; Yan, Zhen; Yang, Haijun; Yang, Un-Ki; Yang, Yi; Yang, Yi; Yang, Zhaoyu; Yanush, Serguei; Yao, Yushu; Yasu, Yoshiji; Ybeles Smit, Gabriel Valentijn; Ye, Jingbo; Ye, Shuwei; Yilmaz, Metin; Yoosoofmiya, Reza; Yorita, Kohei; Yoshida, Riktura; Young, Charles; Youssef, Saul; Yu, Dantong; Yu, Jaehoon; Yu, Jie; Yuan, Li; Yurkewicz, Adam; Zabinski, Bartlomiej; Zaets, Vassilli; Zaidan, Remi; Zaitsev, Alexander; Zajacova, Zuzana; Zanello, Lucia; Zarzhitsky, Pavel; Zaytsev, Alexander; Zeitnitz, Christian; Zeller, Michael; Zeman, Martin; Zemla, Andrzej; Zendler, Carolin; Zenin, Oleg; Ženiš, Tibor; Zenonos, Zenonas; Zenz, Seth; Zerwas, Dirk; Zevi della Porta, Giovanni; Zhan, Zhichao; Zhang, Dongliang; Zhang, Huaqiao; Zhang, Jinlong; Zhang, Xueyao; Zhang, Zhiqing; Zhao, Long; Zhao, Tianchi; Zhao, Zhengguo; Zhemchugov, Alexey; Zheng, Shuchen; Zhong, Jiahang; Zhou, Bing; Zhou, Ning; Zhou, Yue; Zhu, Cheng Guang; Zhu, Hongbo; Zhu, Junjie; Zhu, Yingchun; Zhuang, Xuai; Zhuravlov, Vadym; Zieminska, Daria; Zimmermann, Robert; Zimmermann, Simone; Zimmermann, Stephanie; Ziolkowski, Michael; Zitoun, Robert; Živković, Lidija; Zmouchko, Viatcheslav; Zobernig, Georg; Zoccoli, Antonio; Zolnierowski, Yves; Zsenei, Andras; zur Nedden, Martin; Zutshi, Vishnu; Zwalinski, Lukasz

2013-03-02

The uncertainty on the calorimeter energy response to jets of particles is derived for the ATLAS experiment at the Large Hadron Collider (LHC). First, the calorimeter response to single isolated charged hadrons is measured and compared to the Monte Carlo simulation using proton-proton collisions at centre-of-mass energies of $\\sqrt{s}$ = 900 GeV and 7 TeV collected during 2009 and 2010. Then, using the decay of K_s and Lambda particles, the calorimeter response to specific types of particles (positively and negatively charged pions, protons, and anti-protons) is measured and compared to the Monte Carlo predictions. Finally, the jet energy scale uncertainty is determined by propagating the response uncertainty for single charged and neutral particles to jets. The response uncertainty is 2-5% for central isolated hadrons and 1-3% for the final calorimeter jet energy scale.

Reducing uncertainty in Climate Response Time Scale by Bayesian Analysis of the 8.2 ka event

Science.gov (United States)

Lorenz, A.; Held, H.; Bauer, E.; Schneider von Deimling, T.

2009-04-01

We analyze the possibility of uncertainty reduction in Climate Response Time Scale by utilizing Greenland ice-core data that contain the 8.2 ka event within a Bayesian model-data intercomparison with the Earth system model of intermediate complexity, CLIMBER-2.3. Within a stochastic version of the model it has been possible to mimic the 8.2 ka event within a plausible experimental setting and with relatively good accuracy considering the timing of the event in comparison to other modeling exercises [1]. The simulation of the centennial cold event is effectively determined by the oceanic cooling rate which depends largely on the ocean diffusivity described by diffusion coefficients of relatively wide uncertainty ranges. The idea now is to discriminate between the different values of diffusivities according to their likelihood to rightly represent the duration of the 8.2 ka event and thus to exploit the paleo data to constrain uncertainty in model parameters in analogue to [2]. Implementing this inverse Bayesian Analysis with this model the technical difficulty arises to establish the related likelihood numerically in addition to the uncertain model parameters: While mainstream uncertainty analyses can assume a quasi-Gaussian shape of likelihood, with weather fluctuating around a long term mean, the 8.2 ka event as a highly nonlinear effect precludes such an a priori assumption. As a result of this study [3] the Bayesian Analysis showed a reduction of uncertainty in vertical ocean diffusivity parameters of factor 2 compared to prior knowledge. This learning effect on the model parameters is propagated to other model outputs of interest; e.g. the inverse ocean heat capacity, which is important for the dominant time scale of climate response to anthropogenic forcing which, in combination with climate sensitivity, strongly influences the climate systems reaction for the near- and medium-term future. 1 References [1] E. Bauer, A. Ganopolski, M. Montoya: Simulation of the

Final Report: Quantification of Uncertainty in Extreme Scale Computations (QUEST)

Energy Technology Data Exchange (ETDEWEB)

Marzouk, Youssef [Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States); Conrad, Patrick [Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States); Bigoni, Daniele [Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States); Parno, Matthew [Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)

2017-06-09

QUEST (\\url{www.quest-scidac.org}) is a SciDAC Institute that is focused on uncertainty quantification (UQ) in large-scale scientific computations. Our goals are to (1) advance the state of the art in UQ mathematics, algorithms, and software; and (2) provide modeling, algorithmic, and general UQ expertise, together with software tools, to other SciDAC projects, thereby enabling and guiding a broad range of UQ activities in their respective contexts. QUEST is a collaboration among six institutions (Sandia National Laboratories, Los Alamos National Laboratory, the University of Southern California, Massachusetts Institute of Technology, the University of Texas at Austin, and Duke University) with a history of joint UQ research. Our vision encompasses all aspects of UQ in leadership-class computing. This includes the well-founded setup of UQ problems; characterization of the input space given available data/information; local and global sensitivity analysis; adaptive dimensionality and order reduction; forward and inverse propagation of uncertainty; handling of application code failures, missing data, and hardware/software fault tolerance; and model inadequacy, comparison, validation, selection, and averaging. The nature of the UQ problem requires the seamless combination of data, models, and information across this landscape in a manner that provides a self-consistent quantification of requisite uncertainties in predictions from computational models. Accordingly, our UQ methods and tools span an interdisciplinary space across applied math, information theory, and statistics. The MIT QUEST effort centers on statistical inference and methods for surrogate or reduced-order modeling. MIT personnel have been responsible for the development of adaptive sampling methods, methods for approximating computationally intensive models, and software for both forward uncertainty propagation and statistical inverse problems. A key software product of the MIT QUEST effort is the MIT

Inventory calculation and nuclear data uncertainty propagation on light water reactor fuel using ALEPH-2 and SCALE 6.2

International Nuclear Information System (INIS)

Fiorito, L.; Piedra, D.; Cabellos, O.; Diez, C.J.

2015-01-01

Highlights: • We performed burnup calculations of PWR and BWR benchmarks using ALEPH and SCALE. • We propagated nuclear data uncertainty and correlations using different procedures and code. • Decay data uncertainties have negligible impact on nuclide densities. • Uncorrelated fission yields play a major role on the uncertainties of fission products. • Fission yields impact is strongly reduced by the introduction of correlations. - Abstract: Two fuel assemblies, one belonging to the Takahama-3 PWR and the other to the Fukushima-Daini-2 BWR, were modelled and the fuel irradiation was simulated with the TRITON module of SCALE 6.2 and with the ALEPH-2 code. Our results were compared to the experimental measurements of four samples: SF95-4 and SF96-4 were taken from the Takahama-3 reactor, while samples SF98-6 and SF99-6 belonged to the Fukushima-Daini-2. Then, we propagated the uncertainties coming from the nuclear data to the isotopic inventory of sample SF95-4. We used the ALEPH-2 adjoint procedure to propagate the decay constant uncertainties. The impact was inappreciable. The cross-section covariance information was propagated with the SAMPLER module of the beta3 version of SCALE 6.2. This contribution mostly affected the uncertainties of the actinides. Finally, the uncertainties of the fission yields were propagated both through ALEPH-2 and TRITON with a Monte Carlo sampling approach and appeared to have the largest impact on the uncertainties of the fission products. However, the lack of fission yield correlations results is a serious overestimation of the response uncertainties

Geological-structural models used in SR 97. Uncertainty analysis

Energy Technology Data Exchange (ETDEWEB)

Saksa, P.; Nummela, J. [FINTACT Oy (Finland)

1998-10-01

The uncertainty of geological-structural models was studied for the three sites in SR 97, called Aberg, Beberg and Ceberg. The evaluation covered both regional and site scale models, the emphasis being placed on fracture zones in the site scale. Uncertainty is a natural feature of all geoscientific investigations. It originates from measurements (errors in data, sampling limitations, scale variation) and conceptualisation (structural geometries and properties, ambiguous geometric or parametric solutions) to name the major ones. The structures of A-, B- and Ceberg are fracture zones of varying types. No major differences in the conceptualisation between the sites were noted. One source of uncertainty in the site models is the non-existence of fracture and zone information in the scale from 10 to 300 - 1000 m. At Aberg the development of the regional model has been performed very thoroughly. At the site scale one major source of uncertainty is that a clear definition of the target area is missing. Structures encountered in the boreholes are well explained and an interdisciplinary approach in interpretation have taken place. Beberg and Ceberg regional models contain relatively large uncertainties due to the investigation methodology and experience available at that time. In site scale six additional structures were proposed both to Beberg and Ceberg to variant analysis of these sites. Both sites include uncertainty in the form of many non-interpreted fractured sections along the boreholes. Statistical analysis gives high occurrences of structures for all three sites: typically 20 - 30 structures/km{sup 3}. Aberg has highest structural frequency, Beberg comes next and Ceberg has the lowest. The borehole configuration, orientations and surveying goals were inspected to find whether preferences or factors causing bias were present. Data from Aberg supports the conclusion that Aespoe sub volume would be an anomalously fractured, tectonised unit of its own. This means that

Geological-structural models used in SR 97. Uncertainty analysis

International Nuclear Information System (INIS)

Saksa, P.; Nummela, J.

1998-10-01

The uncertainty of geological-structural models was studied for the three sites in SR 97, called Aberg, Beberg and Ceberg. The evaluation covered both regional and site scale models, the emphasis being placed on fracture zones in the site scale. Uncertainty is a natural feature of all geoscientific investigations. It originates from measurements (errors in data, sampling limitations, scale variation) and conceptualisation (structural geometries and properties, ambiguous geometric or parametric solutions) to name the major ones. The structures of A-, B- and Ceberg are fracture zones of varying types. No major differences in the conceptualisation between the sites were noted. One source of uncertainty in the site models is the non-existence of fracture and zone information in the scale from 10 to 300 - 1000 m. At Aberg the development of the regional model has been performed very thoroughly. At the site scale one major source of uncertainty is that a clear definition of the target area is missing. Structures encountered in the boreholes are well explained and an interdisciplinary approach in interpretation have taken place. Beberg and Ceberg regional models contain relatively large uncertainties due to the investigation methodology and experience available at that time. In site scale six additional structures were proposed both to Beberg and Ceberg to variant analysis of these sites. Both sites include uncertainty in the form of many non-interpreted fractured sections along the boreholes. Statistical analysis gives high occurrences of structures for all three sites: typically 20 - 30 structures/km 3 . Aberg has highest structural frequency, Beberg comes next and Ceberg has the lowest. The borehole configuration, orientations and surveying goals were inspected to find whether preferences or factors causing bias were present. Data from Aberg supports the conclusion that Aespoe sub volume would be an anomalously fractured, tectonised unit of its own. This means that the

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.

Deterministic methods for sensitivity and uncertainty analysis in large-scale computer models

International Nuclear Information System (INIS)

Worley, B.A.; Oblow, E.M.; Pin, F.G.; Maerker, R.E.; Horwedel, J.E.; Wright, R.Q.; Lucius, J.L.

1987-01-01

The fields of sensitivity and uncertainty analysis are dominated by statistical techniques when large-scale modeling codes are being analyzed. This paper reports on the development and availability of two systems, GRESS and ADGEN, that make use of computer calculus compilers to automate the implementation of deterministic sensitivity analysis capability into existing computer models. This automation removes the traditional limitation of deterministic sensitivity methods. The paper describes a deterministic uncertainty analysis method (DUA) that uses derivative information as a basis to propagate parameter probability distributions to obtain result probability distributions. The paper demonstrates the deterministic approach to sensitivity and uncertainty analysis as applied to a sample problem that models the flow of water through a borehole. The sample problem is used as a basis to compare the cumulative distribution function of the flow rate as calculated by the standard statistical methods and the DUA method. The DUA method gives a more accurate result based upon only two model executions compared to fifty executions in the statistical case

Uncertainty Quantification in Scale-Dependent Models of Flow in Porous Media: SCALE-DEPENDENT UQ

Energy Technology Data Exchange (ETDEWEB)

Tartakovsky, A. M. [Computational Mathematics Group, Pacific Northwest National Laboratory, Richland WA USA; Panzeri, M. [Dipartimento di Ingegneria Civile e Ambientale, Politecnico di Milano, Milano Italy; Tartakovsky, G. D. [Hydrology Group, Pacific Northwest National Laboratory, Richland WA USA; Guadagnini, A. [Dipartimento di Ingegneria Civile e Ambientale, Politecnico di Milano, Milano Italy

2017-11-01

Equations governing flow and transport in heterogeneous porous media are scale-dependent. We demonstrate that it is possible to identify a support scale $\\eta^*$, such that the typically employed approximate formulations of Moment Equations (ME) yield accurate (statistical) moments of a target environmental state variable. Under these circumstances, the ME approach can be used as an alternative to the Monte Carlo (MC) method for Uncertainty Quantification in diverse fields of Earth and environmental sciences. MEs are directly satisfied by the leading moments of the quantities of interest and are defined on the same support scale as the governing stochastic partial differential equations (PDEs). Computable approximations of the otherwise exact MEs can be obtained through perturbation expansion of moments of the state variables in orders of the standard deviation of the random model parameters. As such, their convergence is guaranteed only for the standard deviation smaller than one. We demonstrate our approach in the context of steady-state groundwater flow in a porous medium with a spatially random hydraulic conductivity.

Aleatoric and epistemic uncertainties in sampling based nuclear data uncertainty and sensitivity analyses

International Nuclear Information System (INIS)

Zwermann, W.; Krzykacz-Hausmann, B.; Gallner, L.; Klein, M.; Pautz, A.; Velkov, K.

2012-01-01

Sampling based uncertainty and sensitivity analyses due to epistemic input uncertainties, i.e. to an incomplete knowledge of uncertain input parameters, can be performed with arbitrary application programs to solve the physical problem under consideration. For the description of steady-state particle transport, direct simulations of the microscopic processes with Monte Carlo codes are often used. This introduces an additional source of uncertainty, the aleatoric sampling uncertainty, which is due to the randomness of the simulation process performed by sampling, and which adds to the total combined output sampling uncertainty. So far, this aleatoric part of uncertainty is minimized by running a sufficiently large number of Monte Carlo histories for each sample calculation, thus making its impact negligible as compared to the impact from sampling the epistemic uncertainties. Obviously, this process may cause high computational costs. The present paper shows that in many applications reliable epistemic uncertainty results can also be obtained with substantially lower computational effort by performing and analyzing two appropriately generated series of samples with much smaller number of Monte Carlo histories each. The method is applied along with the nuclear data uncertainty and sensitivity code package XSUSA in combination with the Monte Carlo transport code KENO-Va to various critical assemblies and a full scale reactor calculation. It is shown that the proposed method yields output uncertainties and sensitivities equivalent to the traditional approach, with a high reduction of computing time by factors of the magnitude of 100. (authors)

Uncertainty Propagation Analysis for the Monte Carlo Time-Dependent Simulations

International Nuclear Information System (INIS)

Shaukata, Nadeem; Shim, Hyung Jin

2015-01-01

In this paper, a conventional method to control the neutron population for super-critical systems is implemented. Instead of considering the cycles, the simulation is divided in time intervals. At the end of each time interval, neutron population control is applied on the banked neutrons. Randomly selected neutrons are discarded, until the size of neutron population matches the initial neutron histories at the beginning of time simulation. A time-dependent simulation mode has also been implemented in the development version of SERPENT 2 Monte Carlo code. In this mode, sequential population control mechanism has been proposed for modeling of prompt super-critical systems. A Monte Carlo method has been properly used in TART code for dynamic criticality calculations. For super-critical systems, the neutron population is allowed to grow over a period of time. The neutron population is uniformly combed to return it to the neutron population started with at the beginning of time boundary. In this study, conventional time-dependent Monte Carlo (TDMC) algorithm is implemented. There is an exponential growth of neutron population in estimation of neutron density tally for super-critical systems and the number of neutrons being tracked exceed the memory of the computer. In order to control this exponential growth at the end of each time boundary, a conventional time cut-off controlling population strategy is included in TDMC. A scale factor is introduced to tally the desired neutron density at the end of each time boundary. The main purpose of this paper is the quantification of uncertainty propagation in neutron densities at the end of each time boundary for super-critical systems. This uncertainty is caused by the uncertainty resulting from the introduction of scale factor. The effectiveness of TDMC is examined for one-group infinite homogeneous problem (the rod model) and two-group infinite homogeneous problem. The desired neutron density is tallied by the introduction of

Uncertainty Propagation Analysis for the Monte Carlo Time-Dependent Simulations

Energy Technology Data Exchange (ETDEWEB)

Shaukata, Nadeem; Shim, Hyung Jin [Seoul National University, Seoul (Korea, Republic of)

2015-10-15

In this paper, a conventional method to control the neutron population for super-critical systems is implemented. Instead of considering the cycles, the simulation is divided in time intervals. At the end of each time interval, neutron population control is applied on the banked neutrons. Randomly selected neutrons are discarded, until the size of neutron population matches the initial neutron histories at the beginning of time simulation. A time-dependent simulation mode has also been implemented in the development version of SERPENT 2 Monte Carlo code. In this mode, sequential population control mechanism has been proposed for modeling of prompt super-critical systems. A Monte Carlo method has been properly used in TART code for dynamic criticality calculations. For super-critical systems, the neutron population is allowed to grow over a period of time. The neutron population is uniformly combed to return it to the neutron population started with at the beginning of time boundary. In this study, conventional time-dependent Monte Carlo (TDMC) algorithm is implemented. There is an exponential growth of neutron population in estimation of neutron density tally for super-critical systems and the number of neutrons being tracked exceed the memory of the computer. In order to control this exponential growth at the end of each time boundary, a conventional time cut-off controlling population strategy is included in TDMC. A scale factor is introduced to tally the desired neutron density at the end of each time boundary. The main purpose of this paper is the quantification of uncertainty propagation in neutron densities at the end of each time boundary for super-critical systems. This uncertainty is caused by the uncertainty resulting from the introduction of scale factor. The effectiveness of TDMC is examined for one-group infinite homogeneous problem (the rod model) and two-group infinite homogeneous problem. The desired neutron density is tallied by the introduction of

The Lesbian, Gay, and Bisexual Identity Scale: Factor Analytic Evidence and Associations with Health and Well-Being

Science.gov (United States)

Cramer, Robert J.; Burks, Alixandra C.; Golom, Frank D.; Stroud, Caroline H.; Graham, James L.

2017-01-01

We tested the psychometric properties of the Lesbian, Gay, and Bisexual Identity Scale. Findings included (1) a three-factor structure (i.e., Negative Identity, Identity Uncertainty, Identity Superiority); (2) less positive identities among HIV-positive persons, African Americans, males, and bisexuals; and (3) convergent patterns with subjective…

Mapping neighborhood scale survey responses with uncertainty metrics

Directory of Open Access Journals (Sweden)

Charles Robert Ehlschlaeger

2016-12-01

Full Text Available This paper presents a methodology of mapping population-centric social, infrastructural, and environmental metrics at neighborhood scale. This methodology extends traditional survey analysis methods to create cartographic products useful in agent-based modeling and geographic information analysis. It utilizes and synthesizes survey microdata, sub-upazila attributes, land use information, and ground truth locations of attributes to create neighborhood scale multi-attribute maps. Monte Carlo methods are employed to combine any number of survey responses to stochastically weight survey cases and to simulate survey cases' locations in a study area. Through such Monte Carlo methods, known errors from each of the input sources can be retained. By keeping individual survey cases as the atomic unit of data representation, this methodology ensures that important covariates are retained and that ecological inference fallacy is eliminated. These techniques are demonstrated with a case study from the Chittagong Division in Bangladesh. The results provide a population-centric understanding of many social, infrastructural, and environmental metrics desired in humanitarian aid and disaster relief planning and operations wherever long term familiarity is lacking. Of critical importance is that the resulting products have easy to use explicit representation of the errors and uncertainties of each of the input sources via the automatically generated summary statistics created at the application's geographic scale.

Benchmarking and application of the state-of-the-art uncertainty analysis methods XSUSA and SHARK-X

International Nuclear Information System (INIS)

Aures, A.; Bostelmann, F.; Hursin, M.; Leray, O.

2017-01-01

Highlights: • Application of the uncertainty analysis methods XSUSA and SHARK-X. • Propagation of nuclear data uncertainty through PWR pin cell depletion calculation. • Uncertainty quantification of eigenvalue, nuclide densities and Doppler coefficient. • Top contributor to overall output uncertainty by sensitivity analysis. • Comparison with SAMPLER and TSUNAMI of the SCALE code package. - Abstract: This study presents collaborative work performed between GRS and PSI on benchmarking and application of the state-of-the-art uncertainty analysis methods XSUSA and SHARK-X. Applied to a PWR pin cell depletion calculation, both methods propagate input uncertainty from nuclear data to output uncertainty. The uncertainty of the multiplication factors, nuclide densities, and fuel temperature coefficients derived by both methods are compared at various burnup steps. Comparisons of these quantities are furthermore performed with the SAMPLER module of SCALE 6.2. The perturbation theory based TSUNAMI module of both SCALE 6.1 and SCALE 6.2 is additionally applied for comparisons of the reactivity coefficient.

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

Science.gov (United States)

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

2013-07-01

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

Sampling based uncertainty analysis of 10% hot leg break LOCA in large scale test facility

International Nuclear Information System (INIS)

Sengupta, Samiran; Kraina, V.; Dubey, S. K.; Rao, R. S.; Gupta, S. K.

2010-01-01

Sampling based uncertainty analysis was carried out to quantify uncertainty in predictions of best estimate code RELAP5/MOD3.2 for a thermal hydraulic test (10% hot leg break LOCA) performed in the Large Scale Test Facility (LSTF) as a part of an IAEA coordinated research project. The nodalisation of the test facility was qualified for both steady state and transient level by systematically applying the procedures led by uncertainty methodology based on accuracy extrapolation (UMAE); uncertainty analysis was carried out using the Latin hypercube sampling (LHS) method to evaluate uncertainty for ten input parameters. Sixteen output parameters were selected for uncertainty evaluation and uncertainty band between 5 th and 95 th percentile of the output parameters were evaluated. It was observed that the uncertainty band for the primary pressure during two phase blowdown is larger than that of the remaining period. Similarly, a larger uncertainty band is observed relating to accumulator injection flow during reflood phase. Importance analysis was also carried out and standard rank regression coefficients were computed to quantify the effect of each individual input parameter on output parameters. It was observed that the break discharge coefficient is the most important uncertain parameter relating to the prediction of all the primary side parameters and that the steam generator (SG) relief pressure setting is the most important parameter in predicting the SG secondary pressure

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.

Deterministic sensitivity and uncertainty analysis for large-scale computer models

International Nuclear Information System (INIS)

Worley, B.A.; Pin, F.G.; Oblow, E.M.; Maerker, R.E.; Horwedel, J.E.; Wright, R.Q.

1988-01-01

The fields of sensitivity and uncertainty analysis have traditionally been dominated by statistical techniques when large-scale modeling codes are being analyzed. These methods are able to estimate sensitivities, generate response surfaces, and estimate response probability distributions given the input parameter probability distributions. Because the statistical methods are computationally costly, they are usually applied only to problems with relatively small parameter sets. Deterministic methods, on the other hand, are very efficient and can handle large data sets, but generally require simpler models because of the considerable programming effort required for their implementation. The first part of this paper reports on the development and availability of two systems, GRESS and ADGEN, that make use of computer calculus compilers to automate the implementation of deterministic sensitivity analysis capability into existing computer models. This automation removes the traditional limitation of deterministic sensitivity methods. This second part of the paper describes a deterministic uncertainty analysis method (DUA) that uses derivative information as a basis to propagate parameter probability distributions to obtain result probability distributions. This paper is applicable to low-level radioactive waste disposal system performance assessment

Renormalization and factorization scale analysis of b-barb production in antiproton-proton collisions

International Nuclear Information System (INIS)

Chyla, Jiri

2003-01-01

There is a sizable and systematic discrepancy between experimental data on the b-barb production in , p-barp, γp and γγ collisions and existing theoretical calculations within perturbative QCD. Before interpreting this discrepancy as a signal of new physics, it is important to understand quantitatively the ambiguities of conventional calculations. In this paper the uncertainty coming from renormalization and factorization scale dependence of finite order perturbation calculations of the total cross section of b-barb production in p-barp collisions is discussed in detail. It is shown that the mentioned discrepancy is reduced significantly if these scales are fixed via the Principle of Minimal Sensitivity. (author)

Environmental impact and risk assessments and key factors contributing to the overall uncertainties

International Nuclear Information System (INIS)

Salbu, Brit

2016-01-01

There is a significant number of nuclear and radiological sources that have contributed, are still contributing, or have the potential to contribute to radioactive contamination of the environment in the future. To protect the environment from radioactive contamination, impact and risk assessments are performed prior to or during a release event, short or long term after deposition or prior and after implementation of countermeasures. When environmental impact and risks are assessed, however, a series of factors will contribute to the overall uncertainties. To provide environmental impact and risk assessments, information on processes, kinetics and a series of input variables is needed. Adding problems such as variability, questionable assumptions, gaps in knowledge, extrapolations and poor conceptual model structures, a series of factors are contributing to large and often unacceptable uncertainties in impact and risk assessments. Information on the source term and the release scenario is an essential starting point in impact and risk models; the source determines activity concentrations and atom ratios of radionuclides released, while the release scenario determine the physico-chemical forms of released radionuclides such as particle size distribution, structure and density. Releases will most often contain other contaminants such as metals, and due to interactions, contaminated sites should be assessed as a multiple stressor scenario. Following deposition, a series of stressors, interactions and processes will influence the ecosystem transfer of radionuclide species and thereby influence biological uptake (toxicokinetics) and responses (toxicodynamics) in exposed organisms. Due to the variety of biological species, extrapolation is frequently needed to fill gaps in knowledge e.g., from effects to no effects, from effects in one organism to others, from one stressor to mixtures. Most toxtests are, however, performed as short term exposure of adult organisms

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

Science.gov (United States)

Filipsson, Monika; Öberg, Tomas; Bergbäck, Bo

2011-01-01

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

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

Science.gov (United States)

2013-01-01

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

Sustainable water management under future uncertainty with eco-engineering decision scaling

Science.gov (United States)

Poff, N. Leroy; Brown, Casey M.; Grantham, Theodore E.; Matthews, John H.; Palmer, Margaret A.; Spence, Caitlin M.; Wilby, Robert L.; Haasnoot, Marjolijn; Mendoza, Guillermo F.; Dominique, Kathleen C.; Baeza, Andres

2016-01-01

Managing freshwater resources sustainably under future climatic and hydrological uncertainty poses novel challenges. Rehabilitation of ageing infrastructure and construction of new dams are widely viewed as solutions to diminish climate risk, but attaining the broad goal of freshwater sustainability will require expansion of the prevailing water resources management paradigm beyond narrow economic criteria to include socially valued ecosystem functions and services. We introduce a new decision framework, eco-engineering decision scaling (EEDS), that explicitly and quantitatively explores trade-offs in stakeholder-defined engineering and ecological performance metrics across a range of possible management actions under unknown future hydrological and climate states. We illustrate its potential application through a hypothetical case study of the Iowa River, USA. EEDS holds promise as a powerful framework for operationalizing freshwater sustainability under future hydrological uncertainty by fostering collaboration across historically conflicting perspectives of water resource engineering and river conservation ecology to design and operate water infrastructure for social and environmental benefits.

Sustainable water management under future uncertainty with eco-engineering decision scaling

Science.gov (United States)

Poff, N LeRoy; Brown, Casey M; Grantham, Theodore E.; Matthews, John H; Palmer, Margaret A.; Spence, Caitlin M; Wilby, Robert L.; Haasnoot, Marjolijn; Mendoza, Guillermo F; Dominique, Kathleen C; Baeza, Andres

2015-01-01

Managing freshwater resources sustainably under future climatic and hydrological uncertainty poses novel challenges. Rehabilitation of ageing infrastructure and construction of new dams are widely viewed as solutions to diminish climate risk, but attaining the broad goal of freshwater sustainability will require expansion of the prevailing water resources management paradigm beyond narrow economic criteria to include socially valued ecosystem functions and services. We introduce a new decision framework, eco-engineering decision scaling (EEDS), that explicitly and quantitatively explores trade-offs in stakeholder-defined engineering and ecological performance metrics across a range of possible management actions under unknown future hydrological and climate states. We illustrate its potential application through a hypothetical case study of the Iowa River, USA. EEDS holds promise as a powerful framework for operationalizing freshwater sustainability under future hydrological uncertainty by fostering collaboration across historically conflicting perspectives of water resource engineering and river conservation ecology to design and operate water infrastructure for social and environmental benefits.

Jet energy scale uncertainty correlations between ATLAS and CMS at $\\sqrt{s}=8$ TeV

CERN Document Server

The ATLAS collaboration

2015-01-01

An evaluation of the correlations between ATLAS and CMS jet energy scale uncertainties is presented for $\\sqrt{s}=8\\,\\mathrm{TeV}$ $pp$ collisions recorded in 2012. Uncertainties within each experiment are grouped based on the general type of systematic effect they are intended to cover and the means by which they are derived. Inter-experimental correlation value ranges are established for each corresponding group of uncertainty components. This correlation range is intended to cover the possible correlation values when performing combinations between the two experiments, where the most conservative value obtained from scanning over the correlation range should be used for the final combined measurement. The procedure described here is primarily aimed at single-observable analyses, and has limitations when applied to multi-observable measurements.

Probabilistic Physics of Failure-based framework for fatigue life prediction of aircraft gas turbine discs under uncertainty

International Nuclear Information System (INIS)

Zhu, Shun-Peng; Huang, Hong-Zhong; Peng, Weiwen; Wang, Hai-Kun; Mahadevan, Sankaran

2016-01-01

A probabilistic Physics of Failure-based framework for fatigue life prediction of aircraft gas turbine discs operating under uncertainty is developed. The framework incorporates the overall uncertainties appearing in a structural integrity assessment. A comprehensive uncertainty quantification (UQ) procedure is presented to quantify multiple types of uncertainty using multiplicative and additive UQ methods. In addition, the factors that contribute the most to the resulting output uncertainty are investigated and identified for uncertainty reduction in decision-making. A high prediction accuracy of the proposed framework is validated through a comparison of model predictions to the experimental results of GH4133 superalloy and full-scale tests of aero engine high-pressure turbine discs. - Highlights: • A probabilistic PoF-based framework for fatigue life prediction is proposed. • A comprehensive procedure forquantifyingmultiple types of uncertaintyis presented. • The factors that contribute most to the resulting output uncertainty are identified. • The proposed frameworkdemonstrates high prediction accuracybyfull-scale tests.

Quantifying reactor safety margins: Application of code scaling, applicability, and uncertainty evaluation methodology to a large-break, loss-of-coolant accident

International Nuclear Information System (INIS)

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

1989-12-01

The US Nuclear Regulatory Commission (NRC) has issued a revised rule for loss-of-coolant accident/emergency core cooling system (ECCS) analysis of light water reactors to allow the use of best-estimate computer codes in safety analysis as an option. A key feature of this option requires the licensee to quantify the uncertainty of the calculations and include that uncertainty when comparing the calculated results with acceptance limits provided in 10 CFR Part 50. To support the revised ECCS rule and illustrate its application, the NRC and its contractors and consultants have developed and demonstrated an uncertainty evaluation methodology called code scaling, applicability, and uncertainty (CSAU). The CSAU methodology and an example application described in this report demonstrate that uncertainties in complex phenomena can be quantified. The methodology is structured, traceable, and practical, as is needed in the regulatory arena. The methodology is systematic and comprehensive as it addresses and integrates the scenario, experiments, code, and plant to resolve questions concerned with: (a) code capability to scale-up processes from test facility to full-scale nuclear power plants; (b) code applicability to safety studies of a postulated accident scenario in a specified nuclear power plant; and (c) quantifying uncertainties of calculated results. 127 refs., 55 figs., 40 tabs

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

Science.gov (United States)

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

2018-01-01

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

Validation and cultural adaptation of a German version of the Physicians' Reactions to Uncertainty scales.

NARCIS (Netherlands)

Schneider, A.; Szecsenyi, J.; Barie, S.; Joest, K.; Rosemann, T.J.

2007-01-01

BACKGROUND: The aim of the study was to examine the validity of a translated and culturally adapted version of the Physicians' Reaction to Uncertainty scales (PRU) in primary care physicians. METHODS: In a structured process, the original questionnaire was translated, culturally adapted and assessed

CSAU (Code Scaling, Applicability and Uncertainty)

International Nuclear Information System (INIS)

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

1989-01-01

Best Estimate computer codes have been accepted by the U.S. Nuclear Regulatory Commission as an optional tool for performing safety analysis related to the licensing and regulation of current nuclear reactors producing commercial electrical power, providing their uncertainty is quantified. In support of this policy change, the NRC and its contractors and consultants have developed and demonstrated an uncertainty quantification methodology called CSAU. The primary use of the CSAU methodology is to quantify safety margins for existing designs; however, the methodology can also serve an equally important role in advanced reactor research for plants not yet built. This paper describes the CSAU methodology, at the generic process level, and provides the general principles whereby it may be applied to evaluations of advanced reactor designs

Landscape Change in the Southern Piedmont: Challenges, Solutions, and Uncertainty Across Scales

Directory of Open Access Journals (Sweden)

Michael J. Conroy

2003-12-01

Full Text Available The southern Piedmont of the southeastern United States epitomizes the complex and seemingly intractable problems and hard decisions that result from uncontrolled urban and suburban sprawl. Here we consider three recurrent themes in complicated problems involving complex systems: (1 scale dependencies and cross-scale, often nonlinear relationships; (2 resilience, in particular the potential for complex systems to move to alternate stable states with decreased ecological and/or economic value; and (3 uncertainty in the ability to understand and predict outcomes, perhaps particularly those that occur as a result of human impacts. We consider these issues in the context of landscape-level decision making, using as an example water resources and lotic systems in the Piedmont region of the southeastern United States.

Individualized adjustments to reference phantom internal organ dosimetry—scaling factors given knowledge of patient external anatomy

Science.gov (United States)

Wayson, Michael B.; Bolch, Wesley E.

2018-04-01

Internal radiation dose estimates for diagnostic nuclear medicine procedures are typically calculated for a reference individual. Resultantly, there is uncertainty when determining the organ doses to patients who are not at 50th percentile on either height or weight. This study aims to better personalize internal radiation dose estimates for individual patients by modifying the dose estimates calculated for reference individuals based on easily obtainable morphometric characteristics of the patient. Phantoms of different sitting heights and waist circumferences were constructed based on computational reference phantoms for the newborn, 10 year-old, and adult. Monoenergetic photons and electrons were then simulated separately at 15 energies. Photon and electron specific absorbed fractions (SAFs) were computed for the newly constructed non-reference phantoms and compared to SAFs previously generated for the age-matched reference phantoms. Differences in SAFs were correlated to changes in sitting height and waist circumference to develop scaling factors that could be applied to reference SAFs as morphometry corrections. A further set of arbitrary non-reference phantoms were then constructed and used in validation studies for the SAF scaling factors. Both photon and electron dose scaling methods were found to increase average accuracy when sitting height was used as the scaling parameter (~11%). Photon waist circumference-based scaling factors showed modest increases in average accuracy (~7%) for underweight individuals, but not for overweight individuals. Electron waist circumference-based scaling factors did not show increases in average accuracy. When sitting height and waist circumference scaling factors were combined, modest average gains in accuracy were observed for photons (~6%), but not for electrons. Both photon and electron absorbed doses are more reliably scaled using scaling factors computed in this study. They can be effectively scaled using sitting

Individualized adjustments to reference phantom internal organ dosimetry-scaling factors given knowledge of patient external anatomy.

Science.gov (United States)

Wayson, Michael B; Bolch, Wesley E

2018-04-13

Internal radiation dose estimates for diagnostic nuclear medicine procedures are typically calculated for a reference individual. Resultantly, there is uncertainty when determining the organ doses to patients who are not at 50th percentile on either height or weight. This study aims to better personalize internal radiation dose estimates for individual patients by modifying the dose estimates calculated for reference individuals based on easily obtainable morphometric characteristics of the patient. Phantoms of different sitting heights and waist circumferences were constructed based on computational reference phantoms for the newborn, 10 year-old, and adult. Monoenergetic photons and electrons were then simulated separately at 15 energies. Photon and electron specific absorbed fractions (SAFs) were computed for the newly constructed non-reference phantoms and compared to SAFs previously generated for the age-matched reference phantoms. Differences in SAFs were correlated to changes in sitting height and waist circumference to develop scaling factors that could be applied to reference SAFs as morphometry corrections. A further set of arbitrary non-reference phantoms were then constructed and used in validation studies for the SAF scaling factors. Both photon and electron dose scaling methods were found to increase average accuracy when sitting height was used as the scaling parameter (~11%). Photon waist circumference-based scaling factors showed modest increases in average accuracy (~7%) for underweight individuals, but not for overweight individuals. Electron waist circumference-based scaling factors did not show increases in average accuracy. When sitting height and waist circumference scaling factors were combined, modest average gains in accuracy were observed for photons (~6%), but not for electrons. Both photon and electron absorbed doses are more reliably scaled using scaling factors computed in this study. They can be effectively scaled using sitting

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

Large-Scale Transport Model Uncertainty and Sensitivity Analysis: Distributed Sources in Complex Hydrogeologic Systems

International Nuclear Information System (INIS)

Sig Drellack, Lance Prothro

2007-01-01

simulations are challenged by the distributed sources in each of the Corrective Action Units, by complex mass transfer processes, and by the size and complexity of the field-scale flow models. An efficient methodology utilizing particle tracking results and convolution integrals provides in situ concentrations appropriate for Monte Carlo analysis. Uncertainty in source releases and transport parameters including effective porosity, fracture apertures and spacing, matrix diffusion coefficients, sorption coefficients, and colloid load and mobility are considered. With the distributions of input uncertainties and output plume volumes, global analysis methods including stepwise regression, contingency table analysis, and classification tree analysis are used to develop sensitivity rankings of parameter uncertainties for each model considered, thus assisting a variety of decisions

Environmental impact and risk assessments and key factors contributing to the overall uncertainties.

Science.gov (United States)

Salbu, Brit

2016-01-01

There is a significant number of nuclear and radiological sources that have contributed, are still contributing, or have the potential to contribute to radioactive contamination of the environment in the future. To protect the environment from radioactive contamination, impact and risk assessments are performed prior to or during a release event, short or long term after deposition or prior and after implementation of countermeasures. When environmental impact and risks are assessed, however, a series of factors will contribute to the overall uncertainties. To provide environmental impact and risk assessments, information on processes, kinetics and a series of input variables is needed. Adding problems such as variability, questionable assumptions, gaps in knowledge, extrapolations and poor conceptual model structures, a series of factors are contributing to large and often unacceptable uncertainties in impact and risk assessments. Information on the source term and the release scenario is an essential starting point in impact and risk models; the source determines activity concentrations and atom ratios of radionuclides released, while the release scenario determine the physico-chemical forms of released radionuclides such as particle size distribution, structure and density. Releases will most often contain other contaminants such as metals, and due to interactions, contaminated sites should be assessed as a multiple stressor scenario. Following deposition, a series of stressors, interactions and processes will influence the ecosystem transfer of radionuclide species and thereby influence biological uptake (toxicokinetics) and responses (toxicodynamics) in exposed organisms. Due to the variety of biological species, extrapolation is frequently needed to fill gaps in knowledge e.g., from effects to no effects, from effects in one organism to others, from one stressor to mixtures. Most toxtests are, however, performed as short term exposure of adult organisms

Quantification of variability and uncertainty in lawn and garden equipment NOx and total hydrocarbon emission factors.

Science.gov (United States)

Frey, H Christopher; Bammi, Sachin

2002-04-01

Variability refers to real differences in emissions among multiple emission sources at any given time or over time for any individual emission source. Variability in emissions can be attributed to variation in fuel or feedstock composition, ambient temperature, design, maintenance, or operation. Uncertainty refers to lack of knowledge regarding the true value of emissions. Sources of uncertainty include small sample sizes, bias or imprecision in measurements, nonrepresentativeness, or lack of data. Quantitative methods for characterizing both variability and uncertainty are demonstrated and applied to case studies of emission factors for lawn and garden (L&G) equipment engines. Variability was quantified using empirical and parametric distributions. Bootstrap simulation was used to characterize confidence intervals for the fitted distributions. The 95% confidence intervals for the mean grams per brake horsepower/hour (g/hp-hr) emission factors for two-stroke engine total hydrocarbon (THC) and NOx emissions were from -30 to +41% and from -45 to +75%, respectively. The confidence intervals for four-stroke engines were from -33 to +46% for THCs and from -27 to +35% for NOx. These quantitative measures of uncertainty convey information regarding the quality of the emission factors and serve as a basis for calculation of uncertainty in emission inventories (EIs).

Uncertainty quantification of fast sodium current steady-state inactivation for multi-scale models of cardiac electrophysiology.

Science.gov (United States)

Pathmanathan, Pras; Shotwell, Matthew S; Gavaghan, David J; Cordeiro, Jonathan M; Gray, Richard A

2015-01-01

Perhaps the most mature area of multi-scale systems biology is the modelling of the heart. Current models are grounded in over fifty years of research in the development of biophysically detailed models of the electrophysiology (EP) of cardiac cells, but one aspect which is inadequately addressed is the incorporation of uncertainty and physiological variability. Uncertainty quantification (UQ) is the identification and characterisation of the uncertainty in model parameters derived from experimental data, and the computation of the resultant uncertainty in model outputs. It is a necessary tool for establishing the credibility of computational models, and will likely be expected of EP models for future safety-critical clinical applications. The focus of this paper is formal UQ of one major sub-component of cardiac EP models, the steady-state inactivation of the fast sodium current, INa. To better capture average behaviour and quantify variability across cells, we have applied for the first time an 'individual-based' statistical methodology to assess voltage clamp data. Advantages of this approach over a more traditional 'population-averaged' approach are highlighted. The method was used to characterise variability amongst cells isolated from canine epi and endocardium, and this variability was then 'propagated forward' through a canine model to determine the resultant uncertainty in model predictions at different scales, such as of upstroke velocity and spiral wave dynamics. Statistically significant differences between epi and endocardial cells (greater half-inactivation and less steep slope of steady state inactivation curve for endo) was observed, and the forward propagation revealed a lack of robustness of the model to underlying variability, but also surprising robustness to variability at the tissue scale. Overall, the methodology can be used to: (i) better analyse voltage clamp data; (ii) characterise underlying population variability; (iii) investigate

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

Landscape change in the Southern Piedmont: Challenges, solutions and uncertainty across scales

Science.gov (United States)

Conroy, M.J.; Allen, Craig R.; Peterson, J.T.; Pritchard, L.; Moore, C.T.

2003-01-01

The southern Piedmont of the southeastern United States epitomizes the complex and seemingly intractable problems and hard decisions that result from uncontrolled urban and suburban sprawl. Here we consider three recurrent themes in complicated problems involving complex systems: (1) scale dependencies and cross-scale, often nonlinear relationships; (2) resilience, in particular the potential for complex systems to move to alternate stable states with decreased ecological and/or economic value; and (3) uncertainty in the ability to understand and predict outcomes, perhaps particularly those that occur as a result of human impacts. We consider these issues in the context of landscape-level decision making, using as an example water resources and lotic systems in the Piedmont region of the southeastern United States. Copyright ?? 2003 by the author(s). Published here under licence by The Resilience Alliance.

Estimation of uncertainties from missing higher orders in perturbative calculations

International Nuclear Information System (INIS)

Bagnaschi, E.

2015-05-01

In this proceeding we present the results of our recent study (hep-ph/1409.5036) of the statistical performances of two different approaches, Scale Variation (SV) and the Bayesian model of Cacciari and Houdeau (CH)(hep-ph/1105.5152) (which we also extend to observables with initial state hadrons), to the estimation of Missing Higher-Order Uncertainties (MHOUs)(hep-ph/1307.1843) in perturbation theory. The behavior of the models is determined by analyzing, on a wide set of observables, how the MHOU intervals they produce are successful in predicting the next orders. We observe that the Bayesian model behaves consistently, producing intervals at 68% Degree of Belief (DoB) comparable with the scale variation intervals with a rescaling factor r larger than 2 and closer to 4. Concerning SV, our analysis allows the derivation of a heuristic Confidence Level (CL) for the intervals. We find that assigning a CL of 68% to the intervals obtained with the conventional choice of varying the scales within a factor of two with respect to the central scale could potentially lead to an underestimation of the uncertainties in the case of observables with initial state hadrons.

Development of radionuclide inventory estimation method using scaling factor for the Korean NPPs: scope and status

International Nuclear Information System (INIS)

Hwang, Ki Ha; Lee, Sang Chul; Kang, Sang Hee; Lee, Kun Jai; Jeong, Chan Woo; Ahn, Sang Myeon; Kim, Tae Wook; Kim, Kyoung Doek; Herr, Y. H.

2003-01-01

Regulations and guidelines for radionuclide waste disposal require detailed information about the characteristics of radioactive waste drums prior to the transport to the disposal sites. Therefore, it is important to know the accurate radionuclide inventory of radioactive waste. However, estimation of radionuclide concentrations on drummed radioactive waste is difficult and unreliable. In order to overcome these difficulties, scaling factors have been used to assess the activities of radionuclides which could not be directly analyzed. A radionuclides assay system has been operated at Korean nuclear power plant (KORI site) since 1996 and consolidated scaling factor concept has played a dominant role in determination of radionuclides concentrations. For corrosion product radionuclides, generic scaling factors were used due to the similar trend and better-characterized properties of Korean analyzed data compared to the worldwide database. It is not easy to use the generic scaling factors for fission product and TRU radionuclides. Thus simple model reflecting the history of the operation of power plant and nuclear fuel condition is applied. However, some problems are still remained. For examples, disparity between the actual and ideal correlation pairs, inaccuracy of analyzed sample values, uncertainty in representative of derived scaling factor values and so on. As a result, the correlation ratios are somewhat dispersive. So it is planned to establish an assay system using more improved scaling factors. In this study, the scope of research is expanded and planned such as following. 1) Considering more assay target nuclides, 2) Considering more target NPPs, 3) More reliable sampling and measurement techniques, 4) Improvement of accuracy and representativeness of derived scaling factor values and 5) Conformation of correlation pairs based on Korean analyzed data. As this study progresses, it is possible to get more accurate and reliable prediction for the information of

Uncertainty in geological and hydrogeological data

Directory of Open Access Journals (Sweden)

B. Nilsson

2007-09-01

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

Uncertainty Evaluation of the Thermal Expansion of Gd2O3-ZrO2 with a System Calibration Factor

International Nuclear Information System (INIS)

Park, Chang Je; Kang, Kweon Ho; Na, Sang Ho; Song, Kee Chan

2007-01-01

Both gadolinia (Gd 2 O 3 ) and zirconia (ZrO 2 ) are widely used in the nuclear industry, including a burnable absorber and additives in the fabrication of a simulated fuel. Thermal expansions of a mixture of gadolinia (Gd 2 O 3 ) 20 mol% and zirconia (ZrO 2 ) 80 mol% were measured by using a dilatometer (DIL402C) from room temperature to 1500 .deg. C. Uncertainties in the measurement should be quantified based on statistics. Referring to the ISO (International Organization for Standardization) guide, the uncertainties of the thermal expansion were quantified for three parts - the initial length, the length variation, and the system calibration factor. The whole system, the dilatometer, is composed of many complex sub-systems and in fact it is difficult to consider all the uncertainties of the sub-systems. Thus, the system calibration factor was introduced with a standard material for the uncertainty evaluation. In this study, a new system calibration factor was formulated in a multiplicative way. Further, the effect of calibration factor with random deviation was investigated for the uncertainty evaluation of a thermal expansion

A continental-scale hydrology and water quality model for Europe: Calibration and uncertainty of a high-resolution large-scale SWAT model

Science.gov (United States)

Abbaspour, K. C.; Rouholahnejad, E.; Vaghefi, S.; Srinivasan, R.; Yang, H.; Kløve, B.

2015-05-01

A combination of driving forces are increasing pressure on local, national, and regional water supplies needed for irrigation, energy production, industrial uses, domestic purposes, and the environment. In many parts of Europe groundwater quantity, and in particular quality, have come under sever degradation and water levels have decreased resulting in negative environmental impacts. Rapid improvements in the economy of the eastern European block of countries and uncertainties with regard to freshwater availability create challenges for water managers. At the same time, climate change adds a new level of uncertainty with regard to freshwater supplies. In this research we build and calibrate an integrated hydrological model of Europe using the Soil and Water Assessment Tool (SWAT) program. Different components of water resources are simulated and crop yield and water quality are considered at the Hydrological Response Unit (HRU) level. The water resources are quantified at subbasin level with monthly time intervals. Leaching of nitrate into groundwater is also simulated at a finer spatial level (HRU). The use of large-scale, high-resolution water resources models enables consistent and comprehensive examination of integrated system behavior through physically-based, data-driven simulation. In this article we discuss issues with data availability, calibration of large-scale distributed models, and outline procedures for model calibration and uncertainty analysis. The calibrated model and results provide information support to the European Water Framework Directive and lay the basis for further assessment of the impact of climate change on water availability and quality. The approach and methods developed are general and can be applied to any large region around the world.

Using Large-Scale Cooperative Control to Manage Operational Uncertainties for Aquifer Thermal Energy Storage

Science.gov (United States)

Jaxa-Rozen, M.; Rostampour, V.; Kwakkel, J. H.; Bloemendal, M.

2017-12-01

Seasonal Aquifer Thermal Energy Storage (ATES) technology can help reduce the demand of energy for heating and cooling in buildings, and has become a popular option for larger buildings in northern Europe. However, the larger-scale deployment of this technology has evidenced some issues of concern for policymakers; in particular, recent research shows that operational uncertainties contribute to inefficient outcomes under current planning methods for ATES. For instance, systems in the Netherlands typically use less than half of their permitted pumping volume on an annual basis. This overcapacity gives users more flexibility to operate their systems in response to the uncertainties which drive building energy demand; these include short-term operational factors such as weather and occupancy, and longer-term, deeply uncertain factors such as changes in climate and aquifer conditions over the lifespan of the buildings. However, as allocated subsurface volume remains unused, this situation limits the adoption of the technology in dense areas. Previous work using coupled agent-based/geohydrological simulation has shown that the cooperative operation of neighbouring ATES systems can support more efficient spatial planning, by dynamically managing thermal interactions in response to uncertain operating conditions. An idealized case study with centralized ATES control thus showed significant improvements in the energy savings which could obtained per unit of allocated subsurface volume, without degrading the recovery performance of systems. This work will extend this cooperative approach for a realistic case study of ATES planning in the city of Utrecht, in the Netherlands. This case was previously simulated under different scenarios for individual ATES operation. The poster will compare these results with a cooperative case under which neighbouring systems can coordinate their operation to manage interactions. Furthermore, a cooperative game-theoretical framework will be

Update on the jet energy scale systematic uncertainty for jets produced in proton-proton collisions at $\\sqrt{s}=7$~TeV measured with the ATLAS detector

CERN Document Server

The ATLAS collaboration

2011-01-01

An update to the jet energy scale systematic uncertainty for inclusive jets measured in the ATLAS detector and produced in proton-proton collisions at a centre-of-mass energy of $\\sqrt{s}=7$~TeV is described. The jet energy scale systematic uncertainty for jets reconstructed with the \\antikt~algorithm with distance parameters of $R=0.4$ and $R=0.6$ is evaluated starting from a transverse momentum of $20$~GeV and for a calorimeter coverage up to pseudo-rapidities of $|\\eta| = 4.5$. In the central detector region the jet energy scale uncertainty is obtained from the single isolated hadron response measured in-situ in proton proton collisions and in the ATLAS combined test-beam for pion momenta up to $350$~GeV. Further uncertainties are evaluated with systematic variations of Monte Carlo simulations. The uncertainty is extended to the endcap and forward detector regions exploiting the transverse momentum balance between a central and a forward jet in events where only two jets are produced. The JES uncertainty a...

Conversion factor and uncertainty estimation for quantification of towed gamma-ray detector measurements in Tohoku coastal waters

International Nuclear Information System (INIS)

Ohnishi, S.; Thornton, B.; Kamada, S.; Hirao, Y.; Ura, T.; Odano, N.

2016-01-01

Factors to convert the count rate of a NaI(Tl) scintillation detector to the concentration of radioactive cesium in marine sediments are estimated for a towed gamma-ray detector system. The response of the detector against a unit concentration of radioactive cesium is calculated by Monte Carlo radiation transport simulation considering the vertical profile of radioactive material measured in core samples. The conversion factors are acquired by integrating the contribution of each layer and are normalized by the concentration in the surface sediment layer. At the same time, the uncertainty of the conversion factors are formulated and estimated. The combined standard uncertainty of the radioactive cesium concentration by the towed gamma-ray detector is around 25 percent. The values of uncertainty, often referred to as relative root mean squat errors in other works, between sediment core sampling measurements and towed detector measurements were 16 percent in the investigation made near the Abukuma River mouth and 5.2 percent in Sendai Bay, respectively. Most of the uncertainty is due to interpolation of the conversion factors between core samples and uncertainty of the detector's burial depth. The results of the towed measurements agree well with laboratory analysed sediment samples. Also, the concentrations of radioactive cesium at the intersection of each survey line are consistent. The consistency with sampling results and between different lines' transects demonstrate the availability and reproducibility of towed gamma-ray detector system.

Conversion factor and uncertainty estimation for quantification of towed gamma-ray detector measurements in Tohoku coastal waters

Energy Technology Data Exchange (ETDEWEB)

Ohnishi, S., E-mail: ohnishi@nmri.go.jp [National Maritime Research Institute, 6-38-1, Shinkawa, Mitaka, Tokyo 181-0004 (Japan); Thornton, B. [Institute of Industrial Science, The University of Tokyo, 4-6-1, Komaba, Meguro-ku, Tokyo 153-8505 (Japan); Kamada, S.; Hirao, Y.; Ura, T.; Odano, N. [National Maritime Research Institute, 6-38-1, Shinkawa, Mitaka, Tokyo 181-0004 (Japan)

2016-05-21

Factors to convert the count rate of a NaI(Tl) scintillation detector to the concentration of radioactive cesium in marine sediments are estimated for a towed gamma-ray detector system. The response of the detector against a unit concentration of radioactive cesium is calculated by Monte Carlo radiation transport simulation considering the vertical profile of radioactive material measured in core samples. The conversion factors are acquired by integrating the contribution of each layer and are normalized by the concentration in the surface sediment layer. At the same time, the uncertainty of the conversion factors are formulated and estimated. The combined standard uncertainty of the radioactive cesium concentration by the towed gamma-ray detector is around 25 percent. The values of uncertainty, often referred to as relative root mean squat errors in other works, between sediment core sampling measurements and towed detector measurements were 16 percent in the investigation made near the Abukuma River mouth and 5.2 percent in Sendai Bay, respectively. Most of the uncertainty is due to interpolation of the conversion factors between core samples and uncertainty of the detector's burial depth. The results of the towed measurements agree well with laboratory analysed sediment samples. Also, the concentrations of radioactive cesium at the intersection of each survey line are consistent. The consistency with sampling results and between different lines' transects demonstrate the availability and reproducibility of towed gamma-ray detector system.

Hydrogeological boundary settings in SR 97. Uncertainties in regional boundary settings and transfer of boundary conditions to site-scale models

International Nuclear Information System (INIS)

Follin, S.

1999-06-01

The SR 97 project presents a performance assessment (PA) of the overall safety of a hypothetical deep repository at three sites in Sweden arbitrarily named Aberg, Beberg and Ceberg. One component of this PA assesses the uncertainties in the hydrogeological modelling. This study focuses on uncertainties in boundary settings (size of model domain and boundary conditions) in the regional and site-scale hydrogeological modelling of the three sites used to simulating the possible transport of radionuclides from the emplacement waste packages through the host rock to the accessible environment. Model uncertainties associated with, for instance, parameter heterogeneity and structural interpretations are addressed in other studies. This study concludes that the regional modelling of the SR 97 project addresses uncertainties in the choice of boundary conditions and size of model domain differently at each site, although the overall handling is acceptable and in accordance with common modelling practice. For example, the treatment of uncertainties with regard to the ongoing post-glacial flushing of the Baltic Shield is creditably addressed although not exhaustive from a modelling point of view. A significant contribution of the performed modelling is the study of nested numerical models, i.e., the numerical interplay between regional and site-scale numerical models. In the site-scale modelling great efforts are made to address problems associated with (i) the telescopic mesh refinement (TMR) technique with regard to the stochastic continuum approach, and (ii) the transfer of boundary conditions between variable-density flow systems and flow systems that are constrained to treat uniform density flow. This study concludes that the efforts made to handle these problems are acceptable with regards to the objectives of the SR 97 project

Uncertainty of the thyroid dose conversion factor for inhalation intakes of 131I and its parametric uncertainty

International Nuclear Information System (INIS)

Harvey, R. P.; Hamby, D. M.; Palmer, T. S.

2006-01-01

Inhalation exposures of 131 I may occur in the physical form of a gas as well as a particulate. The physical characteristics pertaining to these different types of releases influence the intake and subsequent dose to an exposed individual. The thyroid dose received is influenced by the route through which 131 I enters the body and its subsequent clearance, absorption and movement throughout the body. The radioactive iodine taken up in the gas-exchange tissues is cleared to other tissues or absorbed into the bloodstream of the individual and transferred to other organs. Iodine in the circulatory system is then taken up by the thyroid gland with resulting dose to that tissue. The magnitude of and uncertainty in the thyroid dose is important to the assessment of individuals exposed to airborne releases of radioiodine. Age- and gender-specific modelling parameters have resulted in significant differences between gas uptake, particulate deposition and inhalation dose conversion factors for each age and gender group. Inhalation dose conversion factors and their inherent uncertainty are markedly affected by the type of iodine intake. These differences are expected due to the modelling of particulate deposition versus uptake of gas in the respiratory tract. Inhalation dose estimates via iodine gases are very similar and separate classifications may not be necessarily based on this assessment. (authors)

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

Science.gov (United States)

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

2015-04-01

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

Data replicating the factor structure and reliability of commonly used measures of resilience: The Connor–Davidson Resilience Scale, Resilience Scale, and Scale of Protective Factors

Directory of Open Access Journals (Sweden)

A.N. Madewell

2016-09-01

Full Text Available The data presented in this article are related to the article entitled “Assessing Resilience in Emerging Adulthood: The Resilience Scale (RS, Connor Davidson Resilience Scale (CD-RISC, and Scale of Protective Factors (SPF” (Madewell and Ponce-Garcia, 2016 [1]. The data were collected from a sample of 451 college students from three universities located in the Southwestern region of the United States: 374 from a large public university and 67 from two smaller regional universities. The data from the three universities did not significantly differ in terms of demographics. The data represent participant responses on six measurements to include the Resilience Scale-25 (RS-25, Resilience Scale-14 (RS-14, Connor Davidson Resilience Scale-25 (CD-RISC-25, Connor Davidson Resilience Scale-10 (CD-RISC-10, Scale of Protective Factors-24 (SPF-24, and the Life Stressor Checklist Revised (LSC-R. Keywords: Scale of Protective Factors, Resilience Scale, Connor–Davidson Resilience Scale, Emerging adulthood, Confirmatory factor analysis

Managing Risk and Uncertainty in Large-Scale University Research Projects

Science.gov (United States)

Moore, Sharlissa; Shangraw, R. F., Jr.

2011-01-01

Both publicly and privately funded research projects managed by universities are growing in size and scope. Complex, large-scale projects (over $50 million) pose new management challenges and risks for universities. This paper explores the relationship between project success and a variety of factors in large-scale university projects. First, we…

Identification of the Uncertainties for the Calibration of the Partial Safety Factors for Load in Tidal Turbines

Directory of Open Access Journals (Sweden)

Gaizka Zarraonandia Simeón

2016-03-01

Full Text Available Tidal energy is nowadays one of the fastest growing types of marine renewable energy. In particular, Horizontal Axis Tidal Turbines (HATTs are the most advanced designs and the most appropriate for standardization. This paper presents a review of actual design criteria focusing on the identification of the uncertainties that technology developers need to address during the design process. Key environmental parameters like turbine inflow conditions or predictions of extreme values are still grey areas due to the lack of site measurements and the uncertainty in metocean model predictions. A comparison of turbulence intensity characterization using different tools and at different points in time shows the uncertainty in the prediction of this parameter. Numerical models of HATTs are still quite uncertain, often dependent on experience of the people running them. In the reliability-based calibration of partial safety factors, the uncertainties need to be reflected on the limit state formulation. This paper analyses the different types of uncertainties present in the limit state equation. These uncertainties are assessed in terms of stochastic variables in the limit state equation. In some cases, advantage can be taken from the experience from offshore wind and oil and gas industries. Tidal turbines have a mixture of the uncertainties present in both industries with regard to partial safety factor calibration.

Regime-dependent forecast uncertainty of convective precipitation

Energy Technology Data Exchange (ETDEWEB)

Keil, Christian; Craig, George C. [Muenchen Univ. (Germany). Meteorologisches Inst.

2011-04-15

Forecast uncertainty of convective precipitation is influenced by all scales, but in different ways in different meteorological situations. Forecasts of the high resolution ensemble prediction system COSMO-DE-EPS of Deutscher Wetterdienst (DWD) are used to examine the dominant sources of uncertainty of convective precipitation. A validation with radar data using traditional as well as spatial verification measures highlights differences in precipitation forecast performance in differing weather regimes. When the forecast uncertainty can primarily be associated with local, small-scale processes individual members run with the same variation of the physical parameterisation driven by different global models outperform all other ensemble members. In contrast when the precipitation is governed by the large-scale flow all ensemble members perform similarly. Application of the convective adjustment time scale confirms this separation and shows a regime-dependent forecast uncertainty of convective precipitation. (orig.)

The method of belief scales as a means for dealing with uncertainty in tough regulatory decisions.

Energy Technology Data Exchange (ETDEWEB)

Pilch, Martin M.

2005-10-01

Modeling and simulation is playing an increasing role in supporting tough regulatory decisions, which are typically characterized by variabilities and uncertainties in the scenarios, input conditions, failure criteria, model parameters, and even model form. Variability exists when there is a statistically significant database that is fully relevant to the application. Uncertainty, on the other hand, is characterized by some degree of ignorance. A simple algebraic problem was used to illustrate how various risk methodologies address variability and uncertainty in a regulatory context. These traditional risk methodologies include probabilistic methods (including frequensic and Bayesian perspectives) and second-order methods where variabilities and uncertainties are treated separately. Representing uncertainties with (subjective) probability distributions and using probabilistic methods to propagate subjective distributions can lead to results that are not logically consistent with available knowledge and that may not be conservative. The Method of Belief Scales (MBS) is developed as a means to logically aggregate uncertain input information and to propagate that information through the model to a set of results that are scrutable, easily interpretable by the nonexpert, and logically consistent with the available input information. The MBS, particularly in conjunction with sensitivity analyses, has the potential to be more computationally efficient than other risk methodologies. The regulatory language must be tailored to the specific risk methodology if ambiguity and conflict are to be avoided.

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

Directory of Open Access Journals (Sweden)

Antonius Schneider

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

Uncertainty and sensitivity analysis of early exposure results with the MACCS Reactor Accident Consequence Model

International Nuclear Information System (INIS)

Helton, J.C.; Johnson, J.D.; McKay, M.D.; Shiver, A.W.; Sprung, J.L.

1995-01-01

Uncertainty and sensitivity analysis techniques based on Latin hypercube sampling, partial correlation analysis and stepwise regression analysis are used in an investigation with the MACCS model of the early health effects associated with a severe accident at a nuclear power station. The primary purpose of this study is to provide guidance on the variables to be considered in future review work to reduce the uncertainty in the important variables used in the calculation of reactor accident consequences. The effects of 34 imprecisely known input variables on the following reactor accident consequences are studied: number of early fatalities, number of cases of prodromal vomiting, population dose within 10 mi of the reactor, population dose within 1000 mi of the reactor, individual early fatality probability within 1 mi of the reactor, and maximum early fatality distance. When the predicted variables are considered collectively, the following input variables were found to be the dominant contributors to uncertainty: scaling factor for horizontal dispersion, dry deposition velocity, inhalation protection factor for nonevacuees, groundshine shielding factor for nonevacuees, early fatality hazard function alpha value for bone marrow exposure, and scaling factor for vertical dispersion

Scaling law systematics

International Nuclear Information System (INIS)

Pfirsch, D.; Duechs, D.F.

1985-01-01

A number of statistical implications of empirical scaling laws in form of power products obtained by linear regression are analysed. The sensitivity of the error against a change of exponents is described by a sensitivity factor and the uncertainty of predictions by a ''range of predictions factor''. Inner relations in the statistical material is discussed, as well as the consequences of discarding variables.A recipe is given for the computations to be done. The whole is exemplified by considering scaling laws for the electron energy confinement time of ohmically heated tokamak plasmas. (author)

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)

Uncertainty of the calibration factor

International Nuclear Information System (INIS)

1995-01-01

According to present definitions, an error is the difference between a measured value and the ''true'' value. Thus an error has both a numerical value and a sign. In contrast, the uncertainly associated with a measurement is a parameter that characterizes the dispersion of the values ''that could reasonably be attributed to the measurand''. This parameter is normally an estimated standard deviation. An uncertainty, therefore, has no known sign and is usually assumed to be symmetrical. It is a measure of our lack of exact knowledge, after all recognized ''systematic'' effects have been eliminated by applying appropriate corrections. If errors were known exactly, the true value could be determined and there would be no problem left. In reality, errors are estimated in the best possible way and corrections made for them. Therefore, after application of all known corrections, errors need no further consideration (their expectation value being zero) and the only quantities of interest are uncertainties. 3 refs, 2 figs

Uncertainties in climate change scenarios for the Czech Republic

Czech Academy of Sciences Publication Activity Database

Dubrovský, Martin; Nemešová, Ivana; Kalvová, J.

2005-01-01

Roč. 29, - (2005), s. 139-156 ISSN 0936-577X R&D Projects: GA ČR(CZ) GA521/02/0827; GA MŽP(CZ) SM/640/18/03 Institutional research plan: CEZ:AV0Z30420517 Keywords : Climate change scenarios * Uncertainty analysis * Global climate models * Pattern scaling Subject RIV: GC - Agronomy Impact factor: 1.358, year: 2005

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

Science.gov (United States)

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

2016-12-01

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

Sources of uncertainties in modelling black carbon at the global scale

Directory of Open Access Journals (Sweden)

E. Vignati

2010-03-01

Full Text Available Our understanding of the global black carbon (BC cycle is essentially qualitative due to uncertainties in our knowledge of its properties. This work investigates two source of uncertainties in modelling black carbon: those due to the use of different schemes for BC ageing and its removal rate in the global Transport-Chemistry model TM5 and those due to the uncertainties in the definition and quantification of the observations, which propagate through to both the emission inventories, and the measurements used for the model evaluation.

The schemes for the atmospheric processing of black carbon that have been tested with the model are (i a simple approach considering BC as bulk aerosol and a simple treatment of the removal with fixed 70% of in-cloud black carbon concentrations scavenged by clouds and removed when rain is present and (ii a more complete description of microphysical ageing within an aerosol dynamics model, where removal is coupled to the microphysical properties of the aerosol, which results in a global average of 40% in-cloud black carbon that is scavenged in clouds and subsequently removed by rain, thus resulting in a longer atmospheric lifetime. This difference is reflected in comparisons between both sets of modelled results and the measurements. Close to the sources, both anthropogenic and vegetation fire source regions, the model results do not differ significantly, indicating that the emissions are the prevailing mechanism determining the concentrations and the choice of the aerosol scheme does not influence the levels. In more remote areas such as oceanic and polar regions the differences can be orders of magnitude, due to the differences between the two schemes. The more complete description reproduces the seasonal trend of the black carbon observations in those areas, although not always the magnitude of the signal, while the more simplified approach underestimates black carbon concentrations by orders of

Novel patch modelling method for efficient simulation and prediction uncertainty analysis of multi-scale groundwater flow and transport processes

Science.gov (United States)

Sreekanth, J.; Moore, Catherine

2018-04-01

The application of global sensitivity and uncertainty analysis techniques to groundwater models of deep sedimentary basins are typically challenged by large computational burdens combined with associated numerical stability issues. The highly parameterized approaches required for exploring the predictive uncertainty associated with the heterogeneous hydraulic characteristics of multiple aquifers and aquitards in these sedimentary basins exacerbate these issues. A novel Patch Modelling Methodology is proposed for improving the computational feasibility of stochastic modelling analysis of large-scale and complex groundwater models. The method incorporates a nested groundwater modelling framework that enables efficient simulation of groundwater flow and transport across multiple spatial and temporal scales. The method also allows different processes to be simulated within different model scales. Existing nested model methodologies are extended by employing 'joining predictions' for extrapolating prediction-salient information from one model scale to the next. This establishes a feedback mechanism supporting the transfer of information from child models to parent models as well as parent models to child models in a computationally efficient manner. This feedback mechanism is simple and flexible and ensures that while the salient small scale features influencing larger scale prediction are transferred back to the larger scale, this does not require the live coupling of models. This method allows the modelling of multiple groundwater flow and transport processes using separate groundwater models that are built for the appropriate spatial and temporal scales, within a stochastic framework, while also removing the computational burden associated with live model coupling. The utility of the method is demonstrated by application to an actual large scale aquifer injection scheme in Australia.

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

Modeling sugarcane yield with a process-based model from site to continental scale: uncertainties arising from model structure and parameter values

Science.gov (United States)

Valade, A.; Ciais, P.; Vuichard, N.; Viovy, N.; Caubel, A.; Huth, N.; Marin, F.; Martiné, J.-F.

2014-06-01

Agro-land surface models (agro-LSM) have been developed from the integration of specific crop processes into large-scale generic land surface models that allow calculating the spatial distribution and variability of energy, water and carbon fluxes within the soil-vegetation-atmosphere continuum. When developing agro-LSM models, particular attention must be given to the effects of crop phenology and management on the turbulent fluxes exchanged with the atmosphere, and the underlying water and carbon pools. A part of the uncertainty of agro-LSM models is related to their usually large number of parameters. In this study, we quantify the parameter-values uncertainty in the simulation of sugarcane biomass production with the agro-LSM ORCHIDEE-STICS, using a multi-regional approach with data from sites in Australia, La Réunion and Brazil. In ORCHIDEE-STICS, two models are chained: STICS, an agronomy model that calculates phenology and management, and ORCHIDEE, a land surface model that calculates biomass and other ecosystem variables forced by STICS phenology. First, the parameters that dominate the uncertainty of simulated biomass at harvest date are determined through a screening of 67 different parameters of both STICS and ORCHIDEE on a multi-site basis. Secondly, the uncertainty of harvested biomass attributable to those most sensitive parameters is quantified and specifically attributed to either STICS (phenology, management) or to ORCHIDEE (other ecosystem variables including biomass) through distinct Monte Carlo runs. The uncertainty on parameter values is constrained using observations by calibrating the model independently at seven sites. In a third step, a sensitivity analysis is carried out by varying the most sensitive parameters to investigate their effects at continental scale. A Monte Carlo sampling method associated with the calculation of partial ranked correlation coefficients is used to quantify the sensitivity of harvested biomass to input

Intolerance of uncertainty in opioid dependency - Relationship with trait anxiety and impulsivity.

Directory of Open Access Journals (Sweden)

Julia Garami

Full Text Available Intolerance of uncertainty (IU is the tendency to interpret ambiguous situations as threatening and having negative consequences, resulting in feelings of distress and anxiety. IU has been linked to a number of anxiety disorders, and anxiety felt in the face of uncertainty may result in maladaptive behaviors such as impulsive decision making. Although there is strong evidence that anxiety and impulsivity are risk factors for addiction, there is a paucity of research examining the role of IU in this disorder. The rate of opioid addiction, in particular, has been rising steadily in recent years, which necessitates deeper understanding of risk factors in order to develop effective prevention and treatment methods. The current study tested for the first time whether opioid-dependent adults are less tolerant of uncertainty compared to a healthy comparison group. Opioid dependent patients undergoing methadone maintenance therapy (n = 114 and healthy comparisons (n = 69 completed the following scales: Intolerance of Uncertainty Scale, the Barrett Impulsivity Scale, and the State Trait Anxiety Inventory. Analysis revealed that these measures were positively correlated with each other and that opioid-dependent patients had significantly higher IU scores. Regression analysis revealed that anxiety mediated the relationship between IU and impulsivity. Hierarchical moderation regression found an interaction between addiction status and impulsivity on IU scores in that the relationship between these variables was only observed in the patient group. Findings suggest that IU is a feature of addiction but does not necessarily play a unique role. Further research is needed to explore the complex relationship between traits and how they may contribute to the development and maintenance of addiction.

INFLUENCE OF UNCERTAINTY FACTOR ON DEVELOPMENT OF ECONOMIC CRISIS IN RUSSIA

Directory of Open Access Journals (Sweden)

V. A. Rudyakov

2016-01-01

Full Text Available Observing development of the crisis in the Russian economy, it appears that one of the reasons for the decline in the economic development is an increasing degree of uncertainty. The situation affects investment processes and multiplies itself in a growing deficiency of national income. High uncertainty blocks investments in capital-intensive and specific assets and makes economic entities transfer their resources into financial sector and, most often, outside the economy. 49 % of fixed industrial assets depreciation is an indirect proof of this situation. Depreciation of the Russian fixed assets in mining operations is 53.2 %, which includes 22.9 % of fully depreciated assets. At present, when the coefficient of renewal in this branch of ndustry is a little more than 6 and the coefficient of retirement is 0.9, the situation seems to be disastrous. There are a lot of reasons for such situation, especially in the economic sphere. One of them is that within the neoliberal ideology dominating in the economic science with its emphasis on the automatic spontaneous adaptation there is actually no place for development of recommendations for a willful increase in efficiency of adaptation to uncertainty. After all, if we consider that the market leads the entire system to the most optimum equilibrium state, a need for such development simply does not arise. The main objective of this work is to show how the uncertainty factor increases recessionary trends in the Russian economy. Applying Keynesian analysis technique and dividing all savings into investment and hoarding ones, the author proves that Russia has a very low level of adaptive efficiency which reflects long-term ability of the economy to adjust successfully to changing internal and external conditions without any detriment to the implementation of the intended targets and tasks. It is a low level of adaptive efficiency that makes the current crisis so severe. The application of different

Uncertainties in modelling and scaling of critical flows and pump model in TRAC-PF1/MOD1

International Nuclear Information System (INIS)

Rohatgi, U.S.; Yu, Wen-Shi.

1987-01-01

The USNRC has established a Code Scalability, Applicability and Uncertainty (CSAU) evaluation methodology to quantify the uncertainty in the prediction of safety parameters by the best estimate codes. These codes can then be applied to evaluate the Emergency Core Cooling System (ECCS). The TRAC-PF1/MOD1 version was selected as the first code to undergo the CSAU analysis for LBLOCA applications. It was established through this methodology that break flow and pump models are among the top ranked models in the code affecting the peak clad temperature (PCT) prediction for LBLOCA. The break flow model bias or discrepancy and the uncertainty were determined by modelling the test section near the break for 12 Marviken tests. It was observed that the TRAC-PF1/MOD1 code consistently underpredicts the break flow rate and that the prediction improved with increasing pipe length (larger L/D). This is true for both subcooled and two-phase critical flows. A pump model was developed from Westinghouse (1/3 scale) data. The data represent the largest available test pump relevant to Westinghouse PWRs. It was then shown through the analysis of CE and CREARE pump data that larger pumps degrade less and also that pumps degrade less at higher pressures. Since the model developed here is based on the 1/3 scale pump and on low pressure data, it is conservative and will overpredict the degradation when applied to PWRs

Pain anxiety differentially mediates the association of pain intensity with function depending on level of intolerance of uncertainty.

Science.gov (United States)

Fischerauer, Stefan F; Talaei-Khoei, Mojtaba; Vissers, Frederique L; Chen, Neal; Vranceanu, Ana-Maria

2018-02-01

Uncertainty about symptom duration, cause, prognosis and treatment is common in patients who seek medical care, yet individual ability to manage this uncertainty varies. Intolerance of uncertainty is considered an important factor in the etiology and persistence of negative emotions- in particular, depression and anxiety. We explored the contribution of intolerance of uncertainty to anxiety due to pain and physical function in patients seeking care at an orthopedic medical practice. Participants (N = 105, mean age of 51 ± 17, 63% male) were administered PROMIS Physical Function v1.2 Upper Extremity CAT, Numerical Rating Scale (NRS), Pain Anxiety Symptoms Scale-short form (PASS-20), and the Intolerance of Uncertainty Scale-short version (IUS-12). Results showed that the mediating role of pain anxiety is contingent upon the level of intolerance of uncertainty. Specifically, a minimum level of intolerance of uncertainty is required for the development of pain anxiety and its effect on function, and as intolerance of uncertainty rises from low to medium to high levels, the effect of pain on function goes from being independent of the anxiety to being more and more carried by and through anxiety about pain. These findings support the contention that intolerance of uncertainty plays a crucial role in the relationship between pain, pain anxiety, and physical function. Intolerance of uncertainty appears to be a trans-diagnostic target for coping skills training. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.

Application of code scaling applicability and uncertainty methodology to the large break loss of coolant

International Nuclear Information System (INIS)

Young, M.Y.; Bajorek, S.M.; Nissley, M.E.

1998-01-01

In the late 1980s, after completion of an extensive research program, the United States Nuclear Regulatory Commission (USNRC) amended its regulations (10CFR50.46) to allow the use of realistic physical models to analyze the loss of coolant accident (LOCA) in a light water reactors. Prior to this time, the evaluation of this accident was subject to a prescriptive set of rules (appendix K of the regulations) requiring conservative models and assumptions to be applied simultaneously, leading to very pessimistic estimates of the impact of this accident on the reactor core. The rule change therefore promised to provide significant benefits to owners of power reactors, allowing them to increase output. In response to the rule change, a method called code scaling, applicability and uncertainty (CSAU) was developed to apply realistic methods, while properly taking into account data uncertainty, uncertainty in physical modeling and plant variability. The method was claimed to be structured, traceable, and practical, but was met with some criticism when first demonstrated. In 1996, the USNRC approved a methodology, based on CSAU, developed by a group led by Westinghouse. The lessons learned in this application of CSAU will be summarized. Some of the issues raised concerning the validity and completeness of the CSAU methodology will also be discussed. (orig.)

Uncertainty Quantification Analysis of Both Experimental and CFD Simulation Data of a Bench-scale Fluidized Bed Gasifier

Energy Technology Data Exchange (ETDEWEB)

Shahnam, Mehrdad [National Energy Technology Lab. (NETL), Morgantown, WV (United States). Research and Innovation Center, Energy Conversion Engineering Directorate; Gel, Aytekin [ALPEMI Consulting, LLC, Phoeniz, AZ (United States); Subramaniyan, Arun K. [GE Global Research Center, Niskayuna, NY (United States); Musser, Jordan [National Energy Technology Lab. (NETL), Morgantown, WV (United States). Research and Innovation Center, Energy Conversion Engineering Directorate; Dietiker, Jean-Francois [West Virginia Univ. Research Corporation, Morgantown, WV (United States)

2017-10-02

Adequate assessment of the uncertainties in modeling and simulation is becoming an integral part of the simulation based engineering design. The goal of this study is to demonstrate the application of non-intrusive Bayesian uncertainty quantification (UQ) methodology in multiphase (gas-solid) flows with experimental and simulation data, as part of our research efforts to determine the most suited approach for UQ of a bench scale fluidized bed gasifier. UQ analysis was first performed on the available experimental data. Global sensitivity analysis performed as part of the UQ analysis shows that among the three operating factors, steam to oxygen ratio has the most influence on syngas composition in the bench-scale gasifier experiments. An analysis for forward propagation of uncertainties was performed and results show that an increase in steam to oxygen ratio leads to an increase in H2 mole fraction and a decrease in CO mole fraction. These findings are in agreement with the ANOVA analysis performed in the reference experimental study. Another contribution in addition to the UQ analysis is the optimization-based approach to guide to identify next best set of additional experimental samples, should the possibility arise for additional experiments. Hence, the surrogate models constructed as part of the UQ analysis is employed to improve the information gain and make incremental recommendation, should the possibility to add more experiments arise. In the second step, series of simulations were carried out with the open-source computational fluid dynamics software MFiX to reproduce the experimental conditions, where three operating factors, i.e., coal flow rate, coal particle diameter, and steam-to-oxygen ratio, were systematically varied to understand their effect on the syngas composition. Bayesian UQ analysis was performed on the numerical results. As part of Bayesian UQ analysis, a global sensitivity analysis was performed based on the simulation results, which shows

Towards a different attitude to uncertainty

Directory of Open Access Journals (Sweden)

Guy Pe'er

2014-10-01

Full Text Available The ecological literature deals with uncertainty primarily from the perspective of how to reduce it to acceptable levels. However, the current rapid and ubiquitous environmental changes, as well as anticipated rates of change, pose novel conditions and complex dynamics due to which many sources of uncertainty are difficult or even impossible to reduce. These include both uncertainty in knowledge (epistemic uncertainty and societal responses to it. Under these conditions, an increasing number of studies ask how one can deal with uncertainty as it is. Here, we explore the question how to adopt an overall alternative attitude to uncertainty, which accepts or even embraces it. First, we show that seeking to reduce uncertainty may be counterproductive under some circumstances. It may yield overconfidence, ignoring early warning signs, policy- and societal stagnation, or irresponsible behaviour if personal certainty is offered by externalization of environmental costs. We then demonstrate that uncertainty can have positive impacts by driving improvements in knowledge, promoting cautious action, contributing to keeping societies flexible and adaptable, enhancing awareness, support and involvement of the public in nature conservation, and enhancing cooperation and communication. We discuss the risks of employing a certainty paradigm on uncertain knowledge, the potential benefits of adopting an alternative attitude to uncertainty, and the need to implement such an attitude across scales – from adaptive management at the local scale, to the evolving Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES at the global level.

Potential for improved radiation thermometry measurement uncertainty through implementing a primary scale in an industrial laboratory

Science.gov (United States)

Willmott, Jon R.; Lowe, David; Broughton, Mick; White, Ben S.; Machin, Graham

2016-09-01

A primary temperature scale requires realising a unit in terms of its definition. For high temperature radiation thermometry in terms of the International Temperature Scale of 1990 this means extrapolating from the signal measured at the freezing temperature of gold, silver or copper using Planck’s radiation law. The difficulty in doing this means that primary scales above 1000 °C require specialist equipment and careful characterisation in order to achieve the extrapolation with sufficient accuracy. As such, maintenance of the scale at high temperatures is usually only practicable for National Metrology Institutes, and calibration laboratories have to rely on a scale calibrated against transfer standards. At lower temperatures it is practicable for an industrial calibration laboratory to have its own primary temperature scale, which reduces the number of steps between the primary scale and end user. Proposed changes to the SI that will introduce internationally accepted high temperature reference standards might make it practicable to have a primary high temperature scale in a calibration laboratory. In this study such a scale was established by calibrating radiation thermometers directly to high temperature reference standards. The possible reduction in uncertainty to an end user as a result of the reduced calibration chain was evaluated.

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

Uncertainties in the correction factors as the dose polarization and recombination at different energies

International Nuclear Information System (INIS)

Alejo Luque, L.; Rodriguez Romero, R.; Castro Tejero, P.; Fandino Lareo, J. M.

2011-01-01

This paper discusses the measures and uncertainties of the correction factors for dose-polarization (k, 1) and recombination (k,) of different ionization chambers plane-parallel and cylindrical. The values ??have been obtained using photon and electron beams of various energies generated by linear accelerators nominal Varian 21EX CLJNAC Tomotherapy Hi-Art and JI. We study the cases in which you can avoid the application of the factors obtained, according to the criteria proposed

Introduction of risk size in the determination of uncertainty factor UFL in risk assessment

International Nuclear Information System (INIS)

Xue Jinling; Lu Yun; Velasquez, Natalia; Hu Hongying; Yu Ruozhen; Liu Zhengtao; Meng Wei

2012-01-01

The methodology for using uncertainty factors in health risk assessment has been developed for several decades. A default value is usually applied for the uncertainty factor UF L , which is used to extrapolate from LOAEL (lowest observed adverse effect level) to NAEL (no adverse effect level). Here, we have developed a new method that establishes a linear relationship between UF L and the additional risk level at LOAEL based on the dose–response information, which represents a very important factor that should be carefully considered. This linear formula makes it possible to select UF L properly in the additional risk range from 5.3% to 16.2%. Also the results remind us that the default value 10 may not be conservative enough when the additional risk level at LOAEL exceeds 16.2%. Furthermore, this novel method not only provides a flexible UF L instead of the traditional default value, but also can ensure a conservative estimation of the UF L with fewer errors, and avoid the benchmark response selection involved in the benchmark dose method. These advantages can improve the estimation of the extrapolation starting point in the risk assessment. (letter)

The factor structure of the Social Interaction Anxiety Scale and the Social Phobia Scale.

Science.gov (United States)

Heidenreich, Thomas; Schermelleh-Engel, Karin; Schramm, Elisabeth; Hofmann, Stefan G; Stangier, Ulrich

2011-05-01

The Social Interaction Anxiety Scale (SIAS) and the Social Phobia Scale (SPS) are two compendium measures that have become some of the most popular self-report scales of social anxiety. Despite their popularity, it remains unclear whether it is necessary to maintain two separate scales of social anxiety. The primary objective of the present study was to examine the factor analytic structure of both measures to determine the factorial validity of each scale. For this purpose, we administered both scales to 577 patients at the beginning of outpatient treatment. Analyzing both scales simultaneously, a CFA with two correlated factors showed a better fit to the data than a single factor model. An additional EFA with an oblique rotation on all 40 items using the WLSMV estimator further supported the two factor solution. These results suggest that the SIAS and SPS measure similar, but not identical facets of social anxiety. Thus, our findings provide support to retain the SIAS and SPS as two separate scales. Copyright © 2011 Elsevier Ltd. All rights reserved.

Quantifying uncertainties in radar forward models through a comparison between CloudSat and SPartICus reflectivity factors

Science.gov (United States)

Mascio, Jeana; Mace, Gerald G.

2017-02-01

Interpretations of remote sensing measurements collected in sample volumes containing ice-phase hydrometeors are very sensitive to assumptions regarding the distributions of mass with ice crystal dimension, otherwise known as mass-dimensional or m-D relationships. How these microphysical characteristics vary in nature is highly uncertain, resulting in significant uncertainty in algorithms that attempt to derive bulk microphysical properties from remote sensing measurements. This uncertainty extends to radar reflectivity factors forward calculated from model output because the statistics of the actual m-D in nature is not known. To investigate the variability in m-D relationships in cirrus clouds, reflectivity factors measured by CloudSat are combined with particle size distributions (PSDs) collected by coincident in situ aircraft by using an optimal estimation-based (OE) retrieval of the m-D power law. The PSDs were collected by 12 flights of the Stratton Park Engineering Company Learjet during the Small Particles in Cirrus campaign. We find that no specific habit emerges as preferred, and instead, we find that the microphysical characteristics of ice crystal populations tend to be distributed over a continuum-defying simple categorization. With the uncertainties derived from the OE algorithm, the uncertainties in forward-modeled backscatter cross section and, in turn, radar reflectivity is calculated by using a bootstrapping technique, allowing us to infer the uncertainties in forward-modeled radar reflectivity that would be appropriately applied to remote sensing simulator algorithms.

Evaluation of measurement uncertainty for purity of a monoterpenic acid by small-scale coulometry

Science.gov (United States)

Norte, L. C.; de Carvalho, E. M.; Tappin, M. R. R.; Borges, P. P.

2018-03-01

Purity of the perylic acid (HPe) which is a monoterpenic acid from natural product (NP) with anti-inflammatory and anticancer properties was analyzed by small-scale coulometry (SSC), due to the low availability of HPe on the pharmaceutic market and its high cost. This work aims to present the evaluation of the measurements uncertainty from the purity of HPe by using SSC. Coulometric mean of purity obtained from 5 replicates resulted in 94.23% ± 0.88% (k = 2.06, for an approximately 95% confidence level). These studies aim in the future to develop the production of certified reference materials from NPs.

Uncertainty analysis in seismic tomography

Science.gov (United States)

Owoc, Bartosz; Majdański, Mariusz

2017-04-01

Velocity field from seismic travel time tomography depends on several factors like regularization, inversion path, model parameterization etc. The result also strongly depends on an initial velocity model and precision of travel times picking. In this research we test dependence on starting model in layered tomography and compare it with effect of picking precision. Moreover, in our analysis for manual travel times picking the uncertainty distribution is asymmetric. This effect is shifting the results toward faster velocities. For calculation we are using JIVE3D travel time tomographic code. We used data from geo-engineering and industrial scale investigations, which were collected by our team from IG PAS.

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

DEFF Research Database (Denmark)

Hukkerikar, Amol; Sarup, Bent; Abildskov, Jens

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

Uncertainties in coupled thermal-hydrological processes associated with the drift scale test at Yucca Mountain, Nevada

International Nuclear Information System (INIS)

Mukhopadhyay, Sumitra; Tsang, Y.W.

2002-01-01

Understanding thermally driven coupled hydrological, mechanical, and chemical processes in unsaturated fractured tuff is essential for evaluating the performance of the potential radioactive waste repository at Yucca Mountain, Nevada. The Drift Scale Test (DST), intended for acquiring such an understanding of these processes, has generated a huge volume of temperature and moisture redistribution data. Sophisticated thermal hydrological (TH) conceptual models have yielded a good fit between simulation results and those measured data. However, some uncertainties in understanding the TH processes associated with the DST still exist. This paper evaluates these uncertainties and provides quantitative estimates of the range of these uncertainties. Of particular interest for the DST are the uncertainties resulting from the unmonitored loss of vapor through an open bulkhead of the test. There was concern that the outcome from the test might have been significantly altered by these losses. Using alternative conceptual models, we illustrate that predicted mean temperatures from the DST are within 1 degree C of the measured mean temperatures through the first two years of heating. The simulated spatial and temporal evolution of drying and condensation fronts is found to be qualitatively consistent with measured saturation data. Energy and mass balance computation shows that no more than 13 percent of the input energy is lost because of vapor leaving the test domain through the bulkhead. The change in average saturation in fractures is also relatively small. For a hypothetical situation in which no vapor is allowed to exit through the bulkhead, the simulated average fracture saturation is not qualitatively different enough to be discerned by measured moisture redistribution data. This leads us to conclude that the DST, despite the uncertainties associated with open field testing, has provided an excellent understanding of the TH processes

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

Science.gov (United States)

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

2012-08-01

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

Reusable launch vehicle model uncertainties impact analysis

Science.gov (United States)

Chen, Jiaye; Mu, Rongjun; Zhang, Xin; Deng, Yanpeng

2018-03-01

Reusable launch vehicle(RLV) has the typical characteristics of complex aerodynamic shape and propulsion system coupling, and the flight environment is highly complicated and intensely changeable. So its model has large uncertainty, which makes the nominal system quite different from the real system. Therefore, studying the influences caused by the uncertainties on the stability of the control system is of great significance for the controller design. In order to improve the performance of RLV, this paper proposes the approach of analyzing the influence of the model uncertainties. According to the typical RLV, the coupling dynamic and kinematics models are built. Then different factors that cause uncertainties during building the model are analyzed and summed up. After that, the model uncertainties are expressed according to the additive uncertainty model. Choosing the uncertainties matrix's maximum singular values as the boundary model, and selecting the uncertainties matrix's norm to show t how much the uncertainty factors influence is on the stability of the control system . The simulation results illustrate that the inertial factors have the largest influence on the stability of the system, and it is necessary and important to take the model uncertainties into consideration before the designing the controller of this kind of aircraft( like RLV, etc).

Failure probability under parameter uncertainty.

Science.gov (United States)

Gerrard, R; Tsanakas, A

2011-05-01

In many problems of risk analysis, failure is equivalent to the event of a random risk factor exceeding a given threshold. Failure probabilities can be controlled if a decisionmaker is able to set the threshold at an appropriate level. This abstract situation applies, for example, to environmental risks with infrastructure controls; to supply chain risks with inventory controls; and to insurance solvency risks with capital controls. However, uncertainty around the distribution of the risk factor implies that parameter error will be present and the measures taken to control failure probabilities may not be effective. We show that parameter uncertainty increases the probability (understood as expected frequency) of failures. For a large class of loss distributions, arising from increasing transformations of location-scale families (including the log-normal, Weibull, and Pareto distributions), the article shows that failure probabilities can be exactly calculated, as they are independent of the true (but unknown) parameters. Hence it is possible to obtain an explicit measure of the effect of parameter uncertainty on failure probability. Failure probability can be controlled in two different ways: (1) by reducing the nominal required failure probability, depending on the size of the available data set, and (2) by modifying of the distribution itself that is used to calculate the risk control. Approach (1) corresponds to a frequentist/regulatory view of probability, while approach (2) is consistent with a Bayesian/personalistic view. We furthermore show that the two approaches are consistent in achieving the required failure probability. Finally, we briefly discuss the effects of data pooling and its systemic risk implications. © 2010 Society for Risk Analysis.

Uncertainty of Doppler reactivity worth due to uncertainties of JENDL-3.2 resonance parameters

Energy Technology Data Exchange (ETDEWEB)

Zukeran, Atsushi [Hitachi Ltd., Hitachi, Ibaraki (Japan). Power and Industrial System R and D Div.; Hanaki, Hiroshi; Nakagawa, Tuneo; Shibata, Keiichi; Ishikawa, Makoto

1998-03-01

Analytical formula of Resonance Self-shielding Factor (f-factor) is derived from the resonance integral (J-function) based on NR approximation and the analytical expression for Doppler reactivity worth ({rho}) is also obtained by using the result. Uncertainties of the f-factor and Doppler reactivity worth are evaluated on the basis of sensitivity coefficients to the resonance parameters. The uncertainty of the Doppler reactivity worth at 487{sup 0}K is about 4 % for the PNC Large Fast Breeder Reactor. (author)

Low energy peripheral scaling in nucleon-nucleon scattering and uncertainty quantification

Science.gov (United States)

Ruiz Simo, I.; Amaro, J. E.; Ruiz Arriola, E.; Navarro Pérez, R.

2018-03-01

We analyze the peripheral structure of the nucleon-nucleon interaction for LAB energies below 350 MeV. To this end we transform the scattering matrix into the impact parameter representation by analyzing the scaled phase shifts (L + 1/2) δ JLS (p) and the scaled mixing parameters (L + 1/2)ɛ JLS (p) in terms of the impact parameter b = (L + 1/2)/p. According to the eikonal approximation, at large angular momentum L these functions should become an universal function of b, independent on L. This allows to discuss in a rather transparent way the role of statistical and systematic uncertainties in the different long range components of the two-body potential. Implications for peripheral waves obtained in chiral perturbation theory interactions to fifth order (N5LO) or from the large body of NN data considered in the SAID partial wave analysis are also drawn from comparing them with other phenomenological high-quality interactions, constructed to fit scattering data as well. We find that both N5LO and SAID peripheral waves disagree more than 5σ with the Granada-2013 statistical analysis, more than 2σ with the 6 statistically equivalent potentials fitting the Granada-2013 database and about 1σ with the historical set of 13 high-quality potentials developed since the 1993 Nijmegen analysis.

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

Directory of Open Access Journals (Sweden)

S. Lari

2012-11-01

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

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

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

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

Evaluation of uncertainties in MUF for a LWR fuel fabrication plant. Pt.2 - Pt.4

International Nuclear Information System (INIS)

Mennerdahl, D.

1984-09-01

MUF (Material Unaccounted For) is a parameter defined as the estimated loss of materials during a certain period of time. A suitable method for uncertainty and bias estimations has been developed. The method was specifically adjusted for a facility like the ASEA-ATOM fuel fabrication plant. Operations that are expected to contribute to the uncertainties have been compiled. Information that is required for the application of the developed method is described. Proposals for simplification of the required information without losing the accuracy are suggested. ASEA-ATOM had earlier determined uncertainty data for the scales that are used for nuclear materials. The statistical uncertainties included random errors, short-term and long-term systematic errors. Information for the determination of biases was also determined (constants and formulas). The method proposed by ASEA-ATOM for the determination of uncertainties due to the scales is compatible with the method proposed in this report. For other operations than weighing, the information from ASEA-ATOM is limited. Such operations are completely dominating the total uncertainty in MUF. Examples of calculations of uncertainties and bias are given for uranium oxide powders in large containers. Examples emphasize the differences between various statistical errors (random and systematic errors) and biases (known errors). The importance of correlations between different items in the inventories is explained. A specific correlation of great importance is the use of nominal factors (uranium concentration). A portable personal computer can be used to determine uncertainties in MUF. (author)

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

Science.gov (United States)

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

Sensitivity and uncertainty analysis for a field-scale P loss model

Science.gov (United States)

Models are often used to predict phosphorus (P) loss from agricultural fields. While it is commonly recognized that there are inherent uncertainties with model predictions, limited studies have addressed model prediction uncertainty. In this study we assess the effect of model input error on predict...

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, joint uncertainty, and the quantum uncertainty principle

International Nuclear Information System (INIS)

Narasimhachar, Varun; Poostindouz, Alireza; Gour, Gilad

2016-01-01

Historically, the element of uncertainty in quantum mechanics has been expressed through mathematical identities called uncertainty relations, a great many of which continue to be discovered. These relations use diverse measures to quantify uncertainty (and joint uncertainty). In this paper we use operational information-theoretic principles to identify the common essence of all such measures, thereby defining measure-independent notions of uncertainty and joint uncertainty. We find that most existing entropic uncertainty relations use measures of joint uncertainty that yield themselves to a small class of operational interpretations. Our notion relaxes this restriction, revealing previously unexplored joint uncertainty measures. To illustrate the utility of our formalism, we derive an uncertainty relation based on one such new measure. We also use our formalism to gain insight into the conditions under which measure-independent uncertainty relations can be found. (paper)

Benchmarking observational uncertainties for hydrology (Invited)

Science.gov (United States)

McMillan, H. K.; Krueger, T.; Freer, J. E.; Westerberg, I.

2013-12-01

There is a pressing need for authoritative and concise information on the expected error distributions and magnitudes in hydrological data, to understand its information content. Many studies have discussed how to incorporate uncertainty information into model calibration and implementation, and shown how model results can be biased if uncertainty is not appropriately characterised. However, it is not always possible (for example due to financial or time constraints) to make detailed studies of uncertainty for every research study. Instead, we propose that the hydrological community could benefit greatly from sharing information on likely uncertainty characteristics and the main factors that control the resulting magnitude. In this presentation, we review the current knowledge of uncertainty for a number of key hydrological variables: rainfall, flow and water quality (suspended solids, nitrogen, phosphorus). We collated information on the specifics of the data measurement (data type, temporal and spatial resolution), error characteristics measured (e.g. standard error, confidence bounds) and error magnitude. Our results were primarily split by data type. Rainfall uncertainty was controlled most strongly by spatial scale, flow uncertainty was controlled by flow state (low, high) and gauging method. Water quality presented a more complex picture with many component errors. For all variables, it was easy to find examples where relative error magnitude exceeded 40%. We discuss some of the recent developments in hydrology which increase the need for guidance on typical error magnitudes, in particular when doing comparative/regionalisation and multi-objective analysis. Increased sharing of data, comparisons between multiple catchments, and storage in national/international databases can mean that data-users are far removed from data collection, but require good uncertainty information to reduce bias in comparisons or catchment regionalisation studies. Recently it has

Sources of uncertainties in modelling black carbon at the global scale

NARCIS (Netherlands)

Vignati, E.; Karl, M.; Krol, M.C.; Wilson, J.; Stier, P.; Cavalli, F.

2010-01-01

Our understanding of the global black carbon (BC) cycle is essentially qualitative due to uncertainties in our knowledge of its properties. This work investigates two source of uncertainties in modelling black carbon: those due to the use of different schemes for BC ageing and its removal rate in

Quantifying and managing uncertainty in operational modal analysis

Science.gov (United States)

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

2018-03-01

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

Large-Scale Distributed Bayesian Matrix Factorization using Stochastic Gradient MCMC

NARCIS (Netherlands)

Ahn, S.; Korattikara, A.; Liu, N.; Rajan, S.; Welling, M.

2015-01-01

Despite having various attractive qualities such as high prediction accuracy and the ability to quantify uncertainty and avoid ovrfitting, Bayesian Matrix Factorization has not been widely adopted because of the prohibitive cost of inference. In this paper, we propose a scalable distributed Bayesian

Account for uncertainties of control measurements in the assessment of design margin factors

International Nuclear Information System (INIS)

Dementiev, V. G.; Sidorenko, V. D.; Shishkov, L. K.

2011-01-01

The paper discusses the feasibility of accounting for uncertainties of control measurements in estimation of design margin factors. The feasibility is also taken into consideration proceeding from the fact how much the processed measured data were corrected by a priori calculated data of measurable parameters. The possibility and feasibility of such data correction is demonstrated by the authors with the help of Bayes theorem famous in mathematical statistics. (Authors)

Uncertainty quantification theory, implementation, and applications

CERN Document Server

Smith, Ralph C

2014-01-01

The field of uncertainty quantification is evolving rapidly because of increasing emphasis on models that require quantified uncertainties for large-scale applications, novel algorithm development, and new computational architectures that facilitate implementation of these algorithms. Uncertainty Quantification: Theory, Implementation, and Applications provides readers with the basic concepts, theory, and algorithms necessary to quantify input and response uncertainties for simulation models arising in a broad range of disciplines. The book begins with a detailed discussion of applications where uncertainty quantification is critical for both scientific understanding and policy. It then covers concepts from probability and statistics, parameter selection techniques, frequentist and Bayesian model calibration, propagation of uncertainties, quantification of model discrepancy, surrogate model construction, and local and global sensitivity analysis. The author maintains a complementary web page where readers ca...

Uncertainties in extreme precipitation under climate change conditions

DEFF Research Database (Denmark)

Sunyer Pinya, Maria Antonia

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

Large-scale determinants of diversity across Spanish forest habitats: accounting for model uncertainty in compositional and structural indicators

Energy Technology Data Exchange (ETDEWEB)

Martin-Quller, E.; Torras, O.; Alberdi, I.; Solana, J.; Saura, S.

2011-07-01

An integral understanding of forest biodiversity requires the exploration of the many aspects it comprises and of the numerous potential determinants of their distribution. The landscape ecological approach provides a necessary complement to conventional local studies that focus on individual plots or forest ownerships. However, most previous landscape studies used equally-sized cells as units of analysis to identify the factors affecting forest biodiversity distribution. Stratification of the analysis by habitats with a relatively homogeneous forest composition might be more adequate to capture the underlying patterns associated to the formation and development of a particular ensemble of interacting forest species. Here we used a landscape perspective in order to improve our understanding on the influence of large-scale explanatory factors on forest biodiversity indicators in Spanish habitats, covering a wide latitudinal and attitudinal range. We considered six forest biodiversity indicators estimated from more than 30,000 field plots in the Spanish national forest inventory, distributed in 213 forest habitats over 16 Spanish provinces. We explored biodiversity response to various environmental (climate and topography) and landscape configuration (fragmentation and shape complexity) variables through multiple linear regression models (built and assessed through the Akaike Information Criterion). In particular, we took into account the inherent model uncertainty when dealing with a complex and large set of variables, and considered different plausible models and their probability of being the best candidate for the observed data. Our results showed that compositional indicators (species richness and diversity) were mostly explained by environmental factors. Models for structural indicators (standing deadwood and stand complexity) had the worst fits and selection uncertainties, but did show significant associations with some configuration metrics. In general

Application of bias factor method with use of virtual experimental value to prediction uncertainty reduction in void reactivity worth of breeding light water reactor

International Nuclear Information System (INIS)

Kugo, Teruhiko; Mori, Takamasa; Kojima, Kensuke; Takeda, Toshikazu

2007-01-01

We have carried out the critical experiments for the MOX fueled tight lattice LWR cores using FCA facility and constructed the XXII-1 series cores. Utilizing the critical experiments carried out at FCA, we have evaluated the reduction of prediction uncertainty in the coolant void reactivity worth of the breeding LWR core based on the bias factor method with focusing on the prediction uncertainty due to cross section errors. In the present study, we have introduced a concept of a virtual experimental value into the conventional bias factor method to overcome a problem caused by the conventional bias factor method in which the prediction uncertainty increases in the case that the experimental core has the opposite reactivity worth and the consequent opposite sensitivity coefficients to the real core. To extend the applicability of the bias factor method, we have adopted an exponentiated experimental value as the virtual experimental value and formulated the prediction uncertainty reduction by the use of the bias factor method extended by the concept of the virtual experimental value. From the numerical evaluation, it has been shown that the prediction uncertainty due to cross section errors has been reduced by the use of the concept of the virtual experimental value. It is concluded that the introduction of virtual experimental value can effectively utilize experimental data and extend applicability of the bias factor method. (author)

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

Sensitivity and uncertainty analysis

CERN Document Server

Cacuci, Dan G; Navon, Ionel Michael

2005-01-01

As computer-assisted modeling and analysis of physical processes have continued to grow and diversify, sensitivity and uncertainty analyses have become indispensable scientific tools. Sensitivity and Uncertainty Analysis. Volume I: Theory focused on the mathematical underpinnings of two important methods for such analyses: the Adjoint Sensitivity Analysis Procedure and the Global Adjoint Sensitivity Analysis Procedure. This volume concentrates on the practical aspects of performing these analyses for large-scale systems. The applications addressed include two-phase flow problems, a radiative c

Determining the minimal length scale of the generalized uncertainty principle from the entropy-area relationship

International Nuclear Information System (INIS)

Kim, Wontae; Oh, John J.

2008-01-01

We derive the formula of the black hole entropy with a minimal length of the Planck size by counting quantum modes of scalar fields in the vicinity of the black hole horizon, taking into account the generalized uncertainty principle (GUP). This formula is applied to some intriguing examples of black holes - the Schwarzschild black hole, the Reissner-Nordstrom black hole, and the magnetically charged dilatonic black hole. As a result, it is shown that the GUP parameter can be determined by imposing the black hole entropy-area relationship, which has a Planck length scale and a universal form within the near-horizon expansion

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

Science.gov (United States)

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

1996-06-01

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

Uncertainty in projected climate change arising from uncertain fossil-fuel emission factors

Science.gov (United States)

Quilcaille, Y.; Gasser, T.; Ciais, P.; Lecocq, F.; Janssens-Maenhout, G.; Mohr, S.

2018-04-01

Emission inventories are widely used by the climate community, but their uncertainties are rarely accounted for. In this study, we evaluate the uncertainty in projected climate change induced by uncertainties in fossil-fuel emissions, accounting for non-CO2 species co-emitted with the combustion of fossil-fuels and their use in industrial processes. Using consistent historical reconstructions and three contrasted future projections of fossil-fuel extraction from Mohr et al we calculate CO2 emissions and their uncertainties stemming from estimates of fuel carbon content, net calorific value and oxidation fraction. Our historical reconstructions of fossil-fuel CO2 emissions are consistent with other inventories in terms of average and range. The uncertainties sum up to a ±15% relative uncertainty in cumulative CO2 emissions by 2300. Uncertainties in the emissions of non-CO2 species associated with the use of fossil fuels are estimated using co-emission ratios varying with time. Using these inputs, we use the compact Earth system model OSCAR v2.2 and a Monte Carlo setup, in order to attribute the uncertainty in projected global surface temperature change (ΔT) to three sources of uncertainty, namely on the Earth system’s response, on fossil-fuel CO2 emission and on non-CO2 co-emissions. Under the three future fuel extraction scenarios, we simulate the median ΔT to be 1.9, 2.7 or 4.0 °C in 2300, with an associated 90% confidence interval of about 65%, 52% and 42%. We show that virtually all of the total uncertainty is attributable to the uncertainty in the future Earth system’s response to the anthropogenic perturbation. We conclude that the uncertainty in emission estimates can be neglected for global temperature projections in the face of the large uncertainty in the Earth system response to the forcing of emissions. We show that this result does not hold for all variables of the climate system, such as the atmospheric partial pressure of CO2 and the

Dither Gyro Scale Factor Calibration: GOES-16 Flight Experience

Science.gov (United States)

Reth, Alan D.; Freesland, Douglas C.; Krimchansky, Alexander

2018-01-01

This poster is a sequel to a paper presented at the 34th Annual AAS Guidance and Control Conference in 2011, which first introduced dither-based calibration of gyro scale factors. The dither approach uses very small excitations, avoiding the need to take instruments offline during gyro scale factor calibration. In 2017, the dither calibration technique was successfully used to estimate gyro scale factors on the GOES-16 satellite. On-orbit dither calibration results were compared to more traditional methods using large angle spacecraft slews about each gyro axis, requiring interruption of science. The results demonstrate that the dither technique can estimate gyro scale factors to better than 2000 ppm during normal science observations.

Account of the uncertainty factor in forecasting nuclear power development

International Nuclear Information System (INIS)

Chernavskij, S.Ya.

1979-01-01

Minimization of total discounted costs for linear constraints is commonly used in forecasting nuclear energy growth. This approach is considered inadequate due to the uncertainty of exogenous variables of the model. A method of forecasting that takes into account the presence of uncertainty is elaborated. An example that demonstrates the expediency of the method and its advantage over the conventional approximation method used for taking uncertainty into account is given. In the framework of the example, the optimal strategy for nuclear energy growth over period of 500 years is determined

A survey of resilience, burnout, and tolerance of uncertainty in Australian general practice registrars

Directory of Open Access Journals (Sweden)

Cooke Georga PE

2013-01-01

Full Text Available Abstract Background Burnout and intolerance of uncertainty have been linked to low job satisfaction and lower quality patient care. While resilience is related to these concepts, no study has examined these three concepts in a cohort of doctors. The objective of this study was to measure resilience, burnout, compassion satisfaction, personal meaning in patient care and intolerance of uncertainty in Australian general practice (GP registrars. Methods We conducted a paper-based cross-sectional survey of GP registrars in Australia from June to July 2010, recruited from a newsletter item or registrar education events. Survey measures included the Resilience Scale-14, a single-item scale for burnout, Professional Quality of Life (ProQOL scale, Personal Meaning in Patient Care scale, Intolerance of Uncertainty-12 scale, and Physician Response to Uncertainty scale. Results 128 GP registrars responded (response rate 90%. Fourteen percent of registrars were found to be at risk of burnout using the single-item scale for burnout, but none met the criteria for burnout using the ProQOL scale. Secondary traumatic stress, general intolerance of uncertainty, anxiety due to clinical uncertainty and reluctance to disclose uncertainty to patients were associated with being at higher risk of burnout, but sex, age, practice location, training duration, years since graduation, and reluctance to disclose uncertainty to physicians were not. Only ten percent of registrars had high resilience scores. Resilience was positively associated with compassion satisfaction and personal meaning in patient care. Resilience was negatively associated with burnout, secondary traumatic stress, inhibitory anxiety, general intolerance to uncertainty, concern about bad outcomes and reluctance to disclose uncertainty to patients. Conclusions GP registrars in this survey showed a lower level of burnout than in other recent surveys of the broader junior doctor population in both Australia

Generalized uncertainty principle as a consequence of the effective field theory

Energy Technology Data Exchange (ETDEWEB)

Faizal, Mir, E-mail: mirfaizalmir@gmail.com [Irving K. Barber School of Arts and Sciences, University of British Columbia – Okanagan, Kelowna, British Columbia V1V 1V7 (Canada); Department of Physics and Astronomy, University of Lethbridge, Lethbridge, Alberta T1K 3M4 (Canada); Ali, Ahmed Farag, E-mail: ahmed.ali@fsc.bu.edu.eg [Department of Physics, Faculty of Science, Benha University, Benha, 13518 (Egypt); Netherlands Institute for Advanced Study, Korte Spinhuissteeg 3, 1012 CG Amsterdam (Netherlands); Nassar, Ali, E-mail: anassar@zewailcity.edu.eg [Department of Physics, Zewail City of Science and Technology, 12588, Giza (Egypt)

2017-02-10

We will demonstrate that the generalized uncertainty principle exists because of the derivative expansion in the effective field theories. This is because in the framework of the effective field theories, the minimum measurable length scale has to be integrated away to obtain the low energy effective action. We will analyze the deformation of a massive free scalar field theory by the generalized uncertainty principle, and demonstrate that the minimum measurable length scale corresponds to a second more massive scale in the theory, which has been integrated away. We will also analyze CFT operators dual to this deformed scalar field theory, and observe that scaling of the new CFT operators indicates that they are dual to this more massive scale in the theory. We will use holographic renormalization to explicitly calculate the renormalized boundary action with counter terms for this scalar field theory deformed by generalized uncertainty principle, and show that the generalized uncertainty principle contributes to the matter conformal anomaly.

Generalized uncertainty principle as a consequence of the effective field theory

Directory of Open Access Journals (Sweden)

Mir Faizal

2017-02-01

Full Text Available We will demonstrate that the generalized uncertainty principle exists because of the derivative expansion in the effective field theories. This is because in the framework of the effective field theories, the minimum measurable length scale has to be integrated away to obtain the low energy effective action. We will analyze the deformation of a massive free scalar field theory by the generalized uncertainty principle, and demonstrate that the minimum measurable length scale corresponds to a second more massive scale in the theory, which has been integrated away. We will also analyze CFT operators dual to this deformed scalar field theory, and observe that scaling of the new CFT operators indicates that they are dual to this more massive scale in the theory. We will use holographic renormalization to explicitly calculate the renormalized boundary action with counter terms for this scalar field theory deformed by generalized uncertainty principle, and show that the generalized uncertainty principle contributes to the matter conformal anomaly.

Nuclear data sensitivity/uncertainty analysis for XT-ADS

International Nuclear Information System (INIS)

Sugawara, Takanori; Sarotto, Massimo; Stankovskiy, Alexey; Van den Eynde, Gert

2011-01-01

Highlights: → The sensitivity and uncertainty analyses were performed to comprehend the reliability of the XT-ADS neutronic design. → The uncertainties deduced from the covariance data for the XT-ADS criticality were 0.94%, 1.9% and 1.1% by the SCALE 44-group, TENDL-2009 and JENDL-3.3 data, respectively. → When the target accuracy of 0.3%Δk for the criticality was considered, the uncertainties did not satisfy it. → To achieve this accuracy, the uncertainties should be improved by experiments under an adequate condition. - Abstract: The XT-ADS, an accelerator-driven system for an experimental demonstration, has been investigated in the framework of IP EUROTRANS FP6 project. In this study, the sensitivity and uncertainty analyses were performed to comprehend the reliability of the XT-ADS neutronic design. For the sensitivity analysis, it was found that the sensitivity coefficients were significantly different by changing the geometry models and calculation codes. For the uncertainty analysis, it was confirmed that the uncertainties deduced from the covariance data varied significantly by changing them. The uncertainties deduced from the covariance data for the XT-ADS criticality were 0.94%, 1.9% and 1.1% by the SCALE 44-group, TENDL-2009 and JENDL-3.3 data, respectively. When the target accuracy of 0.3%Δk for the criticality was considered, the uncertainties did not satisfy it. To achieve this accuracy, the uncertainties should be improved by experiments under an adequate condition.

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)

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

Science.gov (United States)

Jacquin, A. P.

2012-04-01

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

More Thoughts on AG-SG Comparisons and SG Scale Factor Determinations

Science.gov (United States)

Crossley, David; Calvo, Marta; Rosat, Severine; Hinderer, Jacques

2018-03-01

We revisit a number of details that arise when doing joint AG-SG (absolute gravimeter-superconducting gravimeter) calibrations, focusing on the scale factor determination and the AG mean value that derives from the offset. When fitting SG data to AG data, the choice of which time span to use for the SG data can make a difference, as well as the inclusion of a trend that might be present in the fitting. The SG time delay has only a small effect. We review a number of options discussed recently in the literature on whether drops or sets provide the most accurate scale factor, and how to reject drops and sets to get the most consistent result. Two effects are clearly indicated by our tests, one being to smooth the raw SG 1 s (or similar sampling interval) data for times that coincide with AG drops, the other being a second pass in processing to reject residual outliers after the initial fit. Although drops can usefully provide smaller SG calibration errors compared to using set data, set values are more robust to data problems but one has to use the standard error to avoid large uncertainties. When combining scale factor determinations for the same SG at the same station, the expected gradual reduction of the error with each new experiment is consistent with the method of conflation. This is valid even when the SG data acquisition system is changed, or different AG's are used. We also find a relationship between the AG mean values obtained from SG to AG fits with the traditional short-term AG (`site') measurements usually done with shorter datasets. This involves different zero levels and corrections in the AG versus SG processing. Without using the Micro-g FG5 software it is possible to use the SG-derived corrections for tides, barometric pressure, and polar motion to convert an AG-SG calibration experiment into a site measurement (and vice versa). Finally, we provide a simple method for AG users who do not have the FG5-software to find an internal FG5 parameter that

More Thoughts on AG-SG Comparisons and SG Scale Factor Determinations

Science.gov (United States)

Crossley, David; Calvo, Marta; Rosat, Severine; Hinderer, Jacques

2018-05-01

We revisit a number of details that arise when doing joint AG-SG (absolute gravimeter-superconducting gravimeter) calibrations, focusing on the scale factor determination and the AG mean value that derives from the offset. When fitting SG data to AG data, the choice of which time span to use for the SG data can make a difference, as well as the inclusion of a trend that might be present in the fitting. The SG time delay has only a small effect. We review a number of options discussed recently in the literature on whether drops or sets provide the most accurate scale factor, and how to reject drops and sets to get the most consistent result. Two effects are clearly indicated by our tests, one being to smooth the raw SG 1 s (or similar sampling interval) data for times that coincide with AG drops, the other being a second pass in processing to reject residual outliers after the initial fit. Although drops can usefully provide smaller SG calibration errors compared to using set data, set values are more robust to data problems but one has to use the standard error to avoid large uncertainties. When combining scale factor determinations for the same SG at the same station, the expected gradual reduction of the error with each new experiment is consistent with the method of conflation. This is valid even when the SG data acquisition system is changed, or different AG's are used. We also find a relationship between the AG mean values obtained from SG to AG fits with the traditional short-term AG (`site') measurements usually done with shorter datasets. This involves different zero levels and corrections in the AG versus SG processing. Without using the Micro-g FG5 software it is possible to use the SG-derived corrections for tides, barometric pressure, and polar motion to convert an AG-SG calibration experiment into a site measurement (and vice versa). Finally, we provide a simple method for AG users who do not have the FG5-software to find an internal FG5 parameter that

Use of an uncertainty analysis for genome-scale models as a prediction tool for microbial growth processes in subsurface environments.

Science.gov (United States)

Klier, Christine

2012-03-06

The integration of genome-scale, constraint-based models of microbial cell function into simulations of contaminant transport and fate in complex groundwater systems is a promising approach to help characterize the metabolic activities of microorganisms in natural environments. In constraint-based modeling, the specific uptake flux rates of external metabolites are usually determined by Michaelis-Menten kinetic theory. However, extensive data sets based on experimentally measured values are not always available. In this study, a genome-scale model of Pseudomonas putida was used to study the key issue of uncertainty arising from the parametrization of the influx of two growth-limiting substrates: oxygen and toluene. The results showed that simulated growth rates are highly sensitive to substrate affinity constants and that uncertainties in specific substrate uptake rates have a significant influence on the variability of simulated microbial growth. Michaelis-Menten kinetic theory does not, therefore, seem to be appropriate for descriptions of substrate uptake processes in the genome-scale model of P. putida. Microbial growth rates of P. putida in subsurface environments can only be accurately predicted if the processes of complex substrate transport and microbial uptake regulation are sufficiently understood in natural environments and if data-driven uptake flux constraints can be applied.

Evaluation of uncertainties in irradiated hardware characterization: Final report, September 30, 1986-March 31, 1987

International Nuclear Information System (INIS)

Bedore, N.; Levin, A.; Tuite, P.

1987-10-01

Waste Management Group, Inc. has evaluated the techniques used by industry to characterize and classify irradiated hardware components for disposal. This report describes the current practices used to characterize the radionuclide content of hardware components, identifies the uncertainties associated with the techniques and practices considered, and recommends areas for improvement which could reduce uncertainty. Industry uses two different characterization methods. The first uses a combination of gamma scanning, direct sampling, underwater radiation profiling and radiochemical analysis to determine radionuclide content, while the second uses a form of activation analysis in conjunction with underwater radiation profiling. Both methods employ the determination of Cobalt 60 content, and the determination of scaling factors for hard-to-detect Part 61 radionuclides. The accurate determination of Cobalt-60 is critical since the Part 61 activation product radionuclides which affect Part 61 classification are scaled from Cobalt-60. Current uncertainties in Cobalt-60 determination can be reduced by improving underwater radiation profiling equipment and techniques. The calculational techniques used for activation analysis can also be refined to reduce the uncertainties with Cobalt-60 determination. 33 refs., 11 figs., 10 tabs

Final Technical Report: Quantification of Uncertainty in Extreme Scale Computations (QUEST)

Energy Technology Data Exchange (ETDEWEB)

Knio, Omar M. [Duke Univ., Durham, NC (United States). Dept. of Mechanical Engineering and Materials Science

2017-06-06

QUEST is a SciDAC Institute comprising Sandia National Laboratories, Los Alamos National Laboratory, University of Southern California, Massachusetts Institute of Technology, University of Texas at Austin, and Duke University. The mission of QUEST is to: (1) develop a broad class of uncertainty quantification (UQ) methods/tools, and (2) provide UQ expertise and software to other SciDAC projects, thereby enabling/guiding their UQ activities. The Duke effort focused on the development of algorithms and utility software for non-intrusive sparse UQ representations, and on participation in the organization of annual workshops and tutorials to disseminate UQ tools to the community, and to gather input in order to adapt approaches to the needs of SciDAC customers. In particular, fundamental developments were made in (a) multiscale stochastic preconditioners, (b) gradient-based approaches to inverse problems, (c) adaptive pseudo-spectral approximations, (d) stochastic limit cycles, and (e) sensitivity analysis tools for noisy systems. In addition, large-scale demonstrations were performed, namely in the context of ocean general circulation models.

Assessing Power System Stability Following Load Changes and Considering Uncertainty

Directory of Open Access Journals (Sweden)

D. V. Ngo

2018-04-01

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

Safety assessment of boron by application of new uncertainty factors and their subdivision.

Science.gov (United States)

Hasegawa, Ryuichi; Hirata-Koizumi, Mutsuko; Dourson, Michael L; Parker, Ann; Ono, Atsushi; Hirose, Akihiko

2013-02-01

The available toxicity information for boron was reevaluated and four appropriate toxicity studies were selected in order to derive a tolerable daily intake (TDI) using newly proposed uncertainty factors (UFs) presented in Hasegawa et al. (2010). No observed adverse effect levels (NOAELs) of 17.5 and 8.8 mgB/kg/day for the critical effect of testicular toxicity were found in 2-year rat and dog feeding studies. Also, the 95% lower confidence limit of the benchmark doses for 5% reduction of fetal body weight (BMDL(05)) was calculated as 44.9 and 10.3 mgB/kg/day in mouse and rat developmental toxicity studies, respectively. Measured values available for differences in boron clearance between rats and humans and variability in the glomerular filtration rate (GFR) in pregnant women were used to derive chemical specific UFs. For the remaining uncertainty, newly proposed default UFs, which were derived from the latest applicable information with a probabilistic approach, and their subdivided factors for toxicokinetic and toxicodynamic variability were applied. Finally, overall UFs were calculated as 68 for rat testicular toxicity, 40 for dog testicular toxicity, 247 for mouse developmental toxicity and 78 for rat developmental toxicity. It is concluded that 0.13 mgB/kg/day is the most appropriate TDI for boron, based on rat developmental toxicity. Copyright © 2012 Elsevier Inc. All rights reserved.

Uncertainty in hydrological change modelling

DEFF Research Database (Denmark)

Seaby, Lauren Paige

applied at the grid scale. Flux and state hydrological outputs which integrate responses over time and space showed more sensitivity to precipitation mean spatial biases and less so on extremes. In the investigated catchments, the projected change of groundwater levels and basin discharge between current......Hydrological change modelling methodologies generally use climate models outputs to force hydrological simulations under changed conditions. There are nested sources of uncertainty throughout this methodology, including choice of climate model and subsequent bias correction methods. This Ph.......D. study evaluates the uncertainty of the impact of climate change in hydrological simulations given multiple climate models and bias correction methods of varying complexity. Three distribution based scaling methods (DBS) were developed and benchmarked against a more simplistic and commonly used delta...

Uncertainties of Large-Scale Forcing Caused by Surface Turbulence Flux Measurements and the Impacts on Cloud Simulations at the ARM SGP Site

Science.gov (United States)

Tang, S.; Xie, S.; Tang, Q.; Zhang, Y.

2017-12-01

Two types of instruments, the eddy correlation flux measurement system (ECOR) and the energy balance Bowen ratio system (EBBR), are used at the Atmospheric Radiation Measurement (ARM) program Southern Great Plains (SGP) site to measure surface latent and sensible fluxes. ECOR and EBBR typically sample different land surface types, and the domain-mean surface fluxes derived from ECOR and EBBR are not always consistent. The uncertainties of the surface fluxes will have impacts on the derived large-scale forcing data and further affect the simulations of single-column models (SCM), cloud-resolving models (CRM) and large-eddy simulation models (LES), especially for the shallow-cumulus clouds which are mainly driven by surface forcing. This study aims to quantify the uncertainties of the large-scale forcing caused by surface turbulence flux measurements and investigate the impacts on cloud simulations using long-term observations from the ARM SGP site.

Estimating the magnitude of prediction uncertainties for field-scale P loss models

Science.gov (United States)

Models are often used to predict phosphorus (P) loss from agricultural fields. While it is commonly recognized that model predictions are inherently uncertain, few studies have addressed prediction uncertainties using P loss models. In this study, an uncertainty analysis for the Annual P Loss Estima...

Model parameter uncertainty analysis for an annual field-scale phosphorus loss model

Science.gov (United States)

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

A generalized Levene's scale test for variance heterogeneity in the presence of sample correlation and group uncertainty.

Science.gov (United States)

Soave, David; Sun, Lei

2017-09-01

We generalize Levene's test for variance (scale) heterogeneity between k groups for more complex data, when there are sample correlation and group membership uncertainty. Following a two-stage regression framework, we show that least absolute deviation regression must be used in the stage 1 analysis to ensure a correct asymptotic χk-12/(k-1) distribution of the generalized scale (gS) test statistic. We then show that the proposed gS test is independent of the generalized location test, under the joint null hypothesis of no mean and no variance heterogeneity. Consequently, we generalize the recently proposed joint location-scale (gJLS) test, valuable in settings where there is an interaction effect but one interacting variable is not available. We evaluate the proposed method via an extensive simulation study and two genetic association application studies. © 2017 The Authors Biometrics published by Wiley Periodicals, Inc. on behalf of International Biometric Society.

Macro Expectations, Aggregate Uncertainty, and Expected Term Premia

DEFF Research Database (Denmark)

Dick, Christian D.; Schmeling, Maik; Schrimpf, Andreas

2013-01-01

as well as aggregate macroeconomic uncertainty at the level of individual forecasters. We find that expected term premia are (i) time-varying and reasonably persistent, (ii) strongly related to expectations about future output growth, and (iii) positively affected by uncertainty about future output growth...... and in ation rates. Expectations about real macroeconomic variables seem to matter more than expectations about nominal factors. Additional findings on term structure factors suggest that the level and slope factor capture information related to uncertainty about real and nominal macroeconomic prospects...

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

Science.gov (United States)

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

2013-04-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2016-09-01

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

Report on the uncertainty methods study

International Nuclear Information System (INIS)

1998-06-01

The Uncertainty Methods Study (UMS) Group, following a mandate from CSNI, has compared five methods for calculating the uncertainty in the predictions of advanced 'best estimate' thermal-hydraulic codes: the Pisa method (based on extrapolation from integral experiments) and four methods identifying and combining input uncertainties. Three of these, the GRS, IPSN and ENUSA methods, use subjective probability distributions, and one, the AEAT method, performs a bounding analysis. Each method has been used to calculate the uncertainty in specified parameters for the LSTF SB-CL-18 5% cold leg small break LOCA experiment in the ROSA-IV Large Scale Test Facility (LSTF). The uncertainty analysis was conducted essentially blind and the participants did not use experimental measurements from the test as input apart from initial and boundary conditions. Participants calculated uncertainty ranges for experimental parameters including pressurizer pressure, primary circuit inventory and clad temperature (at a specified position) as functions of time

A Peep into the Uncertainty-Complexity-Relevance Modeling Trilemma through Global Sensitivity and Uncertainty Analysis

Science.gov (United States)

Munoz-Carpena, R.; Muller, S. J.; Chu, M.; Kiker, G. A.; Perz, S. G.

2014-12-01

Model Model complexity resulting from the need to integrate environmental system components cannot be understated. In particular, additional emphasis is urgently needed on rational approaches to guide decision making through uncertainties surrounding the integrated system across decision-relevant scales. However, in spite of the difficulties that the consideration of modeling uncertainty represent for the decision process, it should not be avoided or the value and science behind the models will be undermined. These two issues; i.e., the need for coupled models that can answer the pertinent questions and the need for models that do so with sufficient certainty, are the key indicators of a model's relevance. Model relevance is inextricably linked with model complexity. Although model complexity has advanced greatly in recent years there has been little work to rigorously characterize the threshold of relevance in integrated and complex models. Formally assessing the relevance of the model in the face of increasing complexity would be valuable because there is growing unease among developers and users of complex models about the cumulative effects of various sources of uncertainty on model outputs. In particular, this issue has prompted doubt over whether the considerable effort going into further elaborating complex models will in fact yield the expected payback. New approaches have been proposed recently to evaluate the uncertainty-complexity-relevance modeling trilemma (Muller, Muñoz-Carpena and Kiker, 2011) by incorporating state-of-the-art global sensitivity and uncertainty analysis (GSA/UA) in every step of the model development so as to quantify not only the uncertainty introduced by the addition of new environmental components, but the effect that these new components have over existing components (interactions, non-linear responses). Outputs from the analysis can also be used to quantify system resilience (stability, alternative states, thresholds or tipping

Scaling with known uncertainty: a synthesis

Science.gov (United States)

Jianguo Wu; Harbin Li; K. Bruce Jones; Orie L. Loucks

2006-01-01

Scale is a fundamental concept in ecology and all sciences (Levin 1992, Wu and Loucks 1995, Barenblatt 1996), which has received increasing attention in recent years. The previous chapters have demonstrated an immerse diversity of scaling issues present in different areas of ecology, covering species distribution, population dynamics, ecosystem processes, and...

Accounting for uncertainty in evaluating water quality impacts of urban development plan

International Nuclear Information System (INIS)

Zhou Jiquan; Liu Yi; Chen Jining

2010-01-01

The implementation of urban development plans causes land use change, which can have significant environmental impacts. In light of this, environmental concerns should be considered sufficiently at an early stage of the planning process. However, uncertainties existing in urban development plans hamper the application of strategic environmental assessment, which is applied to evaluate the environmental impacts of policies, plans and programs. This study develops an integrated assessment method based on accounting uncertainty of environmental impacts. And the proposed method consists of four main steps: (1) designing scenarios of economic scale and industrial structure, (2) sampling for possible land use layouts, (3) evaluating each sample's environmental impact, and (4) identifying environmentally sensitive industries. In doing so, uncertainties of environmental impacts can be accounted. Then environmental risk, overall environmental pressure and potential extreme environmental impact of urban development plans can be analyzed, and environmentally sensitive factors can be identified, especially under considerations of uncertainties. It can help decision-makers enhance environmental consideration and take measures in the early stage of decision-making.

The Uncertainty of Measurement Results

Energy Technology Data Exchange (ETDEWEB)

Ambrus, A. [Hungarian Food Safety Office, Budapest (Hungary)

2009-07-15

Factors affecting the uncertainty of measurement are explained, basic statistical formulae given, and the theoretical concept explained in the context of pesticide formulation analysis. Practical guidance is provided on how to determine individual uncertainty components within an analytical procedure. An extended and comprehensive table containing the relevant mathematical/statistical expressions elucidates the relevant underlying principles. Appendix I provides a practical elaborated example on measurement uncertainty estimation, above all utilizing experimental repeatability and reproducibility laboratory data. (author)

Multi-scenario modelling of uncertainty in stochastic chemical systems

International Nuclear Information System (INIS)

Evans, R. David; Ricardez-Sandoval, Luis A.

2014-01-01

Uncertainty analysis has not been well studied at the molecular scale, despite extensive knowledge of uncertainty in macroscale systems. The ability to predict the effect of uncertainty allows for robust control of small scale systems such as nanoreactors, surface reactions, and gene toggle switches. However, it is difficult to model uncertainty in such chemical systems as they are stochastic in nature, and require a large computational cost. To address this issue, a new model of uncertainty propagation in stochastic chemical systems, based on the Chemical Master Equation, is proposed in the present study. The uncertain solution is approximated by a composite state comprised of the averaged effect of samples from the uncertain parameter distributions. This model is then used to study the effect of uncertainty on an isomerization system and a two gene regulation network called a repressilator. The results of this model show that uncertainty in stochastic systems is dependent on both the uncertain distribution, and the system under investigation. -- Highlights: •A method to model uncertainty on stochastic systems was developed. •The method is based on the Chemical Master Equation. •Uncertainty in an isomerization reaction and a gene regulation network was modelled. •Effects were significant and dependent on the uncertain input and reaction system. •The model was computationally more efficient than Kinetic Monte Carlo

Determination of the jet energy scale at the Collider Detector at Fermilab

Energy Technology Data Exchange (ETDEWEB)

Bhatti, A.; Hatakeyama, K. [Rockefeller Univ., New York, NY 10021 (United States); Canelli, F. [Univ. of California at Los Angeles, Los Angeles, CA 90024 (United States)]. E-mail: canelli@fnal.gov; Heinemann, B. [Univ. of Liverpool, Liverpool L69 7ZE (United Kingdom); Adelman, J.; Hoffman, D.; Kwang, S.; Malkus, A.; Shochet, M. [Enrico Fermi Inst., Univ. of Chicago, Chicago, IL 60637 (United States); Ambrose, D. [Univ. of Pennsylvania, Philadelphia, PA 19104 (United States); Arguin, J.-F. [Univ. of Toronto, Toronto, Canada M5S 1A7 (Canada); Barbaro-Galtieri, A.; Currat, C.; Gibson, A.; Movilla-Fernandez, P.A. [Ernest Orlando Lawrence Berkeley National Lab., Berkeley, CA 94720 (United States); Budd, H.; Chung, Y.S.; Sakumoto, W.; Yun, G. [Univ. of Rochester, Rochester, NY 14627 (United States); Chung, K. [Carnegie Mellon Univ., Pittsburgh, PA 15213 (United States); Cooper, B. [Univ. College London, London WC1E 6BT (United Kingdom); D' Onofrio, M. [Univ. of Geneva, CH-1211 Geneva 4 (Switzerland); Dorigo, T. [Univ. of Padova, Istituto Nazionale di Fisica Nucleare, Sezione di Padova-Trento, I-35131 Padova (Italy); Erbacher, R. [Fermi National Accelerator Lab., Batavia, IL 60510 (United States); Field, R. [Univ. of Florida, Gainesville, FL 32611 (United States); Flanagan, G. [Michigan State Univ., East Lansing, MI 48824 (United States); Happacher, F. [Laboratori Nazionali di Frascati, Istituto Nazionale di Fisica Nucleare, I-00044 Frascati (Italy); Introzzi, G. [Univ. of Pavia, Istituto Nazionale di Fisica Nucleare, Sezione di Pavia, I-27100 Pavia (Italy); Kuhlmann, S.; Nodulman, L.; Proudfoot, J. [Argonne National Lab., Argonne, IL 60439 (United States); Jun, S.; Paulini, M.; Tiwari, V. [Carnegie Mellon Univ., Pittsburgh, PA 15213 (United States); Latino, G. [Istituto Nazionale di Fisica Nucleare Pisa, Univ. of Pisa, Siena and Scuola Normale Superiore of Pisa, I-56127 Pisa (Italy)] [and others

2006-10-15

A precise determination of the energy scale of jets at the Collider Detector at Fermilab at the Tevatron pp-bar collider is described. Jets are used in many analyses to estimate the energies of partons resulting from the underlying physics process. Several correction factors are developed to estimate the original parton energy from the observed jet energy in the calorimeter. The jet energy response is compared between data and Monte Carlo simulation for various physics processes, and systematic uncertainties on the jet energy scale are determined. For jets with transverse momenta above 50GeV the jet energy scale is determined with a 3% systematic uncertainty.

Towards a quantitative, measurement-based estimate of the uncertainty in photon mass attenuation coefficients at radiation therapy energies

Science.gov (United States)

Ali, E. S. M.; Spencer, B.; McEwen, M. R.; Rogers, D. W. O.

2015-02-01

In this study, a quantitative estimate is derived for the uncertainty in the XCOM photon mass attenuation coefficients in the energy range of interest to external beam radiation therapy—i.e. 100 keV (orthovoltage) to 25 MeV—using direct comparisons of experimental data against Monte Carlo models and theoretical XCOM data. Two independent datasets are used. The first dataset is from our recent transmission measurements and the corresponding EGSnrc calculations (Ali et al 2012 Med. Phys. 39 5990-6003) for 10-30 MV photon beams from the research linac at the National Research Council Canada. The attenuators are graphite and lead, with a total of 140 data points and an experimental uncertainty of ˜0.5% (k = 1). An optimum energy-independent cross section scaling factor that minimizes the discrepancies between measurements and calculations is used to deduce cross section uncertainty. The second dataset is from the aggregate of cross section measurements in the literature for graphite and lead (49 experiments, 288 data points). The dataset is compared to the sum of the XCOM data plus the IAEA photonuclear data. Again, an optimum energy-independent cross section scaling factor is used to deduce the cross section uncertainty. Using the average result from the two datasets, the energy-independent cross section uncertainty estimate is 0.5% (68% confidence) and 0.7% (95% confidence). The potential for energy-dependent errors is discussed. Photon cross section uncertainty is shown to be smaller than the current qualitative ‘envelope of uncertainty’ of the order of 1-2%, as given by Hubbell (1999 Phys. Med. Biol 44 R1-22).

Scale factor measure method without turntable for angular rate gyroscope

Science.gov (United States)

Qi, Fangyi; Han, Xuefei; Yao, Yanqing; Xiong, Yuting; Huang, Yuqiong; Wang, Hua

2018-03-01

In this paper, a scale factor test method without turntable is originally designed for the angular rate gyroscope. A test system which consists of test device, data acquisition circuit and data processing software based on Labview platform is designed. Taking advantage of gyroscope's sensitivity of angular rate, a gyroscope with known scale factor, serves as a standard gyroscope. The standard gyroscope is installed on the test device together with a measured gyroscope. By shaking the test device around its edge which is parallel to the input axis of gyroscope, the scale factor of the measured gyroscope can be obtained in real time by the data processing software. This test method is fast. It helps test system miniaturized, easy to carry or move. Measure quarts MEMS gyroscope's scale factor multi-times by this method, the difference is less than 0.2%. Compare with testing by turntable, the scale factor difference is less than 1%. The accuracy and repeatability of the test system seems good.

Uncertainty analysis for a field-scale P loss model

Science.gov (United States)

Models are often used to predict phosphorus (P) loss from agricultural fields. While 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 predic...

Decommissioning funding: ethics, implementation, uncertainties

International Nuclear Information System (INIS)

2006-01-01

This status report on Decommissioning Funding: Ethics, Implementation, Uncertainties also draws on the experience of the NEA Working Party on Decommissioning and Dismantling (WPDD). The report offers, in a concise form, an overview of relevant considerations on decommissioning funding mechanisms with regard to ethics, implementation and uncertainties. Underlying ethical principles found in international agreements are identified, and factors influencing the accumulation and management of funds for decommissioning nuclear facilities are discussed together with the main sources of uncertainties of funding systems. (authors)

Scalable multi-objective control for large scale water resources systems under uncertainty

Science.gov (United States)

Giuliani, Matteo; Quinn, Julianne; Herman, Jonathan; Castelletti, Andrea; Reed, Patrick

2016-04-01

The use of mathematical models to support the optimal management of environmental systems is rapidly expanding over the last years due to advances in scientific knowledge of the natural processes, efficiency of the optimization techniques, and availability of computational resources. However, undergoing changes in climate and society introduce additional challenges for controlling these systems, ultimately motivating the emergence of complex models to explore key causal relationships and dependencies on uncontrolled sources of variability. In this work, we contribute a novel implementation of the evolutionary multi-objective direct policy search (EMODPS) method for controlling environmental systems under uncertainty. The proposed approach combines direct policy search (DPS) with hierarchical parallelization of multi-objective evolutionary algorithms (MOEAs) and offers a threefold advantage: the DPS simulation-based optimization can be combined with any simulation model and does not add any constraint on modeled information, allowing the use of exogenous information in conditioning the decisions. Moreover, the combination of DPS and MOEAs prompts the generation or Pareto approximate set of solutions for up to 10 objectives, thus overcoming the decision biases produced by cognitive myopia, where narrow or restrictive definitions of optimality strongly limit the discovery of decision relevant alternatives. Finally, the use of large-scale MOEAs parallelization improves the ability of the designed solutions in handling the uncertainty due to severe natural variability. The proposed approach is demonstrated on a challenging water resources management problem represented by the optimal control of a network of four multipurpose water reservoirs in the Red River basin (Vietnam). As part of the medium-long term energy and food security national strategy, four large reservoirs have been constructed on the Red River tributaries, which are mainly operated for hydropower

Quantifying Uncertainties in Mass-Dimensional Relationships Through a Comparison Between CloudSat and SPartICus Reflectivity Factors

Science.gov (United States)

Mascio, J.; Mace, G. G.

2015-12-01

CloudSat and CALIPSO, two of the satellites in the A-Train constellation, use algorithms to calculate the scattering properties of small cloud particles, such as the T-matrix method. Ice clouds (i.e. cirrus) cause problems with these cloud property retrieval algorithms because of their variability in ice mass as a function of particle size. Assumptions regarding the microphysical properties, such as mass-dimensional (m-D) relationships, are often necessary in retrieval algorithms for simplification, but these assumptions create uncertainties of their own. Therefore, ice cloud property retrieval uncertainties can be substantial and are often not well known. To investigate these uncertainties, reflectivity factors measured by CloudSat are compared to those calculated from particle size distributions (PSDs) to which different m-D relationships are applied. These PSDs are from data collected in situ during three flights of the Small Particles in Cirrus (SPartICus) campaign. We find that no specific habit emerges as preferred and instead we conclude that the microphysical characteristics of ice crystal populations tend to be distributed over a continuum and, therefore, cannot be categorized easily. To quantify the uncertainties in the mass-dimensional relationships, an optimal estimation inversion was run to retrieve the m-D relationship per SPartICus flight, as well as to calculate uncertainties of the m-D power law.

Factors and uncertainties in the profitability of using nuclear energy in desalination of water

International Nuclear Information System (INIS)

Thiriet, L.; Lievre, P.

1969-01-01

One of the economic advantages of nuclear energy consists of the small proportional element in its cost structure. Economies of scale favour the nuclear station as compared with the conventional thermal one, and when the demand for electricity and heat, in particular for desalination, are sufficient, nuclear energy may, subject to certain conditions, prove advantageous. The object of this paper is to discuss the validity of the conclusions reached according to the hypotheses adopted. In the first part, the different kind of uncertainties connected with technical, economic and financial data (the various transmission coefficients, the life of equipment according to the choice of materials, changes in prices, the form of price functions and interest rates), and with the various constraints, are examined and discussed. In the second part the uncertainties connected with the method of optimisation used and the criterion of selection adopted are examined and discussed. It is shown thereby that it is usually extremely difficult to assume absolutely the competitiveness, or conversely the non-competitiveness, of using nuclear energy in the desalination of water, and that a large number of aspects have to be carefully examined. (author) [fr

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.

On the relationship between aerosol model uncertainty and radiative forcing uncertainty.

Science.gov (United States)

Lee, Lindsay A; Reddington, Carly L; Carslaw, Kenneth S

2016-05-24

The largest uncertainty in the historical radiative forcing of climate is caused by the interaction of aerosols with clouds. Historical forcing is not a directly measurable quantity, so reliable assessments depend on the development of global models of aerosols and clouds that are well constrained by observations. However, there has been no systematic assessment of how reduction in the uncertainty of global aerosol models will feed through to the uncertainty in the predicted forcing. We use a global model perturbed parameter ensemble to show that tight observational constraint of aerosol concentrations in the model has a relatively small effect on the aerosol-related uncertainty in the calculated forcing between preindustrial and present-day periods. One factor is the low sensitivity of present-day aerosol to natural emissions that determine the preindustrial aerosol state. However, the major cause of the weak constraint is that the full uncertainty space of the model generates a large number of model variants that are equally acceptable compared to present-day aerosol observations. The narrow range of aerosol concentrations in the observationally constrained model gives the impression of low aerosol model uncertainty. However, these multiple "equifinal" models predict a wide range of forcings. To make progress, we need to develop a much deeper understanding of model uncertainty and ways to use observations to constrain it. Equifinality in the aerosol model means that tuning of a small number of model processes to achieve model-observation agreement could give a misleading impression of model robustness.

Competitiveness of small-medium reactors. A probabilistic study on the economy of scale factor

International Nuclear Information System (INIS)

Trianni, A.; Locatelli, G.; Trucco, P.

2009-01-01

Smaller size reactors are able to play an important role in the worldwide nuclear renaissance. The major disadvantage of those new reactors - the unit size - would label the small-medium size reactors as not economically competitive with larger plants. But, the economy of scale law applies only if the designs are similar, which is not the case here, since the SMRs are designed with original and innovative solutions not accessible to large size reactors: the IRIS reactor is used as an example of small medium reactors (SMR), but the analyses and conclusions are applicable to the whole spectrum of SMRs. The aim of this paper is to present latest advances in the differential economical assessment of Generation Cost of SMRs compared to LRs. The international literature has started to present studies focused on the two major differential accounts of Levelized Unit Electricity Cost - Captial Costs ($/kWe) and Operation and Maintenance Costs ($/kWh) - providing deterministic values for the main cost drivers (i.e. economy of scale, multiple units, learning during construction, design characteristics and modular build, shorter construction time for CC, economy of scale location of the plant, number of units, capacity factor, learning by doing, plant obsolescence for O and M costs). Since the modern SMR market is in the early stages of development, it is necessary to consider also the uncertainties associated to current estimates of those cost drivers. When available, the uncertainty has been integrated in the Open Model assigning a probabilistic distribution to the input value of each cost driver. As Far as other cost drivers are concerned, parametric analyses are still under development and uncertainty analyses are not available: thus, conservative but realistic values for both of them have been assumed. Some reasonable future scenarios have been assumed, considering the private operator perspective for a single plant investment and postulating, among the others

Mathematical modeling of a survey-meter used to measure radioactivity in human thyroids: Monte Carlo calculations of the device response and uncertainties

Science.gov (United States)

Khrutchinsky, Arkady; Drozdovitch, Vladimir; Kutsen, Semion; Minenko, Victor; Khrouch, Valeri; Luckyanov, Nickolas; Voillequé, Paul; Bouville, André

2012-01-01

This paper presents results of Monte Carlo modeling of the SRP-68-01 survey meter used to measure exposure rates near the thyroid glands of persons exposed to radioactivity following the Chernobyl accident. This device was not designed to measure radioactivity in humans. To estimate the uncertainty associated with the measurement results, a mathematical model of the SRP-68-01 survey meter was developed and verified. A Monte Carlo method of numerical simulation of radiation transport has been used to calculate the calibration factor for the device and evaluate its uncertainty. The SRP-68-01 survey meter scale coefficient, an important characteristic of the device, was also estimated in this study. The calibration factors of the survey meter were calculated for 131I, 132I, 133I, and 135I content in the thyroid gland for six age groups of population: newborns; children aged 1 yr, 5 yr, 10 yr, 15 yr; and adults. A realistic scenario of direct thyroid measurements with an “extended” neck was used to calculate the calibration factors for newborns and one-year-olds. Uncertainties in the device calibration factors due to variability of the device scale coefficient, variability in thyroid mass and statistical uncertainty of Monte Carlo method were evaluated. Relative uncertainties in the calibration factor estimates were found to be from 0.06 for children aged 1 yr to 0.1 for 10-yr and 15-yr children. The positioning errors of the detector during measurements deviate mainly in one direction from the estimated calibration factors. Deviations of the device position from the proper geometry of measurements were found to lead to overestimation of the calibration factor by up to 24 percent for adults and up to 60 percent for 1-yr children. The results of this study improve the estimates of 131I thyroidal content and, consequently, thyroid dose estimates that are derived from direct thyroid measurements performed in Belarus shortly after the Chernobyl accident. PMID:22245289

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

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 Measuring Noise Parameters Of a Communication Receiver

International Nuclear Information System (INIS)

Korcz, Karol; Palczynska, Beata; Spiralski, Ludwik

2005-01-01

The paper presents the method of assessing uncertainty in measuring the usable sensitivity Es of communication receiver. The influence of partial uncertainties of measuring the noise factor F and the energy pass band of the receiver Δf on the combined standard uncertainty level is analyzed. The method to assess the uncertainty in measuring the noise factor on the basis of the systematic component of uncertainty, assuming that the main source of measurement uncertainty is the hardware of the measuring system, is proposed. The assessment of uncertainty in measuring the pass band of the receiver is determined with the assumption that input quantities of the measurement equation are not correlated. They are successive, discrete values of the spectral power density of the noise on the output of receiver. The results of the analyses of particular uncertainties components of measuring the sensitivity, which were carried out for a typical communication receiver, are presented

A Confirmatory Factor Analysis of Reilly's Role Overload Scale

Science.gov (United States)

Thiagarajan, Palaniappan; Chakrabarty, Subhra; Taylor, Ronald D.

2006-01-01

In 1982, Reilly developed a 13-item scale to measure role overload. This scale has been widely used, but most studies did not assess the unidimensionality of the scale. Given the significance of unidimensionality in scale development, the current study reports a confirmatory factor analysis of the 13-item scale in two samples. Based on the…

Large scale applicability of a Fully Adaptive Non-Intrusive Spectral Projection technique: Sensitivity and uncertainty analysis of a transient

International Nuclear Information System (INIS)

Perkó, Zoltán; Lathouwers, Danny; Kloosterman, Jan Leen; Hagen, Tim van der

2014-01-01

Highlights: • Grid and basis adaptive Polynomial Chaos techniques are presented for S and U analysis. • Dimensionality reduction and incremental polynomial order reduce computational costs. • An unprotected loss of flow transient is investigated in a Gas Cooled Fast Reactor. • S and U analysis is performed with MC and adaptive PC methods, for 42 input parameters. • PC accurately estimates means, variances, PDFs, sensitivities and uncertainties. - Abstract: Since the early years of reactor physics the most prominent sensitivity and uncertainty (S and U) analysis methods in the nuclear community have been adjoint based techniques. While these are very effective for pure neutronics problems due to the linearity of the transport equation, they become complicated when coupled non-linear systems are involved. With the continuous increase in computational power such complicated multi-physics problems are becoming progressively tractable, hence affordable and easily applicable S and U analysis tools also have to be developed in parallel. For reactor physics problems for which adjoint methods are prohibitive Polynomial Chaos (PC) techniques offer an attractive alternative to traditional random sampling based approaches. At TU Delft such PC methods have been studied for a number of years and this paper presents a large scale application of our Fully Adaptive Non-Intrusive Spectral Projection (FANISP) algorithm for performing the sensitivity and uncertainty analysis of a Gas Cooled Fast Reactor (GFR) Unprotected Loss Of Flow (ULOF) transient. The transient was simulated using the Cathare 2 code system and a fully detailed model of the GFR2400 reactor design that was investigated in the European FP7 GoFastR project. Several sources of uncertainty were taken into account amounting to an unusually high number of stochastic input parameters (42) and numerous output quantities were investigated. The results show consistently good performance of the applied adaptive PC

Systematic uncertainties in the Monte Carlo calculation of ion chamber replacement correction factors

Energy Technology Data Exchange (ETDEWEB)

Wang, L. L. W.; La Russa, D. J.; Rogers, D. W. O. [Ottawa Carleton Institute of Physics, Carleton University, Campus Ottawa, Ottawa, Ontario KIS 5B6 (Canada)

2009-05-15

In a previous study [Med. Phys. 35, 1747-1755 (2008)], the authors proposed two direct methods of calculating the replacement correction factors (P{sub repl} or p{sub cav}p{sub dis}) for ion chambers by Monte Carlo calculation. By ''direct'' we meant the stopping-power ratio evaluation is not necessary. The two methods were named as the high-density air (HDA) and low-density water (LDW) methods. Although the accuracy of these methods was briefly discussed, it turns out that the assumption made regarding the dose in an HDA slab as a function of slab thickness is not correct. This issue is reinvestigated in the current study, and the accuracy of the LDW method applied to ion chambers in a {sup 60}Co photon beam is also studied. It is found that the two direct methods are in fact not completely independent of the stopping-power ratio of the two materials involved. There is an implicit dependence of the calculated P{sub repl} values upon the stopping-power ratio evaluation through the choice of an appropriate energy cutoff {Delta}, which characterizes a cavity size in the Spencer-Attix cavity theory. Since the {Delta} value is not accurately defined in the theory, this dependence on the stopping-power ratio results in a systematic uncertainty on the calculated P{sub repl} values. For phantom materials of similar effective atomic number to air, such as water and graphite, this systematic uncertainty is at most 0.2% for most commonly used chambers for either electron or photon beams. This uncertainty level is good enough for current ion chamber dosimetry, and the merits of the two direct methods of calculating P{sub repl} values are maintained, i.e., there is no need to do a separate stopping-power ratio calculation. For high-Z materials, the inherent uncertainty would make it practically impossible to calculate reliable P{sub repl} values using the two direct methods.

INVESTIGATING THE FACTOR STRUCTURE OF THE BLOG ATTITUDE SCALE

Directory of Open Access Journals (Sweden)

Zahra SHAHSAVAR

2010-10-01

Full Text Available Due to the wide application of advanced technology in education, many attitude scales have been developed to evaluate learners’ attitudes toward educational tools. However, with the rapid development of emerging technologies, using blogs as one of the Web 2.0 tools is still in its infancy and few blog attitude scales have been developed yet. In view of this need, a lot of researchers like to design a new scale based on their conceptual and theoretical framework of their own study rather than using available scales. The present study reports the design and development of a blog attitude scale (BAS. The researchers developed a pool of items to capture the complexity of the blog attitude trait, selected 29 items in the content analysis, and assigned the scale comprising 29 items to 216 undergraduate students to explore the underlying structure of the BAS. In exploratory factor analysis, three factors were discovered: blog anxiety, blog desirability, and blog self-efficacy; 14 items were excluded. The extracted items were subjected to a confirmatory factor analysis which lent further support to the BAS underpinning structure.

Factor Structure of the Exercise Self-Efficacy Scale

Science.gov (United States)

Cornick, Jessica E.

2015-01-01

The current study utilized exercise self-efficacy ratings from undergraduate students to assess the factor structure of the Self-Efficacy to Regulate Exercise Scale (Bandura, 1997, 2006). An exploratory factor analysis (n = 759) indicated a two-factor model solution and three separate confirmatory factor analyses (n = 1,798) supported this…

Information-theoretic approach to uncertainty importance

International Nuclear Information System (INIS)

Park, C.K.; Bari, R.A.

1985-01-01

A method is presented for importance analysis in probabilistic risk assessments (PRA) for which the results of interest are characterized by full uncertainty distributions and not just point estimates. The method is based on information theory in which entropy is a measure of uncertainty of a probability density function. We define the relative uncertainty importance between two events as the ratio of the two exponents of the entropies. For the log-normal and log-uniform distributions the importance measure is comprised of the median (central tendency) and of the logarithm of the error factor (uncertainty). Thus, if accident sequences are ranked this way, and the error factors are not all equal, then a different rank order would result than if the sequences were ranked by the central tendency measure alone. As an illustration, the relative importance of internal events and in-plant fires was computed on the basis of existing PRA results

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

Can we do better than the grid survey: Optimal synoptic surveys in presence of variable uncertainty and decorrelation scales

Science.gov (United States)

Frolov, Sergey; Garau, Bartolame; Bellingham, James

2014-08-01

Regular grid ("lawnmower") survey is a classical strategy for synoptic sampling of the ocean. Is it possible to achieve a more effective use of available resources if one takes into account a priori knowledge about variability in magnitudes of uncertainty and decorrelation scales? In this article, we develop and compare the performance of several path-planning algorithms: optimized "lawnmower," a graph-search algorithm (A*), and a fully nonlinear genetic algorithm. We use the machinery of the best linear unbiased estimator (BLUE) to quantify the ability of a vehicle fleet to synoptically map distribution of phytoplankton off the central California coast. We used satellite and in situ data to specify covariance information required by the BLUE estimator. Computational experiments showed that two types of sampling strategies are possible: a suboptimal space-filling design (produced by the "lawnmower" and the A* algorithms) and an optimal uncertainty-aware design (produced by the genetic algorithm). Unlike the space-filling designs that attempted to cover the entire survey area, the optimal design focused on revisiting areas of high uncertainty. Results of the multivehicle experiments showed that fleet performance predictors, such as cumulative speed or the weight of the fleet, predicted the performance of a homogeneous fleet well; however, these were poor predictors for comparing the performance of different platforms.

Spiritual well-being in individuals with fibromyalgia syndrome: relationships with symptom pattern variability, uncertainty, and psychosocial adaptation.

Science.gov (United States)

Anema, Cheryl; Johnson, Mary; Zeller, Janice M; Fogg, Louis; Zetterlund, Joan

2009-01-01

This study examined relationships among symptom pattern variability, uncertainty, spiritual well-being, and psychosocial adaptation in individuals with fibromyalgia syndrome (FMS). A survey design was used with 58 individuals with FMS. The Fibromyalgia Symptom Pattern Questionnaire, Mishel Uncertainty in Illness Scale--Community Form, Spiritual Well-Being Scale, and Psychosocial Adjustment to Illness Scale-Self Report were used to collect data. Positive relationships were found between symptom pattern variability and uncertainty and between uncertainty and poor psychosocial adaptation; spiritual well-being moderated the relationship between uncertainty and psychosocial adaptation. A positive sense of well-being aided adaptation to symptoms and uncertainties of FMS. Spiritual well-being had a greater effect on the relationship between symptom pattern variability and uncertainty than expected.

Improvement of Modeling HTGR Neutron Physics by Uncertainty Analysis with the Use of Cross-Section Covariance Information

Science.gov (United States)

Boyarinov, V. F.; Grol, A. V.; Fomichenko, P. A.; Ternovykh, M. Yu

2017-01-01

This work is aimed at improvement of HTGR neutron physics design calculations by application of uncertainty analysis with the use of cross-section covariance information. Methodology and codes for preparation of multigroup libraries of covariance information for individual isotopes from the basic 44-group library of SCALE-6 code system were developed. A 69-group library of covariance information in a special format for main isotopes and elements typical for high temperature gas cooled reactors (HTGR) was generated. This library can be used for estimation of uncertainties, associated with nuclear data, in analysis of HTGR neutron physics with design codes. As an example, calculations of one-group cross-section uncertainties for fission and capture reactions for main isotopes of the MHTGR-350 benchmark, as well as uncertainties of the multiplication factor (k∞) for the MHTGR-350 fuel compact cell model and fuel block model were performed. These uncertainties were estimated by the developed technology with the use of WIMS-D code and modules of SCALE-6 code system, namely, by TSUNAMI, KENO-VI and SAMS. Eight most important reactions on isotopes for MHTGR-350 benchmark were identified, namely: 10B(capt), 238U(n,γ), ν5, 235U(n,γ), 238U(el), natC(el), 235U(fiss)-235U(n,γ), 235U(fiss).

Uncertainty information in climate data records from Earth observation

Science.gov (United States)

Merchant, C. J.

2017-12-01

How to derive and present uncertainty in climate data records (CDRs) has been debated within the European Space Agency Climate Change Initiative, in search of common principles applicable across a range of essential climate variables. Various points of consensus have been reached, including the importance of improving provision of uncertainty information and the benefit of adopting international norms of metrology for language around the distinct concepts of uncertainty and error. Providing an estimate of standard uncertainty per datum (or the means to readily calculate it) emerged as baseline good practice, and should be highly relevant to users of CDRs when the uncertainty in data is variable (the usual case). Given this baseline, the role of quality flags is clarified as being complementary to and not repetitive of uncertainty information. Data with high uncertainty are not poor quality if a valid estimate of the uncertainty is available. For CDRs and their applications, the error correlation properties across spatio-temporal scales present important challenges that are not fully solved. Error effects that are negligible in the uncertainty of a single pixel may dominate uncertainty in the large-scale and long-term. A further principle is that uncertainty estimates should themselves be validated. The concepts of estimating and propagating uncertainty are generally acknowledged in geophysical sciences, but less widely practised in Earth observation and development of CDRs. Uncertainty in a CDR depends in part (and usually significantly) on the error covariance of the radiances and auxiliary data used in the retrieval. Typically, error covariance information is not available in the fundamental CDR (FCDR) (i.e., with the level-1 radiances), since provision of adequate level-1 uncertainty information is not yet standard practice. Those deriving CDRs thus cannot propagate the radiance uncertainty to their geophysical products. The FIDUCEO project (www.fiduceo.eu) is

Using the Karolinska Scales of Personality on male juvenile delinquents: relationships between scales and factor structure.

Science.gov (United States)

Dåderman, Anna M; Hellström, Ake; Wennberg, Peter; Törestad, Bertil

2005-01-01

The aim of the present study was to investigate relationships between scales from the Karolinska Scales of Personality (KSP) and the factor structure of the KSP in a sample of male juvenile delinquents. The KSP was administered to a group of male juvenile delinquents (n=55, mean age 17 years; standard deviation=1.2) from four Swedish national correctional institutions for serious offenders. As expected, the KSP showed appropriate correlations between the scales. Factor analysis (maximum likelihood) arrived at a four-factor solution in this sample, which is in line with previous research performed in a non-clinical sample of Swedish males. More research is needed in a somewhat larger sample of juvenile delinquents in order to confirm the present results regarding the factor solution.

Prospective impact of illness uncertainty on outcomes in chronic lung disease.

Science.gov (United States)

Hoth, Karin F; Wamboldt, Frederick S; Strand, Matthew; Ford, Dee W; Sandhaus, Robert A; Strange, Charlie; Bekelman, David B; Holm, Kristen E

2013-11-01

To determine which aspect of illness uncertainty (i.e., ambiguity or complexity) has a stronger association with psychological and clinical outcomes over a 2-year period among individuals with a genetic subtype of chronic obstructive pulmonary disease (COPD). Ambiguity reflects uncertainty about physical cues and symptoms, and complexity reflects uncertainty about treatment and the medical system. Four-hundred and 7 individuals with alpha-1 antitrypsin deficiency-associated COPD completed questionnaires at baseline, 1- and 2-year follow-up. Uncertainty was measured using the Mishel Uncertainty in Illness Scale. Outcomes were measured using the Hospital Anxiety and Depression Scale, St. George's Respiratory Questionnaire, and MMRC Dyspnea Scale. Ambiguity and complexity were examined as predictors of depressive symptoms, anxiety, quality of life, and breathlessness using linear mixed models adjusting for demographic and health characteristics. Ambiguity was associated with more depressive symptoms (b = 0.09, SE = 0.02, p life (b = 0.57, SE = 0.10, p life, and breathlessness. Thus, ambiguity should be targeted in psychosocial interventions. Time since diagnosis did not affect the association between ambiguity and outcomes, suggesting that the impact of ambiguity is equally strong throughout the course of COPD.

Research of Uncertainty Reasoning in Pineapple Disease Identification System

Science.gov (United States)

Liu, Liqun; Fan, Haifeng

In order to deal with the uncertainty of evidences mostly existing in pineapple disease identification system, a reasoning model based on evidence credibility factor was established. The uncertainty reasoning method is discussed,including: uncertain representation of knowledge, uncertain representation of rules, uncertain representation of multi-evidences and update of reasoning rules. The reasoning can fully reflect the uncertainty in disease identification and reduce the influence of subjective factors on the accuracy of the system.

Waste receiving and processing drum weight measurement uncertainty review findings

International Nuclear Information System (INIS)

LANE, M.P.

1999-01-01

The purpose of reviewing the weight scale operation at the WRAP facility was to determine the uncertainty associated with weight measurements. Weight measurement uncertainty is needed to support WRAP Nondestructive Examination (NDE) and Non-destructive Assay (NDA) analysis

Maximizing probable oil field profit: uncertainties on well spacing

International Nuclear Information System (INIS)

MacKay, J.A.; Lerche, I.

1997-01-01

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

Confirmatory Factor Analysis of the Procrastination Assessment Scale for Students

Directory of Open Access Journals (Sweden)

Ronald D. Yockey

2015-10-01

Full Text Available The relative fit of one- and two-factor models of the Procrastination Assessment Scale for Students (PASS was investigated using confirmatory factor analysis on an ethnically diverse sample of 345 participants. The results indicated that although the two-factor model provided better fit to the data than the one-factor model, neither model provided optimal fit. However, a two-factor model which accounted for common item theme pairs used by Solomon and Rothblum in the creation of the scale provided good fit to the data. In addition, a significant difference by ethnicity was also found on the fear of failure subscale of the PASS, with Whites having significantly lower scores than Asian Americans or Latino/as. Implications of the results are discussed and recommendations made for future work with the scale.

Uncertainties in the Norwegian greenhouse gas emission inventory

Energy Technology Data Exchange (ETDEWEB)

Flugsrud, Ketil; Hoem, Britta

2011-11-15

The national greenhouse gas (GHG) emission inventory is compiled from estimates based on emission factors and activity data and from direct measurements by plants. All these data and parameters will contribute to the overall inventory uncertainty. The uncertainties and probability distributions of the inventory input parameters have been assessed based on available data and expert judgements.Finally, the level and trend uncertainties of the national GHG emission inventory have been estimated using Monte Carlo simulation. The methods used in the analysis correspond to an IPCC tier 2 method, as described in the IPCC Good Practice Guidance (IPCC 2000) (IPCC 2000). Analyses have been made both excluding and including the sector LULUCF (land use, land-use change and forestry). The uncertainty analysis performed in 2011 is an update of the uncertainty analyses performed for the greenhouse gas inventory in 2006 and 2000. During the project we have been in contact with experts, and have collected information about uncertainty from them. Main focus has been on the source categories where changes have occured since the last uncertainty analysis was performed in 2006. This includes new methodology for several source categories (for example for solvents and road traffic) as well as revised uncertainty estimates. For the installations included in the emission trading system, new information from the annual ETS reports about uncertainty in activity data and CO2 emission factor (and N2O emission factor for nitric acid production) has been used. This has improved the quality of the uncertainty estimates for the energy and manufacturing sectors. The results show that the uncertainty level in the total calculated greenhouse gas emissions for 2009 is around 4 per cent. When including the LULUCF sector, the total uncertainty is around 17 per cent in 2009. The uncertainty estimate is lower now than previous analyses have shown. This is partly due to a considerable work made to improve

Factor solutions of the Social Phobia Scale (SPS) and the Social Interaction Anxiety Scale (SIAS) in a Swedish population.

Science.gov (United States)

Mörtberg, Ewa; Reuterskiöld, Lena; Tillfors, Maria; Furmark, Tomas; Öst, Lars-Göran

2017-06-01

Culturally validated rating scales for social anxiety disorder (SAD) are of significant importance when screening for the disorder, as well as for evaluating treatment efficacy. This study examined construct validity and additional psychometric properties of two commonly used scales, the Social Phobia Scale and the Social Interaction Anxiety Scale, in a clinical SAD population (n = 180) and in a normal population (n = 614) in Sweden. Confirmatory factor analyses of previously reported factor solutions were tested but did not reveal acceptable fit. Exploratory factor analyses (EFA) of the joint structure of the scales in the total population yielded a two-factor model (performance anxiety and social interaction anxiety), whereas EFA in the clinical sample revealed a three-factor solution, a social interaction anxiety factor and two performance anxiety factors. The SPS and SIAS showed good to excellent internal consistency, and discriminated well between patients with SAD and a normal population sample. Both scales showed good convergent validity with an established measure of SAD, whereas the discriminant validity of symptoms of social anxiety and depression could not be confirmed. The optimal cut-off score for SPS and SIAS were 18 and 22 points, respectively. It is concluded that the factor structure and the additional psychometric properties of SPS and SIAS support the use of the scales for assessment in a Swedish population.

Quantification of the impact of precipitation spatial distribution uncertainty on predictive uncertainty of a snowmelt runoff model

Science.gov (United States)

Jacquin, A. P.

2012-04-01

This study is intended to quantify the impact of uncertainty about precipitation spatial distribution on predictive uncertainty of a snowmelt runoff model. This problem is especially relevant in mountain catchments with a sparse precipitation observation network and relative short precipitation records. The model analysed is a conceptual watershed model operating at a monthly time step. The model divides the catchment into five elevation zones, where the fifth zone corresponds to the catchment's glaciers. Precipitation amounts at each elevation zone i are estimated as the product between observed precipitation at a station and a precipitation factor FPi. If other precipitation data are not available, these precipitation factors must be adjusted during the calibration process and are thus seen as parameters of the model. In the case of the fifth zone, glaciers are seen as an inexhaustible source of water that melts when the snow cover is depleted.The catchment case study is Aconcagua River at Chacabuquito, located in the Andean region of Central Chile. The model's predictive uncertainty is measured in terms of the output variance of the mean squared error of the Box-Cox transformed discharge, the relative volumetric error, and the weighted average of snow water equivalent in the elevation zones at the end of the simulation period. Sobol's variance decomposition (SVD) method is used for assessing the impact of precipitation spatial distribution, represented by the precipitation factors FPi, on the models' predictive uncertainty. In the SVD method, the first order effect of a parameter (or group of parameters) indicates the fraction of predictive uncertainty that could be reduced if the true value of this parameter (or group) was known. Similarly, the total effect of a parameter (or group) measures the fraction of predictive uncertainty that would remain if the true value of this parameter (or group) was unknown, but all the remaining model parameters could be fixed

Uncertainty in sap flow-based transpiration due to xylem properties

Science.gov (United States)

Looker, N. T.; Hu, J.; Martin, J. T.; Jencso, K. G.

2014-12-01

Transpiration, the evaporative loss of water from plants through their stomata, is a key component of the terrestrial water balance, influencing streamflow as well as regional convective systems. From a plant physiological perspective, transpiration is both a means of avoiding destructive leaf temperatures through evaporative cooling and a consequence of water loss through stomatal uptake of carbon dioxide. Despite its hydrologic and ecological significance, transpiration remains a notoriously challenging process to measure in heterogeneous landscapes. Sap flow methods, which estimate transpiration by tracking the velocity of a heat pulse emitted into the tree sap stream, have proven effective for relating transpiration dynamics to climatic variables. To scale sap flow-based transpiration from the measured domain (often area) to the whole-tree level, researchers generally assume constancy of scale factors (e.g., wood thermal diffusivity (k), radial and azimuthal distributions of sap velocity, and conducting sapwood area (As)) through time, across space, and within species. For the widely used heat-ratio sap flow method (HRM), we assessed the sensitivity of transpiration estimates to uncertainty in k (a function of wood moisture content and density) and As. A sensitivity analysis informed by distributions of wood moisture content, wood density and As sampled across a gradient of water availability indicates that uncertainty in these variables can impart substantial error when scaling sap flow measurements to the whole tree. For species with variable wood properties, the application of the HRM assuming a spatially constant k or As may systematically over- or underestimate whole-tree transpiration rates, resulting in compounded error in ecosystem-scale estimates of transpiration.

Internal and external quasicrystal inflation center and their scaling factors

International Nuclear Information System (INIS)

Masakova, Z.; Patera, J.; Pelantova, E.

1998-01-01

The properties of quasicrystals of the cut and project type - namely, self-similarities or so-called inflation properties - are studied. A complete description is given for centers of the scaling symmetry of a quasicrystal, and the relevant scaling factors are determined for each 'inflation center'. If the center is a quasicrystal point, it is called an 'internal inflation center'; otherwise, it is an 'external' one. It turns out that, for any quasicrystal point u, the set of appropriate scaling factors is a u-dependent one-dimensional quasicrystal. There are infinitely many scaling factors common to all internal inflation centers. The description of external inflation centers, which are plentiful in any quasicrystal, is a slight modification of a similar description for the interval ones

Determination of a PWR key neutron parameters uncertainties and conformity studies applications

International Nuclear Information System (INIS)

Bernard, D.

2002-01-01

The aim of this thesis was to evaluate uncertainties of key neutron parameters of slab reactors. Uncertainties sources have many origins, technologic origin for parameters of fabrication and physical origin for nuclear data. First, each contribution of uncertainties is calculated and finally, a factor of uncertainties is associated to key slab parameter like reactivity, isotherm reactivity coefficient, control rod efficiency, power form factor before irradiation and lifetime. This factors of uncertainties were computed by Generalized Perturbations Theory in case of step 0 and by directs calculations in case of irradiation problems. One of neutronic conformity applications was about fabrication and nuclear data targets precision adjustments. Statistic (uncertainties) and deterministic (deviations) approaches were studied. Then neutronics key slab parameters uncertainties were reduced and so nuclear performances were optimised. (author)

Factoring uncertainty into restoration modeling of in-situ leach uranium mines

Science.gov (United States)

Johnson, Raymond H.; Friedel, Michael J.

2009-01-01

Postmining restoration is one of the greatest concerns for uranium in-situ leach (ISL) mining operations. The ISL-affected aquifer needs to be returned to conditions specified in the mining permit (either premining or other specified conditions). When uranium ISL operations are completed, postmining restoration is usually achieved by injecting reducing agents into the mined zone. The objective of this process is to restore the aquifer to premining conditions by reducing the solubility of uranium and other metals in the ground water. Reactive transport modeling is a potentially useful method for simulating the effectiveness of proposed restoration techniques. While reactive transport models can be useful, they are a simplification of reality that introduces uncertainty through the model conceptualization, parameterization, and calibration processes. For this reason, quantifying the uncertainty in simulated temporal and spatial hydrogeochemistry is important for postremedial risk evaluation of metal concentrations and mobility. Quantifying the range of uncertainty in key predictions (such as uranium concentrations at a specific location) can be achieved using forward Monte Carlo or other inverse modeling techniques (trial-and-error parameter sensitivity, calibration constrained Monte Carlo). These techniques provide simulated values of metal concentrations at specified locations that can be presented as nonlinear uncertainty limits or probability density functions. Decisionmakers can use these results to better evaluate environmental risk as future metal concentrations with a limited range of possibilities, based on a scientific evaluation of uncertainty.

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

Directory of Open Access Journals (Sweden)

K. Steffens

2014-02-01

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

A Unified Approach for Reporting ARM Measurement Uncertainties Technical Report

Energy Technology Data Exchange (ETDEWEB)

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

2016-12-01

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

Estimation of radon progeny equilibrium factors and their uncertainty bounds using solid state nuclear track detectors

International Nuclear Information System (INIS)

Eappen, K.P.; Mayya, Y.S.; Patnaik, R.L.; Kushwaha, H.S.

2006-01-01

For the assessment of inhalation doses due to radon and its progeny to uranium mine workers, it is necessary to have information on the time integrated gas concentrations and equilibrium factors. Passive single cup dosimeters using solid state nuclear track detectors (SSNTD) are best suited for this purpose. These generally contain two SSNTDs, one placed inside the cup to measure only the radon gas concentration and other outside the cup for recording tracks due to both radon gas and the progeny species. However, since one obtains only two numbers by this method whereas information on four quantities is required for an unambiguous estimation of dose, there is a need for developing an optimal methodology for extracting information on the equilibrium factors. Several techniques proposed earlier have essentially been based on deterministic approaches, which do not fully take into account all the possible uncertainties in the environmental parameters. Keeping this in view, a simple 'mean of bounds' methodology is proposed to extract equilibrium factors based on their absolute bounds and the associated uncertainties as obtained from general arguments of radon progeny disequilibrium. This may be considered as reasonable estimates of the equilibrium factors in the absence of a knowledge of fluctuation in the environmental variables. The results are compared with those from direct measurements both in the laboratory and in real field situations. In view of the good agreement found between these, it is proposed that the simple mean of bounds estimate may be useful for practical applications in inhalation dosimetry of mine workers

The Intolerance of Uncertainty Inventory: Validity and Comparison of Scoring Methods to Assess Individuals Screening Positive for Anxiety and Depression.

Science.gov (United States)

Lauriola, Marco; Mosca, Oriana; Trentini, Cristina; Foschi, Renato; Tambelli, Renata; Carleton, R Nicholas

2018-01-01

Intolerance of Uncertainty is a fundamental transdiagnostic personality construct hierarchically organized with a core general factor underlying diverse clinical manifestations. The current study evaluated the construct validity of the Intolerance of Uncertainty Inventory, a two-part scale separately assessing a unitary Intolerance of Uncertainty disposition to consider uncertainties to be unacceptable and threatening (Part A) and the consequences of such disposition, regarding experiential avoidance, chronic doubt, overestimation of threat, worrying, control of uncertain situations, and seeking reassurance (Part B). Community members ( N = 1046; Mean age = 36.69 ± 12.31 years; 61% females) completed the Intolerance of Uncertainty Inventory with the Beck Depression Inventory-II and the State-Trait Anxiety Inventory. Part A demonstrated a robust unidimensional structure and an excellent convergent validity with Part B. A bifactor model was the best fitting model for Part B. Based on these results, we compared the hierarchical factor scores with summated ratings clinical proxy groups reporting anxiety and depression symptoms. Summated rating scores were associated with both depression and anxiety and proportionally increased with the co-occurrence of depressive and anxious symptoms. By contrast, hierarchical scores were useful to detect which facets mostly separated between for depression and anxiety groups. In sum, Part A was a reliable and valid transdiagnostic measure of Intolerance of Uncertainty. The Part B was arguably more useful for assessing clinical manifestations of Intolerance of Uncertainty for specific disorders, provided that hierarchical scores are used. Overall, our study suggest that clinical assessments might need to shift toward hierarchical factor scores.

The Intolerance of Uncertainty Inventory: Validity and Comparison of Scoring Methods to Assess Individuals Screening Positive for Anxiety and Depression

Directory of Open Access Journals (Sweden)

Marco Lauriola

2018-03-01

Full Text Available Intolerance of Uncertainty is a fundamental transdiagnostic personality construct hierarchically organized with a core general factor underlying diverse clinical manifestations. The current study evaluated the construct validity of the Intolerance of Uncertainty Inventory, a two-part scale separately assessing a unitary Intolerance of Uncertainty disposition to consider uncertainties to be unacceptable and threatening (Part A and the consequences of such disposition, regarding experiential avoidance, chronic doubt, overestimation of threat, worrying, control of uncertain situations, and seeking reassurance (Part B. Community members (N = 1046; Mean age = 36.69 ± 12.31 years; 61% females completed the Intolerance of Uncertainty Inventory with the Beck Depression Inventory-II and the State-Trait Anxiety Inventory. Part A demonstrated a robust unidimensional structure and an excellent convergent validity with Part B. A bifactor model was the best fitting model for Part B. Based on these results, we compared the hierarchical factor scores with summated ratings clinical proxy groups reporting anxiety and depression symptoms. Summated rating scores were associated with both depression and anxiety and proportionally increased with the co-occurrence of depressive and anxious symptoms. By contrast, hierarchical scores were useful to detect which facets mostly separated between for depression and anxiety groups. In sum, Part A was a reliable and valid transdiagnostic measure of Intolerance of Uncertainty. The Part B was arguably more useful for assessing clinical manifestations of Intolerance of Uncertainty for specific disorders, provided that hierarchical scores are used. Overall, our study suggest that clinical assessments might need to shift toward hierarchical factor scores.

Main features and possibilities of the new scale module for calculation of sensitivity and uncertainty by sampling: SAMPLER; Principlaes caracteristicas y posibilidades del nuevo modulo de SCALE 6.2 para calculo de sensibilidad e incertidumbre por muestreo: SAMPLER

Energy Technology Data Exchange (ETDEWEB)

Mesado, C.; Miro, R.; Barrachina, T.; Verdu, G.

2014-07-01

Due to the importance of calculating sensitivity and uncertainty in the calculation of field engineering, and especially in the nuclear world, it has been decided to present the main features of the new module present in the new version of SCALE 6.2 (currently beta 3 version) called SAMPLER. This module allows the calculation of uncertainty in a wide range of effective sections, neutron parameters, composition and physical parameters. However, the calculation of sensitivity is not present in the beta 3 release. Even so, this module can be helpful for participants of the proposed Benchmark by Expert Group on Uncertainty Analysis in Modelling (UAM-LWR), as well as to analysts in general. (Author)

Uncertainty Quantification with Applications to Engineering Problems

DEFF Research Database (Denmark)

Bigoni, Daniele

in measurements, predictions and manufacturing, and we can say that any dynamical system used in engineering is subject to some of these uncertainties. The first part of this work presents an overview of the mathematical framework used in Uncertainty Quantification (UQ) analysis and introduces the spectral tensor...... and thus the UQ analysis of the associated systems will benefit greatly from the application of methods which require few function evaluations. We first consider the propagation of the uncertainty and the sensitivity analysis of the non-linear dynamics of railway vehicles with suspension components whose......-scale problems, where efficient methods are necessary with today’s computational resources. The outcome of this work was also the creation of several freely available Python modules for Uncertainty Quantification, which are listed and described in the appendix....

Identification of the underlying factor structure of the Derriford Appearance Scale 24

Directory of Open Access Journals (Sweden)

Timothy P. Moss

2015-07-01

Full Text Available Background. The Derriford Appearance Scale24 (DAS24 is a widely used measure of distress and dysfunction in relation to self-consciousness of appearance. It has been used in clinical and research settings, and translated into numerous European and Asian languages. Hitherto, no study has conducted an analysis to determine the underlying factor structure of the scale.Methods. A large (n = 1,265 sample of community and hospital patients with a visible difference were recruited face to face or by post, and completed the DAS24.Results. A two factor solution was generated. An evaluation of the congruence of the factor solutions on each of the the hospital and the community samples using Tucker’s Coefficient of Congruence (rc = .979 and confirmatory factor analysis, which demonstrated a consistent factor structure. A main factor, general self consciousness (GSC, was represented by 18 items. Six items comprised a second factor, sexual and body self-consciousness (SBSC. The SBSC scale demonstrated greater sensitivity and specificity in identifying distress for sexually significant areas of the body.Discussion. The factor structure of the DAS24 facilitates a more nuanced interpretation of scores using this scale. Two conceptually and statistically coherent sub-scales were identified. The SBSC sub-scale offers a means of identifying distress and dysfunction around sexually significant areas of the body not previously possible with this scale.

FACTOR STRUCTURE OF THE BRIEF NEGATIVE SYMPTOM SCALE

OpenAIRE

Strauss, Gregory P.; Hong, L. Elliot; Gold, James M.; Buchanan, Robert W.; McMahon, Robert P.; Keller, William R.; Fischer, Bernard A.; Catalano, Lauren T.; Culbreth, Adam J.; Carpenter, William T.; Kirkpatrick, Brian

2012-01-01

The current study examined the factor structure of the Brief Negative Symptom Scale (BNSS), a next-generation negative symptom rating instrument developed in response to the NIMH-sponsored Consensus Development Conference on Negative Symptoms. Participants included 146 individuals with a DSM-IV diagnosis of schizophrenia or schizoaffective disorder. Principal axis factoring indicated two distinct factors explaining 68.7% of the variance. Similar to previous findings, the factors reflected mot...

A measurement of the calorimeter response to single hadrons and determination of the jet energy scale uncertainty using LHC Run-1 pp-collision data with the ATLAS detector

Energy Technology Data Exchange (ETDEWEB)

Aaboud, M. [Univ. Mohamed Premier et LPTPM, Oujda (Morocco). Faculte des Sciences; Aad, G. [CPPM, Aix-Marseille Univ. et CNRS/IN2P3, Marseille (France); Abbott, B. [Oklahoma Univ., Norman, OK (United States). Homer L. Dodge Dept. of Physics and Astronomy; Collaboration: ATLAS Collaboration; and others

2017-01-15

A measurement of the calorimeter response to isolated charged hadrons in the ATLAS detector at the LHC is presented. This measurement is performed with 3.2 nb{sup -1} of proton-proton collision data at √(s) = 7 TeV from 2010 and 0.1 nb{sup -1} of data at √(s) = 8 TeV from 2012. A number of aspects of the calorimeter response to isolated hadrons are explored. After accounting for energy deposited by neutral particles, there is a 5% discrepancy in the modelling, using various sets of Geant4 hadronic physics models, of the calorimeter response to isolated charged hadrons in the central calorimeter region. The description of the response to anti-protons at low momenta is found to be improved with respect to previous analyses. The electromagnetic and hadronic calorimeters are also examined separately, and the detector simulation is found to describe the response in the hadronic calorimeter well. The jet energy scale uncertainty and correlations in scale between jets of different momenta and pseudorapidity are derived based on these studies. The uncertainty is 2-5% for jets with transverse momenta above 2 TeV, where this method provides the jet energy scale uncertainty for ATLAS. (orig.)

On the EU approach for DEMO architecture exploration and dealing with uncertainties

Energy Technology Data Exchange (ETDEWEB)

Coleman, M., E-mail: matti.coleman@euro-fusion.org [EUROfusion Consortium, Boltzmannstraße 2, 85748 Garching (Germany); CCFE Fusion Association, Culham Science Centre, Abingdon, Oxfordshire OX14 3DB (United Kingdom); Maviglia, F.; Bachmann, C. [EUROfusion Consortium, Boltzmannstraße 2, 85748 Garching (Germany); Anthony, J. [CCFE Fusion Association, Culham Science Centre, Abingdon, Oxfordshire OX14 3DB (United Kingdom); Federici, G. [EUROfusion Consortium, Boltzmannstraße 2, 85748 Garching (Germany); Shannon, M. [EUROfusion Consortium, Boltzmannstraße 2, 85748 Garching (Germany); CCFE Fusion Association, Culham Science Centre, Abingdon, Oxfordshire OX14 3DB (United Kingdom); Wenninger, R. [EUROfusion Consortium, Boltzmannstraße 2, 85748 Garching (Germany); Max-Planck-Institut für Plasmaphysik, 85748 Garching (Germany)

2016-11-01

Highlights: • The issue of epistemic uncertainties in the DEMO design basis is described. • An approach to tackle uncertainty by investigating plant architectures is proposed. • The first wall heat load uncertainty is addressed following the proposed approach. - Abstract: One of the difficulties inherent in designing a future fusion reactor is dealing with uncertainty. As the major step between ITER and the commercial exploitation of nuclear fusion energy, DEMO will have to address many challenges – the natures of which are still not fully known. Unlike fission reactors, fusion reactors suffer from the intrinsic complexity of the tokamak (numerous interdependent system parameters) and from the dependence of plasma physics on scale – prohibiting design exploration founded on incremental progression and small-scale experimentation. For DEMO, this means that significant technical uncertainties will exist for some time to come, and a systems engineering design exploration approach must be developed to explore the reactor architecture when faced with these uncertainties. Important uncertainties in the context of fusion reactor design are discussed and a strategy for dealing with these is presented, treating the uncertainty in the first wall loads as an example.

Quantifying uncertainty in NDSHA estimates due to earthquake catalogue

Science.gov (United States)

Magrin, Andrea; Peresan, Antonella; Vaccari, Franco; Panza, Giuliano

2014-05-01

of ground motion error can therefore be the factor of 2, intrinsic in MCS scale. We tested this hypothesis by the analysis of uncertainty in ground motion maps due to the catalogue random errors in magnitude and localization.

Validation of an uncertainty of illness scale adapted to use with Spanish emergency department patients and their accompanying relatives or friends.

Science.gov (United States)

Ruymán Brito-Brito, Pedro; García-Tesouro, Esther; Fernández-Gutiérrez, Domingo Ángel; García-Hernández, Alfonso Miguel; Fernández-Gutiérrez, Raquel; Burillo-Putze, Guillermo

2018-01-01

To validate a Spanish adaptation of the Mishel Uncertainty of Illness Scale for use with emergency-department (ED) patients and their accompanying relatives or friends (the UIS-ED). We first developed a version of the questionnaire for Spanish ED situations. Next we assessed the content validity index for each of its items, revised it, and reassessed its face validity to produce a second version, which we then piloted in 20 hospital ED patients. A third revised version was then validated in a population of 320 adults (160 patients and 160 accompanying persons) who attended the ED between November 2015 and September 2016. The 12-item UIS-ED (60 points) was administered by 2 nurses while the patients and accompanying persons were in the ED. We gathered sociodemographic and clinical data as well as the subjects' perception about the information they were given. The mean (SD) uncertainty score among patients was 29 (11) points. Accompanying persons had a mean score of 36 (13) points. Factorial analysis confirmed the instrument's construct validity, finding that both dimensions of the original Mishel scale (complexity and ambiguity) were present in 6 items each. Factorial analysis explained 60% of the total variance in the patient version and 67% of the variance in the version for accompanying persons. Reliability statistics were good, with Cronbach's α values ranging from 0.912 to 0.938. Split-half reliability statistics ranged from 0.901 to 0.933. Correlations were significant in the analysis of convergent validity. The UIS-ED questionnaire may prove to be a simple, valid, and reliable way for assessing uncertainty in patients and their accompanying friends or relatives attending Spanish EDs.

Thermal properties at Aespoe HRL. Analysis of distribution and scale factors

International Nuclear Information System (INIS)

Sundberg, Jan

2003-04-01

A thermal model for the Aespoe HRL as well as a general strategy for thermal modelling is under development. As a part of that work, thermal conductivities have been modelled from reference values of thermal conductivity of different minerals and from the mineral composition of all Aespoe samples in the Sicada database. The produced thermal conductivity database has been analysed in terms of frequency, type of distribution, spatial distribution, variogram etc. A correction factor has been estimated to compensate for discrepancies between measured and calculated values. The calculated values have been corrected according to measured values. The data has been analysed according to different rock types. However, there are uncertainties in the base material of rock classification, mainly due to problem to distinguish between Aespoe diorite and Aevroe granite, but also because of different classification systems. There is a relationship between thermal conductivity and density for the rock types at Aespoe. Equations of the relationship have been developed based on all thermal conductivity, heat capacity and density measurements. The equations have been tested on two bore holes at Aespoe with promising results. It may be possible to evaluate the spatial distribution of the thermal properties from density loggings. However, more work is needed to develop a complete model including the handling of high and low density zones. There is an insufficient knowledge in the variation of thermal properties at different scales. If the whole variation within a rock type is in the cm-m scale the thermal influence on the canister is small. This is due to the fact that the small-scale variation in thermal properties is mainly averaged out in the 5-10 m scale. If the main variation within rock types is in the 5-10 m scale there is probably a significant effect on the canister temperature. However, it is likely that the observed variation occurs in both these scales. Simulation has been

Multi-Scale Fusion of Information for Uncertainty Quantification and Management in Large-Scale Simulations

Science.gov (United States)

2015-12-02

of completely new nonlinear Malliavin calculus . This type of calculus is important for the analysis and simulation of stationary and/or “causal...been limited by the fact that it requires the solution of an optimization problem with noisy gradients . When using deterministic optimization schemes...under uncertainty. We tested new developments on nonlinear Malliavin calculus , combining reduced basis methods with ANOVA, model validation, on

Uncertainty Instability Risk Analysis of High Concrete Arch Dam Abutments

Directory of Open Access Journals (Sweden)

Xin Cao

2017-01-01

Full Text Available The uncertainties associated with concrete arch dams rise with the increased height of dams. Given the uncertainties associated with influencing factors, the stability of high arch dam abutments as a fuzzy random event was studied. In addition, given the randomness and fuzziness of calculation parameters as well as the failure criterion, hazard point and hazard surface uncertainty instability risk ratio models were proposed for high arch dam abutments on the basis of credibility theory. The uncertainty instability failure criterion was derived through the analysis of the progressive instability failure process on the basis of Shannon’s entropy theory. The uncertainties associated with influencing factors were quantized by probability or possibility distribution assignments. Gaussian random theory was used to generate random realizations for influence factors with spatial variability. The uncertainty stability analysis method was proposed by combining the finite element analysis and the limit equilibrium method. The instability risk ratio was calculated using the Monte Carlo simulation method and fuzzy random postprocessing. Results corroborate that the modeling approach is sound and that the calculation method is feasible.

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)

BEPU methods and combining of uncertainties

International Nuclear Information System (INIS)

Prosek, A.; Mavko, B.

2004-01-01

After approval of the revised rule on the acceptance of emergency core cooling system (ECCS) performance in 1988 there has been significant interest in the development of codes and methodologies for best-estimate loss-of-coolant accident (LOCAs) analyses. The Code Scaling, Applicability and Uncertainty (CSAU) evaluation method was developed and demonstrated for large-break (LB) LOCA in a pressurized water reactor. Later several new best estimate plus uncertainty methods (BEPUs) were developed in the world. The purpose of the paper is to identify and compare the statistical approaches of BEPU methods and present their important plant and licensing applications. The study showed that uncertainty analysis with random sampling of input parameters and the use of order statistics for desired tolerance limits of output parameters is today commonly accepted approach. The existing BEPU methods seems mature enough while the future research may be focused on the codes with internal assessment of uncertainty. (author)

A new approach to reduce uncertainties in space radiation cancer risk predictions.

Directory of Open Access Journals (Sweden)

Francis A Cucinotta

Full Text Available The prediction of space radiation induced cancer risk carries large uncertainties with two of the largest uncertainties being radiation quality and dose-rate effects. In risk models the ratio of the quality factor (QF to the dose and dose-rate reduction effectiveness factor (DDREF parameter is used to scale organ doses for cosmic ray proton and high charge and energy (HZE particles to a hazard rate for γ-rays derived from human epidemiology data. In previous work, particle track structure concepts were used to formulate a space radiation QF function that is dependent on particle charge number Z, and kinetic energy per atomic mass unit, E. QF uncertainties where represented by subjective probability distribution functions (PDF for the three QF parameters that described its maximum value and shape parameters for Z and E dependences. Here I report on an analysis of a maximum QF parameter and its uncertainty using mouse tumor induction data. Because experimental data for risks at low doses of γ-rays are highly uncertain which impacts estimates of maximum values of relative biological effectiveness (RBEmax, I developed an alternate QF model, denoted QFγAcute where QFs are defined relative to higher acute γ-ray doses (0.5 to 3 Gy. The alternate model reduces the dependence of risk projections on the DDREF, however a DDREF is still needed for risk estimates for high-energy protons and other primary or secondary sparsely ionizing space radiation components. Risk projections (upper confidence levels (CL for space missions show a reduction of about 40% (CL∼50% using the QFγAcute model compared the QFs based on RBEmax and about 25% (CL∼35% compared to previous estimates. In addition, I discuss how a possible qualitative difference leading to increased tumor lethality for HZE particles compared to low LET radiation and background tumors remains a large uncertainty in risk estimates.

A scaling approach to project regional sea level rise and its uncertainties

Directory of Open Access Journals (Sweden)

M. Perrette

2013-01-01

Full Text Available Climate change causes global mean sea level to rise due to thermal expansion of seawater and loss of land ice from mountain glaciers, ice caps and ice sheets. Locally, sea level can strongly deviate from the global mean rise due to changes in wind and ocean currents. In addition, gravitational adjustments redistribute seawater away from shrinking ice masses. However, the land ice contribution to sea level rise (SLR remains very challenging to model, and comprehensive regional sea level projections, which include appropriate gravitational adjustments, are still a nascent field (Katsman et al., 2011; Slangen et al., 2011. Here, we present an alternative approach to derive regional sea level changes for a range of emission and land ice melt scenarios, combining probabilistic forecasts of a simple climate model (MAGICC6 with the new CMIP5 general circulation models. The contribution from ice sheets varies considerably depending on the assumptions for the ice sheet projections, and thus represents sizeable uncertainties for future sea level rise. However, several consistent and robust patterns emerge from our analysis: at low latitudes, especially in the Indian Ocean and Western Pacific, sea level will likely rise more than the global mean (mostly by 10–20%. Around the northeastern Atlantic and the northeastern Pacific coasts, sea level will rise less than the global average or, in some rare cases, even fall. In the northwestern Atlantic, along the American coast, a strong dynamic sea level rise is counteracted by gravitational depression due to Greenland ice melt; whether sea level will be above- or below-average will depend on the relative contribution of these two factors. Our regional sea level projections and the diagnosed uncertainties provide an improved basis for coastal impact analysis and infrastructure planning for adaptation to climate change.

Dynamic Simulation, Sensitivity and Uncertainty Analysis of a Demonstration Scale Lignocellulosic Enzymatic Hydrolysis Process

DEFF Research Database (Denmark)

Prunescu, Remus Mihail; Sin, Gürkan

2014-01-01

This study presents the uncertainty and sensitivity analysis of a lignocellulosic enzymatic hydrolysis model considering both model and feed parameters as sources of uncertainty. The dynamic model is parametrized for accommodating various types of biomass, and different enzymatic complexes...

Phenomenon of Uncertainty as a Subjective Experience

Directory of Open Access Journals (Sweden)

Lifintseva A.A.

2018-04-01

Full Text Available The phenomenon of uncertainty in illness of patients is discussed and analyzed in this article. Uncertainty in illness is a condition that accompanies the patient from the moment of appearance of the first somatic symptoms of the disease and could be strengthened or weakened thanks to many psychosocial factors. The level of uncertainty is related to the level of stress, emotional disadaptation, affective states, coping strategies, mechanisms of psychological defense, etc. Uncertainty can perform destructive functions, acting as a trigger for stressful conditions and launching negative emotional experiences. As a positive function of uncertainty, one can note a possible positive interpretation of the patient's disease. In addition, the state of uncertainty allows the patient to activate the resources of coping with the disease, among which the leading role belongs to social support.

An uncertainty principle for star formation - II. A new method for characterising the cloud-scale physics of star formation and feedback across cosmic history

Science.gov (United States)

Kruijssen, J. M. Diederik; Schruba, Andreas; Hygate, Alexander P. S.; Hu, Chia-Yu; Haydon, Daniel T.; Longmore, Steven N.

2018-05-01

The cloud-scale physics of star formation and feedback represent the main uncertainty in galaxy formation studies. Progress is hampered by the limited empirical constraints outside the restricted environment of the Local Group. In particular, the poorly-quantified time evolution of the molecular cloud lifecycle, star formation, and feedback obstructs robust predictions on the scales smaller than the disc scale height that are resolved in modern galaxy formation simulations. We present a new statistical method to derive the evolutionary timeline of molecular clouds and star-forming regions. By quantifying the excess or deficit of the gas-to-stellar flux ratio around peaks of gas or star formation tracer emission, we directly measure the relative rarity of these peaks, which allows us to derive their lifetimes. We present a step-by-step, quantitative description of the method and demonstrate its practical application. The method's accuracy is tested in nearly 300 experiments using simulated galaxy maps, showing that it is capable of constraining the molecular cloud lifetime and feedback time-scale to <0.1 dex precision. Access to the evolutionary timeline provides a variety of additional physical quantities, such as the cloud-scale star formation efficiency, the feedback outflow velocity, the mass loading factor, and the feedback energy or momentum coupling efficiencies to the ambient medium. We show that the results are robust for a wide variety of gas and star formation tracers, spatial resolutions, galaxy inclinations, and galaxy sizes. Finally, we demonstrate that our method can be applied out to high redshift (z≲ 4) with a feasible time investment on current large-scale observatories. This is a major shift from previous studies that constrained the physics of star formation and feedback in the immediate vicinity of the Sun.

Quantum wells and the generalized uncertainty principle

International Nuclear Information System (INIS)

Blado, Gardo; Owens, Constance; Meyers, Vincent

2014-01-01

The finite and infinite square wells are potentials typically discussed in undergraduate quantum mechanics courses. In this paper, we discuss these potentials in the light of the recent studies of the modification of the Heisenberg uncertainty principle into a generalized uncertainty principle (GUP) as a consequence of attempts to formulate a quantum theory of gravity. The fundamental concepts of the minimal length scale and the GUP are discussed and the modified energy eigenvalues and transmission coefficient are derived. (paper)

Uncertainty information in climate data records from Earth observation

Science.gov (United States)

Merchant, Christopher J.; Paul, Frank; Popp, Thomas; Ablain, Michael; Bontemps, Sophie; Defourny, Pierre; Hollmann, Rainer; Lavergne, Thomas; Laeng, Alexandra; de Leeuw, Gerrit; Mittaz, Jonathan; Poulsen, Caroline; Povey, Adam C.; Reuter, Max; Sathyendranath, Shubha; Sandven, Stein; Sofieva, Viktoria F.; Wagner, Wolfgang

2017-07-01

The question of how to derive and present uncertainty information in climate data records (CDRs) has received sustained attention within the European Space Agency Climate Change Initiative (CCI), a programme to generate CDRs addressing a range of essential climate variables (ECVs) from satellite data. Here, we review the nature, mathematics, practicalities, and communication of uncertainty information in CDRs from Earth observations. This review paper argues that CDRs derived from satellite-based Earth observation (EO) should include rigorous uncertainty information to support the application of the data in contexts such as policy, climate modelling, and numerical weather prediction reanalysis. Uncertainty, error, and quality are distinct concepts, and the case is made that CDR products should follow international metrological norms for presenting quantified uncertainty. As a baseline for good practice, total standard uncertainty should be quantified per datum in a CDR, meaning that uncertainty estimates should clearly discriminate more and less certain data. In this case, flags for data quality should not duplicate uncertainty information, but instead describe complementary information (such as the confidence in the uncertainty estimate provided or indicators of conditions violating the retrieval assumptions). The paper discusses the many sources of error in CDRs, noting that different errors may be correlated across a wide range of timescales and space scales. Error effects that contribute negligibly to the total uncertainty in a single-satellite measurement can be the dominant sources of uncertainty in a CDR on the large space scales and long timescales that are highly relevant for some climate applications. For this reason, identifying and characterizing the relevant sources of uncertainty for CDRs is particularly challenging. The characterization of uncertainty caused by a given error effect involves assessing the magnitude of the effect, the shape of the

Dimensions of assertiveness: factors underlying the college self-expression scale.

Science.gov (United States)

Kipper, D A; Jaffe, Y

1978-02-01

A total of 447 Israeli students, both males and females, from four educational institutions were administered the College Self-expression Scale, a measure of assertiveness. The obtained responses were factor analyzed using the principal axis solution and the varimax rotation method. The results showed four main factors which included 43 of the 50 items of the original scale. These factors were identified as the willingness to take risks in interpersonal interactions, the ability to communicate feelings, setting rules and rectifying injustices, and the presence or absence of a tendency to invoke a self-punitive attitude. The findings were interpreted as adding support to the validity of the scale as a measure of assertiveness.

The uncertainties in estimating measurement uncertainties

International Nuclear Information System (INIS)

Clark, J.P.; Shull, A.H.

1994-01-01

All measurements include some error. Whether measurements are used for accountability, environmental programs or process support, they are of little value unless accompanied by an estimate of the measurements uncertainty. This fact is often overlooked by the individuals who need measurements to make decisions. This paper will discuss the concepts of measurement, measurements errors (accuracy or bias and precision or random error), physical and error models, measurement control programs, examples of measurement uncertainty, and uncertainty as related to measurement quality. Measurements are comparisons of unknowns to knowns, estimates of some true value plus uncertainty; and are no better than the standards to which they are compared. Direct comparisons of unknowns that match the composition of known standards will normally have small uncertainties. In the real world, measurements usually involve indirect comparisons of significantly different materials (e.g., measuring a physical property of a chemical element in a sample having a matrix that is significantly different from calibration standards matrix). Consequently, there are many sources of error involved in measurement processes that can affect the quality of a measurement and its associated uncertainty. How the uncertainty estimates are determined and what they mean is as important as the measurement. The process of calculating the uncertainty of a measurement itself has uncertainties that must be handled correctly. Examples of chemistry laboratory measurement will be reviewed in this report and recommendations made for improving measurement uncertainties

Quantification of Uncertainty in Extreme Scale Computations (QUEST)

Energy Technology Data Exchange (ETDEWEB)

Ghanem, Roger [Univ. of Southern California, Los Angeles, CA (United States)

2017-04-18

QUEST was a SciDAC Institute comprising Sandia National Laboratories, Los Alamos National Laboratory, the University of Southern California, the Massachusetts Institute of Technology, the University of Texas at Austin, and Duke University. The mission of QUEST is to: (1) develop a broad class of uncertainty quantification (UQ) methods/tools, and (2) provide UQ expertise and software to other SciDAC projects, thereby enabling/guiding their UQ activities. The USC effort centered on the development of reduced models and efficient algorithms for implementing various components of the UQ pipeline. USC personnel were responsible for the development of adaptive bases, adaptive quadrature, and reduced models to be used in estimation and inference.

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

Differential effects of uncertainty on LPP responses to emotional events during explicit and implicit anticipation.

Science.gov (United States)

Lin, Huiyan; Liang, Jiafeng; Jin, Hua; Zhao, Dongmei

2018-07-01

Previous studies have investigated whether uncertainty influences neural responses to emotional events. The findings of such studies, particularly with respect to event-related potentials (ERPs), have been controversial due to several factors, such as the stimuli that serve as cues and the emotional content of the events. However, it is still unknown whether the effects of uncertainty on ERP responses to emotional events are influenced by anticipation patterns (e.g., explicit or implicit anticipation). To address this issue, participants in the present study were presented with anticipatory cues and then emotional (negative and neutral) pictures. The cues either did or did not signify the emotional content of the upcoming picture. In the inter-stimulus intervals between cues and pictures, participants were asked to estimate the expected probability of the occurrence of a specific emotional category of the subsequent picture based on a scale in the explicit anticipation condition, while in the implicit condition, participants were asked to indicate, using a number on a scale, which color was different from the others. The results revealed that in the explicit condition, uncertainty increased late positive potential (LPP) responses, particularly for negative pictures, whereas LPP responses were larger for certain negative pictures than for uncertain negative pictures in the implicit condition. The findings in the present study suggest that the anticipation pattern influences the effects of uncertainty when evaluation of negative events. Copyright © 2018 Elsevier B.V. All rights reserved.

Technical note: Design flood under hydrological uncertainty

Science.gov (United States)

Botto, Anna; Ganora, Daniele; Claps, Pierluigi; Laio, Francesco

2017-07-01

Planning and verification of hydraulic infrastructures require a design estimate of hydrologic variables, usually provided by frequency analysis, and neglecting hydrologic uncertainty. However, when hydrologic uncertainty is accounted for, the design flood value for a specific return period is no longer a unique value, but is represented by a distribution of values. As a consequence, the design flood is no longer univocally defined, making the design process undetermined. The Uncertainty Compliant Design Flood Estimation (UNCODE) procedure is a novel approach that, starting from a range of possible design flood estimates obtained in uncertain conditions, converges to a single design value. This is obtained through a cost-benefit criterion with additional constraints that is numerically solved in a simulation framework. This paper contributes to promoting a practical use of the UNCODE procedure without resorting to numerical computation. A modified procedure is proposed by using a correction coefficient that modifies the standard (i.e., uncertainty-free) design value on the basis of sample length and return period only. The procedure is robust and parsimonious, as it does not require additional parameters with respect to the traditional uncertainty-free analysis. Simple equations to compute the correction term are provided for a number of probability distributions commonly used to represent the flood frequency curve. The UNCODE procedure, when coupled with this simple correction factor, provides a robust way to manage the hydrologic uncertainty and to go beyond the use of traditional safety factors. With all the other parameters being equal, an increase in the sample length reduces the correction factor, and thus the construction costs, while still keeping the same safety level.

Uncertainty Analysis of Light Water Reactor Fuel Lattices

Directory of Open Access Journals (Sweden)

C. Arenas

2013-01-01

Full Text Available The study explored the calculation of uncertainty based on available cross-section covariance data and computational tool on fuel lattice levels, which included pin cell and the fuel assembly models. Uncertainty variations due to temperatures changes and different fuel compositions are the main focus of this analysis. Selected assemblies and unit pin cells were analyzed according to the OECD LWR UAM benchmark specifications. Criticality and uncertainty analysis were performed using TSUNAMI-2D sequence in SCALE 6.1. It was found that uncertainties increase with increasing temperature, while kinf decreases. This increase in the uncertainty is due to the increase in sensitivity of the largest contributing reaction of uncertainty, namely, the neutron capture reaction 238U(n, γ due to the Doppler broadening. In addition, three types (UOX, MOX, and UOX-Gd2O3 of fuel material compositions were analyzed. A remarkable increase in uncertainty in kinf was observed for the case of MOX fuel. The increase in uncertainty of kinf in MOX fuel was nearly twice the corresponding value in UOX fuel. The neutron-nuclide reaction of 238U, mainly inelastic scattering (n, n′, contributed the most to the uncertainties in the MOX fuel, shifting the neutron spectrum to higher energy compared to the UOX fuel.

Uncertainty quantification in nanomechanical measurements using the atomic force microscope

Science.gov (United States)

Ryan Wagner; Robert Moon; Jon Pratt; Gordon Shaw; Arvind Raman

2011-01-01

Quantifying uncertainty in measured properties of nanomaterials is a prerequisite for the manufacture of reliable nanoengineered materials and products. Yet, rigorous uncertainty quantification (UQ) is rarely applied for material property measurements with the atomic force microscope (AFM), a widely used instrument that can measure properties at nanometer scale...

A Bayesian approach for quantification of model uncertainty

International Nuclear Information System (INIS)

Park, Inseok; Amarchinta, Hemanth K.; Grandhi, Ramana V.

2010-01-01

In most engineering problems, more than one model can be created to represent an engineering system's behavior. Uncertainty is inevitably involved in selecting the best model from among the models that are possible. Uncertainty in model selection cannot be ignored, especially when the differences between the predictions of competing models are significant. In this research, a methodology is proposed to quantify model uncertainty using measured differences between experimental data and model outcomes under a Bayesian statistical framework. The adjustment factor approach is used to propagate model uncertainty into prediction of a system response. A nonlinear vibration system is used to demonstrate the processes for implementing the adjustment factor approach. Finally, the methodology is applied on the engineering benefits of a laser peening process, and a confidence band for residual stresses is established to indicate the reliability of model prediction.

Predicted risk of cobalt deficiency in grazing sheep from a geochemical survey; communicating uncertainty with the IPCC verbal scale.

Science.gov (United States)

Lark, R. M.; Ander, E. L.; Cave, M. R.; Knights, K. V.; Glennon, M. M.; Scanlon, R. P.

2014-05-01

Deficiency or excess of certain trace elements in the soil causes problems for agriculture, including disorders of grazing ruminants. Farmers and their advisors in Ireland use index values for the concentration of total soil cobalt and manganese to identify where grazing sheep are at risk of cobalt deficiency. We used cokriging with topsoil data from a regional geochemical survey across six counties of Ireland to form local cokriging predictions of cobalt and manganese concentrations with an attendant distribution which reflects the joint uncertainty of these predictions. From this distribution we then computed conditional probabilities for different combinations of cobalt and manganese index values, and so for the corresponding inferred risk to sheep of cobalt deficiency and the appropriateness of different management interventions. The challenge is to communicate these results effectively to an audience comprising, inter alia, farmers, agronomists and veterinarians. Numerical probabilities are not generally well-understood by non-specialists. For this reason we presented our results as maps using a verbal scale to communicate the probability that a deficiency is indicated by local soil conditions, or that a particular intervention is indicated. In the light of recent research on the effectiveness of the verbal scale used by the Intergovernmental Panel on Climate Change to communicate probabilistic information we reported the geostatistical predictions as follows. First, we use the basic IPCC scale with intensifiers, but we also indicate the corresponding probabilities (as percentages) as recommended by Budescu et al. (2009). Second, we make it clear that the source of uncertainty in these predictions is the spatial variability of soil Co and Mn. The outcome under consideration is therefore that a particular soil management scenario would be indicated if the soil properties were known without error, possible uncertainty about the implications of particular soil

Gridded uncertainty in fossil fuel carbon dioxide emission maps, a CDIAC example

Science.gov (United States)

Andres, Robert J.; Boden, Thomas A.; Higdon, David M.

2016-12-01

Due to a current lack of physical measurements at appropriate spatial and temporal scales, all current global maps and distributions of fossil fuel carbon dioxide (FFCO2) emissions use one or more proxies to distribute those emissions. These proxies and distribution schemes introduce additional uncertainty into these maps. This paper examines the uncertainty associated with the magnitude of gridded FFCO2 emissions. This uncertainty is gridded at the same spatial and temporal scales as the mass magnitude maps. This gridded uncertainty includes uncertainty contributions from the spatial, temporal, proxy, and magnitude components used to create the magnitude map of FFCO2 emissions. Throughout this process, when assumptions had to be made or expert judgment employed, the general tendency in most cases was toward overestimating or increasing the magnitude of uncertainty. The results of the uncertainty analysis reveal a range of 4-190 %, with an average of 120 % (2σ) for populated and FFCO2-emitting grid spaces over annual timescales. This paper also describes a methodological change specific to the creation of the Carbon Dioxide Information Analysis Center (CDIAC) FFCO2 emission maps: the change from a temporally fixed population proxy to a temporally varying population proxy.

Development of a New Scale to Measure Ambiguity Tolerance in Veterinary Students.

Science.gov (United States)

Hammond, Jennifer A; Hancock, Jason; Martin, Margaret S; Jamieson, Susan; Mellor, Dominic J

The ability to cope with ambiguity and feelings of uncertainty is an essential part of professional practice. Research with physicians has identified that intolerance of ambiguity or uncertainty is linked to stress, and some authors have hypothesized that there could be an association between intolerance of ambiguity and burnout. We describe the adaptation of the TAMSAD (Tolerance of Ambiguity in Medical Students and Doctors) scale for use with veterinary students. Exploratory factor analysis supports a uni-dimensional structure for the Ambiguity tolerance construct. Although internal reliability of the 29-item TAMSAD scale is reasonable (α=.50), an alternative 27-item scale (drawn from the original 41 items used to develop TAMSAD) shows higher internal reliability for veterinary students (α=.67). We conclude that there is good evidence to support the validity of this latter TAVS (Tolerance of Ambiguity in Veterinary Students) scale to study ambiguity tolerance in veterinary students.

Incorporating uncertainty in predictive species distribution modelling.

Science.gov (United States)

Beale, Colin M; Lennon, Jack J

2012-01-19

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

Uncertainty governance: an integrated framework for managing and communicating uncertainties

International Nuclear Information System (INIS)

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

2004-01-01

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

Beyond factor analysis: Multidimensionality and the Parkinson's Disease Sleep Scale-Revised.

Directory of Open Access Journals (Sweden)

Maria E Pushpanathan

Full Text Available Many studies have sought to describe the relationship between sleep disturbance and cognition in Parkinson's disease (PD. The Parkinson's Disease Sleep Scale (PDSS and its variants (the Parkinson's disease Sleep Scale-Revised; PDSS-R, and the Parkinson's Disease Sleep Scale-2; PDSS-2 quantify a range of symptoms impacting sleep in only 15 items. However, data from these scales may be problematic as included items have considerable conceptual breadth, and there may be overlap in the constructs assessed. Multidimensional measurement models, accounting for the tendency for items to measure multiple constructs, may be useful more accurately to model variance than traditional confirmatory factor analysis. In the present study, we tested the hypothesis that a multidimensional model (a bifactor model is more appropriate than traditional factor analysis for data generated by these types of scales, using data collected using the PDSS-R as an exemplar. 166 participants diagnosed with idiopathic PD participated in this study. Using PDSS-R data, we compared three models: a unidimensional model; a 3-factor model consisting of sub-factors measuring insomnia, motor symptoms and obstructive sleep apnoea (OSA and REM sleep behaviour disorder (RBD symptoms; and, a confirmatory bifactor model with both a general factor and the same three sub-factors. Only the confirmatory bifactor model achieved satisfactory model fit, suggesting that PDSS-R data are multidimensional. There were differential associations between factor scores and patient characteristics, suggesting that some PDSS-R items, but not others, are influenced by mood and personality in addition to sleep symptoms. Multidimensional measurement models may also be a helpful tool in the PDSS and the PDSS-2 scales and may improve the sensitivity of these instruments.

Do Orthopaedic Surgeons Acknowledge Uncertainty?

Science.gov (United States)

Teunis, Teun; Janssen, Stein; Guitton, Thierry G; Ring, David; Parisien, Robert

2016-06-01

Much of the decision-making in orthopaedics rests on uncertain evidence. Uncertainty is therefore part of our normal daily practice, and yet physician uncertainty regarding treatment could diminish patients' health. It is not known if physician uncertainty is a function of the evidence alone or if other factors are involved. With added experience, uncertainty could be expected to diminish, but perhaps more influential are things like physician confidence, belief in the veracity of what is published, and even one's religious beliefs. In addition, it is plausible that the kind of practice a physician works in can affect the experience of uncertainty. Practicing physicians may not be immediately aware of these effects on how uncertainty is experienced in their clinical decision-making. We asked: (1) Does uncertainty and overconfidence bias decrease with years of practice? (2) What sociodemographic factors are independently associated with less recognition of uncertainty, in particular belief in God or other deity or deities, and how is atheism associated with recognition of uncertainty? (3) Do confidence bias (confidence that one's skill is greater than it actually is), degree of trust in the orthopaedic evidence, and degree of statistical sophistication correlate independently with recognition of uncertainty? We created a survey to establish an overall recognition of uncertainty score (four questions), trust in the orthopaedic evidence base (four questions), confidence bias (three questions), and statistical understanding (six questions). Seven hundred six members of the Science of Variation Group, a collaboration that aims to study variation in the definition and treatment of human illness, were approached to complete our survey. This group represents mainly orthopaedic surgeons specializing in trauma or hand and wrist surgery, practicing in Europe and North America, of whom the majority is involved in teaching. Approximately half of the group has more than 10 years

Survey and Evaluate Uncertainty Quantification Methodologies

Energy Technology Data Exchange (ETDEWEB)

Lin, Guang; Engel, David W.; Eslinger, Paul W.

2012-02-01

The Carbon Capture Simulation Initiative (CCSI) is a partnership among national laboratories, industry and academic institutions that will develop and deploy state-of-the-art computational modeling and simulation tools to accelerate the commercialization of carbon capture technologies from discovery to development, demonstration, and ultimately the widespread deployment to hundreds of power plants. The CCSI Toolset will provide end users in industry with a comprehensive, integrated suite of scientifically validated models with uncertainty quantification, optimization, risk analysis and decision making capabilities. The CCSI Toolset will incorporate commercial and open-source software currently in use by industry and will also develop new software tools as necessary to fill technology gaps identified during execution of the project. The CCSI Toolset will (1) enable promising concepts to be more quickly identified through rapid computational screening of devices and processes; (2) reduce the time to design and troubleshoot new devices and processes; (3) quantify the technical risk in taking technology from laboratory-scale to commercial-scale; and (4) stabilize deployment costs more quickly by replacing some of the physical operational tests with virtual power plant simulations. The goal of CCSI is to deliver a toolset that can simulate the scale-up of a broad set of new carbon capture technologies from laboratory scale to full commercial scale. To provide a framework around which the toolset can be developed and demonstrated, we will focus on three Industrial Challenge Problems (ICPs) related to carbon capture technologies relevant to U.S. pulverized coal (PC) power plants. Post combustion capture by solid sorbents is the technology focus of the initial ICP (referred to as ICP A). The goal of the uncertainty quantification (UQ) task (Task 6) is to provide a set of capabilities to the user community for the quantification of uncertainties associated with the carbon

Predicting the cosmological constant with the scale-factor cutoff measure

International Nuclear Information System (INIS)

De Simone, Andrea; Guth, Alan H.; Salem, Michael P.; Vilenkin, Alexander

2008-01-01

It is well known that anthropic selection from a landscape with a flat prior distribution of cosmological constant Λ gives a reasonable fit to observation. However, a realistic model of the multiverse has a physical volume that diverges with time, and the predicted distribution of Λ depends on how the spacetime volume is regulated. A very promising method of regulation uses a scale-factor cutoff, which avoids a number of serious problems that arise in other approaches. In particular, the scale-factor cutoff avoids the 'youngness problem' (high probability of living in a much younger universe) and the 'Q and G catastrophes' (high probability for the primordial density contrast Q and gravitational constant G to have extremely large or small values). We apply the scale-factor cutoff measure to the probability distribution of Λ, considering both positive and negative values. The results are in good agreement with observation. In particular, the scale-factor cutoff strongly suppresses the probability for values of Λ that are more than about 10 times the observed value. We also discuss qualitatively the prediction for the density parameter Ω, indicating that with this measure there is a possibility of detectable negative curvature.

Disentangling Wording and Substantive Factors in the Spiritual Well-Being Scale.

Science.gov (United States)

Murray, Aja L; Johnson, Wendy; Gow, Alan J; Deary, Ian J

2015-05-01

We evaluated the extent to which the Spiritual Well-Being Scale (SWBS) may help to meet the need for multidimensional, psychometrically sophisticated measures of spiritual and religious traits. Although the various forms of validity of the scale have, for the most part, been supported by psychometric studies, conflicting evidence surrounding its dimensionality has called into question its structural validity. Specifically, numerous authors have suggested that a more appropriate factor structure for the SWBS includes further substantive factors in addition to the 2 factors that the scale was originally intended to measure. In the current study, we attempted to resolve these debates using a combination of exploratory and confirmatory factor analysis based investigations in the Lothian Birth Cohort, 1921 study. Our analyses suggested that the additional factors suggested in previous studies may not have reflected substantive constructs; but rather, common variance due to methodological factors.

Stochastic multi-scale analysis of homogenised properties considering uncertainties in cellular solid microstructures using a first-order perturbation

Directory of Open Access Journals (Sweden)

Khairul Salleh Basaruddin

Full Text Available Randomness in the microstructure due to variations in microscopic properties and geometrical information is used to predict the stochastically homogenised properties of cellular media. Two stochastic problems at the micro-scale level that commonly occur due to fabrication inaccuracies, degradation mechanisms or natural heterogeneity were analysed using a stochastic homogenisation method based on a first-order perturbation. First, the influence of Young's modulus variation in an adhesive on the macroscopic properties of an aluminium-adhesive honeycomb structure was investigated. The fluctuations in the microscopic properties were then combined by varying the microstructure periodicity in a corrugated-core sandwich plate to obtain the variation of the homogenised property. The numerical results show that the uncertainties in the microstructure affect the dispersion of the homogenised property. These results indicate the importance of the presented stochastic multi-scale analysis for the design and fabrication of cellular solids when considering microscopic random variation.

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.

Statistical methodology for discrete fracture model - including fracture size, orientation uncertainty together with intensity uncertainty and variability

Energy Technology Data Exchange (ETDEWEB)

Darcel, C. (Itasca Consultants SAS (France)); Davy, P.; Le Goc, R.; Dreuzy, J.R. de; Bour, O. (Geosciences Rennes, UMR 6118 CNRS, Univ. def Rennes, Rennes (France))

2009-11-15

the lineament scale (k{sub t} = 2) on the other, addresses the issue of the nature of the transition. We develop a new 'mechanistic' model that could help in modeling why and where this transition can occur. The transition between both regimes would occur for a fracture length of 1-10 m and even at a smaller scale for the few outcrops that follow the self-similar density model. A consequence for the disposal issue is that the model that is likely to apply in the 'blind' scale window between 10-100 m is the self-similar model as it is defined for large-scale lineaments. The self-similar model, as it is measured for some outcrops and most lineament maps, is definitely worth being investigated as a reference for scales above 1-10 m. In the rest of the report, we develop a methodology for incorporating uncertainty and variability into the DFN modeling. Fracturing properties arise from complex processes which produce an intrinsic variability; characterizing this variability as an admissible variation of model parameter or as the division of the site into subdomains with distinct DFN models is a critical point of the modeling effort. Moreover, the DFN model encompasses a part of uncertainty, due to data inherent uncertainties and sampling limits. Both effects must be quantified and incorporated into the DFN site model definition process. In that context, all available borehole data including recording of fracture intercept positions, pole orientation and relative uncertainties are used as the basis for the methodological development and further site model assessment. An elementary dataset contains a set of discrete fracture intercepts from which a parent orientation/density distribution can be computed. The elementary bricks of the site, from which these initial parent density distributions are computed, rely on the former Single Hole Interpretation division of the boreholes into sections whose local boundaries are expected to reflect - locally - geology

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)

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

Uncertainty dimensions of information behaviour in a group based problem solving context

DEFF Research Database (Denmark)

Hyldegård, Jette

2009-01-01

This paper presents a study of uncertainty dimensions of information behaviour in a group based problem solving context. After a presentation of the cognitive uncertainty dimension underlying Kuhlthau's ISP-model, uncertainty factors associated with personality, the work task situation and social...... members' experiences of uncertainty differ from the individual information seeker in Kuhlthau's ISP-model, and how this experience may be related to personal, work task and social factors. A number of methods have been employed to collect data on each group member during the assignment process......: a demographic survey, a personality test, 3 process surveys, 3 diaries and 3 interviews. It was found that group members' experiences of uncertainty did not correspond with the ISP-model in that other factors beyond the mere information searching process seemed to intermingle with the complex process...

Uncertainty analysis of scintillometers methods in measuring sensible heat fluxes of forest ecosystem

Science.gov (United States)

Zheng, N.

2017-12-01

Sensible heat flux (H) is one of the driving factors of surface turbulent motion and energy exchange. Therefore, it is particularly important to measure sensible heat flux accurately at the regional scale. However, due to the heterogeneity of the underlying surface, hydrothermal regime, and different weather conditions, it is difficult to estimate the represented flux at the kilometer scale. The scintillometer have been developed into an effective and universal equipment for deriving heat flux at the regional-scale which based on the turbulence effect of light in the atmosphere since the 1980s. The parameter directly obtained by the scintillometer is the structure parameter of the refractive index of air based on the changes of light intensity fluctuation. Combine with parameters such as temperature structure parameter, zero-plane displacement, surface roughness, wind velocity, air temperature and the other meteorological data heat fluxes can be derived. These additional parameters increase the uncertainties of flux because the difference between the actual feature of turbulent motion and the applicable conditions of turbulence theory. Most previous studies often focused on the constant flux layers that are above the rough sub-layers and homogeneous flat surfaces underlying surfaces with suitable weather conditions. Therefore, the criteria and modified forms of key parameters are invariable. In this study, we conduct investment over the hilly area of northern China with different plants, such as cork oak, cedar-black and locust. On the basis of key research on the threshold and modified forms of saturation with different turbulence intensity, modified forms of Bowen ratio with different drying-and-wetting conditions, universal function for the temperature structure parameter under different atmospheric stability, the dominant sources of uncertainty will be determined. The above study is significant to reveal influence mechanism of uncertainty and explore influence

Decommissioning Funding: Ethics, Implementation, Uncertainties

International Nuclear Information System (INIS)

2007-01-01

This status report on decommissioning funding: ethics, implementation, uncertainties is based on a review of recent literature and materials presented at NEA meetings in 2003 and 2004, and particularly at a topical session organised in November 2004 on funding issues associated with the decommissioning of nuclear power facilities. The report also draws on the experience of the NEA Working Party on Decommissioning and Dismantling (WPDD). This report offers, in a concise form, an overview of relevant considerations on decommissioning funding mechanisms with regard to ethics, implementation and uncertainties. Underlying ethical principles found in international agreements are identified, and factors influencing the accumulation and management of funds for decommissioning nuclear facilities are discussed together with the main sources of uncertainties of funding systems

Uncertainty 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

FACTOR ANALYSIS OF A SOCIAL SKILLS SCALE FOR HIGH SCHOOL STUDENTS.

Science.gov (United States)

Wang, H-Y; Lin, C-K

2015-10-01

The objective of this study was to develop a social skills scale for high school students in Taiwan. This study adopted stratified random sampling. A total of 1,729 high school students were included. The students ranged in age from 16 to 18 years. A Social Skills Scale was developed for this study and was designed for classroom teachers to fill out. The test-retest reliability of this scale was tested by Pearson's correlation coefficient. Exploratory factor analysis was used to determine construct validity. The Social Skills Scale had good overall test-retest reliability of .92, and the internal consistency of the five subscales was above .90. The results of the factor analysis showed that the Social Skills Scale covered the five domains of classroom learning skills, communication skills, individual initiative skills, interaction skills, and job-related social skills, and the five factors explained 68.34% of the variance. Thus, the Social Skills Scale had good reliability and validity and would be applicable to and could be promoted for use in schools.

Some Implications of Two Forms of the Generalized Uncertainty Principle

Directory of Open Access Journals (Sweden)

Mohammed M. Khalil

2014-01-01

Full Text Available Various theories of quantum gravity predict the existence of a minimum length scale, which leads to the modification of the standard uncertainty principle to the Generalized Uncertainty Principle (GUP. In this paper, we study two forms of the GUP and calculate their implications on the energy of the harmonic oscillator and the hydrogen atom more accurately than previous studies. In addition, we show how the GUP modifies the Lorentz force law and the time-energy uncertainty principle.

Uncertainties in Nuclear Proliferation Modeling

International Nuclear Information System (INIS)

Kim, Chul Min; Yim, Man-Sung; Park, Hyeon Seok

2015-01-01

There have been various efforts in the research community to understand the determinants of nuclear proliferation and develop quantitative tools to predict nuclear proliferation events. Such systematic approaches have shown the possibility to provide warning for the international community to prevent nuclear proliferation activities. However, there are still large debates for the robustness of the actual effect of determinants and projection results. Some studies have shown that several factors can cause uncertainties in previous quantitative nuclear proliferation modeling works. This paper analyzes the uncertainties in the past approaches and suggests future works in the view of proliferation history, analysis methods, and variable selection. The research community still lacks the knowledge for the source of uncertainty in current models. Fundamental problems in modeling will remain even other advanced modeling method is developed. Before starting to develop fancy model based on the time dependent proliferation determinants' hypothesis, using graph theory, etc., it is important to analyze the uncertainty of current model to solve the fundamental problems of nuclear proliferation modeling. The uncertainty from different proliferation history coding is small. Serious problems are from limited analysis methods and correlation among the variables. Problems in regression analysis and survival analysis cause huge uncertainties when using the same dataset, which decreases the robustness of the result. Inaccurate variables for nuclear proliferation also increase the uncertainty. To overcome these problems, further quantitative research should focus on analyzing the knowledge suggested on the qualitative nuclear proliferation studies

Gridded uncertainty in fossil fuel carbon dioxide emission maps, a CDIAC example

Directory of Open Access Journals (Sweden)

R. J. Andres

2016-12-01

Full Text Available Due to a current lack of physical measurements at appropriate spatial and temporal scales, all current global maps and distributions of fossil fuel carbon dioxide (FFCO2 emissions use one or more proxies to distribute those emissions. These proxies and distribution schemes introduce additional uncertainty into these maps. This paper examines the uncertainty associated with the magnitude of gridded FFCO2 emissions. This uncertainty is gridded at the same spatial and temporal scales as the mass magnitude maps. This gridded uncertainty includes uncertainty contributions from the spatial, temporal, proxy, and magnitude components used to create the magnitude map of FFCO2 emissions. Throughout this process, when assumptions had to be made or expert judgment employed, the general tendency in most cases was toward overestimating or increasing the magnitude of uncertainty. The results of the uncertainty analysis reveal a range of 4–190 %, with an average of 120 % (2σ for populated and FFCO2-emitting grid spaces over annual timescales. This paper also describes a methodological change specific to the creation of the Carbon Dioxide Information Analysis Center (CDIAC FFCO2 emission maps: the change from a temporally fixed population proxy to a temporally varying population proxy.

Uncertainty analysis of multiple canister repository model by large-scale calculation

International Nuclear Information System (INIS)

Tsujimoto, K.; Okuda, H.; Ahn, J.

2007-01-01

A prototype uncertainty analysis has been made by using the multiple-canister radionuclide transport code, VR, for performance assessment for the high-level radioactive waste repository. Fractures in the host rock determine main conduit of groundwater, and thus significantly affect the magnitude of radionuclide release rates from the repository. In this study, the probability distribution function (PDF) for the number of connected canisters in the same fracture cluster that bears water flow has been determined in a Monte-Carlo fashion by running the FFDF code with assumed PDFs for fracture geometry. The uncertainty for the release rate of 237 Np from a hypothetical repository containing 100 canisters has been quantitatively evaluated by using the VR code with PDFs for the number of connected canisters and the near field rock porosity. The calculation results show that the mass transport is greatly affected by (1) the magnitude of the radionuclide source determined by the number of connected canisters by the fracture cluster, and (2) the canister concentration effect in the same fracture network. The results also show the two conflicting tendencies that the more fractures in the repository model space, the greater average value but the smaller uncertainty of the peak fractional release rate is. To perform a vast amount of calculation, we have utilized the Earth Simulator and SR8000. The multi-level hybrid programming method is applied in the optimization to exploit high performance of the Earth Simulator. The Latin Hypercube Sampling has been utilized to reduce the number of samplings in Monte-Carlo calculation. (authors)

Uncertainty analysis of the radiological characteristics of radioactive waste using a method based on log-normal distributions

International Nuclear Information System (INIS)

Gigase, Yves

2007-01-01

Available in abstract form only. Full text of publication follows: The uncertainty on characteristics of radioactive LILW waste packages is difficult to determine and often very large. This results from a lack of knowledge of the constitution of the waste package and of the composition of the radioactive sources inside. To calculate a quantitative estimate of the uncertainty on a characteristic of a waste package one has to combine these various uncertainties. This paper discusses an approach to this problem, based on the use of the log-normal distribution, which is both elegant and easy to use. It can provide as example quantitative estimates of uncertainty intervals that 'make sense'. The purpose is to develop a pragmatic approach that can be integrated into existing characterization methods. In this paper we show how our method can be applied to the scaling factor method. We also explain how it can be used when estimating other more complex characteristics such as the total uncertainty of a collection of waste packages. This method could have applications in radioactive waste management, more in particular in those decision processes where the uncertainty on the amount of activity is considered to be important such as in probability risk assessment or the definition of criteria for acceptance or categorization. (author)

Development of scaling factor prediction method for radionuclide composition in low-level radioactive waste

International Nuclear Information System (INIS)

Park, Jin Beak

1995-02-01

Low-level radioactive waste management require the knowledge of the natures and quantities of radionuclides in the immobilized or packaged waste. U. S. NRC rules require programs that measure the concentrations of all relevant nuclides either directly or indirectly by relating difficult-to-measure radionuclides to other easy-to-measure radionuclides with application of scaling factors. Scaling factors previously developed through statistical approach can give only generic ones and have many difficult problem about sampling procedures. Generic scaling factors can not take into account for plant operation history. In this study, a method to predict plant-specific and operational history dependent scaling factors is developed. Realistic and detailed approach are taken to find scaling factors at reactor coolant. This approach begin with fission product release mechanisms and fundamental release properties of fuel-source nuclide such as fission product and transuranic nuclide. Scaling factors at various waste streams are derived from the predicted reactor coolant scaling factors with the aid of radionuclide retention and build up model. This model make use of radioactive material balance within the radioactive waste processing systems. Scaling factors at reactor coolant and waste streams which can include the effects of plant operation history have been developed according to input parameters of plant operation history

Confirmatory factor analysis of the Drive for Muscularity Scale-S (DMS-S) and Male Body Attitudes Scale-S (MBAS-S) among male university students in Buenos Aires.

Science.gov (United States)

Compte, Emilio J; Sepúlveda, Ana R; de Pellegrin, Yolanda; Blanco, Miriam

2015-06-01

Several studies have demonstrated that men express body dissatisfaction differently than women. Although specific instruments that address body dissatisfaction in men have been developed, only a few have been validated in Latin-American male populations. The aim of this study was to reassess the factor structure of the Spanish versions of the Drive for Muscularity Scale (DMS-S) and the Male Body Attitudes Scale (MBAS-S) in an Argentinian sample. A cross-sectional study was conducted among 423 male students to examine: the factorial structure (confirmatory factor analysis), the internal consistency reliability, and the concurrent, convergent and discriminant validity of both scales. Results replicated the two factor structures for the DMS-S and MBAS-S. Both scales showed excellent levels of internal consistency, and various measures of construct validity indicated that the DMS-S and MBAS-S were acceptable and valid instruments to assess body dissatisfaction in Argentinian males. Copyright © 2015 Elsevier Ltd. All rights reserved.

Greenhouse gas scenario sensitivity and uncertainties in precipitation projections for central Belgium

Science.gov (United States)

Van Uytven, E.; Willems, P.

2018-03-01

Climate change impact assessment on meteorological variables involves large uncertainties as a result of incomplete knowledge on the future greenhouse gas concentrations and climate model physics, next to the inherent internal variability of the climate system. Given that the alteration in greenhouse gas concentrations is the driver for the change, one expects the impacts to be highly dependent on the considered greenhouse gas scenario (GHS). In this study, we denote this behavior as GHS sensitivity. Due to the climate model related uncertainties, this sensitivity is, at local scale, not always that strong as expected. This paper aims to study the GHS sensitivity and its contributing role to climate scenarios for a case study in Belgium. An ensemble of 160 CMIP5 climate model runs is considered and climate change signals are studied for precipitation accumulation, daily precipitation intensities and wet day frequencies. This was done for the different seasons of the year and the scenario periods 2011-2040, 2031-2060, 2051-2081 and 2071-2100. By means of variance decomposition, the total variance in the climate change signals was separated in the contribution of the differences in GHSs and the other model-related uncertainty sources. These contributions were found dependent on the variable and season. Following the time of emergence concept, the GHS uncertainty contribution is found dependent on the time horizon and increases over time. For the most distinct time horizon (2071-2100), the climate model uncertainty accounts for the largest uncertainty contribution. The GHS differences explain up to 18% of the total variance in the climate change signals. The results point further at the importance of the climate model ensemble design, specifically the ensemble size and the combination of climate models, whereupon climate scenarios are based. The numerical noise, introduced at scales smaller than the skillful scale, e.g. at local scale, was not considered in this study.

Modeling Uncertainty in Climate Change: A Multi-Model Comparison

Energy Technology Data Exchange (ETDEWEB)

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

2015-10-01

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

Uncertainty quantification using evidence theory in multidisciplinary design optimization

International Nuclear Information System (INIS)

Agarwal, Harish; Renaud, John E.; Preston, Evan L.; Padmanabhan, Dhanesh

2004-01-01

Advances in computational performance have led to the development of large-scale simulation tools for design. Systems generated using such simulation tools can fail in service if the uncertainty of the simulation tool's performance predictions is not accounted for. In this research an investigation of how uncertainty can be quantified in multidisciplinary systems analysis subject to epistemic uncertainty associated with the disciplinary design tools and input parameters is undertaken. Evidence theory is used to quantify uncertainty in terms of the uncertain measures of belief and plausibility. To illustrate the methodology, multidisciplinary analysis problems are introduced as an extension to the epistemic uncertainty challenge problems identified by Sandia National Laboratories. After uncertainty has been characterized mathematically the designer seeks the optimum design under uncertainty. The measures of uncertainty provided by evidence theory are discontinuous functions. Such non-smooth functions cannot be used in traditional gradient-based optimizers because the sensitivities of the uncertain measures are not properly defined. In this research surrogate models are used to represent the uncertain measures as continuous functions. A sequential approximate optimization approach is used to drive the optimization process. The methodology is illustrated in application to multidisciplinary example problems

Modeling and solving a large-scale generation expansion planning problem under uncertainty

Energy Technology Data Exchange (ETDEWEB)

Jin, Shan; Ryan, Sarah M. [Iowa State University, Department of Industrial and Manufacturing Systems Engineering, Ames (United States); Watson, Jean-Paul [Sandia National Laboratories, Discrete Math and Complex Systems Department, Albuquerque (United States); Woodruff, David L. [University of California Davis, Graduate School of Management, Davis (United States)

2011-11-15

We formulate a generation expansion planning problem to determine the type and quantity of power plants to be constructed over each year of an extended planning horizon, considering uncertainty regarding future demand and fuel prices. Our model is expressed as a two-stage stochastic mixed-integer program, which we use to compute solutions independently minimizing the expected cost and the Conditional Value-at-Risk; i.e., the risk of significantly larger-than-expected operational costs. We introduce stochastic process models to capture demand and fuel price uncertainty, which are in turn used to generate trees that accurately represent the uncertainty space. Using a realistic problem instance based on the Midwest US, we explore two fundamental, unexplored issues that arise when solving any stochastic generation expansion model. First, we introduce and discuss the use of an algorithm for computing confidence intervals on obtained solution costs, to account for the fact that a finite sample of scenarios was used to obtain a particular solution. Second, we analyze the nature of solutions obtained under different parameterizations of this method, to assess whether the recommended solutions themselves are invariant to changes in costs. The issues are critical for decision makers who seek truly robust recommendations for generation expansion planning. (orig.)

Uncertainty quantification for proton–proton fusion in chiral effective field theory

Energy Technology Data Exchange (ETDEWEB)

Acharya, B. [Department of Physics and Astronomy, University of Tennessee, Knoxville, TN 37996 (United States); Carlsson, B.D. [Department of Physics, Chalmers University of Technology, SE-412 96 Göteborg (Sweden); Ekström, A. [Department of Physics and Astronomy, University of Tennessee, Knoxville, TN 37996 (United States); Physics Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States); Department of Physics, Chalmers University of Technology, SE-412 96 Göteborg (Sweden); Forssén, C. [Department of Physics, Chalmers University of Technology, SE-412 96 Göteborg (Sweden); Platter, L., E-mail: lplatter@utk.edu [Department of Physics and Astronomy, University of Tennessee, Knoxville, TN 37996 (United States); Physics Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States)

2016-09-10

We compute the S-factor of the proton–proton (pp) fusion reaction using chiral effective field theory (χEFT) up to next-to-next-to-leading order (NNLO) and perform a rigorous uncertainty analysis of the results. We quantify the uncertainties due to (i) the computational method used to compute the pp cross section in momentum space, (ii) the statistical uncertainties in the low-energy coupling constants of χEFT, (iii) the systematic uncertainty due to the χEFT cutoff, and (iv) systematic variations in the database used to calibrate the nucleon–nucleon interaction. We also examine the robustness of the polynomial extrapolation procedure, which is commonly used to extract the threshold S-factor and its energy-derivatives. By performing a statistical analysis of the polynomial fit of the energy-dependent S-factor at several different energy intervals, we eliminate a systematic uncertainty that can arise from the choice of the fit interval in our calculations. In addition, we explore the statistical correlations between the S-factor and few-nucleon observables such as the binding energies and point-proton radii of {sup 2,3}H and {sup 3}He as well as the D-state probability and quadrupole moment of {sup 2}H, and the β-decay of {sup 3}H. We find that, with the state-of-the-art optimization of the nuclear Hamiltonian, the statistical uncertainty in the threshold S-factor cannot be reduced beyond 0.7%.

A Bayesian Framework of Uncertainties Integration in 3D Geological Model

Science.gov (United States)

Liang, D.; Liu, X.

2017-12-01

3D geological model can describe complicated geological phenomena in an intuitive way while its application may be limited by uncertain factors. Great progress has been made over the years, lots of studies decompose the uncertainties of geological model to analyze separately, while ignored the comprehensive impacts of multi-source uncertainties. Great progress has been made over the years, while lots of studies ignored the comprehensive impacts of multi-source uncertainties when analyzed them item by item from each source. To evaluate the synthetical uncertainty, we choose probability distribution to quantify uncertainty, and propose a bayesian framework of uncertainties integration. With this framework, we integrated data errors, spatial randomness, and cognitive information into posterior distribution to evaluate synthetical uncertainty of geological model. Uncertainties propagate and cumulate in modeling process, the gradual integration of multi-source uncertainty is a kind of simulation of the uncertainty propagation. Bayesian inference accomplishes uncertainty updating in modeling process. Maximum entropy principle makes a good effect on estimating prior probability distribution, which ensures the prior probability distribution subjecting to constraints supplied by the given information with minimum prejudice. In the end, we obtained a posterior distribution to evaluate synthetical uncertainty of geological model. This posterior distribution represents the synthetical impact of all the uncertain factors on the spatial structure of geological model. The framework provides a solution to evaluate synthetical impact on geological model of multi-source uncertainties and a thought to study uncertainty propagation mechanism in geological modeling.

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

International Nuclear Information System (INIS)

Cranwell, R.M.

1987-01-01

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

Factor structure of the Brief Negative Symptom Scale.

Science.gov (United States)

Strauss, Gregory P; Hong, L Elliot; Gold, James M; Buchanan, Robert W; McMahon, Robert P; Keller, William R; Fischer, Bernard A; Catalano, Lauren T; Culbreth, Adam J; Carpenter, William T; Kirkpatrick, Brian

2012-12-01

The current study examined the factor structure of the Brief Negative Symptom Scale (BNSS), a next-generation negative symptom rating instrument developed in response to the NIMH-sponsored Consensus Development Conference on Negative Symptoms. Participants included 146 individuals with a DSM-IV diagnosis of schizophrenia or schizoaffective disorder. Principal axis factoring indicated two distinct factors explaining 68.7% of the variance. Similar to previous findings, the factors reflected motivation and pleasure and emotional expressivity. These findings provide further support for the construct validity of the BNSS, and for the existence of these two negative symptom factors. Copyright © 2012 Elsevier B.V. All rights reserved.

Expanded uncertainty associated with determination of isotope enrichment factors: Comparison of two point calculation and Rayleigh-plot.

Science.gov (United States)

Julien, Maxime; Gilbert, Alexis; Yamada, Keita; Robins, Richard J; Höhener, Patrick; Yoshida, Naohiro; Remaud, Gérald S

2018-01-01

The enrichment factor (ε) is a common way to express Isotope Effects (IEs) associated with a phenomenon. Many studies determine ε using a Rayleigh-plot, which needs multiple data points. More recent articles describe an alternative method using the Rayleigh equation that allows the determination of ε using only one experimental point, but this method is often subject to controversy. However, a calculation method using two points (one experimental point and one at t 0 ) should lead to the same results because the calculation is derived from the Rayleigh equation. But, it is frequently asked "what is the valid domain of use of this two point calculation?" The primary aim of the present work is a systematic comparison of results obtained with these two methodologies and the determination of the conditions required for the valid calculation of ε. In order to evaluate the efficiency of the two approaches, the expanded uncertainty (U) associated with determining ε has been calculated using experimental data from three published articles. The second objective of the present work is to describe how to determine the expanded uncertainty (U) associated with determining ε. Comparative methodologies using both Rayleigh-plot and two point calculation are detailed and it is clearly demonstrated that calculation of ε using a single data point can give the same result as a Rayleigh-plot provided one strict condition is respected: that the experimental value is measured at a small fraction of unreacted substrate (f < 30%). This study will help stable isotope users to present their results in a more rigorous expression: ε ± U and therefore to define better the significance of an experimental results prior interpretation. Capsule: Enrichment factor can be determined through two different methods and the calculation of associated expanded uncertainty allows checking its significance. Copyright © 2017 Elsevier B.V. All rights reserved.

Uncertainties in the Bidirectional Biodiesel Supply Chain

NARCIS (Netherlands)

Bot, Pieter; van Donk, Dirk Pieter; Pennink, Bartjan; Simatupang, Togar M.

2015-01-01

For remote areas, small-scale local biodiesel production is particularly attractive if producers and consumers are the same. Such supply chains are labeled as bidirectional. However, little is known on how raw material supply, transportation, logistics, production and operations uncertainties impact

N2O emission hotspots at different spatial scales and governing factors for small scale hotspots

International Nuclear Information System (INIS)

Heuvel, R.N. van den; Hefting, M.M.; Tan, N.C.G.; Jetten, M.S.M.; Verhoeven, J.T.A.

2009-01-01

Chronically nitrate-loaded riparian buffer zones show high N 2 O emissions. Often, a large part of the N 2 O is emitted from small surface areas, resulting in high spatial variability in these buffer zones. These small surface areas with high N 2 O emissions (hotspots) need to be investigated to generate knowledge on the factors governing N 2 O emissions. In this study the N 2 O emission variability was investigated at different spatial scales. Therefore N 2 O emissions from three 32 m 2 grids were determined in summer and winter. Spatial variation and total emission were determined on three different scales (0.3 m 2 , 0.018 m 2 and 0.0013 m 2 ) at plots with different levels of N 2 O emissions. Spatial variation was high at all scales determined and highest at the smallest scale. To test possible factors inducing small scale hotspots, soil samples were collected for slurry incubation to determine responses to increased electron donor/acceptor availability. Acetate addition did increase N 2 O production, but nitrate addition failed to increase total denitrification or net N 2 O production. N 2 O production was similar in all soil slurries, independent of their origin from high or low emission soils, indicating that environmental conditions (including physical factors like gas diffusion) rather than microbial community composition governed N 2 O emission rates

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

Energy Technology Data Exchange (ETDEWEB)

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

2017-01-15

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

Factor structure of the Body Appreciation Scale among Malaysian women.

Science.gov (United States)

Swami, Viren; Chamorro-Premuzic, Tomas

2008-12-01

The present study examined the factor structure of a Malay version of the Body Appreciation Scale (BAS), a recently developed scale for the assessment of positive body image that has been shown to have a unidimensional structure in Western settings. Results of exploratory and confirmatory factor analyses based on data from community sample of 591 women in Kuala Lumpur, Malaysia, failed to support a unidimensional structure for the Malay BAS. Results of a confirmatory factor analysis suggested two stable factors, which were labelled 'General Body Appreciation' and 'Body Image Investment'. Multi-group analysis showed that the two-factor structure was invariant for both Malaysian Malay and Chinese women, and that there were no significant ethnic differences on either factor. Results also showed that General Body Appreciation was significant negatively correlated with participants' body mass index. These results are discussed in relation to possible cross-cultural differences in positive body image.

Analysis of uncertainty in modeling perceived risks

International Nuclear Information System (INIS)

Melnyk, R.; Sandquist, G.M.

2005-01-01

Expanding on a mathematical model developed for quantifying and assessing perceived risks, the distribution functions, variances, and uncertainties associated with estimating the model parameters are quantified. The analytical model permits the identification and assignment of any number of quantifiable risk perception factors that can be incorporated within standard risk methodology. Those risk perception factors associated with major technical issues are modeled using lognormal probability density functions to span the potentially large uncertainty variations associated with these risk perceptions. The model quantifies the logic of public risk perception and provides an effective means for measuring and responding to perceived risks. (authors)

Inclusion of time uncertainty in calibration of ionizing radiations

International Nuclear Information System (INIS)

Jordao, B.O.; Quaresma, D.S.; Carvalho, R.J.; Peixoto, J.G.P.

2014-01-01

In terms of metrology, two key factors for reliability employed in the calibration process are what we call Traceability and Uncertainty. Traceability will provide confidence in measurements. Already uncertainty will provide security and quality of what this being measured. Based on the above, this article suggests the implementation time of uncertainty in the calibration of radiological instruments thus increasing the reliability and traceability of the system. (author)

Uncertainties in Cancer Risk Coefficients for Environmental Exposure to Radionuclides. An Uncertainty Analysis for Risk Coefficients Reported in Federal Guidance Report No. 13

Energy Technology Data Exchange (ETDEWEB)

Pawel, David [U.S. Environmental Protection Agency; Leggett, Richard Wayne [ORNL; Eckerman, Keith F [ORNL; Nelson, Christopher [U.S. Environmental Protection Agency

2007-01-01

Federal Guidance Report No. 13 (FGR 13) provides risk coefficients for estimation of the risk of cancer due to low-level exposure to each of more than 800 radionuclides. Uncertainties in risk coefficients were quantified in FGR 13 for 33 cases (exposure to each of 11 radionuclides by each of three exposure pathways) on the basis of sensitivity analyses in which various combinations of plausible biokinetic, dosimetric, and radiation risk models were used to generate alternative risk coefficients. The present report updates the uncertainty analysis in FGR 13 for the cases of inhalation and ingestion of radionuclides and expands the analysis to all radionuclides addressed in that report. The analysis indicates that most risk coefficients for inhalation or ingestion of radionuclides are determined within a factor of 5 or less by current information. That is, application of alternate plausible biokinetic and dosimetric models and radiation risk models (based on the linear, no-threshold hypothesis with an adjustment for the dose and dose rate effectiveness factor) is unlikely to change these coefficients by more than a factor of 5. In this analysis the assessed uncertainty in the radiation risk model was found to be the main determinant of the uncertainty category for most risk coefficients, but conclusions concerning the relative contributions of risk and dose models to the total uncertainty in a risk coefficient may depend strongly on the method of assessing uncertainties in the risk model.

The Euler anomaly and scale factors in Liouville/Toda CFTs

Energy Technology Data Exchange (ETDEWEB)

Balasubramanian, Aswin [Theory Group, Department of Physics, University of Texas at Austin,2515 Speedway Stop C1608, Austin, TX 78712-1197 (United States)

2014-04-22

The role played by the Euler anomaly in the dictionary relating sphere partition functions of four dimensional theories of class S and two dimensional non rational CFTs is clarified. On the two dimensional side, this involves a careful treatment of scale factors in Liouville/Toda correlators. Using ideas from tinkertoy constructions for Gaiotto duality, a framework is proposed for evaluating these scale factors. The representation theory of Weyl groups plays a critical role in this framework.

A Factor Analytic Study of the Internet Usage Scale

Science.gov (United States)

Monetti, David M.; Whatley, Mark A.; Hinkle, Kerry T.; Cunningham, Kerry T.; Breneiser, Jennifer E.; Kisling, Rhea

2011-01-01

This study developed an Internet Usage Scale (IUS) for use with adolescent populations. The IUS is a 26-item scale that measures participants' beliefs about how their Internet usage impacts their behavior. The sample for this study consisted of 947 middle school students. An exploratory factor analysis with varimax rotation was conducted on the…

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

Science.gov (United States)

Bishop, Daniel A; Beier, Colin M

2013-01-01

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

Estimation of a Reactor Core Power Peaking Factor Using Support Vector Regression and Uncertainty Analysis

International Nuclear Information System (INIS)

Bae, In Ho; Naa, Man Gyun; Lee, Yoon Joon; Park, Goon Cherl

2009-01-01

The monitoring of detailed 3-dimensional (3D) reactor core power distribution is a prerequisite in the operation of nuclear power reactors to ensure that various safety limits imposed on the LPD and DNBR, are not violated during nuclear power reactor operation. The LPD and DNBR should be calculated in order to perform the two major functions of the core protection calculator system (CPCS) and the core operation limit supervisory system (COLSS). The LPD at the hottest part of a hot fuel rod, which is related to the power peaking factor (PPF, F q ), is more important than the LPD at any other position in a reactor core. The LPD needs to be estimated accurately to prevent nuclear fuel rods from melting. In this study, support vector regression (SVR) and uncertainty analysis have been applied to estimation of reactor core power peaking factor

Feelings about culture scales: development, factor structure, reliability, and validity.

Science.gov (United States)

Maffini, Cara S; Wong, Y Joel

2015-04-01

Although measures of cultural identity, values, and behavior exist in the multicultural psychological literature, there is currently no measure that explicitly assesses ethnic minority individuals' positive and negative affect toward culture. Therefore, we developed 2 new measures called the Feelings About Culture Scale--Ethnic Culture and Feelings About Culture Scale--Mainstream American Culture and tested their psychometric properties. In 6 studies, we piloted the measures, conducted factor analyses to clarify their factor structure, and examined reliability and validity. The factor structure revealed 2 dimensions reflecting positive and negative affect for each measure. Results provided evidence for convergent, discriminant, criterion-related, and incremental validity as well as the reliability of the scales. The Feelings About Culture Scales are the first known measures to examine both positive and negative affect toward an individual's ethnic culture and mainstream American culture. The focus on affect captures dimensions of psychological experiences that differ from cognitive and behavioral constructs often used to measure cultural orientation. These measures can serve as a valuable contribution to both research and counseling by providing insight into the nuanced affective experiences ethnic minority individuals have toward culture. (c) 2015 APA, all rights reserved).

Incorporation of Satellite Data and Uncertainty in a Nationwide Groundwater Recharge Model in New Zealand

Directory of Open Access Journals (Sweden)

Rogier Westerhoff

2018-01-01

Full Text Available A nationwide model of groundwater recharge for New Zealand (NGRM, as described in this paper, demonstrated the benefits of satellite data and global models to improve the spatial definition of recharge and the estimation of recharge uncertainty. NGRM was inspired by the global-scale WaterGAP model but with the key development of rainfall recharge calculation on scales relevant to national- and catchment-scale studies (i.e., a 1 km × 1 km cell size and a monthly timestep in the period 2000–2014 provided by satellite data (i.e., MODIS-derived evapotranspiration, AET and vegetation in combination with national datasets of rainfall, elevation, soil and geology. The resulting nationwide model calculates groundwater recharge estimates, including their uncertainty, consistent across the country, which makes the model unique compared to all other New Zealand estimates targeted towards groundwater recharge. At the national scale, NGRM estimated an average recharge of 2500 m 3 /s, or 298 mm/year, with a model uncertainty of 17%. Those results were similar to the WaterGAP model, but the improved input data resulted in better spatial characteristics of recharge estimates. Multiple uncertainty analyses led to these main conclusions: the NGRM model could give valuable initial estimates in data-sparse areas, since it compared well to most ground-observed lysimeter data and local recharge models; and the nationwide input data of rainfall and geology caused the largest uncertainty in the model equation, which revealed that the satellite data could improve spatial characteristics without significantly increasing the uncertainty. Clearly the increasing volume and availability of large-scale satellite data is creating more opportunities for the application of national-scale models at the catchment, and smaller, scales. This should result in improved utility of these models including provision of initial estimates in data-sparse areas. Topics for future

Uncertainty and sensitivity analysis in nuclear accident consequence assessment

International Nuclear Information System (INIS)

Karlberg, Olof.

1989-01-01

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

Uncertainty Quantification in High Throughput Screening ...

Science.gov (United States)

Using uncertainty quantification, we aim to improve the quality of modeling data from high throughput screening assays for use in risk assessment. ToxCast is a large-scale screening program that analyzes thousands of chemicals using over 800 assays representing hundreds of biochemical and cellular processes, including endocrine disruption, cytotoxicity, and zebrafish development. Over 2.6 million concentration response curves are fit to models to extract parameters related to potency and efficacy. Models built on ToxCast results are being used to rank and prioritize the toxicological risk of tested chemicals and to predict the toxicity of tens of thousands of chemicals not yet tested in vivo. However, the data size also presents challenges. When fitting the data, the choice of models, model selection strategy, and hit call criteria must reflect the need for computational efficiency and robustness, requiring hard and somewhat arbitrary cutoffs. When coupled with unavoidable noise in the experimental concentration response data, these hard cutoffs cause uncertainty in model parameters and the hit call itself. The uncertainty will then propagate through all of the models built on the data. Left unquantified, this uncertainty makes it difficult to fully interpret the data for risk assessment. We used bootstrap resampling methods to quantify the uncertainty in fitting models to the concentration response data. Bootstrap resampling determines confidence intervals for

Forest Conversion, Agricultural Transitions and the Influence of Multi-scale Market Factors in Southwest Cameroon

Science.gov (United States)

Ordway, E.; Lambin, E.; Asner, G. P.

2015-12-01

The changing structure of demand for commodities associated with food security and energy has had a startling impact on land use change in tropical forests in recent decades. Yet, the composition of conversion in the Congo basin remains a major uncertainty, particularly with regards to the scale of drivers of change. Owing to rapid expansion of production globally and longstanding historical production locally in the Congo basin, oil palm offers a lens through which to evaluate local land use decisions across a spectrum of small- to large-scales of production as well as interactions with regional and global supply chains. We examined the effect of global commodity crop expansion on land use change in Southwest Cameroon using a mixed-methods approach to integrate remote sensing, field surveys and socioeconomic data. Southwest Cameroon (2.5 Mha) has a long history of large- and small-scale agriculture, ranging from mixed crop subsistence agriculture to large monocrop plantations of oil palm, cocoa, and rubber. Trends and spatial patterns of forest conversion and agricultural transitions were analyzed from 2000-2015 using satellite imagery. We used economic, demographic and field survey datasets to assess how regional and global market factors and local commodity crop decisions affect land use patterns. Our results show that oil palm is a major commodity crop expanding in this region, and that conversion is occurring primarily through expansion by medium-scale producers and local elites. Results also indicate that global and regional supply chain dynamics influence local land use decision making. This research contributes new information on land use patterns and dynamics in the Congo basin, an understudied region. More specifically, results from this research contribute information on recent trends of oil palm expansion in Cameroon that will be used in national land use planning strategies.

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

OpenAIRE

Susmita Ghosh; Bhaskar Bhowmick

2015-01-01

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

An audit of the global carbon budget: identifying and reducing sources of uncertainty

Science.gov (United States)

Ballantyne, A. P.; Tans, P. P.; Marland, G.; Stocker, B. D.

2012-12-01

Uncertainties in our carbon accounting practices may limit our ability to objectively verify emission reductions on regional scales. Furthermore uncertainties in the global C budget must be reduced to benchmark Earth System Models that incorporate carbon-climate interactions. Here we present an audit of the global C budget where we try to identify sources of uncertainty for major terms in the global C budget. The atmospheric growth rate of CO2 has increased significantly over the last 50 years, while the uncertainty in calculating the global atmospheric growth rate has been reduced from 0.4 ppm/yr to 0.2 ppm/yr (95% confidence). Although we have greatly reduced global CO2 growth rate uncertainties, there remain regions, such as the Southern Hemisphere, Tropics and Arctic, where changes in regional sources/sinks will remain difficult to detect without additional observations. Increases in fossil fuel (FF) emissions are the primary factor driving the increase in global CO2 growth rate; however, our confidence in FF emission estimates has actually gone down. Based on a comparison of multiple estimates, FF emissions have increased from 2.45 ± 0.12 PgC/yr in 1959 to 9.40 ± 0.66 PgC/yr in 2010. Major sources of increasing FF emission uncertainty are increased emissions from emerging economies, such as China and India, as well as subtle differences in accounting practices. Lastly, we evaluate emission estimates from Land Use Change (LUC). Although relative errors in emission estimates from LUC are quite high (2 sigma ~ 50%), LUC emissions have remained fairly constant in recent decades. We evaluate the three commonly used approaches to estimating LUC emissions- Bookkeeping, Satellite Imagery, and Model Simulations- to identify their main sources of error and their ability to detect net emissions from LUC.; Uncertainties in Fossil Fuel Emissions over the last 50 years.

Success Factors of Large Scale ERP Implementation in Thailand

OpenAIRE

Rotchanakitumnuai; Siriluck

2010-01-01

The objectives of the study are to examine the determinants of ERP implementation success factors of ERP implementation. The result indicates that large scale ERP implementation success consist of eight factors: project management competence, knowledge sharing, ERP system quality , understanding, user involvement, business process re-engineering, top management support, organization readiness.

A Taxonomy of Medical Uncertainties in Clinical Genome Sequencing

Science.gov (United States)

Han, Paul K. J.; Umstead, Kendall L.; Bernhardt, Barbara A.; Green, Robert C.; Joffe, Steven; Koenig, Barbara; Krantz, Ian; Waterston, Leo B.; Biesecker, Leslie G.; Biesecker, Barbara B.

2017-01-01

Purpose Clinical next generation sequencing (CNGS) is introducing new opportunities and challenges into the practice of medicine. Simultaneously, these technologies are generating uncertainties of unprecedented scale that laboratories, clinicians, and patients are required to address and manage. We describe in this report the conceptual design of a new taxonomy of uncertainties around the use of CNGS in health care. Methods Interviews to delineate the dimensions of uncertainty in CNGS were conducted with genomics experts, and themes were extracted in order to expand upon a previously published three-dimensional taxonomy of medical uncertainty. In parallel we developed an interactive website to disseminate the CNGS taxonomy to researchers and engage them in its continued refinement. Results The proposed taxonomy divides uncertainty along three axes: source, issue, and locus, and further discriminates the uncertainties into five layers with multiple domains. Using a hypothetical clinical example, we illustrate how the taxonomy can be applied to findings from CNGS and used to guide stakeholders through interpretation and implementation of variant results. Conclusion The utility of the proposed taxonomy lies in promoting consistency in describing dimensions of uncertainty in publications and presentations, to facilitate research design and management of the uncertainties inherent in the implementation of CNGS. PMID:28102863

Uncertainty in adaptive capacity

International Nuclear Information System (INIS)

Neil Adger, W.; Vincent, K.

2005-01-01

The capacity to adapt is a critical element of the process of adaptation: it is the vector of resources that represent the asset base from which adaptation actions can be made. Adaptive capacity can in theory be identified and measured at various scales, from the individual to the nation. The assessment of uncertainty within such measures comes from the contested knowledge domain and theories surrounding the nature of the determinants of adaptive capacity and the human action of adaptation. While generic adaptive capacity at the national level, for example, is often postulated as being dependent on health, governance and political rights, and literacy, and economic well-being, the determinants of these variables at national levels are not widely understood. We outline the nature of this uncertainty for the major elements of adaptive capacity and illustrate these issues with the example of a social vulnerability index for countries in Africa. (authors)

Up-scaling of multi-variable flood loss models from objects to land use units at the meso-scale

Science.gov (United States)

Kreibich, Heidi; Schröter, Kai; Merz, Bruno

2016-05-01

Flood risk management increasingly relies on risk analyses, including loss modelling. Most of the flood loss models usually applied in standard practice have in common that complex damaging processes are described by simple approaches like stage-damage functions. Novel multi-variable models significantly improve loss estimation on the micro-scale and may also be advantageous for large-scale applications. However, more input parameters also reveal additional uncertainty, even more in upscaling procedures for meso-scale applications, where the parameters need to be estimated on a regional area-wide basis. To gain more knowledge about challenges associated with the up-scaling of multi-variable flood loss models the following approach is applied: Single- and multi-variable micro-scale flood loss models are up-scaled and applied on the meso-scale, namely on basis of ATKIS land-use units. Application and validation is undertaken in 19 municipalities, which were affected during the 2002 flood by the River Mulde in Saxony, Germany by comparison to official loss data provided by the Saxon Relief Bank (SAB).In the meso-scale case study based model validation, most multi-variable models show smaller errors than the uni-variable stage-damage functions. The results show the suitability of the up-scaling approach, and, in accordance with micro-scale validation studies, that multi-variable models are an improvement in flood loss modelling also on the meso-scale. However, uncertainties remain high, stressing the importance of uncertainty quantification. Thus, the development of probabilistic loss models, like BT-FLEMO used in this study, which inherently provide uncertainty information are the way forward.

Uncertainty analysis of hydrological modeling in a tropical area using different algorithms

Science.gov (United States)

Rafiei Emam, Ammar; Kappas, Martin; Fassnacht, Steven; Linh, Nguyen Hoang Khanh

2018-01-01

Hydrological modeling outputs are subject to uncertainty resulting from different sources of errors (e.g., error in input data, model structure, and model parameters), making quantification of uncertainty in hydrological modeling imperative and meant to improve reliability of modeling results. The uncertainty analysis must solve difficulties in calibration of hydrological models, which further increase in areas with data scarcity. The purpose of this study is to apply four uncertainty analysis algorithms to a semi-distributed hydrological model, quantifying different source of uncertainties (especially parameter uncertainty) and evaluate their performance. In this study, the Soil and Water Assessment Tools (SWAT) eco-hydrological model was implemented for the watershed in the center of Vietnam. The sensitivity of parameters was analyzed, and the model was calibrated. The uncertainty analysis for the hydrological model was conducted based on four algorithms: Generalized Likelihood Uncertainty Estimation (GLUE), Sequential Uncertainty Fitting (SUFI), Parameter Solution method (ParaSol) and Particle Swarm Optimization (PSO). The performance of the algorithms was compared using P-factor and Rfactor, coefficient of determination (R 2), the Nash Sutcliffe coefficient of efficiency (NSE) and Percent Bias (PBIAS). The results showed the high performance of SUFI and PSO with P-factor>0.83, R-factor 0.91, NSE>0.89, and 0.18uncertainty analysis must be accounted when the outcomes of the model use for policy or management decisions.

An experimental verification of the compensation of length change of line scales caused by ambient air pressure

International Nuclear Information System (INIS)

Takahashi, Akira; Miwa, Nobuharu

2010-01-01

Line scales are used as a working standard of length for the calibration of optical measuring instruments such as profile projectors, measuring microscopes and video measuring systems. The authors have developed a one-dimensional calibration system for line scales to obtain a lower uncertainty of measurement. The scale calibration system, named Standard Scale Calibrator SSC-05, employs a vacuum interferometer system for length measurement, a 633 nm iodine-stabilized He–Ne laser to calibrate the oscillating frequency of the interferometer laser light source and an Abbe's error compensation structure. To reduce the uncertainty of measurement, the uncertainty factors of the line scale and ambient conditions should not be neglected. Using the length calibration system, the expansion and contraction of a line scale due to changes in ambient air pressure were observed and the measured scale length was corrected into the length under standard atmospheric pressure, 1013.25 hPa. Utilizing a natural rapid change in the air pressure caused by a tropical storm (typhoon), we carried out an experiment on the length measurement of a 1000 mm long line scale made of glass ceramic with a low coefficient of thermal expansion. Using a compensation formula for the length change caused by changes in ambient air pressure, the length change of the 1000 mm long line scale was compensated with a standard deviation of less than 1 nm

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

Directory of Open Access Journals (Sweden)

Zhenyu Wang

2018-01-01

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

Scale factor duality for conformal cyclic cosmologies

Energy Technology Data Exchange (ETDEWEB)

Silva, University Camara da; Lima, A.L. Alves; Sotkov, G.M. [Departamento de Física - CCE,Universidade Federal de Espirito Santo, 29075-900, Vitoria ES (Brazil)

2016-11-16

The scale factor duality is a symmetry of dilaton gravity which is known to lead to pre-big-bang cosmologies. A conformal time version of the scale factor duality (SFD) was recently implemented as a UV/IR symmetry between decelerated and accelerated phases of the post-big-bang evolution within Einstein gravity coupled to a scalar field. The problem investigated in the present paper concerns the employment of the conformal time SFD methods to the construction of pre-big-bang and cyclic extensions of these models. We demonstrate that each big-bang model gives rise to two qualitatively different pre-big-bang evolutions: a contraction/expansion SFD model and Penrose’s Conformal Cyclic Cosmology (CCC). A few examples of SFD symmetric cyclic universes involving certain gauged Kähler sigma models minimally coupled to Einstein gravity are studied. We also describe the specific SFD features of the thermodynamics and the conditions for validity of the generalized second law in the case of Gauss-Bonnet (GB) extension of these selected CCC models.

Scale factor duality for conformal cyclic cosmologies

International Nuclear Information System (INIS)

Silva, University Camara da; Lima, A.L. Alves; Sotkov, G.M.

2016-01-01

The scale factor duality is a symmetry of dilaton gravity which is known to lead to pre-big-bang cosmologies. A conformal time version of the scale factor duality (SFD) was recently implemented as a UV/IR symmetry between decelerated and accelerated phases of the post-big-bang evolution within Einstein gravity coupled to a scalar field. The problem investigated in the present paper concerns the employment of the conformal time SFD methods to the construction of pre-big-bang and cyclic extensions of these models. We demonstrate that each big-bang model gives rise to two qualitatively different pre-big-bang evolutions: a contraction/expansion SFD model and Penrose’s Conformal Cyclic Cosmology (CCC). A few examples of SFD symmetric cyclic universes involving certain gauged Kähler sigma models minimally coupled to Einstein gravity are studied. We also describe the specific SFD features of the thermodynamics and the conditions for validity of the generalized second law in the case of Gauss-Bonnet (GB) extension of these selected CCC models.

Site utility system optimization with operation adjustment under uncertainty

International Nuclear Information System (INIS)

Sun, Li; Gai, Limei; Smith, Robin

2017-01-01

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

Gridded Uncertainty Maps of Fossil Fuel Carbon Dioxide Emissions: A New Data Product

Science.gov (United States)

Andres, R. J.; Boden, T.

2014-12-01

With the publication of a new assessment of the uncertainty associated with the mass of fossil fuel carbon dioxide (FFCO2) emissions (2014, Tellus B, 66, 23616, doi:10.3402/tellusb.v66.23616), it is now possible to extend that work with a gridded map of fossil fuel emission uncertainties. The new data product was created to be paired with the long-used, Carbon Dioxide Information Analysis Center (CDIAC), emission year 1751-present, one degree latitude by one degree longitude (1x1) mass of emissions data product (http://cdiac.ornl.gov/epubs/ndp/ndp058/ndp058_v2013.html). Now, for the first time, data users will have FFCO2 emission information that represents both mass and uncertainty, each of which varies in both time and space. The new data product was constructed by examining the individual uncertainties in each of the input data sets to the gridded mass maps and then combining these individual uncertainties into an overall uncertainty for the mass maps. The input data sets include a table of the mass of FFCO2 emissions by country and year, the one degree geographic map of emissions which includes changing borders on an annual time scale and ties the mass of emissions to location, and the one degree population proxy used to distribute the mass of emissions within each country. As the three input data sets are independent of each other, their combination for the overall uncertainty is accomplished by a simple square root of the sum of the squares procedure. The resulting uncertainty data product is gridded at 1x1 and exactly overlays the 1x1 mass emission maps. The default temporal resolution is annual, but a companion product is also available at monthly time scales. The monthly uncertainty product uses the same input data sets, but the mass uncertainty is scaled as described in the monthly mass product description paper (2011, Tellus B, 63:309-327, doi: 10.1111/j.1600-0889.2011.00530.x). The gridded uncertainty maps cover emission year 1950 to 2010. The start

A New Data Product: Gridded Uncertainty Maps of Fossil Fuel Carbon Dioxide Emissions

Science.gov (United States)

Andres, R. J.; Boden, T.

2015-12-01

Gridded uncertainty maps of fossil fuel carbon dioxide (FFCO2) emissions are a new data product that is currently in the process of being completed and published. This work is based on the relatively new assessment of the uncertainty associated with the mass of FFCO2 emissions (2014, Tellus B, 66, 23616, doi:10.3402/tellusb.v66.23616). The new data product was created to be paired with the long-used, Carbon Dioxide Information Analysis Center (CDIAC), emission year 1751-present, one degree latitude by one degree longitude (1x1) mass of emissions data product (http://cdiac.ornl.gov/epubs/ndp/ndp058/ndp058_v2013.html). Now, data users will have FFCO2 emission information that represents both mass and uncertainty, each of which varies in both time and space. The new data product was constructed by examining the individual uncertainties in each of the input data sets to the gridded mass maps and then combining these individual uncertainties into an overall uncertainty for the mass maps. The input data sets include a table of the mass of FFCO2 emissions by country and year, the one degree geographic map of emissions which includes changing borders on an annual time scale and ties the mass of emissions to location, and the one degree population proxy used to distribute the mass of emissions within each country. As the three input data sets are independent of each other, their combination for the overall uncertainty is accomplished by a simple square root of the sum of the squares procedure. The resulting uncertainty data product is gridded at 1x1 and exactly overlays the 1x1 mass emission maps. The default temporal resolution is annual, but a companion product is also available at monthly time scales. The monthly uncertainty product uses the same input data sets, but the mass uncertainty is scaled as described in the monthly mass product description paper (2011, Tellus B, 63:309-327, doi: 10.1111/j.1600-0889.2011.00530.x). The gridded uncertainty maps cover emission year

Scale for positive aspects of caregiving experience: development, reliability, and factor structure.

Science.gov (United States)

Kate, N; Grover, S; Kulhara, P; Nehra, R

2012-06-01

OBJECTIVE. To develop an instrument (Scale for Positive Aspects of Caregiving Experience [SPACE]) that evaluates positive caregiving experience and assess its psychometric properties. METHODS. Available scales which assess some aspects of positive caregiving experience were reviewed and a 50-item questionnaire with a 5-point rating was constructed. In all, 203 primary caregivers of patients with severe mental disorders were asked to complete the questionnaire. Internal consistency, test-retest reliability, cross-language reliability, split-half reliability, and face validity were evaluated. Principal component factor analysis was run to assess the factorial validity of the scale. RESULTS. The scale developed as part of the study was found to have good internal consistency, test-retest reliability, cross-language reliability, split-half reliability, and face validity. Principal component factor analysis yielded a 4-factor structure, which also had good test-retest reliability and cross-language reliability. There was a strong correlation between the 4 factors obtained. CONCLUSION. The SPACE developed as part of this study has good psychometric properties.

Uncertainty quantification an accelerated course with advanced applications in computational engineering

CERN Document Server

Soize, Christian

2017-01-01

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

Factor analysis of Wechsler Adult Intelligence Scale-Revised in developmentally disabled persons.

Science.gov (United States)

Di Nuovo, Santo F; Buono, Serafino

2006-12-01

The results of previous studies on the factorial structure of Wechsler Intelligence Scales are somewhat inconsistent across normal and pathological samples. To study specific clinical groups, such as developmentally disabled persons, it is useful to examine the factor structure in appropriate samples. A factor analysis was carried out using the principal component method and the Varimax orthogonal rotation on the Wechsler Adult Intelligence Scale (WAIS-R) in a sample of 203 developmentally disabled persons, with a mean age of 25 years 4 months. Developmental disability ranged from mild to moderate. Partially contrasting with previous studies on normal samples, results found a two-factor solution. Wechsler's traditional Verbal and Performance scales seems to be more appropriate for this sample than the alternative three-factor solution.

Chemical model reduction under uncertainty

KAUST Repository

Malpica Galassi, Riccardo

2017-03-06

A general strategy for analysis and reduction of uncertain chemical kinetic models is presented, and its utility is illustrated in the context of ignition of hydrocarbon fuel–air mixtures. The strategy is based on a deterministic analysis and reduction method which employs computational singular perturbation analysis to generate simplified kinetic mechanisms, starting from a detailed reference mechanism. We model uncertain quantities in the reference mechanism, namely the Arrhenius rate parameters, as random variables with prescribed uncertainty factors. We propagate this uncertainty to obtain the probability of inclusion of each reaction in the simplified mechanism. We propose probabilistic error measures to compare predictions from the uncertain reference and simplified models, based on the comparison of the uncertain dynamics of the state variables, where the mixture entropy is chosen as progress variable. We employ the construction for the simplification of an uncertain mechanism in an n-butane–air mixture homogeneous ignition case, where a 176-species, 1111-reactions detailed kinetic model for the oxidation of n-butane is used with uncertainty factors assigned to each Arrhenius rate pre-exponential coefficient. This illustration is employed to highlight the utility of the construction, and the performance of a family of simplified models produced depending on chosen thresholds on importance and marginal probabilities of the reactions.

Factor validation of the portuguese version of the social skills scale of the Preschool and Kindergarten Behavior Scales

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Maria João Seabra-Santos

2014-05-01

Full Text Available The assessment of preschoolers’ social skills represents a topic of growing importance in research recently developed in the field. The purpose of this article is to present confirmatory factor analyses studies for the Social Skills scale of the Preschool and Kindergarten Behavior Scales – Second Edition (PKBS-2, a behavior rating scale that evaluates social skills and problem behaviors, adapted and validated for Portuguese preschool children. The 34 items of the Social Skills scale, distributed on three subscales (Social Cooperation/Adjustment, Social Interaction/Empathy and Social Independence/Assertiveness, were grouped into item-parcels. Model adjustment was analyzed for the total sample (N = 2000 and the analyses were replicated for the subsamples collected in the home (n = 1000 and school settings (n = 1000. The factor structure was very stable for the three samples, with high internal consistency levels and correlations between parcels/scales. The results highlight the utility/validity of the Social Skills scale of the PKBS-2 (Portuguese version.

Factor Analysis of the Brazilian Version of UPPS Impulsive Behavior Scale

Science.gov (United States)

Sediyama, Cristina Y. N.; Moura, Ricardo; Garcia, Marina S.; da Silva, Antonio G.; Soraggi, Carolina; Neves, Fernando S.; Albuquerque, Maicon R.; Whiteside, Setephen P.; Malloy-Diniz, Leandro F.

2017-01-01

Objective: To examine the internal consistency and factor structure of the Brazilian adaptation of the UPPS Impulsive Behavior Scale. Methods: UPPS is a self-report scale composed by 40 items assessing four factors of impulsivity: (a) urgency, (b) lack of premeditation; (c) lack of perseverance; (d) sensation seeking. In the present study 384 participants (278 women and 106 men), who were recruited from schools, universities, leisure centers and workplaces fulfilled the UPPS scale. An exploratory factor analysis was performed by using Varimax factor rotation and Kaiser Normalization, and we also conducted two confirmatory analyses to test the independency of the UPPS components found in previous analysis. Results: Results showed a decrease in mean UPPS total scores with age and this analysis showed that the youngest participants (below 30 years) scored significantly higher than the other groups over 30 years. No difference in gender was found. Cronbach’s alpha, results indicated satisfactory values for all subscales, with similar high values for the subscales and confirmatory factor analysis indexes also indicated a poor model fit. The results of two exploratory factor analysis were satisfactory. Conclusion: Our results showed that the Portuguese version has the same four-factor structure of the original and previous translations of the UPPS. PMID:28484414

Factor Analysis of the Brazilian Version of UPPS Impulsive Behavior Scale

Directory of Open Access Journals (Sweden)

Leandro F. Malloy-Diniz

2017-04-01

Full Text Available Objective: To examine the internal consistency and factor structure of the Brazilian adaptation of the UPPS Impulsive Behavior Scale.Methods: UPPS is a self-report scale composed by 40 items assessing four factors of impulsivity: (a urgency, (b lack of premeditation; (c lack of perseverance; (d sensation seeking. In the present study 384 participants (278 women and 106 men, who were recruited from schools, universities, leisure centers and workplaces fulfilled the UPPS scale. An exploratory factor analysis was performed by using Varimax factor rotation and Kaiser Normalization, and we also conducted two confirmatory analyses to test the independency of the UPPS components found in previous analysis.Results: Results showed a decrease in mean UPPS total scores with age and this analysis showed that the youngest participants (below 30 years scored significantly higher than the other groups over 30 years. No difference in gender was found. Cronbach’s alpha, results indicated satisfactory values for all subscales, with similar high values for the subscales and confirmatory factor analysis indexes also indicated a poor model fit. The results of two exploratory factor analysis were satisfactory.Conclusion: Our results showed that the Portuguese version has the same four-factor structure of the original and previous translations of the UPPS.

Factor Analysis of the Brazilian Version of UPPS Impulsive Behavior Scale.

Science.gov (United States)

Sediyama, Cristina Y N; Moura, Ricardo; Garcia, Marina S; da Silva, Antonio G; Soraggi, Carolina; Neves, Fernando S; Albuquerque, Maicon R; Whiteside, Setephen P; Malloy-Diniz, Leandro F

2017-01-01

Objective: To examine the internal consistency and factor structure of the Brazilian adaptation of the UPPS Impulsive Behavior Scale. Methods: UPPS is a self-report scale composed by 40 items assessing four factors of impulsivity: (a) urgency, (b) lack of premeditation; (c) lack of perseverance; (d) sensation seeking. In the present study 384 participants (278 women and 106 men), who were recruited from schools, universities, leisure centers and workplaces fulfilled the UPPS scale. An exploratory factor analysis was performed by using Varimax factor rotation and Kaiser Normalization, and we also conducted two confirmatory analyses to test the independency of the UPPS components found in previous analysis. Results: Results showed a decrease in mean UPPS total scores with age and this analysis showed that the youngest participants (below 30 years) scored significantly higher than the other groups over 30 years. No difference in gender was found. Cronbach's alpha, results indicated satisfactory values for all subscales, with similar high values for the subscales and confirmatory factor analysis indexes also indicated a poor model fit. The results of two exploratory factor analysis were satisfactory. Conclusion: Our results showed that the Portuguese version has the same four-factor structure of the original and previous translations of the UPPS.

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

International Nuclear Information System (INIS)

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

1990-01-01

Best Estimate computer codes have been accepted by the US Nuclear Regulatory Commission as an optional tool for performing safety analysis related to the licensing and regulation of current nuclear reactors producing commercial electrical power, providing their uncertainty is quantified. In support of this policy change, the NRC and its contractors and consultants have developed and demonstrated an uncertainty quantification methodology called CSAU. At the process level, the method is generic to any application which relies on best estimate computer code simulations to determine safe operating margins. The primary use of the CSAU methodology is to quantify safety margins for existing designs; however, the methodology can also serve an equally important role in advanced reactor research for plants not yet built. Applied early, during the period when alternate designs are being evaluated, the methodology can identify the relative importance of the sources of uncertainty in the knowledge of each plant behavior and, thereby, help prioritize the research needed to bring the new designs to fruition. This paper describes the CSAU methodology, at the generic process level, and provides the general principles whereby it may be applied to evaluations of advanced reactor designs. 9 refs., 1 fig., 1 tab

Summary of existing uncertainty methods

International Nuclear Information System (INIS)

Glaeser, Horst

2013-01-01

A summary of existing and most used uncertainty methods is presented, and the main features are compared. One of these methods is the order statistics method based on Wilks' formula. It is applied in safety research as well as in licensing. This method has been first proposed by GRS for use in deterministic safety analysis, and is now used by many organisations world-wide. Its advantage is that the number of potential uncertain input and output parameters is not limited to a small number. Such a limitation was necessary for the first demonstration of the Code Scaling Applicability Uncertainty Method (CSAU) by the United States Regulatory Commission (USNRC). They did not apply Wilks' formula in their statistical method propagating input uncertainties to obtain the uncertainty of a single output variable, like peak cladding temperature. A Phenomena Identification and Ranking Table (PIRT) was set up in order to limit the number of uncertain input parameters, and consequently, the number of calculations to be performed. Another purpose of such a PIRT process is to identify the most important physical phenomena which a computer code should be suitable to calculate. The validation of the code should be focused on the identified phenomena. Response surfaces are used in some applications replacing the computer code for performing a high number of calculations. The second well known uncertainty method is the Uncertainty Methodology Based on Accuracy Extrapolation (UMAE) and the follow-up method 'Code with the Capability of Internal Assessment of Uncertainty (CIAU)' developed by the University Pisa. Unlike the statistical approaches, the CIAU does compare experimental data with calculation results. It does not consider uncertain input parameters. Therefore, the CIAU is highly dependent on the experimental database. The accuracy gained from the comparison between experimental data and calculated results are extrapolated to obtain the uncertainty of the system code predictions

Self-Compassion Scale: IRT Psychometric Analysis, Validation, and Factor Structure – Slovak Translation

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Júlia Halamová

2018-01-01

Full Text Available The present study verifies the psychometric properties of the Slovak version of the Self-Compassion Scale through item response theory, factor-analysis, validity analyses and norm development. The surveyed sample consisted of 1,181 participants (34% men and 66% women with a mean age of 30.30 years (SD = 12.40. Two general factors (Self-compassionate responding and Self-uncompassionate responding were identified, whereas there was no support for a single general factor of the scale and six subscales. The results of the factor analysis were supported by an independent sample of 676 participants. Therefore, the use of total score for the whole scale would be inappropriate. In Slovak language the Self-Compassion Scale should be used in the form of two general subscales (Self-compassionate responding and Self-uncompassionate responding. In line with our theoretical assumptions, we obtained relatively high Spearman’s correlation coefficients between the Self-Compassion Scale and related external variables, demonstrating construct validity for the scale. To sum up, the Slovak translation of The Self-Compassion Scale is a reliable and valid instrument that measures Self-compassionate responding and Self-uncompassionate responding.

Statistical uncertainty analysis of radon transport in nonisothermal, unsaturated soils

International Nuclear Information System (INIS)

Holford, D.J.; Owczarski, P.C.; Gee, G.W.; Freeman, H.D.

1990-10-01

To accurately predict radon fluxes soils to the atmosphere, we must know more than the radium content of the soil. Radon flux from soil is affected not only by soil properties, but also by meteorological factors such as air pressure and temperature changes at the soil surface, as well as the infiltration of rainwater. Natural variations in meteorological factors and soil properties contribute to uncertainty in subsurface model predictions of radon flux, which, when coupled with a building transport model, will also add uncertainty to predictions of radon concentrations in homes. A statistical uncertainty analysis using our Rn3D finite-element numerical model was conducted to assess the relative importance of these meteorological factors and the soil properties affecting radon transport. 10 refs., 10 figs., 3 tabs

Stress From Uncertainty and Resilience Among Depressed and Burned Out Residents: A Cross-Sectional Study.

Science.gov (United States)

Simpkin, Arabella L; Khan, Alisa; West, Daniel C; Garcia, Briana M; Sectish, Theodore C; Spector, Nancy D; Landrigan, Christopher P

2018-03-07

Depression and burnout are highly prevalent among residents, but little is known about modifiable personality variables, such as resilience and stress from uncertainty, that may predispose to these conditions. Residents are routinely faced with uncertainty when making medical decisions. To determine how stress from uncertainty is related to resilience among pediatric residents and whether these attributes are associated with depression and burnout. We surveyed 86 residents in pediatric residency programs from 4 urban freestanding children's hospitals in North America in 2015. Stress from uncertainty was measured with the use of the Physicians' Reaction to Uncertainty Scale, resilience with the use of the 14-item Resilience Scale, depression with the use of the Harvard National Depression Screening Scale; and burnout with the use of single-item measures of emotional exhaustion and depersonalization from the Maslach Burnout Inventory. Fifty out of 86 residents responded to the survey (58.1%). Higher levels of stress from uncertainty correlated with lower resilience (r = -0.60; P resilience (56.6 ± 10.7 vs 85.4 ± 8.0; P resilience (76.7 ± 14.8 vs 85.0 ± 9.77; P = .02) compared with residents who were not burned out. We found high levels of stress from uncertainty, and low levels of resilience were strongly correlated with depression and burnout. Efforts to enhance tolerance of uncertainty and resilience among residents may provide opportunities to mitigate resident depression and burnout. Copyright © 2018 Academic Pediatric Association. Published by Elsevier Inc. All rights reserved.

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

Validity and factor structure of the bodybuilding dependence scale.

Science.gov (United States)

Smith, D; Hale, B

2004-04-01

To investigate the factor structure, validity, and reliability of the bodybuilding dependence scale and to investigate differences in bodybuilding dependence between men and women and competitive and non-competitive bodybuilders. Seventy two male competitive bodybuilders, 63 female competitive bodybuilders, 87 male non-competitive bodybuilders, and 63 non-competitive female bodybuilders completed the bodybuilding dependence scale (BDS), the exercise dependence questionnaire (EDQ), and the muscle dysmorphia inventory (MDI). Confirmatory factor analysis of the BDS supported a three factor model of bodybuilding dependence, consisting of social dependence, training dependence, and mastery dependence (Q = 3.16, CFI = 0.98, SRMR = 0.04). Internal reliability of all three subscales was high (Cronbach's alpha = 0.92, 0.92, and 0.93 respectively). Significant (pbodybuilders scored significantly (pbodybuilders. However, there were no significant sex differences on any of the BDS subscales (p>0.05). The three factor BDS appears to be a reliable and valid measure of bodybuilding dependence. Symptoms of bodybuilding dependence are more prevalent in competitive bodybuilders than non-competitive ones, but there are no significant sex differences in bodybuilding dependence.

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

International Nuclear Information System (INIS)

Shimada, Yoshio

2002-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2002-09-01

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

Uncertainty of future projections of species distributions in mountainous regions.

Directory of Open Access Journals (Sweden)

Ying Tang

Full Text Available Multiple factors introduce uncertainty into projections of species distributions under climate change. The uncertainty introduced by the choice of baseline climate information used to calibrate a species distribution model and to downscale global climate model (GCM simulations to a finer spatial resolution is a particular concern for mountainous regions, as the spatial resolution of climate observing networks is often insufficient to detect the steep climatic gradients in these areas. Using the maximum entropy (MaxEnt modeling framework together with occurrence data on 21 understory bamboo species distributed across the mountainous geographic range of the Giant Panda, we examined the differences in projected species distributions obtained from two contrasting sources of baseline climate information, one derived from spatial interpolation of coarse-scale station observations and the other derived from fine-spatial resolution satellite measurements. For each bamboo species, the MaxEnt model was calibrated separately for the two datasets and applied to 17 GCM simulations downscaled using the delta method. Greater differences in the projected spatial distributions of the bamboo species were observed for the models calibrated using the different baseline datasets than between the different downscaled GCM simulations for the same calibration. In terms of the projected future climatically-suitable area by species, quantification using a multi-factor analysis of variance suggested that the sum of the variance explained by the baseline climate dataset used for model calibration and the interaction between the baseline climate data and the GCM simulation via downscaling accounted for, on average, 40% of the total variation among the future projections. Our analyses illustrate that the combined use of gridded datasets developed from station observations and satellite measurements can help estimate the uncertainty introduced by the choice of baseline

Optimization Under Uncertainty for Wake Steering Strategies: Preprint

Energy Technology Data Exchange (ETDEWEB)

Quick, Julian [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Annoni, Jennifer [National Renewable Energy Laboratory (NREL), Golden, CO (United States); King, Ryan N [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Dykes, Katherine L [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Fleming, Paul A [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Ning, Andrew [Brigham Young University

2017-05-01

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

SU-E-J-159: Analysis of Total Imaging Uncertainty in Respiratory-Gated Radiotherapy

Energy Technology Data Exchange (ETDEWEB)

Suzuki, J; Okuda, T [Toyota memorial hospital, Toyota, Aichi (Japan); Sakaino, S; Yokota, N [Suzukake central hospital, Hamamatsu, Shizuoka (Japan)

2015-06-15

Purpose: In respiratory-gated radiotherapy, the gating phase during treatment delivery needs to coincide with the corresponding phase determined during the treatment plan. However, because radiotherapy is performed based on the image obtained for the treatment plan, the time delay, motion artifact, volume effect, and resolution in the images are uncertain. Thus, imaging uncertainty is the most basic factor that affects the localization accuracy. Therefore, these uncertainties should be analyzed. This study aims to analyze the total imaging uncertainty in respiratory-gated radiotherapy. Methods: Two factors of imaging uncertainties related to respiratory-gated radiotherapy were analyzed. First, CT image was used to determine the target volume and 4D treatment planning for the Varian Realtime Position Management (RPM) system. Second, an X-ray image was acquired for image-guided radiotherapy (IGRT) for the BrainLAB ExacTrac system. These factors were measured using a respiratory gating phantom. The conditions applied during phantom operation were as follows: respiratory wave form, sine curve; respiratory cycle, 4 s; phantom target motion amplitude, 10, 20, and 29 mm (which is maximum phantom longitudinal motion). The target and cylindrical marker implanted in the phantom coverage of the CT images was measured and compared with the theoretically calculated coverage from the phantom motion. The theoretical position of the cylindrical marker implanted in the phantom was compared with that acquired from the X-ray image. The total imaging uncertainty was analyzed from these two factors. Results: In the CT image, the uncertainty between the target and cylindrical marker’s actual coverage and the coverage of CT images was 1.19 mm and 2.50mm, respectively. In the Xray image, the uncertainty was 0.39 mm. The total imaging uncertainty from the two factors was 1.62mm. Conclusion: The total imaging uncertainty in respiratory-gated radiotherapy was clinically acceptable. However

SU-E-J-159: Analysis of Total Imaging Uncertainty in Respiratory-Gated Radiotherapy

International Nuclear Information System (INIS)

Suzuki, J; Okuda, T; Sakaino, S; Yokota, N

2015-01-01

Purpose: In respiratory-gated radiotherapy, the gating phase during treatment delivery needs to coincide with the corresponding phase determined during the treatment plan. However, because radiotherapy is performed based on the image obtained for the treatment plan, the time delay, motion artifact, volume effect, and resolution in the images are uncertain. Thus, imaging uncertainty is the most basic factor that affects the localization accuracy. Therefore, these uncertainties should be analyzed. This study aims to analyze the total imaging uncertainty in respiratory-gated radiotherapy. Methods: Two factors of imaging uncertainties related to respiratory-gated radiotherapy were analyzed. First, CT image was used to determine the target volume and 4D treatment planning for the Varian Realtime Position Management (RPM) system. Second, an X-ray image was acquired for image-guided radiotherapy (IGRT) for the BrainLAB ExacTrac system. These factors were measured using a respiratory gating phantom. The conditions applied during phantom operation were as follows: respiratory wave form, sine curve; respiratory cycle, 4 s; phantom target motion amplitude, 10, 20, and 29 mm (which is maximum phantom longitudinal motion). The target and cylindrical marker implanted in the phantom coverage of the CT images was measured and compared with the theoretically calculated coverage from the phantom motion. The theoretical position of the cylindrical marker implanted in the phantom was compared with that acquired from the X-ray image. The total imaging uncertainty was analyzed from these two factors. Results: In the CT image, the uncertainty between the target and cylindrical marker’s actual coverage and the coverage of CT images was 1.19 mm and 2.50mm, respectively. In the Xray image, the uncertainty was 0.39 mm. The total imaging uncertainty from the two factors was 1.62mm. Conclusion: The total imaging uncertainty in respiratory-gated radiotherapy was clinically acceptable. However

Structure of Rosenberg’s Self-Esteem Scale: Three-factor solution

Czech Academy of Sciences Publication Activity Database

Blatný, Marek; Urbánek, Tomáš; Osecká, Terezie

2006-01-01

Roč. 48, č. 4 (2006), s. 371-378 ISSN 0039-3320 Institutional research plan: CEZ:AV0Z70250504 Keywords : Rosenberg Self - Esteem Scale * confirmatory factor analysis * adolescents Subject RIV: AN - Psychology Impact factor: 0.410, year: 2006

Quantifying phenomenological importance in best-estimate plus uncertainty analyses

International Nuclear Information System (INIS)

Martin, Robert P.

2009-01-01

This paper describes a general methodology for quantifying the importance of specific phenomenological elements to analysis measures evaluated from non-parametric best-estimate plus uncertainty evaluation methodologies. The principal objective of an importance analysis is to reveal those uncertainty contributors having the greatest influence on key analysis measures. This characterization supports the credibility of the uncertainty analysis, the applicability of the analytical tools, and even the generic evaluation methodology through the validation of the engineering judgments that guided the evaluation methodology development. A demonstration of the importance analysis is provided using data from a sample problem considered in the development of AREVA's Realistic LBLOCA methodology. The results are presented against the original large-break LOCA Phenomena Identification and Ranking Table developed by the Technical Program Group responsible for authoring the Code Scaling, Applicability and Uncertainty methodology. (author)

Uncertainty analysis in Monte Carlo criticality computations

International Nuclear Information System (INIS)

Qi Ao

2011-01-01

Highlights: ► Two types of uncertainty methods for k eff Monte Carlo computations are examined. ► Sampling method has the least restrictions on perturbation but computing resources. ► Analytical method is limited to small perturbation on material properties. ► Practicality relies on efficiency, multiparameter applicability and data availability. - Abstract: Uncertainty analysis is imperative for nuclear criticality risk assessments when using Monte Carlo neutron transport methods to predict the effective neutron multiplication factor (k eff ) for fissionable material systems. For the validation of Monte Carlo codes for criticality computations against benchmark experiments, code accuracy and precision are measured by both the computational bias and uncertainty in the bias. The uncertainty in the bias accounts for known or quantified experimental, computational and model uncertainties. For the application of Monte Carlo codes for criticality analysis of fissionable material systems, an administrative margin of subcriticality must be imposed to provide additional assurance of subcriticality for any unknown or unquantified uncertainties. Because of a substantial impact of the administrative margin of subcriticality on economics and safety of nuclear fuel cycle operations, recently increasing interests in reducing the administrative margin of subcriticality make the uncertainty analysis in criticality safety computations more risk-significant. This paper provides an overview of two most popular k eff uncertainty analysis methods for Monte Carlo criticality computations: (1) sampling-based methods, and (2) analytical methods. Examples are given to demonstrate their usage in the k eff uncertainty analysis due to uncertainties in both neutronic and non-neutronic parameters of fissionable material systems.

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

Uncertainty Quantification for Ice Sheet Science and Sea Level Projections

Science.gov (United States)

Boening, C.; Schlegel, N.; Limonadi, D.; Schodlok, M.; Seroussi, H. L.; Larour, E. Y.; Watkins, M. M.

2017-12-01

In order to better quantify uncertainties in global mean sea level rise projections and in particular upper bounds, we aim at systematically evaluating the contributions from ice sheets and potential for extreme sea level rise due to sudden ice mass loss. Here, we take advantage of established uncertainty quantification tools embedded within the Ice Sheet System Model (ISSM) as well as sensitivities to ice/ocean interactions using melt rates and melt potential derived from MITgcm/ECCO2. With the use of these tools, we conduct Monte-Carlo style sampling experiments on forward simulations of the Antarctic ice sheet, by varying internal parameters and boundary conditions of the system over both extreme and credible worst-case ranges. Uncertainty bounds for climate forcing are informed by CMIP5 ensemble precipitation and ice melt estimates for year 2100, and uncertainty bounds for ocean melt rates are derived from a suite of regional sensitivity experiments using MITgcm. Resulting statistics allow us to assess how regional uncertainty in various parameters affect model estimates of century-scale sea level rise projections. The results inform efforts to a) isolate the processes and inputs that are most responsible for determining ice sheet contribution to sea level; b) redefine uncertainty brackets for century-scale projections; and c) provide a prioritized list of measurements, along with quantitative information on spatial and temporal resolution, required for reducing uncertainty in future sea level rise projections. Results indicate that ice sheet mass loss is dependent on the spatial resolution of key boundary conditions - such as bedrock topography and melt rates at the ice-ocean interface. This work is performed at and supported by the California Institute of Technology's Jet Propulsion Laboratory. Supercomputing time is also supported through a contract with the National Aeronautics and Space Administration's Cryosphere program.

Up-scaling of multi-variable flood loss models from objects to land use units at the meso-scale

Directory of Open Access Journals (Sweden)

H. Kreibich

2016-05-01

Full Text Available Flood risk management increasingly relies on risk analyses, including loss modelling. Most of the flood loss models usually applied in standard practice have in common that complex damaging processes are described by simple approaches like stage-damage functions. Novel multi-variable models significantly improve loss estimation on the micro-scale and may also be advantageous for large-scale applications. However, more input parameters also reveal additional uncertainty, even more in upscaling procedures for meso-scale applications, where the parameters need to be estimated on a regional area-wide basis. To gain more knowledge about challenges associated with the up-scaling of multi-variable flood loss models the following approach is applied: Single- and multi-variable micro-scale flood loss models are up-scaled and applied on the meso-scale, namely on basis of ATKIS land-use units. Application and validation is undertaken in 19 municipalities, which were affected during the 2002 flood by the River Mulde in Saxony, Germany by comparison to official loss data provided by the Saxon Relief Bank (SAB.In the meso-scale case study based model validation, most multi-variable models show smaller errors than the uni-variable stage-damage functions. The results show the suitability of the up-scaling approach, and, in accordance with micro-scale validation studies, that multi-variable models are an improvement in flood loss modelling also on the meso-scale. However, uncertainties remain high, stressing the importance of uncertainty quantification. Thus, the development of probabilistic loss models, like BT-FLEMO used in this study, which inherently provide uncertainty information are the way forward.

Robust Performance of Systems with Structured Uncertainties in State Space

OpenAIRE

Zhou, K.; Khargonekar, P.P.; Stoustrup, Jakob; Niemann, H.H.

1995-01-01

This paper considers robust performance analysis and state feedback design for systems with time-varying parameter uncertainties. The notion of a strongly robust % performance criterion is introduced, and its applications in robust performance analysis and synthesis for nominally linear systems with time-varying uncertainties are discussed and compared with the constant scaled small gain criterion. It is shown that most robust performance analysis and synthesisproblems under this strongly rob...

Tolerance for uncertainty in elderly people

Directory of Open Access Journals (Sweden)

KHRYSTYNA KACHMARYK

2014-09-01

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

Managing Measurement Uncertainty in Building Acoustics

Directory of Open Access Journals (Sweden)

Chiara Scrosati

2015-12-01

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

An inter-battery factor analysis of the comrey personality scales and the 16 personality factor questionnaire

OpenAIRE

Gideon P. de Bruin

2000-01-01

The scores of 700 Afrikaans-speaking university students on the Comrey Personality Scales and the 16 Personality Factor Questionnaire were subjected to an inter-battery factor analysis. This technique uses only the correlations between two sets of variables and reveals only the factors that they have in common. Three of the Big Five personality factors were revealed, namely Extroversion, Neuroticism and Conscientiousness. However, the Conscientiousness factor contained a relatively strong uns...

Low cost high performance uncertainty quantification

KAUST Repository

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

2009-01-01

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

The factor structure of the self-directed learning readiness scale | de ...

African Journals Online (AJOL)

The factor structure of the Self-Directed Learning Readiness Scale (SDLRS) was investigated for Afrikaans and English-speaking first-year university students. Five factors were extracted and rotated to oblique simple structure for both groups. Four of the five factors were satisfactorily replicated. The fifth factor appeared to ...

Adaptively Addressing Uncertainty in Estuarine and Near Coastal Restoration Projects

Energy Technology Data Exchange (ETDEWEB)

Thom, Ronald M.; Williams, Greg D.; Borde, Amy B.; Southard, John A.; Sargeant, Susan L.; Woodruff, Dana L.; Laufle, Jeffrey C.; Glasoe, Stuart

2005-03-01

Restoration projects have an uncertain outcome because of a lack of information about current site conditions, historical disturbance levels, effects of landscape alterations on site development, unpredictable trajectories or patterns of ecosystem structural development, and many other factors. A poor understanding of the factors that control the development and dynamics of a system, such as hydrology, salinity, wave energies, can also lead to an unintended outcome. Finally, lack of experience in restoring certain types of systems (e.g., rare or very fragile habitats) or systems in highly modified situations (e.g., highly urbanized estuaries) makes project outcomes uncertain. Because of these uncertainties, project costs can rise dramatically in an attempt to come closer to project goals. All of the potential sources of error can be addressed to a certain degree through adaptive management. The first step is admitting that these uncertainties can exist, and addressing as many of the uncertainties with planning and directed research prior to implementing the project. The second step is to evaluate uncertainties through hypothesis-driven experiments during project implementation. The third step is to use the monitoring program to evaluate and adjust the project as needed to improve the probability of the project to reach is goal. The fourth and final step is to use the information gained in the project to improve future projects. A framework that includes a clear goal statement, a conceptual model, and an evaluation framework can help in this adaptive restoration process. Projects and programs vary in their application of adaptive management in restoration, and it is very difficult to be highly prescriptive in applying adaptive management to projects that necessarily vary widely in scope, goal, ecosystem characteristics, and uncertainties. Very large ecosystem restoration programs in the Mississippi River delta (Coastal Wetlands Planning, Protection, and Restoration

Uncertainties in radioecological assessment models

International Nuclear Information System (INIS)

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

1983-01-01

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

Uncertainty in predictions of forest carbon dynamics: separating driver error from model error.

Science.gov (United States)

Spadavecchia, L; Williams, M; Law, B E

2011-07-01

compensated for each other. The time scales on which precipitation errors occurred in the simulations were shorter than the temporal scales over which drought developed in the model, so drought events were reasonably simulated. The approach outlined here provides a means to assess the uncertainty and bias introduced by meteorological drivers in regional-scale ecological forecasting.

Uncertainties in modelling the climate impact of irrigation

Science.gov (United States)

de Vrese, Philipp; Hagemann, Stefan

2017-11-01

Irrigation-based agriculture constitutes an essential factor for food security as well as fresh water resources and has a distinct impact on regional and global climate. Many issues related to irrigation's climate impact are addressed in studies that apply a wide range of models. These involve substantial uncertainties related to differences in the model's structure and its parametrizations on the one hand and the need for simplifying assumptions for the representation of irrigation on the other hand. To address these uncertainties, we used the Max Planck Institute for Meteorology's Earth System model into which a simple irrigation scheme was implemented. In order to estimate possible uncertainties with regard to the model's more general structure, we compared the climate impact of irrigation between three simulations that use different schemes for the land-surface-atmosphere coupling. Here, it can be shown that the choice of coupling scheme does not only affect the magnitude of possible impacts but even their direction. For example, when using a scheme that does not explicitly resolve spatial subgrid scale heterogeneity at the surface, irrigation reduces the atmospheric water content, even in heavily irrigated regions. Contrarily, in simulations that use a coupling scheme that resolves heterogeneity at the surface or even within the lowest layers of the atmosphere, irrigation increases the average atmospheric specific humidity. A second experiment targeted possible uncertainties related to the representation of irrigation characteristics. Here, in four simulations the irrigation effectiveness (controlled by the target soil moisture and the non-vegetated fraction of the grid box that receives irrigation) and the timing of delivery were varied. The second experiment shows that uncertainties related to the modelled irrigation characteristics, especially the irrigation effectiveness, are also substantial. In general the impact of irrigation on the state of the land

An approach of sensitivity and uncertainty analyses methods installation in a safety calculation

International Nuclear Information System (INIS)

Pepin, G.; Sallaberry, C.

2003-01-01

Simulation of the migration in deep geological formations leads to solve convection-diffusion equations in porous media, associated with the computation of hydrogeologic flow. Different time-scales (simulation during 1 million years), scales of space, contrasts of properties in the calculation domain, are taken into account. This document deals more particularly with uncertainties on the input data of the model. These uncertainties are taken into account in total analysis with the use of uncertainty and sensitivity analysis. ANDRA (French national agency for the management of radioactive wastes) carries out studies on the treatment of input data uncertainties and their propagation in the models of safety, in order to be able to quantify the influence of input data uncertainties of the models on the various indicators of safety selected. The step taken by ANDRA consists initially of 2 studies undertaken in parallel: - the first consists of an international review of the choices retained by ANDRA foreign counterparts to carry out their uncertainty and sensitivity analysis, - the second relates to a review of the various methods being able to be used in sensitivity and uncertainty analysis in the context of ANDRA's safety calculations. Then, these studies are supplemented by a comparison of the principal methods on a test case which gathers all the specific constraints (physical, numerical and data-processing) of the problem studied by ANDRA

Information measures and uncertainty of particular symbols

Czech Academy of Sciences Publication Activity Database

Mareš, Milan

2011-01-01

Roč. 47, č. 1 (2011), s. 144-163 ISSN 0023-5954 R&D Projects: GA MŠk(CZ) 1M0572; GA ČR GA402/08/0618 Institutional research plan: CEZ:AV0Z10750506 Keywords : Information source * Information measure * Uncertainty modelling Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.454, year: 2011 http://library.utia.cas.cz/separaty/2011/E/mares-information measures and uncertainty of particular symbols.pdf

Evaluation of uncertainties treatment of DNBR calculation for Angra-1 reactor core

International Nuclear Information System (INIS)

Pontedeiro, A.C.; Galetti, M.R.S.

1986-01-01

The results of DNBR sensitivity analysis for NPP Angra 1 are presented in this report. Sensitivity study was carried out using computer code COBRAIIIP and all the sensitivity factors were calculated for the nominal condition as the reference case. These sensitivity factors were used according to the Westinghouse methodology 'Improved Thermal Design Procedure', to calculate a statistical uncertainty factor. In this methodology the best estimate DNBR is penalized by the uncertainty factor and compared with a statistical limit to the minimum DNBR. Westinghouse has been using this statistical uncertainty treatment in the core thermal design to get a better operation flexibility of the plant in order to keep the same design basis established in Angra 1 FSAR methodology. (Author) [pt

Periodic Verification of the Scaling Factor for Radwastes in Korean NPPs - 13294

Energy Technology Data Exchange (ETDEWEB)

Park, Yong Joon; Ahn, Hong Joo; Song, Byoung Chul; Song, Kyuseok [Korea Atomic Energy Research Institute, P.O. Box 105, Yuseong, Daejeon, 305-330 (Korea, Republic of)

2013-07-01

According to the acceptance criteria for a low and intermediate level radioactive waste (LILW) listed in Notice No. 2012-53 of the Nuclear Safety and Security Commission (NSSC), specific concentrations of radionuclides inside a drum has to be identified and quantified. In 5 years of effort, scaling factors were derived through destructive radiochemical analysis, and the dry active waste, spent resin, concentration bottom, spent filter, and sludge drums generated during 2004 ∼ 2008 were evaluated to identify radionuclide inventories. Eventually, only dry active waste among LILWs generated from Korean NPPs were first shipped to a permanent disposal facility on December 2010. For the LILWs generated after 2009, the radionuclides are being radiochemically quantified because the Notice clarifies that the certifications of the scaling factors should be verified biennially. During the operation of NPP, the radionuclides designated in the Notice are formed by neutron activation of primary coolant, reactor structural materials, corrosion products, and fission products released into primary coolant through defects or failures in fuel cladding. Eventually, since the radionuclides released into primary coolant are transported into the numerous auxiliary and support systems connected to primary system, the LILWs can be contaminated, and the radionuclides can have various concentration distributions. Thus, radioactive wastes, such as spent resin and dry active waste generated at various Korean NPP sites, were sampled at each site, and the activities of the regulated radionuclides present in the sample were determined using radiochemical methods. The scaling factors were driven on the basis of the activity ratios between a or β-emitting nuclides and γ-emitting nuclides. The resulting concentrations were directly compared with the established scaling factors' data using statistical methods. In conclusions, the established scaling factors were verified with a reliability

Multi-Scale Validation of a Nanodiamond Drug Delivery System and Multi-Scale Engineering Education

Science.gov (United States)

Schwalbe, Michelle Kristin

2010-01-01

This dissertation has two primary concerns: (i) evaluating the uncertainty and prediction capabilities of a nanodiamond drug delivery model using Bayesian calibration and bias correction, and (ii) determining conceptual difficulties of multi-scale analysis from an engineering education perspective. A Bayesian uncertainty quantification scheme…

Trajectory Reconstruction and Uncertainty Analysis Using Mars Science Laboratory Pre-Flight Scale Model Aeroballistic Testing

Science.gov (United States)

Lugo, Rafael A.; Tolson, Robert H.; Schoenenberger, Mark

2013-01-01

As part of the Mars Science Laboratory (MSL) trajectory reconstruction effort at NASA Langley Research Center, free-flight aeroballistic experiments of instrumented MSL scale models was conducted at Aberdeen Proving Ground in Maryland. The models carried an inertial measurement unit (IMU) and a flush air data system (FADS) similar to the MSL Entry Atmospheric Data System (MEADS) that provided data types similar to those from the MSL entry. Multiple sources of redundant data were available, including tracking radar and on-board magnetometers. These experimental data enabled the testing and validation of the various tools and methodologies that will be used for MSL trajectory reconstruction. The aerodynamic parameters Mach number, angle of attack, and sideslip angle were estimated using minimum variance with a priori to combine the pressure data and pre-flight computational fluid dynamics (CFD) data. Both linear and non-linear pressure model terms were also estimated for each pressure transducer as a measure of the errors introduced by CFD and transducer calibration. Parameter uncertainties were estimated using a "consider parameters" approach.

The Uncertainty of Local Background Magnetic Field Orientation in Anisotropic Plasma Turbulence

Energy Technology Data Exchange (ETDEWEB)

Gerick, F.; Saur, J.; Papen, M. von, E-mail: felix.gerick@uni-koeln.de [Institute of Geophysics and Meteorology, University of Cologne, Cologne (Germany)

2017-07-01

In order to resolve and characterize anisotropy in turbulent plasma flows, a proper estimation of the background magnetic field is crucially important. Various approaches to calculating the background magnetic field, ranging from local to globally averaged fields, are commonly used in the analysis of turbulent data. We investigate how the uncertainty in the orientation of a scale-dependent background magnetic field influences the ability to resolve anisotropy. Therefore, we introduce a quantitative measure, the angle uncertainty, that characterizes the uncertainty of the orientation of the background magnetic field that turbulent structures are exposed to. The angle uncertainty can be used as a condition to estimate the ability to resolve anisotropy with certain accuracy. We apply our description to resolve the spectral anisotropy in fast solar wind data. We show that, if the angle uncertainty grows too large, the power of the turbulent fluctuations is attributed to false local magnetic field angles, which may lead to an incorrect estimation of the spectral indices. In our results, an apparent robustness of the spectral anisotropy to false local magnetic field angles is observed, which can be explained by a stronger increase of power for lower frequencies when the scale of the local magnetic field is increased. The frequency-dependent angle uncertainty is a measure that can be applied to any turbulent system.

The Uncertainty of Local Background Magnetic Field Orientation in Anisotropic Plasma Turbulence

International Nuclear Information System (INIS)

Gerick, F.; Saur, J.; Papen, M. von

2017-01-01

In order to resolve and characterize anisotropy in turbulent plasma flows, a proper estimation of the background magnetic field is crucially important. Various approaches to calculating the background magnetic field, ranging from local to globally averaged fields, are commonly used in the analysis of turbulent data. We investigate how the uncertainty in the orientation of a scale-dependent background magnetic field influences the ability to resolve anisotropy. Therefore, we introduce a quantitative measure, the angle uncertainty, that characterizes the uncertainty of the orientation of the background magnetic field that turbulent structures are exposed to. The angle uncertainty can be used as a condition to estimate the ability to resolve anisotropy with certain accuracy. We apply our description to resolve the spectral anisotropy in fast solar wind data. We show that, if the angle uncertainty grows too large, the power of the turbulent fluctuations is attributed to false local magnetic field angles, which may lead to an incorrect estimation of the spectral indices. In our results, an apparent robustness of the spectral anisotropy to false local magnetic field angles is observed, which can be explained by a stronger increase of power for lower frequencies when the scale of the local magnetic field is increased. The frequency-dependent angle uncertainty is a measure that can be applied to any turbulent system.

Uncertainty analysis for hot channel

International Nuclear Information System (INIS)

Panka, I.; Kereszturi, A.

2006-01-01

The fulfillment of the safety analysis acceptance criteria is usually evaluated by separate hot channel calculations using the results of neutronic or/and thermo hydraulic system calculations. In case of an ATWS event (inadvertent withdrawal of control assembly), according to the analysis, a number of fuel rods are experiencing DNB for a longer time and must be regarded as failed. Their number must be determined for a further evaluation of the radiological consequences. In the deterministic approach, the global power history must be multiplied by different hot channel factors (kx) taking into account the radial power peaking factors for each fuel pin. If DNB occurs it is necessary to perform a few number of hot channel calculations to determine the limiting kx leading just to DNB and fuel failure (the conservative DNBR limit is 1.33). Knowing the pin power distribution from the core design calculation, the number of failed fuel pins can be calculated. The above procedure can be performed by conservative assumptions (e.g. conservative input parameters in the hot channel calculations), as well. In case of hot channel uncertainty analysis, the relevant input parameters (k x, mass flow, inlet temperature of the coolant, pin average burnup, initial gap size, selection of power history influencing the gap conductance value) of hot channel calculations and the DNBR limit are varied considering the respective uncertainties. An uncertainty analysis methodology was elaborated combining the response surface method with the one sided tolerance limit method of Wilks. The results of deterministic and uncertainty hot channel calculations are compared regarding to the number of failed fuel rods, max. temperature of the clad surface and max. temperature of the fuel (Authors)

Understanding uncertainty

CERN Document Server

Lindley, Dennis V

2013-01-01

Praise for the First Edition ""...a reference for everyone who is interested in knowing and handling uncertainty.""-Journal of Applied Statistics The critically acclaimed First Edition of Understanding Uncertainty provided a study of uncertainty addressed to scholars in all fields, showing that uncertainty could be measured by probability, and that probability obeyed three basic rules that enabled uncertainty to be handled sensibly in everyday life. These ideas were extended to embrace the scientific method and to show how decisions, containing an uncertain element, could be rationally made.

The neurobiology of uncertainty: implications for statistical learning.

Science.gov (United States)

Hasson, Uri

2017-01-05

The capacity for assessing the degree of uncertainty in the environment relies on estimating statistics of temporally unfolding inputs. This, in turn, allows calibration of predictive and bottom-up processing, and signalling changes in temporally unfolding environmental features. In the last decade, several studies have examined how the brain codes for and responds to input uncertainty. Initial neurobiological experiments implicated frontoparietal and hippocampal systems, based largely on paradigms that manipulated distributional features of visual stimuli. However, later work in the auditory domain pointed to different systems, whose activation profiles have interesting implications for computational and neurobiological models of statistical learning (SL). This review begins by briefly recapping the historical development of ideas pertaining to the sensitivity to uncertainty in temporally unfolding inputs. It then discusses several issues at the interface of studies of uncertainty and SL. Following, it presents several current treatments of the neurobiology of uncertainty and reviews recent findings that point to principles that serve as important constraints on future neurobiological theories of uncertainty, and relatedly, SL. This review suggests it may be useful to establish closer links between neurobiological research on uncertainty and SL, considering particularly mechanisms sensitive to local and global structure in inputs, the degree of input uncertainty, the complexity of the system generating the input, learning mechanisms that operate on different temporal scales and the use of learnt information for online prediction.This article is part of the themed issue 'New frontiers for statistical learning in the cognitive sciences'. © 2016 The Author(s).

Multi-Scale Factor Analysis of High-Dimensional Brain Signals

KAUST Repository

Ting, Chee-Ming

2017-05-18

In this paper, we develop an approach to modeling high-dimensional networks with a large number of nodes arranged in a hierarchical and modular structure. We propose a novel multi-scale factor analysis (MSFA) model which partitions the massive spatio-temporal data defined over the complex networks into a finite set of regional clusters. To achieve further dimension reduction, we represent the signals in each cluster by a small number of latent factors. The correlation matrix for all nodes in the network are approximated by lower-dimensional sub-structures derived from the cluster-specific factors. To estimate regional connectivity between numerous nodes (within each cluster), we apply principal components analysis (PCA) to produce factors which are derived as the optimal reconstruction of the observed signals under the squared loss. Then, we estimate global connectivity (between clusters or sub-networks) based on the factors across regions using the RV-coefficient as the cross-dependence measure. This gives a reliable and computationally efficient multi-scale analysis of both regional and global dependencies of the large networks. The proposed novel approach is applied to estimate brain connectivity networks using functional magnetic resonance imaging (fMRI) data. Results on resting-state fMRI reveal interesting modular and hierarchical organization of human brain networks during rest.

Dealing with uncertainties in environmental burden of disease assessment

Directory of Open Access Journals (Sweden)

van der Sluijs Jeroen P

2009-04-01

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

The Effects of Uncertainty in Speed-Flow Curve Parameters on a Large-Scale Model

DEFF Research Database (Denmark)

Manzo, Stefano; Nielsen, Otto Anker; Prato, Carlo Giacomo

2014-01-01

-delay functions express travel time as a function of traffic flows and the theoretical capacity of the modeled facility. The U.S. Bureau of Public Roads (BPR) formula is one of the most extensively applied volume delay functions in practice. This study investigated uncertainty in the BPR parameters. Initially......-stage Danish national transport model. The results clearly highlight the importance to modeling purposes of taking into account BPR formula parameter uncertainty, expressed as a distribution of values rather than assumed point values. Indeed, the model output demonstrates a noticeable sensitivity to parameter...

A Survey of Clinical Uncertainty from the Paediatric Basic Specialist Trainee Perspective

LENUS (Irish Health Repository)

O’Neill, MB

2017-06-01

This study was undertaken to evaluate uncertainty from the Basic Specialist Trainee perspective. The survey of trainees explored 1) factors in decision making, 2) the personal impact of uncertainty, 3) the responses to both clinical errors and challenges to their decision making and 4) the potential strategies to address uncertainty. Forty-one (93%) of trainees surveyed responded. Important factors in decision making were clinical knowledge and senior colleague’s opinion. Sixty percent experienced significant anxiety post call as a consequence of their uncertainty. When errors are made by colleagues, the trainee’s response is acceptance (52.5%), and sympathy (32%).Trainees are strongly influenced by the opinions of senior colleagues often changing their opinions having made confident decisions. Solutions to address uncertainty include enhanced knowledge translation, and to a lesser extent, enhanced personal awareness and resilience awareness. To enhance the training experience for BST and lessen the uncertainty experienced these strategies need to be enacted within the training milieu.

Uncertainties associated with inertial-fusion ignition

International Nuclear Information System (INIS)

McCall, G.H.

1981-01-01

An estimate is made of a worst case driving energy which is derived from analytic and computer calculations. It will be shown that the uncertainty can be reduced by a factor of 10 to 100 if certain physical effects are understood. That is not to say that the energy requirement can necessarily be reduced below that of the worst case, but it is possible to reduce the uncertainty associated with ignition energy. With laser costs in the $0.5 to 1 billion per MJ range, it can be seen that such an exercise is worthwhile

Validity and factor structure of the bodybuilding dependence scale

OpenAIRE

Smith, D; Hale, B

2004-01-01

Objectives: To investigate the factor structure, validity, and reliability of the bodybuilding dependence scale and to investigate differences in bodybuilding dependence between men and women and competitive and non-competitive bodybuilders.

Determination of uncertainties in energy and exergy analysis of a power plant

International Nuclear Information System (INIS)

Ege, Ahmet; Şahin, Hacı Mehmet

2014-01-01

Highlights: • Energy and exergy efficiency uncertainties in a large thermal power plant examined. • Sensitivity analysis shows importance of basic measurements on efficiency analysis. • A quick and practical approach is provided for determining efficiency uncertainties. • Extreme case analysis characterizes maximum possible boundaries of uncertainties. • Uncertainty determination in a plant is a dynamic process with real data. - Abstract: In this study, energy and exergy efficiency uncertainties of a large scale lignite fired power plant cycle and various measurement parameter sensitivities were investigated for five different design power outputs (100%, 85%, 80%, 60% and 40%) and with real data of the plant. For that purpose a black box method was employed considering coal flow with Lower Heating Value (LHV) as a single input and electricity produced as a single output of the plant. The uncertainty of energy and exergy efficiency of the plant was evaluated with this method by applying sensitivity analysis depending on the effect of measurement parameters such as LHV, coal mass flow rate, cell generator output voltage/current. In addition, an extreme case analysis was investigated to determine the maximum range of the uncertainties. Results of the black box method showed that uncertainties varied between 1.82–1.98% for energy efficiency and 1.32–1.43% for exergy efficiency of the plant at an operating power level of 40–100% of full power. It was concluded that LHV determination was the most important uncertainty source of energy and exergy efficiency of the plant. The uncertainties of the extreme case analysis were determined between 2.30% and 2.36% for energy efficiency while 1.66% and 1.70% for exergy efficiency for 40–100% power output respectively. Proposed method was shown to be an approach for understanding major uncertainties as well as effects of some measurement parameters in a large scale thermal power plant

Low cost high performance uncertainty quantification

KAUST Repository

Bekas, C.

2009-01-01

Uncertainty quantification in risk analysis has become a key application. In this context, computing the diagonal of inverse covariance matrices is of paramount importance. Standard techniques, that employ matrix factorizations, incur a cubic cost which quickly becomes intractable with the current explosion of data sizes. In this work we reduce this complexity to quadratic with the synergy of two algorithms that gracefully complement each other and lead to a radically different approach. First, we turned to stochastic estimation of the diagonal. This allowed us to cast the problem as a linear system with a relatively small number of multiple right hand sides. Second, for this linear system we developed a novel, mixed precision, iterative refinement scheme, which uses iterative solvers instead of matrix factorizations. We demonstrate that the new framework not only achieves the much needed quadratic cost but in addition offers excellent opportunities for scaling at massively parallel environments. We based our implementation on BLAS 3 kernels that ensure very high processor performance. We achieved a peak performance of 730 TFlops on 72 BG/P racks, with a sustained performance 73% of theoretical peak. We stress that the techniques presented in this work are quite general and applicable to several other important applications. Copyright © 2009 ACM.

Radionuclide analysis and scaling factors verification for LLRW of Taipower Reactor

International Nuclear Information System (INIS)

King, J.-Y.; Liu, K.-T.; Chen, S.-C.; Chang, T.-M.; Pung, T.-C.; Men, L.-C.; Wang, S.-J.

2004-01-01

The Atomic Energy Council of the Republic of China (CAEC) final disposal policy for Low Level Radwaste (LLRW) will be carried on in 1996. Institute of Nuclear Energy Research has the contract to develop the Radionuclide analysis method and to establish the scaling factors for LLRW of Taipower reactors. The radionuclides analyzed including: Co-60, Cs-137, Ce-144, γ-nuclides; H-3, C-14, Fe-55, Ni-59, Ni-63, Sr-90, Nb-94, Tc-99, I-129, Pu-238, Pu-239/240, Pu-241, Am-241, Cm-242, Cm-244 α, β and low energy γ nuclides. 120 samples taken from 21 waste streams were analyzed and the database was collected within 2 years. The scaling factors for different kind of waste streams were computed with weighted log-mean average method. In 1993, the scaling factors for each waste stream has been verified through actual station samples. (author)

Uncertainty in prostate cancer. Ethnic and family patterns.

Science.gov (United States)

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

1998-01-01

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

Statistical methodology for discrete fracture model - including fracture size, orientation uncertainty together with intensity uncertainty and variability

International Nuclear Information System (INIS)

Darcel, C.; Davy, P.; Le Goc, R.; Dreuzy, J.R. de; Bour, O.

2009-11-01

the other, addresses the issue of the nature of the transition. We develop a new 'mechanistic' model that could help in modeling why and where this transition can occur. The transition between both regimes would occur for a fracture length of 1-10 m and even at a smaller scale for the few outcrops that follow the self-similar density model. A consequence for the disposal issue is that the model that is likely to apply in the 'blind' scale window between 10-100 m is the self-similar model as it is defined for large-scale lineaments. The self-similar model, as it is measured for some outcrops and most lineament maps, is definitely worth being investigated as a reference for scales above 1-10 m. In the rest of the report, we develop a methodology for incorporating uncertainty and variability into the DFN modeling. Fracturing properties arise from complex processes which produce an intrinsic variability; characterizing this variability as an admissible variation of model parameter or as the division of the site into subdomains with distinct DFN models is a critical point of the modeling effort. Moreover, the DFN model encompasses a part of uncertainty, due to data inherent uncertainties and sampling limits. Both effects must be quantified and incorporated into the DFN site model definition process. In that context, all available borehole data including recording of fracture intercept positions, pole orientation and relative uncertainties are used as the basis for the methodological development and further site model assessment. An elementary dataset contains a set of discrete fracture intercepts from which a parent orientation/density distribution can be computed. The elementary bricks of the site, from which these initial parent density distributions are computed, rely on the former Single Hole Interpretation division of the boreholes into sections whose local boundaries are expected to reflect - locally - geology and fracturing properties main characteristics. From that